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Res
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016
-2019
LEARNING RESOURCE CENTRE
BENNETT UNIVERSITY
GREATER NOIDA
Edited and Compiled by
Dr. Sanjay Kataria
Editorial Assistance Mr. Jamil Ahmed
Dr. Shiv Singh
Ms. Tulika Dey
Mr. Tarun Kumar Singh
I
IIIIIIII
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Table of Contents
Foreword III
Message 1V
Preface V
Summary of BU Research Publications VI-X
Growth of Publications VI
School-wise Publications VI
Department-wise Publications VII
Type of Publications VII
Publications Indexed VIII
Top Cited Papers IX
Top Impact Factor Papers X
List of Abbreviations XI
School of Engineering & Applied Sciences 1-239
Department of Biotechnology 1-12
Department of Civil Engineering 13-19
Department of Computer Science Engineering 20-109
Department of Electronics & Communication Engineering 110-166
Department of Mathematics 167-169
Department of Mechanical and Aerospace Engineering 170-225
Department of Physics 226-239
School of Law 240-252
Centre for Innovation & Entrepreneurship 253-256
School of Management 257-274
Times School of Media 275-279
Learning Resource Centre 280-286
Author Index 287-290
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FOREWORD
I am happy that the Learning Resource Centre (Library) has compiled a Research Compendium for
inspiring, motivating and supporting the research fraternity of the University. The Compendium
will help at promoting the research work of the University and inspiring the young professionals
with a stimulus to continue in this direction.
The Compendium is a collection of 373 publications including Journals Research Papers,
Conference Papers, Book Chapters, Books etc., published with BU affiliation during 2016 to 2019.
It’s a matter of great satisfaction that in spite of being a young University with limited resources, a
good number of papers has been published by the Faculty Members, Research Scholars and Staff.
I congratulate Dr. Sanjay Kataria and his team for this excellent work. I believe the BU Research
Compendium will be an annual feature.
Wishing the entire BU family the very best for all future endeavors!
Prof. Raghunath K. Shevgaonkar
Vice-Chancellor
III
Prof. Raghunath K. Shevgaonkar
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MESSAGE
I am delighted to see that the Learning Resource Centre has taken an earnest effort to facilitate BU
research community with a Compendium compiling research published by faculty members, staff and
research scholars. Being only 4-years old, the University academic fraternity has shown strong research
acumen by publishing 373 Papers, of which 287 are Scopus-indexed and 126 SCIE-indexed.
The Compendium will provide a ready reference to research work published by researchers across
schools and disciplines, thereby opening up avenues to develop inter-disciplinary linkages through
research groups and centres, thus not only enriching and accelerating the pace of research at Bennett
University but also broadening the scope of putting up strong joint research proposals for fetching
national/international funding. In addition, the Compendium would also be of great help to
undergraduate students in deciding and pursuing their project problems, aligned to research strengths of
the faculty.
I would like to caution the readers that the differential proportion of school-wise and Department-wise
distribution of publications presented in the compendium shouldn’t be taken as the yardstick of
productivity in producing higher numbers of publications because the School of Engineering & Applied
Sciences enrolled PhD programme in 2016 with substantial growth in numbers of research-driven
faculty and strength of scholars in subsequent years compared to other schools which launched PhD
programmes much later.
I complement Dr. Sanjay Kataria and his team in putting up this effort and wish that this activity be con-tinued at regular intervals.
Prof. Rajinder Singh Chauhan
Dean (Research & Consultancy)
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Prof. Rajinder Singh Chauhan
VVVV
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PREFACE
In the pursuit of continuing the rich legacy of the Times of India Group, Bennett University lays a
strong emphasis on not just teaching but creating new knowledge and securing a strong foothold in
the world of education and research. As benchmark to assess proficiency, intellectual contribution in
the knowledge domain serves to be a very significant tool. Research work not only helps in building
goodwill and prestige, but also finding collaborators and grants. Students, being the most important
stakeholders, research triggers their analytical and problem-solving skills, activates critical and crea-
tive thinking in them and motivates them to contribute further.
The future is constantly evolving, and adaptation calls for innovative and skilled generation that places
young professionals at the forefront and Bennett University has already set the ground for the same
when one of its proposals was recently recommended by the Department of Biotechnology from the
Ministry of Science & Technology, Government of India for funding among 70 proposals for
developing “safe and effective biomedical solutions” in the war against COVID-19 in May 2020.
As an integral part of the University, the Learning Resource Centre (Library) is playing a vital role not
only by curating the intellectual assets, but also by long-term preservation of the same in the form of a
Digital Research Repository (DRS) and Research Compendium to motivate the fresh talents. The
Compendium will serve as a ready reference of research work by the University at a glance.
In such a short span of time (less than 4 years), 373 research publications including Journal papers,
conference papers, book chapters, and other scholarly works have been published by the faculty
members, research scholars and staff. Out of the 373 research publications, 287 publications are
indexed in Scopus and 126 are indexed in Web of Science. The indexed publications received a total
of 845 citations.
Dr. Vinayak Ranjan, (HOD, Mechanical Engineering) with 31 papers is the most prolific author so far
followed by Dr. Rama S. Komaragiri (Dean of Academic Affairs & Head Electronics and
Communication Engineering Department) with 24 papers, Dr. Manjeet Kumar (Faculty at Department
of Electronics) with 22 papers and Dr. Shivani Goel (Faculty from the Department of Computer
Science) with 19 papers, respectively.
Dr. Vinit Jakhetiya’s paper from the Department of Computer Science Engineering, “A prediction
backed model for quality assessment of screen content and 3-D synthesized images” published on
2017 in IEEE Transactions on Industrial Informatics received the highest impact factor of 7.377.
The Compendium contains a detailed information of publications including research trends in BU,
Growth of research, contribution of research school/department-wise, prolific authors in term of high
citation, number of publications and impact factor, abstracts, etc.
Contribution of publication is high in SEAS & SOM as they were started with the inception of the
University along with the Phd programs in 2016.
Looking forward for your suggestions and feedback for further improvement of the Compendium.
Dr. Sanjay Kataria
Editor
VIVIVIVI
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*Note: Contribution of publication is high in SEAS & SOM as they were started with the inception of the University along
with the Phd programs in 2016.
VI
Summary of BU Research Publications
VIIVIIVIIVII
VII
VII
VIIIVIIIVIIIVIII
VIII
Publications Indexed
School Document Type No. of Publications Scopus Indexed SCIE Indexed
SEAS
Book & Conference Pro-ceedings
3 2
Book Chapters 13 6
Conference Papers 99 85
Journal Papers 190 165 119
Papers in arXiv Repository 2
SOL
Book Chapters 4
Book Review 1
Journal Papers 12 2 1
SOM
Book & Conference Pro-ceedings
1
Book Chapters 4 1
Conference Papers 2
Journal Papers 23 16 6
TSOM
Book Chapters 1 1
Conference Papers 3
Journal Papers 4 1
LRC
Book & Conference Pro-ceedings
1 1
Book Chapters 1
Conference Papers 7 6
Journal Papers 2 1
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*As per Scopous database 03-05-2020 IX
Top Cited Papers
S.N. BU Faculty Department Title of Article Name of Journal Year by Cited
1 Vinit Jakhetiya CSE Model-Based Referenceless Quality Metric of 3D
Synthesized Images Using Local Image Description IEEE Transactions Image
Processing 2018 51
2 Samayveer Singh CSE Energy efficient heterogeneous DEEC protocol for
enhancing lifetime in WSNs Engineering Science and
Technology, an International
Journal
2017 39
3 Milind Shrikant
Padalkar Management Six decades of project management research: Thematic
trends and future opportunities International Journal of Project
Management 2016 35
4 Bishnu P Pal Physics Role of Resonance Modes on Terahertz Metamaterials
based Thin Film Sensors Scientific Reports 2017 31
5 Visalakshi
Talakokula Civil
Engineering Monitoring early hydration of reinforced concrete structures
using structural parameters identified by piezo sensors via
electromechanical impedance technique
Mechanical Systems and
Signal Processing 2018 30
6 Pratik Narang CSE Mix design factors and strength prediction of
metakaolin-based geopolymer Ceramics International 2017 29
7 Pushpendra
Singh ECE A novel Signal Modeling Approach for Classification of
Seizure and Seizure-free EEG Signals IEEE Transactions on Neural
Systems & Rehabilitation
Engineering
2018 26
8 Manjeet Kumar ECE Design of minimum multiplier fractional order
differentiator based on lattice wave digital filter ISA Transactions 2017 22
9 Pushpendra
Singh ECE Classification of focal and nonfocal EEG signals using
features derived from Fourier-based rhythms Journal of Mechanics in
Medicine and Biology 2017 21
10 Vinit Jakhetiya CSE A prediction backed model for quality assessment of screen
content and 3-D synthesized images IEEE Transactions on
Industrial Informatics 2017 20
11 Sudhir Chandra ECE Synthesis of WO3 nanorods by thermal oxidation technique
for NO2 gas sensing application Materials Science in
Semiconductor Processing 2018 19
12 Saurabh Jyoti
Sarma Biotechnolo-
gy Aerobic granulation for future wastewater treatment
technology: challenges ahead Environmental Science-Water
Research & Technology 2017 18
13 Rama S
Komaragiri,
Ashish Kumar,
Manjeet Kumar
ECE From Pacemaker to Wearable: Techniques for ECG
Detection Systems Journal of Medical Systems 2018 17
14 Manjeet Kumar,
Ashish Kumar,
Rama S
Komaragiri
ECE Design of wavelet transform based electrocardiogram
monitoring system ISA Transactions 2018 16
15 Shivani Goel CSE Plants disease identification and classification through leaf
images: A survey Archives of Computational
Methods in Engineering 2018 15
16 Manjeet Kumar ECE Adaptive infinite impulse response system identification
using modified-interior search algorithm with Levy flight ISA Transactions 2017 15
17 Shivani Goel CSE Semi-automatic leaf disease detection and classification
system for soybean culture IET Image Processing 2018 14
18 Samayveer Singh CSE Energy efficient multilevel network model for
heterogeneous WSNs Engineering Science and
Technology, an International
Journal
2017 14
19 Rama S Komara-
giri, Ashish Ku-
mar, Manjeet
Kumar
ECE Heart rate monitoring and therapeutic devices: A wavelet
transform based approach for the modeling and classifica-
tion of congestive heart failure
ISA Transactions 2018 14
20 Kanad Kishore
Biswas CSE A recursive PSO scheme for gene selection in microarray
data Applied Soft Computing 2018 12
21 Joy Pal Civil Engi-
neering Damage-induced acoustic emission source identification in
an advanced sandwich composite structure Composite Structures 2018 10
22 Arjun Kumar ECE An offset CPW-fed triple-band circularly polarized printed
antenna for multiband wireless applications Int. J. Electron.
Commun. (AEÜ) 2018 10
23 Bishnu P Pal Physics Design of chip scale silicon rib slot waveguide for sub-ppm
detection of N2O gas at mid-IR band Sensors and Actuators B:
Chemical 2018 10
24 Nakul
Parameswar Management Purpose of international joint venture and interaction post
termination Journal for Global Business
Advancement 2018 10
XXXX
X Top Impact Factor Papers
S.N Name of Faculty Department Title of Article Name of Journal IF Year
1 Vinit Jakhetiya CSE A prediction backed model for quality assessment of screen content and 3-D synthesized images
IEEE Transactions on Industrial Informatics 7.377 2017
2 Shivani Goel CSE Plants disease identification and classification through leaf images: A survey
Archives of Computational Methods in Engineering 7.242 2018
3 Saurabh Jyoti Sarma Biotechnology Carbon, Nitrogen and Phosphorus Removal Mechanisms of Aerobic Granules
Critical Reviews in Biotechnology 7.054 2018
4 Vinit Jakhetiya CSE Model-Based Referenceless Quality Metric of 3D Synthesized Images Using Local Image Description
IEEE Transactions Image Processing 6.790 2018
5 Bishnu P Pal Physics Design of chip scale silicon rib slot waveguide for sub-ppm detection of N2O gas at mid-IR band
Sensors and Actuators B: Chemical 6.393 2018
6 Shivani Goel CSE Local Graph Based Correlation Clustering Knowledge-Based Systems
5.101 2017
7 Visalakshi Talakokula Civil Engineering
Monitoring early hydration of reinforced concrete structures using structural parameters identified by piezo sensors via electromechanical impedance technique
Mechanical Systems and Signal Processing
5.005 2018
8 Kanad Kishore Biswas CSE A recursive PSO scheme for gene selection in microarray data
Applied Soft Computing 4.873 2018
9 Joy Pal Civil Engineering Damage-induced acoustic emission source identification in an advanced sandwich composite structure
Composite Structures 4.829 2018
10 Vinayak Ranjan Mech Engg. Free vibration analysis of thin functionally graded rectangular plates using the dynamic stiffness method
Composite Structures 4.829 2018
11 Milind Shrikant Padal-kar Management
Six decades of project management research: Thematic trends and future opportunities
International Journal of Project Management 4.694 2016
12 Deepali Atheaya Mech Engg.
Energy and exergy analysis of solar driven recuperated organic Rankine cycle using glazed reverse absorber conventional compound parabolic concentrator (GRACCPC) system
Solar Energy
4.674 2017
13 Shivani Goel CSE
SP-J48: a novel optimization and machine-learning-based approach for solving complex problems: special application in software engineering for detecting code smells
Neural Computing and Applications
4.664 2019
14 Gaurav Shukla Physics Bullen's Parameter as a Seismic Observable for Spin Crossovers in the Lower Mantle
Geophysical Research Letters 4.578 2017
15 Alok Shukla Physics From Half-Metal to Semiconductor: Electron-Correlation Effects in Zigzag SiC Nanoribbons From First Principles
Physical Review Applied 4.532 2017
16 Ashish Kumar ECE Design of high performance QRS complex detector for wearable healthcare devices using biorthogonal spline wavelet transform
ISA Transactions 4.343 2018
17 Manjeet Kumar, Ashish Kumar, Rama S Komaragiri
ECE Design of wavelet transform based electrocardiogram monitoring system
ISA Transactions 4.343 2018
18 Rama S Komaragiri, Ashish Kumar, Manjeet Kumar
ECE Heart rate monitoring and therapeutic devices: A wavelet transform based approach for the modeling and classification of congestive heart failure
ISA Transactions 4.343 2018
19 Manjeet Kumar ECE Adaptive infinite impulse response system identification using modified-interior search algorithm with Levy flight
ISA Transactions 4.343 2017
20 Manjeet Kumar ECE Design of minimum multiplier fractional order differentiator based on lattice wave digital filter
ISA Transactions 4.343 2017
21 Alok Shukla Physics Tunable Optoelectronic Properties of Triply Bonded Carbon Molecules with Linear and Graphyne Substructures
J. Phys. Chem. C 4.309 2017
22 Saurabh Jyoti Sarma Biotechnology Aerobic granulation for future wastewater treatment technology: challenges ahead
Environmental Science-Water Research & Technology 4.195 2017
23 Amit Singhal ECE 3D local ternary co-occurrence patterns for natural, texture, face and bio medical image retrieval
Neurocomputing 4.072 2018
24 Vinit Jakhetiya CSE Just Noticeable Difference for Natural Images using RMS Contrast and Feed-back Mechanism
Nuerocomputing 4.072 2018
25 Rajinder Singh Chauhan Biotechnology
A novel miRNA analysis framework to analyze differential biological networks
Scientific Reports 4.011 2017
26 Alok Shukla Physics Origin of multiple band gap values in single width nanoribbons
Scientific Reports 4.011 2016
27 Bishnu P Pal Physics Role of Resonance Modes on Terahertz Metamaterials based Thin Film Sensors
Scientific Reports 4.011 2017
X
XIXIXIXI
XI
List of Abbreviations
Short Form Full Form
BT Biotechnology
BU Bennett University
CIE Center of Innovation & Entrepreneurship
Civil Civil Engineering
CSE Computer Science and Engineering
DRS@BU Digital Repository Service @Bennett University
ECE Electronics & Communication Engineering
IF Impact Factor
JCR Journal Citation Reports
LRC Learning Resources Centre
Maths Mathematics
ME Mechanical Engineering
MGMT Management
Phy Physics
SEAS School of Engineering & Applied Science
SOL School of Law
SOM School of Management
TSOM Times School of Media
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Department of Biotechnology
Dr. Rajinder Singh Chauhan, Professor & HOD, Department of
Biotechnology
Chauhan, Rajinder Singh (2017). A novel miRNA analysis framework to
analyze differential biological networks. Scientific Reports, 8, 2584.
Abstract: For understanding complex biological systems, a systems biology
approach, involving both the top down and bottom-up analyses, is often
required. Numerous system components and their connections are best
visualization as networks, which are primarily represented as graphs, with
several nodes connected at multiple edges. Inefficient network visualization is a
common problem related to transcriptomic and genomic datasets. In this article,
we demonstrate a miRNA analysis framework with the help of Jatropha curcas
healthy and disease transcriptome datasets, functioning as a pipeline derived
from the graph theory universe, and discuss how the network theory, along with
gene ontology (GO) analysis, can be used to infer biological properties and other
important features of a network. Network profiling, combined with GO,
correlation, and co-expression analyses, can aid in efficiently understanding the
biological significance of pathways, networks, as well as a studied system. The
proposed framework may help experimental and computational biologists to
analyse their own data and infer meaningful biological information.
Keyword: Novel miRNA analysis framework, Biological networks, miRNA,
Correlation Coefficient
Chauhan, Rajinder Singh (2017). Endocellulase Production by Cotylidia
pannosa and its Application in Saccharification of Wheat Bran to Bioethanol.
Bioenergy Research, 219-227.
Abstract: For efficient bioconversion of lignocellulosic materials to bioethanol,
the study screened 19 white-rot fungal strains for their endocellulolytic activity
and saccharification potential. Preliminary qualitative and quantitative screening
revealed Cotylidia pannosa to be the most efficient endocellulase producing
fungal strain when compared to the standard strain of Trichoderma reesei MTCC
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164. Ensuing initial screening, the production of endocellulase was further
optimized using submerged fermentation to recognize process parameters such as
temperature, time, agitation pH, and supplementation of salts in media required
for achieving maximum production of endocellulase. The strain C. pannosa
produced the maximum amount of endocellulase (8.48U/mL) under submerged
fermentation with wheat bran(2%) supplemented yeast extract peptone dextrose
(YEPD) medium after an incubation time of 56 h at 30 °C and pH 5.0 at an
agitation rate of 120 rpm with a saccharification value of 50.5%. The
fermentation of wheat bran hydrolysate with Saccharomyces cerevisiae
MTCC174 produced 4.12g/L of bioethanol after 56h of incubation at 30°C.
There results obtained from the present investigation establish the potential of
white-rot fungus C. pannosa for hydrolysis and saccharification of wheat bran to
yield fermentable sugars for their subsequent conversion to bioethanol,
suggesting its application in efficient bioprocessing of lignocellulosic wastes.
Keyword: Cotylidiapannosa, Endocellulase, Saccharification, Bioethanol
Chauhan, Rajinder Singh (2018). Comparative transcriptomics reveals a
reduction in carbon capture and flux between source and sink in cytokinin-
treated inflorescences of Jatropha curcas L. 3 Biotech, 8(64), 2-17.
Abstract: The low seed yield of Jatropha curcas has been a stumbling block in
realizing its full potential as an ideal bioenergy crop. Low female to male
flower ratio is considered as a major limiting factor responsible for low seed
yield in Jatropha. An exogenous cytokinin application was performed on floral
meristems to increase the seed yield. This resulted in an increase of total
flowers count with a higher female to male flower ratio. However, the seed
biomass did not increase in the same proportion. The possible reason for this
was hypothesized to be the lack of increased photosynthesis efficiency at source
tissues which could fulfil the increased demand of photosynthates and primary
metabolites in maturing seeds. After cytokinin application, possible molecular
mechanisms underlying carbon capture and flux affected between the source
and sink in developing flowers, fruits and seeds were investigated. Comparative
transcriptome analysis was performed on inflorescence meristems (treated with
cytokinin) and control (untreated inflorescence meristems) at time intervals of
15 and 30 days, respectively. KEGG-based functional annotation identified
various metabolic pathways associated with carbon capture and flux. Pathways
such as photosynthesis, carbon fixation, carbohydrate metabolism and nitrogen
metabolism were upregulated after 15 days of cytokinin treatment; however,
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those were downregulated after 30 days. Five genes FBP, SBP, GS, GDH and
AGPase showed significant increase in transcript abundance after 15 days of
treatment but showed a significant decrease after 30 days. These genes, after
functional validation, can be suitable targets in designing a suitable genetic
intervention strategy to increase overall seed yield in Jatropha.
Keyword: Jatropha curcas, Transcriptome, Carbon flux, Yield, Starch
Chauhan, Rajinder Singh (2018). Comparative transcriptomics uncovers
differences in photoautotrophic versus photoheterotrophic modes of nutrition
in relation to secondary metabolites biosynthesis in Swertia chirayita.
Molecular Biology Reports, 77-98.
Abstract: Swertia chirayita is a high-value medicinal herb exhibiting
antidiabetic, hepatoprotective, anticancer, antiediematogenic and antipyretic
properties. Scarcity of its plant material has necessitated in vitro production of
therapeutic metabolites; however, their yields were low compared to field
grown plants. Possible reasons for this could be differences in physiological
and biochemical processes between plants grown in photoautotrophic versus
photoheterotrophic modes of nutrition. Comparative transcriptomes of S.
chirayita were generated to decipher the crucial molecular components
associated with the secondary metabolites biosynthesis. Illumina HiSeq
sequencing yielded 57,460 and 43,702 transcripts for green house grown
(SCFG) and tissue cultured (SCTC) plants, respectively. Biological role
analysis (GO and COG assignments) revealed major differences in SCFG and
SCTC transcriptomes. KEGG orthology mapped 351 and 341 transcripts onto
secondary metabolites biosynthesis pathways for SCFG and SCTC
transcriptomes, respectively. Nineteen out of 30 genes from primary
metabolism showed higher in silico expression (FPKM) in SCFG versus
SCTC, possibly indicating their involvement in regulating the central carbon
pool. In silico data were validated by RT-qPCR using a set of 16 genes,
wherein 10 genes showed similar expression pattern across both the methods.
Comparative transcriptomes identified differentially expressed transcription
factors and ABC-type transporters putatively associated with secondary
metabolism in S. chirayita. Additionally, functional classification was
performed using NCBI Biosystems database.
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This study identified the molecular components implicated in differential
modes of nutrition (photoautotrophic vs. photoheterotrophic) in relation to
secondary metabolites production in S. chirayita.
Keyword: Swertia chirayita, Secondary metabolites, Transcriptome, Next
generation sequencing, Photoheterotrophic
Chauhan, Rajinder Singh (2018). Uncovering interconnections between
kinases vis-a-vis physiological and biochemical processes contributing to
picroside-I biosynthesis in a medicinal herb, Picrorhiza kurroa Royle ex. Benth.
Acta Physiologiae Plantarum, 40(6), 1-14.
Abstract: Picroside-I (P-I) is an iridoid glycoside of Picrorhiza kurroa, a
perennial medicinal herb native to North-Western Himalayas, used in the
preparation of herbal drug formulations. Natural habitat shoots (PKSS) produce
significantly higher P-I content as compared to in vitro shoots (PKS-15 and
PKS-25). Although temperature and culture conditions are known to play a
major role in influencing P-I biosynthesis in different shoots of P. kurroa, the
molecular mechanisms behind signal perception of variable environments are
completely unknown. Kinases have been considered as key signaling proteins
which control cellular processes involved in adaptability under diverse
environments, thereby affecting downstream primary and secondary metabolic
pathways. The current study investigated the association of kinases with P-I
production and shoot biomass in P. kurroa. Transcriptome mining and in silico
transcript abundance in three shoot tissues revealed differentially expressed
kinases under high and low P-I accumulating conditions. A total of 521, 473
and 346 transcripts encoding kinases were identified in PKS-25, PKS-15 and
PKSS tissues, respectively. Gene expression analysis of 43 selected genes in
differential P-I content shoot tissues and genotypes revealed key processes
regulated by kinases which might be associated with P-I biosynthesis.
Expression of 16 kinases genes involved in plant–pathogen interactions, abiotic
stress, wounding, hormonal response and carbohydrate metabolism was
observed to be up-regulated in high P-I accumulating conditions, indicating
their possible role in eliciting P-I biosynthesis in P. kurroa. Analysis of kinases
along with genes involved in controlling shoot biomass productivity revealed
that auxin response plays a major role in affecting biomass productivity in in
vitro shoots of P. kurroa.
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This study provides a basic understanding of physiological processes affected
under variable environmental conditions leading to differential biosynthesis of
P-I in P. kurroa.
Keyword: Picrorhiza kurroa, Picroside-I, Kinases, Secondary metabolism,
Shoot biomass, Transcriptome
Dr. Saurabh Jyoti Sarma, Assistant Professor, Department of
Biotechnology.
Sarma, Saurabh Jyoti (2019). Aerobic Granulation in Wastewater Treatment:
A General Overview. In Maulin Shah Susana Rodriguez-Couto (Ed.), Microbial
Wastewater Treatment. (pp, 57-81).
Abstract: The cell interaction in a microorganism is a capability of aggregation
to make them self-immobilized. These self-immobilized aggregates, mostly
formed in a spherical shape, are named as granules (Khan et al., 2013). The rate
of oxygen flow and other physical parameters results in the aerobic granules
development. The granule formed in the absence of oxygen categories as
anaerobic granules. Aerobic granules have become the most promising tool in
the wastewater treatment technologies. The treatment efficiency depends on the
growth of the microorganism and settling properties. Bulk sludge with higher
filamentous microorganisms causes the difficulty to settle in the clarifiers
because cells naturally have the dispersion characteristic, not aggregation
(Etterer, 2006). The applied adhesive force and shearing form aerobic granules
which have characteristics features like more settling property (Lochmatter,
2008), high retention time (Liu et al., 2016), and high activity (Bindhu and
Madhu, 2013). There are various uses of the aerobic granules in treatment
process such as biodegradation of dye, Bisphenol A, fluorinated compounds,
antibiotics, herbicides, pesticides, phenols, volatile organic compounds, etc.
(Sarma et al., 2016). Recently, aerobic granulation is being used in paper and
pulp wastewater treatment (Vashi et al., 2017). In this chapter, various aspects of
the aerobic granulation are discussed such as granular characteristics,
mechanism of granules formation, microbial diversity, reactors used for
granulation, process parameters, and the role and application of aerobic granules
in wastewater treatment.
Keyword: Aerobic Granules, Microorganism, Granule Formation,
Hydrophobicity
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Sarma, Saurabh Jyoti (2019). Aerobic Granulation Technology for
Wastewater Treatment. In Y.V. Nancharaiah & Vayalam P. Venugopalan (Eds.),
Microbial Biofilms in Bioremediation and Wastewater Treatment (pp. 296).
Abstract: Aerobic granulation technology is an emerging technology of
wastewater treatment, which has been mostly explored by the researchers
from around 1998-2000. Aerobic granules are formed during wastewater
treatment in sequencing batch reactor (SBR) by self-immobilization of
different types of microorganisms present in the wastewater. This chapter
provides an outline of the roles of SBR in granule formation and proposes
various hypotheses to explain the granulation process. Many hypotheses have
been proposed to explain the mechanisms behind microbial granule
formation. Extracellular polymeric substances (EPS) produced by the
microbial cells may include proteins, polysaccharides, and nucleic acids
among others. Exopolysaccharides, proteins, lipids and nucleic acid are the
major components of the EPS found in aerobic granules. Long incubation
time required for granule development and the uncertainty involving the
appearance of stable granules are the other concerns of this technology.
Bioaugmentation is a strategy to enhance the performance of a bioprocess by
externally adding one or more microbial strains to the process.
Sarma, Saurabh Jyoti (2017). Aerobic granulation for future wastewater
treatment technology: challenges ahead. Environmental Science-Water Research
& Technology, 4, 9-15.
Abstract: Aerobic granules were discovered around 20 years back. These are
spherical aggregates of mixed microbial culture, typically around 0.5-3 mm in
diameter. Aerobic granule-based wastewater treatment technology has been
successfully used in full-scale for real wastewater treatment. It is argued that the
aerobic granule-based technology can potentially replace the traditional activated
sludge process. First of all, advantages, aerobic granule-based wastewater
treatment plants can be built within around one fourth of the land occupied by
conventional activated sludge-based plants. Additionally, this technology can
reduce the operating cost by nearly 25%. Reduction in sludge production and
reduction in energy consumption (around 30%) are other benefits of this
technology. Granule formation is a relatively slow process. In fact, the time
taken for granule formation is a challenge for full-scale application of this
technology. The mechanism behind aerobic granule formation is not fully
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understood. Thus, further investigation of the molecular mechanism of granule
formation would be crucial for successful commercialization of this technology.
Keyword: Aerobic, Granulation
Sarma, Saurabh Jyoti (2017). Bioenergy feasibility study of a raw corn and
peas processing facility in Lethbridge, Alberta. Biofuels, 1-10.
Abstract: A bioenergy feasibility study was conducted for Canada Safeway on
their Lucerne vegetable processing plant located in Lethbridge, Alberta. An
energy load profile for the plant was estimated using utility records from the
years 2005 to 2007, inclusive. Organic load was calculated from the wastewater
utility records for the same period. The study used a common energy unit (the
kilowatt, kW) to compare plant energy load with a theoretical biogas yield and
proposes a bioenergy system. Based on two existing cogeneration plants of
similar size located in Alberta, a system size of 800 to 1000 kW is proposed. The
proposed system assumes wastewater ‘peak shaving’ and the establishment of
‘feedstock co-digestion’. An estimated cost for the facility is Canadian Dollar
(AD) 7M to CAD 8M (2002 dollars), with an assumed return on investment of 8
to 9 years.
Keyword: Biogas, Feasibility, Cogeneration, Present worth analysis, Co-
digestion
Sarma, Saurabh Jyoti (2017). Magnetic particles for sugar separation from
sulphuric acid solution generated during nano-crystalline cellulose production.
Canadian Journal of Chemical Engineering, 4-10.
Abstract: Nano-crystalline cellulose (NCC) is a renewable material having
different applications ranging from drug delivery to a reinforcing filling agent in
polymer synthesis. Concentrated sulphuric acid is used to hydrolyze cellulosic
biomass to obtain NCC. Manufacturers are keen to reuse the diluted acid
solution left after the process. However, presence of mono and oligosaccharides
makes it unsuitable for repeated use. About 99 % of these compounds have been
successfully separated from the acid solution by employing NaOH-treated
magnetic particles developed during this investigation. It has been observed that
by NaOH treatment, zeta potential of the magnetic particles could be increased
from +11 mV to +37.5 mV; correspondingly, sugar removal efficiency was
increased from 23.04 % to more than 99 %. Thus, a direct correlation between
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the change in zeta potential of the particles and sugar separation efficiency has
been observed. This article is protected by copyright. All rights reserved
Keyword: Nano-crystalline cellulose, Magnetic particles, Surfactant coating,
Sugar separation, Zeta potential
Sarma, Saurabh Jyoti (2018). Carbon, Nitrogen and Phosphorus Removal
Mechanisms of Aerobic Granules. Critical Reviews in Biotechnology, 1077-
1088.
Abstract: Aerobic granules are the potential tools to develop modern
wastewater treatment technologies with improved nutrient removal efficiency.
These granules have several promising advantages over conventional activated
sludge-based wastewater treatment processes. This technology has the
potential of reducing the infrastructure and operation costs of wastewater
treatment by 25%, energy requirement by 30%, and space requirement by
75%. The nutrient removal mechanisms of aerobic granules are slightly
different from that of the activated sludge. For instance, unlike activated
sludge process, according to some reports, as high as 70% of the total
phosphorus removed by aerobic granules were attributed to precipitation
within the granules. Similarly, aerobic granule-based technology reduces the
total amount of sludge produced during wastewater treatment. However, the
reason behind this observation is unknown and it needs further explanations
based on carbon and nitrogen removal mechanisms. Thus, as a part of the
present review, a set of new hypotheses have been proposed to explain the
peculiar nutrient removal mechanisms of the aerobic granules.
Keyword: Aerobic granules, Carbon, Nitrogen, Removal mechanisms
Sarma, Saurabh Jyoti (2019). Production of Cellulase by Trichoderma sp. By
Utilization of Various Agrofood Residues. International Journal of
Environment and Health Sciences, 1(1), 1-6.
Abstract: This mini review has been written from the standpoint of the
potential of lignocellulose bioconversion in meeting the ever-growing demands
of the world for various products. The mini-review is divided into three sections
- uses of cellulose, possible sources and submerged fermentation and global
environmental perspectives: solid state fermentation-details and measurement
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protocols and process parameters – submerged and solid-state fermentation
(SSF).
Keywords: Cellulases, Solid-state fermentation, Nutrients.
Sarma, Saurabh Jyoti (2019). Statistical model for performance analysis of
DART -A steel wool based arsenic removal water filter installed in various
affected villages. International Journal of Environment and Health Sciences, 1
(1), 7-14.
Abstract: This paper reports the results of performance analysis of DART
(DRDO Arsenic Removal Technology), a novel household water filter providing
arsenic free drinking water to the people who are affected by arsenic poisoning
of ground water. DART has been developed by DRDO, (Defence Research and
Development Organization), India as an utmost required immediate solution to
the arsenic affected population, and has also been validated as an economic,
easy to maintain and low power consuming solution. These filters were installed
in seven affected villages and evaluated in terms of their efficiency to remove
arsenic from drinking water. The waste generated from the filter was converted
to standard grade impermeable concrete blocks for its disposal complying with
EPA's toxicity characteristics and leaching procedure (TCLP), for zero waste
generation from construction industries. The primary users, mainly the ladies of
the houses covered under this program were trained to operate and maintain the
system. A statistical model has also been designed to automatically convert the
raw data in a proper format data structure in order to carry out fundamental
statistical data analysis by which the life span of the material used for the
filtration has been predicted.
Keywords: Affected villages; Arsenic removal; Drinking water; Filter;
Statistical analysis.
Sarma, Saurabh Jyoti. (Ed.). (2018). Microbial sensing in fermentation.
Wiley Blackwell ISBN: 9781119247975
Abstract: A comprehensive review of the fundamental molecular mechanisms
in fermentation and explores the microbiology of fermentation technology and
industrial applications Microbial Sensing in Fermentation presents the
fundamental molecular mechanisms involved in the process of fermentation
and explores the applied art of microbiology and fermentation technology. The
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text contains descriptions regarding the extraordinary sensing ability of
microorganisms towards small physicochemical changes in their
surroundings. The contributors - noted experts in the field - cover a wide
range of topics such as microbial metabolism and production (fungi, bacteria,
yeast etc); refined and non refined carbon sources; bioprocessing; microbial
synthesis, responses and performance; and biochemical, molecular and extra/
intracellular controlling. This resource contains a compilation of literature on
biochemical and cellular level mechanisms for microbial controlled
production and includes the most significant recent advances in industrial
fermentation. The text offers a balanced approach between theory and
practical application, and helps readers gain a clear understanding of
microbial physiological adaptation during fermentation and its cumulative
effect on productivity.
Keyword: fungi; refined carbon; Bioprocessing; Microbial synthesis,
Responses and performance and performance; bioche intracellular controlling.
Sumit Sharma, Research Scholar, Department of Biotechnology
Sharma, Sumit (2019). Production of Cellulase by Trichoderma sp. By
Utilization of Various Agrofood Residues. International Journal of
Environment and Health Sciences, 1(1), 1-6.
Abstract: This mini review has been written from the standpoint of the
potential of lignocellulose bioconversion in meeting the ever-growing demands
of the world for various products. The mini-review is divided into three
sections - uses of cellulose, possible sources and submerged fermentation and
global environmental perspectives: solid state fermentation-details and
measurement protocols and process parameters – submerged and solid-state
fermentation (SSF).
Keywords: Cellulases, Solid-state fermentation, Nutrients.
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Sharma, Sumit (2019). Statistical model for performance analysis of DART -A
steel wool based arsenic removal water filter installed in various affected
villages. International Journal of Environment and Health Sciences, 1(1), 7-14.
Abstract: This paper reports the results of performance analysis of DART
(DRDO Arsenic Removal Technology), a novel household water filter
providing arsenic free drinking water to the people who are affected by arsenic
poisoning of ground water. DART has been developed by DRDO, (Defence
Research and Development Organization), India as an utmost required
immediate solution to the arsenic affected population, and has also been
validated as an economic, easy to maintain and low power consuming solution.
These filters were installed in seven affected villages and evaluated in terms of
their efficiency to remove arsenic from drinking water. The waste generated
from the filter was converted to standard grade impermeable concrete blocks for
its disposal complying with EPA's toxicity characteristics and leaching
procedure (TCLP), for zero waste generation from construction industries. The
primary users, mainly the ladies of the houses covered under this program were
trained to operate and maintain the system. A statistical model has also been
designed to automatically convert the raw data in a proper format data structure
in order to carry out fundamental statistical data analysis by which the life span
of the material used for the filtration has been predicted.
Keywords: Affected villages; Arsenic removal; Drinking water; Filter;
Statistical analysis.
Dr. Vinayak Gupta, Assistant Professor, Department of Biotechnology.
Gupta, Vinayak (2019). Role of Monoamine Oxidases in Heart Diseases. In
Chakraborti S., Dhalla N., Dikshit M. & Ganguly N. (Eds), Modulation of
Oxidative Stress in Heart Disease (pp. 129-150). Singapore: Springer.
Abstract: Monoamine oxidases (MAOs) are flavoenzymes that metabolize
biogenic amines, dietary amines, and catecholamines in the brain and peripheral
tissues. While MAOs are known to contribute to psychiatric and
neurodegenerative (Parkinson’s and Alzheimer’s) diseases for a long time,
recent studies have established their role in heart diseases as these enzymes
potently generate reactive oxygen species (ROS) in cardiomyocytes via
oxidative deamination of mainly norepinephrine and serotonin. Indeed, MAOs
have emerged as important regulators of mitochondrial/endothelial/cardiac
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dysfunction, essential hypertension, ventricular hypertrophy, myocardial
infarction, cardiomyocyte apoptosis, post ischemic cardiac damage, and heart
failure. Transcriptional and posttranscriptional regulation of MAOs (via certain
transcription factors or microRNAs) may emerge as new therapeutic strategies
for treatment of cardiovascular pathological conditions. The next-generation
MAO inhibitors (that do not cause irreversible inhibition of MAOs) may also be
useful for management of cardiovascular disease states involving dysregulated
expression/activity of MAOs.
Keyword: Cardiovascular, Monoamine oxidase, Reactive oxygen species,
Catecholamines
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Department of Civil Engineering
Dr. Joy Pal, Assistant Professor, Department of Civil Engineering.
Pal, Joy (2017). Identification of loosening of bolts in a steel plane frame
structure using fourier decomposition method. International Conference on
Vibration Problems.
Abstract: In the present study, an adaptive Fourier Decomposition Method
(FDM) is applied to identify damage at connections. For that purpose, an
experimental single-story plane frame model is considered. The beam and
columns of the frame are connected by angles and bolts, and the damage is
introduced by loosening bolts at different locations. The frame is excited by a
hammer at the right top corner and strain time histories are collected from
different points. The FDM and empirical mode decomposition (EMD) algorithm
are applied to characterize the damage sensitive features. The results obtained
from the FDM are compared with the EMD algorithm, which show that the
performance of FDM is better, that motivates to extend its application further to
estimate the amount of bolt loosening in terms of extracted damage sensitive
features
Keyword: Framed structure, Loosening of bolts, Damage at connections,
Damage detection, Fourier decomposition method, EMD
Pal, Joy (2018). Identification of Semi-rigid Joints in Steel Frame Structures
Using Vibration-Based Technique. Recent Advances in Structural Engineering
(pp. 363-374).
Abstract: The connections are the critical locations where damage commonly
occurs. However, very limited vibration-based studies using the artificial
neural network (ANN) are found to identify the damaged connections. Again,
the ANN-based technique requires retraining of network for little variation in
geometry of the structure. Moreover, those studies were limited to damage at
the beam end connection. In this present study, health monitoring of steel plane
frame structures having semi-rigid connections either at the beam side or at the
column side using a limited number of sensors is addressed. With that purpose,
a single-storey and a two-storey frame are considered. The frames are modeled
using plane frame elements, in which two rotational springs are placed at the
ends to affect the stiffness of the rotational springs only. The frames are
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excited using an impact at the right top corner, and strain time responses are
collected from the connections only. The strain data are then transformed into
frequency spectra. Using the frequency spectra, an objective function is
developed and minimized using particle swarm optimization (PSO) to get the
updated fixity factors for all the springs. In order to get more accurate values
of fixity factors of the two-storey frame, it is divided into sub-structures, and it
is found that the technique estimates fixity factors with an acceptable error.
Keyword: Planar frame, Structure Semi-rigid joint, Rotational spring, Particle
swarm optimization
Pal, Joy (2018). Damage-induced acoustic emission source identification in an
advanced sandwich composite structure. Composite Structures, 202, 860-866.
Abstract: This paper proposes an acoustic emission (AE) based real-time
health monitoring framework to efficiently identify the probable damage
initiation/propagation locations in advanced sandwich composite structures.
Towards this, numerical simulations and laboratory experiments on damage-
induced AE-wave propagation in an aramid honeycomb composite structure
have been carried out using a randomly selected sensory network. The
simulation results are successfully validated with laboratory experiments.
Eventually, the damage-source/AE-source regions are efficiently identified by
applying an evolutionary algorithm- Particle-Swarm- Optimization based
monitoring framework, which uses the registered AE-signals from the sensory
network. A thorough assessment of different AE-source locations was carried
out to evaluate the performance and the robustness of the proposed online
monitoring strategy. The results clearly represent the efficiency of the
framework for localizing the AE-source locations in such advanced and
complex structures. Moreover, the proposed framework is reliable,
independent of sensor positions, and not dependent upon the operator’s
expertise.
Keyword: Acoustic emission, Aramid honeycomb composite sandwich panel,
Piezoelectric transducer disc sensors, Damage localization, Particle swarm
optimization, Particle swarm optimization.
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Tushar Bansal, Research Scholar, Department of Civil Engineering.
Bansal, Tushar (2018). Model based Corrosion Assessment in Rebars of
Different Fly Ash Blended Concrete using Piezo Sensors. In APWSHM 2018 -
Asia-Pacific Workshop on Structural Health Monitoring (pp. 1-12).
Abstract: With the increase in infrastructure developments and increasing
emphasis on the use of green materials, the construction industry is in the need
of constant innovation and improvisation in both materials and technology. The
fly ash (FA) is most widely used in construction field as a replacement of
cement in concrete production. In this paper, model-based corrosion assessment
in rebar of different FA blended concrete using non- dimensional structural
parameters determined by piezo sensors is studied. The Accelerated corrosion
tests are conducted on rebar of different blended concrete cylindrical
specimens, before embedding the rebar in concrete piezo sensors are surface
bonded. The measurements are made with piezo sensor of size 10x10x0.3mm
surface bonded on rebar using electro-mechanical impedance (EMI) technique.
The non-dimensional structural parameters are acquired out from the
conductance and susceptance signatures of the piezo sensor. The structural
parameters are standard against the corrosion level. Based on the level, a
corrosion evaluation model is proposed. The experimental results based on the
qualitative and quantitative analysis shows that the piezo sensor are assess the
corrosion using the non-dimensional structural parameters.
Keyword: Chloride-Induced Corrosion, non-dimensional Structural
Parameters, Electromechanical Impedance Technique, Piezo-sensors
Bansal, Tushar (2018). Rebar corrosion assessment comparison of different
piezo configurations in blended concrete. In APWSHM 2018 - Asia-Pacific
Workshop on Structural Health Monitoring (pp. 1-12).
Abstract: An embedded piezo sensor has high sensitivity, higher longevity,
low cost and special encapsulation to the sensing element such that it is
protected against deterioration by water. Its application of self-sensing
mechanism technology is aimed at achieving high performance, better and
more reliability and uniform quality. In this study different blended concrete
cylindrical specimens were prepared to investigate the rebar corrosion
assessment comparison of two different piezo configurations (surface bonded
and embedded) in blended concrete. Experiments are conducted on different
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blended concrete on which piezo sensors are surface bonded on rebar and
embedded in the surrounding of the rebar inside the concrete to compare the
sensing capability of the two configurations. A series of accelerated corrosion
tests has been performed on reinforced cylindrical concrete specimens. The non
-dimensional structural parameters and the statistical index are being compared
for the two types of sensor configurations. The experimental results based on
the qualitative and quantitative analysis shows that the surface bonded and
embedded piezo sensor are able to diagnosis corrosion and are complementary
to each other.
Keyword: Chloride-Induced Corrosion, Non-dimensional Structural
Parameters, Electro-mechanical Impedance Technique, Fly Ash, Surface
Bonded, Embedded Piezo Sensors
Dr. Visalakshi Talakokula, Professor, Department of Civil Engineering
Talakokula, Visalakshi (2018). Model based Corrosion Assessment in Rebars
of Different Fly Ash Blended Concrete using Piezo Sensors. In APWSHM
2018 - Asia-Pacific Workshop on Structural Health Monitoring (pp. 1-12).
Abstract: With the increase in infrastructure developments and increasing
emphasis on the use of green materials, the construction industry is in the need
of constant innovation and improvisation in both materials and technology. The
fly ash (FA) is most widely used in construction field as a replacement of
cement in concrete production. In this paper, model-based corrosion assessment
in rebar of different FA blended concrete using non- dimensional structural
parameters determined by piezo sensors is studied. The Accelerated corrosion
tests are conducted on rebar of different blended concrete cylindrical
specimens, before embedding the rebar in concrete piezo sensors are surface
bonded. The measurements are made with piezo sensor of size 10x10x0.3mm
surface bonded on rebar using electro-mechanical impedance (EMI) technique.
The non-dimensional structural parameters are acquired out from the
conductance and susceptance signatures of the piezo sensor. The structural
parameters are standard against the corrosion level. Based on the level, a
corrosion evaluation model is proposed. The experimental results based on the
qualitative and quantitative analysis shows that the piezo sensor are assess the
corrosion using the non-dimensional structural parameters.
Keyword: Chloride-Induced Corrosion, Non-dimensional Structural
Parameters, Electromechanical Impedance Technique, Piezo-sensors
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Talakokula, Visalakshi (2018). Rebar corrosion assessment comparison of
different piezo configurations in blended concrete. In APWSHM 2018 - Asia-
Pacific Workshop on Structural Health Monitoring (pp. 1-12).
Abstract: An embedded piezo sensor has high sensitivity, higher longevity,
low cost and special encapsulation to the sensing element such that it is
protected against deterioration by water. Its application of self-sensing
mechanism technology is aimed at achieving high performance, better and
more reliability and uniform quality. In this study different blended concrete
cylindrical specimens were prepared to investigate the rebar corrosion
assessment comparison of two different piezo configurations (surface bonded
and embedded) in blended concrete. Experiments are conducted on different
blended concrete on which piezo sensors are surface bonded on rebar and
embedded in the surrounding of the rebar inside the concrete to compare the
sensing capability of the two configurations. A series of accelerated corrosion
tests has been performed on reinforced cylindrical concrete specimens. The
non-dimensional structural parameters and the statistical index are being
compared for the two types of sensor configurations. The experimental results
based on the qualitative and quantitative analysis shows that the surface
bonded and embedded piezo sensor are able to diagnosis corrosion and are
complementary to each other.
Keyword: Chloride-Induced Corrosion, non-dimensional Structural
Parameters, Electromechanical Impedance Technique, Piezo-sensors
Talakokula, Visalakshi (2019). Industrial applications of electro-mechanical
impedance technique in novel non-bonded configurations. Proceedings of SPIE
-The International Society for Optical Engineering (pp. 109701-11).
Abstract: Ease of implementation of any sensor system must involve simple
instrumentation techniques along with adequate adaptability to change in
specimen configuration. The past decade has witnessed an exponential upsurge
in applications of piezoelectric transducers in various fields of engineering and
biotechnology, whereas sensor types has remained the same, narrowing its
suitability in certain fields. The present research deals with development of two
novel piezo sensor configurations namely the single clamp non-bonded sensor
(SCNS) and re-useable bolted sensor (RBS). The sensor was developed to
accommodate change in dimension and is tested on different specimens based on
its design. Fundamentally, SCNS is developed for circular structures such as
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pipelines and RBS is developed for 2-D plates. Effectiveness of both sensors is
tested by mounting it on a specimen based on its design. Damage sensitivity of
the sensors was studied by analyzing the conductance signatures extracted from
the piezo patches based on electromechanical impedance (EMI) technique.
Repeatability of less than 2% was observed in both cases. At different levels of
damage created shifts in signatures is observed. A statistical index used to
quantify the amount of shift showed a gradual increase in magnitude
corresponding to increase in damage. Similar trends are observed in both sensor
data making both sensors suitable for application. Through the damage
sensitivity tests, SCNS and RBS its proved viability for application in field
studies. However, it might be noted that all tests were conducted in controlled
environments of temperature and pressure and negating its effects by application
of correction factors must be carried out for field application.
Keyword: Single Clamp Non-bonded Sensor (SCNS), Re-useable Bolted
Sensor (RBS)
Talakokula, Visalakshi (2019). Internal corrosion detection in pipes using
piezoelectric transducers. Structural Health Monitoring 2019: Enabling
Intelligent Life-Cycle Health Management for Industry Internet of Things
(IIOT). Proceedings of the 12th International Workshop on Structural Health
Monitoring (pp. 1595).
Abstract: This paper introduces a new method for internal corrosion detection
in metal pipelines using an externally surface bonded (SB) piezoelectric
transducer working on electromechanical impedance technique (EMI).
Specifically, changes in mechanical properties of the structure is monitored by
observing the changes in structural mechanical impedance obtained through the
bonded piezo electric sensor thereby employing EMI technique. Through
controlled incremental corrosion induced in the pipe segment considered for
experimentation using accelerated corrosion tests a realistic corrosion
environment was proposed. The hourly exposure to corrosion is correlated with
the signatures acquired through the sensors. Sensitive parameters such as
temperature and humidity were kept constant to discern changes solely due to
corrosion. Through timely phased acquisition of signatures using an LCR meter,
shift in conductance may be monitored. Changes in structural parameters such as
stiffness, mass and damping is calibrated through conductance signature
analysis. Development of corrosive products was monitored simultaneously with
scanning electron microscopy (SEM). Experimental results show that good
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correlation exists between the obtained SEM analysis and change in structural
parameters. A steady decrease in stiffness and mass was witnessed with a
noticeable trend in magnitude. In essence, a simple, easy implementable method
in employing EMI method to detect internal corrosion in pipelines is
demonstrated.
Talakokula, Visalakshi (2018). Monitoring early hydration of reinforced
concrete structures using structural parameters identified by piezo sensors via
electromechanical impedance technique. Mechanical Systems and Signal
Processing, 99, 129-141.
Abstract: Concrete is the most widely used material in civil engineering
construction. Its life begins when the hydration process is activated after
mixing the cement granulates with water. In this paper, a non-dimensional
hydration parameter, obtained from piezoelectric ceramic (PZT) patches
bonded to rebars embedded inside concrete, is employed to monitor the early
age hydration of concrete. The non-dimensional hydration parameter is derived
from the equivalent stiffness determined from the piezo-impedance transducers
using the electro-mechanical impedance (EMI) technique. The focus of the
study is to monitor the hydration process of cementitious materials
commencing from the early hours and continue till 28 days using single non
dimensional parameter. The experimental results show that the proposed piezo-
based non-dimensional hydration parameter is very effective in monitoring the
early age hydration, as it has been derived from the refined structural
impedance parameters, obtained by eliminating the PZT contribution, and
using both the real and imaginary components of the admittance signature.
Keyword: Concrete, Piezo Ceramics, Admittance, Conductance, Suseptance,
Hydration
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Department of Computer Science & Engineering
Akshay Kumar Goel, B.Tech Student, Department of CSE
Goel, Akshay Kumar, (2019). Profit or Loss: A Long Short Term Memory
based model for the Prediction of share price of DLF group in India. 2019 IEEE
9th International Conference on Advanced Computing (IACC) (pp. 120-124).
Tiruchirappalli, India.
Abstract: Presently, the prediction of share is a challenging issue for the
research community as share market is a chaotic place. The reason behind it,
there are several factors such as government policies, international market,
weather, performance of company. In this article, a model has been developed
using long short-term memory (LSTM) to predict the share price of DLF group.
Moreover, for the experimental purpose the data of DLF group has been taken
from yahoo financial services in the time duration of 2008 to 2018 and the
recurrent neural network (RNN) model has been trained using data ranging from
2008 to 2017. This RNN based model has been tested on the data of year 2018.
For the performance comparison purpose, other linear regression algorithms i.e.
k-nn regression, lasso regression, XGboost etc has been executed and the
proposed algorithm outperforms with 2.6% root mean square error.
Keywords: Prediction Model, Recurrent Neural Network, Long Short-Term
Memory (LSTM), Mean Square Error (MSE).
Dr. Anurag Goswami, Assistant Professor, Department of CSE
Goswami, Anurag (2017). An Empirical Investigation to Overcome Class-
Imbalance in Inspection Reviews. ICMLDS, 2017 (pp. 15-22).
Abstract: Software inspection results in reviews that report the presence of
faults. Requirements author must manually read through the reviews and
differentiate between true-faults and false-positives. Problem: post-inspection
decisions (fault or non-fault) are difficult and time consuming. It is difficult to
employ machine learning (ML) techniques directly to raw (unstructured) data
because of class imbalance problem and possible fault-slippage through
misclassification of fault. Aim: The aim of this research is to solve this problem
with the help of ensemble approach and priority analysis to achieve significant
accuracy in determining true-fault and false-positive reviews without losing any
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listed fault. Method: We conducted empirical experiment using two trained
models (with reviews from inspection domain vs. movies domain) to address
class imbalance problem. Our approach uses ensemble methods to develop
classification confidence of inspection reviews and assigns them to appropriate
priority class. Results: The results showed that movies trained model performed
better than inspection trained and restricted any possible fault-slippage.
Keyword: Fault priority, Class imbalance, Ensemble, Sampling, Inspections
reviews, Part of speech, Machine learning, fault slippage
Goswami, Anurag (2017). Validation of Inspection Reviews over Variable
Features Set Threshold. ICMLDS, 2017 (pp. 128-135).
Abstract: Mining software requirement reviews involve natural language
processing (NLP) to efficiently validate a true-fault as useful and false-positive
as non-useful. Aim: The aim of this paper is to evaluate our proposed mining
approach to automate the validation of requirement reviews generated during an
inspection of NL requirements document. Method: Our approach utilized two
training models; one from requirement reviews and other from online movies.
We conducted an empirical study to test our approach using part of speech
(POS) against these two trained models and observed trends w.r.t. F-measure and
G-mean along with percentage of features used to train two models. Results: The
results showed that using training reviews from two different domains report
similar trend across evaluation metrics. Our results show that the most stable and
promising validation results for F-measure and G-mean are obtained when a
model over inspection and movies reviews are trained using feature set threshold
value 65% and 45% respectively
Keyword: Feature sets, Faults, Inspection reviews, Class imbalance, Sampling,
Machine learning
Goswami, Anurag (2018). Using Supervised Learning to Guide the Selection
of Software Inspectors in Industry. 29th IEEE International Symposium on
Software Reliability Engineering Workshops (pp. 12-17).
Abstract: Software development is a multi-phase process that starts with
requirement engineering. Requirements elicited from different stakeholders are
documented in natural language (NL) software requirement specification (SRS)
document. Due to the inherent ambiguity of NL, SRS is prone to faults (e.g.,
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ambiguity, incorrectness, inconsistency). To find and fix faults early (where
they are cheapest to find), companies routinely employ inspections, where
skilled inspectors are selected to review the SRS and log faults. While other
researchers have attempted to understand the factors (experience and learning
styles) that can guide the selection of effective inspectors but could not report
improved results. This study analyses the reading patterns (RPs) of inspectors
recorded by eye-tracking equipment and evaluates their abilities to find various
fault types. The inspectors’ characteristics are selected by employing ML
algorithms to find the most common RPs w.r.t each fault types. Our results
show that our approach could guide the inspector selection with an accuracy
ranging between 79.3% and 94% for various fault-types.
Keyword: Fault types, Machine learning
Goswami, Anurag (2018). Validating Requirements Reviews by Introducing
Fault-Type Level Granularity: A Machine Learning Approach. 11th ACM
Innovations in Software Engineering Conference (pp. 1-11).
Abstract: Inspections are a proven approach for improving software
requirements quality. Owing to the fact that inspectors report both faults and
non-faults (i.e., false positives) in their inspection reports, a major chunk of
work falls on the person who is responsible for consolidating the reports
received from multiple inspectors. We aim at automation of fault-consolidation
step by using supervised machine learning algorithms that can effectively
isolate faults from non-faults. Three different inspection studies were conducted
in controlled environments to obtain real inspection data from inspectors
belonging to both industry and from academic backgrounds. Next, we devised a
methodology to separate faults from non-faults by first using ten individual
classifiers from five different classification families to categorize different fault
-types (e.g., omission, incorrectness, and inconsistencies). Based on the
individual performance of classifiers for each fault-type, we created targeted
ensembles that are suitable for identification of each fault type. Our analysis
showed that our selected ensemble classifiers were able to separate faults from
non-faults with very high accuracy (as high as 85-89% for some fault-types),
with a notable result being that in some cases, individual classifiers performed
better than ensembles. In general, our approach can significantly reduce effort
required to isolate faults from false positives during the fault consolidation step
of requirements inspections.
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Our approach also discusses the percentage possibility of correctly classifying
each fault-type.
Keyword: Machine learning Ensemble, Inspection reviews, Supervised
learning
Goswami, Anurag (2019). Email Spam Detection: An Empirical Comparative
Study of Different ML and Ensemble Classifiers. 2019 IEEE 9th International
Conference on Advanced Computing (IACC) (pp. 69-74). Tiruchirappalli, India.
Abstract: Recent Development in Hardware and Software Technology for the
communication email is preferred. But due to the unbidden emails, it affects
communication. There is a need for detection and classification of spam email.
In this present research email spam detection and classification, models are built.
We have used different Machine learning classifiers like Naive Bayes, SVM,
KNN, Bagging and Boosting (Adaboost), and Ensemble Classifiers with a
voting mechanism. Evaluation and testing of classifiers is performed on email
spam dataset from UCI Machine learning repository and Kaggle website.
Different accuracy measures like Accuracy Score, F measure, Recall, Precision,
Support and ROC are used. The preliminary result shows that Ensemble
Classifier with a voting mechanism is the best to be used. It gives the minimum
false positive rate and high accuracy.
Keywords: Spam detection and classification, Machine learning Classifiers,
Accuracy Measure, Voting Mechanism.
Goswami, Anurag (2019). Multiclass Fake News Detection using Ensemble
Machine Learning. 2019 IEEE 9th International Conference on Advanced
Computing (pp. 103-107).
Abstract: Over the past few years, fake news and its influence have become a
growing cause of concern in terms of debate and public discussions. Due to the
availability of the Internet, a lot of user-generated content is produced across the
globe in a single day using various social media platforms. Nowadays, it has
become very easy to create fake news and propagate it worldwide within a short
period of time. Despite receiving significant attention in the research
community, fake news detection did not improve significantly due to insufficient
context-specific news data. Most of the researchers have analysed the fake news
problem as a binary classification problem, but many more prediction classes
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exist. In this research work, experiments have been conducted using a tree-based
Ensemble Machine Learning framework (Gradient Boosting) with optimized
parameters combining content and context level features for fake news
detection. Recently, adaptive boosting methods for classification problems have
been derived as gradient descent algorithms. This formulation justifies key
elements and parameters in the methods, which are chosen to optimize a single
common objective function. Experiments are conducted using a multi-class
dataset (FNC) and various machine learning models are used for classification.
Experimental results demonstrate the effectiveness of the ensemble framework
compared to existing benchmark results. Using the Gradient Boosting algorithm
(an ensemble machine learning framework), we achieved an accuracy of 86%
for multi-class classification of fake news having four classes.
Keywords: Fake News, Machine Learning, Deep Learning, Gradient Boosting.
Goswami, Anurag (2019). Pitfree: Pot-holes detection on Indian Roads using
Mobile Sensors. Proceedings of the 8th International Advance Computing
Conference (pp. 185-190).
Abstract: Potholes on road will make transportation slower and costly. India
has a big network of roads to connect the villages and cities, the authority
persons cannot travel across the region for identification of holes. As per
advancement in machine learning in recent time, we can use this technology for
the identification and patching the potholes. As per the recent survey around
400millions, people have a smartphone in India. We can use smartphone sensors
(such as Accelerometer and gyroscope) to identify the potholes on road and GPS
for the location of the pit. The major task of this problem is to capture the data
and annotation. We have developed an android app for capturing the value of
displacement while travelling on road. We have applied different classification
algorithms to sensor raw data. SVM is the most suitable classification technique
for this problem. The android app will sound an alarm when a pothole is
detected.
Keyword: Machine Learning, Mobile Sensors, Road safety
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Goswami, Anurag (2019). SMS Spam Filtering on Multiple Background
Datasets Using Machine Learning Techniques: A Novel Approach. Proceedings
of the 8th International Advance Computing Conference (pp. 59-65).
Abstract: Short Message Service (SMS) is one of the well-known and reliable
communication services in which a message sends electronically. In the current
era, the declining in the cost per SMS day by day by overall all the telecom
organizations in India has encouraged the extended utilization of SMS. This
ascent pulled in assailants, which have brought about SMS Spam problem. Spam
messages include advertisements, free services, promotions and marketing,
awards, etc. Individuals are utilizing the ubiquity of cell phone gadgets is
growing day by day as telecom giants give a vast variety of new and existing
services by reducing the cost of all services. Short Message Service (SMS) is
one of the broadly utilized communication services. Due to the high demand for
SMS service, it has prompted a growth in mobile phones attacks like SMS
Spam. In our proposed approach, we have presented a general model that can
distinguish and filter the spam messages utilizing some existing machine
learning classification algorithms. Our approach builds a generalized SMS spam-
filtering model, which can filter messages from various backgrounds (Singapore,
American, Indian English etc.). In our approach, preliminary results are
mentioned below based on Singapore and Indian English based publicly
available datasets. Our approach showed promise to accomplish a high precision
utilizing Indian English SMS large datasets and others background’s datasets
also.
Keyword: Short Message Service (SMS), SMS Spam-filtering, Feature matrix,
Telecom organizations
Dr. Apoorva Mishra, Assistant Professor, Department of CSE
Mishra, Apoorva (2019). A Novel Genetically Optimized Convolutional Neural
Network for Traffic Sign Recognition: A New Benchmark on Belgium and
Chinese Traffic Sign Datasets. Neural Processing Letters, 1-25.
Abstract: Traffic signs are a key constituent of the road network and prove to be
very useful for warning and guiding the drivers. In intelligent transport systems,
traffic sign recognition (TSR) is indispensable for autonomous driving.
However, due to the complex outdoor environment, real-time recognition of
traffic signs is much more challenging in comparison with many other pattern
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recognition tasks. Convolutional neural networks (CNNs) have an exceptional
capability of recognizing patterns and are one of the most popular deep learning
techniques. Finding the optimal configuration of a CNN for a task is a major
challenge and is an active area of research. Genetic algorithm (GA) is a meta-
heuristic approach well-known for its optimization power. In this paper, we
propose a novel deep learning technique based on the concept of domain transfer
learning for the recognition of traffic signs. This technique utilizes a newly
proposed variant of the GA for finding the optimal values of the number of
epochs and the learning rate parameter for each layer of the pre-trained CNN
model (VGG-16). To examine the effectiveness of our technique, we apply it to
the following two benchmark datasets of TSR: Belgium Traffic Sign
Classification (BTSC) dataset and Chinese Traffic Sign Dataset (TT100K). The
results indicate that our model outperforms all the existing approaches applied to
these datasets and gives a new benchmark of the recognition accuracies of
99.16% for the BTSC and 96.28% for the TT100K datasets, thus establishing the
robustness of our model.
Keyword: Traffic sign recognition, Convolutional neural network, Domain
transfer learning, Genetic algorithms, Ternary crossover
Mishra, Apoorva (2019). Texture classification using convolutional neural
network optimized with whale optimization algorithm. SN Applied Science,
1:655, 1-11.
Abstract: Texture classification is an active area of research in the field of
pattern recognition. Convolutional neural networks (CNNs) have a remarkable
capability of recognizing patterns and are one of the most efficient deep learning
techniques. But, finding the optimal values of the different hyperparameters of
the CNN is a major challenge. Nature-inspired algorithms (NIAs) are the meta-
heuristic algorithms well-known for their optimizing capability. Whale
optimization algorithm (WOA) is a recent nature-inspired algorithm (NIA) that
is inspired by the hunting behaviour of the humpback whales. In this paper, we
propose a novel deep learning technique for texture recognition using a CNN
optimized through WOA. We apply WOA at the two different levels in the
CNN: In the convolutional layer (for optimizing the values of the filters), and in
the fully connected layer (for optimizing the values of the weights and biases).
For examining the performance of our technique, we apply it to the following
three benchmark texture datasets: Kylberg v1.0, Brodatz, and Outex_TC_00012.
Our model performs better than most of the existing methods for the Kylberg
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and the Outex_TC_00012 datasets and gives competitive results for the Brodatz
dataset. It is evident from the results that our model has the potential for
application in the Feld of texture recognition.
Keyword: Convolutional neural network, Whale optimization algorithm
Dr. Arpit Bhardwaj, Assistant Professor, Department of CSE
Bhardwaj, Arpit (2019). Breast Cancer Diagnosis using Simultaneous Feature
Selection and Classification: A Genetic Programming Approach. Proceedings of
the 2018 IEEE Symposium Series on Computational Intelligence (pp. 2186-
2192).
Abstract: Breast cancer is the most prevalent type of cancer found in women
worldwide. It is becoming a leading cause of death among women in the whole
world. Early detection and effective treatment of this disease is the only rescue to
reduce breast cancer mortality. Because of the effective classification and high
diagnostic capability expert systems are gaining popularity in this field. But the
problem with machine learning algorithms is that if redundant and irrelevant
features are available in the dataset then they are not being able to achieve
desired performance. Therefore, in this paper, a simultaneous feature selection
and classification technique using Genetic Programming (GPsfsc) is proposed
for breast cancer diagnosis. To demonstrate our results, we had taken the
Wisconsin Breast Cancer (WBC) and Wisconsin Diagnostic Breast Cancer
(WDBC) databases from UCI Machine Learning repository and compared the
classification accuracy, sensitivity, specificity, confusion matrix, and Mann
Whitney test results of GONN with classical multi-tree GP algorithm for feature
selection (GPmtfs). The experimental results on WBC and WDBC datasets show
that the proposed method produces better classification accuracy with reduced
features. Therefore, our proposed method is of great significance and can serve
as first-rate clinical tool for the detection of breast cancer.
Keyword: Breast Cancer, Genetic Programming
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Bhardwaj, Arpit (2018). Classification of electroencephalogram signal for the
detection of epilepsy using Innovative Genetic Programming. Expert Systems,
36(1), 1-14.
Abstract: Epilepsy, sometimes called seizure disorder, is a neurological
condition that justifies itself as a susceptibility to seizures. A seizure is a sudden
burst of rhythmic discharges of electrical activity in the brain that causes an
alteration in behaviour, sensation, or consciousness. It is essential to have a
method for automatic detection of seizures, as these seizures are arbitrary and
unpredictable. A profound study of the electroencephalogram (EEG) recordings
is required for the accurate detection of these epileptic seizures. In this study, an
Innovative Genetic Programming framework is proposed for classification of
EEG signals into seizure and nonseizure. An empirical mode decomposition
technique is used for the feature extraction followed by genetic programming
for the classification. Moreover, a method for intron deletion, hybrid crossover,
and mutation operation is proposed, which are responsible for the increase in
classification accuracy and a decrease in time complexity. This suggests that the
Innovative Genetic Programming classifier has a potential for accurately
predicting the seizures in an EEG signal and hints on the possibility of building
a real‐time seizure detection system.
Keyword: Electroencephalogram, Genetic Programming
B.R. Dattu, Department of CSE
Dattu, B. R. (2019). Predicting Damage to Buildings Caused by Earthquakes
Using Machine Learning Techniques. 9th International Conference on Advanced
Computing (pp. 82-87).
Abstract: This paper presents the level of damage prediction to buildings caused
by Gorkha Earthquake in Nepal using machine learning techniques. The
predictions have been made based on mathematically calculated eight tectonic
indicators and past vibrational activity records. In this research the objective is to
predict earthquake damage on existing data set of seismic activity by using
machine learning techniques. In this study, two well-known approaches of
machine learning viz. Neural Network (NN) and Random Forest (RF) have been
implemented and optimal parameters for accurate prediction are investigated.
The analysis reveals that Random forest method has outperformed the neural
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network approach for building damage prediction. The F1 score using the
random forest classification has been obtained as 74.32%.
Keyword: Neural Network, Random Forest
Dr. Deeepak Garg, Professor & HOD, Department of CSE
Garg, Deepak (2019). A Convolution Neural Network based approach to detect
the disease in Corn Crop. 2019 IEEE 9th International Conference on Advanced
Computing (IACC) (pp. 176-181). Tiruchirappalli, India.
Abstract: The agricultural production is affected by the climate changes i.e.
humidity, rain, extremes of temperature etc. Additionally, abiotic stresses are
causative element to the etiology of disease as well as pest on crops. The
production of the crops can be improved by diagnosis as well as detecting the
accurate disease on time or in early stage. Moreover, it is very difficult for
accurately detecting and treatment based on the technique which used in disease
and insect pests diagnosis. Few researchers have made efforts on predicting
disease as well as pest crops using machine learning algorithms. Therefore, this
paper presents disease identification in corn crops by analyzing the leaves in the
very early stage. We have used Plant Village dataset for experiments and
analysis. The validity of the results has been cheeked on various performance
metrics such as precision, accuracy, recall, storage space, running time of the
model and AUC-RoC. The obtained results shows the proposed technique
outperform in comparison with the traditional machine learning algorithms.
Developed model is able to achieve the accuracy of 94%.
Keywords: convolution neural network, traditional machine learning methods,
pre-trained models, augmentation.
Garg, Deepak (2019). Profit or Loss: A Long Short Term Memory based model
for the Prediction of share price of DLF group in India. 2019 IEEE 9th
International Conference on Advanced Computing (IACC) (pp. 120-124).
Tiruchirappalli, India.
Abstract: Presently, the prediction of share is a challenging issue for the
research community as share market is a chaotic place. The reason behind it,
there are several factors such as government policies, international market,
weather, performance of company. In this article, a model has been developed
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using long short-term memory (LSTM) to predict the share price of DLF group.
Moreover, for the experimental purpose the data of DLF group has been taken
from yahoo financial services in the time duration of 2008 to 2018 and the
recurrent neural network (RNN) model has been trained using data ranging from
2008 to 2017. This RNN based model has been tested on the data of year 2018.
For the performance comparison purpose, other linear regression algorithms i.e.
k-nn regression, lasso regression, XGboost etc has been executed and the
proposed algorithm outperforms with 2.6% root mean square error.
Keywords: Prediction Model, Recurrent Neural Network, Long Short-Term
Memory (LSTM), Mean Square Error (MSE).
Garg, Deepak (2017). Approximation algorithm for resource allocation
problems with time dependent penalties. International Journal of Foundations of
Computer Science, 931-943.
Abstract: The Resource Allocation Problem with Time Dependent Penalties
(RAPTP) is a variant of uncapacitated resource allocation problems generally
referred as uncapacitated facility allocation problems or uncapacitated facility
location problem (UFLP). Work done in this paper is motivated by the work of
Du, Lu and Xu [7] in which authors considered facility location problems with
submodular penalties and presented a 3-approximation primal dual algorithm.
This paper considers that each unallocated demand point adds to penalty that
increases as time passes and is thus represented by function x (ti; pi) where ti
and pi are elapse time and priority of demand point di. As this problem has been
considered for emergency service allocation, all demand points should be
allocated to some facility or resource within some stipulated time limit beyond
which it may lose its purpose. Thus, penalty incurred by a demand point is
considered till that threshold value only. Thus, it is assumed that penalty
contribution by a demand point remains constant after a specified threshold
value. By exploiting the properties of time dependent penalties, a 4-
approximation primal-dual algorithm is proposed which is based on LP
framework and is the first constant-factor approximation algorithm for RAPTP.
Keyword: Resource allocation, Time dependent penalty, Primal-dual
approximation
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Garg, Deepak (2017). Rapidly converging solution for p-centers in nonconvex
regions. Turkish Journal of Electrical Engineering & Computer Sciences, 25,
2424-2433.
Abstract: This paper aims to locate p resources in a nonconvex demand plane
having n demand points. The objective of the location problem is to find the
location for these p resources so that the distance from each of n demand points
to its nearest resource is minimized, thus simulating a p-center problem. We
employ various geometrical structures for solving this location problem. The
suggested approach is also capable of ending the optimal value of p so that all
demand points have at least one resource at a distance Δ, where Δ is the
maximum permissible distance for emergency services. Finally, an
implementation of the proposed approach is presented, and it is observed that the
suggested approach rapidly converges towards the optimal location.
Keyword: Facility location, P-center, Convex polygon, Geodesic distance,
Garg, Deepak (2018). Analysis of students' ratings of teaching quality to
understand the role of gender and socio-economic diversity in higher
education. IEEE Transactions on Education, 61(4), 319-327.
Abstract: This paper contributes to the literature by confirming the existence,
in gender and socio-economic diversified higher educational environments, of
differential evaluation ratings given by students to their teachers. Background:
Women and low socio-economic classes have historically been under-
represented, both as students and teachers. Various policies and measures are
being put in place internationally to raise their standing, equity, and success as
they progress in their careers. To be effective, the aftereffects of these policies
must be investigated and understood. Research Questions: This paper
addressed the question of whether gender and socio-economic differences, in
both teachers and students, affect students’ opinion of their teachers in higher
education, across a number of disciplines. Methodology: The research analyzed
the differentials in students’ ratings of their teachers in five disciplines in the
field of education. Data was drawn from student responses to the surveys
conducted in a large Indian university at the end of each course unit. The
survey questions elicit their perceptions of teaching quality in the disciplines of
civil engineering, electrical engineering, computer science engineering,
mathematics, humanities and social sciences. This paper analyzes 112 919 and
16 354 complete sets of student ratings, to study the gender and socio-
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economic diversity-based effects respectively. Statistical multivariate and
univariate general linear models were used to derive the relevant results and
graphs. Findings: The study reveals the existence of socio-economic status bias,
gender-typical behavior, gender-atypical behavior, and same-gender and cross-
gender biases; these resulted in differential ratings in the disciplines examined.
Index Terms—Engineering education, gender, higher
Keyword: Engineering education, gender, higher education, socio-economic
status, teaching evaluations
Garg, Deepak (2018). Dynamizing Dijkstra: A solution to dynamic shortest
path problem through retroactive priority queue. Journal of King Saud
University - Computer and Information Sciences, S1319-1578(17), 30382-8.
Abstract: Dynamic shortest path algorithms are the ones which are used to
accommodate the online sequence of update operations to the underlying graph
topology and facilitate the subsequent query operations. Many solutions exist
for the different versions of the problem, all of which identify the set of vertices
whose shortest paths may be affected by the changes and then update their
shortest paths according to the update sequence. In this paper, we are
dynamizing the Dijkstra algorithm which helps to efficiently solve the dynamic
single source shortest path problem. Dynamization is achieved by using the
retroactive priority queue data structure. Retroactive data structure identifies the
set of affected vertices step by step and thus help to accommodate the changes
in least number of computations. So, with a suitable dynamic graph
representation and the use of retroactive priority queue, we have proposed
algorithm to dynamize Dijkstra algorithm giving solution of dynamic single
source shortest path problem with complexity O (nlg m) for the update time.
We have performed experimental analysis by comparing the performance of the
proposed algorithm with other algorithms. Our experimental results indicate
that the proposed algorithm has better performance in terms of time and
memory usage.
Keyword: Data Structure; Algorithms; Dynamic Shortest Path; Retroactive
Data Structure
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Garg, Deepak (2018). Extended suffix array construction using Lyndon
factors. Sadhana-Academy Proceedings in Engineering Sciences, 43(133), 3-
9.
Abstract: In this paper, we are extending the novel approach of incremental
suffix array construction using Lyndon factorization to the construction of
extended suffix array where extended suffix array is the suffix array along with
the corresponding longest common prefix (LCP) array. Main motive behind
the incremental and simultaneous construction of suffix array and LCP array is
that both involve in calculating the order information by considering the
common prefixes of the suffixes. As local suffixes once sorted have the same
sorted order when these are merged with sorted suffixes of another Lyndon
factor. So, merging of Lyndon factors is simply merging of two sorted lists of
suffixes of these Lyndon factors. Also, the two sorted orders coincide thus
making the merging of Lyndon factors a simple merging of two sorted lists of
suffixes. Incremental LCP construction simultaneously saves a lot of
computation and hence time. The proposed approach has quadratic run time
and the disk working space requirement is O (n). Experiments also show the
performance gain of our approach in terms of time over the existing method of
incremental construction.
Keyword: Computer science; Data structure, Suffix array; Lyndon factors;
Longest common prefix
Devottam Gaurav, Ph.D. Student , Department of CSE
Gaurav, Devottam (2018). An Outline on Big Data and Big Data Analytics.
Proceedings - IEEE 2018 International Conference on Advances in
Computing, Communication Control and Networking (pp. 74-79).
Abstract: With the rapid advancements in technological applications have led
to the flooding of data from various sources like web, social network data,
business data, medical records, etc. over the preceding years. As compared to
traditional data, big data reveals a unique characteristic from its three V's
which means big data is unstructured. In this era, the emerging trend requires
the involvement of advanced data analysis, acquisition and management
techniques to mine and collect appropriate data in a structured way. In this
paper, we describe the definitions and the challenges of big data systems.
Next, a systematic framework decomposes the architecture of big data systems
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into four stages like data generation, data acquisition, data storage and data
analytics. These stages form the basis of big data value chain. Finally, some
solutions are discussed to tackle the challenges of big data and future attention
is required for big data systems.
Keyword: Big Data, Social Networking, Real-time systems, Sensors
Gaurav, Devottam (2019). Detection of false positive situation in review
mining. Advances in Intelligent Systems and Computing (pp. 90083-90).
Abstract: As the Internet is evolving at a steeper rate, reviews related to a
product have become a vital data which help users to make informed decisions.
Users are totally dependent upon those reviews given by customers with the
experience they felt and makers depend on these user-generated reviews to
apprehend the sentiments of users related to a product. Henceforth, it is
mandatory for both makers and users to create a portal where customers can
peruse all the reviews in a comprehensive manner in a less amount of time.
Considering this, a predictive model is developed that detects false positive
reviews from original reviews and ratings are calculated to judge how these fake
reviews create confusion in the mind of customers.
Keyword: False positive, Naïve Bayes, K-NN, Decision tree
Dr. Gaurav Singal, Assistant Professor, Department of CSE
Singal, Gaurav (2018). Smart Vehicles for Traffic Management and Systems
Using Cloud Computing, Chapter 8. Vehicular Cloud Computing for Traffic
Management and Systems (pp. 178-199). IGI Global.
Abstract: A vehicular ad hoc network (VANET) is the network of mobile
devices as well as stationary objects that can communicate with each other.
This technology comprises of both vehicle-to-vehicle (V2V) and vehicle to-
infrastructure (V2I) data transmission links. At present, vehicular mobility
framework has a lot of limitations, which includes lack of real-time operations,
frequent disconnects due to dynamic-restricted topology, tracking vehicle that
break rules, lane-changes, exceed speed-limit, etc. These characteristics call for
a new type of high class of protocol. This chapter presents a survey report on
“smart traffic control” system that incorporates traffic-related parameters to
further augment the control and management of vehicular movements on the
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roadways. This can support efficient management of traffic in the city, and
cops can communicate with each other, get real-time, accurate, status update of
the traffic, track the vehicular movements, etc. In addition, jam control
mechanism can be placed on heavy traffic days to optimize the routes. This
system introduces artificial intelligence (AI) that can optimize deployed of
cops and find alternate routes for the driver to reach the destination address
without much fuel consumption.
Keyword: Vehicular Ad Hoc Network, Vehicular Movements
Singal, Gaurav (2017). Detailed analysis of footprint geometry for person
identification. Proceedings - 13th International Conference on Signal-Image
Technology and Internet-Based Systems (pp. 229-236).
Abstract: in this article we propose a novel biometric identification method
using Footprint. A paper scanner was used to obtain images to uniquely identify
the person. 312 footprint images from 78 persons (2 samples each foot) were
analyzed, leading to the conclusion that footprints could also be used to identify
human. Physiological and behavioral biometric characteristics make it a great
alternative to computational intensive algorithms like fingerprint, palm print,
retina or iris scan, and face. Foot biometric is also a great alternative. In spite of
having minutia features (considered totally unique and already tested in
fingerprint) it also has geometric features like hand geometry which give
satisfactory results in recognition. We have computed province, major axis,
minor axis, eccentricity in one approach, where a foot is divided into 15 equal
sized boxes in another shape-based algorithm. This article also examines the
texture features of the foot. It could be applied at those places where people
inherently remove their shoes, such as holy places (temples and mosque). They
remove shoes at famous monuments such as The Taj Mahal, India from the
perspective of hygiene and preservation. Usually, these places are with a strong
foot fall and high-risk security due to the chaotic crowd. It could also be
employed in newborn authentication and identification. Uniqueness of minutiae
footprint in newborns has been already proved
Keyword: Footprint, Biometrics, Geometry feature, Dynamic time warp,
Principal component analysis, Newborn identification
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Singal, Gaurav (2019). A Travel Aid for Visually Impaired: R-Cane. In Wang
G., El Saddik A., Lai X., Martinez Perez G. & Choo KK. (Eds.), Smart City and
Informatization. iSCI 2019. Communications in Computer and Information
Science, 1122 (pp. 404-417).
Abstract: An Electronic Travel Aid (ETA) has become a necessity for visually
impaired to provide them proper guidance and assistance in their daily routine.
As the number of blind persons are gradually increasing, there is a dire need of
an effective and low-cost solution for assisting them in their daily tasks. This
paper presents a cane called R-Cane which is an ETA for the visually impaired
and is capable of detecting obstacles in front direction using sonar sensor and
alerts the user by informing whether the obstacle is within the range of one
meter. In R-Cane, tensor flow object-detection API has been used for object
recognition. It makes the user aware about the nature of objects by providing
them voice-based output through blue tooth earphones. Raspberry Pi has been
used for processing and Pi camera has been used to capture frames for object
recognition. Further, we have implemented four models based on Single Shot
Multi box Detector (SSD) for object detection. The experimental analysis shows
that out of the four models, the average F1 score for all the classes is highest for
SSD_Mobilenet_v1 _Ppn_oco model.
Keyword: Electronic travel aids, Assistive technology
Singal, Gaurav (2019). Automatic Parallelization of C Code Using OpenMP.
Communications in Computer and Information Science (pp. 985298-309).
Abstract: Automatic parallelization is necessary for all system. Every person
wants the program to execute as soon as possible. Now Days, programmer want
to get run faster the sequential program. Automatic parallelization is the greatest
challenge in now days. Parallelization implies converting the sequential code to
parallel code to getting better utilization of multi-core processor. In
parallelization, multi-core uses the memory in sharing mode or massage passing.
Now day’s programmers don’t want to take extra overheads of parallelization
because they want it from the compiler that’s called automatic parallelization. Its
main reason is to free the programmers from manual parallelization process. The
conversion of a program into parallelize form is very complex work due to
program analysis and an unknown value of the variable during compile time. The
main reason of conversion is execution time of program due to loops, so the most
challenging task is to parallelize the loops and run it on multi-core by breaking
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the loop iterations. In parallelization process, the compiler must have to check
the dependent between loop statements that they are independent of each other.
If they are dependent or effect the other statement by running the statement in
parallel, so it does not convert it. After checking the dependency, test converts it
into parallelization by using OpenMP API. We add some line of OpenMP for
enabling parallelization in the loop.
Keyword: OpenMP, Automatic parallelization, Data dependency, C
Programming, Lex and Yacc, Language
Singal, Gaurav (2019). DDOS Attack Detection & Prevention in SDN using
OpenFlow Statistics. 9th International Conference on Advanced Computing (pp.
148-153).
Abstract: Software defined Network is a network defined by software, which is
one of the important features which makes the legacy old networks to be flexible
for dynamic configuration and so can cater to today’s dynamic application
requirement. It is a programmable network, but it is prone to different type of
attacks due to its centralized architecture. The author provided a solution to
detect and prevent Distributed Denial of service attack in the paper. Mini net [5]
which is a popular emulator for Software defined Network is used. We followed
the approach in which collection of the traffic statistics from the various
switches is done. After collection we calculated the packet rate and bandwidth
which shoots up to high values when attack take place. The abrupt increase
detects the attack which is then prevented by changing the forwarding logic of
the host nodes to drop the packets instead of forwarding. After this, no more
packets will be forwarded and then we also delete the forwarding rule in the
flow table. Hence, we are finding out the change in packet rate and bandwidth to
detect the attack and to prevent the attack we modify the forwarding logic of the
switch flow table to drop the packets coming from malicious host instead of
forwarding it.
Keyword: SDN, Mininet
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Singal, Gaurav (2019). FCNN-LDA: A faster convolution neural network
model for leaf disease identification on apple's leaf dataset. Proceedings of 2019
International Conference on Information and Communication Technology and
Systems (pp. 246).
Abstract: Fruits are common items bought by every household. They are
delicious to eat and rich in nourishment. However, they may also adversely
affect health if the fruits are from a diseased tree/plant. Moreover, Farmers may
also loose lot of amount of profit if their plants get affected by some disease. In
this article, the main objective/goal is to develop a convolution neural network-
based approach to identify the disease in apple fruit. The data for experiment has
been taken from Plant Village. In the proposed work, a convolution neural
network model has been developed to identify the disease in apple and it consists
of three convolution layer, three max pooling layers followed by two densely
connected layers. This model was formed after testing with varying number of
convolution layers from 2 to 6 and found that 3 layers was giving best accuracy.
For the result comparison purpose, the traditional machine learning algorithms
are also executed on the same dataset. Along with traditional machine learning
approaches, the famous pre-trained CNN models i.e. VGG16 and InceptionV3
are also executed. The experiments results show the efficacy of proposed
algorithm over pre-trained models and traditional machine learning approach in
terms of accuracy, computational time, specificity, F1 score and AUC-ROC
curve. The proposed model achieves the state-of-the-art accuracy of 99%.
Moreover, the proposed model requires only 20% of the space as compared to
pre-trained model with inference time less than 1 second as pre-trained models
require minimum 30 second.
Keyword: Convolution neural network, Deep learning
Singal, Gaurav (2019). Identification of Dog Breeds Using Deep Learning. 9th
International Conference on Advanced Computing (pp. 194-199).
Abstract: In this forecourt competition, we are provided a stringently mongrel
division of ImageNet in order to exercise fine-grained image cataloguing. The
dataset contains images of dogs of different breeds. Deep Learning is a technique
by which a computer program learns statistical patterns within the data that will
enable it to recognize or help us to distinguish between the different breeds of
dogs. The model trains itself on the different features based on the images
present and represent the data numerically, organizing the data in space. Initially,
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the image is divided into numerous lattices and a training batch size is set
accordingly, then an algorithm is used to split and combine the descriptors, and
the channel information of the image is extracted as the input of the
convolutional neural network and finally, we design a convolutional neural
network based to identify the dog species.
Keyword: Convolutional neural network, Fast AI, Keras library, Image
classification
Singal, Gaurav (2019). MIRA: Moment Invariability Analysis of Footprint
Features. Proceedings of the 8th International Advance Computing Conference
(pp. 196-201).
Abstract: Person authentication using footprint is still an abandoned field even
though it has physiological and behavioral both types of available features due
to unavailability of dataset. To examine the credibility of footprint we have
collected the footprint dataset. This dataset collection is done in 2 phases. 1) We
have collected the 2 footprint samples of each foot from 110 persons and 2) We
have collected the 5-footprint sample of each foot from 80 people. The paper
scanner is used for the data collection and whole footprint is captured. The
collected samples are taken at different orientations and position, sometimes
scanner is not aligned and creates noise. To overcome these problems a footprint
image requires extensive preprocessing. To make any image invariant to
translation and rotation, we use Hu’s 7 moment invariant features. It can
efficiently check that an input image belongs to a particular person or not even
after translation, scaling and rotation. The probability of translation and scaling
is very less in footprint, but slight rotation in foot image is noticeable, which
could result in different geometry features for same person. This technique is not
suitable for the authentication, but it can surely reduce the sample space by
rejecting the samples. If the difference of 3rd order moment invariant value of
two samples is more than the decided threshold, then samples surely does not
belong to the same person. This reduced sample size could be used further in
authentication. It reduces the time complexity and computation cost. We tested
it on 1320 images with the FMR of 4.52% and FNMR of 5.18%. It leads us to
the conclusion that 3rd order of moment is enough to make any image rotation
invariant.
Keyword: Footprint, Biometrics, Moment invariant
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Singal, Gaurav (2019). Person Identification using Autonomous Drone through
Resource Constraint Devices. 2019 6th International Conference on Internet of
Things: Systems, Management and Security (pp. 124-129).
Abstract: Detecting a specific person from the crowd using drone along with
some resource constraint device is a major concern which we are discussing in
the paper. Combining the advanced algorithms and some smart hardware
material, we will be finding a way to search for a missing individual in a crowd
or at some location. We can also search for a person at a specific location by
setting our aerial vehicle to fly autonomously and search for the required person.
This will help us to cover areas which cannot be reached by humans easily. The
flying robot helps to solve real-time problems and come up with some new and
more advanced ways to search for the missing ones with more ease, as advanced
technological methods are applied, the probability of getting accurate results
increases axiomatically. The drone can fly fully autonomously and search or
capture videos/photos of the required location. Location commands could be
given using PC, mobile and with the help of IoT, using Raspberry Pi.
Keyword: Arduino APM, Altitude hold, Autonomous Drone, Face Detection
Singal, Gaurav (2019). Pitfree: Pot-holes detection on Indian Roads using
Mobile Sensors. Proceedings of the 8th International Advance Computing
Conference (pp. 185-190).
Abstract: Potholes on road will make transportation slower and costly. India
has a big network of roads to connect the villages and cities, the authority
persons cannot travel across the region for identification of holes. As per
advancement in machine learning in recent time, we can use this technology for
the identification and patching the potholes. As per the recent survey around
400millions, people have a smartphone in India. We can use smartphone sensors
(such as Accelerometer and gyroscope) to identify the potholes on road and GPS
for the location of the pit. The major task of this problem is to capture the data
and annotation. We have developed an android app for capturing the value of
displacement while travelling on road. We have applied different classification
algorithms to sensor raw data. SVM is the most suitable classification technique
for this problem. The android app will sound an alarm when a pothole is
detected.
Keyword: Machine Learning, Mobile Sensors, Road safety
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Singal, Gaurav (2019). UAVs Reliable Transmission for Multicast Protocols in
FANETs. 2019 6th International Conference on Internet of Things: Systems,
Management and Security (pp. 130-135).
Abstract: Communication in the sky” is a trend because the increment of
Unmanned Aerial Vehicles (UAVs) use in wireless communications. UAVs
have diverse applications in civil and military domains. Swarm of UAV system
is able to combinedly finish the operations more reliably and financial more than
single UAV. UAV system has rapidly changing topology due to high mobility
devices. Currently, Mobile Ad hoc networks (MANETs) routing is used for
communication in UAV networks, the standards for communication system in
Flying Ad hoc Networks is yet to be developed. UAV system streaming
information needs protocol with high bandwidth, high mobility, varying link
stability and high energy consumption compare to ad hoc networks. It leads to
abruptly breaking communication in between UAV-to-UAV and UAV-to-
ground. In this paper, we discuss the link stability issues in UAV
communication systems. Link stability estimation is required for reliable
communication in between end-to-end flying nodes. We have simulated the
MANETs protocol for reliable communication in flying ad hoc networks. We
evaluate the performance of Flying Ad hoc networks (FANETs) communication
model based on multiple performance metrics, and also suggested deployment
scenarios on EXata/Cyber 2.0 to analyse the network performance.
Keyword: Protocols in FANETs, UAVs Reliable
Singal, Gaurav (2017). Multi-constraints link stable multicast routing protocol
in MANETs. Ad Hoc Networks, 63, 115–128.
Abstract: In MANETs, real-time multimedia applications make Quality of
Service (QoS) support, a crucial issue regarding terms of increased throughput,
reduced jitter, and available bandwidth. Most of the existing routing protocols
focus on straight forward hop-count metric and are less adaptable to densely
distributed and highly mobile networks. Therefore, Multicast communication
with QoS in densely populated highly dynamic network an exciting research
challenge. The objective of the present paper is to introduce a QoS aware
routing metric that determines a reliable forwarding node based on Link
Stability cost Function (LSF). A mesh of Multicast routes between Multicast
source and destinations has been established using nodes with a maximum LSF.
The principle theme underlying our protocol is optimum contention count that
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can be estimated with the help of received signal strength. The proposed protocol
comprises the following stages 1) Calculation of Link Stability Factor (2)
Determination of maximum LSF value (3) Pruning adjacent nodes (4) Creation
of a mesh consisting of more stable forwarding nodes (5) Creation of a mobile
network in which no node remains isolated, as well as nodes, face lesser
contention. Our proposed protocol has been demonstrated on an existing mesh-
based Multicast routing protocols, ODMRP. Simulations are carried out on
Exata/Cyber simulator, and obtained results are compared with that of ODMRP.
The comparative analysis reveals that our protocol is more efficient in contrast to
ODMRP, LSMRP, and MMRNS, regarding performance parameters like Packet
Delivery Ratio (PDR), Average End-to-End Latency and Average Route
Lifetime. Also, we have analysed the impact of minimum and maximum
contention count on PDR and delay
Keyword: MANETs, Link stability
Dr. Hiren Kumar Thakkar, Department of CSE
Thakkar, Hiren Kumar (2019). On the Design of Supervised Binary
Classifiers for Malware Detection Using Portable Executable Files. 2019 IEEE
9th International Conference on Advanced Computing (IACC) (pp. 141-146).
Tiruchirappalli, India.
Abstract: Executable files such as .exe, .bat, .msi etc. are used to install the
software in Windows-based machines. However, downloading these files from
untrusted sources may have a chance of having maliciousness. Moreover, these
executables are intelligently modified by the anomalous user to bypass antivirus
definitions. In this paper, we propose a method to detect malicious executables
by analyzing Portable Executable (PE) files extracted from executable files. We
trained a supervised binary classifier using features extracted from the PE files
of normal and malicious executables. We experimented our method on a large
publicly available dataset and reported more than 95% of classification accuracy.
Keywords: Machine Learning, Malware Analysis, Feature Extraction, Portable
Executable.
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Dr. Indrajeet Gupta, Assistant Professor, Department of CSE
Gupta, Indrajeet (2019). An Energy Efficient Algorithm for Workflow
Scheduling in IaaS Cloud. Journal of Grid Computing, 1-20.
Abstract: Energy efficient workflow scheduling is the demand of the present
time’s computing platforms such as an infrastructure-as-a-service (IaaS) cloud.
An appreciable amount of energy can be saved if a dynamic voltage scaling
(DVS) enabled environment is considered. But it is important to decrease make
span of a schedule as well, so that it may not extend beyond the deadline
specified by the cloud user. In this paper, we propose a workflow scheduling
algorithm which is inspired from hybrid chemical reaction optimization (HCRO)
algorithm. The proposed scheme is shown to be energy efficient. Apart from
this, it is also shown to minimize make span. We refer the proposed approach as
energy efficient workflow scheduling (EEWS) algorithm. The EEWS is
introduced with a novel measure to determine the amount of energy which can
be conserved by considering a DVS-enabled environment. Through simulations
on a variety of scientific workflow applications, we demonstrate that the
proposed scheme performs better than the existing algorithms such as HCRO
and V. Singh · P. K. Jana Department of Computer Science & Engineering,
Indian Institute of Technology (ISM), Dhanbad 826004, India e-mail:
[email protected] Prasanta K. Jana e-mail: [email protected] I.
Gupta ( ) Department of Computer Science Engineering, Bennett University,
Greater Noida, 201310, India e-mail: [email protected] multiple
priority queues genetic algorithm (MPQGA) in terms of various performance
metrics including make span and the amount of energy conserved. The
significance of the proposed algorithm is also judged through the analysis of
variance (ANOVA) test and its subsequent LSD analysis.
Keyword: Workflow scheduling, Energy conservation
Gupta, Indrajeet (2019). Mortality Prediction using Machine Learning
Techniques: Comparative Analysis. 9th International Conference on Advanced
Computing (pp. 230-234).
Abstract: In recent past, data mining, artificial intelligence, and machine
learning have gained enormous attention to improve hospital performance. In
some hospitals, medical personals want to improve their statists by decreasing
the number of patients dying in the hospital. The research is focused on the
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mortality prediction of measurable outcomes, including the risk of
complications & length of hospital stay. The duration spent in the hospital of the
patient plays an important role both for patients & healthcare providers,
influenced by numerous factors. LOS (length of stay) in critical care has great
importance, both to the patient experience as well as the cost of care and is
influenced by the complex environmental factors of the Hospitals. LOS is a
parameter that is used to identify the extremity of illness & health-related
resource utilization. This paper provides the improved prediction rate that a
patient survives or dies in the range of length of stay in the hospital. It also
anchors the analytical methods for the length of stay and mortality prediction.
Keyword: Machine Learning Algorithm, Feature Scaling
Dr. Jai Prakash Gupta, Professor, Department of CSE
Gupta, Jai Prakash (2017). Integration scheme of network coding and address
bit vector in wireless network to acquire more reliability. International Journal
of Applied Engineering Research, 12(22), 12701-12706.
Abstract: Network Coding (NC) is affirmed to be power and transmission
capacity proficient procedure, in light of the less number of transmitted packets
over the system. The proposed situation in this paper applies the upsides of NC
over wireless network to acquire more reliability even in case of increase in loss
of un-coded packets. Network coding uses the XOR operator to code overheard
packets. Our algorithm uses bit addresses to where every node is distinguished
by bit value ‘1’ in an address bit vector. Distinguishing packets and processing
the network coding of packets can be effectively done utilizing address bit
vectors. This algorithm also acknowledges redundancy with total no. of coded
packets sent with respect to actual no. of nodes present in the system
Keyword: Network Coding, Relay Nodes, Wireless Networks
Dr. Kishore Kanand Biswas, Professor, Department of CSE
Biswas, Kanad Kishore (2017). Feature Selection using Autoencoders.
International Conference on Machine Learning and Data Science (pp. 56-60).
Abstract: Feature selection plays a vital role in improving the generalization
accuracy in many classification tasks where datasets are high-dimensional. In
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feature selection, a minimal subset of relevant as well as non-redundant features
is selected. Autoencoders are used to represent the datasets from original feature
space to a reduced and more informative feature space. In this paper, we propose
a novel approach for feature selection by traversing back the autoencoders
through more prob able links. Experiments on five publicly available large
datasets show that our approach gives significant gains in accuracy over most of
the state-of-the-art feature selection methods
Keyword: Feature Selection, Autoencoders
Biswas, Kanad Kishore (2017). Recurrent neural network-based action
recognition from 3D skeleton data. 13th International Conference on Signal-
Image Technology & Internet-Based Systems. SITIS (pp. 339-345).
Abstract: In this paper, we present an approach for human action recognition
from 3D skeleton data. The proposed method utilizes Recurrent Neural Network
(RNN) and Long Short-Term Memory (LSTM) to learn the temporal dependency
between joints’ positions. The proposed architecture uses a hierarchical scheme
for aggregating the learned responses of various RNN units. We demonstrate the
effectiveness of using only a few joints as opposed to all the available joints’
position for action recognition. The proposed approach is evaluated on well-
known publicly available MSR-Action3D dataset.
Keyword: Neural Network, 3D Skeleton Data
Biswas, Kanad Kishore (2018). Human Activity Recognition Using Local
Motion Histogram. Int. Conf. on Next Generation Computing Technologies
(pp. 908-917).
Abstract: Human activity recognition is an important problem in computer
vision area with multiple challenges. In this paper we have proposed a method
for human activity recognition based on local estimation of motion in RGB
videos. Background subtraction method is used on pair of consecutive frames
to determine local motion, and for a small bundle of frames, the maximum
magnitude of motion at a pixel is saved to create a Projected Motion Matrix.
The matrix is segmented into horizontal and vertical strips and binned
histograms of each strip serve as feature descriptors. We have used these
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descriptors in a random forest-based classification scheme and evaluated the
performance on JHMDB, a publicly available human action RGB dataset
Keyword: Human Activity, Histogram, Motion Projection Matrix, Random
Forest
Biswas, Kanad Kishore (2018). Trajectory based Integrated Features for
Action Classification from Depth Data. NCVPRIG, National Conf. Vision,
Pattern Recognition, Image Processing and Graphics (pp. 54-65).
Abstract: We present an approach for Human Action Recognition based on
amalgamation of features from depth maps and body-joint data. This Integrated
feature set consists of depth features based on gradient orientation and motion
energy, in addition to features from 3D- skeleton data capturing its statistical
details. Feature selection is carried out to extract a relevant set of features for
action recognition. The resultant set of features are evaluated using SVM
classifier. We validate our proposed method on various benchmark datasets for
Action Recognition such as MSR-Daily Activity and UT-Kinect dataset.
Keyword: Trajectory, Depth Data, 3D- skeleton data
Biswas, Kanad Kishore (2019). A Robust Framework for Effective Human
Activity Analysis. International Conference on Innovative Computing and
Communications. Lecture Notes in Networks and Systems, vol 56 (pp. 56331-
337). Singapore.
Abstract: Human activity analysis is an interesting and challenging problem
among the researchers of computer vision area. The applications of human
activity analysis are monitoring and surveillance. There are various surveillance
approaches available in literature for witnessing activities, events or persons. In
this paper, we present a robust framework for human action analysis. In the
proposed framework we extract the features named generate motion image from
frames deviation. Random forest is used as a feature classifier. To show the
robustness of proposed framework we analyse and classify the publicly available
HMDB dataset. The average accuracy of classification is 46.83% achieved.
Keyword: Computer vision, Robust Framework
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Biswas, Kanad Kishore (2019). Grape Disease Identification Using
Convolution Neural Network. 2019 23rd International Computer Science and
Engineering Conference (pp. 224-229).
Abstract: In this paper, we present a CNN model to identify the disease in
grapes plant in early stage by analyzing the leaf images. The model is illustrated
on publicly available Plant Village dataset and the performance compared with
traditional machine learning models and pre-trained convolution neural network
models. The performance of algorithms has been compared on various
evaluation metrics i.e. accuracy, precision recall, running time of model, storage
space and AUC-RoC. From the experimental results, it has been observed that
the performance of proposed model is better than traditional machine learning
algorithms as well as pre-trained models by achieving an accuracy of 99%.
Biswas, Kanad Kishore (2018). A recursive PSO scheme for gene selection in
microarray data. Applied Soft Computing, 71, 213-225.
Abstract: In DNA microarray datasets, the number of genes is very large,
typically in thousands while the number of samples are in hundreds. This
raises the issue of generalization in the classification process. Gene selection
plays a significant role in improving the accuracy. In this paper, we have
proposed a recursive particle swarm optimization approach (PSO) for gene
selection. The proposed method refines the feature (gene) space from a very
coarse level to a fine-grained one at each recursive step of the algorithm
without degrading the accuracy. In addition, we have integrated various filter
based ranking methods with the proposed recursive PSO approach. We also
propose to use linear support vector machine weight vector to serve as initial
gene pool selection. We evaluate our method on five publicly available
benchmark micro array data sets. Our approach selects only a small number of
genes while yielding substantia improvements in accuracy over state-of-the-art
evolutionary methods
Keyword: Particles warm optimization, Support Vector Machine (SVM),
Gene Selection (GS),
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Biswas, Kanad Kishore (2019). Intuitionistic Fuzzy Logit Model of Discrete
Choice. IEEE Transactions on Emerging Topics in Computational Intelligence,
3(1), 85-89.
Abstract: In the real-world multicriteria decision making, the evaluations of the
various criteria are often vague (or not crisp). The existing choice models are
difficult to apply in such situations. In this paper, we introduce an intuitionistic
fuzzy variant of the multinomial logit model, whichhelpsustosuggestadecision-
maker’slikelychoiceswithvagueevaluations. The applicability of the proposed
model is shown through a real multicriteria decision-making application.
Keyword: Decision analysis, Intuitionistic fuzzy
Biswas, Kanad Kishore (2019). Real time human action recognition from RGB
clips using local motion histogram. Intelligent Decision Technologies, 13(2), 219
-228.
Abstract: This paper proposes a method to human action recognition from RGB
video clips. The method is based on capturing the local motion information from
smaller size video clips. Local motion information is captured through
accumulation of motion in different shape and size of patches of spatial domain.
The motion information is then transformed to motion histograms. Further, all
the histograms are concatenated to make the proposed feature vector. Bagging
ensemble technique, in form of random forest, is used for classification. The idea
is further extended to real time human action recognition mechanism. To show
the robustness and efficiency of proposed algorithm, it is performed on publicly
available human action datasets Joint-annotated Human Motion Data Base
(JHMDB) [29] and University of Rzeszow (UR) Fall detection dataset [19]. The
results are also compared with other state of art methods.
Keyword: Human action recognition, Random forest, Real time fall detection
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Kanak Manjari, Research Scholar, Department of CSE
Manjari, Kanak (2019). A Travel Aid for Visually Impaired: R-Cane. In Wang
G., El Saddik A., Lai X., Martinez Perez G. & Choo KK. (Eds.), Smart City and
Informatization. iSCI 2019. Communications in Computer and Information
Science, 1122 (pp. 404-417).
Abstract: An Electronic Travel Aid (ETA) has become a necessity for visually
impaired to provide them proper guidance and assistance in their daily routine.
As the number of blind persons are gradually increasing, there is a dire need of
an effective and low-cost solution for assisting them in their daily tasks. This
paper presents a cane called R-Cane which is an ETA for the visually impaired
and is capable of detecting obstacles in front direction using sonar sensor and
alerts the user by informing whether the obstacle is within the range of one
meter. In R-Cane, tensor flow object-detection API has been used for object
recognition. It makes the user aware about the nature of objects by providing
them voice-based output through blue tooth earphones. Raspberry Pi has been
used for processing and Pi camera has been used to capture frames for object
recognition. Further, we have implemented four models based on Single Shot
Multi box Detector (SSD) for object detection. The experimental analysis shows
that out of the four models, the average F1 score for all the classes is highest for
SSD_Mobilenet_v1 _Ppn_oco model.
Keyword: Electronic travel aids, Assistive technology
Karan Singh, B.Tech Student, Department of CSE
Singh, Karan (2019). An interoperable and secure e-wallet architecture based
on digital ledger technology using blockchain. 2018 International Conference on
Computing, Power and Communication Technologies (pp. 165-169).
Abstract: Governments and financial Institutions worldwide are in deep need to
reduce the payment, clearing and settlement cycles of various transactions
thereby eliminating operational and financial inefficiencies and mitigating risks.
Various consortia have been formed in order to lay the foundation stones,
standards to create industry acceptable solutions. Seamless transactions and
information sharing between different banks and financial institutions is still a
distant dream. This paper presents a novel architecture to seamlessly integrate e-
wallets of different banks and participating institutions using blockchains that
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shall act as a foundation of Digital ledger technology (DLT) for financial sector
in India. A swarm-based peer-to-peer network is designed for the proposed e-
wallet system. The proposed solution shall minimize the load on the Core
Banking Solution of the banks thus reducing the load on the servers at the data
centers.
Keyword: E-wallet, Blockchain, Digital ledger technology, Core banking
solution, Peer to peer network
Dr. Kuldeep Chaurasia, Assistant Professor, Department of CSE
Chaurasia, Kuldeep (2019). Integration of Lidar Data in Topographical Feature
Extraction from Very High-Resolution Aerial Imagery. In Jain K., Khoshelham
K., Zhu X. & Tiwari A. (Eds), Proceedings of UASG 2019. UASG 2019. Lecture
Notes in Civil Engineering (pp. 39-44), vol 51. Cham: Springer.
Abstract: Geospatial technology has been demonstrated as a reliable and
efficient tool for monitoring of the land cover pattern for vast geographical areas.
Although, the demand for the various thematic layers including landcover maps
at finer scale has got increased for various applications such as urban studies,
forestry and disaster management. In this paper, the utilization of LiDAR data for
urban land cover classification of aerial imagery has been discussed. The study
area has been classified into seven land-use/cover classes based on the textural,
and spectral features using object-oriented classification approach. The
applicability of various texture measures based on the gray level co-occurrence
matrix along with the effect of varying pixel window has also been discussed.
The classification results indicate that homogeneity texture image generated
using 3 * 3 window size is best suitable for extraction of various topographical
objects. The suitability of the various textural features has also been investigated.
The LiDAR data has been found best suitable for the identification of small
objects such as buildings, trees and vehicles over aerial imagery. The overall
accuracy of the classification has been obtained as 87.21% with the kappa
coefficient of 0.84. The outcome of the study can be effectively utilized for
disaster management applications such as evacuation planning, damage
assessment, and post-flood recovery effort.
Keyword: Remote sensing, Feature extraction
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Chaurasia, Kuldeep (2019). Predicting Damage to Buildings Caused by
Earthquakes Using Machine Learning Techniques. 9th International Conference
on Advanced Computing (pp. 82-87).
Abstract: This paper presents the level of damage prediction to buildings caused
by Gorkha Earthquake in Nepal using machine learning techniques. The
predictions have been made based on mathematically calculated eight tectonic
indicators and past vibrational activity records. In this research the objective is to
predict earthquake damage on existing data set of seismic activity by using
machine learning techniques. In this study, two well-known approaches of
machine learning viz. Neural Network (NN) and Random Forest (RF) have been
implemented and optimal parameters for accurate prediction are investigated.
The analysis reveals that Random forest method has outperformed the neural
network approach for building damage prediction. The F1 score using the
random forest classification has been obtained as 74.32%.
Keyword: Neural Network, Random Forest
Dr. Madhushi Verma, Assistant Professor, Department of CSE
Verma, Madhushi (2019). A New Fuzzy Algorithm for Delay Constrained
Minimum Energy Transmission of Sensor Array Data in Wireless Sensor
Networks. Proceedings of the 2019 5th International Conference on Robotics
and Artificial Intelligence (pp.87-93).
Abstract: An array of diverse sensors interfaced with a small computing device
that has a short-range radio transceiver forms a wireless sensor or node. A
network of such devices forms a wireless sensor network (WSN). Today WSNs
find application in various fields like battlefield awareness, environmental
monitoring, agriculture etc. In this paper, we propose an algorithm that can
determine a minimum energy consumption path that also maintains smallest
possible end-to-end delay. This will ensure that the data generated by sensor
arrays reach their destination in shortest time while consuming minimum energy.
The network parameters involved i.e. energy and delay are imprecise in nature,
therefore to tackle the prevailing uncertainty, we represent them as trapezoidal
fuzzy numbers (TFN) leading to the constrained fuzzy shortest path problem
(CFSPP). To solve this problem, we use CoC ranking and demonstrate the
effectiveness of the proposed method by simulation analysis. The method
proposed in this paper can be integrated with any energy aware WSN protocol.
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Verma, Madhushi (2019). A Travel Aid for Visually Impaired: R-Cane. In
Wang G., El Saddik A., Lai X., Martinez Perez G. & Choo KK. (Eds.), Smart
City and Informatization. iSCI 2019. Communications in Computer and
Information Science, 1122 (pp. 404-417).
Abstract: An Electronic Travel Aid (ETA) has become a necessity for visually
impaired to provide them proper guidance and assistance in their daily routine.
As the number of blind persons are gradually increasing, there is a dire need of
an effective and low-cost solution for assisting them in their daily tasks. This
paper presents a cane called R-Cane which is an ETA for the visually impaired
and is capable of detecting obstacles in front direction using sonar sensor and
alerts the user by informing whether the obstacle is within the range of one
meter. In R-Cane, tensor flow object-detection API has been used for object
recognition. It makes the user aware about the nature of objects by providing
them voice-based output through blue tooth earphones. Raspberry Pi has been
used for processing and Pi camera has been used to capture frames for object
recognition. Further, we have implemented four models based on Single Shot
Multi box Detector (SSD) for object detection. The experimental analysis shows
that out of the four models, the average F1 score for all the classes is highest for
SSD_Mobilenet_v1 _Ppn_oco model.
Keyword: Electronic travel aids, Assistive technology
Verma, Madhushi (2019). Breast Cancer Diagnosis using Simultaneous Feature
Selection and Classification: A Genetic Programming Approach. Proceedings of
the 2018 IEEE Symposium Series on Computational Intelligence (pp. 2186-
2192).
Abstract: Breast cancer is the most prevalent type of cancer found in women
worldwide. It is becoming a leading cause of death among women in the whole
world. Early detection and effective treatment of this disease is the only rescue
to reduce breast cancer mortality. Because of the effective classification and high
diagnostic capability expert systems are gaining popularity in this field. But the
problem with machine learning algorithms is that if redundant and irrelevant
features are available in the dataset then they are not being able to achieve
desired performance. Therefore, in this paper, a simultaneous feature selection
and classification technique using Genetic Programming (GPsfsc) is proposed
for breast cancer diagnosis. To demonstrate our results, we had taken the
Wisconsin Breast Cancer (WBC) and Wisconsin Diagnostic Breast Cancer
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(WDBC) databases from UCI Machine Learning repository and compared the
classification accuracy, sensitivity, specificity, confusion matrix, and Mann
Whitney test results of GONN with classical multi-tree GP algorithm for feature
selection (GPmtfs). The experimental results on WBC and WDBC datasets show
that the proposed method produces better classification accuracy with reduced
features. Therefore, our proposed method is of great significance and can serve
as first-rate clinical tool for the detection of breast cancer.
Keyword: Breast Cancer, Genetic Programming
Verma, Madhushi (2017). Flower Pollination Algorithm for the Orienteering
Problem. International Journal of Scientific Research in Computer Science,
Engineering and Information Technology, 2(7), 226-231.
Abstract: The orienteering problem is an NP-Hard combinatorial optimization
problem where the aim is to determine a Hamiltonian path that connects the
stated source and target and includes a subset of the vertex set V such that the
total collected score is maximized within the given time bound (T_max).
Orienteering problem finds application in logistics, transportation, tourism
industry etc. We have proposed an algorithm FPA_OP that can be implemented
on complete graphs and its performance has been evaluated using standard
benchmarks. Also, the results thus obtained have been compared against the
latest heuristic for OP i.e. GRASP and it has been shown that for larger T_max,
FPA_OP outperforms GRASP. Therefore, the decision maker can implement
FPA_OP if he is willing to achieve a larger total collected score at the cost of
time delay.
Keyword: Flower pollination algorithm, Metaheuristic, Orienteering problem,
NP-Hard problems.
Verma, Madhushi (2017). Intuitionistic Fuzzy Orienteering Problem and Its
Work-Depth Analysis. International Journal of Scientific Research in Computer
Science, Engineering and Information Technology, 2(7), 302-310.
Abstract: Orienteering is an NP-hard problem that originated from a water sport
where a player is required to visit a set of control points connecting the source
and the destination, collect the maximum possible rewards or scores associated
with the control points and arrive at the destination within the time bound. It
finds its application in the tourism industry, telecommunication networks and
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other computational problems where things like human behavior and hesitancy
of the decision maker must be considered. To tackle the uncertainty involved in
the parameters we represent them using trapezoidal intuitionistic fuzzy numbers
(TIFN) resulting in intuitionistic fuzzy orienteering problem (IFOP). A
technique based on max-min formulation is presented to deal with IFOP using a
new method for ranking TIFNs. Also, a work-depth analysis for the parallel
version of IFOP is presented to show that IFOP is work-preserving and can be
implemented on a multiprocessor model like PRAM to obtain the solution for
large instances efficiently.
Keyword: Centroid of Centroids, Fuzzy Optimization, Intuitionistic Fuzzy
Orienteering Problem, Orienteering Problem, Trapezoidal Intuitionistic Fuzzy
Number
Dr. Mayank Swarnkar, Assistant Professor, Department of CSE
Swarnkar, Mayank (2019). On the Design of Supervised Binary Classifiers for
Malware Detection Using Portable Executable Files. 2019 IEEE 9th
International Conference on Advanced Computing (IACC) (pp. 141-146).
Tiruchirappalli, India.
Abstract: Executable files such as .exe, .bat, .msi etc. are used to install the
software in Windows-based machines. However, downloading these files from
untrusted sources may have a chance of having maliciousness. Moreover, these
executables are intelligently modified by the anomalous user to bypass antivirus
definitions. In this paper, we propose a method to detect malicious executables
by analyzing Portable Executable (PE) files extracted from executable files. We
trained a supervised binary classifier using features extracted from the PE files
of normal and malicious executables. We experimented our method on a large
publicly available dataset and reported more than 95% of classification
accuracy.
Keywords: Machine Learning, Malware Analysis, Feature Extraction, Portable
Executable.
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Mohit Agarwal, Research Scholar, Department of CSE
Agarwal, Mohit 2019). A Convolution Neural Network based approach to
detect the disease in Corn Crop. 2019 IEEE 9th International Conference on
Advanced Computing (IACC) (pp. 176-181). Tiruchirappalli, India.
Abstract: The agricultural production is affected by the climate changes i.e.
humidity, rain, extremes of temperature etc. Additionally, abiotic stresses are
causative element to the etiology of disease as well as pest on crops. The
production of the crops can be improved by diagnosis as well as detecting the
accurate disease on time or in early stage. Moreover, it is very difficult for
accurately detecting and treatment based on the technique which used in disease
and insect pests diagnosis. Few researchers have made efforts on predicting
disease as well as pest crops using machine learning algorithms. Therefore, this
paper presents disease identification in corn crops by analyzing the leaves in the
very early stage. We have used PlantVillage dataset for experiments and
analysis. The validity of the results has been cheeked on various performance
metrics such as precision, accuracy, recall, storage space, running time of the
model and AUC-RoC. The obtained results shows the proposed technique
outperform in comparison with the traditional machine learning algorithms.
Developed model is able to achieve the accuracy of 94%.
Keywords: Convolution neural network, Traditional machine learning methods,
Pre-trained models, Augmentation.
Agarwal, Mohit (2019). FCNN-LDA: A faster convolution neural network
model for leaf disease identification on apple's leaf dataset. Proceedings of 2019
International Conference on Information and Communication Technology and
Systems (pp. 246).
Abstract: Fruits are common items bought by every household. They are
delicious to eat and rich in nourishment. However, they may also adversely affect
health if the fruits are from a diseased tree/plant. Moreover, Farmers may also
loose lot of amount of profit if their plants get affected by some disease. In this
article, the main objective/goal is to develop a convolution neural network-based
approach to identify the disease in apple fruit. The data for experiment has been
taken from Plant Village. In the proposed work, a convolution neural network
model has been developed to identify the disease in apple and it consists of three
convolution layer, three max pooling layers followed by two densely connected
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layers. This model was formed after testing with varying number of convolution
layers from 2 to 6 and found that 3 layers was giving best accuracy. For the
result comparison purpose, the traditional machine learning algorithms are also
executed on the same dataset. Along with traditional machine learning
approaches, the famous pre-trained CNN models i.e. VGG16 and InceptionV3
are also executed. The experiments results show the efficacy of proposed
algorithm over pre-trained models and traditional machine learning approach in
terms of accuracy, computational time, specificity, F1 score and AUC-ROC
curve. The proposed model achieves the state-of-the-art accuracy of 99%.
Moreover, the proposed model requires only 20% of the space as compared to
pre-trained model with inference time less than 1 second as pre-trained models
require minimum 30 second.
Keyword: Convolution neural network, Deep learning
Agarwal, Mohit (2019). Grape Disease Identification Using Convolution Neural
Network. 2019 23rd International Computer Science and Engineering
Conference (pp. 224-229).
Abstract: In this paper, we present a CNN model to identify the disease in
grapes plant in early stage by analyzing the leaf images. The model is illustrated
on publicly available Plant Village dataset and the performance compared with
traditional machine learning models and pre-trained convolution neural network
models. The performance of algorithms has been compared on various
evaluation metrics i.e. accuracy, precision recall, running time of model, storage
space and AUC-RoC. From the experimental results, it has been observed that
the performance of proposed model is better than traditional machine learning
algorithms as well as pre-trained models by achieving an accuracy of 99%.
Agarwal, Mohit, (2019). Profit or Loss: A Long Short Term Memory based
model for the Prediction of share price of DLF group in India. 2019 IEEE 9th
International Conference on Advanced Computing (IACC) (pp. 120-124).
Tiruchirappalli, India.
Abstract: Presently, the prediction of share is a challenging issue for the
research community as share market is a chaotic place. The reason behind it,
there are several factors such as government policies, international market,
weather, performance of company. In this article, a model has been developed
using long short-term memory (LSTM) to predict the share price of DLF group.
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Moreover, for the experimental purpose the data of DLF group has been taken
from yahoo financial services in the time duration of 2008 to 2018 and the
recurrent neural network (RNN) model has been trained using data ranging from
2008 to 2017. This RNN based model has been tested on the data of year 2018.
For the performance comparison purpose, other linear regression algorithms i.e.
k-nn regression, lasso regression, XGboost etc has been executed and the
proposed algorithm outperforms with 2.6% root mean square error.
Keywords: Prediction Model, Recurrent Neural Network, Long Short-Term
Memory (LSTM), Mean Square Error (MSE).
Nisha Ahuja, Research Scholar, Department of CSE
Ahuja, Nisha (2019). DDOS Attack Detection & Prevention in SDN using
OpenFlow Statistics. 9th International Conference on Advanced Computing (pp.
148-153).
Abstract: Software defined Network is a network defined by software, which is
one of the important features which makes the legacy old networks to be flexible
for dynamic configuration and so can cater to today’s dynamic application
requirement. It is a programmable network, but it is prone to different type of
attacks due to its centralized architecture. The author provided a solution to
detect and prevent Distributed Denial of service attack in the paper. Mini net [5]
which is a popular emulator for Software defined Network is used. We followed
the approach in which collection of the traffic statistics from the various switches
is done. After collection we calculated the packet rate and bandwidth which
shoots up to high values when attack take place. The abrupt increase detects the
attack which is then prevented by changing the forwarding logic of the host
nodes to drop the packets instead of forwarding. After this, no more packets will
be forwarded and then we also delete the forwarding rule in the flow table.
Hence, we are finding out the change in packet rate and bandwidth to detect the
attack and to prevent the attack we modify the forwarding logic of the switch
flow table to drop the packets coming from malicious host instead of forwarding
it.
Keyword: SDN, Mininet
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Dr. Pratik Narang, Assistant Professor, Department of CSE
Narang, Pratik (2017). Temperature Compensation of ISFET Based pH Sensor
Using Artificial Neural Networks. IEEE Regional Symposium on Micro and
Nanoelectronics (pp. 155-158).
Abstract: This paper presents a new Machine Learning based temperature
compensation technique for Ion -Sensitive Field-Effect Transistor (ISFET). The
circuit models for various electronic devices like MOSFET are available in
commercial Technology Computer Aided Design (TCAD) tools such as LT-
SPICE but no built-in model exists for ISFET. Considering SiO2 as the sensing
film an ISFET circuit model was created in LT-SPICE and simulations were
carried out to obtain characteristic curves for SiO2 based ISFET. A Machine
Learning (ML) model was trained using the data collected from the simulations
performed using the ISFET macro model in the read-out circuitry. The
simulations were performed at various temperatures and the temperature drift
behavior of ISFET was fed into the ML model. Constant pH (predicted by the
system) curves were obtained when the device is tested for various pH (7 and 10)
solutions at different ambient temperatures.
Keyword: ISFET, SPICE, Machine Learning, Artificial Neural Networks,
Micromodel
Narang, Pratik (2017). Mix design factors and strength prediction of metakaolin
-based geopolymer. Ceramics International, 11433-11441.
Abstract: Geopolymer is a promising alternative binder to Portland cement.
However, the importance of mix design parameters affecting the mechanical
properties of geopolymer has yet to be quantitatively assessed. This work
evaluates the significance of the four common mix design parameters, namely Si/
Al (molar ratio), water/solids (mass ratio), Al/Na (molar ratio) and H2O/Na2O
(molar ratio), in determining compressive strength of metakaolin-based
geopolymers through experiments and statistical analyses. In addition, machine
learning based classifiers were engaged for strength predictions. Results showed
that Si/Al ratio is the most significant parameter followed by Al/Na ratio. Unlike
ordinary Portland cement system, water/solids ratio is not the chief factor
governing strength of metakaolin-based geopolymers. Machine learning-based
classifiers were able to predict the compressive strength with high precision. The
strength predictions can potentially guide preliminary mix proportioning of
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metakaolin-based geopolymers to achieve required strength grade without going
through tedious (trial and error) mix formulation.
Keyword: Electron microscopy, Porosity, Strength, Attribute evaluation
Dr. R. Shashidhara, Assistant Professor, Department of CSE
Shashidhara, R. (2019). A novel DNA based password authentication system
for global roaming in resource-limited mobile environments. Multimedia Tools
and Applications, 2185-2212.
Abstract: Mobile environments are highly vulnerable to security threats and
pose a great challenge for the wireless and mobile networks being used today.
Because the mode of a wireless channel is open, these networks do not carry any
inherent security and hence are more prone to attacks. Therefore, designing a
secure and robust protocol for authentication in a global mobile network is
always a challenging. In these networks, it is crucial to provide authentication to
establish a secure communication between the Mobile User (MU), Foreign
Agent (FA) and Home Agent (HA). In order to secure communication among
these entities, a number of authentication protocols have been proposed. The
main security flaw of the existing authentication protocols is that attackers have
the ability to impersonate a legal user at any time. Moreover, the existing
authentication protocols in the literature are exposed to various kind of
cryptographic attacks. Besides, the authentication protocols require larger key
length and more computation overhead. To remedy these weaknesses in mobility
networks, DNA (Deoxyribonucleic Acid) based authentication scheme using
Hyper Elliptic Curve Cryptosystem (HECC) is introduced. It offers greater
security and allows a MU, FA and HA to establish a secure communication
channel, in order to exchange the sensitive information over the radio link. The
proposed system derive benefit from HECC, which is smaller in terms of key
size, more computational efficiency. In addition, the security strength of this
authentication system is validated through widely accepted security verification
tool called ProVerif. Further, the performance analysis shows that the DNA
based authentication system using HECC is secure and practically
implementable in the resource-constrained mobility nodes.
Keyword: Authentication, DNA cryptography
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Rachna Sable, Research Scholar, Department of CSE
Sable, Rachna (2019). Empirical Study on Stock Market Prediction Using
Machine Learning. 019 International Conference on Advances in Computing,
Communication and Control (ICAC3) (pp. 1-5). Mumbai, India.
Abstract: Stock market prediction is a crucial and challenging task due to its
nonlinear, evolutionary, complex, and dynamic nature. Research on the stock
market has been an important issue for researchers in recent years. Companies
invest in trading the stock market. Predicting the stock market trend accurately
will minimize the risk and bring a maximum amount of profit for all the
stakeholders. During the last several years, a lot of studies have been done to
predict stock market trends using Traditional, Machine learning and deep
learning techniques. This survey will assist the readers & researchers in selecting
algorithms that can be useful for a predicting the stock market. A survey of
various algorithms and its parameters for stock market prediction is presented in
this paper.
Keywords: Stock market prediction, machine learning, SVM, ARIMA, DAN2
Naïve Bayes, KNN, RBF.
Rajita Shukla, Department of CSE
Shukla, Rajita (2018). Hindi Wordnet for Language Teaching: Experiences
and Lessons Learnt. 9th Global WordNet Conference (pp. 1-10).
Abstract: This paper reports the work-related making Hindi Wordnet1
available as a digital resource for language learning and teaching, and the
experiences and lessons that were learnt during the process. The language data
of the Hindi Wordnet has been suitably modified and enhanced to make it into a
language learning aid. This aid is based on modern pedagogical axioms and is
aligned to the learning objectives of the syllabi of the school education in India.
To make it into a comprehensive language tool, grammatical information has
also been encoded, as far as these can be marked on the lexical items. The
delivery of information is multi-layered, multi-sensor Yandi’s available across
multiple digital platforms. The front end has been designed to offer an eye-
catching user-friendly interface which is suitable for learners starting from age
six onward. Preliminary testing of the tool has been done and it has been
modified as per the feedbacks that were received. Above all, the entire exercise
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has offered gainful insights into learning based on associative networks and
how knowledge based on such networks can be made available to modern
learners.
Keyword: Hindi Wordnet, Language Teaching
Shukla, Rajita (2018). Public Apologies in India - Semantics, Sentiment and
Emotion. 9th Global WordNet Conference (pp. 1-17).
Abstract: This paper reports a pilot study related to public apologies in India,
with reference to certain keywords found in them. The study is of importance
as the choice of lexical items holds importance which goes beyond the surface
meaning of the words. The analysis of the lexical items has been done using
interlinked digital lexical resources which, in future, can lend this study to
computational tasks related to opinion mining, sentiment analysis and
document classification. The study attempts an in-depth psycholinguistic
analysis of whether the apology conveys a sincerity of intent or is it a mere
ritualistic exercise to control and repair damage.
Keyword: SentiWordNet, WordNet-Affect, Corporate apologies, Corporate
communication
Dr. Rishav Singh, Assistant Professor, Department of CSE
Singh, Rishav (2018). Animal Biometrics: Techniques and Applications.
Springer.
Abstract: This book presents state-of-the-art methodologies and a
comprehensive introduction to the recognition and representation of species and
individual animals based on their physiological and phenotypic appearances,
biometric characteristics, and morphological image patterns. It provides in-depth
coverage of this emerging area, with an emphasis on the design and analysis
techniques used in visual animal biometrics-based recognition systems.
The book offers a comprehensive introduction to visual animal biometrics,
addressing a range of recent advances and practices like sensing, feature
extraction, feature selection and representation, matching, indexing of feature
sets, and animal biometrics-based multimodal systems. It provides authoritative
information on all the major concepts, as well as highly specific topics, e.g. the
identification of cattle based on their muzzle point image pattern and face
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images to prevent false insurance claims, or the monitoring and registration of
animals based on their biometric features.
As such, the book provides a sound platform for understanding the Visual
Animal Biometrics paradigm, a vital catalyst for researchers in the field, and a
valuable guide for professionals. In addition, it can help both private and public
organizations adapt and enhance their classical animal recognition systems.
Singh, Rishav (2019). Identifying tiny faces in thermal images using transfer
learning. Journal of Ambient Intelligence and Humanized Computing, 1-10.
Abstract: This article focuses on identifying tiny faces in thermal images using
transfer learning. Although the issue of identifying faces in images is not new,
the problem of tiny face identification is a recently identified research area.
Indeed challenging, however, in this paper, we take the problem one step ahead
and focus on recognizing tiny faces in thermal images. To do that, we use the
paradigm of transfer learning. We use the famous residual network to extract the
features in the target domain. Subsequently, with this model as a reference point,
we then retrain it in the target domain of thermal images. Through testing
performed in Terravic datasets, we have found that the method outperforms
existing methods in literature to identify tiny faces in thermal images.
Keyword: Machine learning, Biometrics, Tiny faces, Thermal images
Rishi Dutt Sharma, Department of CSE
Sharma, Rishi Dutt (2018). Orthogonal-state-based and semi-quantum
protocols for quantum private comparison in noisy environment. International
Journal of Quantum Information, 16(5), 1850047.
Abstract: Private comparison is a primitive for many cryptographic tasks, and
recently several schemes for the quantum private comparison (QPC) have been
proposed, where two users can compare the equality of their secrets with the
help of a semi-honest third party (TP) without knowing each other's secret and
without disclosing the same to the TP. In the existing schemes, secrecy is
obtained by using conjugate coding, and considering all participants as
quantum users who can perform measurement(s) and/or create states in basis
other than computational basis. In contrast, here we propose two new protocols
for QPC, first of which does not use conjugate coding (uses orthogonal states
only) and the second one allows the users other than TP to be classical whose
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activities are restricted to either reflecting a quantum state or measuring it in
computational basis. Further, the performance of the protocols is evaluated
under various noise models.
Keyword: Quantum private comparison, Secure multiparty computation,
Socialist millionaire problem, Quantum cryptography
Dr. Rohan Sharma, Assistant Professor, Department of CSE
Sharma, Rohan (2019). Self-Organized Corona Graphs: A Deterministic
Complex Network Model with Hierarchical Structure. Advances in Complex
Systems, 22(6), 1950019.
Abstract: In this paper, we propose a self-organization mechanism for newly
appeared nodes during the formation of corona graphs that define a hierarchical
pattern in the resulting corona graphs, and we call it self-organized corona
graphs (SoCG). We show that the degree distribution of SoCG follows power-
law in its tail with power-law exponent approximately 2. We also show that the
diameter is less equal to 4 for SoCG defined by any seed graph and for certain
seed graphs, the diameter remains constant during its formation. We derive
lower bounds of clustering coefficients of SoCG defined by certain seed graphs.
Thus, the proposed SoCG can be considered as a growing network generative
model which is defined by using the corona graphs and a self-organization
process such that the resulting graphs are scale-free small-world highly clustered
growing networks. The SoCG defined by a seed graph can also be considered as
a network with a desired motif which is the seed graph itself.
Keyword: Corona graphs; Self-organization; Degree distribution; Diameter;
Clustering coefficient
Rohit Kumar Kaliyar, Research Scholar, Department of CSE
Kaliyar, Rohit Kumar (2019). Misinformation Detection on Online Social
Media-A Survey. 10th International Conference on Computing,
Communication and Networking Technologies (ICCCNT) (pp. 1-6). Kanpur,
India.
Abstract: In the current social media era, people are sharing some pieces of
information about different types among each other using various social media
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platforms. This type of available information is not authentic and reliable so-
called misinformation. Nowadays, Detection of misinformation regained large
attention among researchers. Misinformation detection is related to the text
classification problem and connects the content level of news articles with the
detection analysis based on some Machine Learning algorithms like Naive
Bayes and Support Vector Machine etc. In the specific domain analysis,
labeled data based on reliability domain is rarely available. Previous research
work relied on news articles collected from so-called reputable and suspicious
websites and labeled accordingly. We leverage fact-checking websites to
collect individually-labeled news articles with regard to the veracity of their
content and use this data to test the cross-domain generalization of a classifier
trained on bigger text collections but labeled according to source reputation.
This paper provides a comprehensive survey of misinformation and its
detection using various social media platforms. Future directions for research
have also been also discussed in this research article. Therefore collecting well-
balanced and carefully-assessed training data is a priority for developing robust
misinformation detection systems in the future.
Kaliyar, Rohit Kumar (2018). An Outline on Big Data and Big Data
Analytics. Proceedings - IEEE 2018 International Conference on Advances in
Computing, Communication Control and Networking (pp. 74-79).
Abstract: With the rapid advancements in technological applications have led
to the flooding of data from various sources like web, social network data,
business data, medical records, etc. over the preceding years. As compared to
traditional data, big data reveals a unique characteristic from its three V's
which means big data is unstructured. In this era, the emerging trend requires
the involvement of advanced data analysis, acquisition and management
techniques to mine and collect appropriate data in a structured way. In this
paper, we describe the definitions and the challenges of big data systems. Next,
a systematic framework decomposes the architecture of big data systems into
four stages like data generation, data acquisition, data storage and data
analytics. These stages form the basis of big data value chain. Finally, some
solutions are discussed to tackle the challenges of big data and future attention
is required for big data systems.
Keyword: Big Data, Social Networking, Real-time systems, Sensors
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Kaliyar, Rohit Kumar (2018). Fake News Detection Using A Deep Neural
Network. 2018 4th International Conference on Computing Communication
and Automation (pp. 1-7).
Abstract: The process of obtaining news from social media is like double
edged weapon. On one hand, it is easy to access, less time consuming, user
friendly, easily conveyable socially relevant news, possibility for obtaining
various perspective of a single news and is being updated in every minute. On
other hand, news is being manipulated by various networking sites based on
private opinions or interest. Fake news is misinformation or manipulated news
that is spread across the social media with an intention to damage a person,
agency and organization. Due to the dissemination of fake news, there is need
for computational methods to detect them. Fake news detection aims to help
users to expose varieties of fabricated news. We can decide whether the news is
solid or forged based on formerly witnessed fake or real news. We can use
various models to access deceptive news in social media. Our contribution is
bifold. First, we must introduce the datasets which contain both fake and real
news and conduct various experiments to organize fake news detector. We use
Natural Language Processing, Machine learning and deep learning techniques
to classify the datasets. We yield a comprehensive audit of detecting fake news
by including fake news categorization, existing algorithms from machine
learning techniques.
Keyword: Fake News, Natural Language Processing, Opinion Mining,
Machine Learning
Kaliyar, Rohit Kumar (2019). Detection of false positive situation in review
mining. Advances in Intelligent Systems and Computing (pp. 90083-90).
Abstract: As the Internet is evolving at a steeper rate, reviews related to a
product have become a vital data which help users to make informed decisions.
Users are totally dependent upon those reviews given by customers with the
experience they felt and makers depend on these user-generated reviews to
apprehend the sentiments of users related to a product. Henceforth, it is
mandatory for both makers and users to create a portal where customers can
peruse all the reviews in a comprehensive manner in a less amount of time.
Considering this, a predictive model is developed that detects false positive
reviews from original reviews and ratings are calculated to judge how these fake
reviews create confusion in the mind of customers.
Keyword: False positive, Naïve Bayes, K-NN, Decision tree
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Kaliyar, Rohit Kumar (2019). FCNN-LDA: A faster convolution neural
network model for leaf disease identification on apple's leaf dataset. Proceedings
of 2019 International Conference on Information and Communication
Technology and Systems (pp. 246).
Abstract: Fruits are common items bought by every household. They are
delicious to eat and rich in nourishment. However, they may also adversely affect
health if the fruits are from a diseased tree/plant. Moreover, Farmers may also
loose lot of amount of profit if their plants get affected by some disease. In this
article, the main objective/goal is to develop a convolution neural network-based
approach to identify the disease in apple fruit. The data for experiment has been
taken from Plant Village. In the proposed work, a convolution neural network
model has been developed to identify the disease in apple and it consists of three
convolution layer, three max pooling layers followed by two densely connected
layers. This model was formed after testing with varying number of convolution
layers from 2 to 6 and found that 3 layers was giving best accuracy. For the result
comparison purpose, the traditional machine learning algorithms are also
executed on the same dataset. Along with traditional machine learning
approaches, the famous pre-trained CNN models i.e. VGG16 and InceptionV3
are also executed. The experiments results show the efficacy of proposed
algorithm over pre-trained models and traditional machine learning approach in
terms of accuracy, computational time, specificity, F1 score and AUC-ROC
curve. The proposed model achieves the state-of-the-art accuracy of 99%.
Moreover, the proposed model requires only 20% of the space as compared to
pre-trained model with inference time less than 1 second as pre-trained models
require minimum 30 second.
Keyword: Convolution neural network, Deep learning
Kaliyar, Rohit Kumar (2019). Multiclass Fake News Detection using Ensemble
Machine Learning. 2019 IEEE 9th International Conference on Advanced
Computing (pp. 103-107).
Abstract: Over the past few years, fake news and its influence have become a
growing cause of concern in terms of debate and public discussions. Due to the
availability of the Internet, a lot of user-generated content is produced across the
globe in a single day using various social media platforms. Nowadays, it has
become very easy to create fake news and propagate it worldwide within a short
period of time. Despite receiving significant attention in the research community,
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fake news detection did not improve significantly due to insufficient context-
specific news data. Most of the researchers have analysed the fake news problem
as a binary classification problem, but many more prediction classes exist. In
this research work, experiments have been conducted using a tree-based
Ensemble Machine Learning framework (Gradient Boosting) with optimized
parameters combining content and context level features for fake news
detection. Recently, adaptive boosting methods for classification problems have
been derived as gradient descent algorithms. This formulation justifies key
elements and parameters in the methods, which are chosen to optimize a single
common objective function. Experiments are conducted using a multi-class
dataset (FNC) and various machine learning models are used for classification.
Experimental results demonstrate the effectiveness of the ensemble framework
compared to existing benchmark results. Using the Gradient Boosting algorithm
(an ensemble machine learning framework), we achieved an accuracy of 86%
for multi-class classification of fake news having four classes.
Keywords: Fake News, Machine Learning, Deep Learning, Gradient Boosting.
Kaliyar, Rohit Kumar (2019). SMS Spam Filtering on Multiple Background
Datasets Using Machine Learning Techniques: A Novel Approach. Proceedings
of the 8th International Advance Computing Conference (pp. 59-65).
Abstract: Short Message Service (SMS) is one of the well-known and reliable
communication services in which a message sends electronically. In the current
era, the declining in the cost per SMS day by day by overall all the telecom
organizations in India has encouraged the extended utilization of SMS. This
ascent pulled in assailants, which have brought about SMS Spam problem. Spam
messages include advertisements, free services, promotions and marketing,
awards, etc. Individuals are utilizing the ubiquity of cell phone gadgets is
growing day by day as telecom giants give a vast variety of new and existing
services by reducing the cost of all services. Short Message Service (SMS) is
one of the broadly utilized communication services. Due to the high demand for
SMS service, it has prompted a growth in mobile phones attacks like SMS
Spam. In our proposed approach, we have presented a general model that can
distinguish and filter the spam messages utilizing some existing machine
learning classification algorithms. Our approach builds a generalized SMS spam-
filtering model, which can filter messages from various backgrounds (Singapore,
American, Indian English etc.). In our approach, preliminary results are
mentioned below based on Singapore and Indian English based publicly
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available datasets. Our approach showed promise to accomplish a high precision
utilizing Indian English SMS large datasets and others background’s datasets
also.
Keyword: Short Message Service (SMS), SMS Spam-filtering, Feature matrix,
Telecom organizations
Rupak Chakraborty, Assistant Professor, Department of CSE
Chakraborty, Rupak, (2019). Profit or Loss: A Long Short Term Memory
based model for the Prediction of share price of DLF group in India. 2019 IEEE
9th International Conference on Advanced Computing (IACC) (pp. 120-124).
Tiruchirappalli, India.
Abstract: Presently, the prediction of share is a challenging issue for the
research community as share market is a chaotic place. The reason behind it,
there are several factors such as government policies, international market,
weather, performance of company. In this article, a model has been developed
using long short-term memory (LSTM) to predict the share price of DLF group.
Moreover, for the experimental purpose the data of DLF group has been taken
from yahoo financial services in the time duration of 2008 to 2018 and the
recurrent neural network (RNN) model has been trained using data ranging from
2008 to 2017. This RNN based model has been tested on the data of year 2018.
For the performance comparison purpose, other linear regression algorithms i.e.
k-nn regression, lasso regression, XGboost etc has been executed and the
proposed algorithm outperforms with 2.6% root mean square error.
Keywords: Prediction Model, Recurrent Neural Network, Long Short-Term
Memory (LSTM), Mean Square Error (MSE).
Chakraborty, Rupak (2019). A hybrid privacy preserving scheme using
fingerprint detection in cloud environment. Ingenierie des Systemes
d'Information, 24(3), 343.
Abstract: Cloud computing provides a new paradigm of computing. It offers a
scalable, manageable and huge pool of resources that can be accessed by users
from anywhere anytime. It also ensures the integrity of data stored on the cloud.
But ensuring the confidentiality and integrity of sensitive information is still a
big challenge. To overcome this challenge, a hybrid two-phase security system
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for preserving the privacy of data on the cloud has been proposed. The hybrid
approach combines feature extraction and encryption techniques to enhance the
security of accessing data from the cloud. At first, the minutiae point has been
extracted from the biometric fingerprint, locally collected from the state
university in Northern India. The private key has been finalized by generating an
elliptic curve using the minutiae point for achieving better encryption of
fingerprint. The effectiveness of the approach has been tested in terms of
similarity score, False Matching Ratio (FMR), False Non-Matching Ratio
(FNMR) and recognition accuracy, when applied on the local fingerprint
database. The evidence of the outcomes suggests that the proposed technique
ensures relatively improved security and privacy of data in the cloud system as
compared to some recent state-of-art methods.
Keyword: Cloud computing, Security, Biometric, Fingerprint detection,
Minutiae points, Elliptic curve
Chakraborty, Rupak (2019). Hyper-spectral image segmentation using an
improved PSO aided with multilevel fuzzy entropy. Multimedia Tools and
Applications, 78(23), 34027.
Abstract: This paper proposes a novel histogram-based multi-level segmentation
scheme of hyperspectral images. In the proposed scheme an Improved Particle
Swarm Optimization (IPSO) algorithm is implemented as a nature-inspired
evolutionary algorithm to overcome the drawback of premature convergence and
hence getting stuck in local optima problem of PSO. The high dimension of PSO
is decomposed into several one-dimensional problems and premature
convergence is removed from each one-dimensional problem. This algorithm is
further extended for replacing the worst particles by the fittest particles,
determined by their fitness values. Multiple optimal threshold values have been
evaluated based on fuzzy entropy aided with the proposed algorithm. The
performance of the IPSO is compared statistically with other global optimization
algorithms namely Cuckoo Search (CS), Differential Evolution (DE), Firefly
(FF), Genetic Algorithm (GA), and PSO. The produced segmented output of
IPSO-fuzzy is then combined with the available ground truth values of image
classes to train a Support Vector Machine (SVM) classifier via the composite
kernel approach to improving the classification accuracy. This hybrid approach
(IPSO-SVM) is then applied to popular hyper-spectral imageries acquired by
AVRIS and ROSIS sensors. The final evaluated outcomes of the proposed
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scheme are also qualitatively compared to show its effectiveness over the other
state-of-art global optimizers.
Keyword: Improved particle swarm optimization (IPSO), Multilevel-
thresholding, Hyper-spectral imageries, Fuzzy entropy, Support vector machine
(SVM), Composite kernel
Dr. Samayyeer Singh, Assistant Professor, Department of CSE
Singh, Samayveer (2016). Reversible Data Hiding Scheme for LZW Codes
using LSB Flipping Strategy. AICTC'16 Proceedings of the International
Conference on Advances in Information Communication Technology &
Computing. ACM (pp. 1-5).
Abstract: This paper introduces a high capacity reversible data hiding scheme
which embeds the secret data into LZW codes. It firstly compresses the cover
media using LZW compression algorithm and then the output codes are used to
embed the secret data. It constructs a location map of the LZW codes before
embedding the secret data so that reversibility of the scheme is ensured. The
secret data is embedded into the LZW codes by either flipping their first LSB or
leaving them unchanged. Thus, the maximum change made to a code is ±1
which helps in achieving better compression ratio. This scheme is very simple
and has high hiding capacity. Experimentally, our scheme embeds more secret
data and achieves better compression ratio than the existing state of the art
schemes.
Keyword: Even pixel, Odd pixel, LZW, Data hiding, Codes
Singh, Samayveer (2018). A New Image Steganography Technique Based on
Pixel Intensity and Similarity in Secret Message. Proceedings - IEEE 2018
International Conference on Advances in Computing, Communication Control
and Networking (pp. 828-831).
Abstract: In this paper, we propose a new enhanced image steganography
scheme for color images. The proposed scheme is based on the pixel intensity
of the cover image and the similarity in secret message. It can hide the secret
text data into the color or gray scale images. In this scheme, we try to exploit
the characteristic of the secret data which is the closeness in its basic elements.
We firstly pre-process the secret data that is to be hidden; then the resultant
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secret data is embedded into the LSBs of the cover image according to intensity
values of the pixels in cover image. In pre-processing, we actually divide the
secret data into clusters in a sequential manner and then the basic information
about each cluster such as its size, its minimum value and the cluster itself are
embedded. The pre-processing reduces the size of the secret data significantly
which helps in improving the quality of the stego-image. The security of this
method also increases because of the pre-processing as the actual data is not
embedded.
Keyword: Steganography, Cluster Analysis, Difference-Value, PSNR
Singh, Samayveer (2019). An Efficient and Secure Authentication Scheme
using Markov Chain for Wireless Sensor Networks. Proceedings of the 8th
International Advance Computing Conference (pp. 33-38).
Abstract: Due to varied applications of wireless sensor networks (WSNs), data
is required by any user when and wherever they require. Usually, base station
gathers all information from the sensor and sends it periodically to the user. But
for real-time application, mutual authentication among the communicating nodes
is required. During user authentication base station checks that the user is
authorized to gather the collected information from the sensor node through an
insecure channel. In this paper, we propose an efficient authentication scheme
which provides anonymity of user in WSNs that uses Markov chain. The
Markov chain is a stochastic process that can be used for a system in which it
follows a chain of linked events, but next event depends only on the current state
of the system. Stationary limit distribution of matrix is created by the base
station to help the user to keep their password and identity safe. The security
analysis verifies that the proposed scheme is safe against various attacks like
forgery, parallel session attacks, user impersonation, etc.
Keyword: Wireless sensor network, Authentication, Smart card, Session key
Singh, Samayveer (2019). Anonymity Preserving Authentication and Key
Agreement Scheme for Wireless Sensor Networks. Communications in
Computer and Information Science (pp. 484–495).
Abstract: The main purpose of our paper is to design efficient smart card-based
authentication and session key agreement scheme for wireless sensor networks.
Our scheme uses registration phase for both user and sensor nodes. We analyse
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security and simulation results using AVISPA shows that our scheme is secure
against attacks.
Keyword: Wireless sensor network, Authentication
Singh, Samayveer (2019). Performance Investigation of Energy Efficient
HetSEP for Prolonging Lifetime in WSNs. Communications in Computer and
Information Science (pp. 496–509).
Abstract: In this work, we investigate the performance of heterogeneous stable
election protocol (HetSEP) for prolonging the network lifetime. An order-5
heterogeneous energy network model is proposed in this work that can defines
theorder-1, order-2, order-3, order-4, and order-5 heterogeneity. We consider the
SEP protocol to calculate the lifetime of the network and consequently describe
its accomplishments as HetSEP-1, HetSEP-2, HetSEP-3, HetSEP-4, and HetSEP
-5. The SEP protocol is HetSEP-1 in which all the sensor nodes have same
amount of energy. The HetSEP-2, HetSEP-3, HetSEP-4, and HetSEP-5 contain
two, three, four, and five orders of energy, respectively. The network lifetime
increases as increasing the order of heterogeneity. The HetSEP-2, HetSEP-3,
HetSEP-4, &HetSEP-5, prolong the life time of the network100.39%, 126.12%,
186.56%, & 285.67%, in respect to the increase the energy of the network by
65.0%, 72.58%, 107.10%, & 208.40% with respect to the HetSEP-1.
Keywords: Network lifetime, Heterogeneity.
Singh, Samayveer (2016). Energy Efficient Scheduling Protocols for
Heterogeneous WSNs. International Journal of Forensic Computer Science, 1, 8
-29.
Abstract: In this paper, we propose a 3-level heterogeneous network model for
WSNs to enhance the network lifetime, which is characterized by a single
parameter. Depending upon the value of the model parameter, it can describe 1-
level, 2-level, and 3-level heterogeneity. Our heterogeneous network model also
helps to select effective active sensor nodes for scheduling. We compute the
network lifetime by implementing two protocols for our network model, which
include ALBP and ADEEPS. The ALBP implementation for the existing 1-level,
2-level, and 3-level heterogeneous network models are denoted as ALBP-1,
ALBP-2, and ALBP-3, respectively, and for our proposed 3-level heterogeneous
network model, the ALBP implementations are denoted as het ALBP-1, het
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ALBP-2, and het ALBP-3, respectively. The naming convention for ADEEPS is
done in the same way. The hetALBP-3 provides maximum network lifetime
11.96% for linear energy model and 11.86% for quadratic energy model, then
that of the ALBP-3, without any increase in the network energy for 60M sensing
range and 25 number of targets. The hetADEEPS-3 increases the network
lifetime by 20.0% for linear energy model and 15.55% for quadratic energy
model, with respect to ADEEPS-3 protocol, without any increase in the network
energy for 60M sensing range and 25 number of targets.
Keyword: Heterogeneity, Network lifetime, Scheduling, Sensor nodes,
Adjustable sensing range
Singh, Samayveer (2017). An Improved Histogram-Shifting-Imitated reversible
data hiding based on HVS characteristics. Multimedia Tools and Applications,
13445-13457.
Abstract: In this paper, we propose a reversible data hiding scheme to hide a
secret message into a cover image by considering the characteristics of Human
Visual System (HVS) in order to improve the visual imperceptibility. The
human eyes are more sensitive to the changes in the low intensity pixels than the
higher intensity ones. Therefore, we divide the intensity levels (0–255) into four
groups: the first group contains 0–79 intensity level; second, third, and fourth
group contain, respectively, 80–151, 152–215, and 216–255 intensity levels. We
further divide first group into segments of size 2 elements, second, third, and
fourth group into 3, 4, and 5 elements sized segments, respectively. After
constructing the segments, we scan the image in raster order to identify the peak
points for each segment, which are used to embed the secret data. The secret
data is also divided into the four segments according to the identified peak
points per group. The first segment data is converted into base2 representation,
second, third and fourth segment secret data into 3, 4, and 5 base representation,
respectively. The first segment of secret data is embedded into the peak points
belonging to first group, second, third and fourth group secret data is embedded
into the peak points of second, third and fourth group, respectively. Thus, our
scheme makes least changes into the pixels belonging to the first group which
have least intensity values and most to the fourth group pixels which have
highest intensity values. Experimentally, our scheme provides better quality
stego image and hides more secret data than the other state of the art schemes.
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We also build a location map for all the peak points to ensure the reversibility of
the proposed scheme.
Keyword: Reversible data hiding, Human Visual System, Peak Points,
Embeddable pixel, PSNR
Singh, Samayveer (2017). Energy efficient heterogeneous DEEC protocol for
enhancing lifetime in WSNs. Engineering Science and Technology, an
International Journal, 20(1), 345-353.
Abstract: In this paper, we propose a 3-level heterogeneous network model for
WSNs to enhance the network lifetime, which is characterized by a single
parameter. Depending upon the value of the model parameter, it can describe 1-
level, 2-level, and 3-level heterogeneity. Our heterogeneous network model also
helps to select cluster heads and their respective cluster members by using
weighted election probability and threshold function. We compute the network
lifetime by implementing DEEC protocol for our network model. The DEEC
implementation for the existing 1-level, 2-level, and 3-level heterogeneous
network models are denoted as DEEC-1, DEEC-2, and DEEC-3, respectively,
and for our proposed 3-level heterogeneous network model, the DEEC
implementations are denoted as hetDEEC-1, hetDEEC-2, and hetDEEC-3,
respectively. The network lifetime in DEEC-3 and hetDEEC-3 increases by
154.17% and 182.67%, respectively by increasing the total network energy 100%
with respect to the original DEEC.
Keyword: Heterogeneity, Energy efficiency, Network lifetime, Election
probability, Threshold function
Singh, Samayveer (2017). Energy efficient multilevel network model for
heterogeneous WSNs. Engineering Science and Technology, an International
Journal, 20(1), 105-115.
Abstract: In this paper, we propose a multilevel heterogeneous network model
that is characterized by two types of parameters: primary and secondary
parameters. The primary parameter decides the level of heterogeneity and the
secondary parameters are decided according to the level of heterogeneity. This
model can describe a network in which the nodes can have up to nth level of
energy (n is a finite number) depending upon the parameter values. We evaluate
the performance of the HEED, a clustering protocol, using this model and name
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the resultant protocol as MLHEED (Multi Level HEED) protocol. For n level of
heterogeneity, this protocol is denoted by MLHEED-n. The numbers of nodes of
each type in any level of heterogeneity are determined by the secondary model
parameter. The MLHEED protocol (for all level heterogeneity) considers two
parameters for deciding the cluster heads, i.e., residual energy and node density.
In this work, we illustrate the network model up to six levels. Experimentally, as
the level of heterogeneity increases, the rate of energy dissipation decreases and
hence the nodes stay alive for longer time. The MLHEED-1, MLHEED-2,
MLHEED-3, MLHEED-4, MLHEED-5, and MLHEED-6 increase the network
lifetime by 73.05%, 143.40%, 213.17%, 267.90%, 348.60%, respectively, by
increasing the network energy as 40%, 57%, 68.5%, 78%, 84%, with respect to
the original HEED protocol.
Keyword: Multi level heterogeneity, Network lifetime Clustering, Number of
rounds
Singh, Samayveer (2017). hetDEEC: Heterogeneous DEEC Protocol for
Prolonging Lifetime in Wireless Sensor Networks. Journal of Information and
Optimization Sciences, 38(5), 699-720.
Abstract: In this paper, we propose a 3-level heterogeneous network model for
WSNs to enhance the network lifetime, which is characterized by a single
parameter. Depending upon the value of the model parameter, it can describe 1-
level, 2-level, and 3-level heterogeneity. Our heterogeneous network model also
helps to select cluster heads and their respective cluster members by using
weighted election probability and threshold function. We compute the network
lifetime by implementing DEEC protocol for our network model. The DEEC
implementation for the existing 1-level, 2-level, and 3-level heterogeneous
network models are denoted as DEEC-1, DEEC-2, and DEEC-3, respectively,
and for our proposed 3-level heterogeneous network model, the DEEC
implementations are denoted as hetDEEC-1, hetDEEC-2, and hetDEEC-3,
respectively. The network lifetime in DEEC-3 and hetDEEC-3 increases by
154.17% and 182.67%, respectively for increasing 100% in the network energies
with respect to the original DEEC.
Keyword: Heterogeneity, Energy efficiency Network lifetime, Election
probability, Threshold function
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Singh, Samayveer (2017). hetSEP: Heterogeneous SEP Protocol for Increasing
Lifetime in WSNs. Journal of Information and Optimization Sciences, 38(5), 721
-743.
Abstract: In this paper, we propose a 3-level heterogeneous network model for
WSNs to enhance the network lifetime, which is characterized by a single
parameter. Depending upon the value of the model parameter, it can describe 1-
level, 2-level, and 3-level heterogeneity. Our heterogeneous network model also
helps to select cluster heads and their respective cluster members by using
weighted election probability and threshold function. We compute the network
lifetime by implementing SEP protocol for our network model. The SEP
implementation for the existing 1-level, 2-level, and 3-level heterogeneous
network models are denoted as SEP-1, SEP-2, and SEP-3, respectively, and for
our proposed 3-level heterogeneous network model, the SEP implementations
are denoted as hetSEP-1, hetSEP-2, and hetSEP-3, respectively. In SEP-3 and
hetSEP-3 the values of the network lifetime increase by 164.18% and 192.80%,
respectively for increasing 100% in network energies as compared to the original
implementation of SEP.
Keyword: Heterogeneity, Network lifetime, Weighted election probability, SEP
Singh, Samayveer (2017). Recovery based high capacity reversible data hiding
scheme using even-odd embedding. Multimedia Tools and Applications, 15803-
15827.
Abstract: There have been discussed various data hiding methods which can
embed the secret data in an image. However, the image gets destroyed after
extraction of the secret data at the receiving end. Thus, there exists a need to
have data hiding methods which can recover the image after extraction of the
secret data. Such types of schemes are called reversible data hiding schemes
which are commonly used in sensitive military, legal, and medical applications.
The existing reversible data hiding schemes either provide good hiding capacity
but low quality stego-image or good quality stego-image but poor data hiding
capacity because the stego-image quality and the hiding capacity are
diametrically related metrics. To address this problem, we propose a high
capacity reversible data hiding scheme using recovery strategy. It hides the secret
data into a cover image in two phases. In the first phase, the cover image is
scanned in a specific scan order and constructs a location map in which even
valued pixels are denoted by ‘1’ and odd valued pixels by ‘0’. It embeds the
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secret data into every pixel of the image by changing its value at most by 1. The
second phase repeats the process of the first phase embedding so that some of the
pixels can be recovered to its original form as well as the secret data can further
be embedded. Experimentally, it is proved that the proposed scheme provides
good quality of stego-image and having the high data hiding capacity at the same
time. Further, it is able to maintain the image quality even when the secret data is
embedded in layers.
Keyword: Reversible data hiding, Recovery strategy, Location map, Stego-
image, Embedding layers
Singh, Samayveer (2018). A Reversible High Capacity Data Hiding Scheme
using Combinatorial Strategy. International Journal of Multimedia Intelligence
and Security, 10, 146.
Abstract: In this paper, we propose a new reversible high capacity data hiding
scheme using combinatorial strategy which has very less distortion while
hiding the secret data. It first builds a location map for the pixels of the cover
image and then identifies the embeddable pixels. It divides the image into pairs
of embeddable pixels and hides the secret data bits in each pair. The values of
the embeddable pixels are updated according to pre-specified rules. The pixel
values get changed at most by one and some of them may remain unchanged.
Thus, there are minor changes in pixel values, which helps our scheme to
achieve very good quality and with good hiding capacity. Furthermore, it is
very simple as it just increases or decreases the pixel values rather than
performing complex computations. The experimental results show that our
scheme is superior to the state-of-the-art schemes.
Keyword: Reversible data hiding, Embeddable pixels, combinatorial strategy,
Distortion, PSNR, Hiding capacity, Pixel mapping table, Secret data,
Singh, Samayveer (2019). A Proficient Node Deployment Mechanism Using
Adjustable Sensing Range in Wireless Sensor Networks. Iranian Journal of
Science and Technology-Transactions of Electrical Engineering, 43(1), 191–
199.
Abstract: In this paper, a proficient node deployment mechanism is proposed
which covers all the target points using adjustable sensing ranges in grid-based
wireless sensor networks. In the beginning, the sink and the target points are
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randomly deployed in a grid-based environment where locations are arbitrarily
selected. At first, the ants are positioned at the sink location (grid point) from
where the deployment of sensors starts. An ant can move in one of the four
possible directions, i.e., 1 (left); 2 (right); 3 (top); 4 (bottom) from the sink
location depending on the maximum number of uncovered target points. In case
there is no path to move forward, an existing sensor is selected as the next
location corresponding to that next sensor point where a deployed sensor can
cover maximum number of uncovered targets in one of the four possible
directions. Our method deploys minimum number of sensors to cover all the
targets with least number of iterations. It also provides full coverage and
connectivity with minimum deployment cost.
Keyword: Ant colony optimization, Target coverage, Connectivity, Network
lifetime
Dr. Seung-Hwa Chung, Associate Professor, Department of CSE
Chung S.H (2018). Pragmatic approach using OAuth mechanism for IoT
device authorization in cloud. Proceedings - IEEE 2018 International
Conference on Advances in Computing, Communication Control and
Networking (pp. 1-4).
Abstract: To address the problem of authorization that enables a third-party
service to access a resource server in a secured manner (a token-based
authorization without exposing user id and password), there has been research
called OAuth framework. The OAuth framework gives permission for
restricted access to a third-party entity in a token-based access control
mechanism. This framework is widely used as a de-facto standard. The
companies such as Google, Facebook, LinkedIn, and Microsoft are using the
OAuth mechanism to enable third-party services to access their resources in a
secured manner. However, the OAuth mechanism is operating on HTTP
(Hypertext Transfer Protocol) that assumes a server in the cloud, which adapts
the OAuth mechanism, will primarily operates using HTTP. The de-facto
standard protocol used by IoT (Internet of Things) devices is CoAP
(Constrained Application Protocol) that is designed to be used by a simple, in
other word limited, device. In the case of IoT cloud that interconnects IoT
devices and related applications mainly use CoAP over TCP (Transmission
Control Protocol). This paper describes the development of a pragmatic
approach to authorize an application accessing IoT devices using CoAP and
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inter-working with already deployed HTTP based authorization servers using
OAuth mechanism. The developed architecture using the proposed approach
has been evaluated using the real-world device, i.e. Samsung air conditioner,
with Samsung, Facebook and Github accounts. This work has become the open
source IoT cloud reference implementation of OCF (Open Connectivity
Foundation).
Keyword: Cloud computing, Servers, Internet of Things, Standards
Dr. Shivani Goel, Professor, Department of CSE
Goel, Shivani (2017). Test Your Skills in Python. BPB Publishers.
Abstract: Dear reader, have you learnt programming in Python? It is a high-
level Programming language developed by Guido van Rossum. It was released in
1991. Do you really know how to write programs in Python? Well, this book
gives you an opportunity to check your proficiency in Python By answering the
questions in this book. The Programs/ commands presented in this book are
executed using Python version 3.5.2. The questions are categorizes based on
various facets of programming in Python. The aim is to cover the topics in depth
test papers help you attempt many type of question in including writing
programs.
Salient features
More than 400 questions for testing skill in Python
Topics covered in sequence for novice readers
Questions are represented topic-wise so that a Python programmer can directly
go for testing a particular topic
Multiple choice question with Ture/False options also
Questions based on output help to learn the programming skills and various in-
built function in Python
Detailed explanation helps the reader learn the know concepts
Solved Model test papers help to learn theory questions
Keyword: python, test your skill
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Goel, Shivani (2017). A Support Vector Machine based Approach for Code
Smell Detection. IEEE International Conference on Machine Learning and Data
Science (pp. 9-14).
Abstract: Code smells may be introduced in software due to market rivalry,
work pressure deadline, improper functioning, skills or inexperience of software
developers. Code smells indicate problems in design or code which makes
software hard to change and maintain. Detecting code smells could reduce the
effort of developers, resources and cost of the software. Many researchers have
proposed different techniques like DETEX for detecting code smells which have
limited precision and recall. To overcome these limitations, a new technique
named as SVMCSD has been proposed for the detection of code smells, based on
support vector machine learning technique. Four code smells are specified
namely God Class, Feature Envy, Data Class and Long Method and the proposed
technique is validated on two open source systems namely Argo UML and
Xerces. The accuracy of SVMCSD is found to be better than DETEX in terms of
two metrics, precision and recall, when applied on a subset of a system. While
considering the entire system, SVMCSD detect more occurrences of code smells
than DETEX.
Keyword: Code smells, Anti-patterns, Support Vector Machine, Software
maintenance
Goel, Shivani (2017). Managing Software Product Line using an Ontological
Rule-Based Framework. International Conference on Infocom Technologies and
Unmanned Systems (pp. 376-382).
Abstract: Feature model is amongst the widely used approach to managing
variability and commonality in software product line for enabling software reuse.
Modeling variability and developing variable software product from feature
model is an arduous task. Due to the growing complexity and size of feature
model, defect such a false optional and dead feature can arise which lead to the
developing of low-quality erroneous software products. We propose an
ontological rule-based framework that improves software product line by
identifying feature model defect due to false optional and dead feature with their
causes. This information further suggest corrections to the modelers for resolving
defects. The evaluation results show the applicability to proposed framework to
handle false optional and dead feature and indicate its accuracy and scalability
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for large size feature models up to 21’050 features. Thereby enhancing the
reusability and quality of software product line.
Keyword: Feature model, First order logic rules, Ontology, Dead feature
Goel, Shivani (2018). Inspecting the Efficiency of Deep Neural Networks for
Classification of Images with Noise. Proceedings of 136th IASTEM
International Conference (pp. 81-85).
Abstract: Noise is the undesirable data in digital images which can produce
undesirable impacts like obscured objects. It becomes necessary to apply filters
for denoising the images. There are many deep learning techniques for image
classification. The study in this paper aims to challenge the performance of
deep learning in the presence of noise in the images. The experiments are
carried out on the popular dataset- Caltech 101. The images are corrupted using
Gaussian noise. Denoising is performed using combination of Median and
Gaussian filters. Feature extraction methods considered are edge detection,
wavelet transformation, their concatenation, LBP and Gabor filter. Classifiers
such as nearest Neighbors, Support Vector Machine, Neural Network and Deep
neural network with auto encoders are used. The experimental outcomes
demonstrate that though noise can upset the execution of image mining task in
terms of accuracy, deep neural networks with auto encoders has reported higher
accuracy of the classification of images with noise as well as without noise.
Keyword: Deep neural networks, Support Vector Machine, Noise, Image
classification
Goel, Shivani (2018). Survey on Human Emotion Recognition: Speech
Database, Features and Classification. Proceedings - IEEE 2018 International
Conference on Advances in Computing, Communication Control and
Networking (pp. 298-301).
Abstract: Recently, Speech Emotion Recognition (SER) has gained the
attention of researchers because of its wide application and many SER systems
have been proposed. In this paper, the process of SER has been discussed. The
important aspects include speech database used for analysis, the features which
are focused and the classifiers which affect the accuracy of the emotion
recognition. The details about various speech databases and classifiers have
been summarized. The performance of 8 machine learning classifiers is
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compared using many speech databases. The languages included are English,
German, Spanish etc.
Keyword: Emotion recognition, Speech Database, Classifier, Feature
Extraction
Goel, Shivani (2018). Using Artificial Intelligence for Improving Personalized
Learning. 5th International Conference on Transformations in Engineering
Education.
Abstract: Understanding the learning style of a student is an important aspect
in designing techniques for improving personalized learning. In this paper,
various learning styles are studied. The concept of expert system in artificial
intelligence is used to help classify the learning style of various students. Same
techniques for improving learning may not be suitable for students with varied
learning styles. So, in the proposed expert system, suggestions for improving
learning are provided based on the learning style of the student. The student
should also be free from stress for improving learning. Many types of stresses
are identified through various factors and counselling tips are provided for
handling different types of stress
Keyword: Learning styles, Expert system artificial intelligence, Stress
Goel, Shivani (2019). Empirical Study on Stock Market Prediction Using
Machine Learning. 019 International Conference on Advances in Computing,
Communication and Control (ICAC3) (pp. 1-5). Mumbai, India.
Abstract: Stock market prediction is a crucial and challenging task due to its
nonlinear, evolutionary, complex, and dynamic nature. Research on the stock
market has been an important issue for researchers in recent years. Companies
invest in trading the stock market. Predicting the stock market trend accurately
will minimize the risk and bring a maximum amount of profit for all the
stakeholders. During the last several years, a lot of studies have been done to
predict stock market trends using Traditional, Machine learning and deep
learning techniques. This survey will assist the readers & researchers in selecting
algorithms that can be useful for a predicting the stock market. A survey of
various algorithms and its parameters for stock market prediction is presented in
this paper.
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Keywords: Stock market prediction, machine learning, SVM, ARIMA, DAN2
Naïve Bayes, KNN, RBF.
Goel, Shivani (2019). Hybrid Approaches for Brain Tumor Detection in MR
Images. In: Singh M., Gupta P., Tyagi V., Flusser J., Ören T., Kashyap R. (eds)
Advances in Computing and Data Sciences. ICACDS 2019. Communications in
Computer and Information Science, vol 1045, 1045264
Abstract: The growing technology in medical image processing helps in quick
as well as an accurate analysis of several life-threatening diseases. Interestingly,
domain of brain tumor analysis has effectively utilized this trend to automate
core steps, i.e. extraction, detection, and the most important proximate
segmentation for tumor examination. To diagnose neurological disorders
magnetic resonance (MR) imaging methods are of great help. Discussing the
MR image types this paper briefs the parameters influencing the process of brain
tumor detection. Also, the study proposes a hybrid segmentation approach
combining k-means with fuzzy c-means (FCM) and support vector machine
(SVM) with fuzzy c-means. Experimentation performed show that fusion
outperforms three of the base approaches in brain tumor identification on
DICOM dataset using 200 T1W and T2W MR Images. The evaluation
parameters show that k-means combined with fuzzy c-means produce better
accuracy. Results further prove applicability of the proposal in detecting ranges
and shapes of brain tumor using MR images.
Keyword: Medical images, Segmentation, Brain tumor, Magnetic Resonance
Goel, Shivani (2016). Improving software product line using an ontological
approach. Sadhana-Academy Proceedings in Engineering Sciences, 41, 1381–
1391.
Abstract: Software product line (SPL) is an emergent strategy for generating
software products. The variability and commonality of SPL is illustrated by
feature models (FMs). The quality of software products relies on the correctness
of SPL. The overall benefits of software product line engineering (SPLE) are
reduced by various kinds of defects such as dead features and false optional
features in an FM. These defects can be inherited in the software products built
from a defective product line model (PLM). In this paper, the problem of
enhancing the quality of software products derived from SPLE is handled. An
ontological based approach is proposed following first-order logic (FOL) rules
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to identify defects namely dead features and false optional features. The
classification of cases for these defects in FMs that represent variability of SPL
is defined. The presented approach has been explained with the help of an FM
derived from the standard case in product line (PL) community. The initial
empirical evaluation of the proposed approach analyses 35FMs with different
sizes. The results obtained exhibit that the proposed approach is accurate,
effective, scalable up to 200 features and therefore improves SPL.
Keyword: Feature model (FM), Software product line (SPL), Defects,
Ontologies, Feature model ontology (FMO)
Goel, Shivani (2017). An automatic leaf disease detection system for legume
species. Journal of Biology and Today’s World, 6(6), 115-122.
Abstract: Legumes are crucial species which are used by the community
worldwide. In this manuscript, a two-stage approach to identify infected leaf
region percentage in legumes (particularly Groundnut and Soybean) is proposed.
First stage classifies between a healthy and a diseased leaf sample. Second stage
detects the diseased region and identifies the proportion of leaf infected area. The
two-stage approach provides high accuracy and also, shows that texture features
plays an important role for classification of healthy and diseased leaves. The
experimental results obtained on a self-collected leaf image dataset show that the
proposed approach accurately identifies the diseased region in legumes. The
proposed methodology can also be used for the classification of different disease
types.
Keyword: Machine learning, Pattern recognition, Plant disease
Goel, Shivani (2017). An intuitive general rank-based correlation coefficient.
Frontiers of Information Technology & Electronic Engineering, 699-711.
Abstract: Correlation analysis is an effective mechanism for studying patterns in
data and making predictions based on them. Many interesting discoveries have
been made by formulating correlations in seemingly unrelated data. This paper
attempts to quantify the theory of correlations by proposing an algorithm for
giving an intuitive, more accurate correlation coefficient. We propose a
predictive metric to calculate correlations between paired values known as the
general rank-based correlation coefficient (GRCC). It fulfills the five basic
criteria of a predictive metric, which are: independence from sample size; value
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between -1 and 1; measuring the degree of monotonicity; insensitivity to
outliers; and demonstrates intuitively. Further, the metric has been validated by
performing experiments using a real-time dataset and random number
simulations. The mathematical derivations of the proposed equations have also
been provided. We have compared it to Spearman’s rank correlation coefficient.
The results of this comparison show that the proposed metric fares better than
the existing metric on all the predictive metric criteria.
Keyword: General rank-based correlation coefficient, Multivariate analysis,
Predictive metric, Pearman’s rank correlation coefficient
Goel, Shivani (2017). Analyzing inconsistencies in software product lines using
an ontological rule-based approach. The Journal of Systems and Software, 605-
617.
Abstract: Software product line engineering (SPLE) is an evolving technical
paradigm for generating software products. Feature model (FM) represents
commonality and variability of a group of software products that appears within
a specific domain. The quality of FMs is one of the factors that impacts the
correctness of software product line (SPL). Developing FMs might also
incorporate inaccurate relationships among features which cause numerous
defects in models. Inconsistency is one of such defects that decreases the benefits
of SPL. Existing approaches have focused in identifying inconsistencies in FMs
however, only a few of these approaches are able to provide their causes. In this
paper FM is formalized from an ontological view by converting model into a
predicate-based ontology and defining a set of first-order logic based rules for
identifying FM inconsistencies along with their causes in natural language in
order to assist developers with solutions to fix defects. A FM available in
software product lines online tools repository has been used to explain the
presented approach and validated using 24 FMs of varied sizes up to 22,035
features. Evaluation results demonstrate that our approach is effective and
accurate for the FMs scalable up to thousands of features and thus, improves
SPL.
Keyword: Feature model, Software product line, Rule-based approach,
Ontology
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Goel, Shivani (2017). Correlation Clustering Methodologies and their
Fundamental Results. Expert Systems, 35(1), e12229.
Abstract: Correlation clustering possibly represents the most intuitive form of
clustering construction. It gives solutions that can be approximated while
automatically selecting the number of clusters. This approach handles scenarios
where the focus is on relationships between the objects instead of on actual
representations of the objects. The suitability of this method extends to the
structured objects for which feature vectors are not easy to obtain. Given the
increasing scale of data these days, correlation clustering has become a powerful
addition to the fields of data mining and agnostic learning. Correlation clustering
considers a weighted graph G = (V;E), where the edge weight indicates whether
two nodes are similar (positive edge weight) or different (negative edge weight).
The task is to find a clustering that either maximizes agreements or minimizes
disagreements. Unlike other clustering algorithms this does not require choosing
the number of clusters(k) in advance. The objective to minimize the sum of
weights of the cut edges is independent of the number of clusters. Many
methodologies, such as approximations and linear programming formulations,
have been used to approach this problem.
Keyword: Correlation Clustering, Approximation Algorithm, Minimizing
Disagreements, Maximizing Agreements, Linear Programming
Goel, Shivani (2017). Local Graph Based Correlation Clustering. Knowledge-
Based Systems, 155-175.
Abstract: In high dimensional data, clusters often exist in the form complex
hierarchical relationships. In order to explore these relationships, there is a need
to integrate dimensionality reduction techniques with data mining approaches.
The correlations in data points emerge more clearly if this integration is flawless.
We propose an approach called Local Graph Based Correlation Clustering
(LGBACC). This approach merges hierarchical clustering, with PCA to uncover
complex hierarchical relationships, and uses graph models to visualize the
results. We propose a framework of this approach that is divided into four
phases. Each phase is flawlessly integrated with the next phase. Visualization of
data after each phase is an important output and is knitted into the fabric of the
framework. The focus of this technique remains on obtaining high quality
clusters. The quality of the final clusters obtained is measured using standard
indices. It is found that LGBACC is better or equivalent to the existing
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hierarchical clustering approaches. We have used real world data sets to validate
our framework. These datasets test the approach on low as well as high
dimensional data. It is found that LGBACC produces high quality clusters
across a wide spectrum of dimensionality.
Keyword: Correlation clustering, Dimensionality reduction, Graph analysis,
Hierarchical clustering, Cluster quality
Goel, Shivani (2018). General correlation coefficient based agglomerative
clustering. Cluster Computing: The Journal of Networks, Software Tools and
Applications, 22(2), 553-583.
Abstract: Correlation analysis is an important concept for studying patterns in
data and making predictions. There have been many interesting revelations by
applying this concept as patterns emerge out of seemingly unrelated data. In
this paper, the focus is on exploring the role of correlation analysis in data
clustering. We propose an algorithm, that defines an intuitive and accurate
correlation coefficient metric known as the general correlation coefficient (G).
We then define a framework for agglomerative clustering, based on this metric,
called G based agglomerative clustering (GBAC). This framework is validated
by performing experiments using synthetic as well as real datasets. The real-
world dataset is taken from http:// databank.worldbank.org, a high dimensional
dataset on human development indicators. The objective of these evaluations is
to compare the performance of the proposed framework on different types of
datasets. Comparative studies are performed in order to validate the proposed
metric and the clustering framework. Our approach is found to be better than
the existing agglomerative clustering techniques and correlation coefficient
based clustering. It is found to be effective for small, large, as well as high
dimensional data. Finally, the clusters generated using this framework are
validated against the existing validation measures. It is found that GBAC
generates clean, more cohesive clusters. This framework combines the
predictive power of correlation coefficients with the ability of finding patterns
in data obtained from agglomerative hierarchical clustering. GBAC can be
applied on a wide range of clustering-based applications such as social network
analysis, customer segmentation, collaborative filtering, construction of
biological models, etc.
Keyword: General correlation coefficient, Cluster validation, Correlation
analysis, Agglomerative clustering
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Goel, Shivani (2018). Improving quality of software product line by analysing
inconsistencies in feature models using an ontological rule-based approach.
Expert Systems, 35(3), e12256.
Abstract: In Software product line engineering (SPLE), the variability and
commonality of a family of software products that belong to a particular
domain is represented through feature models (FMs). The development of FMs
may introduce inaccurate and incorrect feature relationships which may cause
various types of defects such as inconsistency which deteriorates the quality of
software products. Several researchers have worked on the identification of
defects due to inconsistency in FMs, but only a few of them have explained
their causes. In this paper, FM is transformed to predicate based feature model
ontology (FMO) using Prolog; and, first-order logic (FOL) is used to define
rules to identify inconsistency defects, to provide explanations for their causes
and to suggest corrections for resolving defects. The presented approach has
been explained with the aid of a FM derived from the Software Product Lines
Online Tools (SPLOT) repository and validated using 26 FMs of discrete sizes
up to 5543 features. Evaluation shows that the proposed approach is accurate,
scalable, effective, and thereby improves SPL, as it is validated using real-
world FMs as well as models generated using Feature IDE tool.
Keyword: Feature model, Software product line, Ontological rule-based
approach, Feature model ontology, Inconsistency
Goel, Shivani (2018). Plants disease identification and classification through
leaf images: A survey. Archives of Computational Methods in Engineering, 507
-530.
Abstract: The symptoms of plant diseases are evident in different parts of a
plant; however, leaves are found to be the most commonly observed part for
detecting an infection. Researchers have thus attempted to automate the process
of plant disease detection and classification using leaf images. Several works
utilized computer vision technologies effectively and contributed a lot in this
domain. This manuscript summarizes the pros and cons of all such studies to
throw light on various important research aspects. A discussion on commonly
studied infections and research scenario in different phases of a disease
detection system is presented. The performance of state-of-the-art techniques
are analyzed to identify those that seem to work well across several crops or
crop categories. Discovering a set of acceptable techniques, the manuscript
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highlights several points of consideration along with the future research
directions. The survey would help researchers to gain understanding of
computer vision applications in plant disease detection.
Keyword: Plants Disease Identification, Cash Crops, Horticulture Crops,
Floriculture Crops, Assorted Cultures
Goel, Shivani (2018). Semi-automatic leaf disease detection and classification
system for soybean culture. IET Image Processing, 1038-1048.
Abstract: Development of automatic disease detection and classification
system is significantly explored in precision agriculture. In the past few
decades, researchers have studied several cultures exploiting different parts of
a plant. A similar study is performed for Soybean using leaf images. A rule
based semi-automatic system using concepts of k-means is designed and
implemented to distinguish healthy leaves from diseased leaves. In addition, a
diseased leaf is classified into one of the three categories (downy mildew, frog
eye, and Septoria leaf blight). Experiments are performed by separately
utilizing colour features, texture features, and their combinations to train three
models based on support vector machine classifier. Results are generated using
thousands of images collected from Plant Village dataset. Acceptable average
accuracy values are reported for all the considered combinations which are also
found to be better than existing ones. This study also attempts to discover the
best performing feature set for leaf disease detection in Soybean. The system is
shown to efficiently compute the disease severity as well. Visual examination
of leaf samples further proves the suitability of the proposed system for
detection, classification, and severity calculation
Keyword: Automatic Disease, Soybean
Goel, Shivani (2018). Systematic review of clustering high-Dimensional and
large datasets. ACM Transactions on Knowledge Discovery from Data, 68.
Abstract: Technological advancement has enabled us to store and process
huge amount of data in relatively short spans of time. The nature of data is
rapidly increasing its dimensionality to become multi and high-dimensional.
There is an immediate need to expand our focus to include analysis of high-
dimensional and large datasets. Data analysis is becoming a mammoth task,
due to in cemental increase in data volume and complexity in terms of
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heterogony of data. It is due to this dynamic computing environment that the
existing techniques either need to be modified or discarded to handle new data
in multiple high dimensions. Data clustering is a tool that is used in many
disciplines, including data mining, so that meaningful knowledge can be
extracted from seemingly unstructured data. The aim of this paper is to
understand the problem of clustering and various approaches addressing this
problem. This paper discusses the process of clustering from both micro (data
treating) and macro (overall clustering process) views. Different distance and
similarity measures, which form the cornerstone of effective data clustering are
also identified. Further, an in-depth analysis of different clustering approaches
focused on data mining, dealing with large-scale data sets is given. These
approaches are so comprehensively compared to bring out a clear
differentiation among them. This paper also surveys the problem of high-
dimensional data and the existing approaches that helps to make it more
relevant. It also explores the latest trends in cluster analysis, and there al life
applications of this concept. This survey is exhaustive as it tries to cover all the
aspects of clustering in the field of data mining.
Keyword: Cluster analysis, Dimensionality reduction, Data clustering
applications, Clustering tendency, Data clustering process,
Goel, Shivani (2019). Sandpiper optimization algorithm: a novel approach for
solving real-life engineering problems. Applied Intelligence, 582-619.
Abstract: This paper presents a novel bio-inspired algorithm called Sandpiper
Optimization Algorithm (SOA) and applies it to solve challenging real-life
problems. The main inspiration behind this algorithm is the migration and
attacking behavior of sandpipers. These two steps are modelled and
implemented computationally to emphasize intensification and diversification in
the search space. The comparison of proposed SOA algorithm is performed with
nine competing optimization algorithms over 44 benchmark functions. The
analysis of computational complexity and convergence behaviors of the
proposed algorithm have been evaluated. Further, SOA algorithm is hybridized
with decision tree machine-learning algorithm to solve real-life applications. The
experimental results demonstrated that the proposed algorithm is able to solve
challenging constrained optimization problems and outperforms the other state-
of-the-art optimization algorithms.
Keyword: Bio-inspired metaheuristic techniques, Machine-learning
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Goel, Shivani (2019). SP-J48: a novel optimization and machine-learning-based
approach for solving complex problems: special application in software
engineering for detecting code smells. Neural Computing and Applications, 1-19.
Abstract: This paper presents a novel hybrid algorithm based on optimization
and machine-learning approaches for solving real-life complex problems. The
optimization algorithm is inspired from the searching and attacking behaviors of
sandpipers, called as Sandpiper Optimization Algorithm (SPOA). These two
behaviors are modeled and implemented computationally to emphasize
intensification and diversification in the search space. A comparison of the
proposed SPOA algorithm is performed with nine competing optimization
algorithms over 23 benchmark test functions. The proposed SPOA is further
hybridized with B-J48 pruned machine-learning approach for efficiently
detecting the code smells from the data set. The results reveal that the proposed
technique is able to solve challenging problems and outperforms the other well-
known approaches.
Keyword: Optimization, Bio-inspired metaheuristic techniques, Machine-
learning, Code smells
Dr. Shyam Singh Rajput, Assistant Professor, Department of CSE
Rajput, Shyam Singh (2019). Face Recognition in Low-Resolution Space. In
Veer Arya & Robin Singh Bhadoria (Eds.), The Biometric Computing:
Recognition and Registration (pp. 263-279).
Abstract: Face recognition in low-resolution space is challenging as low-
resolution (LR) images do not have efficient personal characteristics. In recent
years, many works have been proposed for providing solution to the problem of
recognition of LR images. This chapter presented the survey of existing methods
used for low-resolution face recognition. Moreover, the analysis of different
existing methods for LR images having different dimensions from several
popular databases have also been presented here.
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Rajput, Shyam Singh (2019). A robust facial image super-resolution model via
mirror-patch based neighbor representation. Multimedia Tools and Applications,
78(18), 25407–25426.
Abstract: Many patch-based facial images super-resolution (or hallucination)
techniques have been proposed in literature but all of them fail in the presence of
high-density impulse noise and occlusion. A novel mirror-patch based neighbor
representation (MPNR) model is proposed here which uses mirror-patch based
data fidelity along with the input-patch based fidelity in low-resolution (LR)
space to address the above problem. The computation of mirror-patch based data
fidelity helps in compensating the corrupted features of an input patch through
its mirror-patch. The objective function of the proposed model is designed in
such a way that it hallucinates the input LR faces and takes care of occlusion/
heavy noise effect simultaneously in the reconstruction process. It is conspicuous
from experimental results attained on FEI and CAS-PEAL-R1 databases that the
proposed MPNR model has outperformed all the comparative methods.
Keyword: Face super-resolution, Face hallucination
Rajput, Shyam Singh (2019). Noise Robust Face Hallucination via Outlier
Regularized Least Square and Neighbor Representation. IEEE Transactions on
Biometrics, Behavior, and Identity Science, 20(20), 1-12.
Abstract: In surveillance scenario the captured face may be of small size, low-
quality, low-resolution and noisy. Noise introduces outliers in the captured face
images which cause problems in similarity matching, an essential component in
attaining the face reconstruction constraints. The situation becomes even more
complicated when face images are corrupted by mixed Gaussian Impulse noise
(MIXGIN). To address this problem, a novel outlier regularized least square and
neighbor representation (ORLSNR) based face hallucination method is proposed
here. The proposed method starts with the detection of the outliers in an input
face and performs outlier regularization to reduce the impact of outliers on the
reconstruction produce. This assists in achieving the sparsity and locality
simultaneously by allowing the selection of the most relevant patches for
reconstruction of the high-resolution face.
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Experimental results performed on public FEI, CMU+MIT face databases, and
surveillance videos reflect that the proposed method is computationally efficient
and demonstrate better performance than the existing state-of-the-art face
hallucination methods.
Keyword: Outlier regularization, Face hallucination, Super resolution, Patch-
based method
Siva Skandha Sanagala, Research Scholar, Department of CSE
Sanagala, Siva Skandha (2019). A Fast and Light Weight Deep Convolution
Neural Network Model for Cancer Disease Identification in Human Lung(s).
IEEE International Conference on Machine Learning and Applications
(ICMLA) (pp. 1382-1387). Boca Raton, USA.
Abstract: In the proposed work, a convolution neural network (CNN) based
model has been used to identify the cancer disease in human lung(s). Moreover,
this approach identifies the single or multi-module in lungs by analyzing the
Computer Tomography (CT) scan. For the purpose of the experiment, publicly
available dataset named as Early Lung Cancer Action Program (ELCAP) has
been used. Moreover, the performance of proposed CNN model has been
compared with traditional machine learning approaches i.e. support vector
machine, k-NN, Decision Tree, Random Forest, etc under various parameters
i.e. accuracy, precision, recall, Cohen Kappa. The performance of proposed
model is also compared with famous CNN models i.e. VGG16, Inception V3 in
terms of accuracy, storage space and inference time. The experimental results
show the efficacy of proposed algorithms over traditional machine learning and
pre-trained models by achieving the accuracy of 99.5%.
Dr. Sridhar Swaminathan, Assistant Professor, Department of CSE
Swaminathan, Sridhar (2017). Twitter Sports: Real Time Detection of Key
Events from Sports Tweets. Transaction on Machine Learning and Artificial
Intelligence, 5(6), 36-60.
Abstract: Twitter users play a role of human sensors and update information
about real-life events by posting their tweets about them. Event detection in
Twitter is the process of detecting an event which is an occurrence causing
change in the volume of tweets that discuss the associated topic at a specific time
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and a location by Twitter users. Twitter has been extensively used to detect
major social and physical events such as earthquakes, celebrity deaths,
presidential elections, traffic jam and others. Real time event detection in Twitter
is detecting real-life events from live tweets instantly as soon as the event has
occurred. Real time event detection from Cricket sports using Twitter media is
an interesting, yet a complex problem. Because, event detection algorithm needs
live tweets streamed at real-time about the game and should detect events such as
boundary and sixer, at near real-time within few seconds from their occurrences.
In this paper, a novel real-time event detection approach is proposed for the
Cricket sports domain. The proposed approach first computes the post rate of an
adaptive window, which is the ratio between the volumes of tweets in the second
half window and the volume of tweets in the first half. An event has occurred if
the post rate is above the pre-defined threshold, otherwise the algorithm selects
the next big window in an adaptive manner. The predefined threshold helps to
filter out the small spikes in the streaming tweets volume. Once an event is
detected in a time window along the tweet stream, the event represented inside
the window is recognized using the event lexicon representing different events of
a cricket game. The proposed real-time event detection algorithm is extensively
evaluated on 2017 IPL T20 Cricket sports dataset using ROC and AUC
evaluation measures. The experimental results on the performance of the
proposed approach show that the adaptive sliding window detects sports events
with over 80% true positives and around 15% false positive rates.
Keyword: Social media, Microblogs, Twitter, Event detection, Sports events,
Adaptive sliding windows
Swaminathan, Sridhar (2018). Real Time Event Detection Adopting
Incremental TF-IDF based LSH and Event Summary Generation. International
Journal of Computer Applications, 180(12), 22-30.
Abstract: Recently, twitter users are leveraged to detect social and physical
events such as festivals and traffic jam at real time. Real time event detection
and summarization from Cricket sports is the process of detecting events such
as boundary at real time from live Cricket tweet stream as soon as event
happens and generating a quick game summary. This is an interesting, yet a
complex problem. Because of the need for rapid detection of sports events and
for the generation of a concise summary from huge volume of tweets for
Cricket enthusiasts. In this paper, a novel framework is proposed for detecting
key events from live Cricket tweets and for generating a game summary using
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the crawled tweets. Feature vectors of live tweets are created using incremental
TF-IDF representation and tweet clusters are discovered using Locality
Sensitive Hashing (LSH) where the post rate of each cluster determines the key
event. A key event is recognized from that cluster using our domain specific
event lexicon. Then, important moments from the crawled tweets are computed
by identifying the spikes in the tweets volume. Top-k tweets from each moment
are selected by ranking tweets on top-k words. Representative tweets from top-
k tweets are identified using Jaccard similarity. The evaluation on 2017 IPL
T20 Cricket live tweets using ROC measure shows that the proposed
incremental TF-IDF based LSH approach detects key events with nearly 95%
true positive rate and around 5% false positive rate. The proposed game
summarization algorithm generates summaries which are readable and
competitive to human tailored summaries.
Keyword: Event Detection, Incremental TF-IDF, Locality Sensitive Hashing,
Live Sports Tweets, Event Summarization
Swaminathan, Sridhar (2018). Sports Buzzer: Detecting Events at Real Time
in Twitter using Incremental Clustering. Transaction on Machine Learning and
Artificial Intelligence, 6(1), 1-23.
Abstract: In the recent past, twitter users are highly regarded as social sensors
who can report events and Twitter has been widely used to detect social and
physical events such as earthquakes and traffic jam. Real time event detection
in Twitter is the process of detecting events at real time from live tweet stream
as soon as an event has happened. Real time event detection from sports tweets,
such as Cricket is an interesting, yet a complex problem. Because, an event
detection system needs to collect live sports tweets and should rapidly detect
key events such as boundary and catch at real-time when the game is ongoing.
In this paper, a novel framework is proposed for detecting key events at real
time from live tweets of the Cricket sports domain. Feature vectors of live
tweets are created using TF-IDF representation and tweet clusters are
discovered using Locality Sensitive Hashing (LSH) where the post rate of each
cluster based on the volume of tweets is computed. If the post rate is above the
predefined threshold, then a key event recognized from that cluster using our
domain specific event lexicon for Cricket sports. The predefined threshold
helps to filter out small spikes in the tweets volume. The proposed real-time
event detection algorithm is extensively evaluated on 2017 IPL T20 Cricket
live tweets using ROC evaluation measure. The experimental results on the
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performance of the proposed approach show that the LSH approach detects
sports events with nearly 90% true positive rate and around 10% false positive
rate. The results have also demonstrated the influence of different parameters
on the accuracy of the event detection.
Keyword: Social media, Twitter, Sports event detection, Locality sensitive
hashing, Incremental clustering
Swaminathan, Sridhar (2019). Movie Video Summarization- Generating
Personalized Summaries Using Spatiotemporal Salient Region Detection.
International Journal of Multimedia Data Engineering and Management, 10(3),
1-26.
Abstract: Video summarization condenses a video by extracting its informative
and interesting segments. In this article, a novel video summarization approach is
proposed based on spatiotemporal salient region detection. The proposed
approach first segments a video into a set of shots which are ranked with
spatiotemporal saliency scores. The score for a shot is computed by aggregating
the frame level spatiotemporal saliency scores. This approach detects spatial and
temporal salient regions separately using different saliency theories related to
objects present in a visual scenario. The spatial saliency of a video frame is
computed using color contrast and color distribution estimations and center prior
integration. The temporal saliency of a video frame is estimated as an integration
of local and global temporal saliencies computed using patch level optical flow
abstractions. Finally, top ranked shots with the highest saliency scores are
selected for generating the video summary. The objective and subjective
experimental results demonstrate the efficacy of the proposed approach.
Keyword: Salient Region Detection, Spatial Saliency, Salient Region Detection,
Spatial Saliency, Spatiotemporal Saliency, Temporal Saliency
Suchi Kumari, Assistant Professor, Department of CSE
Kumari, Suchi (2019). Effect of correlation on the traffic capacity of time-
varying communication network. Modern Physics Letters B, 33(26), 1950314.
Abstract: The network topology and the routing strategy are major factors to
affect the traffic dynamics of the network. In this work, we aim to design an
optimal time-varying network structure and an ancient route is allocated to each
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user in the network. The network topology is designed by considering addition,
removal and rewiring of links. At each time instant, a new node connects with an
existing node based on the degree and correlation with its neighbor. Trac
congestion is handled by rewiring of some congested links along with the
removal of the anti-preferential and correlated links. Centrality plays an
important role to the most important node in the network. The more a node is
central, the more it can be used for the shortest route of the user pairs and it can
be congested due to a large number of data coming from its neighborhood.
Therefore, routes of the users are selected such that the sum of the centrality of
the nodes appearing in the user's route is minimum. Thereafter, we analyze the
network structure by using various network properties such as the clustering
coefficient, centrality, average shortest path, rich club coefficient, average packet
travel time and order parameter.
Keyword: Time-varying communication network, Routing, Congestion,
Entrality
Dr. Suneet Kumar Gupta, Department of CSE
Gupta, Suneet Kumar (2018). Learning with Software-Defined Area.
Innovations in Software-Defined Networking and Network Functions
Virtualization (pp. 291-305).
Abstract: The idea of software-defined networking (SDN) is a paradigm shift
in computer networking. There are various advantages of SDN (e.g., network
automation, fostering innovation in network using software, minimizing the
CAPEX and OPEX cost with minimizing the power consumption in the
network). SDN is one of the recently developed network-driven methodologies
where the core of all lower-level services is operated by one centralized device.
Developers tried to develop such approaches to make it easy for an
administrator to control information flow from one node to another node. To
obtain these services, lower-level static architecture is decoupled for the higher
level. This chapter introduces a new approach that is based on complex network
processing and forecasting for an event.
Keyword: Software-defined networking
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Gupta, Suneet Kumar (2019). A Convolution Neural Network based approach
to detect the disease in Corn Crop. 2019 IEEE 9th International Conference on
Advanced Computing (IACC) (pp. 176-181). Tiruchirappalli, India.
Abstract: The agricultural production is affected by the climate changes i.e.
humidity, rain, extremes of temperature etc. Additionally, abiotic stresses are
causative element to the etiology of disease as well as pest on crops. The
production of the crops can be improved by diagnosis as well as detecting the
accurate disease on time or in early stage. Moreover, it is very difficult for
accurately detecting and treatment based on the technique which used in disease
and insect pests diagnosis. Few researchers have made efforts on predicting
disease as well as pest crops using machine learning algorithms. Therefore, this
paper presents disease identification in corn crops by analyzing the leaves in the
very early stage. We have used Plant Village dataset for experiments and
analysis. The validity of the results has been cheeked on various performance
metrics such as precision, accuracy, recall, storage space, running time of the
model and AUC-RoC. The obtained results shows the proposed technique
outperform in comparison with the traditional machine learning algorithms.
Developed model is able to achieve the accuracy of 94%.
Keywords: Convolution neural network, Traditional machine learning methods,
Pre-trained models, Augmentation.
Gupta, Suneet Kumar (2019). EERP: Energy-Efficient Relay Node Placement
for k-Connected Wireless Sensor Networks Using Genetic Algorithm. Advances
in Intelligent Systems and Computing (pp. 9043).
Abstract: In this article, we propose relay node placement for providing k-
connectivity to randomly deployed sensor nodes with energy efficacy using
Genetic Algorithm (GA). Here, we also explain the basic step of GA with
suitable examples. Also, we carried out the extensive simulations to study
proposed algorithm’s performance with existing one in terms of number of
deployed nodes and lifetime of the network.
Gupta, Suneet Kumar (2019). FCNN-LDA: A faster convolution neural
network model for leaf disease identification on apple's leaf dataset. Proceedings
of 2019 International Conference on Information and Communication
Technology and Systems (pp. 246).
Abstract: Fruits are common items bought by every household. They are
delicious to eat and rich in nourishment. However, they may also adversely affect
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health if the fruits are from a diseased tree/plant. Moreover, Farmers may also
loose lot of amount of profit if their plants get affected by some disease. In this
article, the main objective/goal is to develop a convolution neural network-based
approach to identify the disease in apple fruit. The data for experiment has been
taken from Plant Village. In the proposed work, a convolution neural network
model has been developed to identify the disease in apple and it consists of three
convolution layer, three max pooling layers followed by two densely connected
layers. This model was formed after testing with varying number of convolution
layers from 2 to 6 and found that 3 layers was giving best accuracy. For the
result comparison purpose, the traditional machine learning algorithms are also
executed on the same dataset. Along with traditional machine learning
approaches, the famous pre-trained CNN models i.e. VGG16 and InceptionV3
are also executed. The experiments results show the efficacy of proposed
algorithm over pre-trained models and traditional machine learning approach in
terms of accuracy, computational time, specificity, F1 score and AUC-ROC
curve. The proposed model achieves the state-of-the-art accuracy of 99%.
Moreover, the proposed model requires only 20% of the space as compared to
pre-trained model with inference time less than 1 second as pre-trained models
require minimum 30 second.
Keyword: Convolution neural network, Deep learning
Gupta, Suneet Kumar. (2019). Grape Disease Identification Using Convolution
Neural Network. 2019 23rd International Computer Science and Engineering
Conference (pp. 224-229).
Abstract: In this paper, we present a CNN model to identify the disease in
grapes plant in early stage by analyzing the leaf images. The model is illustrated
on publicly available Plant Village dataset and the performance compared with
traditional machine learning models and pre-trained convolution neural network
models. The performance of algorithms has been compared on various evaluation
metrics i.e. accuracy, precision recall, running time of model, storage space and
AUC-RoC. From the experimental results, it has been observed that the
performance of proposed model is better than traditional machine learning
algorithms as well as pre-trained models by achieving an accuracy of 99%.
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Gupta, Suneet Kumar (2019). Profit or Loss: A Long Short Term Memory
based model for the Prediction of share price of DLF group in India. 2019 IEEE
9th International Conference on Advanced Computing (IACC) (pp. 120-124).
Tiruchirappalli, India.
Abstract: Presently, the prediction of share is a challenging issue for the
research community as share market is a chaotic place. The reason behind it,
there are several factors such as government policies, international market,
weather, performance of company. In this article, a model has been developed
using long short-term memory (LSTM) to predict the share price of DLF group.
Moreover, for the experimental purpose the data of DLF group has been taken
from yahoo financial services in the time duration of 2008 to 2018 and the
recurrent neural network (RNN) model has been trained using data ranging from
2008 to 2017. This RNN based model has been tested on the data of year 2018.
For the performance comparison purpose, other linear regression algorithms i.e.
k-nn regression, lasso regression, XGboost etc has been executed and the
proposed algorithm outperforms with 2.6% root mean square error.
Keywords: Prediction Model, Recurrent Neural Network, Long Short-Term
Memory (LSTM), Mean Square Error (MSE).
Gupta, Suneet Kumar (2019). Wilson's disease: A new perspective review on
its genetics, diagnosis and treatment. Frontiers in bioscience, 11, 166-185.
Abstract: Wilson's disease (WD) is an autosomal recessive disorder which is
caused by poor excretion of copper in mammalian cells. In this review, various
issues such as effective characterization of ATP7B genes, scope of gene network
topology in genetic analysis, pattern recognition using different computing
approaches and fusion possibilities in imaging and genetic dataset are discussed
vividly. We categorized this study into three major sections: (A) WD genetics,
(B) diagnosis guidelines and (3) treatment possibilities. We addressed the scope
of advanced mathematical modelling paradigms for understanding common
genetic sequences and dominating WD imaging biomarkers. We have also
discussed current state-of-the-art software models for genetic sequencing.
Further, we hypothesized that involvement of machine and deep learning
techniques in the context of WD genetics and image processing for precise
classification of WD.
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These computing procedures signify changing roles of various data
transformation techniques with respect to supervised and unsupervised learning
models.
Keyword: Wilson’s Disease, Genetics, Copper Transportation Sites, Focal Liver
Lesion
Dr. Tanmay Bhowmik, Assistant Professor, Department of CSE
Bhowmik, Tanmay (2019). Prosodic word boundary detection from Bengali
continuous speech. Language Resources and Evaluation, 1-19.
Abstract: Detection of word boundaries in continuous speech is a tedious
process due to the absence of a definite pause or silence in the word boundary
position. Thus, continuous speech recognition is a very challenging task.
However, the prosodic word boundaries, unlike the written word boundaries, can
be predicted using the prosodic parameters of continuous speech. This paper
proposes a method for detecting such prosodic word boundaries from Bengali
continuous speech. Bengali is a bound-stress language, where stress is observed
on the first syllable of a prosodic word. Empirical Mode Decomposition is
applied to the logarithm of fundamental frequency (F0) contour of continuous
speech to detect prosodic word boundaries. 200 Bengali readout sentences, read
by ten speakers, are analyzed for the present work. An overall prosodic boundary
detection accuracy of 88.05% is achieved, whereas precision and recall values
are 90.73% and 88.31%, respectively, with f-score as 89.5. A prosodic word
dictionary comprising 5031 prosodic words has been developed by analyzing
1526 Bengali sentences with the proposed prosodic word boundary detection
method.
Keyword: Prosodic word boundaries, Fundamental frequency
Dr. Tanveer Ahmed, Assistant Professor, Department of CSE
Ahmed, Tanveer (2019). Identifying tiny faces in thermal images using transfer
learning. Journal of Ambient Intelligence and Humanized Computing, 1-10.
Abstract: This article focuses on identifying tiny faces in thermal images using
transfer learning. Although the issue of identifying faces in images is not new,
the problem of tiny face identification is a recently identified research area.
Indeed challenging, however, in this paper, we take the problem one step ahead
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and focus on recognizing tiny faces in thermal images. To do that, we use the
paradigm of transfer learning. We use the famous residual network to extract the
features in the target domain. Subsequently, with this model as a reference point,
we then retrain it in the target domain of thermal images. Through testing
performed in Terravic datasets, we have found that the method outperforms
existing methods in literature to identify tiny faces in thermal images.
Keyword: Machine learning, Biometrics, Tiny faces, Thermal images
Ahmed, Tanveer (2018). Analyzing crowdsourcing to teach mobile
crowdsensing a few lessons. Cognition, Technology, and Work, 20(3), 457–475.
Abstract: In recent years, mobile computing has shown so much potential that
one can see a boundary-blurring expansion between the physical and the digital
world. In this context, one of the most sought-after research areas is mobile
crowdsensing. To realize the vision of crowdsensing, there is a plethora of work
in the literature that focuses on the technical capabilities of a mobile device.
However, an important and a critical problem that eludes literature is the issue
of human participation. We base this argument on a very simple, yet powerful
fact that a mobile device is still a person’s private property. Therefore,
considering human mentality, can we expect a person to contribute all the time?
In this respect, it is not feasible for a human dependent computational system to
ignore the inevitable human factor and focus only on the mechanical properties.
In this paper, we look into the often-ignored human aspects and will study the
problem from a psychological perspective. We take inspiration from the mature
paradigm of crowdsourcing and discuss the importance of a few human factors
that could teach us how to encourage user participation in mobile crowdsensing.
Further, we also explore a person’s habitual characteristics that could help
answer the decade’s old question: How to get quality responses from the
crowd? We use a psycho-technological approach to observe, understand, and
find a few details regarding human behavior in online systems. Lastly, we take
inspiration from the analysis to present a roadmap that aids in engineering a
better and effective crowdsensing platform.
Keyword: Crowdsourcing, Crowdsensing, Human–computer interaction, Data
mining
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Dr. Tapas Badal, Assistant Professor, Department of CSE
Badal, Tapas (2019). WIDER Face Challenge using Multi-Task Cascading
Neural Network. 9th International Conference on Advanced Computing (pp. 189
-193).
Abstract: Nowadays, face detection is common. It’s used in many areas. With
the help of face detection benchmark datasets, many signs of progress have been
made. Face detection methods used nowadays is not matching the real-world
requirements. With new advancing technologies and services, we need to
upgrade our existing systems. By using a dataset called a WIDER FACE which
is very large in size than already existing datasets, we can improve the
performance. WIDER FACE dataset has many faces in it which may be
challenging as it includes faces under different conditions. Moreover, we can see
that in face detection task, WIDER FACE dataset is best for training and testing
the accuracy of the model. But existing face detection algorithms and models are
not up-to the marks. They have major limitations. So, we created a WIDER
FACE detection system which will help us overcome all those issues.
Keyword: WIDER FACE dataset, Cascading Neural Network
Badal, Tapas (2019). An efficient vision based elderly care monitoring
framework using fall detection. Journal of Statistics and Management Systems,
22(4), 603–611.
Abstract: Fall is one of the major reasons of elderly people living alone for
getting injured. Numerous elderly individuals are living alone in their homes. In
case if the elderly tumble down, it might be troublesome for them to ask for
help. Due to this problem there is a dire requirement of an efficient home
monitoring framework. An effective fall detection system can help provide rapid
help to the patient and improve the chances of survival of the patient. The
principle goal of this paper is to design a vision-based fall detection framework
for the elderly people. Fall identification framework at home is progressively
vital and dependable observation framework is a need to mitigate the outcomes
of fall. In this paper, we look forward to detecting a fall and normal walking of
an individual using background subtraction, Motion History Image, feature
extractor like Zernike Moments and then using a learning model.
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The proposed framework is able to detect fall and normal walking with an
accuracy of 92.86% and 90.82%.
Keyword: Fall detection, Background subtraction
Dr. Vijay Kumar Bohat, Assistant Professor, Department of CSE
Bohat, Vijay Kumar (2019). A Convolution Neural Network based approach to
detect the disease in Corn Crop. 2019 IEEE 9th International Conference on
Advanced Computing (IACC) (pp. 176-181). Tiruchirappalli, India.
Abstract: The agricultural production is affected by the climate changes i.e.
humidity, rain, extremes of temperature etc. Additionally, abiotic stresses are
causative element to the etiology of disease as well as pest on crops. The
production of the crops can be improved by diagnosis as well as detecting the
accurate disease on time or in early stage. Moreover, it is very difficult for
accurately detecting and treatment based on the technique which used in disease
and insect pests diagnosis. Few researchers have made efforts on predicting
disease as well as pest crops using machine learning algorithms. Therefore, this
paper presents disease identification in corn crops by analyzing the leaves in the
very early stage. We have used Plant Village dataset for experiments and
analysis. The validity of the results has been cheeked on various performance
metrics such as precision, accuracy, recall, storage space, running time of the
model and AUC-RoC. The obtained results shows the proposed technique
outperform in comparison with the traditional machine learning algorithms.
Developed model is able to achieve the accuracy of 94%.
Keywords: Convolution neural network, Traditional machine learning methods,
Pre-trained models, Augmentation
Dr. Vinit Jakhetiya, Department of CSE
Jakhetiya, Vinit (2017). A prediction backed model for quality assessment of
screen content and 3-D synthesized images. IEEE Transactions on Industrial
Informatics, 652-660.
Abstract: In this paper, we address problems associated with free-energy-
principle based image quality assessment (IQA) algorithms for objectively
assessing the quality of Screen Content (SC) and 3D synthesized images. These
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algorithms separate an image into predicted and disorder residual parts and
assume disorder residual part does not contribute much to the overall perceptual
quality. These algorithms fails for quality estimation of SC images as
information of textual regions in SC images are largely separated into the
disorder residual part and less information in the predicted part and
subsequently, given a negligible emphasis. However, this is in contrast with the
characteristics of human vision. Since our eyes are well trained to detect text in
daily life. So, our human vision has prior information about text regions and can
sense small distortions in these regions. In this paper, we proposed a new
reduced-reference IQA algorithm for SC images based upon a more perceptually
relevant prediction model, which overcomes problems with existing free-energy
principle-based predictors. From experiments, it is validated that the proposed
algorithm has a better ability of efficiently estimating the quality of SC images
as compared to the recently developed reduced reference IQA algorithms. We
also applied, the proposed algorithm to judge the quality of 3D synthesized
images and observed that it even achieves better performance than the full-
reference IQA metrics specifically designed for the 3D synthesized views.
Keyword: Screen content images, 3D synthesized images, image quality
assessment (IQA), Distortion categorization, Textual region, Human vision
Jakhetiya, Vinit (2018). Just Noticeable Difference for Natural Images using
RMS Contrast and Feed-back Mechanism. Neurocomputing, 366-376.
Abstract: Contrast Sensitivity (CS), Luminance Adaptation (LA) and Contrast
Masking (CM) are important contributing factors for Just Noticeable
Difference (JND) in images. Most of the existing pixel domain JND algo-
rhythms are based only on LA and CM. Research shows that the human vision
depends significantly on CS, and an underlying assumption in the existing
algorithms is that CS cannot be estimated in the pixel domain JND algorithms.
However, in the case of natural images, this assumption is not true. Studies on
human vision suggest that CS can be estimated using the Root Mean Square
(RMS) contrast in the pixel domain. With this in perspective, we propose the
first pixel based JND algorithm that includes a very important component of
the human vision, namely CS by measuring RMS contrast. This RMS contrast
is combined with LA and CM to form a comprehensive pixel-domain model to
efficiently estimate JND in the low frequency regions. For high frequency
regions (edge and texture), a feedback mechanism is pro- posed to efficiently
alleviate the over- and under-estimation of CM. To facilitate this, a prediction-
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based algorithm is used to classify an image into low (smooth) and high
frequency regions. This feed-back mechanism is based on the relationship
between the CS and RMS contrast. Experiments validate that the proposed JND
algorithm efficiently matches with human perception and produces significantly
better results when compared to existing pixel domain JND algorithms.
Keyword: Just Noticeable Difference, Contrast sensitivity, RMS contrast,
Feedback mechanism, Bilateral filter
Jakhetiya, Vinit (2018). Model-Based Reference less Quality Metric of 3D
Synthesized Images Using Local Image Description. IEEE Transactions Image
Processing, 1-1.
Abstract: New challenges have been brought out along with the emerging of
3D-related technologies such as virtual reality (VR), augmented reality (AR),
and mixed reality (MR). Free viewpoint video (FVV), due to its applications in
remote surveillance, remote education etc, based on the flexible selection of
direction and viewpoint, has been perceived as the development direction of
next-generation video technologies and has drawn a wide range of researchers’
attention. Since FVV images are synthesized via a depth image-based rendering
(DIBR) procedure in the “blind” environment (without reference images), a
reliable real-time blind quality evaluation and monitoring system is urgently
required. But existing assessment metrics do not render human judgments
faithfully mainly because geometric distortions are generated by DIBR. To this
end, this paper proposes a novel reference less quality metric of DIBR-
synthesized images using the autoregression (AR)-based local image
description. It was found that, after the AR prediction, the reconstructed error
between a DIBR-synthesized image and its AR-predicted image can accurately
capture the geometry distortion. The visual saliency is then leveraged to modify
the proposed blind quality metric to a sizable margin. Experiments validate the
superiority of our no-reference quality method as compared with prevailing full
-, reduced- and no-reference approaches.
Keyword: Quality assessment, no-reference (NR), Depth image-based
rendering (DIBR)
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Dr. Vipul Kumar Mishra, Assistant Professor, Department of CSE
Mishra, Vipul Kumar (2017). Comprehensive Operation Chaining Based
Schedule Delay Estimation during High Level Synthesis. IEEE International
Symposium on Nanoelectronic and Information Systems (pp. 66-68).
Abstract: Design space exploration (DSE) during high level synthesis (HLS)
involves a major step called scheduling which is responsible for estimating the
delay of a control data flow graph (CDFG). However, a DSE process which
concurrently estimates schedule delay by considering functional unit (FU),
switching devices (such as mux, demux) and storage elements (such as latches),
much before creation of its controller timing sequence, is an unsolved problem in
the literature. Current DSE approaches either consider only FU during scheduling
or generate the complete controller timing sequence for delay evaluation of a
CDFG based on provided resource constraint. The prior case, though fast but is
not realistic in delay estimation. The latter case, though very slow, but provides
realistic delay estimation. This paper solves the aforesaid problem by proposing a
balanced DSE methodology that includes comprehensive delay estimation by
considering combined delay of FU, switching devices and storage elements
directly from scheduling. Results indicate improvement in achieving more
realistic delay estimation process than previous approaches
Keyword: Design space exploration, Schedule Delay Estimation, High level
synthesis
Mishra, Vipul Kumar (2017). Cost Aware Majority Logic Synthesis for
Emerging Technologies. 2017 IEEE International Symposium on Nanoelectronic
and Information Systems (pp. 69-73).
Abstract: Continuous growth of semiconductor industry-based n More’s law is
in danger due to the physical limitation of CMOS technology. In order to sustain
more’s law, researchers are aggressively discovering other alternatives such as
nano magnetic logic (NML) and quantum dot cellular automata (QCA). Majority
gate is the base element for these technologies for synthesis of logic circuit. This
paper presents a novel majority logic synthesis (MLS) which optimize Area
delay using a novel Cost of Circuit (CoC) parameter during the synthesis process
which was faced by currently available synthesis algorithms which are mainly
focused on area optimization. In addition, an updated library is presented for
majority logic synthesis based on 3-input(M3) and 5-input(m5) majority gates for
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area-Delay optimization during MLS. Experiments on microelectronics center of
North Carolina (MCNC) benchmarks indicate that, the proposed approach has
achieved an average reduction of 39% in delay, an average reduction of 14% in
cost of circuit with the 2% overhead in the circuit are
Keyword: Majority logic synthesis, Cost of Circuit, Heuristic, Emerging
technology
Mishra, Vipul Kumar (2017). Heuristic Based Majority/Minority Logic
Synthesis for Emerging Technologies. 30th IEEE Conference on VLSI Design
(pp. 295-300).
Abstract: Due to the physical limitation of CMOS technology researchers are
actively exploring other alternatives such as Quantum dot cellular automata
(QCA), Nano magnetic logic (NLM), single electron tunneling (SET) and
tunneling phase logic (TPL). These emerging technologies utilize majority gate
as a base component foe synthesis of logic network. This paper presents a novel
heuristic-based majority logic synthesis (HMLS) which reduces the time
complexity of the synthesis process, and also overcome the scalability problem
faced by currently available synthesis algorithms based on k- map technique. In
addition, an update library is proposed for majority logic synthesis based on 3
input and 5 input majority gates for further optimization of synthesis process.
Experiments of microelectronics center of North Carolina (MCNC) benchmark
indicate that the proposed approach has achieved an average reduction of 33% in
gate count. Furthermore, while performing experiment for QCA as test case, the
proposed approach has achieved an average reduction of 33% in circuit delay and
an average reduction of 4% in circuit area.
Keyword: Majority Logic Synthesis, Heuristic, Emerging technology
Mishra, Vipul Kumar (2018). Majority Logic Synthesis for Area Delay Trade
-off in Emerging Technologies. VLSI Circuits and Systems Letter (pp. 48-12).
Abstract: This letter presents a novel majority logic synthesis (MLS) which
optimize area delay trade-off using a novel cost of circuit (CoC) parameter. The
CoC overcome the problem faced by previous synthesis algorithms, which were
mainly focused on the area or delay optimization. Experiments on
microelectronics center of North Carolina (MCNC) benchmarks indicate that
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the proposed approach has achieved an average reduction of 36% in delay, and
an average reduction of 15% in cost of circuit with a 1.5% overhead in the area.
Keyword: Majority Logic Synthesis, Area Delay Trade-off
Mishra, Vipul Kumar (2019). Dengue Disease Spread Prediction Using
Twofold Linear Regression. 2019 IEEE 9th International Conference on
Advanced Computing (IACC) (pp. 182-187). Tiruchirappalli, India.
Abstract: Dengue is a disease caused by four types of related viruses
transmitted by a mosquito, most commonly Aedes Aegypti. The disease is
considered an alarming threat to the health of populations spanning millions of
people living in tropical and subtropical areas of the globe where the mosquito
thrives. A large number of studies have confirmed that the rise of dengue disease
is positively correlated with climate and climatic conditions, specifically,
humidity, temperature and precipitation levels. Many of these studies include
quantitative models correlating climate variables with the incidence of dengue
cases. The quantitative models invite the question: how well would we be able
to predict future cases of the disease based on climate variables that are included
in weather forecasts? To answer this question we conducted a study on Dengue
Forecasting using machine learning, which utilizes climate and dengue data
(available to data scientists by US government) to forecast future dengue
epidemics. In this research we proposed a novel model twofold linear regression
which out perform compare to all previous models. we achieve 19.81 mean
absolute error which is minimum as compare to traditional machine learning
techniques. Moreover, we have analyzed various neural network, support vector
machine, random forest, boosted tree, XGBoost based predictive models and
evaluate their performance against proposed method.
Keywords: Twofold linear regression, Dengue disease prediction, Neural
network, XGBoost.
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Department of Electronics & Communication Engineering
Dr. Aditya Abburi, Assistant Professor, Department of ECE
Abburi, Aditya (2017). Surfactant-assisted synthesis and characterization of
hydroxyapatite nanoparticles. The 17th IEEE International Conference on
Nanotechnology (pp. 951-955).
Abstract: The objective of this study was to demonstrate a proof of concept for
a technology platform which could produce engineered hydroxyapatite
nanoparticles with respect to size, shape and morphology with ease and adapt it
to a continuous production line. The conventional processes that are used in the
production of hydroxyapatite are not only cumbersome but also expensive since
the precursors are of high cost. It appears that none of the processes are capable
of producing materials with different size, shape, porosity and more importantly
the surface charge which is a very important characteristic for materials
particularly used in medical applications. This paper shows that a single process
line could eventually produce a designed nano product. The experiments were
limited to producing Hydroxyapatite using inexpensive starting materials and
simple unit operations. The results obtained demonstrate that nano
Hydroxyapatite could be produced with variations in size, morphology and
surface charge with the same experimental set up by changing several variables
in the process conditions. Hydroxyapatite nanoparticles of varying crystal size,
in different shapes such as needles, flakes and rhombic, surface charge from
negative to positive were obtained in the same set up. The results demonstrated
that by changing the conditions, it is possible to seamlessly vary the
characteristic of nanomaterials. Bulk and continuous process line makes the
process platform amenable for economical production.
Dr. Amit Singhal, Assistant Professor, Department of ECE
Singhal, Amit (2019). DoG Based Local Ternary Pattern for Image Retrieval.
2019 International Conference on Signal Processing and Communication
(ICSC) (pp. 242-245). NOIDA, India.
Abstract: In this paper, a novel pattern-based feature is proposed for the
purpose of image retrieval. It extracts edge information of images using
difference of Gaussian (DoG) filter. The choice of DoG filter depends upon the
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quality of available image and the information content, i.e, the value of
blurriness (standard deviation) can be controlled and hence the edges can be
highlighted more accurately. From the filtered image, texture statistics are
captured using local ternary pattern (LTP) extracted from four different
orientation images to form DoGLTP. The different orientations used in this
work enable us to capture angle information usually ignored by many pattern-
based features. In the proposed feature, color information is included through
Hue and Saturation histograms. This makes the proposed feature more robust
and the retrieval results highlight its superior performance in comparison to
existing techniques on two popular databases: Corel 1000 and Corel 10k.
Keywords: Corel 1000, Corel 10k, DoG filter, Image retrieval, Local ternary
pattern.
Singhal, Amit (2019). Haar-like Local Ternary Pattern for Image Retrieval.
2018 13th International Conference on Industrial and Information Systems, ICIIS
2018 - Proceedings (pp. 158-162).
Abstract: In this paper a novel Haar- like local ternary pattern (HLTP) is
introduced for content-based image retrieval. Many variants of local patterns like
LBP, LTP etc. ignore the high pass information present in an image. The
proposed HLTP feature not only extracts this information but the best suited
Haar-like filter is also selected to represent the high pass information. Selection
of only the best filter reduces the complexity of the feature. Then, in order to
capture the structural similarity within the image, local ternary edges are
computed in 3x3 neighborhood for each pixel of the dominant filter image. Hue
and saturation histograms are concatenated with the HLTP feature to make it
robust against colour variations. Experiments are conducted on two diversified
datasets and performance of proposed method is compared with the existing
methods.
Keyword: Corel 1000, Haar-like filter, Image retrieval, Local patterns, Texture
Singhal, Amit (2018). 3D local ternary co-occurrence patterns for natural,
texture, face and bio medical image retrieval. Neurocomputing, 313(3), 333-
345.
Abstract: In this paper, a novel feature called three-dimensional local ternary
co-occurrence pattern (3D-LTCoP) is proposed for natural, texture, face and
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biomedical image retrieval. Standard local binary pattern and its variants like
local ternary patterns, local derivative patterns, local tetra patterns etc. encode
relationship between reference pixel and neighboring pixels in a two-
dimensional plane of the image. The edge distribution information in these
local patterns are extracted using first-order derivatives and are represented in
the form of histogram. Proposed technique of feature representation draws a
three-dimensional cubical image block in the local region using Gaussian
filtered images and extracts relationship between reference pixel and
neighboring pixels in five diverse directions of the 3D block. Further,
frequency analysis of ternary patterns is performed by storing mutual local
directional information in the co-occurrence matrix. Experiments are conducted
on six benchmark databases ranging from natural, texture, and face to
biomedical categories to observe the robustness of the proposed feature.
Results are analyzed and compared with typical state-of-the-art local patterns
and superiority of the proposed technique is clearly evident in terms of
performance evaluation measures.
Keyword: Feature descriptor, Local Ternary Pattern, Image Retrieval, Medical
Imaging
Singhal, Amit (2019). Multi-channel local ternary pattern for content-based
image retrieval. Pattern Analysis and Applications, 22(4), 1585-1596.
Abstract: A feature based on a single modality such as color or texture is not
sufficient to investigate the appearance variation across multiple images. In this
paper, a novel feature referred to as multi-channel local ternary pattern is
proposed for image retrieval. The proposed method captures cross-channel color
–texture information through the combination of H–V, S–V and V–V channels
obtained from HSV representation of the image. Not only texture statistics
extracted in this manner contain color information, but local texture information
is also incorporated in such representations. The effectiveness of the proposed
image retrieval method is measured by performing experiments on popular
natural, face and texture databases including Corel 1000, Corel 10k, CMU-PIE,
Stex and MIT VisTex, and results are compared with the existing state-of-the-art
techniques. Retrieval results clearly highlight the superior performance of the
proposed approach in terms of average precision and average recall.
Keyword: CMU-PIE database, Content-based image retrieval (CBIR), Local
ternary pattern (LTP), Corel database, MIT VisTex database, Stex database
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Dr. Arjun Kumar, Assistant Professor, Department of ECE
Kumar, Arjun (2018). Design and Studies of Band stop Filters Using
Modified CSRR DGS For WLAN Applications. International Conference on
Optical & Wireless Technologies (pp.467-475).
Abstract: In this paper various dumbbell shaped defected ground structure
(DB-DGS) are compared with complementary split ring resonator DB-DGS
which has sharp roll off factor as compared to other DB-DGS and a one pole
Band stop filter with modified complementary split ring resonator (CSRR) DB-
DGS has been proposed with compact size 0.12 x 0.28 and low return loss
in passband at 2.4GHz. The proposed filter is fabricated and measured with
insertion loss of -28dB in stopband and -0.8dB return loss.
Keyword: DGS (Defected ground structure), modified CSRR, Band stop,
HFSS, High frequency structure simulator
Kumar, Arjun (2018). An offset CPW-fed triple-band circularly polarized
printed antenna for multiband wireless applications. Int. J. Electron. Commun.
(AEÜ), 131-141.
Abstract: An offset coplanar waveguide (CPW)-fed triple-band circularly
polarized tilted asymmetrical E-shaped printed antenna for multiband wireless
applications is presented in this paper. The antenna mainly consists of a tilted
asymmetrical E-shaped patch and excite by a 50 Ω offset CPW feed line using
a transformer for impedance matching to generate wide quad operating bands.
By properly embedding rectangular slots in the tilted asymmetrical shaped
patch and triangular stubs loaded modified CPW ground plane, the antenna
reveals triple-band circular polarization (CP) features. Numerical analysis and
experimental validation of the antenna structure have been carried out and
results are presented. The mechanism of triple-band CP operation, analysis of
surface current distributions, design procedure and parametric study of the
design is discussed in detail. It is well suited for the application of UMTS-
2100, 3.5/5.5 GHz WiMAX, 5.2/5.8 GHz WLAN, ITS, downlink of X band
satellite communication, and ITU 8 GHz bands.
Keyword: Circular polarization, E-shaped patch, Printed antenna, Wireless
communication frequencies
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Ashish Kumar, Research Scholar, Department of ECE
Kumar, Ashish (2018). A Wavelet Transform-Based Filter Bank Architecture
for ECG Signal Denoising. Advances in Intelligent Systems and Computing (pp.
249-255).
Abstract: In the present work, a wavelet transform-based filter bank
architecture suitable for ECG signal denoising is proposed. Firstly, wavelet
transform functions are used to filter the signals in Matlab R2013b, and then,
the resulting signal is converted into 16-bit binary data. This data is used
further as an input of QRS detection block. Modified architecture contains only
three low-pass filters and a high-pass filter, which is less compared to
previously designed architectures. One of the key advantages of the proposed
architecture is that no multiplexer and multiplier circuits are required for the
further processing. The proposed architecture consumes less area and is
relatively fast compared to previously designed architectures.
Keyword: Cardiovascular diseases (CVDs), Electrocardiogram (ECG)
Kumar, Ashish (2016). A Robust Digital Image Watermarking Algorithm Using
DWT and SVD. In Pant M., Ray K., Sharma T., Rawat S. & Bandyopadhyay A.
(Eds), Soft Computing: Theories and Applications. Advances in Intelligent
Systems and Computing (pp. 25-36). vol 583. Singapore.
Abstract: A robust digital image watermarking method based on Discrete
Wavelet Transform (DWT) and Singular Value Decomposition (SVD) is
proposed in the present work. In this method, first, the original image of size 256
× 256 is DWT decomposed into the third level using Haar wavelet providing the
four sub-bands LL3, LH3, HL3, and HH3. After that, SVD is applied on these
sub-bands to get the diagonal matrices of singular values. The watermark image
is then embedded in these singular values of the four sub-bands. Proposed
algorithm is simulated using MATLAB v. 2013 and the results show that the
PSNR value obtained is 84.25 which is in the range of 0.1–0.11 (of the scale
factor). The PSNR value obtained for the current work is better compared to the
previous approaches.
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Furthermore, the obtained results also show that using the present method the
watermark image can be extracted properly even when the watermarked image is
under various attacks like rotation, motion blur, Gaussian noise, gamma
correction, rescaling, cropping, Gaussian blur, contrast adjustment, histogram
equalization etc.
Keyword: Digital image watermarking Discrete wavelet transform (DWT) Haar
wavelet Singular value decomposition (SVD) Median filter
Kumar, Ashish (2017). A filter bank architecture based on wavelet transform
for ECG signal denoising. 4th IEEE International Conference on Signal
Processing, Computing and Control (pp. 212-215).
Abstract: One of the most important aspect of the electrocardiogram (ECG)
signal processing is the removal off noise from the signals. In the present work a
filter bank architecture based on wavelet transform is proposed for this purpose.
Proposed design uses four levels of wavelet transform based filter bank for the
ECG signals denoising. A digited ECG signal is an applied as an input to the
four level of wavelet transform based filter bank that separates the ECG signal
from the noise. Obtained results show that the proposed architecture requires
less hardware, small area on the chip and lower cost compared to the previously
designed architecture.
Keyword: Electrocardiogram, Integrated Circuit, Wavelet Transform
Ashish Kumar (2017). Hamming filter design for ECG signal detection and
processing using co-simulation. 2017 International Conference on Computing,
Communication and Automation (pp. 212-215). Greater Noida.
Abstract: Present work proposes a new method for automatic detection of the
QRS complex wave of an ECG signal using digital signal processing (DSP)
technique. The main focus in this work is to remove the noises that interfere with
the ECG signal. For this purpose, a Hamming window FIR filter is used for the
removal of Power line and base line drift noises. Firstly, Noise detection is done
using the bit error rate measurement (In bit error rate measurement, two signals
of the same type are used, out of which one is containing noisy signal and other
is a filtered signal. The value of bit error rate lies between 0 and 1; if value is
more close to 1 then presence of noise is maximum). After that Noise filtering is
the next step. In filtering of the ECG signal, we have used one band stop filter
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and one low pass filter. These filters are used to remove 60 Hz power line and
0.5 Hz baseline wander noises. Data has been taken from the MIT/BIH
arrhythmias database for the performance analysis of the present design. For the
detection of the ECG signal, data is first converted into 16 bit input logical data.
Co-simulation technique is used to simulate the Hardware Description Language
(HDL) module with Modalism software in real time systems Final step of the
present work is the QRS detection. A new method is used to detect the QRS
wave which includes the heart rate calculation and R-R time interval. Several
analyses performed for the detection of ECG signal verify that Co-simulation is
a suitable method to check the HDL module for real time systems.
Keyword: Implantable cardiac pacemaker (ICP), Wavelet based ECG detector,
Biorthogonal 2.2 wavelet, MATLAB, VHDL
Kumar, Ashish (2017). Simplified R-peak detection algorithm of an ECG
Signal using Daubechies 20 Wavelet Transform. International Conference
Nanotechnology for Instrumentation and Measurement Workshop.
Abstract: In this manuscript, a simplified R-peak detection algorithm is
proposed. Firstly, ECG signal is denoised using Daubechies 20 wavelet
transform based wavelet filter bank. The use of derivative and thresholding
makes the R-peak detection simple and accurate. The proposed algorithm
achieved an overall R-peak detection rate of 99.77% on the MIT-BIH database.
The individual R-peak detection rate of the individual ECG signal varies from
98.64% to 100%.
Keyword: Electrocardiogram, R-peak detector, wavelet filter bank
Kumar, Ashish (2018). Design of a Biorthogonal Wavelet Transform Based R
-Peak Detection and Data Compression Scheme for Implantable Cardiac
Pacemaker Systems. Journal of Medical Systems, 102.
Abstract: Bradycardia can be modulated using the cardiac pacemaker, an
implantable medical device which sets and balances the patient’s cardiac
health. The device has been widely used to detect and monitor the patient’s
heart rate. The data collected hence has the highest authenticity assurance and
is convenient for further electric stimulation. In the pacemaker, ECG detector
is one of the most important elements. The device is available in its new digital
form, which is more efficient and accurate in performance with the added
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advantage of economic power consumption platform. In this work, a joint
algorithm based on biorthogonal wavelet transform and run-length encoding
(RLE) is proposed for QRS complex detection of the ECG signal and
compressing the detected ECG data. Biorthogonal wavelet transform of the
input ECG signal is first calculated using a modified demand-based filter bank
architecture which consists of a series combination of three lowpass filters with
a high pass filter. Low pass and high pass filters are realized using a linear
phase structure which reduces the hardware cost of the proposed design
approximately by 50%. Then, the location of the R-peak is found by comparing
the denoised ECG signal with the threshold value. The proposed R-peak
detector achieves the highest sensitivity and positive predictivity of 99.75 and
99.98 respectively with the MIT-BIH arrhythmia database. Also, the proposed
R-peak detector achieves a comparatively low data error rate (DER) of 0.002.
The use of RLE for the compression of detected ECG data achieves a higher
compression ratio (CR) of 17.1. To justify the effectiveness of the proposed
algorithm, the results have been compared with the existing methods, like
Huffman coding/simple predictor, Huffman coding/adaptive, and slope
predictor/fixed length packaging.
Keyword: Electrocardiogram (ECG), Run-length encoding (RLE), Low pass
and High pass filter, Continuous wavelet transform (CWT), Discrete wavelet
transform (DWT), Wavelet filter bank (WFB)
Kumar, Ashish (2018). Design of high performance QRS complex detector for
wearable healthcare devices using biorthogonal spline wavelet transform. ISA
Transactions, 81, 222-230.
Abstract: A high performance QRS complex detector applicable for wearable
healthcare devices is proposed in the present work. Since, higher SNR results in
better detection accuracy and lesser number of coefficients reduces the
hardware resources as well as power dissipation during on chip implementation.
Biorthogonal spline wavelet transform is chosen for the proposed detector as it
has high signal to noise ratio (SNR) and uses only four coefficients for
decomposition. In the proposed approach, a Biorthogonal wavelet filter bank
with fourth level decomposition is first used to separate the different frequency
components and then a fourth level wavelet filter bank is used to get the
denoised electrocardiogram (ECG) signals. Wavelet filter bank outputs are
multiplied, and soft threshold method is applied to get the QRS complex peaks
by the QRS complex peak detector block. Add and shift multiplier used in the
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earlier designs has been replaced by a Booth multiplier in our approach to
achieve the higher performance. Booth multiplier and QRS complex peak
detector blocks have been designed for low hardware complexity, high
performance and accurate detection of the QRS complex peaks. Time interval
between the consecutive QRS peaks is calculated using the R-R peak time
calculator block and the heart rate (HR) by the HR calculator block. Heart Rate
Variability (HRV) and arrhythmia are detected based on these heart rate
calculations. Proposed design has been tested for its robustness on multiple
datasets (namely, MIT-BIH arrhythmia, MIT-BIH noise stress test, and MIT-
BIH atrial fibrillation databases). Sensitivity of 99.31%, positive predictivity of
99.19% and the Detection Error Rate (DER) of 1.49% shown by the proposed
design makes it preferable for QRS complex detectors used in wearable
healthcare devices.
Keyword: QRS complex
Kumar, Ashish (2018). Design of High-Performance ECG Detector for
Implantable Cardiac Pacemaker Systems using Biorthogonal Wavelet
Transform. Circuits Systems and Signal Processing, 3995-4014.
Abstract: A digital electrocardiogram (ECG) detector with low power
consumption and high performance based on biorthogonal 2.2 wavelet
transform and applicable for the modern implantable cardiac pacemakers is
proposed in the present work. Biorthogonal 2.2 wavelet transform is chosen
due to its high SNR, less number of coefficients, resemblance of shape with
ECG wave and ability to increase QRS complex detection performance.
Architecture of the proposed ECG detector includes modified biorthogonal2.2
wavelet filter bank and a modified soft threshold-based QRS complex detector.
Three low-pass filters and one high-pass filter with pipelined architecture are
used which are lesser than the earlier designed detectors. Various blocks of
proposed detector are designed to denoise the input ECG signal and then to find
the correct location of R-wave. Verilog hardware description language for
design entry, Models embedded in XilinxISEv.14.1for simulation, Virtex-6
FPGAs for synthesis and Xilinx ISE tools are used to measure the performance,
area and power of the proposed ECG detector and its constituent blocks.
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A low detection error rate of 0.13%, positive predictivity (P+) of 99.94% and
sensitivity (Se) of 99.92% are achieved for the proposed ECG
Keyword: Implantable cardiac pacemaker (ICP), Wavelet-based ECG detector
biorthogonal 2.2 wavelet, MATLAB, Verilog HDL, Xilinx
Kumar, Ashish (2018). Design of wavelet transform based electrocardiogram
monitoring system. ISA Transactions, 80, 381-398.
Abstract: The new age advancements in information technology due to
materials and integrated circuit (IC) technologies and their applications in
biomedical sciences have made the healthcare facilities more compact and
affordable for the aging population. Market trends in healthcare and related
devices indicate a sharp rise in their demand. Hence the researchers have
converged the efforts on designing more smart and advanced medical devices
using IC technology. Among these devices, cardiac pacemakers have become
a recurrent biomedical device which is engrafted in the human body to detect
and monitor a person's heart beating rate. The data thus generated is processed
for various medical usages and devices via wireless methods. Cardiovascular
diseases (CVDs) or diseases related to the heart are due to abnormalities or
disorders of the heart and blood vessels. Till date, limited literature is available
which focuses on a single technique that can perform all of the ECG signal
denoising, ECG detection, lossless data compression and wireless
transmission. In this work, a joint approach for denoising, detection,
compression, and wireless transmission of ECG signal is proposed. The
modified biorthogonal wavelet transform is used for denoising, detection and
lossless compression of ECG signal. To reduce the circuit complexity,
biorthogonal wavelet transform is realized using linear phase structure.
Further, it is found in this work that the usage of modified biorthogonal
wavelet transform increases the detection accuracy and CR of the proposed
design. Also, in this work, the Wi-Fi-based wireless protocol is used for
compressed data transmission. The proposed ECG detector achieves the
highest sensitivity and positive predictivity of 99.95% and 99.92%,
respectively, with the MIT-BIH arrhythmia database. The use of modified
biorthogonal 3.1 wavelet transform and run-length encoding (RLE) for the
compression of ECG data achieves a higher compression ratio (CR) of 6.271.
To justify the effectiveness of the proposed algorithm, which uses modified
biorthogonal wavelet 3.1transform, the results are compared with the existing
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methods, namely, Huffman coding/simple predictor, Huffman coding/adaptive,
and slope predictor/fixed length packaging.
Keyword: Cardiovascular disease, Electrocardiogram, MIT-BIH database,
Discrete wavelet transform,
Kumar, Ashish (2018). From Pacemaker to Wearable: Techniques for ECG
Detection Systems. Journal of Medical Systems, 1-17.
Abstract: With the alarming rise in the deaths due to cardiovascular diseases
(CVD), present medical research scenario places notable importance on
techniques and methods to detect CVDs. As adduced by world health
organization, technological proceeds in the field of cardiac function assessment
have become the nucleus and heart of all leading research studies in CVDs in
which electrocardiogram (ECG) analysis is the most functional and convenient
tool used to test the range of heart-related irregularities. Most of the approaches
present in the literature of ECG signal analysis consider noise removal, rhythm
-based analysis, and heartbeat detection to improve the performance of a
cardiac pacemaker. Advancements achieved in the field of ECG segments
detection and beat classification have a limited evaluation and still require
clinical approvals. In this paper, approaches on techniques to implement on-
chip ECG detector for a cardiac pacemaker system are discussed. Moreover,
different challenges regarding the ECG signal morphology analysis deriving
from medical literature is extensively reviewed. It is found that robustness to
noise, wavelet parameter choice, numerical efficiency, and detection
performance are essential performance indicators required by a state-of-the-art
ECG detector. Furthermore, many algorithms described in the existing
literature are not verified using ECG data from the standard databases. Some
ECG detection algorithms show very high detection performance with the total
number of detected QRS complexes. However, the high detection performance
of the algorithm is verified using only a few datasets. Finally, gaps in current
advancements and testing are identified, and the primary challenge remains to
be implementing bullseye test for morphology analysis evaluation.
Keyword: Electrocardiogram (ECG), ECG detector, Body sensor network
(BSN). Bio signal processor (BSP), Bio signal processor (BSP), Discrete
wavelet transform (DWT)
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Kumar, Ashish (2018). Heart rate monitoring and therapeutic devices: A
wavelet transform based approach for the modeling and classification of
congestive heart failure. ISA Transactions, 79, 239-250.
Abstract: Heart rate monitoring and therapeutic devices include real-time
sensing capabilities reflecting the state of the heart. Current circuitry can be
interpreted as a cardiac electrical signal compression algorithm representing the
time signal information into a single event description of the cardiac activity. It
is observed that some detection techniques developed for ECG signal detection
like artificial neural network, genetic algorithm, Hilbert transform, hidden
Markov model are some sophisticated algorithms which provide suitable results
but their implementation on a silicon chip is very complicated. Due to less
complexity and high performance, wavelet transform based approaches are
widely used. In this paper, after a thorough analysis of various wavelet
transforms, it is found that Biorthogonal wavelet transform is best suited to
detect ECG signal's QRS complex. The main steps involved in ECG detection
process consist of de-noising and locating different ECG peaks using adaptive
slope prediction thresholding. Furthermore, the significant challenges involved
in the wireless transmission of ECG data are data conversion and power
consumption. As medical regulatory boards demand a lossless compression
technique, lossless compression technique with a high bit compression ratio is
highly required. Furthermore, in this work, LZMA based ECG data
compression technique is proposed. The proposed methodology achieves the
highest signal to noise ratio, and lowest root mean square error. Also, the
proposed ECG detection technique is capable of distinguishing accurately
between healthy, myocardial infarction, congestive heart failure and coronary
artery disease patients with a detection accuracy, sensitivity, specificity, and
error of 99.92%, 99.94%, 99.92% and 0.0013, respectively. The use of LZMA
data compression of ECG data achieves a high compression ratio of 18.84. The
advantages and effectiveness of the proposed algorithm are verified by
comparing with the existing methods.
Keyword: Heart rate monitoring, Congestive heart failure, Electrocardiogram,
Biorthogonal wavelet transform, Wavelet filter bank
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Kumar, Ashish (2019). Design of efficient fractional operator for ECG signal
detection in implantable cardiac pacemaker systems. International Journal of
Circuit Theory and Applications.
Abstract: A low power and high‐performance digital electrocardiogram (ECG)
detector has become a basic requirement in modern implantable cardiac
pacemakers. A fractional operator‐based digital ECG detector for modern
pacemaker systems is proposed in this work. Instead of conventional
thresholding, an adaptive slope prediction threshold is utilized for the detection
of ECG peaks. A stochastic search‐based algorithm, namely, cuckoo search
algorithm, is used to design an optimal fractional operator that is used for ECG
denoising. It has been found that the proposed adaptive slope prediction
threshold increases the QRS complex detection performance. A low detection
error rate (DER) ranges from 0.01% to 0.56%, positive predictivity (P+) ranges
from 99.32% to 99.98%, sensitivity (Se) ranges from 99.45% to 99.98%, and a
detection accuracy (Acc) ranges from 99.43% to 99.96% for different databases
are achieved for the proposed ECG detector, which is better compared with the
existing ECG detectors. The proposed design of fractional order operator based
on the lattice wave digital filter (LWDF) requires a minimum number of the
multipliers for its structural realization.
Keyword: Biomedical signals, electrocardiography, Fractional order operators,
Heart rate variability, Lattice wave digital filter
Kumar, Ashish (2019). Efficient QRS complex detection algorithm based on
Fast Fourier Transform. Biomedical Engineering Letters, 9(1), 145-151.
Abstract: An ECG signal, generally filled with noise, when de-noised, enables a
physician to effectively determine and predict the condition and health of the
heart. This paper aims to address the issue of denoising a noisy ECG signal
using the Fast Fourier Transform based bandpass filter. Multi-stage adaptive
peak detection is then applied to identify the R-peak in the QRS complex of the
ECG signal. The result of test simulations using the MIT/BIH Arrhythmia
database shows high sensitivity and positive predictivity (PP) of 99.98 and
99.96% respectively, confirming the accuracy and reliability of proposed
algorithm for detecting R-peaks in the ECG signal.
Keywords: Electrocardiogram (ECG) Cardiovascular diseases (CVD) Fast
Fourier Transform (FFT)
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Kumar, Ashish (2019). Time–frequency localization using three-tap
biorthogonal wavelet filter bank for electrocardiogram compressions. Biomedical
Engineering Letters, 3(3), 407-411.
Abstract: A joint time–frequency localized three-band biorthogonal wavelet
filter bank to compress Electrocardiogram signals is proposed in this work.
Further, the use of adaptive thresholding and modified run-length encoding
resulted in maximum data volume reduction while guaranteeing reconstructing
quality. Using signal-to-noise ratio, compression ratio (CR), maximum absolute
error (EMA), quality score (Qs), root mean square error, compression time (CT)
and percentage root mean square difference the validity of the proposed approach
is studied. The experimental results deduced that the performance of the
proposed approach is better when compared to the two-band wavelet filter bank.
The proposed compression method enables loss-less data transmission of medical
signals to remote locations for therapeutic usage.
Keyword: Electrocardiogram, Biorthogonal wavelet transform, Wavelet filter
bank, Electrocardiogram compression
Dr. Manjeet Kumar, Assistant Professor, Department of ECE
Kumar, Manjeet (2018). A Wavelet Transform-Based Filter Bank
Architecture for ECG Signal Denoising. Advances in Intelligent Systems and
Computing (pp. 249-255).
Abstract: In the present work, a wavelet transform-based filter bank
architecture suitable for ECG signal denoising is proposed. Firstly, wavelet
transform functions are used to filter the signals in Matlab R2013b, and then,
the resulting signal is converted into 16-bit binary data. This data is used further
as an input of QRS detection block. Modified architecture contains only three
low-pass filters and a high-pass filter, which is less compared to previously
designed architectures. One of the key advantages of the proposed architecture
is that no multiplexer and multiplier circuits are required for the further
processing. The proposed architecture consumes less area and is relatively fast
compared to previously designed architectures.
Keyword: Cardiovascular diseases (CVDs), Electrocardiogram (ECG)
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Kumar, Manjeet (2017). A filter bank architecture based on wavelet transform
for ECG signal denoising. 4th IEEE International Conference on Signal
Processing, Computing and Control (pp. 212-215).
Abstract: One of the most important aspect of the electrocardiogram (ECG)
signal processing is the removal off noise from the signals. In the present work a
filter bank architecture based on wavelet transform is proposed for this purpose.
Proposed design uses four levels of wavelet transform based filter bank for the
ECG signals denoising. A digited ECG signal is an applied as an input to the
four level of wavelet transform based filter bank that separates the ECG signal
from the noise. Obtained results show that the proposed architecture requires
less hardware, small area on the chip and lower cost compared to the previously
designed architecture.
Keyword: Electrocardiogram, Integrated Circuit, Wavelet Transform
Kumar, Manjeet (2017). Design of Notch and Multi-Notch FIR Filters Using
Fractional Derivative Constraints. International Conference on Signal Processing
& Integrated Networks (pp. 334-339).
Abstract: In this paper, the design of 1-dimensional (1-D) finite impulse
response (FIR) notch filters is achieved constraint to fractional order derivatives.
In order to actualize the ideal frequency response, fractional derivative
constraints are imposed such that there is no deviation in fractional derivative of
designed frequency response at prescribed frequency points. The divergence in
designed frequency response and ideal frequency response is curtailed using
conventional least square design method along with Lagrange multiplier to attain
closed loop filter coefficients. The design of 1-D notch filter and 1-D m
Keyword: 1-D FIR filter, Notch filter, Fractional derivative constraints,
Lagrange multiplier, Grunwald Letnikov definition
Kumar, Manjeet (2017). Design of optimal 2-D FIR differentiators with
quadrantally symmetric properties using the L1-method. International
Conference on Signal Processing and Communication Systems (pp. 1-6).
Abstract: In this paper the design of 2-dimensional finite impulse response (2-D
FIR) digital differentiator (DD) with quadrantally odd symmetric impulse
response is presented. The L1-method is developed to design the 2-D system and
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minimize the L1-error. The design problem of 2-D FIR-DD is formulated as an
optimization problem in order to compute the system coefficients with
quadrantally odd symmetric properties. Finally, the design examples of 2-D
differentiator of different order is demonstrated and analyzed in terms of the L1-
error and elapsed time. The proposed 2-D FIR L1-DD is also compared with the
existing 2-D differentiators designed using metaheuristic techniques and is
observed to yield least L1-error
Keyword: 2-D Digital differentiator, Finite impulse response, Quandrantally
symmetric, L1-method
Kumar, Manjeet (2017). Simplified R-peak detection algorithm of an ECG
Signal using Daubechies 20 Wavelet Transform. International Conference
Nanotechnology for Instrumentation and Measurement Workshop.
Abstract: In this manuscript, a simplified R-peak detection algorithm is
proposed. Firstly, ECG signal is denoised using Daubechies 20 wavelet
transform based wavelet filter bank. The use of derivative and thresholding
makes the R-peak detection simple and accurate. The proposed algorithm
achieved an overall R-peak detection rate of 99.77% on the MIT-BIH database.
The individual R-peak detection rate of the individual ECG signal varies from
98.64% to 100%.
Keyword: Electrocardiogram, R-peak detector, Wavelet filter bank
Kumar, Manjeet (2018). Optimal Design of IIR Filter Using Dragonfly
Algorithm. International Conference on Signals, Machines and Automation (pp.
211-223).
Abstract: The field of infinite impulse response (IIR) filter design mainly
focused on the proper selection of filter parameters from the numerous possible
combinations. This filter design problem is based on determining the optimal
set of parameters for unknown model such that it’s closely matches with the
parameters of the benchmark filter. Many researchers have designed IIR filters
using gradient based techniques like least mean square (LMS) method, etc. But,
these gradient-based techniques have drawback of getting trapped into local
solutions. To overcome this problem, evolutionary optimization techniques are
used, which give global solutions. This paper utilizes a novel optimization
technique known as dragonfly algorithm (DA) for the computation of the
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parameters of unknown IIR filter. Two benchmark functions are considered to
prove the efficacy of the DA for IIR filter design problem. The results obtained
using DA are compared with three existing algorithms namely, cat swarm
optimization (CSO), particle swarm optimization (PSO), and bat algorithm
(BA). The obtained results verify that the performance of DA-based IIR filter
design is superior to that achieved by PSO, CSO, and BA.
Keyword: IIR filter, Dragonfly algorithm, Cat swarm optimization, Particle
swarm optimization
Kumar, Manjeet (2017). Adaptive infinite impulse response system
identification using modified-interior search algorithm with Levy flight. ISA
Transactions, 266-279.
Abstract: In this paper, a new meta-heuristic optimization technique called
interior search algorithm (ISA) with Levy flight is proposed and applied to
determine the optimal parameters of an unknown infinite impulse response (IIR)
system for the system identification problem. ISA is based on aesthetics, which is
commonly used in interior design and decoration processes. In ISA, composition
phase and mirror phase are applied for addressing the nonlinear and multimodal
system identification problems. System identification using modified-ISA (M-
ISA) based method involves faster convergence, single parameter tuning and
does not require derivative information because it uses a stochastic random
search using the concepts of Levy flight. A proper tuning of control parameter
has been performed in order to achieve a balance between intensification and
diversification phases. In order to evaluate the performance of the proposed
method, mean square error (MSE), computation time and percentage
improvement are considered as the performance measure. To validate the
performance of M-ISA based method, simulations has been carried out for three
benchmarked IIR systems using same order and reduced order system. Genetic
algorithm (GA), particle swarm optimization (PSO), cat swarm optimization
(CSO), cuckoo search algorithm (CSA), differential evolution using wave let
mutation (DEWM), firefly algorithm (FFA), craziness based particles warm
optimization (CRPSO), harmony search (HS) algorithm, opposition based
harmony search (OHS) algorithm, hybrid particle swarm optimization
gravitational search algorithm (HPSO-GSA) and ISA are also used to model the
same examples and simulation results are compared.
Obtained results confirm the efficiency of the proposed method.
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Keyword: Infinite impulse response (IIR) system, Interior search algorithm
(ISA), System identification, Meta-heuristic and Levy flight
Kumar, Manjeet (2017). Design of fractional order differentiator using type-III
and type-IV discrete cosine transform. Engineering Science and Technology: An
International Journal, 51-58.
Abstract: In this paper, an interpolation method based on discrete cosine
transform (DCT) is employed for digital finite impulse response-fractional order
differentiator (FIR-FOD) design. Here, a fractional order digital differentiator is
modelled as finite impulse response (FIR) system to get an optimized frequency
response that approximates the ideal response of a fractional order differentiator.
Next, DCT-III and DCT-IV are utilized to determine the filter coefficients of FIR
filter that compute the Fractional derivative of a given signal. To improve the
frequency response of the proposed FIR-FOD, the filter coefficients are further
modified using windows. Several design examples are presented to demonstrate
the superiority of the proposed method. The simulation results have also been
compared with the existing FIR-FOD design methods such as DFT interpolation,
radial basis function (RBF) interpolation, DCT-II interpolation and DST
interpolation methods. The result reveals that the proposed FIR-FOD design
technique using DCT-III and DCT-IV outperforms DFT interpolation, RBF
interpolation, DCT-II interpolation and DST interpolation methods in terms of
magnitude error.
Keyword: Fractional order differentiator, Discrete Fourier transform, Fractional
derivative, Finite impulse response, Discrete cosine transform, Discrete sine
transform
Kumar, Manjeet (2017). Design of minimum multiplier fractional order
differentiator based on lattice wave digital filter. ISA Transactions, 404-413.
Abstract: In this paper, a novel design of fractional order differentiator (FOD)
based on lattice wave digital filter (LWDF) is proposed which requires minimum
number of multipliers of its structural realization. Firstly, the FOD design
problem is formulated as an optimization problem using the transfer function of
lattice wave digital filter. Then, three optimization algorithms, namely, genetic
algorithm (GA), particle swarm optimization (PSO) and cuckoo search algorithm
(CSA)are applied to determine the optimal LWDF coefficients. The realization of
FOD using LWD structure increases the design accuracy, as only N number of
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of coefficients are to be optimized or Nth order FOD. Finally, two design
examples of 3rd and 5th order lattice wave digital fractional order differentiate or
(LWDFOD) are demonstrated to justify the design accuracy. The performance
analysis of the proposed design is carried out based on magnitude response,
absolute magnitude error (dB), root mean square(RMS)magnitude error,
arithmetic complexity, con- vergence profile and computation time. Simulation
results are attained to show the comparison of the proposed LWDFOD with the
published works and it is observed that an improvement of 29% is obtained in the
proposed design. The proposed LWDFOD approximates the idea FOD and
surpasses the existing ones reasonably well in mid and high frequency range,
thereby making the proposed LWDFOD a promising technique for the design of
digital FODs.
Keyword: Lattice wave digital filters, Fractional order differentiator, Particle
swarm optimization, Cuckoo search algorithm, Minimum multiplier, Genetic
algorithm
Kumar, Manjeet (2018). Adaptive infinite impulse response system
identification using teacher learner-based optimization algorithm. Applied
Intelligence, 49(5), 1785-1802.
Abstract: In this paper, optimal coefficients of unknown infinite impulse
response (IIR) system are computed by utilizing a new population-based
algorithm called teacher learner-based optimization (TLBO) for system
identification problem. TLBO algorithm is inspired by the teaching learning
process in the classroom and is free from algorithmic specific parameters. In
TLBO, difference mean is calculated for each learner, which is the difference
between the existing mean result of the class and the teacher. This difference
mean is updated in each iteration and is responsible for maintaining the
diversity of this algorithm. System identification problem is based on
minimizing the mean square error (MSE) function and finding the optimal
coefficients of an unknown IIR system. The MSE is the difference between the
outputs of an adaptive IIR system and an unknown IIR system. Exhaustive
simulations have been done for finding the unknown system coefficients of
same order and reduced order case. Four benchmark functions are tested using
TLBO algorithm to verify its efficacy for system identification problem. In
order to prove the effectiveness of the applied algorithm, evaluated coefficients
and MSE values are compared with that of the genetic algorithm (GA), particle
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swarm optimization (PSO), cat swarm optimization (CSO), cuckoo search
algorithm (CSA), firefly algorithm (FFA), bat algorithm (BAT), differential
evolution with wavelet mutation (DEWM), harmony search (HS) and
opposition based harmony search (OHS) algorithm.
Kumar, Manjeet (2018). Design of a Biorthogonal Wavelet Transform Based
R-Peak Detection and Data Compression Scheme for Implantable Cardiac
Pacemaker Systems. Journal of Medical Systems, 102.
Abstract: Bradycardia can be modulated using the cardiac pacemaker, an
implantable medical device which sets and balances the patient’s cardiac health.
The device has been widely used to detect and monitor the patient’s heart rate.
The data collected hence has the highest authenticity assurance and is
convenient for further electric stimulation. In the pacemaker, ECG detector is
one of the most important elements. The device is available in its new digital
form, which is more efficient and accurate in performance with the added
advantage of economic power consumption platform. In this work, a joint
algorithm based on biorthogonal wavelet transform and run-length encoding
(RLE) is proposed for QRS complex detection of the ECG signal and
compressing the detected ECG data. Biorthogonal wavelet transform of the
input ECG signal is first calculated using a modified demand-based filter bank
architecture which consists of a series combination of three lowpass filters with
a high pass filter. Low pass and high pass filters are realized using a linear
phase structure which reduces the hardware cost of the proposed design
approximately by 50%. Then, the location of the R-peak is found by comparing
the denoised ECG signal with the threshold value. The proposed R-peak
detector achieves the highest sensitivity and positive predictivity of 99.75 and
99.98 respectively with the MIT-BIH arrhythmia database. Also, the proposed
R-peak detector achieves a comparatively low data error rate (DER) of 0.002.
The use of RLE for the compression of detected ECG data achieves a higher
compression ratio (CR) of 17.1. To justify the effectiveness of the proposed
algorithm, the results have been compared with the existing methods, like
Huffman coding/simple predictor, Huffman coding/adaptive, and slope
predictor/fixed length packaging.
Keyword: Electrocardiogram (ECG), Run-length encoding (RLE), Low pass
and High pass filter, Continuous wavelet transform (CWT), Discrete wavelet
transform (DWT), Wavelet filter bank (WFB)
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Kumar, Manjeet (2018). Design of wavelet transform based electrocardiogram
monitoring system. ISA Transactions, 80, 381-398.
Abstract: The new age advancements in information technology due to
materials and integrated circuit (IC) technologies and their applications in
biomedical sciences have made the healthcare facilities more compact and
affordable for the aging population. Market trends in healthcare and related
devices indicate a sharp rise in their demand. Hence the researchers have
converged the efforts on designing more smart and advanced medical devices
using IC technology. Among these devices, cardiac pacemakers have become a
recurrent biomedical device which is engrafted in the human body to detect and
monitor a person's heart beating rate. The data thus generated is processed for
various medical usages and devices via wireless methods. Cardiovascular
diseases (CVDs) or diseases related to the heart are due to abnormalities or
disorders of the heart and blood vessels. Till date, limited literature is available
which focuses on a single technique that can perform all of the ECG signal
denoising, ECG detection, lossless data compression and wireless transmission.
In this work, a joint approach for denoising, detection, compression, and
wireless transmission of ECG signal is proposed. The modified biorthogonal
wavelet transform is used for denoising, detection and lossless compression of
ECG signal. To reduce the circuit complexity, biorthogonal wavelet transform
is realized using linear phase structure. Further, it is found in this work that the
usage of modified biorthogonal wavelet transform increases the detection
accuracy and CR of the proposed design. Also, in this work, the Wi-Fi-based
wireless protocol is used for compressed data transmission. The proposed ECG
detector achieves the highest sensitivity and positive predictivity of 99.95% and
99.92%, respectively, with the MIT-BIH arrhythmia database. The use of
modified biorthogonal 3.1 wavelet transform and run-length encoding (RLE)
for the compression of ECG data achieves a higher compression ratio (CR) of
6.271. To justify the effectiveness of the proposed algorithm, which uses
modified biorthogonal wavelet 3.1transform, the results are compared with the
existing methods, namely, Huffman coding/simple predictor, Huffman coding/
adaptive, and slope predictor/fixed length packaging.
Keyword: Cardiovascular disease, Electrocardiogram, MIT-BIH database,
Discrete wavelet transform,
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Kumar, Manjeet (2018). Fractional order FIR differentiator design using
particle swarm optimization algorithm. International Journal of Numerical
Modelling, 32(2), 2514.
Abstract: In this paper, a population-based evolutionary optimization
technique called particle swarm optimization (PSO) is applied for the
optimization of system coefficients of the finite impulse response-fractional
order differentiator (FIR-FOD) design problem. The conventional FIR-FOD
design methods are not efficient for nonlinear, nonuniform, and multimodal
design problem due to getting trapped in local optimal solution. To overcome
this problem, global optimization techniques are required. The superior FIR-
FOD design capability of the proposed method is evident from the results
obtained through an exhaustive simulation study. Simulation results
demonstrate that the proposed FOD design technique using PSO outperforms
the genetic algorithm in terms of design accuracy (magnitude error and phase
error), speed of convergence, and optimal solution. The simulation results have
also been compared with those obtained by the conventional FOD design
methods such as DFT interpolation, radial basis function (RBF) interpolation,
DCT interpolation, and DST interpolation methods
Keyword: Evolutionary optimization, Fractional order differentiator, Genetic
algorithm, Particle swarm optimization
Kumar, Manjeet (2018). From Pacemaker to Wearable: Techniques for ECG
Detection Systems. Journal of Medical Systems, 1-17.
Abstract: With the alarming rise in the deaths due to cardiovascular diseases
(CVD), present medical research scenario places notable importance on
techniques and methods to detect CVDs. As adduced by world health
organization, technological proceeds in the field of cardiac function assessment
have become the nucleus and heart of all leading research studies in CVDs in
which electrocardiogram (ECG) analysis is the most functional and convenient
tool used to test the range of heart-related irregularities. Most of the approaches
present in the literature of ECG signal analysis consider noise removal, rhythm-
based analysis, and heartbeat detection to improve the performance of a cardiac
pacemaker. Advancements achieved in the field of ECG segments detection and
beat classification have a limited evaluation and still require clinical approvals.
In this paper, approaches on techniques to implement on-chip ECG detector for
a cardiac pacemaker system are discussed. Moreover, different challenges
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regarding the ECG signal morphology analysis deriving from medical literature
is extensively reviewed. It is found that robustness to noise, wavelet parameter
choice, numerical efficiency, and detection performance are essential
performance indicators required by a state-of-the-art ECG detector.
Furthermore, many algorithms described in the existing literature are not
verified using ECG data from the standard databases. Some ECG detection
algorithms show very high detection performance with the total number of
detected QRS complexes. However, the high detection performance of the
algorithm is verified using only a few datasets. Finally, gaps in current
advancements and testing are identified, and the primary challenge remains to
be implementing bullseye test for morphology analysis evaluation.
Keyword: Electrocardiogram (ECG), ECG detector, Body sensor network
(BSN). Bio signal processor (BSP), Bio signal processor (BSP), Discrete
wavelet transform (DWT)
Kumar, Manjeet (2018). Heart rate monitoring and therapeutic devices: A
wavelet transform based approach for the modeling and classification of
congestive heart failure. ISA Transactions, 79, 239-250.
Abstract: Heart rate monitoring and therapeutic devices include real-time
sensing capabilities reflecting the state of the heart. Current circuitry can be
interpreted as a cardiac electrical signal compression algorithm representing the
time signal information into a single event description of the cardiac activity. It
is observed that some detection techniques developed for ECG signal detection
like artificial neural network, genetic algorithm, Hilbert transform, hidden
Markov model are some sophisticated algorithms which provide suitable results
but their implementation on a silicon chip is very complicated. Due to less
complexity and high performance, wavelet transform based approaches are
widely used. In this paper, after a thorough analysis of various wavelet
transforms, it is found that Biorthogonal wavelet transform is best suited to
detect ECG signal's QRS complex. The main steps involved in ECG detection
process consist of de-noising and locating different ECG peaks using adaptive
slope prediction thresholding. Furthermore, the significant challenges involved
in the wireless transmission of ECG data are data conversion and power
consumption. As medical regulatory boards demand a lossless compression
technique, lossless compression technique with a high bit compression ratio is
highly required. Furthermore, in this work, LZMA based ECG data
compression technique is proposed. The proposed methodology achieves the
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highest signal to noise ratio, and lowest root mean square error. Also, the
proposed ECG detection technique is capable of distinguishing accurately
between healthy, myocardial infarction, congestive heart failure and coronary
artery disease patients with a detection accuracy, sensitivity, specificity, and
error of 99.92%, 99.94%, 99.92% and 0.0013, respectively. The use of LZMA
data compression of ECG data achieves a high compression ratio of 18.84. The
advantages and effectiveness of the proposed algorithm are verified by
comparing with the existing methods.
Keyword: Heart rate monitoring, Congestive heart failure, Electrocardiogram,
Biorthogonal wavelet transform, Wavelet filter bank
Kumar, Manjeet (2018). Optimal design of fractional delay FIR filter using
cuckoo search algorithm. Int. J.Circ.Theor.Appl, 46(12), 2364-2379.
Abstract: The conventional gradient-based optimization methods are not
sufficient to optimize nonlinear, multimodal, and nonuniform objective
functions of fractional delay FIR (FD-FIR) filters, and the objective function
cannot converge to the global minimum solution. So, a population-based meta-
heuristic optimization algorithm called as cuckoo search algorithm (CSA) has
been implemented in the design of optimal FD-FIR filter. Cuckoo search
algorithm is based on lifestyle and unique parasitic behavior in egg laying and
breeding of some cuckoo species along with Lévy flight behavior of some birds
and fruit flies. To attain a balance between exploration and exploitation in the
search space, different set of control parameters is tested by simulation.
Extensive simulations were performed to ensure how CSA exploits in the
design of optimal FD-FIR filter. A quantitative assessment of the proposed
CSA-based method is accomplished using several performance metrics such as
magnitude error, convergence rate, and optimal solution. The simulation results
reveal the advantages of the proposed FD filter using CSA compared with the
FD filter designed using evolutionary algorithm like genetic algorithm and
conventional FD filter design methods such as Lagrange, discrete Hartley
transform, discrete Fourier transform, discrete cosine transform, and radial basis
function methods.
Keyword: Cuckoo search algorithm, FD-FIR filter, Lévy flight, Meta-
heuristics, Genetic algorithm
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Kumar, Manjeet (2019). Design of Digital Differentiator Using the L1-Method
and Swarm Intelligence Based Optimization Algorithms. Arabian Journal for
Science and Engineering, 44(3), 1917-1931.
Abstract: In this paper, a novel approach to design the digital linear-phase finite
impulse response (FIR) differentiator is introduced. First, the differentiator
design problem is formulated using the L1-method. Then, the L1 optimality
criterion is applied using the Bat algorithm (BA) and Particle swarm optimization
(PSO) to further optimize the differentiator design. A novel fitness function is
developed based on the L1-error norm which is unique and is liable to produce a
flat response. These techniques are developed in order to minimize the non-
differentiable fitness function. Finally, the simulation results have been presented
for 5th-, 7th- and 11th-order FIR differentiator using the L1-method, PSO-L1 and
BA-L1. The magnitude response of the designed differentiators is analyzed for
different frequency bands on the basis of relative magnitude error computed with
respect to the ideal response. All the reported techniques contribute toward
superior results, when compared with the traditional gradient-based
optimizations, such as the window method, minimax, and least-squares approach.
In addition, the L1-method yields better results for higher-order designs.
Furthermore, the proposed designs are tested on two input signals for their
efficient response.
Keywords: Finite impulse response, L1-error criterion, Digital differentiator, Bat
algorithm, Particle swarm optimization
Kumar, Manjeet (2019). Design of efficient fractional operator for ECG signal
detection in implantable cardiac pacemaker systems. International Journal of
Circuit Theory and Applications.
Abstract: A low power and high‐performance digital electrocardiogram (ECG)
detector has become a basic requirement in modern implantable cardiac
pacemakers. A fractional operator‐based digital ECG detector for modern
pacemaker systems is proposed in this work. Instead of conventional
thresholding, an adaptive slope prediction threshold is utilized for the detection
of ECG peaks. A stochastic search‐based algorithm, namely, cuckoo search
algorithm, is used to design an optimal fractional operator that is used for ECG
denoising. It has been found that the proposed adaptive slope prediction
threshold increases the QRS complex detection performance. A low detection
error rate (DER) ranges from 0.01% to 0.56%, positive predictivity (P+) ranges
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from 99.32% to 99.98%, sensitivity (Se) ranges from 99.45% to 99.98%, and a
detection accuracy (Acc) ranges from 99.43% to 99.96% for different databases
are achieved for the proposed ECG detector, which is better compared with the
existing ECG detectors. The proposed design of fractional order operator based
on the lattice wave digital filter (LWDF) requires a minimum number of the
multipliers for its structural realization.
Keyword: Biomedical signals, Electrocardiography, Fractional order operators,
Heart rate variability, Lattice wave digital filter
Kumar, Manjeet (2019). Design of Optimal Two-Dimensional FIR Filters with
Quadrantally Symmetric Properties Using Vortex Search Algorithm. Journal of
Circuits, Systems and Computers. DOI: 10.1142/S0218126620501558
Abstract: This research paper presents a new evolutionary technique named
vortex search optimization (VSO) to design digital 2D finite impulse response
(FIR) filter for improved performance both in passband and stop-band regions.
Optimum filter coefficients are calculated by minimizing the deviation of actual
frequency response from specified or desired response. efficiency of the designed
fitter is measured by several parameters, such as maximum pass-band ripple,
maximum stop-band ripple, mean attenuation in stop band and time taken, to
execute the code. Analysis of the performance of designed filter is correlated
with various different algorithms like real coded genetic algorithm, particle
swarm optimization, genetic search algorithm and hybrid particle swarm
optimization gravitational algorithm. Comparative study shows significant
reduction in pass-band error, stop-band error and execution time.
Keyword: Optimal Two-Dimensional, Vortex Search Algorithm
Kumar, Manjeet (2019). Design of two-dimensional FIR filters with
quadrantally symmetric properties using the 2D L-1-method. IET Signal
Processing, 13(3), 262-272.
Abstract: The mathematical formulation of the two-dimensional (2D) 1-
method for designing of the 2D-finite impulse response (FIR) filter is introduced
in this study. It features the 2D-FIR filter with narrow transition width and flatter
passband and stopband response. The 2D complexity is reduced using the
quadrant symmetricity concept for the reduction of filter coefficients to be
evaluated. Here, the unique features of the 2D 1-method are exploited for the
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efficient design of the 2D-FIR filter. To study the effectiveness of the 2D-FIR
filter using the proposed method, its performance is compared with other existing
2D-FIR filter methods. Simulation results for five design examples of 2D
lowpass, high pass, bandpass, band stop filters and 2D differentiator are
presented to prove the efficacy of the proposed design in terms of passband
ripple, stopband ripple, passband error, stopband error and magnitude response.
Keyword: Low-pass filters, Band-pass filters, FIR filters, Computational
complexity, High-pass filters
Kumar, Manjeet (2019). Efficient QRS complex detection algorithm based on
Fast Fourier Transform. Biomedical Engineering Letters, 9(1), 145-151.
Abstract: An ECG signal, generally filled with noise, when de-noised, enables a
physician to effectively determine and predict the condition and health of the
heart. This paper aims to address the issue of denoising a noisy ECG signal using
the Fast Fourier Transform based bandpass filter. Multi-stage adaptive peak
detection is then applied to identify the R-peak in the QRS complex of the ECG
signal. The result of test simulations using the MIT/BIH Arrhythmia database
shows high sensitivity and positive predictivity (PP) of 99.98 and 99.96%
respectively, confirming the accuracy and reliability of proposed algorithm for
detecting R-peaks in the ECG signal.
Keywords: Electrocardiogram (ECG), Cardiovascular diseases (CVD), Fast
Fourier Transform (FFT)
Kumar, Manjeet (2019). Time–frequency localization using three-tap
biorthogonal wavelet filter bank for electrocardiogram compressions. Biomedical
Engineering Letters, 3(3), 407-411.
Abstract: A joint time–frequency localized three-band biorthogonal wavelet
filter bank to compress Electrocardiogram signals is proposed in this work.
Further, the use of adaptive thresholding and modified run-length encoding
resulted in maximum data volume reduction while guaranteeing reconstructing
quality. Using signal-to-noise ratio, compression ratio (CR), maximum absolute
error (EMA), quality score (Qs), root mean square error, compression time (CT)
and percentage root mean square difference the validity of the proposed approach
is studied. The experimental results deduced that the performance of the
proposed approach is better when compared to the two-band wavelet filter bank.
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The proposed compression method enables loss-less data transmission of medical
signals to remote locations for therapeutic usage.
Keyword: Electrocardiogram, Biorthogonal wavelet transform, Wavelet filter
bank, Electrocardiogram compression
Dr. Pushpendra Singh, Assistant Professor, Department of ECE
Singh, Pushpendra (2017). An Efficient ML Frequency Estimation of a
Sinusoid Using the Secant Method. IEEE International Conference on Advanced
Networks and Telecommunications Systems (pp. 1-5).
Abstract: The maximum likelihood frequency of a sinusoid is estimated by
determining the peak in the frequency domain, and the peak position of any
function can be obtained as a root of its derivative. In this paper, we build on this
idea and use powerful root-finding algorithms, the Newton-Raphson method and
its variant, the Secant method, to estimate the frequency of a signal received in a
white Gaussian noise environment. We consider complex exponentials as well as
real sinusoids in this work. Our results demonstrate a superior performance in
terms of accuracy and efficiency as compared to the existing methods.
Furthermore, the proposed method is not sensitive to variations of the frequency
and initial phase of the sinusoid.
Keyword: Complex and real sinusoids, maximum likelihood, Newton-Raphson
method, Secant method
Singh, Pushpendra (2017). Identification of loosening of bolts in a steel plane
frame structure using fourier decomposition method. International Conference on
Vibration Problems.
Abstract: In the present study, an adaptive Fourier Decomposition Method
(FDM) is applied to identify damage at connections. For that purpose, an
experimental single-story plane frame model is considered. The beam and
columns of the frame are connected by angles and bolts, and the damage is
introduced by loosening bolts at different locations. The frame is excited by a
hammer at the right top corner and strain time histories are collected from
different points. The FDM and empirical mode decomposition (EMD) algorithm
are applied to characterize the damage sensitive features. The results obtained
from the FDM are compared with the EMD algorithm, which show that the
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performance of FDM is better, that motivates to extend its application further to
estimate the amount of bolt loosening in terms of extracted damage sensitive
features
Keyword: framed structure, loosening of bolts, damage at connections, damage
detection, Fourier decomposition method, EMD
Singh, Pushpendra (2018). Time-Frequency Analysis of Gravitational Waves.
In IEEE International Conference on Signal Processing and Communications
(pp. 1-5).
Abstract: The instantaneous frequency (IF) is a vital parameter for time-
frequency analysis of a nonstationary signal such as gravitational wave. In this
paper, IF of gravitational waves, recorded by the Laser Interferometer
Gravitational-Wave Observatory detectors, is estimated by applying the energy
preserving empirical mode decomposition and the Fourier decomposition
method. The frequency values corresponding to minimum in spiral strain,
maximum strain that indicates the merger of binary black holes, and the
subsequent ringdown are obtained as (a) GW150914: 30–160–264 Hz, and (b)
GW151226: 19–164–265 Hz. The proposed methods demonstrate a superior
performance in terms of better time-frequency resolution as compared to the
widely used continuous wavelet transform
Keyword: Analytic signal, empirical mode, decomposition, Fourier
decomposition method, gravitational wave
Singh, Pushpendra (2019). Baseline wander and power-line interference
removal from ECG signals using Fourier decomposition method. Machine
Intelligence and Signal Analysis (pp. 25-36).
Abstract: Analysis of electrocardiogram (ECG) signals helps us in detecting
various abnormalities and diseases of heart. These signals commonly suffer from
the problems of baseline wander and power-line interference. In this paper, we
propose a new approach to eliminate such noises from ECG signals using the
Fourier decomposition method. Simulation results are presented to show the
efficacy of our method over previously used EMD based methods. The proposed
method has been shown to preserve shape characteristics of ECG signals of heart
abnormalities.
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Keywords: Baseline wander and Power-line interference, ECG signal, Empirical
mode decomposition, Fourier decomposition method, Linearly Independent Non-
Orthogonal yet Energy Preserving (LINOEP) vectors
Singh, Pushpendra (2017). Breaking the Limits: Redefining the Instantaneous
Frequency. Circuits Syst Signal Process, 3515-3536.
Abstract: The Carson and Fry introduced the concept of variable frequency as a
generalization of the constant frequency. The instantaneous frequency (IF) is the
time derivative of the instantaneous phase, and it is well defined only when this
derivative is positive. If this derivative is negative, the IF creates problem
because it does not provide any physical significance. This study proposes a
mathematical solution and eliminates this problem by redefining the IF such that
it is valid for all mono component, multicomponent signals of nonlinear and
nonstationary nature. This is achieved by using the property of the multivalued
inverse tangent function that provides base to ensure that the instantaneous phase
is an increasing function. The efforts and understanding of all the methods based
on the IF would improve significantly by using this proposed definition of the IF.
We also demonstrate that the decomposition of a signal, using zero-phase
filtering based on the well-established Fourier and filter theory, into a set of
desired frequency bands with proposed IF produces accurate time–frequency–
energy (TFE) distribution that reveals true nature of signal. Simulation results
demonstrate the efficacy of the proposed IF that makes zero-phase filter-based
decomposition most powerful for the TFE analysis of a signal.
Keyword: Analytic signal (AS), Hilbert transform (HT), Instantaneous
frequency (IF), Linearly independent nonorthogonal yet energy preserving
(LINOEP) vectors, Zero-phase filtering (ZPF)
Singh, Pushpendra (2017). Classification of focal and nonfocal EEG signals
using features derived from Fourier-based rhythms. Journal of Mechanics in
Medicine and Biology, 1740002.
Abstract: We propose a new technique for the automated classification of focal
and nonfocal electroencephalogram (EEG) signals using Fourier-based rhythms
in this paper. The EEG rhythms, namely, delta, theta, alpha, beta and gamma, are
obtained using the discrete Fourier transform (DFT)-based filter bank applied on
EEG signals. The mean-frequency (MF) and rootmean square (RMS) bandwidth
features are derived using DFT-based computation on rhythms of EEG signals
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and their envelopes. These derived features, namely, MF and RMS bandwidths
have been provided as an input feature set for the classification of focal and
nonfocal EEG signals using a least-squares support vector machine (LS-SVM)
classifier. We present experimental results obtained from the publicly available
database in order to demonstrate the effectiveness of the proposed feature sets for
the automated classification of the focal and non-focal classes of EEG signals.
The obtained classification accuracy in this dataset for the automated
classification of focal and non-focal 50 pairs and 750 pairs of EEG signals are
89.7% and 89.52%, respectively.
Keyword: Focal and nonfocal electroencephalogram (EEG) signals, Mean-
frequency and rootmean- square bandwidth features, EEG rhythms, Least-
squares support vector machine classifier
Singh, Pushpendra (2018). A novel Signal Modeling Approach for
Classification of Seizure and Seizure-free EEG Signals. IEEE Transactions on
Neural Systems & Rehabilitation Engineering, 925-935.
Abstract: This paper presents a signal modeling based new methodology of
automatic seizure detection in EEG signals. The proposed method consists of
three stages. First, a multi rate filter bank structure is proposed that is
constructed using the basis vectors of discrete cosine transform (DCT). The
proposed filter bank decomposes EEG signals into its respective brain rhythms:
delta, theta, alpha, beta, and gamma. Second, these brain rhythms are
statistically modeled with the class of self-similar Gaussian random processes,
namely, fractional Brownian motion (fBm) and fractional Gaussian noises
(fGn). The statistics of these processes are modeled using a single parameter
called the Hurst exponent. In the last stage, the value of Hurst exponent and
autoregressive moving average (ARMA) parameters are used as features to
design a binary SVM classifier to classify pre-ictal, inter-ictal (epileptic with
seizure free interval), and ictal (seizure) EEG segments. The performance of the
classifier is assessed via extensive analysis on two widely used dataset and is
observed to provide good accuracy on both the dataset. Thus, this paper
proposes a novel signal model for EEG data that best captures the attributes of
these signals and hence, allows to boost the classification accuracy of seizure
and seizure-free epochs.
Keyword: Fractional Gaussian noise, Epileptic EEG data, Seizure Detection
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Singh, Pushpendra (2018). Discussion of "An orthogonal Hilbert-Huang
transform and its application in the spectral representation of earthquake
accelerograms" by Tian-Li Huang, Meng-Lin Lou, Hua-Peng Chen, Ning-Bo
Wanga. Soil Dynamics and Earthquake Engineering, 108, 378–389.
Abstract: This paper first discusses the limitation that the intrinsic mode
functions (IMFs) decomposed by the empirical mode decomposition (EMD) in
Hilbert-Huang transform (HHT) are not orthogonal. As an improvement to the
HHT method, three orthogonal techniques (the forward, backward and arbitrary
sequence orthogonalization algorithms) based on the Gram-Schmidt method are
then proposed to obtain the completely orthogonal IMFs. According to the
orthogonal index and the energy index, the effectiveness of the proposed
technique and algorithms is validated through a synthetic signal generated by
the combination of three sinusoidal waves with different frequencies and the El
Centro (1940, N-S) earthquake accelerogram. By taking the El Centro (1940, N
-S) earthquake accelerogram as an example, the problem that whether the
orthogonal IMFs satisfy the requirements of IMF is discussed, then the
backward and the arbitrary sequence orthogonalization algorithms are
recommended. Three historic earthquake accelerograms are analyzed by using
the recommended orthogonalization algorithms combined with the Hilbert
spectral analysis.
The results show that the orthogonal Hilbert spectrum and the orthogonal
Hilbert marginal spectrum can produce more faithful representation of
earthquake accelerograms than the Hilbert spectrum and the Hilbert marginal
spectrum, and they can be used to quantitatively characterize the energy
distribution of earthquake accelerograms at different frequency regions.
Keyword: Empirical mode decomposition (EMD), intrinsic mode functions
(IMFs), Orthogonal EMD, Orthogonal IMFs
Singh, Pushpendra (2018). Novel Fourier quadrature transforms and analytic
signal representations for nonlinear and non-stationary time-series analysis.
Royal Society Open Science, 5(11), 1-25.
Abstract: The Hilbert transform (HT) and associated Gabor analytic signal
(GAS) representation are well known and widely used mathematical
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formulations for modeling and analysis of signals in various applications. In
this study, like the HT, to obtain quadrature component of a signal, we propose
the novel discrete Fourier cosine quadrature transforms (FCQTs) and discrete
Fourier sine quadrature transforms (FSQTs), designated as Fourier quadrature
transforms (FQTs). Using these FQTs, we propose sixteen Fourier-Singh
analytic signal (FSAS) representations with following properties: (1) real part
of eight FSAS representations is the original signal and imaginary part is the
FCQT of the real part, (2) imaginary part of eight FSAS representations is the
original signal and real part is the FSQT of the real part, (3) like the GAS,
Fourier spectrum of the all FSAS representations has only positive frequencies,
however unlike the GAS, the real and imaginary parts of the proposed FSAS
representations are not orthogonal to each other. The Fourier decomposition
method (FDM) is an adaptive data analysis approach to decompose a signal into
a set of small number of Fourier intrinsic band functions which are AM-FM
components. This study also proposes a new formulation of the FDM using the
discrete cosine transform (DCT) with the GAS and FSAS representations and
demonstrate its e cacy for improved time-frequency-energy representation and
analysis of nonlinear and non-stationary time series.
Keyword: Hilbert transform (HT), Gabor analytic signal (GAS) representation,
Instantaneous frequency (IF), Fourier Quadrature Transform (FQT), Fourier-
Singh analytic signal (FSAS) representations
Singh, Pushpendra (2018). On the Approximate Discrete KLT of Fractional
Brownian Motion and Applications. Journal of the Franklin Institute, 355(17),
8989-9016.
Abstract: This paper establishes connection between discrete cosine transform
(DCT) and the discrete-time fractional Brownian motion process (dfBm). It is
proved that the eigenvectors of the auto-covariance matrix of a dfBm can be
approximated by DCT basis vectors in the asymptotic sense. This shows that
DCT basis acts as discrete Karhunen–Loève transform (DKLT) for these
processes in the approximate sense. Analytic perturbation theory of linear
operators is used to prove this result. This result will be of great practical
significance in applications where one is looking for an appropriate basis to
work with signals that can perhaps be modeled as belonging to fBm processes.
The utility of the proposed work has been illustrated with two real-life data (a)
on compressive sampling-based reconstruction of financial time-series and (b)
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in denoising gravitational wave event GW150914 data obtained from a binary
black hole merger.
Keyword: Discrete cosine transforms, Karhunen–Loève transform
Singh, Pushpendra (2019). Some Studies on Multidimensional Fourier Theory
for Hilbert Transform, Analytic Signal and AM–FM Representation. Circuits,
Systems, and Signal Processing, 38(12), 5623–5650.
Abstract: In this paper, we propose the notion of Fourier frequency vector (FFV)
which is inherently associated with the multidimensional (MD) Fourier
representation (FR) of a signal. The proposed FFV provides physical meaning to
the so-called negative frequencies in the MD-FR that in turn yields MD spatial
and MD space-time series analysis. The one-dimensional Hilbert transform (1D-
HT) and associated 1D analytic signal (1D-AS) of an 1D signal are well
established; however, their true generalization to an MD signal, which possess all
the properties of 1D case, are not available in the literature. To achieve this, we
observe that in MD-FR the complex exponential representation of a sinusoidal
function always yields two frequencies, namely negative frequency
corresponding to positive frequency and vice versa. Thus, using the MD-FR, we
propose MD-HT and associated MD analytic signal (AS) as a true generalization
of the 1D-HT and 1D-AS, respectively, and obtain an explicit expression for the
analytic image computation by 2D discrete Fourier transform (2D-DFT). We also
extend the Fourier decomposition method for 2D signals that decomposes an
image into a set of amplitude-modulated and frequency-modulated (AM–FM)
image components. We finally propose a single-orthant Fourier transform (FT) of
real MD signals which computes FT in the first orthant, and values in rest of the
orthants are obtained by simple conjugation defined in this study.
Keyword: Fourier representation (FR), Fourier frequency vector (FFV), Hilbert
transform (HT), analytic signal (AS), Single-orthant Fourier transform (SOFT),
Fourier decomposition method (FDM)
Singh, Pushpendra (2017). Comments on the Representations of Instantaneous
Frequency using the Hilbert Transform, Direct Quadrature and Hilbert
Quadrature. hal-01570332, 1-13.
Abstract: Using the two parameters amplitude and frequency of a signal, four
different types of representations can be obtained. The rest two representations of
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a signal with (i) constant amplitudes and constant frequencies (CA-CF) by the
Fourier theory, (ii) variable amplitudes and variable frequencies (VA-VF) using
AM-FM model are well established. In this study, we present methods to obtain
other two representations: (iii) constant amplitudes and variable frequencies (CA-
VF) representation (FM model), and (iv) variable amplitudes and constant
frequencies (VA-CF) representation (AM model) for time-frequency analysis of
a signal. Moreover, contrary to perception available in literature, we show that
the direct quadrature (DQ), which is a CA-VF type representation, cannot
produce full sine wave form cosine wave and vice versa, thus not suitable for
instantaneous frequency (IF) computation. In order to overcome the limitations
of DQ, a novel Hilbert Quadrature (HQ) representation of a signal is proposed.
Practically, some noise is always present in the signal under analysis and in such
cases we demonstrate that the analytic signal representation obtained by
suppressing the negative frequencies in the Fourier method, which is equivalent
to the Hilbert transform, is the most robust and suitable for the computation of
IF.
Keyword: Analytic signal, Hilbert transform, Direct Quadrature, Hilbert
Quadrature
Singh, Pushpendra (2018). Studies on Generalized Fourier Representations
and Phase Transforms. arXiv:1808.06550 [eess.SP], 2018, 1-23.
Abstract: Fourier representation (FR) is an indispensable mathematical
formulation for modeling and analysis of physical phenomenon, engineering
systems and signals in numerous applications. In this study, we present the
generalized Fourier representation (GFR) that is completely based on the FR of
a signal and introduce the phase transform (PT) which is a special case of the
GFR and a true generalization of the Hilbert transform. We derive the PT kernel
to obtain any constant phase shift, discuss the various properties of the PT, and
demonstrate that (i) a constant phase shift in a signal corresponds to variable
time-delays in all harmonics, (ii) to obtain a constant time-delay in a signal, one
need to provide variable phase shift in all harmonics, (iii) a constant phase shift
is same as the constant time-delay only for single frequency sinusoid. The time
derivative and time integral, including fractional order, of a signal can be
obtained using the GFR. We propose to use discrete cosine transform (DCT)
based implementation to avoid end artifacts due to discontinuities present in
both end of the signal. We introduce fractional delay of a discrete time signal
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using the FR and present the fast Fourier transform (FFT) implementation of all
the above proposed representations.
Keyword: Generalized Fourier representation (GFR), Hilbert transform (HT),
phase transform (PT), Analytic signal representation
Dr. Rahul Mukherjee, Assistant Professor, Department of ECE
Mukherjee, Rahul (2019). Design of a Dual Axis Thermal Accelerometer using
Single Axis Structure. Proceedings of the 2019 COMSOL Conference (pp. 2-4).
Bangalore.
Abstract: In this paper, we are reporting a dual axis thermal accelerometer using
a single axis structure. The structure of the device is very simple and can be
easily realized. The device contains a bridge shaped heater with four temperature
sensors to detect x and y axis acceleration. The device is designed in 3D and
simulated using FEM simulator. In this accelerometer, when acceleration is
applied along x-axis its sensitivity is 1.07 K/g and along y-axis 0.23 K/g when
the heater temperature is 610K. However, this difference in sensitivity between
two axes can be improved through on-chip amplifiers.
Thus, we believe that this work may lead to a simpler highly sensitive dual axis
thermal accelerometer.
Keyword: Thermal Accelerometer, Heater
Dr. Rama S. Komaragiri, Professor & HOD, Department of ECE
Komaragiri, Rama S. (2018). A Wavelet Transform-Based Filter Bank
Architecture for ECG Signal Denoising. Advances in Intelligent Systems and
Computing (pp. 249-255).
Abstract: In the present work, a wavelet transform-based filter bank
architecture suitable for ECG signal denoising is proposed. Firstly, wavelet
transform functions are used to filter the signals in Matlab R2013b, and then,
the resulting signal is converted into 16-bit binary data. This data is used further
as an input of QRS detection block. Modified architecture contains only three
low-pass filters and a high-pass filter, which is less compared to previously
designed architectures. One of the key advantages of the proposed architecture
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is that no multiplexer and multiplier circuits are required for the further
processing. The proposed architecture consumes less area and is relatively fast
compared to previously designed architectures.
Keyword: Cardiovascular diseases (CVDs), Electrocardiogram (ECG)
Komaragiri, Rama S. (2019). HEMT Material Technology and Epitaxial
Deposition Techniques. In D. Nirmal & J. Ajayan (Eds), Handbook for III-V
High Electron Mobility Transistor Technologies, (pp. 65-80).
Abstract: Compounds like gallium nitride (GaN), aluminum nitride (AIN,
indium nitride (InN) and their alloys form a unique material system termed as
nitride semiconductors. When compared to most of the other material systems, a
much wider spectrum of bandgaps is covered by the nitrides. This is illustrated in
Figure with the help of a bandgap-lattice constant plot. Nitrides have been
researched by several research groups for more than three decades; it started
when the first GaN-based light-emitting diode (LED) was reported by Pankove
et al. The intrinsic material properties did not drive the performance of these
early devices; instead, high-defect density and poor surface morphology of the
heteroepitaxial films dictated the performance of these nitride semiconductor
devices. The work done by Isamu Akasaki at Nagoya and Meijo Universities and
Shuji Nakamura at Nichia Chemical Company in Japan during the mid-1980s did
go a long way in mitigating such performance issues. Using AIN or GaN
nucleation layers, metal-organic chemical vapor deposition (MOCVD) has been
used to grow GaN films of high quality on sapphire substrates. This has led to an
explosion in the field of GaN research in optoelectronics and gradually moved
into electronics. Using the nitride semiconductor family of materials, blue, white,
green and violet LEDs (along with blue-light semiconductor) lasers were
fabricated by Shuji Nakamura, who currently a professor at the University of
California at Santa Barbara. Owing to all the work that has happened to date, a
very large number of applications starting from traffic light to large displays and
high-definition DVD players make wide use of such nitride-based
optoelectronics.
Keyword: HEMT Material Technology
Komaragiri, Rama S. (2019). Introduction to High Electron Mobility
Transistors. In D. Nirmal, J. Ajayan (Ed), Handbook for III-V High Electron
Mobility Transistor Technologies (pp. 45-64).
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Abstract: High electron mobility transistors utilize quantum phenomenon to
conduct charge. At the interface of a type -I heterojunction, a triangular quantum
well is formed, in which electrons are confined to bound energy states. These
bound energy states form a 2DEG. Due to reduced scattering mechanisms, the
carrier mobility is large. A HEMT’s operation is constrained by two threshold
voltages, to create 2DEG and then to control gate. Based on the electrical
conduction behavior, a normally on HEMT is classified as a depletion mode
HEMT and a normally off HEMT is called as enhancement mode HEMT.
Depending on the structure, pHEMT and mHEMT are two fundamental
classifications. An induced HEMT is a HEMT which uses III-V nitrides. InP
HEMTs shows superior transistor gain, transition frequency, and low noise
behaviour. GaAs substrate based HEMTs are omnipresent due to their cost
advantage and GaN based HEMTs are useful for high-power, high frequency and
low noise systems.
Keyword: High Electron Mobility Transistors
Komaragiri, Rama S. (2016). Reconfigurable tunnel field effect transistor
exhibiting reduced ambipolar behavior. IEEE Annual India Conference.
INDICON (pp. 1-5).
Abstract: This paper proposes an architecture for tunnel field effect transistor
(TFET), which provides the reconfigurable property while controlling the
ambipolar behaviour of the device. It is a double gate structure where the gates
split and placed near the area where tunnelling occurs. The effect of metal work
function variations as well device dimension reduction on current performance is
analysed in this work. As per the analysis of the device, symmetrical p-type and
n-type behaviour are achieved with the metal having middle band-gap work
function. Technology computer-aided design (TCAD) simulations are carried out
to examine the device performance.
Keyword: Ambipolar, Work function, Tunnel field effect transistor (TFET),
Metal oxide semiconductor field effect transistor (MOSFET), Band to band
tunnelling (BTBT)
Komaragiri, Rama S. (2017). Non-spiral planar microcoils for biomedical
applications. 12th IEEE International Conference on Nano/micro-engineered and
molecular systems, 780-783
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Abstract: Use of planar microcoils is widely accepted for various sensing and
actuating applications in diverse engineering fields. In this work, the applications
of a non-spiral planar micro coil as electromagnetic MEMS actuator in micro
pumps for miniaturized biomedical devices is studied. Microfabrication of non-
spiral coils is easier compared to that of a conventional spiral coil. Moreover,
non-spiral coils have lesser series resistance compared to spiral micro coils. The
range of magnetic field and force produced by non-spiral coils are simulated
using COMSOL Multiphysics software and found to be sufficient for various
biomedical applications. Therefore non-spiral coils can become a better
alternative to the spiral coils being used at present.
Komaragiri, Rama S. (2017). Simplified R-peak detection algorithm of an ECG
Signal using Daubechies 20 Wavelet Transform. International Conference
Nanotechnology for Instrumentation and Measurement Workshop.
Abstract: In this manuscript, a simplified R-peak detection algorithm is
proposed. Firstly, ECG signal is denoised using Daubechies 20 wavelet
transform based wavelet filter bank. The use of derivative and thresholding
makes the R-peak detection simple and accurate. The proposed algorithm
achieved an overall R-peak detection rate of 99.77% on the MIT-BIH database.
The individual R-peak detection rate of the individual ECG signal varies from
98.64% to 100%.
Keyword: Electrocardiogram, R-peak detector, Wavelet filter bank
Komaragiri, Rama S. (2018). Analysis of Reconfigurable Tunnel Field Effect
Transistor for Improved Current Characteristics. 7th IEEE International
Symposium on Next-Generation Electronics (pp. 1-4).
Abstract: This paper presents different techniques to improve the current
performance of reconfigurable tunnel field effect transistor (RTFET).
Homojunction RTFETs are considered in this paper. The current performance
of RTFETs designed using different semiconductor material and dielectric
material is compared in this paper. Proper selection of gate metal work function
plays important role in the RTFET design to get symmetric current behavior.
The selection of apt gate work function for different homojunction RTFETs is
given in this paper. Technology computer-aided design (TCAD) simulations are
used to analyze the device performance.
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Keyword: TFET, RFET, Work function, Homojunction, OFF-current, ON-
current
Komaragiri, Rama S. (2018). Performance Analysis of Nonspiral Planar
Microcoils for Electromagnetic MEMS Actuator. In 8th ISSS International
conference on smart materials, structures and systems (pp. 1-4).
Abstract: Planar microcoils have a wide scope for various actuating
applications in biomedical scenario. Magnetic micropumps used for lab-on-chip
devices require electromagnetic microactuator for fluid control purposes. In this
work, analysis of the effect of non-spiral planar microcoil’s geometrical
parameters and the spacing between the microcoil and the magnet on the
electromagnetic force has been presented.
A parametrically optimized coil geometry is also shown to yield maximum
electromagnetic force required for micro pump applications.
Keyword: Planar microcoil, micropump, Lab-on-chip devices, Nonspiral coil,
Membrane displacement
Komaragiri, Rama S. (2018). Study of Circuits Based on SOI-vertical Gate-All
-Around FET. 2018 15th IEEE India Council International Conference
(INDICON) (pp. 1-6). Coimbatore, India.
Abstract: The device performance of silicon-on-insulator vertical gate all
around field effect transistor (SOI-VGAAFET) with three channels and optimal
gate length is presented. The electrical parameters of the SOI-VGAAFET are
compared with the bulk VGAAFET. SOI-VGAAFET exhibits low leakage
current, good sub-threshold slope and low drain induced barrier lowering
compared to the bulk VGAAFET device. The performance of analog and digital
circuits based on SOI-VGAAFET are studied using three-dimensional mixed-
mode device simulations. The results indicate that SOI-VGAAFET with optimal
gate length is a suitable device in analog and mixed-signal integrated circuit
applications at low feature-length and low supply voltage.
Keywords: SOI, Bulk substrate, GAAFET, Inverter, Amplifier, Current mirror,
OTA, Ring Oscillator.
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Komaragiri, Rama S. (2019). Microfabrication and electrical characterization of
non-spiral planar microcoils for biomedical applications. Lecture Notes in
Electrical Engineering (pp. 547123-129).
Abstract: Use of planar micro coils is widely accepted for various sensing and
actuating applications in diverse engineering fields. In this work, the applications
of a non-spiral planar micro coil as electromagnetic MEMS actuator in micro
pumps for miniaturized biomedical devices is studied. Microfabrication of non-
spiral coils is easier compared to that of a conventional spiral coil. Moreover, non
-spiral coils have lesser series resistance compared to spiral micro coils. The
range of magnetic field and force produced by non-spiral coils are simulated
using COMSOL Multiphysics software and found to be sufficient for various
biomedical applications.
Therefore, non-spiral coils can become a better alternative to the spiral coils
being used at present.
Keyword: Non-spiral Planar, Micro coils
Komaragiri, Rama S. (2017). Modeling and simulation of non-spiral coil for
magnetic sensing applications. Journal of Mechanical Science and Technology,
31, 5415-5421.
Abstract: Microcoils are essential components in magnetic sensors made using
Micro-electro-mechanical systems (MEMS) technology. Non-spiral microcoils
have fabrication advantages over conventional spiral coils and can be effectively
used in MEMS micro sensors for generation and detection of magnetic fields. In
this work, an analytical model of peak flux density, sensitivity, and resolution for
the non-spiral planar microcoil is reported for the first time. Self and mutual
inductances of a non-spiral coil are used to calculate the flux density at the
innermost turn of the coil. The model derived is compared with standard
fabrication results, and it is found to be in good agreement with the experimental
results.
Keyword: Flux density, Inductance; Micro-electro-mechanical systems; Non-
spiral planar microcoil
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Komaragiri, Rama S. (2018). Design of a Biorthogonal Wavelet Transform
Based R-Peak Detection and Data Compression Scheme for Implantable
Cardiac Pacemaker Systems. Journal of Medical Systems, 102.
Abstract: Bradycardia can be modulated using the cardiac pacemaker, an
implantable medical device which sets and balances the patient’s cardiac health.
The device has been widely used to detect and monitor the patient’s heart rate.
The data collected hence has the highest authenticity assurance and is
convenient for further electric stimulation. In the pacemaker, ECG detector is
one of the most important elements. The device is available in its new digital
form, which is more efficient and accurate in performance with the added
advantage of economic power consumption platform. In this work, a joint
algorithm based on biorthogonal wavelet transform and run-length encoding
(RLE) is proposed for QRS complex detection of the ECG signal and
compressing the detected ECG data. Biorthogonal wavelet transform of the
input ECG signal is first calculated using a modified demand-based filter bank
architecture which consists of a series combination of three lowpass filters with
a high pass filter. Low pass and high pass filters are realized using a linear
phase structure which reduces the hardware cost of the proposed design
approximately by 50%. Then, the location of the R-peak is found by comparing
the denoised ECG signal with the threshold value. The proposed R-peak
detector achieves the highest sensitivity and positive predictivity of 99.75 and
99.98 respectively with the MIT-BIH arrhythmia database. Also, the proposed
R-peak detector achieves a comparatively low data error rate (DER) of 0.002.
The use of RLE for the compression of detected ECG data achieves a higher
compression ratio (CR) of 17.1. To justify the effectiveness of the proposed
algorithm, the results have been compared with the existing methods, like
Huffman coding/simple predictor, Huffman coding/adaptive, and slope
predictor/fixed length packaging.
Keyword: Electrocardiogram (ECG), Run-length encoding (RLE), Low pass
and High pass filter, Continuous wavelet transform (CWT), Discrete wavelet
transform (DWT), Wavelet filter bank (WFB)
Komaragiri, Rama S. (2018). Design of wavelet transform based
electrocardiogram monitoring system. ISA Transactions, 80, 381-398.
Abstract: The new age advancements in information technology due to
materials and integrated circuit (IC) technologies and their applications in
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biomedical sciences have made the healthcare facilities more compact and
affordable for the aging population. Market trends in healthcare and related
devices indicate a sharp rise in their demand. Hence the researchers have
converged the efforts on designing more smart and advanced medical devices
using IC technology. Among these devices, cardiac pacemakers have become a
recurrent biomedical device which is engrafted in the human body to detect and
monitor a person's heart beating rate. The data thus generated is processed for
various medical usages and devices via wireless methods. Cardiovascular
diseases (CVDs) or diseases related to the heart are due to abnormalities or
disorders of the heart and blood vessels. Till date, limited literature is available
which focuses on a single technique that can perform all of the ECG signal
denoising, ECG detection, lossless data compression and wireless transmission.
In this work, a joint approach for denoising, detection, compression, and
wireless transmission of ECG signal is proposed. The modified biorthogonal
wavelet transform is used for denoising, detection and lossless compression of
ECG signal. To reduce the circuit complexity, biorthogonal wavelet transform
is realized using linear phase structure. Further, it is found in this work that the
usage of modified biorthogonal wavelet transform increases the detection
accuracy and CR of the proposed design. Also, in this work, the Wi-Fi-based
wireless protocol is used for compressed data transmission. The proposed ECG
detector achieves the highest sensitivity and positive predictivity of 99.95% and
99.92%, respectively, with the MIT-BIH arrhythmia database. The use of
modified biorthogonal 3.1 wavelet transform and run-length encoding (RLE)
for the compression of ECG data achieves a higher compression ratio (CR) of
6.271. To justify the effectiveness of the proposed algorithm, which uses
modified biorthogonal wavelet 3.1transform, the results are compared with the
existing methods, namely, Huffman coding/simple predictor, Huffman coding/
adaptive, and slope predictor/fixed length packaging.
Keyword: Cardiovascular disease, Electrocardiogram, MIT-BIH database,
Discrete wavelet transform,
Komaragiri, Rama S. (2018). Electromagnetic Micro actuators using Non-
spiral Planar Micro coils for Robotic Applications. Procedia Computer Science,
133, 545–552.
Abstract: Electromagnetic micro actuators offer several advantages for robotic
applications such as relatively large stroke and low input voltage requirements.
Micro coils are significant components for electromagnetic micro actuators for
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generating force required for micro robots. Non-spiral planar micro coils of
square and circular geometries are analyzed here considering the fabrication
easiness and low power consumption of non-spiral planar coils.
Microfabrication of non-spiral planar coil is simpler and requires a single mask
process only. Comparison between non-spiral coils and conventional spiral
coils are also discussed. Series resistance of non-spiral coil is found out to be
lesser than that of spiral coils though magnetic field is slightly lesser for non-
spiral coils. The fabrication advantages and low power dissipation of non-spiral
structures make them a strong alternative for conventional spiral planar micro
coils. Comparison of different planar micro coils shows that the circular non-
spiral coil gives better performance than other coil geometries considered here
for robotic applications. Circular coil is found to provide a uniform field with
lesser parasitic resistance. Electromagnetic micro actuator using non-spiral
planar circular and square micro coils are also analyzed to compare the
performance between the two coil types. The results show that the force
generated using non-spiral circular micro coil in the micro actuator is adequate
for micro robotic applications with an added advantage of uniform magnetic
field provided by the circular coils.
Keyword: Electromagnetic micro actuator, Non-spiral planar micro coil,
Conventional spiral coils, Series resistance
Komaragiri, Rama S. (2018). From Pacemaker to Wearable: Techniques for
ECG Detection Systems. Journal of Medical Systems, 1-17.
Abstract: With the alarming rise in the deaths due to cardiovascular diseases
(CVD), present medical research scenario places notable importance on
techniques and methods to detect CVDs. As adduced by world health
organization, technological proceeds in the field of cardiac function assessment
have become the nucleus and heart of all leading research studies in CVDs in
which electrocardiogram (ECG) analysis is the most functional and convenient
tool used to test the range of heart-related irregularities. Most of the approaches
present in the literature of ECG signal analysis consider noise removal, rhythm-
based analysis, and heartbeat detection to improve the performance of a cardiac
pacemaker. Advancements achieved in the field of ECG segments detection and
beat classification have a limited evaluation and still require clinical approvals.
In this paper, approaches on techniques to implement on-chip ECG detector for
a cardiac pacemaker system are discussed. Moreover, different challenges
regarding the ECG signal morphology analysis deriving from medical literature
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is extensively reviewed. It is found that robustness to noise, wavelet parameter
choice, numerical efficiency, and detection performance are essential
performance indicators required by a state-of-the-art ECG detector.
Furthermore, many algorithms described in the existing literature are not
verified using ECG data from the standard databases. Some ECG detection
algorithms show very high detection performance with the total number of
detected QRS complexes. However, the high detection performance of the
algorithm is verified using only a few datasets. Finally, gaps in current
advancements and testing are identified, and the primary challenge remains to
be implementing bullseye test for morphology analysis evaluation.
Keyword: Electrocardiogram (ECG), ECG detector, Body sensor network
(BSN). Bio signal processor (BSP), Bio signal processor (BSP), Discrete
wavelet transform (DWT)
Komaragiri, Rama S. (2018). Heart rate monitoring and therapeutic devices:
A wavelet transform based approach for the modeling and classification of
congestive heart failure. ISA Transactions, 79, 239-250.
Abstract: Heart rate monitoring and therapeutic devices include real-time
sensing capabilities reflecting the state of the heart. Current circuitry can be
interpreted as a cardiac electrical signal compression algorithm representing the
time signal information into a single event description of the cardiac activity. It
is observed that some detection techniques developed for ECG signal detection
like artificial neural network, genetic algorithm, Hilbert transform, hidden
Markov model are some sophisticated algorithms which provide suitable results
but their implementation on a silicon chip is very complicated. Due to less
complexity and high performance, wavelet transform based approaches are
widely used. In this paper, after a thorough analysis of various wavelet
transforms, it is found that Biorthogonal wavelet transform is best suited to
detect ECG signal's QRS complex. The main steps involved in ECG detection
process consist of de-noising and locating different ECG peaks using adaptive
slope prediction thresholding. Furthermore, the significant challenges involved
in the wireless transmission of ECG data are data conversion and power
consumption. As medical regulatory boards demand a lossless compression
technique, lossless compression technique with a high bit compression ratio is
highly required. Furthermore, in this work, LZMA based ECG data
compression technique is proposed. The proposed methodology achieves the
highest signal to noise ratio, and lowest root mean square error. Also, the
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proposed ECG detection technique is capable of distinguishing accurately
between healthy, myocardial infarction, congestive heart failure and coronary
artery disease patients with a detection accuracy, sensitivity, specificity, and
error of 99.92%, 99.94%, 99.92% and 0.0013, respectively. The use of LZMA
data compression of ECG data achieves a high compression ratio of 18.84. The
advantages and effectiveness of the proposed algorithm are verified by
comparing with the existing methods.
Keyword: Heart rate monitoring, Congestive heart failure, Electrocardiogram,
Biorthogonal wavelet transform, Wavelet filter bank
Komaragiri, Rama S. (2018). Two-dimensional analytical model for a
reconfigurable field effect transistor. Superlattices and Microstructures, 62-74.
Abstract: This paper presents two-dimensional potential and current models
for a reconfigurable field effect transistor (RFET). Two potential models which
describe subthreshold and above-threshold channel potentials are developed by
solving two-dimensional (2D) Poisson's equation. In the first potential model,
2D Poisson's equation is solved by considering constant/zero charge density in
the channel region of the device to get the subthreshold potential characteristics.
In the second model, accumulation charge density is considered to get above-
threshold potential characteristics of the device. The proposed models are
applicable for the device having lightly doped or intrinsic channel. While
obtaining the mathematical model, whole body area is divided into two regions:
gated region and un-gated region. The analytical models are compared with
technology computer-aided design (TCAD) simulation results and are in
complete agreement for different lengths of the gated regions as well as at
various supply voltage levels.
Keyword: Reconfigurable field effect transistor, Analytical modelling,
Poisson's equation, Simulations
Komaragiri, Rama S. (2019). An analytical model for a reconfigurable tunnel
field effect transistor. Superlattices and Microstructures, 131, 40-52.
Abstract: In this work, an analytical model for surface potential and current
through a reconfigurable tunnel field effect transistor (RTFET) are proposed.
While obtaining the mathematical potential model, the whole channel region is
divided into three: two regions with gate electrodes and a region in between two
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gates. The 2D Poisson’s equation is solved in the region under the gate by
appropriately selecting the boundary conditions. The current model is derived by
integrating the band to band generation rate. The analytical models are validated
using technology computer-aided design (TCAD) simulation and the analytical
model and TCAD simulations are in good agreement.
Keyword: Reconfigurable field effect transistor, Analytical modelling, Poisson’s
equation, TCAD simulations
Komaragiri, Rama S. (2019). Design and Analysis of Non-spiral Planar Micro
Coil-Based Electromagnetic Micro actuator. Arabian Journal for Science and
Engineering, 44(8), 6805-6811.
Abstract: Lab-on-chip devices essentially require micropumps and valves which
incorporate a micro actuating mechanism to control fluid flow. In this work, a
non-spiral type planar micro coil is reported for implementing an electromagnetic
micro actuator. The effect of variation in coil geometries on the micro actuator
performance is analyzed for the first time. The micro coil fabricated and
characterized in this work considerably reduces the number of lithography layers,
thus improving the ease of fabrication while reducing the series coil resistance.
The micro coil structures are further analyzed for the micro actuator performance
using finite element method, and the effect of coil geometries on the
electromagnetic force generated by the actuator is studied. Microfabrication and
electrical characterization results of the non-spiral planar micro coils show the
influence of the same on the actuator performance. A tapered square micro coil
geometry is proposed to improve the outputs from the actuator.
Keyword: Lab-on chip, Finite element method, Micro actuator, Non-spiral
planar micro coils, Tapered square geometry
Komaragiri, Rama S. (2019). Design of efficient fractional operator for ECG
signal detection in implantable cardiac pacemaker systems. International Journal
of Circuit Theory and Applications. 47(9), 1459-1476.
Abstract: A low power and high‐performance digital electrocardiogram (ECG)
detector has become a basic requirement in modern implantable cardiac
pacemakers. A fractional operator‐based digital ECG detector for modern
pacemaker systems is proposed in this work. Instead of conventional
thresholding, an adaptive slope prediction threshold is utilized for the detection
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of ECG peaks. A stochastic search‐based algorithm, namely, cuckoo search
algorithm, is used to design an optimal fractional operator that is used for ECG
denoising. It has been found that the proposed adaptive slope prediction
threshold increases the QRS complex detection performance. A low detection
error rate (DER) ranges from 0.01% to 0.56%, positive predictivity (P+) ranges
from 99.32% to 99.98%, sensitivity (Se) ranges from 99.45% to 99.98%, and a
detection accuracy (Acc) ranges from 99.43% to 99.96% for different databases
are achieved for the proposed ECG detector, which is better compared with the
existing ECG detectors. The proposed design of fractional order operator based
on the lattice wave digital filter (LWDF) requires a minimum number of the
multipliers for its structural realization.
Keyword: Biomedical signals, Electrocardiography, Fractional order operators,
Heart rate variability, Lattice wave digital filter
Komaragiri, Rama S. (2019). Efficient QRS complex detection algorithm based
on Fast Fourier Transform. Biomedical Engineering Letters, 9(1), 145-151.
Abstract: An ECG signal, generally filled with noise, when de-noised, enables a
physician to effectively determine and predict the condition and health of the
heart. This paper aims to address the issue of denoising a noisy ECG signal using
the Fast Fourier Transform based bandpass filter. Multi-stage adaptive peak
detection is then applied to identify the R-peak in the QRS complex of the ECG
signal. The result of test simulations using the MIT/BIH Arrhythmia database
shows high sensitivity and positive predictivity (PP) of 99.98 and 99.96%
respectively, confirming the accuracy and reliability of proposed algorithm for
detecting R-peaks in the ECG signal.
Keywords: Electrocardiogram (ECG) Cardiovascular diseases (CVD) Fast
Fourier Transform (FFT)
Komaragiri, Rama S. (2019). Fabrication, characterization, and modelling of a
novel via-less single metal level magnetic micro coil sensor for biosensing
applications. Sensors and Actuators A: Physical, 290(1), 190-197.
Abstract: The emerging field of micro dimensioned biomedical sensors involves
tremendous research to detect biomolecules and pathogens with an improved
sensitivity and a low limit of detection. The use of magnetic labels in biosensors
has increased so much over the past years due to unique advantages of magnetic
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sensing techniques. Planar micro coil based magnetic biosensors help to reduce
the system size and improve the sensitivity. This paper proposes non-spiral
planar micro coil based magnetic sensors which are advantageous over
conventional spiral coil-based sensors regarding fabrication easiness and heating
losses. The method of microfabrication of the coil sensor described in this paper
makes use of a single mask process which is the simplest among all existing
processes. Non-spiral planar micro coil sensors based on induction-balance and
differential sensing principles are studied in this work. Also, an analytical model
is developed to design the dimensions of the sensing coil. Comprehensive finite
element analysis of the sensors is performed, and the results are compared with
the experimental outcomes. A comparative study of the proposed sensors with
the existing planar coil magnetic sensors is also presented to show the advantages
of the proposed coil sensors over the existing ones.
Keyword: Fabrication, Magnetic Micro coil Sensor, Biosensing, Modelling of a
Novel via-less.
Komaragiri, Rama S. (2019). Modelling, microfabrication and performance
evaluation of non-spiral planar micro coils for biomedical wireless power
transfer systems. Micro and Nano Letters, 14(12), 1223.
Abstract: Microfabrication, electrical characterization, and mathematical
modelling of a non-spiral planar micro coil useful for wireless power transfer
applications in biomedical devices are presented in this work. The fabrication
method using the existing very-large-scale integration manufacturing process
requires a single mask level, and a single metal level without any via enables
direct integration with a complementary metal oxide semiconductor sensing
circuitry. An analytical model of magnetic field distribution in a non-spiral micro
coil is developed for the first time in this work, which satisfies the form of a
Bessel function of the first kind. An electrical model of the non-spiral planar
micro coil is also developed and compared with experimental results.
Experimental results are in good agreement with the theoretical model. Based on
the experimental results, using optimized coil geometry, a wireless power
transfer link suitable for biomedical wireless power transfer applications is
studied. The maximum possible value of coupling factor of the wireless link is
found to be 60% for a small separation between the coil and the magnet whereas
the minimum value of coupling factor is found to be below 10% for large
separations. It is found that introducing Neodymium magnetic shield layer at the
receiving coil enhances the coupling factor significantly.
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Keyword: INSPEC: Controlled Indexing Bessel functions, CMOS integrated
circuits, Coils, Inductive power transmission, Magnetic shielding,
Microfabrication
Komaragiri, Rama S. (2019). Performance analysis of planar micro coils for
biomedical wireless power transfer links. Sadhana - Academy Proceedings in
Engineering Sciences, 44(8).
Abstract: Planar micro coils are significant components of inductive devices
used for biomedical wireless power transfer applications. Biomedical devices
implanted inside the human body needs to be powered up at regular intervals
which can be done electromagnetically through a planar micro coils’ setup.
Different types of planar micro coils such as spiral and non-spiral planar micro
coils are compared in this work in terms of their electrical parameters. An
analytical model is also developed which is validated using experimental results.
The fabrication advantages and low power dissipation of non-spiral coil
structures make them a strong alternative for conventional spiral planar coils.
Though the magnitude of magnetic flux density is slightly lesser for non-spiral
coils, series resistance required for wireless power link is found to be better for
the same. The fabrication of non-spiral planar micro coils of various geometries
is shown using a single mask level. Coupling factors of various wireless power
links are also simulated using different non-spiral planar micro coil geometries to
select the optimum geometry for the wireless power link application.
Keyword: Non-spiral planar micro coil, Magnetic flux density, Wireless power
link, Coupling factor
Komaragiri, Rama S. (2019). Time–frequency localization using three-tap
biorthogonal wavelet filter bank for electrocardiogram compressions. Biomedical
Engineering Letters, 3(3), 407-411.
Abstract: A joint time–frequency localized three-band biorthogonal wavelet
filter bank to compress Electrocardiogram signals is proposed in this work.
Further, the use of adaptive thresholding and modified run-length encoding
resulted in maximum data volume reduction while guaranteeing reconstructing
quality. Using signal-to-noise ratio, compression ratio (CR), maximum absolute
error (EMA), quality score (Qs), root mean square error, compression time (CT)
and percentage root mean square difference the validity of the proposed approach
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is studied. The experimental results deduced that the performance of the
proposed approach is better when compared to the two-band wavelet filter bank.
The proposed compression method enables loss-less data transmission of medical
signals to remote locations for therapeutic usage.
Keyword: Electrocardiogram, Biorthogonal wavelet transform, Wavelet filter
bank, Electrocardiogram compression
Ramana Ranganatham, B.Tech Student, Department of ECE
Ranganatham, Ramana (2017). Simplified R-peak detection algorithm of an
ECG Signal using Daubechies 20 Wavelet Transform. International Conference
Nanotechnology for Instrumentation and Measurement Workshop.
Abstract: In this manuscript, a simplified R-peak detection algorithm is
proposed. Firstly, ECG signal is denoised using Daubechies 20 wavelet
transform based wavelet filter bank. The use of derivative and thresholding
makes the R-peak detection simple and accurate. The proposed algorithm
achieved an overall R-peak detection rate of 99.77% on the MIT-BIH database.
The individual R-peak detection rate of the individual ECG signal varies from
98.64% to 100%.
Keyword: Electrocardiogram, R-peak detector, Wavelet filter bank
Ranganatham, Ramana (2019). Efficient QRS complex detection algorithm
based on Fast Fourier Transform. Biomedical Engineering Letters, 9(1), 145-151.
Abstract: An ECG signal, generally filled with noise, when de-noised, enables a
physician to effectively determine and predict the condition and health of the
heart. This paper aims to address the issue of denoising a noisy ECG signal using
the Fast Fourier Transform based bandpass filter. Multi-stage adaptive peak
detection is then applied to identify the R-peak in the QRS complex of the ECG
signal. The result of test simulations using the MIT/BIH Arrhythmia database
shows high sensitivity and positive predictivity (PP) of 99.98 and 99.96%
respectively, confirming the accuracy and reliability of proposed algorithm for
detecting R-peaks in the ECG signal.
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Keywords: Electrocardiogram (ECG) Cardiovascular diseases (CVD) Fast
Fourier Transform (FFT)
Dr. Sudhir Chandra, Professor, Department of ECE
Chandra, Sudhir (2019). A Technique for Noncontact Measurement of Cavity
Lengths and Deflection Shape in Optical MEMS Pressure Transducer. In
Symposium on Design, Test, Integration and Packaging of MEMS and MOEMS
(pp. 5-9).
Abstract: Noncontact measurements are very important for the characterization
MEMS devices. In this paper, a novel technique for noncontact measurement
cavity length (CL) and defection shape (DS) in an optical MEMS pressure
transducer is reported. The technique introduces a multimode optical fiber
terminated with an ‘angle polished connector (APC)’ for noncontact and
convenient measurement of cavity length in the device. An interferometer is
formed between two nearest surfaces of glass wafer and the silicon diaphragm in
the device. The diaphragm is already in deflected position under the normal
ambient pressure. The APC based ‘fiber probe’ is positioned at some gap above
the glass surface and scanned in X-Y plane to measure the cavity length at
various positions over the deflected silicon diaphragm. The signals are achieved
very casily even with a millimeter gap of the probe above the glass and hence
noncontact scanning X-Y plane becomes possible. The optical detection is based
on white light interferometry (WLI) for absolute measurement of cavity length.
The deflection shape of square anisotropic silicon diaphragm was derived from
measured CL values. A deflection shape function (DSF) was fitted on
experimental data. The presented technique facilitates nondestructive evaluation
of the device post-fabrication and offers a low-cost metrology system.
Keyword: Micro electromechanical systems (MEMS), Optical fiber, Multimode
fiber, APC connector, PC connector, Fbry Peron interferometer (FPI), White
Light interferometry (WLI)
Chandra, Sudhir (2019). Ammonia Gas Sensing Using ZnO Nanowires
Synthesized by Thermal Oxidation of Zn Film. International Journal of Advances
in Science Engineering and Technology (pp. 71-74).
Abstract: In this work, long, dense and uniformly distributed ZnO nanowires
have been synthesized and studied as the sensing element for detection of
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ammonia gas. For this purpose, 130 nm thick Zn film was deposited on oxidized
Si substrate by RF magnetron sputtering at the rate of 4.5 nm/min in Ar ambient.
The film was thermally oxidized at 500 ⁰C in moist environment for 1 hr. The
structural phase of post-oxidized sample indicated that Zn film was completely
oxidized. The morphology indicated that Zn was covered into nanowires of ZnO.
The diameter of nanowires was estimated to be about 40-50 nm and the length
was in the range of few tens of micron. MEMS technology was used to integrate
these nanowires to fabricate a gas sensing device. The device showed excellent
sensing performance towards trace amount of ammonia gas. Keywords - Thermal
oxidation, Zinc oxide, Nanowire, Ammonia gas sensor.
Keyword: Thermal Oxidation
Chandra, Sudhir (2017). Suppression of span in sealed microcavity Fabry-Perot
pressure sensors. Optical Engineering, 016105.
Abstract: Optical microelectromechanical system pressure sensors working on
the principle of extrinsic Fabry-Perot (FP) interferometer are designed and
fabricated for pressure range of 1-bar absolute. Anodic bonding of silicon with
glass is performed under atmospheric pressure to form FP cavity. This process
results in entrapment of gas in the sealed microcavity. The effect of trapped gas
is investigated on sensor characteristics. A closed-loop solution is derived for the
deflection of the sealed microcavity pressure sensor. Phenomenon of
“suppression of span” is brought out. The sensors are tested using white light
interferometry technique. The residual pressure of the trapped gas is estimated
from the experiments. The developed model has been used to estimate the
defection sensitivity of the free diaphragm and the extent of suppression of span
after bonding.
Keyword: Suppression, Fabry–Perot Pressure Sensors, Microcavity
Chandra, Sudhir (2018). Synthesis of WO3 nanorods by thermal oxidation
technique for NO2 gas sensing application. Materials Science in Semiconductor
Processing, 86, 79-84.
Abstract: In this work, WO3 nanorods were successfully synthesized by
thermal oxidation method and further investigated for gas sensing application.
For WO3 nanorods synthesis, tungsten film was deposited on oxidized Si
substrate by sputtering method and subsequently subjected to thermal oxidation
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process at 500 °C in atmospheric environment. The synthesized nanorods were
analyzed using SEM, XRD, Raman, and XPS. A chemiresistive type MEMS
based sensing device was fabricated incorporating these nanorods. The sensor
was tested for different gases and VOCs over operating temperatures ranging
from 75 to 300°C. It showed high selectivity towards NO2 gas over H2S, NH3,
acetone, methanol, and ethanol. The excellent sensing performance and
sophisticated method of synthesis make this a promising candidate for gas
sensing applications.
Keyword: WO3 Nanorods, NO2, Gas sensor, Selective detection
Chandra, Sudhir (2018). Teaching Fundamentals of Microelectronic
Technology Using Test Chip. Journal of Engineering Education
Transformations, 32(2), 19-24.
Abstract: In this work, we present an innovative approach to provide training
to undergraduate and postgraduate students in the area of microelectronics
technology through test chip design, fabrication and testing. A large number of
academic institutions across the world do not have device fabrication facilities
at their disposal. In such cases, imparting even basic training to the students in
the area of microelectronics technology is severely restricted. In the work
presented here, a test chip, based on a generic bipolar process, has been
designed and fabricated. The test chip contains various test structures through
which process parameters (such as sheet resistance of diffused layers, contact
resistance etc.) can be measured. In addition, the chip has a few diodes and
bipolar junction transistors of different designs and dimensions. The devices
were packaged in a standard integrated circuit header but with a transparent
cover to enable optical viewing. The devices and test structures were
characterized, and the measured parameters were correlated with the processing
parameters. The electrical measurement on these structures together with
processes used in fabrication and the visual observation under an optical
microscope is helpful to students in developing better understanding of the
intricacies of device fabrication
Keyword: Microfabrication, Test chip, Semiconductor device experiments,
Integrated circuit technology training,
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Chandra, Sudhir (2019). Finite element analysis and experimental validation of
suppression of span in optical MEMS pressure sensors. Microsystem
Technologies, 25(10), 3691–3701.
Abstract: An optical pressure sensor working on the principle of Fabry–Perot
Interferometer (FPI) is designed for pressures range of 1 bar absolute. The sensor
is based on MEMS fabrication technology involving micromachined silicon
diaphragm and anodic bonding with glass wafer. The fabrication results in
trapped gas in the sealed reference cavity. The pressure of gas is likely to change
with the movement of diaphragm in response to applied pressure. To find the
deflection of diaphragm in presence of ‘deflection-dependent reference pressure’,
a finite element (FE) based model of sensor is developed. The model includes
structural as well as fluidic parts for diaphragm and the trapped gas respectively.
The reference pressure as well as diaphragm deflection are evaluated at various
applied pressures. The FE simulations are carried out for sensor models of
various cavity lengths. It is established that the span of the sensor gets reduced
(suppressed) for small cavity lengths. Two types of sensors are fabricated and
tested. Close agreement is found between theoretically predicted and
experimentally observed values.
Keyword: Fabry–Perot Interferometer (FPI)
Dr. Suneet Tuli, Professor, Department of ECE
Tuli, Suneet (2017). Comparison of lock-in and pulse compression thermal
imaging techniques for non-destructive defect detection. WCCM 2017 - 1st
World Congress on Condition Monitoring 2017.
Abstract: Pulsed, lock-in and frequency modulated thermography are three
alternative nondestructive evaluation techniques. The defect imaging
performance of these techniques are compared using matched excitation energy,
the same carbon fiber composite test piece and infrared camera system. The lock-
in technique suffers from “blind frequencies” at which phase images for some
defects disappear. It is shown that this problem can be overcome by using
frequency modulated (chirp) excitation and an image fusion algorithm is
presented that enhance phase imaging of defects. The signal-to-noise ratios
(SNRs) of defect images obtained by the three techniques are presented. For the
shallowest defects (depths 0.25 and 0.5 mm, 6 mm diameter), the pulsed
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technique exhibits the highest SNRs. For deeper defects the SNRs of the three
techniques are similar in magnitude under matched excitation energy condition.
Tuli, Suneet (2017). A novel pulse compression algorithm for frequency
modulated active thermography using band-pass filter. Infrared Physics &
Technology, 82, 75-84.
Abstract: This paper proposes a novel pulse compression algorithm, in the
context of frequency modulated thermal wave imaging. The compression filter is
derived from a predefined reference pixel in a recorded video, which contains
direct measurement of the excitation signal alongside the thermal image of a test
piece. The filter causes all the phases of the constituent frequencies to be adjusted
to nearly zero value, so that on reconstruction a pulse is obtained. Further, due to
band-limited nature of the excitation, signal-to-noise ratio is improved by
suppressing out-of-band noise. The result is similar to that of a pulsed
thermography experiment, although the peak power is drastically reduced. The
algorithm is successfully demonstrated on mild steel and carbon fibre reference
samples. Objective comparisons of the proposed pulse compression algorithm
with the existing techniques are presented.
Keyword: Thermal imaging NDT, Frequency modulated thermal wave imaging,
Pulse thermography, Pulse compression, Band-pass filter
Tuli, Suneet (2017). Applicability of LED-Based Excitation Source for Defect
Depth Resolved Frequency Modulated Thermal Wave Imaging. IEEE
Transactions on Instrumentation and Measurement, 2658-2665.
Abstract: This paper proposes an energy efficient instrumentation set-up for
pulse-compression thermal-wave imaging with a low-power LED excitation
source. The set-up consists of three different subsystems that are synchronized in
time. The individual systems consist of a LED modulation circuitry, reference
signal measurement circuitry, and an IR camera trigger signal generation
circuitry for frame capture. A separate reference acquisition circuitry is useful in
quantifying defect depth resolution. This paper also proposes a nonuniform frame
capture technique to reduce the memory allocation space of the recorded video.
The technique is based on varying the sampling rate with a change in
instantaneous frequency and is specifically useful for frequency modulated
excitation signal. The proposed technique is implemented on a carbon fiber
reinforced polymer test-piece. The variation of pulse compression parameters
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with different defect dimension is studied, and the results are verified with an
electro-thermal simulator. Further, an objective comparison of pulse compression
experiment for different experiment duration is presented.
Keyword: Frequency modulated thermal wave imaging, 21 pulse compression,
Pulse thermography, Thermal nondestructive testing (NDT).
Tuli, Suneet (2017). Modelling and Analysis of Power Distribution of
Electromagnetic Waves on Plane Surfaces Using Lock-in IR Thermography.
Journal of Nondestructive Evaluation, 36(60), 1-8.
Abstract: The electric field distribution (magnitude only) near a radiating source
(antenna) can be easily determined using infrared thermography. A thin screen
(made of carbon fiber reinforced polymers) is placed in front of a microwave
source. The electromagnetic waves impinging on the screen are partially
absorbed, resulting in temperature rise of the screen. This temperature rise is
monitored by an infrared camera. The temperature distribution thus observed is
mapped to the electric field strength (magnitude of electric field) of the
electromagnetic waves. Points on the screen where the temperature rise is low
correspond to weak electromagnetic fields whereas points with high temperature
rise correspond to strong electromagnetic fields. In this paper electro-thermal
modelling is done so as to obtain the temperature distribution over the screen,
when an electromagnetic field is incident on it. This model can conversely be
used for finding electromagnetic field distributions from IR thermal images.
Keyword: Infrared thermography, IR Camera, Electric field, Absorption screen,
Amplitude image, Thermal diffusivity
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Department of Mathematics
Dr. Sarika Goyal, Assistant Professor, Department of Mathematics
Goyal, Sarika (2016). Multiplicity results of fractional-Laplace system with sign
-changing and singular nonlinearity. Electronic Journal of Differential
Equations, (183), 1-28.
Abstract: In this article, we study the following fractional-Laplacian system with
singular nonlinearity (−∆)su = λf(x)u −q + α α + β b(x)u α−1w β in Ω (−∆)sw =
µg(x)w −q + β α + β b(x)u αw β−1 in Ω u, w > 0 in Ω, u = w = 0 in R n \ Ω,
where Ω is a bounded domain in Rn with smooth boundary ∂Ω, n > 2s, s ∈ (0,
1), 0 < q < 1, α > 1, β > 1 satisfy 2 < α + β < 2 * s − 1 with 2 * s = 2n n−2s , the
pair of parameters (λ, µ) ∈ R2 \ (0, 0). The weight functions f, g: Ω ⊂ Rn →
R such that 0 < f, g ∈ L α+β α+β−1+q (Ω), and b : Ω ⊂ Rn → R is a sign-
changing function such that b(x) ∈ L∞(Ω). Using variational methods, we show
existence and multiplicity of positive solutions with respect to the pair of
parameters (λ, µ).
Keyword: Fractional -Laplace
Goyal, Sarika (2017). On the eigenvalues and Fuik spectrum of p-fractional
Hardy-Sobolev operator with weight function. Applicable Analysis, 97(4), 1-26.
Abstract: In this article, we study the nonlinear eigenvalue problem of fractional
Hardy–Sobolev operator
where is a bounded domain in with Lipschitz boundary containing
0, , , , and the weight function V, having
nontrivial positive part, belongs to suitable integrable class and may change sign. We
investigate some properties of the first eigenvalue such as simplicity and isolation.
Moreover, we also study the Fučik spectrum of fractional Hardy-Sobolev
operator, which is defined as the set such
that
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has a non-trivial solution u. We show the existence of a first nontrivial curve of
this spectrum and also we prove some properties of this curve. At the end, we study a
nonresonance problem with respect to the weighted Fučik spectrum.
Keywords: Non-local operator, fractional Hardy–Sobolev operator, eigenvalue
problem, Fučik spectrum, nonresonance
Goyal, Sarika (2018). First curve of fucik spectrum for the p-fractional
laplacian operator with nonlocal normal boundary conditions. Electronic
Journal of Differential Equations, (74), 1-21.
Abstract: In this article, we study the Fucik spectrum of the p-fractional
Laplace operator with nonlocal normal derivative conditions which is defined
as the set of all (a, b) ∈ R2 such that Λn,p(1 − α)(−∆)α p u + |u| p−2u = χΩ (a(u
+) p−1 − b(u −) p−1 ) in Ω, Nα,pu = 0 in R n \ Ω, has a non-trivial solution u,
where Ω is a bounded domain in Rn with Lipschitz boundary, p ≥ 2, n > pα, , α
∈ (0, 1) and Ω := x ∈ Ω : d(x, ∂Ω) ≤ . We show existence of the first non-
trivial curve C of the Fucik spectrum which is used to obtain the variational
characterization of a second eigenvalue of the problem defined above. We also
discuss some properties of this curve C, e.g. Lipschitz continuous, strictly
decreasing and asymptotic behavior and nonresonance with respect to the Fucik
spectrum.
Keyword: Fucik Spectrum, P-fractional Laplacian Operator
Goyal, Sarika (2019). A note on the eigenvalues of p-fractional Hardy–Sobolev
operator with indefinite weight. Mathematische Nachrichten, 292(10), 2189-
2202.
Abstract: In this article, we study the eigenvalues of p‐fractional Hardy operator
where n>pa,
p>-2 , a ∈ (0,1) , 0≤μ <Cn,a,p and Ω is an unbounded domain in with
Lipschitz boundary containing 0. The weight function V may change sign and
may have singular points. We also show that the least positive eigenvalue is
simple, and it is uniquely associated to a nonnegative eigenfunction. Moreover,
we proved that there exists a sequence of eigenvalues
Keyword: Eigenvalue problem, Fractional Hardy-Sobolev operator, Indefinite
weight
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Goyal, Sarika (2019). Fractional Hardy-Sobolev operator with sign-changing
and singular nonlinearity. Applicable Analysis, 1-26.
Abstract: We study the following fractional equation with Hardy potential and
singular nonlinearity (Pμ,λ) (− )sw−μ w |x|2s =a(x)w−q +λb(x)wr in w > 0 in , w
=0 in Rn \ , where0∈ is a bounded domain in Rn with smooth boundary∂ ,n>2s,
s∈ (0,1),0<μ< n,s, the sharp constant of the fractional Hardy So bolev in
equality, λ>0, 0 < q < 1 < r < 2* s −1 with 2* s =2n/(n−2s), a : ⊂ Rn → R such
that 0 < a(x) ∈L 2* s 2* s−1+q (Ω), and b : ⊂ Rn → R is a sign changing
function such tha tb(x) ∈L 2* s 2* s−1−r (Ω).Using variational methods, we
show existence, non-existence and multiplicity of positive solutions of (Pμ,λ)
with respect to the parameter λ.
Keyword: Non-local operator, Hardy term, Singular nonlinearity, Sign-changing
weight function, Nehari manifold
Dr. Urvashi Arora, Department of Mathematics
Arora, Urvashi (2018). Approximate Controllability of Semilinear Fractional
Stochastic System with Nonlocal Conditions. Dynamic Systems and
Applications, 27, 45-62.
Abstract: This paper deals with the approximate controllability of semilinear
fractional stochastic system of order ρ ∈ (1, 2] with nonlocal conditions. By
using Sadovskii’s fixed point theorem with fractional calculus and stochastic
analysis theory, we derive a new set of sufficient conditions for the approximate
controllability of fractional stochastic system with nonlocal conditions under
the assumption that the corresponding linear system is approximately
controllable. Finally, an application to a fractional stochastic system with
nonlocal initial conditions is provided to illustrate the feasibility of the obtained
results.
Keyword: Semilinear Fractional Stochastic System, Linear systems
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Department of Mechanical and Aerospace Engineering
Abhishek Mishra, B.Tech Student, Department of Mechanical and
Aerospace Engineering
Mishra, Abhishek (2019). Computational fluid dynamics analysis and
experimental validation of solar panel cleaning mechanism. Vibroengineering
Procedia, 29, 225-230.
Abstract: Solar energy is one of the widely used non-conventional form of
energy. Photo voltaic panels generate electricity and heat by absorbing solar
irradiation. The performance of solar panels depends on several factors like dust
accumulation on the surface, solar cell temperature, angle of inclination etc., to
perform the cleaning action efficiently a semi-automatic cleaning mechanism has
been designed and fabricated. The designed experimental setup consists of
several nozzles attached on top of the solar panels and water is supplied to each
nozzle using a Poly Vinyl Chloride (PVC) pipe frame connected to an AC motor
operated with a time switch. Water flows on the surface of photo voltaic module,
thus heat exchange takes place. One dimensional heat transfer analysis is
performed, and the results are compared to the experimental results for
validation. The experiments were conducted at Bennett University, Greater
Noida dated 9 October to 16 October. An increase in efficiency by 1.28 % to
2.65 % was reported in this experimental study.
Keyword: Photo voltaic module, Computational fluid dynamics analysis, Solar
panel cleaning mechanism.
Adil Ashraf Bhukhari, B.Tech Student, Department of Mechanical and
Aerospace Engineering
Bhukhari, Adil Ashraf (2019). Experimental investigation of photovoltaic
module system coupled with solar panel cleaning system. Vibroengineering
Procedia, 29, 219-224.
Abstract: Solar energy is a non-conventional source of energy. Solar panels
generate electrical output by absorbing solar radiation. The performance of
photovoltaic (PV) module often depends on environmental factors like dust,
humidity, hail and temperature. Installation elements like altitude, installation
site, tilt angle also affects the efficiency of solar energy output. The objective of
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this research work is to clean the dust deposited on PV panels using the
minimum amount of water and energy. To regularly clean the dust, a semi-
automatic self-cleaning mechanism has been designed and fabricated, which
cleans the deposited dust on the solar panel automatically. Therefore, the process
turns out to be reliable and faster and it leads to increased power output of the
solar panels. An experimental investigation has been done at Bennett University;
Greater Noida dated 15 October to 21st October 2019. An increase in efficiency
by 1.2 % to 3 % was reported in this experimental study.
Keyword: Photovoltaic (PV), Nozzle, Semi-automatic self-cleaning mechanism.
Akshaj Kulshreshtha, B.Tech Student, Department of Mechanical and
Aerospace Engineering
Kulshreshtha, Akshaj (2019). Numerical simulation of vortex induced
vibrations on a circular cylinder at different Reynold’s number. Vibroengineering
Procedia, 29, 171-175.
Abstract: This research investigates the effect of vortex induced vibrations on
flow past a circular cylinder for two-dimensional unsteady incompressible flow
at different Reynold’s number. The pressure bases steady solver is used for
computation along with standard k-å turbulence model. The change in the lift and
drag coefficient with respect to increase in Reynolds number is studied and
contours of vorticity are plotted. The pressure distribution on the fixed cylinder
for different Reynolds number is also presented. It is found that drag coefficient
reduces with the increasing Re and lift coefficient increases up to Reynold’s
number 104. Moreover, the pressure difference on the fixed cylinder increases
with the increasing Reynold’s number.
Keyword: Vortex induced vibration (VIV), Wake flow, Standard k-å turbulence
model.
Kulshreshtha, Akshaj (2019). Sound radiation of simply supported rectangular
plate using finite element method. Vibroengineering Procedia, 29, 195-200.
Abstract: In this paper sound radiation of simply supported rectangular plate has
been reported. The novelty in this research paper is a new method is prescribed
for sound radiation calculation. The phenomenon of uncoupled structural
acoustics have been followed such that structure is the critical part in structural
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vibration using modal analysis and harmonic response calculation for frequency
range of interest 0 to 200 Hz, but in harmonic acoustic analysis the structure does
not takes part in physics point of view but is used for only for transferring the
normal velocity from wetted surface of the structure to the interface acoustic
medium i.e. air. Sound Radiation parameters like Sound Pressure Level, Sound
Power Level and Sound Radiation efficiency has been reported. Upon comparing
the results with that from I. Zaman’s literature, it is found that the results are
quite varying due to the fact the speed of sound in air as taken in literature is
unjustified. So true simulation using correct data has been carried out in this
paper and sound radiation results has been reported for frequency range of
interest 0 to 200 Hz. It is found that the maximum sound pressure level is 72 dB
and maximum sound power level is 78 dB which is suitable for noiseless
environment.
Keyword: Acoustic radiation, Sound pressure level, Acoustic power, Sound
power level, Radiation efficiency.
Amit Kumar Singh, Research Scholar, Department of Mechanical and
Aerospace Engineering
Singh, Amit Kumar (2018). FEM simulation of three-point bending test of
Inconel 718 coating on stainless steel substrate. Vibroengineering Procedia, 21,
248-252.
Abstract: Three-point bending test is conducted by help of Finite Element
Method to find out mechanical properties of Inconel 718 coating on stainless
steel. For doing this ANSYS package are employed to visualise exact situation
of bending test so that can find out stress field developed during the test. A 3D
modelling of coating and substrate material is used. Load versus displacement
relationships is compared with reference results. It is noticed that yield stress of
substrate material is higher than the tensile stress of substrate and coating. Due
to this reason there is initiation of crack at coating-substrate interface and it is
propagated which leads to failure with applied load.
Keyword: Three-point bending, Finite element method, Simulation, Coating.
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Singh, Amit Kumar (2019). Numerical analysis of temperature distribution in
sliding contacts of pin on disc model. Vibroengineering Procedia, 29, 274-278.
Abstract: Pin on disc is a tribosystem confirming to ASTM G99, is employed in
this work. It consists of deformable cylindrical disc and rigid pin with friction.
Coating of Inconel 712 is added on stainless steel disc and pin is made of SiC3.
The FEM software ANSYS R19.1 is employed for simulation of temperature
distribution produced due to friction between pin on disc. Stress distribution is
calculated from result produced between pin and disc interface due to applied
contact load on pin. The governing equation is mentioned in introduction section.
Result showing as contact load on pin increases maximum principle stress is
increases. Temperature rises in direct proportion with sliding distance and time.
Simulation result validates and confirmed with experimental results.
Keyword: Contact stress analysis, FEA, Pin on disc, Temperature distribution.
Arnab Bose, B.Tech Student, Department of Mechanical and Aerospace
Engineering
Bose, Arnab (2019). Natural Frequency Analysis of a Functionally Graded
Rotor System using Three-Dimensional Finite Element Method.
Vibroengineering Procedia, 29, 70-75.
Abstract: Three-dimensional Finite Element (FE) analysis has been carried out
using ANSYS software to study the natural frequencies of functionally graded
(FG) rotor system. Temperature and position-dependent material properties of
the FG shaft system are considered to be graded in the radial direction. Power-
law with the nonlinear temperature distribution (NLTD) and exponential law
with exponential temperature distribution (ETD) have been used to model the
material gradation and temperature distribution. Rotor systems of two different
FG materials, namely Stainless Steel-ZrO2 and Stainless Steel-Al2O3 have been
studied. Python codes have been developed to generate ANSYS macros that
apply the material properties. Simply supported FG shaft and FG rotor system
supported on bearings have been analyzed in the current work. The results show
the influence of different power-law coefficients, different material and material
laws on the natural frequencies of the rotor system. The effect of these
parameters on whirl frequencies has also been studied for FG rotor systems.
Keyword: functionally graded shaft, finite element, and whirl frequency.
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Ashish Kumar, Department of Mechanical and Aerospace Engineering
Kumar, Ashish (2018). Numerical study of shear thickening fluid with distinct
particles dispersed in carrier fluid. Vibroengineering Procedia, 21, 242-247.
Abstract: The Shear Thickening Fluid (STF) is a non- Newtonian fluid which
comes under dilatant material, STF undergoes phase transition from a low to
high viscosity when shear stress is applied on it. In this paper modelling and
simulation tools are used to study the STF fluid interaction when subjected to
applied shear stress. The Eulerian description used for the fluid flow and the
model considered the Lagrangian description of the rigid particles. The
numerical analysis inspects important guideline such as acceleration of the
flow, particle dispersion and the base of Non-Newtonian fluid. The fluid
particles interrelation of STF showed that the shape, arrangement, volume
concentration, and size of the particles had a vital effect on the behavior of STF.
By adding sand particles in non-Newtonian fluids and applying high shear
strain rates showed improvement in the shear thickening effects.
Keyword: Non-Newtonian fluid, Viscosity function, Shear thickening fluids
Kumar, Ashish (2019). Effect of slant angle variation on the drag force for
Ahmed body car model. Vibroengineering Procedia, 29, 153-158.
Abstract: In this paper, numerical investigation is carried out on two-
dimensional Ahmed body model using Computational Fluid Dynamics in
ANSYS Fluent 19.1. The 2-D model is designed in Catia v5 for 25°, 35° and 45°
slant angles. The turbulent model used to analyze the flow dynamics is
Realizable k-å model. The drag coefficient variation with respect to slant angle is
computed. The skin friction coefficient, wall shear stress and frictional velocity
are also calculated.
Keyword: Slant angle, Drag force, Ahmed body, and frictional velocity.
Kumar, Ashish (2019). Numerical analysis of single grit grinding on aluminum
workpiece. Vibroengineering Procedia, 29, 291-294.
Abstract: Grinding is a finishing process used in almost every industry. The
purpose of this research is to study the effects of grinding on aluminum. Finite
Element Method (FEM) is used to numerically simulate grinding by using
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microscale modeling. It is found that though under grinding, stress mises
developed do not exceed yield stress. The force variation and displacement
parameters have been correspondingly discussed. The effects of grinding on the
workpiece with and without lubrication.
Keyword: Grit grinding, Microscale modelling, Friction coefficient, Stress
analysis
Ashish Saurabh, Research Scholar, Department of Mechanical and
Aerospace Engineering
Saurabh, Ashish (2019). Computational fluid dynamics (CFD) modelling of
hybrid photovoltaic thermal system. Vibroengineering Procedia, 29, 243-248.
Abstract: In this paper an attempt has been made to simulate and evaluate the
distribution of temperature and heat flux for the hybrid photovoltaic thermal
system with CFD (computational fluid dynamics) module in ANSYS 19.1
software. The simulation was carried to determine the temperature and heat flux
across the different layers of HPVT (hybrid photovoltaic thermal) system. The
temperature and heat flux were found to gradually decrease from the top glass
layer to the bottom tedlar layer. The temperature varied from 36.4 °C (ambient)
to 26.8 °C across the layers from top glass layer to bottom tedlar layer. The heat
flux of (561.2 W/m2) at the glass layer due to solar insolation was also found to
gradually decrease with the increasing thickness. The reduction in temperature
and heat flux with increasing thickness is attributed to fluid flowing beneath the
system. The water flowing beneath the tedlar layer takes the excess heat out of
the photovoltaic layer, thereby increasing the efficiency of the hybrid
photovoltaic thermal system.
Keyword: Computational fluid dynamics, Hybrid photovoltaic thermal system,
Temperature distribution.
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Baij Nath Singh, Research Associate, Department of Mechanical and
Aerospace Engineering
Singh, Baij Nath (2017). Vibration Model Localization of Aluminum
Rectangular Plate. International Journal of Advance Research in Science and
Engineering, 6(2), 350-362.
Abstract: Modal analyses are carried out to calculate the natural frequencies
and natural modes of the system. Ship structures are stealth shaped structures and
these stealth structures are simulated by taking an assumption that structures are
plane and homogenous throughout. Rectangular aluminum plate model is
simulated in this paper using ABAQUS® 13.1 and Pulse 18.1. Vibration Mode
localization analysis using point mass variation has been carried out. Mode
shapes and frequencies obtained in this paper shows that vibration along major
portion of the plate is found to be curbed. Often modal analyses are performed
using a somewhat coarser mesh, since the mode shapes and Eigen frequencies
can be accurately estimated as long as the basic mass and stiffness distributions
are correct. In one way or the other this analysis can also be said as acoustic
analysis as sound transmitted by hammer impact on the aluminum plate is
transformed into voltage signals by the use of accelerometer containing
piezoelectric material. The voltage signal is transformed into displacement signal
and frequency signal by means of amplifier used in the setup of the experimental
modal analysis software Pulse 18.1.
Keyword: ABAQUS CAE, Modal Analysis,
Singh, Baij Nath (2019). Numerical analysis of single grit grinding on
aluminum workpiece. Vibroengineering Procedia, 29, 291-294.
Abstract: Grinding is a finishing process used in almost every industry. The
purpose of this research is to study the effects of grinding on aluminum. Finite
Element Method (FEM) is used to numerically simulate grinding by using
microscale modeling. It is found that though under grinding, stress mises
developed do not exceed yield stress. The force variation and displacement
parameters have been correspondingly discussed. The effects of grinding on the
workpiece with and without lubrication.
Keyword: Grit grinding, Microscale modelling, Friction coefficient, Stress
analysis
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Dr. Deepali Atheaya, Assistant Professor, Department of Mechanical and
Aerospace Engineering
Atheaya, Deepali (2017). Economics of solar drying. Solar Drying Technology
Concept, Design, Testing, Modeling, Economics, and Environment (pp. 441-
462).
Abstract: Solar drying is an ancient and inexpensive technique used for the
preservation of agricultural item. Solar drying involves the removal of moisture
content from crop. It is very important that the solar crop drying system should
be cost-effective. Different methods of solar drying have been developed like
open sun drying and greenhouse solar drying. The recent development in this
area is greenhouse photovoltaic thermal mixed mode drying in which electricity
is also produced while crop drying is done. This system is quite useful for people
living in remote areas. The solar drying of commercial industrial crops such as
cotton, jute, sugarcane, tobacco, and ground nut has been popular and feasible.
There is a need to invent cheaper solar drying methods to meet the demands of
farmers of developing countries
Keywords: Cash flow, Uniform annual cost, Payback period, Net present value
Atheaya, Deepali (2017). Thermodynamic analysis of a novel design of
conventional compound parabolic concentrator system integrated with an organic
Rankine. Proceedings of National Conference on “Design & Innovation” (pp. 69-
73).
Abstract: In this paper a novel design of conventional compound parabolic
concentrator system coupled with an organic rankine cycle has been proposed.
The exergetic efficiency and exergy destruction have been calculated to evaluate
the system performance by using zeotropic mixture of cyclopentane/R1234yf.
The results indicated that the zeotropic mixture exhibited better exergetic
efficiency and lower exergy destruction than pure fluid. Further, the internal heat
exchanger was also incorporated in the system. It was observed that first law
efficiency improved, and exergy destruction reduced. The proposed system can
be utilized for the power generation purposes and be the best answer for solving
the energy crisis all across the globe
Keyword: Organic rankine cycle (ORC), Zeotropic mixture, Exergy
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Atheaya, Deepali (2019). Performance analysis of thermoelectric generator by
using lead telluride, perovskites, skutterudites and tetrahedrites. WEENTECH
Proceedings in Energy (pp. 566-78).
Abstract: In this research paper performance analysis of thermoelectric
generator by using lead telluride, perovskites, skutterudites and tetrahedrites has
been proposed. The performance of thermoelectric materials and thermoelectric
modules has been calculated. These thermoelectric materials were combined to
make thermoelectric couple which will be used in thermoelectric generator. The
performance analysis of these thermoelectric couples were simulated on
COMSOL Multiphysics 5.2 software. The results indicated that Pb1-
xMgxTe0.8Se0.2 and n-type PbTe, Pb1-xMgxTe0.8Se0.2 and CoSb3-xTex, Pb1-
xMgxTe0.8Se0.2 and CaMn0.98Nb0.02O3, Cu12Sb4S13 and CoSb3-xTex
indicated higher efficiency than other thermoelectric couples. The proposed
system can be utilized for varied range of applications for waste heat recovery
and renewable power generation in automotive, industrial, power plants and
space sector at an excellent efficiency and lower cost.
Keyword: Seebeck effect, Lead telluride, Perovskites, Skutterudites, Tetrahedrit
Atheaya, Deepali (2016). Effect of Angle of Abduction and Illumination Level
on Performance in a Human-Machine Interaction Environment. Global Journal
of Enterprise Information System, 8(4), 11-17.
Abstract: An experimental investigation was conducted to evaluate the human
performance in the context of human-machine interaction environment. It was
observed that both the illumination level and an angle of abduction have
significant effect on human performance when workers work in human-machine
interaction environment.
Keyword: Anthropometry, Angle of Abduction, Ergonomics, Illumination Level
Atheaya, Deepali (2017). Energy and exergy analysis of solar driven
recuperated organic Rankine cycle using glazed reverse absorber conventional
compound parabolic concentrator (GRACCPC) system. Solar Energy, 1431-
1442.
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Abstract: In this research work, the computer code is written in MATLAB 9.0
which is interfaced with Refprop 9.0. In order to develop a thermodynamic
model of solar driven organic Rankine cycle. A novel glazed reverse absorber
conventional compound parabolic concentrator integrated with recuperated
organic Rankine cycle case (ii) using low global warming potential and zero
ozone depletion potential working fluid cyclohexane/R245fa has been proposed.
The coding has been done to evaluate hourly concentrator fluid outlet
temperature, heat gain in concentrator, expander output, overall thermal
efficiency, overall exergetic efficiency and exergy destruction. The performance
of the glazed reversed absorber conventional compound parabolic concentrator
integrated with recuperated organic Rankine cycle case (ii) has been compared
with glazed reversed absorber compound parabolic concentrator with non
recuperated organic Rankine cycle case (i). It is observed that overall, first law
efficiency improves by 40.9% and exergetic efficiency 36.28% using recuperated
organic Rankine ORC case (ii) in comparison of non-recuperated ORC case
(i). The system in case ii has been found to be self-sustainable system and
gives better result in term of thermal efficiency, environmental, space heating,
day lighting and electricity use.
Keyword: Reverse absorber, Compound parabolic concentrator, Zeotropic
mixture
Atheaya, Deepali (2017). Review on Solar Thermal Power Concentrators. MOJ
Solar Photoen Sys, 1(3), 71-89.
Abstract: In this review, an attempt has been made to explore all the possibility
of solar thermal concentrator to be used for various applications namely cleaner
power generation, heat process, and solar cooking etc. Classification of
concentrators, applications, thermal modelling, energy and exergy analysis based
on energy balances carried out by many researchers have been reviewed. The
optical, thermal and exergy efficiency of some system have also been discussed
in terms of concentration ratio. Recent progresses in the advances of solar
concentrators integrated with photovoltaic module have been proposed and
analyzed with a characteristic equation.
Keyword: Solar concentrator, Concentration ratio, Exergy, Photovoltaic thermal
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Atheaya, Deepali (2018). Performance evaluation of Jaipur knee joint through
kinematics gait symmetry with unilateral transfemoral Indian amputees.
Vibroengineering Procedia, 21, 149-154.
Abstract: Gait analysis is considered as the most systematic study of human
motion. The analysis of gait includes visual and analytical perception of the
individual, augmentation of various mechanical instrumentations for measuring
movement of body, muscles activity and body mechanics. Past study focused
on gait analysis of various animal locomotion and humans mainly on sports
biomechanics. This paper aims to quantify the gait performance with Jaipur
Knee, which is one of the most widely used prosthesis in Indian population.
Gait data with Jaipur knee joint is not available till date. The proposed study
targets to predict the performance of Jaipur knee joint in terms of gait symmetry
with transfemoral Indian amputees. Gait symmetry may be the basis of
recommendation of knee joint to prosthetic patients. This study used kinematics
and kinetics parameters together to quantify the performance of Jaipur knee
joint to evaluate gait symmetry. This research will be helpful for clinician to
predict and further to prevent the degenerated musculoskeletal effects generally
seen in unilateral transfemoral amputees.
Keyword: Amputation, Gait Analysis, Jaipur knee, Transfemoral, Prosthesis,
Atheaya, Deepali (2018). Thermodynamic analysis of solar power organic
Rankine cycle based on experimental data. International Journal of Ambient
Energy, 1-8.
Abstract: In the current work, analytical expressions have been coded in
MATLAB 9.0 linked with REFPROP 9.0, for solar-powered ORC system
integrated with conventional compound parabolic concentrator using
environment-friendly hexane/R1234yf zeotropic mixture to calculate hourly (8
AM to 4 PM) combined performance of solar power ORC based on
experimental data. It has been observed that maximum heat gain in the collector
is 5.132 × 105 W at 1 PM for the mass fraction (0.7/0.3). Moreover, maximum
overall thermal efficiency 17.65% is attained at 1 PM for the mass fraction
0.3/0.7 whereas overall exergetic efficiency 49.23% is achieved at the same
time for the mass fraction 0.3/0.7
Keyword: Conventional compound, parabolic concentrator, zeotropic mixture,
exergy
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Atheaya, Deepali (2019). Computational fluid dynamics (CFD) modelling of
hybrid photovoltaic thermal system. Vibroengineering Procedia, 29, 243-248.
Abstract: In this paper an attempt has been made to simulate and evaluate the
distribution of temperature and heat flux for the hybrid photovoltaic thermal
system with CFD (computational fluid dynamics) module in ANSYS 19.1
software. The simulation was carried to determine the temperature and heat flux
across the different layers of HPVT (hybrid photovoltaic thermal) system. The
temperature and heat flux were found to gradually decrease from the top glass
layer to the bottom tedlar layer. The temperature varied from 36.4 °C (ambient)
to 26.8 °C across the layers from top glass layer to bottom tedlar layer. The heat
flux of (561.2 W/m2) at the glass layer due to solar insolation was also found to
gradually decrease with the increasing thickness. The reduction in temperature
and heat flux with increasing thickness is attributed to fluid flowing beneath the
system. The water flowing beneath the tedlar layer takes the excess heat out of
the photovoltaic layer, thereby increasing the efficiency of the hybrid
photovoltaic thermal system.
Keyword: Computational fluid dynamics, Hybrid photovoltaic thermal system,
Temperature distribution.
Atheaya, Deepali (2019). Computational fluid dynamics analysis and
experimental validation of solar panel cleaning mechanism. Vibroengineering
Procedia, 29, 225-230.
Abstract: Solar energy is one of the widely used non-conventional form of
energy. Photo voltaic panels generate electricity and heat by absorbing solar
irradiation. The performance of solar panels depends on several factors like dust
accumulation on the surface, solar cell temperature, angle of inclination etc., to
perform the cleaning action efficiently a semi-automatic cleaning mechanism has
been designed and fabricated. The designed experimental setup consists of
several nozzles attached on top of the solar panels and water is supplied to each
nozzle using a Poly Vinyl Chloride (PVC) pipe frame connected to an AC motor
operated with a time switch. Water flows on the surface of photo voltaic module,
thus heat exchange takes place. One dimensional heat transfer analysis is
performed, and the results are compared to the experimental results for
validation. The experiments were conducted at Bennett University, Greater
Noida dated 9 October to 16 October.
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An increase in efficiency by 1.28 % to 2.65 % was reported in this experimental
study.
Keyword: Photo voltaic module, Computational fluid dynamics analysis, Solar
panel cleaning mechanism
Atheaya, Deepali (2019). Experimental investigation of photovoltaic module
system coupled with solar panel cleaning system. Vibroengineering Procedia,
29, 219-224.
Abstract: Solar energy is a non-conventional source of energy. Solar panels
generate electrical output by absorbing solar radiation. The performance of
photovoltaic (PV) module often depends on environmental factors like dust,
humidity, hail and temperature. Installation elements like altitude, installation
site, tilt angle also affects the efficiency of solar energy output. The objective of
this research work is to clean the dust deposited on PV panels using the
minimum amount of water and energy. To regularly clean the dust, a semi-
automatic self-cleaning mechanism has been designed and fabricated, which
cleans the deposited dust on the solar panel automatically. Therefore, the process
turns out to be reliable and faster and it leads to increased power output of the
solar panels. An experimental investigation has been done at Bennett University;
Greater Noida dated 15 October to 21st October 2019. An increase in efficiency
by 1.2 % to 3 % was reported in this experimental study.
Keyword: Photovoltaic (PV), Nozzle, Semi-automatic self-cleaning mechanism
Atheaya, Deepali (2019). Experimental study of self-sustainable hybrid solar
photovoltaic cleaning mechanism coupled with water distillation unit.
Vibroengineering Procedia, 29, 213-218.
Abstract: In the present research work a novel self-sustainable hybrid solar
photovoltaic cleaning mechanism coupled with water distillation unit has been
proposed. The experiments were conducted on the PV (photovoltaic) modules at
Bennett University, Greater Noida A-block terrace from 7th to 13th October
2019. Post installation, the average efficiencies of the solar PV module system
with and without cleaning were compared to obtain a hike by 1.34 %. The water
used for cleaning was recycled using a single slope basin type solar still which
indicated a working efficiency of 67.94 %. On an average the solar still yielded
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5.3 Liters of pure water every day during the experiment with a TDS (total
dissolved solids) level of 104 ppm.
Keyword: Photovoltaic modules, Cleaning mechanism, Water distillation unit,
Efficiency.
Atheaya, Deepali (2019). Optimization and analysis of novel thermoelectric
module. Vibroengineering Procedia, 29, 231-236.
Abstract: Optimization and analysis of novel thermoelectric module is proposed
in this research paper. The simulation for four thermoelectric modules were
performed in COMSOL Multiphysics 5.4 software and detailed analysis of these
thermoelectric modules were carried out. The three thermoelectric modules
showed the efficiency and power output above-average thermoelectric modules.
It also indicated that lead telluride based thermoelectric modules could be used in
isolated areas due to toxicity of lead whereas tetrahedrite based thermoelectric
module could be used in non-isolated areas due to its non-toxic properties. The
proposed thermoelectric modules can be utilized in applications such as
industries, deep space explorations, automobiles, thermal power plants,
renewable electricity generation, hybrid renewable systems, etc. in an
economically viable manner.
Keyword: Thermoelectric module, Lead telluride, Tetrahedrites, Skutterudites,
Perovskites.
Ganesh Naik Guguloth, B.Tech Student, Department of Mechanical and
Aerospace Engineering
Guguloth, Ganesh Naik (2019). Free vibration analysis of simply supported
rectangular plates. Vibroengineering Procedia, 29, 270-273.
Abstract: In this paper, numerical analysis for free vibration of simply supported
thin rectangular plates has been simulated using Ansys. The vibration of plate
follows Kirchhoff plate theory. The natural frequency calculated using Ansys has
been compared with Levy type solution results available in the literature.
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It is observed that the natural frequencies of the simply supported rectangular
plate is in close agreement with exact solution results as reported in literature.
Keyword: Kirchhoff plate theory, Levy solution, Simply supported rectangular
plate.
Dr. Kaushik Saha, Assistant Professor, Department of Mechanical and
Aerospace Engineering
Saha, Kaushik (2018). Evaluation of a new cavitation erosion metric based on
fluid-solid energy transfer in channel flow simulations. 14th International
Conference on Liquid Atomization and Spray Systems (pp. 1-9).
Abstract: Although there have been extensive investigations characterizing
cavitation phenomenon in fuel injectors, much is still unknown about the
mechanisms driving cavitation-induced erosion, and how these complicated
physics should be represented in a model. In lieu of computationally expensive
fluid-structure interaction modeling, the Eulerian mixture modeling approach
has been accepted as an efficient means of capturing cavitation phenomena.
However, there remains a need to link the erosive potential of cloud collapse
events with the subsequent material deformation and damage of neighboring
surfaces. Even though several cavitation erosion indices have been proposed in
the literature, no single metric has been identified as universally applicable
across all injector relevant conditions. The objective of this work is to identify
parameters that characterize the erosive potential of cavitation cloud collapse
mechanisms that are likely to occur within injector orifices. While a commonly
employed cavitation erosion metric, namely the maximum local pressure, was
found to provide indications of potential sites for pitting and material rupture
from single impact events, no additional information could be determined
regarding the material erosion process. To improve representation of the
incubation period within the cavitation erosion process, a new metric was
derived based on cumulative energy absorbed by the solid material from
repeated hydrodynamic impacts. Through evaluation of predicted cavitation
cloud collapse events in a channel geometry against available experimental
data, the stored energy metric yielded insight into the erosive potential of
recorded impact events. The stored energy metric provided a means to
accurately predict the influence of flow conditions on the incubation period
before material erosion.
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Additionally, detailed analysis of cavitation cloud collapse events preceding
impacts suggests that the cloud collapse mechanism governs the erosive
potential of impacts and the resultant incubation period. Specifically, horseshoe
cloud implosions were found to yield higher impact energies relative to
spherical cloud collapse events.
Keyword: Diesel injector, Cavitation cloud collapse, Homogeneous relaxation
model, Erosion index
Saha, Kaushik (2018). Modeling the Dynamic Coupling of Internal Nozzle
Flow and Spray Formation for Gasoline Direct Injection Applications. SAE
World Congress (pp. 13).
Abstract: A numerical study has been carried out to assess the effects of needle
movement and internal nozzle flow on spray formation for a multi-hole
Gasoline Direct Injection system. The coupling of nozzle flow and spray
formation is dynamic in nature and simulations with pragmatic choice of spatial
and temporal resolutions are needed to analyze the sprays in a GDI system. The
dynamic coupling of nozzle flow and spray formation will be performed using
an Eulerian-Lagrangian Spray Atomization (ELSA) approach. In this approach,
the liquid fuel will remain in the Eulerian framework while exiting the nozzle,
while, depending on local instantaneous liquid concentration in a given cell and
amount of liquid in the neighboring cells, part of the liquid mass will be
transferred to the Lagrangian framework in the form of Lagrangian parcels.
Such approach requires solving an additional transport equation apart from the
conservation equations of mass, momentum, species, energy, and turbulence in
Eulerian framework. This additional equation is termed as the Σ equation. Σ
represents the liquid-gas interfacial area per unit volume in a given
computational cell. Once the liquid mass is transferred to the Lagrangian
framework, parcels undergo breakup, collision, coalescence and evaporation,
similar to any typical Lagrangian spray approach. This hybrid approach will
have the potential of capturing the transient flow characteristics due to needle
movement transcending downstream and affecting time-fluctuating spray
phenomenon. The Spray G condition from the Engine Combustion Network
(ECN) has been chosen for this study. Parametric studies on the effect of
turbulence models, Eulerian to Lagrangian mass transfer criterion, breakup
models have been performed.
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While these simulations are very expensive, they are expected to be more
predictive than the standing approach of initializing a Lagrangian simulation
with a ‘blob’ injection model. Simulation predictions with ELSA are shown to
be in good agreement with measured data on spray penetration, and gas
velocities, available in the literature.
Keyword: Dynamic coupling, Internal nozzle flow, Gasoline direct injection,
Spray formation
Madhusmita Mohanta, Research Scholar, Department of Mechanical and
Aerospace Engineering
Mohanta, Madhusmita (2018). Indian railway track analysis for displacement
and vibration pattern estimation. Vibroengineering Procedia, 21, 71-76.
Abstract: This paper presents the dynamic response of the Indian Railway
track. Two track models are considered for the dynamic response in terms of
vertical displacement and acceleration at different wheel speeds, keeping the
moving point load at constant magnitude. The rail is treated as a beam either on
viscoelastic foundation or on the discrete elastic support system. The governing
equation is implemented in finite element analysis using ANSYS 14.0. For the
validation of result from system equation are compared with those available in
published literature and the maximum deviation for displacement at the
midpoint of rail is found to be within 5 %. Different wheel speed generates
variation in displacement and acceleration of the rail track. The study can be
viewed as the foundation for the comparison of FEA based simulation of rail
track to specify its dynamic response useful to provide better safety and comfort
to commuters
Keyword: Viscoelastic foundation, Discrete elastic support
Mohanta, Madhusmita (2018). Performance evaluation of Jaipur knee joint
through kinematics gait symmetry with unilateral transfemoral Indian
amputees. Vibroengineering Procedia, 21, 149-154.
Abstract: Gait analysis is considered as the most systematic study of human
motion. The analysis of gait includes visual and analytical perception of the
individual, augmentation of various mechanical instrumentations for measuring
movement of body, muscles activity and body mechanics. Past study focused
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on gait analysis of various animal locomotion and humans mainly on sports
biomechanics. This paper aims to quantify the gait performance with Jaipur
Knee, which is one of the most widely used prosthesis in Indian population.
Gait data with Jaipur knee joint is not available till date. The proposed study
targets to predict the performance of Jaipur knee joint in terms of gait symmetry
with transfemoral Indian amputees. Gait symmetry may be the basis of
recommendation of knee joint to prosthetic patients. This study used kinematics
and kinetics parameters together to quantify the performance of Jaipur knee
joint to evaluate gait symmetry. This research will be helpful for clinician to
predict and further to prevent the degenerated musculoskeletal effects generally
seen in unilateral transfemoral amputees.
Keyword: Amputation, Gait Analysis, Jaipur knee, Transfemoral, Prosthesis,
Manish Chauhan, Research Scholar, Department of Mechanical and
Aerospace Engineering
Chauhan, Manish (2018). Comparison of natural frequencies of isotropic plate
using DSM with Wittrick-Williams algorithm. Vibroengineering Procedia, 21,
59-64.
Abstract: In this paper, comparison of natural undamped frequencies of
isotropic plates are investigated by using the dynamics stiffness element for
isotropic plates. The DS Matrix for isotropic has been formulated by the
application of classical plate theory. The generalized DS matrix has to solve by
using Wittrick-Williams algorithm. Results of different aspect ratio have been
validated from the existing literature.
Keyword: Dynamic stiffness matrix, Isotropic plate
Chauhan, Manish (2019). Dynamic stiffness method for free vibration analysis
of thin functionally graded rectangular plates. Vibroengineering Procedia, 29, 76
-81.
Abstract: In this present work, the dynamic stiffness method (DSM) is used to
analyze the free vibration of a thin functionally graded rectangular plate.
Classical plate theory (CPT) is used to develop the dynamic stiffness matrix of a
functionally graded material (FGM) plate. For free vibration analysis, the natural
frequencies of the functionally graded material plate are estimated by using DSM
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with Wittrick-Williams algorithm for different aspect ratios and different
boundary conditions. The present research compared the DSM natural
frequencies results with those available in the published literature.
Keyword: Dynamic stiffness method, Free vibration, Functionally graded
material, CPT.
Dr. Mohammad Danish, Assistant Professor, Department of Mechanical
and Aerospace Engineering
Danish, Mohammad (2018). Numerical simulation of Vortex-shedding from
NACA4418 hydrofoil. Vibroengineering Procedia, 21, 121-130.
Abstract: To get better understanding of vortex shedding mechanism, we
conducted numerical simulation on NACA 4418 hydrofoil at an angle of attack
of 12° for 2D incompressible flow. The numerical method consists of transient,
finite volume method using Transient SST turbulent model to capture the
turbulent wake flows. At high Reynolds number the occurrence of 2D structures
of shed vortices and the modulation of vortex-induced frequency are
investigated. The lift, pressure and skin friction coefficients of hydrofoil were
studied
Keyword: NACA 4418, Hydrofoil, Vortex shedding, Transition SST
Danish, Mohammad (2018). Numerical study of shear thickening fluid with
distinct particles dispersed in carrier fluid. Vibroengineering Procedia, 21, 242-
247.
Abstract: The Shear Thickening Fluid (STF) is a non- Newtonian fluid which
comes under dilatant material, STF undergoes phase transition from a low to
high viscosity when shear stress is applied on it. In this paper modelling and
simulation tools are used to study the STF fluid interaction when subjected to
applied shear stress. The Eulerian description used for the fluid flow and the
model considered the Lagrangian description of the rigid particles. The
numerical analysis inspects important guideline such as acceleration of the
flow, particle dispersion and the base of Non-Newtonian fluid.
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The fluid particles interrelation of STF showed that the shape, arrangement,
volume concentration, and size of the particles had a vital effect on the behavior
of STF. By adding sand particles in non-Newtonian fluids and applying high
shear strain rates showed improvement in the shear thickening effects.
Keyword: Non-Newtonian fluid, Viscosity function, Shear thickening fluids
Danish, Mohammad (2019). Computational investigation of cavitating flow
around two dimensional NACA 4424 and MHKF-240 hydrofoil.
Vibroengineering Procedia, 29, 159-164.
Abstract: This study focuses on the comparison of the performance of two
unsymmetrical hydrofoils, NACA 4424 and MHKF-240 at 60 angles of attack
under cavitation. The Schnarr and Sauer cavitation model along with Realizable
k-å turbulence model is used for numerical computation in commercial software
ANSYS Fluent. The lift drags and pressure coefficients for different cavitation
numbers were studied. Among both the hydrofoils MHKF-240 gives a higher lift
coefficient which is the parameter of better performance.
Keyword: NACA 4424, MHKF-240, realizable k-å, Schnarr and Sauer model.
Danish, Mohammad (2019). Numerical modelling of shear thickening fluid in
nanosilica dispersion. Vibroengineering Procedia, 29, 260-265.
Abstract: In this paper, a numerical model of the shear thickening fluid (STF) is
generated and the rheological properties are compared with the experimental
data. Power Law model has been used to fit the rheological data for STF.
Experimental data is taken from a performed study and a user defined function
(UDF) has been written to develop the shear thickening behavior. The purpose of
this study is to exactly model the behavior of shear thickening fluids by using
UDF, to explain the shear-thickening mechanisms under different shear rates.
Different parameters like viscosity, shear stress and velocity of the STF have also
been reported.
Keyword: Non-Newtonian fluid, Viscosity function, Shear thickening fluids
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Dr. Neelanchali Asija Bhalla, Assistant Professor, Department of
Mechanical and Aerospace Engineering
Bhalla, Neelanchali Asija (2018). Numerical study of shear thickening fluid
with distinct particles dispersed in carrier fluid. Vibroengineering Procedia, 21,
242-247.
Abstract: The Shear Thickening Fluid (STF) is a non- Newtonian fluid which
comes under dilatant material, STF undergoes phase transition from a low to
high viscosity when shear stress is applied on it. In this paper modelling and
simulation tools are used to study the STF fluid interaction when subjected to
applied shear stress. The Eulerian description used for the fluid flow and the
model considered the Lagrangian description of the rigid particles. The
numerical analysis inspects important guideline such as acceleration of the
flow, particle dispersion and the base of Non-Newtonian fluid. The fluid
particles interrelation of STF showed that the shape, arrangement, volume
concentration, and size of the particles had a vital effect on the behavior of STF.
By adding sand particles in non-Newtonian fluids and applying high shear
strain rates showed improvement in the shear thickening effects.
Keyword: Non-Newtonian fluid, Viscosity function, Shear thickening fluids
Bhalla, Neelanchali Asija (2019). Effect of slant angle variation on the drag
force for Ahmed body car model. Vibroengineering Procedia, 29, 153-158.
Abstract: In this paper, numerical investigation is carried out on two-
dimensional Ahmed body model using Computational Fluid Dynamics in
ANSYS Fluent 19.1. The 2-D model is designed in Catia v5 for 25°, 35° and 45°
slant angles. The turbulent model used to analyze the flow dynamics is
Realizable k-å model. The drag coefficient variation with respect to slant angle is
computed. The skin friction coefficient, wall shear stress and frictional velocity
are also calculated.
Keyword: Slant angle, Drag force, Ahmed body, frictional velocity.
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Bhalla, Neelanchali Asija (2019). Numerical modelling of shear thickening
fluid in nanosilica dispersion. Vibroengineering Procedia, 29, 260-265.
Abstract: In this paper, a numerical model of the shear thickening fluid (STF) is
generated and the rheological properties are compared with the experimental
data. Power Law model has been used to fit the rheological data for STF.
Experimental data is taken from a performed study and a user defined function
(UDF) has been written to develop the shear thickening behavior. The purpose of
this study is to exactly model the behavior of shear thickening fluids by using
UDF, to explain the shear-thickening mechanisms under different shear rates.
Different parameters like viscosity, shear stress and velocity of the STF have also
been reported.
Keyword: Non-Newtonian fluid, Viscosity function, Shear thickening fluids
Bhalla, Neelanchali Asija (2019). Study on the low and high strain rate behavior
of fumed nano silica dispersions. Procedia Structural Integrity, 14, 564-570.
Abstract: Shear Thickening Fluids (STFs) are a special class of field responsive
non-Newtonian fluids which exhibit transition from low viscosity to high
viscosity state when they are subjected to shearing deformation above the critical
shear rate (CSR). Due to this unique characteristic of STFs, these have found
application in ballistics, especially in the development of special class of body
armors called Liquid Body Armors (LBAs) which are lighter in weight and more
flexible as compared to conventional heavy armours. Fumed silica (FS) is a
rheologically significant material as it is a well-known viscosity modifier owing
to its fractal structure, and is generally used in paints, coatings, sealants, printing
inks etc. In this study, two different grades of FS (A-130 and A-150) were used
for the synthesis of STFs. The low strain rate studies were conducted on cone and
plate rheometer and high strain rate experiments were accomplished on split
Hopkinson pressure bar (SHPB) set up. The colloidal dispersions in PPG-400
(Poly Propylene Glycol 400) were synthesized using ultrasonic homogenization
technique. From the experiments it was observed that A-150 fumed silica
dispersion exhibited higher severity in shear thickening in the low strain rate
domain, whereas A-130 fumed silica dispersion exhibited higher specimen stress
and compressional strain rate under high strain rate dynamic compressive
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loading. Thus, it can be inferred that the same material may exhibit different
behaviors in the low and high strain rate regimes. Therefore, both the studies play
a vital role to completely characterize the material, especially when the material
has to be subjected to ballistic applications.
Keyword: Fumed silica, Split Hopkinson Pressure Bar
Pawan Mishra, Research Associate, Department of Mechanical and
Aerospace Engineering
Mishra, Pawan (2019). Assessment of foot trajectories and ground reaction
force in a trans-femoral amputee with Jaipur Knee and 3R20 knee joints.
Vibroengineering Procedia, 29, 189-194.
Abstract: In developing countries like India, unilateral transfemoral amputees
encounter with the challenge to select and evaluate the knee joint performance.
This study aims to evaluate the response of knee joint on vertical ground reaction
forces (vGRFs), walking speed, range of motion (ROM) of joints like hip, knee
and ankle joints in first two weeks and enhanced response. Movements of
different joints were recorded through VICON motion analysis system. Vertical
ground reaction forces were captured through AMTI strain gauzed force plate. It
has been observed that in two weeks normalized speed increases 0.41 to 0.49
with 3R20. Range of motion of joints was observed with interesting fact that in
general with 3R20, joints angle their respective ROM were more than Jaipur
Knee but in same cases in second half of gait cycle Jaipur Knee responded better
than 3R20 knee joint.
Keyword: Adaptation, range of motion (ROM), Transfemoral, Jaipur Knee
3R20.
Mishra, Pawan (2019). Performance Evaluation of Jaipur Knee Joint through
Kinematics and Kinetics Gait Symmetry with Unilateral Transfemoral Indian
Amputees. Journal of Medical Systems, 43(3), 2-8.
Abstract: Gait analysis is considered as the most systematic study of human
motion. The analysis of gait includes visual and analytical perception of the
individual, augmentation of various mechanical instrumentations for measuring
movement of body, muscles activity and body mechanics. Past study focused on
gait analysis of various animal locomotion and humans mainly on sports
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biomechanics. This paper aims to quantify the gait performance with Jaipur
Knee, which is one of the most widely used prosthesis in Indian population. Gait
data with Jaipur knee joint is not available till date. The proposed study targets to
predict the performance of Jaipur knee joint in terms of gait symmetry with
transfemoral Indian amputees. Gait symmetry may be the basis of
recommendation of knee joint to prosthetic patients. This study used kinematics
and kinetics parameters together to quantify the performance of Jaipur knee joint
to evaluate gait symmetry. This research will be helpful for clinician to predict
and further to prevent the degenerated musculoskeletal effects generally seen in
unilateral transfemoral amputees.
Keyword: Amputation, Gait Analysis, Jaipur knee, Transfemoral, Prosthesis
Dr. Prabhakar Sathujoda, Professor, Department of Mechanical and
Aerospace Engineering
Sathujoda, Prabhakar (2018). FEM simulation of three-point bending test of
Inconel 718 coating on stainless steel substrate. Vibroengineering Procedia, 21,
248-252.
Abstract: Three-point bending test is conducted by help of Finite Element
Method to find out mechanical properties of Inconel 718 coating on stainless
steel. For doing this ANSYS package are employed to visualise exact situation
of bending test so that can find out stress field developed during the test. A 3D
modelling of coating and substrate material is used. Load versus displacement
relationships is compared with reference results. It is noticed that yield stress of
substrate material is higher than the tensile stress of substrate and coating. Due
to this reason there is initiation of crack at coating-substrate interface and it is
propagated which leads to failure with applied load.
Keyword: Three-point bending, Finite element method, Simulation, Coating.
Sathujoda, Prabhakar (2019). Dynamic stiffness method for free vibration
analysis of thin functionally graded rectangular plates. Vibroengineering
Procedia, 29, 76-81.
Abstract: In this present work, the dynamic stiffness method (DSM) is used to
analyze the free vibration of a thin functionally graded rectangular plate.
Classical plate theory (CPT) is used to develop the dynamic stiffness matrix of a
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functionally graded material (FGM) plate. For free vibration analysis, the natural
frequencies of the functionally graded material plate are estimated by using DSM
with Wittrick-Williams algorithm for different aspect ratios and different
boundary conditions. The present research compared the DSM natural
frequencies results with those available in the published literature.
Keyword: Dynamic stiffness method, Free vibration, Functionally graded
material, CPT.
Sathujoda, Prabhakar (2019). Moisture absorption in thick composite plates:
modelling and experiments. Multidiscipline Modeling in Materials and
Structures.
Abstract: Purpose – When a thick structure is, on the contrary, subjected to
moisture absorption, a fairly long time may be needed to reach full saturation. It
is, therefore, important to understand and predict the areas of complex composite
structures that are more prone to saturation. The material knock-down factors
(proportional to the moisture content) may be applied only to these zones, in
order to obtain a less pessimistic structural response prediction. The purpose of
this paper is to investigate an FE diffusion model that was used to validate the
absorption testing results of thick carbon epoxy laminates. Design/methodology/
approach – The experimental results were validated by using a diffusion model in
Abaqus FE code. Findings – The absorption results of three 15 mm thick carbon
epoxy laminates are presented and reproduced via a mass diffusion model. The
laminates were conditioned at 70°C and 85 per cent relative humidity in a
moisture chamber. Areas more prone to saturation have been predicted by the FE
model and the moisture content in the non-saturated areas has been calculated.
Practical implications – The practical implications of the absorption model are
discussed on an example of an aero-engine fan blade-like structure. Originality/
value – Validation of thick panels’ absorption data is an important point of
novelty of this paper, given the lack of experimental and modelling validation in
the open literature.
Keyword: Composite fan blade, Moisture absorption, Thick composite laminates
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Sathujoda, Prabhakar (2019). Natural Frequency Analysis of a Functionally
Graded Rotor System using Three-Dimensional Finite Element Method.
Vibroengineering Procedia, 29, 70-75.
Abstract: Three-dimensional Finite Element (FE) analysis has been carried out
using ANSYS software to study the natural frequencies of functionally graded
(FG) rotor system. Temperature and position-dependent material properties of
the FG shaft system are considered to be graded in the radial direction. Power-
law with the nonlinear temperature distribution (NLTD) and exponential law
with exponential temperature distribution (ETD) have been used to model the
material gradation and temperature distribution. Rotor systems of two different
FG materials, namely Stainless Steel-ZrO2 and Stainless Steel-Al2O3 have been
studied. Python codes have been developed to generate ANSYS macros that
apply the material properties. Simply supported FG shaft and FG rotor system
supported on bearings have been analyzed in the current work. The results show
the influence of different power-law coefficients, different material and material
laws on the natural frequencies of the rotor system. The effect of these
parameters on whirl frequencies has also been studied for FG rotor systems.
Keyword: Functionally graded shaft, Finite element, Whirl frequency.
Sathujoda, Prabhakar (2019). Study of mixed-mode cracking of dovetail root
of an aero-engine blade like structure. Applied Sciences, 9(18), 1-23.
Abstract: Aerospace structures must be designed in such a way so as to be able
to withstand even more flight cycles and/or increased loads. Damage tolerance
analysis could be exploited more and more to study, understand, and calculate
the residual life of a component when a crack occurs in service. In this paper, the
authors are presenting the results of a systematic crack propagation analysis
campaign performed on a compressor-blade-like structure. The point of novelty
is that different blade design parameters are varied and explored in order to
investigate how the crack propagation rate in low cycle fatigue (LCF, at R ratio R
= 0) could be reduced. The design parameters/variables studied in this work are:
(1) The length of the contact surfaces between the dovetail root and the disc and
(2) their inclination angle (denoted as “flank angle” in the aero-engine industry).
Effects of the friction coefficient between the disc and the blade root have also
been investigated.
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The LCF crack propagation analyses have been performed by recalculating the
stress field as a function of the crack propagation by using the Fracture Analysis
Code (Franc3D®)
Keyword: LCF, Crack propagation, Blade-disc-Franc3D, Mixed-mode cracking
Dr. Rajnesh Tyagi, Assistant Professor, Department of Mechanical and
Aerospace Engineering
Tyagi, Rajnesh (2018). Estimation of wear rate in dual phase steel on the basis
of the load sharing between constituent phases. Vibroengineering Procedia, 21,
196-201.
Abstract: Model has been for proposed for estimating the wear rate in dual
phase (DP) steel for the run-in and the steady state of wear based on estimated
load sharing between the constituent phases i.e., ferrite and martensite. The
model has been checked by conducting pin-on-disc sliding wear tests on DP
steel, Armco (pure) iron and fully martensitic steel (FMS) samples at normal
loads of 14.7, 19.6, 24.5, 29.4 and 34.3 N and at a fixed sliding velocity of 1.15
m/s. Armco iron and FMS simulate the constituent phases in DP steel i.e.,
ferrite and martensite. The wear rates predicted by the proposed model have
been found to match well with the experimentally observed wear rates in the
regime of lower loads for the steels containing relatively lower volume fraction
of martensite. However, wear rates have increasingly larger difference at higher
loads. The difference in the estimated and the observed wear rates has been
attributed to the flow of the softer phase of ferrite over the hard martensite
islands and its relatively higher rate of wear.
Keyword: Modelling of wear, Dual phase steel
Tyagi, Rajnesh (2018). FEM simulation of three-point bending test of Inconel
718 coating on stainless steel substrate. Vibroengineering Procedia, 21, 248-
252.
Abstract: Three-point bending test is conducted by help of Finite Element
Method to find out mechanical properties of Inconel 718 coating on stainless
steel. For doing this ANSYS package are employed to visualise exact situation
of bending test so that can find out stress field developed during the test. A 3D
modelling of coating and substrate material is used. Load versus displacement
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relationships is compared with reference results. It is noticed that yield stress of
substrate material is higher than the tensile stress of substrate and coating. Due
to this reason there is initiation of crack at coating-substrate interface and it is
propagated which leads to failure with applied load.
Keyword: Three-point bending, Finite element method, Simulation, Coating.
Sabyasachi Souguny, B.Tech Student, Department of Mechanical and
Aerospace Engineering
Souguny, Sabyasachi (2019). Assessment of foot trajectories and ground
reaction force in a trans-femoral amputee with Jaipur Knee and 3R20 knee joints.
Vibroengineering Procedia, 29, 189-194.
Abstract: In developing countries like India, unilateral transfemoral amputees
encounter with the challenge to select and evaluate the knee joint performance.
This study aims to evaluate the response of knee joint on vertical ground reaction
forces (vGRFs), walking speed, range of motion (ROM) of joints like hip, knee
and ankle joints in first two weeks and enhanced response. Movements of
different joints were recorded through VICON motion analysis system. Vertical
ground reaction forces were captured through AMTI strain gauzed force plate. It
has been observed that in two weeks normalized speed increases 0.41 to 0.49
with 3R20. Range of motion of joints was observed with interesting fact that in
general with 3R20, joints angle their respective ROM were more than Jaipur
Knee but in same cases in second half of gait cycle Jaipur Knee responded better
than 3R20 knee joint.
Keyword: Adaptation, Range of motion (ROM), Transfemoral, Jaipur Knee
3R20.
Sai Manoj Katakam, B.Tech Student, Department of Mechanical and
Aerospace Engineering
Katakam, Sai Manoj (2019). Computational fluid dynamics analysis and
experimental validation of solar panel cleaning mechanism. Vibroengineering
Procedia, 29, 225-230.
Abstract: Solar energy is one of the widely used non-conventional form of
energy. Photo voltaic panels generate electricity and heat by absorbing solar
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irradiation. The performance of solar panels depends on several factors like dust
accumulation on the surface, solar cell temperature, angle of inclination etc., to
perform the cleaning action efficiently a semi-automatic cleaning mechanism has
been designed and fabricated. The designed experimental setup consists of
several nozzles attached on top of the solar panels and water is supplied to each
nozzle using a Poly Vinyl Chloride (PVC) pipe frame connected to an AC motor
operated with a time switch. Water flows on the surface of photo voltaic module,
thus heat exchange takes place. One dimensional heat transfer analysis is
performed, and the results are compared to the experimental results for
validation. The experiments were conducted at Bennett University, Greater
Noida dated 9 October to 16 October. An increase in efficiency by 1.28 % to
2.65 % was reported in this experimental study.
Keyword: Photo voltaic module, Computational fluid dynamics analysis, Solar
panel cleaning mechanism.
Katakam, Sai Manoj (2019). Experimental investigation of photovoltaic
module system coupled with solar panel cleaning system. Vibroengineering
Procedia, 29, 219-224.
Abstract: Solar energy is a non-conventional source of energy. Solar panels
generate electrical output by absorbing solar radiation. The performance of
photovoltaic (PV) module often depends on environmental factors like dust,
humidity, hail and temperature. Installation elements like altitude, installation
site, tilt angle also affects the efficiency of solar energy output. The objective of
this research work is to clean the dust deposited on PV panels using the
minimum amount of water and energy. To regularly clean the dust, a semi-
automatic self-cleaning mechanism has been designed and fabricated, which
cleans the deposited dust on the solar panel automatically. Therefore, the process
turns out to be reliable and faster and it leads to increased power output of the
solar panels. An experimental investigation has been done at Bennett University;
Greater Noida dated 15 October to 21st October 2019. An increase in efficiency
by 1.2 % to 3 % was reported in this experimental study.
Keyword: Photovoltaic (PV), Nozzle, Semi-automatic self-cleaning mechanism.
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Katakam, Sai Manoj (2019). Experimental study of self-sustainable hybrid
solar photovoltaic cleaning mechanism coupled with water distillation unit.
Vibroengineering Procedia, 29, 213-218.
Abstract: In the present research work a novel self-sustainable hybrid solar
photovoltaic cleaning mechanism coupled with water distillation unit has been
proposed. The experiments were conducted on the PV (photovoltaic) modules at
Bennett University, Greater Noida A-block terrace from 7th to 13th October
2019. Post installation, the average efficiencies of the solar PV module system
with and without cleaning were compared to obtain a hike by 1.34 %. The water
used for cleaning was recycled using a single slope basin type solar still which
indicated a working efficiency of 67.94 %. On an average the solar still yielded
5.3 Liters of pure water every day during the experiment with a TDS (total
dissolved solids) level of 104 ppm.
Keyword: Photovoltaic modules, Cleaning mechanism, Water distillation unit,
Efficiency.
Shivam Yadav, B.Tech Student, Department of Mechanical and Aerospace
Engineering
Yadav, Shivam (2019). Numerical simulation of vortex induced vibrations on a
circular cylinder at different Reynold’s number. Vibroengineering Procedia, 29,
171-175.
Abstract: This research investigates the effect of vortex induced vibrations on
flow past a circular cylinder for two-dimensional unsteady incompressible flow
at different Reynold’s number. The pressure bases steady solver is used for
computation along with standard k-å turbulence model. The change in the lift and
drag coefficient with respect to increase in Reynolds number is studied and
contours of vorticity are plotted. The pressure distribution on the fixed cylinder
for different Reynolds number is also presented. It is found that drag coefficient
reduces with the increasing Re and lift coefficient increases up to Reynold’s
number 104. Moreover, the pressure difference on the fixed cylinder increases
with the increasing Reynold’s number.
Keyword: Vortex induced vibration (VIV), Wake flow, Standard k-å turbulence
model.
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Yadav, Shivam (2019). Sound radiation of simply supported rectangular plate
using finite element method. Vibroengineering Procedia, 29, 195-200.
Abstract: In this paper sound radiation of simply supported rectangular plate has
been reported. The novelty in this research paper is a new method is prescribed
for sound radiation calculation. The phenomenon of uncoupled structural
acoustics have been followed such that structure is the critical part in structural
vibration using modal analysis and harmonic response calculation for frequency
range of interest 0 to 200 Hz, but in harmonic acoustic analysis the structure does
not takes part in physics point of view but is used for only for transferring the
normal velocity from wetted surface of the structure to the interface acoustic
medium i.e. air. Sound Radiation parameters like Sound Pressure Level, Sound
Power Level and Sound Radiation efficiency has been reported. Upon comparing
the results with that from I. Zaman’s literature, it is found that the results are
quite varying due to the fact the speed of sound in air as taken in literature is
unjustified. So true simulation using correct data has been carried out in this
paper and sound radiation results has been reported for frequency range of
interest 0 to 200 Hz. It is found that the maximum sound pressure level is 72 dB
and maximum sound power level is 78 dB which is suitable for noiseless
environment.
Keyword: Acoustic radiation, Sound pressure level, Acoustic power, Sound
power level, Radiation efficiency.
Shubham Agarwal, B.Tech Student, Department of Mechanical and
Aerospace Engineering
Agarwal, Shubham (2019). Assessment of foot trajectories and ground reaction
force in a trans-femoral amputee with Jaipur Knee and 3R20 knee joints.
Vibroengineering Procedia, 29, 189-194.
Abstract: In developing countries like India, unilateral transfemoral amputees
encounter with the challenge to select and evaluate the knee joint performance.
This study aims to evaluate the response of knee joint on vertical ground reaction
forces (vGRFs), walking speed, range of motion (ROM) of joints like hip, knee
and ankle joints in first two weeks and enhanced response. Movements of
different joints were recorded through VICON motion analysis system. Vertical
ground reaction forces were captured through AMTI strain gauzed force plate. It
has been observed that in two weeks normalized speed increases 0.41 to 0.49
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with 3R20. Range of motion of joints was observed with interesting fact that in
general with 3R20, joints angle their respective ROM were more than Jaipur
Knee but in same cases in second half of gait cycle Jaipur Knee responded better
than 3R20 knee joint.
Keyword: Adaptation, Range of motion (ROM), Transfemoral, Jaipur Knee
3R20.
Srijna Singh, Research Scholar, Department of Mechanical and Aerospace
Engineering
Singh, Srijna (2018). Numerical simulation of Vortex-shedding from
NACA4418 hydrofoil. Vibroengineering Procedia, 21, 121-130.
Abstract: To get better understanding of vortex shedding mechanism, we
conducted numerical simulation on NACA 4418 hydrofoil at an angle of attack
of 12° for 2D incompressible flow. The numerical method consists of transient,
finite volume method using Transient SST turbulent model to capture the
turbulent wake flows. At high Reynolds number the occurrence of 2D structures
of shed vortices and the modulation of vortex-induced frequency are
investigated. The lift, pressure and skin friction coefficients of hydrofoil were
studied
Keyword: NACA 4418, Hydrofoil, Vortex shedding, Transition SST
Singh, Srijna (2019). Computational investigation of cavitating flow around two
dimensional NACA 4424 and MHKF-240 hydrofoil. Vibroengineering Procedia,
29, 159-164.
Abstract: This study focuses on the comparison of the performance of two
unsymmetrical hydrofoils, NACA 4424 and MHKF-240 at 60 angles of attack
under cavitation. The Schnarr and Sauer cavitation model along with Realizable
k-å turbulence model is used for numerical computation in commercial software
ANSYS Fluent. The lift drags and pressure coefficients for different cavitation
numbers were studied. Among both the hydrofoils MHKF-240 gives a higher lift
coefficient which is the parameter of better performance.
Keyword: NACA 4424, MHKF-240, realizable k-å, Schnarr and Sauer model.
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Singh, Srijna (2019). Effect of slant angle variation on the drag force for Ahmed
body car model. Vibroengineering Procedia, 29, 153-158.
Abstract: In this paper, numerical investigation is carried out on two-
dimensional Ahmed body model using Computational Fluid Dynamics in
ANSYS Fluent 19.1. The 2-D model is designed in Catia v5 for 25°, 35° and 45°
slant angles. The turbulent model used to analyze the flow dynamics is
Realizable k-å model. The drag coefficient variation with respect to slant angle is
computed. The skin friction coefficient, wall shear stress and frictional velocity
are also calculated.
Keyword: Slant angle, Drag force, Ahmed body, Frictional velocity
Srinivasa Reddy Bode, B.Tech Student, Department of Mechanical and
Aerospace Engineering
Bode, Srinivasa Reddy (2019). Numerical analysis of single grit grinding on
aluminum workpiece. Vibroengineering Procedia, 29, 291-294.
Abstract: Grinding is a finishing process used in almost every industry. The
purpose of this research is to study the effects of grinding on aluminum. Finite
Element Method (FEM) is used to numerically simulate grinding by using
microscale modeling. It is found that though under grinding, stress mises
developed do not exceed yield stress. The force variation and displacement
parameters have been correspondingly discussed. The effects of grinding on the
workpiece with and without lubrication.
Keyword: Grit grinding, Microscale modelling, Friction coefficient, Stress
analysis
Susheel Reddy Aligireddy, B.Tech Student, Department of Mechanical and
Aerospace Engineering
Aligireddy, Susheel Reddy (2019). Computational fluid dynamics analysis and
experimental validation of solar panel cleaning mechanism. Vibroengineering
Procedia, 29, 225-230.
Abstract: Solar energy is one of the widely used non-conventional form of
energy. Photo voltaic panels generate electricity and heat by absorbing solar
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irradiation. The performance of solar panels depends on several factors like dust
accumulation on the surface, solar cell temperature, angle of inclination etc., to
perform the cleaning action efficiently a semi-automatic cleaning mechanism has
been designed and fabricated. The designed experimental setup consists of
several nozzles attached on top of the solar panels and water is supplied to each
nozzle using a Poly Vinyl Chloride (PVC) pipe frame connected to an AC motor
operated with a time switch. Water flows on the surface of photo voltaic module,
thus heat exchange takes place. One dimensional heat transfer analysis is
performed, and the results are compared to the experimental results for
validation. The experiments were conducted at Bennett University, Greater
Noida dated 9 October to 16 October. An increase in efficiency by 1.28 % to
2.65 % was reported in this experimental study.
Keyword: Photo voltaic module, Computational fluid dynamics analysis, Solar
panel cleaning mechanism.
Aligireddy, Susheel Reddy (2019). Experimental investigation of photovoltaic
module system coupled with solar panel cleaning system. Vibroengineering
Procedia, 29, 219-224.
Abstract: Solar energy is a non-conventional source of energy. Solar panels
generate electrical output by absorbing solar radiation. The performance of
photovoltaic (PV) module often depends on environmental factors like dust,
humidity, hail and temperature. Installation elements like altitude, installation
site, tilt angle also affects the efficiency of solar energy output. The objective of
this research work is to clean the dust deposited on PV panels using the
minimum amount of water and energy. To regularly clean the dust, a semi-
automatic self-cleaning mechanism has been designed and fabricated, which
cleans the deposited dust on the solar panel automatically. Therefore, the process
turns out to be reliable and faster and it leads to increased power output of the
solar panels. An experimental investigation has been done at Bennett University;
Greater Noida dated 15 October to 21st October 2019. An increase in efficiency
by 1.2 % to 3 % was reported in this experimental study.
Keyword: Photovoltaic (PV), Nozzle, Semi-automatic self-cleaning mechanism.
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Aligireddy, Susheel Reddy (2019). Experimental study of self-sustainable
hybrid solar photovoltaic cleaning mechanism coupled with water distillation
unit. Vibroengineering Procedia, 29, 213-218.
Abstract: In the present research work a novel self-sustainable hybrid solar
photovoltaic cleaning mechanism coupled with water distillation unit has been
proposed. The experiments were conducted on the PV (photovoltaic) modules at
Bennett University, Greater Noida A-block terrace from 7th to 13th October
2019. Post installation, the average efficiencies of the solar PV module system
with and without cleaning were compared to obtain a hike by 1.34 %. The water
used for cleaning was recycled using a single slope basin type solar still which
indicated a working efficiency of 67.94 %. On an average the solar still yielded
5.3 Liters of pure water every day during the experiment with a TDS (total
dissolved solids) level of 104 ppm.
Keyword: Photovoltaic modules, Cleaning mechanism, Water distillation unit,
Efficiency.
Vimal Chauhan, Research Scholar, Department of Mechanical and
Aerospace Engineering
Chauhan, Vimal (2018). Numerical study of shear thickening fluid with
distinct particles dispersed in carrier fluid. Vibroengineering Procedia, 21, 242-
247.
Abstract: The Shear Thickening Fluid (STF) is a non- Newtonian fluid which
comes under dilatant material, STF undergoes phase transition from a low to
high viscosity when shear stress is applied on it. In this paper modelling and
simulation tools are used to study the STF fluid interaction when subjected to
applied shear stress. The Eulerian description used for the fluid flow and the
model considered the Lagrangian description of the rigid particles. The
numerical analysis inspects important guideline such as acceleration of the
flow, particle dispersion and the base of Non-Newtonian fluid. The fluid
particles interrelation of STF showed that the shape, arrangement, volume
concentration, and size of the particles had a vital effect on the behavior of STF.
By adding sand particles in non-Newtonian fluids and applying high shear
strain rates showed improvement in the shear thickening effects.
Keyword: Non-Newtonian fluid, Viscosity function, Shear thickening fluids
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Chauhan, Vimal (2019). Numerical modelling of shear thickening fluid in
nanosilica dispersion. Vibroengineering Procedia, 29, 260-265.
Abstract: In this paper, a numerical model of the shear thickening fluid (STF) is
generated and the rheological properties are compared with the experimental
data. Power Law model has been used to fit the rheological data for STF.
Experimental data is taken from a performed study and a user defined function
(UDF) has been written to develop the shear thickening behavior. The purpose of
this study is to exactly model the behavior of shear thickening fluids by using
UDF, to explain the shear-thickening mechanisms under different shear rates.
Different parameters like viscosity, shear stress and velocity of the STF have also
been reported.
Keyword: Non-Newtonian fluid, Viscosity function, Shear thickening fluids
Dr. Vinayak Ranjan, Professor & HOD, Department of Mechanical and
Aerospace Engineering
Ranjan, Vinayak (2018). Burst strength analysis of gas turbine disc based on
deformation characteristics. Proceedings of the 1st International Conference on
Mechanical and Materials Science Engineering (pp. 1-7).
Abstract: In aircraft gas turbine engine, the rotating turbine disc is highly
stressed component. The demand of high strength to weight ratio for each
component of aeroengine makes the disc, a critical component from design
point of view. Burst of rotor disc is one of the catastrophic failure mode of gas
turbine engine. The present paper, therefore, deliberates the burst of rotating
turbine disc due to overspeed. A typical gas turbine disc is modeled, and elastic
-plastic analysis is carried out by linearly increasing the speed. Finite element
technique has been used for the analysis. The burst criteria are proposed based
on the deformation taking place in the disc. A safe permissible speed between
burst rotation speed and maximum allowable speed of the turbine disc is also
identified as per federal aviation regulations.
Ranjan, Vinayak (2017). Dynamic analysis of Indian railway track. Journal of
Advanced Research in Dynamical and Control Systems, 335-348.
Abstract: This paper presents the dynamic response of the Indian railway track.
Two track models are considered for the dynamic response in terms of vertical
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displacement and acceleration at different wheel speeds, keeping the moving
point load of constant magnitude. One treats the rail as a beam on viscoelastic
foundation and the other assumes it to be on the discrete elastic support system.
The governing equation is studied through finite element software package
ANSYS 14.0. For the validation of the models results are compared with those
available in published literature and the maximum deviation for displacement at
the midpoint of rail is found less than 5%. Different wheel speed generates
variation in displacement and acceleration on the track. The study can be viewed
as the foundation for the comparison of FEA based simulation of rail track to
specify its dynamic response useful for safer design of the track layout.
Keyword: Viscoelastic foundation, Discrete elastic support, Vertical
displacement
Ranjan, Vinayak (2017). Effect of electrode location and thickness ratio of
flange and web on I cross section piezoelectric cantilever beam for its actuation
capability. Journal of Vibroengineering, 19(8), 5657-5667.
Abstract: Present work deals with the numerical investigation of a cantilever
beam having I cross section made up of piezoelectric material for its actuation
capability. The beam is modeled under the assumption of Euler’s Bernoulli
equation. Eight cases are considered for different electrode locations. The beam
was subjected to voltage loads at different locations. It was noticed that tip
deflection increases with increasing applied voltage across the electrodes.
Maximum tip deflection was achieved with the increase in voltage with particular
electrode arrangement. In this report we have also demonstrated that for
downward tip deflection, there are two values of thickness ratio of flange and
web for a given tip deflection at a given applied voltage.
Keyword: Cross section, Tip deflection, Piezoelectric
Ranjan, Vinayak (2017). Finite element modelling and analysis of the burst
margin of a gas turbine disc using an area weighted mean hoop stress method.
Engineering Failure Analysis, 90, 425–433.
Abstract: One of the main failure modes of the turbine disc is formation of yield
zone at bore which leads to burst of the disc. Hence, disc burst is treated as a
critical factor while designing the disc. The scope of present work is to carry-out
the elastic - plastic analysis and to find the burst margin of a typical model of a
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gas turbine disc by means of the finite-element technique for different speed of
rotation. The additional goal of the analysis is to compare the burst margin of
turbine disc having variable thickness and uniform thickness profile of the disc.
The burst margin is estimated using area weighted mean hoop stress (AWMHS)
approach. For given burst margin greater than 122%, the variable thickness disc
provides lower operating speed in comparison to uniform thickness disc. This
helps in reducing hoop stress, which is highly desirable in aero-engine.
Keyword: Burst margin, Rotating disc, Stress analysis, Finite element method
Ranjan, Vinayak (2017). Rolling contact fatigue life of rail for different slip
conditions. Latin American Journal of Solids and Structures, 2243-2264.
Abstract: A three-dimensional elastic-plastic finite element analysis (FEA) is
carried out to estimate the rolling contact fatigue (RCF) crack initiation life for
varied slip range on the rail arising from operational variations. The wheel load
produces Hertzian contact pressure. Variation in engine traction induces slip
variations that evolves thermal load in terms of heat flux. The aperiodic rolling of
wheel on rail develops non-proportional multiaxial fatigue loading. Present study
combines these effects by translating the wheel load on rail for multiple (twelve)
pass in presence of thermal load, contact pressure and traction through a
proposed simulation. The temperature dependent Chaboche material model with
nonlinear kinematic hardening law is implemented to estimate the stresses and
plastic strains governing the multiaxial fatigue condition at the interface. The
location of maximum von Mises stress, found at a material point on or a layer
below the rail-head, contemplates the fatigue crack initiation site. A coded search
algorithm helps to identify the critical plane of crack initiation corresponding to
the maximum fatigue parameter (FP). In contrast to available predictions of RCF
life considering contact pressure and/or traction or frictional heat in isolation,
present study combines all these loads together and provides a more realistic
result by numerical simulation.
Keyword: Wheel-rail contact, Slippage, Non-proportional loading, Ratchetting,
Critical plane, Rolling contact fatigue
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Ranjan, Vinayak (2017). Vibration Model Localization of Aluminum
Rectangular Plate. International Journal of Advance Research in Science and
Engineering, 6(2), 350-362.
Abstract: Modal analyses are carried out to calculate the natural frequencies
and natural modes of the system. Ship structures are stealth shaped structures and
these stealth structures are simulated by taking an assumption that structures are
plane and homogenous throughout. Rectangular aluminum plate model is
simulated in this paper using ABAQUS® 13.1 and Pulse 18.1. Vibration Mode
localization analysis using point mass variation has been carried out. Mode
shapes and frequencies obtained in this paper shows that vibration along major
portion of the plate is found to be curbed. Often modal analyses are performed
using a somewhat coarser mesh, since the mode shapes and Eigen frequencies
can be accurately estimated as long as the basic mass and stiffness distributions
are correct. In one way or the other this analysis can also be said as acoustic
analysis as sound transmitted by hammer impact on the aluminum plate is
transformed into voltage signals by the use of accelerometer containing
piezoelectric material. The voltage signal is transformed into displacement signal
and frequency signal by means of amplifier used in the setup of the experimental
modal analysis software Pulse 18.1.
Keyword: ABAQUS CAE, Modal Analysis,
Ranjan, Vinayak (2018). A Comparison of axisymmetric vibration of tapered
annular circular plate with different linearly and parabolically varying thickness
with different boundary conditions. International Journal of Advanced in
Management, Technology and Engineering Sciences, 8(2), 626-637.
Abstract: In this study, a vibration analysis of a tapered annular circular plate
having different linearly and parabolically varying thickness with different
taper ratios for free- free and clamped - free boundary conditions are
investigated by keeping the total mass of the plate constant. FEM is used to
determine the Eigen value of the plate. The present work is validated with the
existing literature and good agreement of results is observed. Further, the mode
variation and stiffness variation due to taper ratio is observed for all the
thickness variations.
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Finally, the solution for flexural response for actuation and suppression
associated with different thickness variation is suggested.
Keyword: Axisymmetric vibration, Annular circular plate, Plate free vibration,
Modal frequency
Ranjan, Vinayak (2018). A numerical study on effects of friction-induced
thermal load for rail under varied wheel slip conditions. Simulation:
Transactions of the Society for Modeling and Simulation International, 95(4),
351-362.
Abstract: A finite element-based simulation was carried out to investigate the
effects of friction-induced thermal load on rail under varied wheel slip
conditions. The surface temperature rises from six different percentage slips
(1%, 1.5%, 2%, 5%, 8.5%, and 10%) at the contact interface was examined for
eight-wheel pass. The residual stresses and accumulated plastic strains evolved
by the effect of localized temperature rise are estimated. Analytical formulation
for conduction mode of heat transfer at the contact patch is used to estimate the
temperature distribution. The interaction of thermal-elastic plastic field
conditions is obtained by a proposed simulation model. This is implemented in
commercial finite element software ANSYS 14.0. In order to capture the steep
thermal gradient beneath the contact surface, refined mesh is used in the upper
layers up to a depth of 2 mm of the simulation domain. For better manifestation
of thermally affected material layers, a temperature dependent bilinear-
kinematic hardening material condition is applied. Results indicate the
maximum temperature rise at about 0.6a from the trailing end in the contact
ellipse of semi-major axis a. At higher slippage conditions the initial pearlite
rail steel gets converted to martensite which is often observed on rail surface as
white etching layer known to be associated with rolling contact fatigue. The
study reveals the mechanisms of thermally induced defects observable on rail
surface. The outcomes, in addition, can provide useful information for the
development of thermo-mechanically superior rail steels.
Keyword: Rail–wheel contact, Frictional heat, Thermal softening, Martensite
formation, Rolling contact fatigue
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Ranjan, Vinayak (2018). Acoustic Response of Thin Plate with Discrete
Patches with Variable Thickness in Water Medium. Journal of Vibrational
Engineering and Technologies, 8, 27–34.
Abstract: Background this paper analyses acoustic response of thin plate with
discrete patches with variable thickness in water medium. Method Finite-
element method and Rayleigh integral method are used for sound power
calculation in water medium. Results For low-frequency range up to 50 Hz, the
peak sound power level (SPL) is achieved at higher taper ratio of 0.9 with
parabolically increasing–decreasing thickness variation with one patch. In the
frequency range of 70–180 Hz and 260–290 Hz, a taper ratio of 0.6 with four
patches on the plate with parabolically increasing–decreasing variation is
preferred for minimum SPL. Conclusions It is observed that SPL is influenced
by redistribution of patches, thickness variations, and taper ratios.
Keyword: Isotropic rectangular plate, Taper parameter
Ranjan, Vinayak (2018). Analysis of free vibration of nano plate resting on
Winkler foundation. Vibroengineering Procedia, 21, 65-70.
Abstract: Present paper deals with the vibration analysis of nano plate
supported by Winkler foundation using Eringen’s elasticity theory with
Classical Plate theory. Rayleigh-Ritz method has been employed in this study
for finding frequencies of plate subjected to different edge conditions. The
obtained results are first tested for convergence and then validated with the
published literature. Further study is carried out to analyses the effect of various
parameters on natural nondimensional frequencies of nano plate resting on
Winkler foundation. The study reveals that the non-local effect has significant
effect on vibration behavior of nano plate resting on elastic foundation.
Observations shows that on increasing the Winkler foundation modulus and
aspect ratio the nondimensional frequency parameters increases
Keyword: Nano plate, Rayleigh Ritz method, Frequency parameter, Nonlocal
elasticity theory
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Ranjan, Vinayak (2018). Comparison of natural frequencies of isotropic plate
using DSM with Wittrick-Williams algorithm. Vibroengineering Procedia, 21,
59-64.
Abstract: In this paper, comparison of natural undamped frequencies of
isotropic plates are investigated by using the dynamics stiffness element for
isotropic plates. The DS Matrix for isotropic has been formulated by the
application of classical plate theory. The generalized DS matrix has to solve by
using Wittrick-Williams algorithm. Results of different aspect ratio have been
validated from the existing literature.
Keyword: Dynamic stiffness matrix, Isotropic plate
Ranjan, Vinayak (2018). Estimation of wear rate in dual phase steel on the
basis of the load sharing between constituent phases. Vibroengineering
Procedia, 21, 196-201.
Abstract: Model has been for proposed for estimating the wear rate in dual
phase (DP) steel for the run-in and the steady state of wear based on estimated
load sharing between the constituent phases i.e., ferrite and martensite. The
model has been checked by conducting pin-on-disc sliding wear tests on DP
steel, Armco (pure) iron and fully martensitic steel (FMS) samples at normal
loads of 14.7, 19.6, 24.5, 29.4 and 34.3 N and at a fixed sliding velocity of 1.15
m/s. Armco iron and FMS simulate the constituent phases in DP steel i.e.,
ferrite and martensite. The wear rates predicted by the proposed model have
been found to match well with the experimentally observed wear rates in the
regime of lower loads for the steels containing relatively lower volume fraction
of martensite. However, wear rates have increasingly larger difference at higher
loads. The difference in the estimated and the observed wear rates has been
attributed to the flow of the softer phase of ferrite over the hard martensite
islands and its relatively higher rate of wear.
Keyword: Modelling of wear, Dual phase steel
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Ranjan, Vinayak (2018). FEM simulation of three-point bending test of
Inconel 718 coating on stainless steel substrate. Vibroengineering Procedia, 21,
248-252.
Abstract: Three-point bending test is conducted by help of Finite Element
Method to find out mechanical properties of Inconel 718 coating on stainless
steel. For doing this ANSYS package are employed to visualise exact situation
of bending test so that can find out stress field developed during the test. A 3D
modelling of coating and substrate material is used. Load versus displacement
relationships is compared with reference results. It is noticed that yield stress of
substrate material is higher than the tensile stress of substrate and coating. Due
to this reason there is initiation of crack at coating-substrate interface and it is
propagated which leads to failure with applied load.
Keyword: Three-point bending, Finite element method, Simulation, Coating.
Ranjan, Vinayak (2018). Free vibration analysis of thin functionally graded
rectangular plates using the dynamic stiffness method. Composite Structures,
197(1), 39-53.
Abstract: In this paper, free vibration behavior of thin functionally graded
rectangular plates is investigated by using the dynamic stiffness method (DSM).
Classical plate theory along with the concept of physical neutral surface of the
functionally graded plate is used to formulate the dynamic stiffness matrix. The
dynamic stiffness matrix is finally solved by using the Wittrick-Williams
algorithm to compute the natural frequencies. DSM frequencies are compared
with those available in the literature. Some inaccurate published results are
pointed out and possible reasons for these inaccuracies are discussed. Results
for several plate parameters are given and the influence of these parameters on
natural frequencies of the functionally graded plate is highlighted. The present
study shows that the dynamic stiffness method provides very accurate results
for vibration analysis of thin functionally graded plates and these results can be
used as benchmark solutions for comparison purposes.
Keyword: Free Vibration, Dynamic Stiffness Method, Rectangular Plate,
Functionally Graded Material
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Ranjan, Vinayak (2018). Indian railway track analysis for displacement and
vibration pattern estimation. Vibroengineering Procedia, 21, 71-76.
Abstract: This paper presents the dynamic response of the Indian Railway
track. Two track models are considered for the dynamic response in terms of
vertical displacement and acceleration at different wheel speeds, keeping the
moving point load at constant magnitude. The rail is treated as a beam either on
viscoelastic foundation or on the discrete elastic support system. The governing
equation is implemented in finite element analysis using ANSYS 14.0. For the
validation of result from system equation are compared with those available in
published literature and the maximum deviation for displacement at the
midpoint of rail is found to be within 5 %. Different wheel speed generates
variation in displacement and acceleration of the rail track. The study can be
viewed as the foundation for the comparison of FEA based simulation of rail
track to specify its dynamic response useful to provide better safety and comfort
to commuters.
Keyword: Viscoelastic foundation, Discrete elastic support
Ranjan, Vinayak (2018). Mathematical Modeling for Estimation of Acoustic
Radiation from Clamped Free Tapered Annular Circular Plate having different
Parabolically Varying Thickness. Vibroengineering Procedia, 21, 161-167.
Abstract: In this study, a comparison of sound radiation characteristic of an
annular circular plate with different parabolically varying thickness with
different taper ratio and different excitation locations are analyzed by keeping
the mass of the plate constant. Rayleigh integral is applied to determine the
acoustic behavior of the plate. The same problem is also solved by FEM to
draw the comparison. It is observed that excitation locations and modes have a
significant effect on sound power level in comparison to stiffness variation due
to different taper ratios. Further, the variation of peak sound power level is
investigated with different taper ratio with different excitation locations.
Finally, the design options for peak sound power are suggested for different
excitation locations with different taper ratios.
Keyword: Thick annular plate Excitation location, Taper ratio, Sounds power
level
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Ranjan, Vinayak (2018). Numerical simulation of Vortex-shedding from
NACA4418 hydrofoil. Vibroengineering Procedia, 21, 121-130.
Abstract: To get better understanding of vortex shedding mechanism, we
conducted numerical simulation on NACA 4418 hydrofoil at an angle of attack
of 12° for 2D incompressible flow. The numerical method consists of transient,
finite volume method using Transient SST turbulent model to capture the
turbulent wake flows. At high Reynolds number the occurrence of 2D structures
of shed vortices and the modulation of vortex-induced frequency are
investigated. The lift, pressure and skin friction coefficients of hydrofoil were
studied
Keyword: NACA 4418, Hydrofoil, Vortex shedding, Transition SST
Ranjan, Vinayak (2018). Numerical study of shear thickening fluid with
distinct particles dispersed in carrier fluid. Vibroengineering Procedia, 21, 242-
247.
Abstract: The Shear Thickening Fluid (STF) is a non- Newtonian fluid which
comes under dilatant material, STF undergoes phase transition from a low to
high viscosity when shear stress is applied on it. In this paper modelling and
simulation tools are used to study the STF fluid interaction when subjected to
applied shear stress. The Eulerian description used for the fluid flow and the
model considered the Lagrangian description of the rigid particles. The
numerical analysis inspects important guideline such as acceleration of the
flow, particle dispersion and the base of Non-Newtonian fluid. The fluid
particles interrelation of STF showed that the shape, arrangement, volume
concentration, and size of the particles had a vital effect on the behavior of STF.
By adding sand particles in non-Newtonian fluids and applying high shear
strain rates showed improvement in the shear thickening effects.
Keyword: Non-Newtonian fluid, Viscosity function, Shear thickening fluids
Ranjan, Vinayak (2018). Performance evaluation of Jaipur knee joint through
kinematics gait symmetry with unilateral transfemoral Indian amputees.
Vibroengineering Procedia, 21, 149-154.
Abstract: Gait analysis is considered as the most systematic study of human
motion. The analysis of gait includes visual and analytical perception of the
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individual, augmentation of various mechanical instrumentations for measuring
movement of body, muscles activity and body mechanics. Past study focused
on gait analysis of various animal locomotion and humans mainly on sports
biomechanics. This paper aims to quantify the gait performance with Jaipur
Knee, which is one of the most widely used prosthesis in Indian population.
Gait data with Jaipur knee joint is not available till date. The proposed study
targets to predict the performance of Jaipur knee joint in terms of gait symmetry
with transfemoral Indian amputees. Gait symmetry may be the basis of
recommendation of knee joint to prosthetic patients. This study used kinematics
and kinetics parameters together to quantify the performance of Jaipur knee
joint to evaluate gait symmetry. This research will be helpful for clinician to
predict and further to prevent the degenerated musculoskeletal effects generally
seen in unilateral transfemoral amputees.
Keyword: Amputation, Gait Analysis, Jaipur knee, Transfemoral, Prosthesis,
Ranjan, Vinayak (2018). Theoretical and numerical estimation of sound power
from out of plane modes of a free annular circular plate having parabolically
varying thickness. International Journal of Mechanical and Production
Engineering Research and Development, 9(1), 379-392.
Abstract: In this study, the sound radiation characteristic of an annular circular
plate with parabolically varying thickness with different taper ratios and
different excitation locations are analysed. The mass of the plate is kept
constant for all thickness variations. Rayleigh integral is applied to determine
the acoustic radiation coupling between interacting structural modes of the
plate. Further, this method is applied to determine the self and mutual radiation
from out of plane (m, n)th modes. The same problem is also solved by ANSYS
to draw the comparison. The sound power is generated by harmonic force at
different excitation locations is calculated from self and mutual radiation. It is
observed that the mutual radiation due to modal coupling exists only when two
out of plane structural modes have same n. Finally, excitation location with
different taper ratios provides us a solution for peak sound power actuation as
well as peak sound power reduction.
Keyword: Thick annular circular plate; Rayleigh integral; Finite element
modeling; Rectangular and concentric stiffener patches; Taper ratio; Thickness
variation
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Ranjan, Vinayak (2018). Theoretical and Numerical Estimation of
Vibroacoustic Behavior of Clamped Free Parabolic Tapered Annular Circular
Plate with Different Arrangement of Stiffener Patches. Applied Science, 8, 1-31.
Abstract: This paper compares the vibroacoustic behavior of a tapered annular
circular plate having different parabolic varying thickness with different
combinations of rectangular and concentric stiffener patches keeping the mass
of the plate and the patch constant for a clamped-free boundary condition. Both
numerical and analytical methods are used to solve the plate. The finite element
method (FEM) is used to determine the vibration characteristic and both Ray
Leigh integra land FEM is used to determine the acoustic behavior of the plate.
It is observed that a Case II plate with parabolic decreasing–increasing
thickness variation for a plate with different stiffener patches shows reduction
in frequency parameter in comparison to other cases. For acoustic response, the
variation of peak sound power level for different combinations of stiffener
patches is investigated with different taper ratios. It is investigated that
CaseIIplate with parabolic decreasing–increasing thickness variation for an
unloaded tapered plate as well as caseIIplate with 2 rectangular and 4
concentric stiffeners patches shows the maximum sound power level among all
variations. However, it is shown that the Case III plate with parabolically
increasing–decreasing thickness variation with different combinations of
rectangular and concentric stiffeners patches is least prone to acoustic radiation.
Furthermore, it is shown that at low forcing frequency, average radiation
efficiency with different combinations of stiffeners patches remains the same,
but at higher forcing frequency a higher taper ratio causes higher radiation
efficiency, and the radiation peak shifts towards the lower frequency and alters
its stiffness as the taper ratio increases. Finally, the design options for peak
sound power actuation and reduction for different combinations of stiffener
patches with different taper ratios are suggested.
Keyword: Hick annular circular plate, Rayleigh integral
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Ranjan, Vinayak (2018). Vibration analysis of a thin functionally graded plate
having an out of plane material inhomogeneity resting on Winkler–Pasternak
foundation under different combinations of boundary conditions. Proceedings
of the Institution of Mechanical Engineers, Part C: Journal of Mechanical
Engineering Science, 233(8), 2636-2662.
Abstract: In the present research article, classical plate theory has been adopted
to analyze functionally graded material plate, having out of plane material
inhomogeneity, resting on Winkler–Pasternak foundation under different
combinations of boundary conditions. The material properties of the
functionally graded material plate vary according to power law in the thickness
direction. Rayleigh–Ritz method in conjugation with polynomial displacement
functions has been used to develop a computationally efficient mathematical
model to study free vibration characteristics of the plate. Convergence of
frequency parameters (nondimensional natural frequencies) has been attained
by increasing the number of polynomials of displacement function. The
frequency parameters of the functionally graded material plate obtained by
proposed method are compared with the open literature to validate the present
model. Firstly, the present model is used to calculate first six natural
frequencies of the functionally graded plate under all possible combinations of
boundary conditions for the constant value of stiffness of Winkler and
Pasternak foundation moduli. Further, the effects of density, aspect ratio, power
law exponent, Young’s modulus on frequency parameters of the functionally
graded plate resting on Winkler–Pasternak foundation under specific boundary
conditions viz. CCCC (all edges clamped), SSSS (all edges simply supported),
CFFF (cantilever), SCSF (simply supported-clamped-free) are studied
extensively. Furthermore, effect of stiffness of elastic foundation moduli (kp
and kw) on frequency parameters are analyzed. It has been observed that effects
of aspect ratios, boundary conditions, Young’s modulus and density on
frequency parameters are significant at lower value of the power law exponent.
It has also been noted from present investigation that Pasternak foundation
modulus has greater effect on frequency parameters as compared to the Winkler
foundation modulus. Most of the results presented in this paper are novel and
may be used for the validation purpose by researchers. Three-dimensional mode
shapes for the functionally graded plate resting on elastic foundation have also
been presented in this article
Keyword: Power law exponent, Rayleigh–Ritz method
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Ranjan, Vinayak (2018). Vibration analysis of an isotropic annular circular
plate having arbitrarily varying thickness with different taper ratio.
International Journal of Innovative Research & Studies, 212-220.
Abstract: In this study, a vibration analysis of a tapered annular circular plate
having different parabolically varying thickness with different taper ratios for
free- free and clamped - free boundary conditions are investigated by keeping
the total mass of the plate constant. FEM is used to determine the Eigen value
of the plate. The present work is validated with the existing literature and good
agreement of results is observed. Further, the mode variation and stiffness
variation due to taper ratio is observed for all the thickness variation. Finally,
the solution for flexural response for actuation and suppression associated with
different thickness variation is suggested.
Keyword: Vibration analysis, Isotropic annular circular plate
Ranjan, Vinayak (2019). Assessment of foot trajectories and ground reaction
force in a trans-femoral amputee with Jaipur Knee and 3R20 knee joints.
Vibroengineering Procedia, 29, 189-194.
Abstract: In developing countries like India, unilateral transfemoral amputees
encounter with the challenge to select and evaluate the knee joint performance.
This study aims to evaluate the response of knee joint on vertical ground reaction
forces (vGRFs), walking speed, range of motion (ROM) of joints like hip, knee
and ankle joints in first two weeks and enhanced response. Movements of
different joints were recorded through VICON motion analysis system. Vertical
ground reaction forces were captured through AMTI strain gauzed force plate. It
has been observed that in two weeks normalized speed increases 0.41 to 0.49
with 3R20. Range of motion of joints was observed with interesting fact that in
general with 3R20, joints angle their respective ROM were more than Jaipur
Knee but in same cases in second half of gait cycle Jaipur Knee responded better
than 3R20 knee joint.
Keyword: Adaptation, Range of motion (ROM), transfemoral, Jaipur Knee
3R20.
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Ranjan, Vinayak (2019). Comparison for the Effect of Different Attachment of
Point Masses on Vibroacoustic Behavior of Parabolic Tapered Annular Circular
Plate. Applied Sciences-Basel, 9(4), 4-21.
Abstract: In this paper, a comparison for the effect of different arrangement of
point masses on vibroacoustic behavior of parabolic tapered annular circular
plate with different taper ratios are analyzed by keeping the total mass of the
plate plus point masses constant. Three different arrangement of thickness
variation are considered. The mathematical tool FEM using ANSYS is used to
determine the vibration characteristic and both FEM and Rayleigh integral is
used to determine the acoustic behavior of the plate. Further, Case II plate
(parabolic decreasing increasing thickness variation) for all combination of point
masses is found to have reduction in natural frequency parameter in comparison
to other cases of parabolic tapered plate. In terms of acoustic behavior, sound
power levels of different cases of plate with different point mass combination are
observed. It is observed that the Case II plate with two-point masses combination
shows the highest sound power and the Case III plate for all cases of point mass
combination is least prone to acoustic behavior. Furthermore, it is observed that
at low forcing frequency average radiation efficiency of parabolic tapered plate
for different arrangement of point masses is almost same, but at high forcing
frequency average radiation increases for higher taper ratio. Finally, a brief
discussion of peak sound power reduction and actuation for different
arrangement of point masses with different taper ratios are provided.
Keyword: Thick annular circulate plane, Finite element modelling, Rayleigh
integral, Point mass, Taper ratio, Parabolic thickness variation
Ranjan, Vinayak (2019). Dynamic stiffness method for free vibration analysis
of thin functionally graded rectangular plates. Vibroengineering Procedia, 29, 76
-81.
Abstract: In this present work, the dynamic stiffness method (DSM) is used to
analyze the free vibration of a thin functionally graded rectangular plate.
Classical plate theory (CPT) is used to develop the dynamic stiffness matrix of a
functionally graded material (FGM) plate. For free vibration analysis, the natural
frequencies of the functionally graded material plate are estimated by using DSM
with Wittrick-Williams algorithm for different aspect ratios and different
boundary conditions. The present research compared the DSM natural
frequencies results with those available in the published literature.
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Keyword: Dynamic stiffness method, Free vibration, Functionally graded
material, CPT.
Ranjan, Vinayak (2019). Free vibration analysis of simply supported
rectangular plates. Vibroengineering Procedia, 29, 270-273.
Abstract: In this paper, numerical analysis for free vibration of simply supported
thin rectangular plates has been simulated using Ansys. The vibration of plate
follows Kirchhoff plate theory. The natural frequency calculated using Ansys has
been compared with Levy type solution results available in the literature. It is
observed that the natural frequencies of the simply supported rectangular plate is
in close agreement with exact solution results as reported in literature.
Keyword: Kirchhoff plate theory, Levy solution, Simply supported rectangular
plate.
Ranjan, Vinayak (2019). Numerical analysis of temperature distribution in
sliding contacts of pin on disc model. Vibroengineering Procedia, 29, 274-278.
Abstract: Pin on disc is a tribosystem confirming to ASTM G99, is employed in
this work. It consists of deformable cylindrical disc and rigid pin with friction.
Coating of Inconel 712 is added on stainless steel disc and pin is made of SiC3.
The FEM software ANSYS R19.1 is employed for simulation of temperature
distribution produced due to friction between pin on disc. Stress distribution is
calculated from result produced between pin and disc interface due to applied
contact load on pin. The governing equation is mentioned in introduction section.
Result showing as contact load on pin increases maximum principle stress is
increases. Temperature rises in direct proportion with sliding distance and time.
Simulation result validates and confirmed with experimental results.
Keyword: Contact stress analysis, FEA, Pin on disc, Temperature distribution.
Ranjan, Vinayak (2019). Performance Evaluation of Jaipur Knee Joint through
Kinematics and Kinetics Gait Symmetry with Unilateral Transfemoral Indian
Amputees. Journal of Medical Systems, 43(3), 2-8.
Abstract: Gait analysis is considered as the most systematic study of human
motion. The analysis of gait includes visual and analytical perception of the
individual, augmentation of various mechanical instrumentations for measuring
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movement of body, muscles activity and body mechanics. Past study focused on
gait analysis of various animal locomotion and humans mainly on sports
biomechanics. This paper aims to quantify the gait performance with Jaipur
Knee, which is one of the most widely used prosthesis in Indian population. Gait
data with Jaipur knee joint is not available till date. The proposed study targets to
predict the performance of Jaipur knee joint in terms of gait symmetry with
transfemoral Indian amputees. Gait symmetry may be the basis of
recommendation of knee joint to prosthetic patients. This study used kinematics
and kinetics parameters together to quantify the performance of Jaipur knee joint
to evaluate gait symmetry. This research will be helpful for clinician to predict
and further to prevent the degenerated musculoskeletal effects generally seen in
unilateral transfemoral amputees.
Keyword: Amputation, Gait Analysis, Jaipur knee, Transfemoral, Prosthesis
Ranjan, Vinayak (2019). Size-dependent natural frequencies of functionally
graded plate with out of plane material inhomogeneity using Eringen’s theory of
nonlocal elasticity. Proceedings of the Institution of Mechanical Engineers, Part
L: Journal of Materials: Design and Applications, 1-20.
Abstract: Nonlocal effect is one of the critical reasons which cause an
extraordinary vibration response in small-scale structures. In the present work,
vibration characteristics of functionally graded nonlocal plate are studied using
Eringen’s nonlocal classical elasticity theory. A computationally efficient
numerical method has been proposed in this study by reformulating the classical
plate theory and Rayleigh–Ritz method using nonlocal differential relationship of
Eringen’s theory in conjugation with algebraic polynomial displacement
functions. The reformulated method helps to evaluate the natural frequencies of
functionally graded nonlocal plates subjected to all possible combinations of
edge conditions. The material properties are assumed to vary through the
thickness of the plate following the power law. The computed results of natural
frequencies are first tested for convergence and then validated with the published
one. A parametric study has been thoroughly conducted focusing on the effects
of aspect ratio, nonlocal parameter, material property index and Young’s
modulus ratio on the natural frequency parameters of the functionally graded
nonlocal plate. It has been observed that the material property index and aspect
ratio affect the vibration behaviour of the functionally graded plate. The study
also establishes that nonlocal effect has a pronounced influence on the higher
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modes of vibration of functionally graded plate. 3D mode shapes of functionally
graded material nonlocal plate have also been reported.
Keyword: Nonlocal effect, Eringen’s nonlocal elasticity theory, Rayleigh–Ritz
method, functionally graded plate
Ranjan, Vinayak (2019). Sound radiation of simply supported rectangular plate
using finite element method. Vibroengineering Procedia, 29, 195-200.
Abstract: In this paper sound radiation of simply supported rectangular plate has
been reported. The novelty in this research paper is a new method is prescribed
for sound radiation calculation. The phenomenon of uncoupled structural
acoustics have been followed such that structure is the critical part in structural
vibration using modal analysis and harmonic response calculation for frequency
range of interest 0 to 200 Hz, but in harmonic acoustic analysis the structure does
not takes part in physics point of view but is used for only for transferring the
normal velocity from wetted surface of the structure to the interface acoustic
medium i.e. air. Sound Radiation parameters like Sound Pressure Level, Sound
Power Level and Sound Radiation efficiency has been reported. Upon comparing
the results with that from I. Zaman’s literature, it is found that the results are
quite varying due to the fact the speed of sound in air as taken in literature is
unjustified. So true simulation using correct data has been carried out in this
paper and sound radiation results has been reported for frequency range of
interest 0 to 200 Hz. It is found that the maximum sound pressure level is 72 dB
and maximum sound power level is 78 dB which is suitable for noiseless
environment.
Keyword: Acoustic radiation, Sound pressure level, Acoustic power, Sound
power level, Radiation efficiency.
Waseem Shameer, B.Tech Student, Department of Mechanical and
Aerospace Engineering
Shameer, Waseem (2019). Experimental study of self-sustainable hybrid solar
photovoltaic cleaning mechanism coupled with water distillation unit.
Vibroengineering Procedia, 29, 213-218.
Abstract: In the present research work a novel self-sustainable hybrid solar
photovoltaic cleaning mechanism coupled with water distillation unit has been
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proposed. The experiments were conducted on the PV (photovoltaic) modules at
Bennett University, Greater Noida A-block terrace from 7th to 13th October
2019. Post installation, the average efficiencies of the solar PV module system
with and without cleaning were compared to obtain a hike by 1.34 %. The water
used for cleaning was recycled using a single slope basin type solar still which
indicated a working efficiency of 67.94 %. On an average the solar still yielded
5.3 Liters of pure water every day during the experiment with a TDS (total
dissolved solids) level of 104 ppm.
Keyword: Photovoltaic modules, Cleaning mechanism, Water distillation unit,
Efficiency
Yash Guptaa, B.Tech Student, Department of Mechanical and Aerospace
Engineering
Guptaa, Yash (2019). Computational fluid dynamics analysis and experimental
validation of solar panel cleaning mechanism. Vibroengineering Procedia, 29,
225-230.
Abstract: Solar energy is one of the widely used non-conventional form of
energy. Photo voltaic panels generate electricity and heat by absorbing solar
irradiation. The performance of solar panels depends on several factors like dust
accumulation on the surface, solar cell temperature, angle of inclination etc., to
perform the cleaning action efficiently a semi-automatic cleaning mechanism has
been designed and fabricated. The designed experimental setup consists of
several nozzles attached on top of the solar panels and water is supplied to each
nozzle using a Poly Vinyl Chloride (PVC) pipe frame connected to an AC motor
operated with a time switch. Water flows on the surface of photo voltaic module,
thus heat exchange takes place. One dimensional heat transfer analysis is
performed, and the results are compared to the experimental results for
validation. The experiments were conducted at Bennett University, Greater
Noida dated 9 October to 16 October. An increase in efficiency by 1.28 % to
2.65 % was reported in this experimental study.
Keyword: Photo voltaic module, Computational fluid dynamics analysis, Solar
panel cleaning mechanism.
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Guptaa, Yash (2019). Experimental investigation of photovoltaic module
system coupled with solar panel cleaning system. Vibroengineering Procedia,
29, 219-224.
Abstract: Solar energy is a non-conventional source of energy. Solar panels
generate electrical output by absorbing solar radiation. The performance of
photovoltaic (PV) module often depends on environmental factors like dust,
humidity, hail and temperature. Installation elements like altitude, installation
site, tilt angle also affects the efficiency of solar energy output. The objective of
this research work is to clean the dust deposited on PV panels using the
minimum amount of water and energy. To regularly clean the dust, a semi-
automatic self-cleaning mechanism has been designed and fabricated, which
cleans the deposited dust on the solar panel automatically. Therefore, the process
turns out to be reliable and faster and it leads to increased power output of the
solar panels. An experimental investigation has been done at Bennett University;
Greater Noida dated 15 October to 21st October 2019. An increase in efficiency
by 1.2 % to 3 % was reported in this experimental study.
Keyword: Photovoltaic (PV), Nozzle, Semi-automatic self-cleaning mechanism.
Guptaa, Yash (2019). Experimental study of self-sustainable hybrid solar
photovoltaic cleaning mechanism coupled with water distillation unit.
Vibroengineering Procedia, 29, 213-218.
Abstract: In the present research work a novel self-sustainable hybrid solar
photovoltaic cleaning mechanism coupled with water distillation unit has been
proposed. The experiments were conducted on the PV (photovoltaic) modules at
Bennett University, Greater Noida A-block terrace from 7th to 13th October
2019. Post installation, the average efficiencies of the solar PV module system
with and without cleaning were compared to obtain a hike by 1.34 %. The water
used for cleaning was recycled using a single slope basin type solar still which
indicated a working efficiency of 67.94 %. On an average the solar still yielded
5.3 Liters of pure water every day during the experiment with a TDS (total
dissolved solids) level of 104 ppm.
Keyword: Photovoltaic modules, Cleaning mechanism, Water distillation unit,
efficiency.
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Yash Jaiman, B.Tech Student, Department of Mechanical and Aerospace
Engineering
Jaiman, Yash (2019). Free vibration of circular annular plate with different
boundary conditions. Vibroengineering Procedia, 29, 82-86.
Abstract: This paper deals with the numerical simulation of free vibration
analysis of a thin circular annular plate for various boundary conditions at the
outer edge and inner edge. Classical plate theory is used to derive the governing
differential equation for the transverse deflection of the thin isotropic plate. The
finite element method is used to evaluate the first six natural frequencies and
mode shapes of the thin uniform circular annular plate with radius ratios (r1/r2)
for different boundary conditions. These natural frequencies results are compared
with those available in the literature. The results are verified with classical plate
theory with our Abaqus results and checked with the previous research literature
on the topic.
Keyword: Circular annular plate, Free vibration, Numerical simulation.
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Department of Physics
Dr. Alok Shukla, Assistant Professor, Department of Physics
Shukla, Alok (2016). Origin of multiple band gap values in single width
nanoribbons. Scientific Reports, 6(36168), 1-7.
Abstract: Deterministic band gap in quasi-one-dimensional nanoribbons is
prerequisite for their integrated functionalities in high performance molecular-
electronics based devices. However, multiple band gaps commonly observed in
graphene nanoribbons of the same width, fabricated in same slot of experiments,
remain unresolved, and raise a critical concern over scalable production of
pristine and/ or hetero-structure nanoribbons with deterministic properties and
functionalities for plethora of applications. Here, we show that a modification in
the depth of potential wells in the periodic direction of a supercell on relative
shifting of passivating atoms at the edges is the origin of multiple band gap
values in nanoribbons of the same width in a crystallographic orientation,
although they carry practically the same ground state energy. The results are
similar when calculations are extended from planar graphene to buckled silicane
nanoribbons. Thus, the findings facilitate tuning of the electronic properties of
quasi-one-dimensional materials such as bio-molecular chains, organic and
inorganic nanoribbons by performing edge engineering.
Shukla, Alok (2017). From Half-Metal to Semiconductor: Electron-Correlation
Effects in Zigzag SiC Nanoribbons from First Principles. Physical Review
Applied, 7, 064009.
Abstract: We perform electronic-structure calculations based on the first
principles many-body–theory approach in order to study quasiparticle band gaps
and optical absorption spectra of hydrogen-passivated zigzag SiC nanoribbons.
Self-energy corrections are included using the GW approximation, and excitonic
effects are included using the Be the-Salpeter equation. We systematically study
nanoribbons that have widths between 0.6and2.2nm. Quasi particle corrections
widen the Kohn-Sham band gaps because of enhanced interaction effects, caused
by reduced dimensionality. Zigzag SiC nanoribbons with widths larger than 1 nm
exhibit half-metallicity at the mean-field level. The self-energy corrections
increase band gaps substantially, thereby transforming the half-metallic zigzag
SiC nanoribbons to narrow gap spin-polarized semiconductors. Optical
absorption spectra of these nanoribbons get dramatically modified upon inclusion
of electron-hole interactions, and the narrowest ribbon exhibits strongly bound
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excitons, with binding energy of 2.1eV. Thus, the narrowest zigzag SiC
nanoribbon has the potential to be used in optoelectronic devices operating in the
IR region of the spectrum, while the broader ones, exhibiting spin polarization,
can be utilized in spintronic applications.
Keyword: Semiconductor, Electron-Correlation
Shukla, Alok (2017). Tunable Optoelectronic Properties of Triply Bonded
Carbon Molecules with Linear and Graphyne Substructures. J. Phys. Chem. C,
122, 1309.
Abstract: In this paper we present a detailed computational study of the
electronic structure and optical properties of triply bonded hydrocarbons with
linear and graphyne substructures, with the aim of identifying their potential in
optoelectronic device applications. For this reason, we employed a correlated
electron methodology based upon the Pariser−Parr−Pople model Hamiltonian,
coupled with the configuration interaction (CI) approach, and studied structures
containing up to 42 carbon atoms. Our calculations, based upon large-scale CI
expansions, reveal that the linear structures have intense optical absorption at the
HOMO− LUMO gap, while the graphyne ones have those at higher energies.
Thus, the optoelectronic properties depend on the topology of the graphyne
substructures, suggesting that they can be tuned by means of structural
modifications. Our results are in very good agreement with the available
experimental data.
Shukla, Alok (2018). Effect of edge defects on band structure of zigzag
graphene nanoribbons. Journal of Applied Physics, 123, 161416.
Abstract: In this article, we report band structure studies of zigzag graphene
nanoribbons (ZGNRs) on introducing defects (sp3 hybridized carbon atoms) in
different concentrations at edges by varying the ratio of sp3 to sp2 hybridized
carbon atoms. On the basis of theoretical analyses, bandgap values of ZGNRs
are found to be strongly dependent on the relative arrangement of sp3 to sp2
hybridized carbon atoms at the edges for a defect concentration; so the findings
would greatly help in understanding the bandgap of nanoribbons for their
electronic applications
Shukla, Alok (2018). Electron correlation effects and two-photon absorption in
diamond-shaped graphene quantum dots. Physical Review B, 98(3), 035401-9.
Abstract: In quasi-1D π-conjugated polymers such as trans-polyacetylene and
polyenes, electron correlation effects determine the “reversed” excited state
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ordering in which the lowest two-photon 2Ag state lies below the lowest one-
photon 1Bu state. In this paper, we present conclusive theoretical evidence of
reversed excited state ordering in fairly 2D π-conjugated systems, namely,
diamond-shaped graphene quantum dots (DQDs). Our electron correlated
calculations show that DQDs begin to exhibit reversed excited ordering with
increasing size, in disagreement with independent-particle picture. This signals
the onset of strong correlation effects which renders them non luminescent.
Further, we calculate and analyze the two-photon absorption (TPA) spectra as
well as photoinduced absorption (PA) spectra of these systems and find
excellent agreement with the available experimental results. Our investigations
demonstrate that unlike a strictly 1 system like trans-polyacetylene, the
nonlinear and excited state absorptions in DQDs are highly intricate, with
several even parity states responsible for strong absorptions. Our results could
play an important role in the design of graphene-based non-linear optical
devices.
Keyword: Electron correlation, Photon absorption
Shukla, Alok (2018). Tunable electronic properties of partially edge-
hydrogenated armchair boron-nitrogen-carbon nanoribbons. Physical Chemistry
Chemical Physics, 20, 10345-10358.
Abstract: We employ a first-principles calculations-based density-functional-
theory (DFT) approach to study the electronic properties of partially and fully
edge-hydrogenated armchair boron–nitrogen–carbon (BNC) nanoribbons
(ABNCNRs), with widths between 0.85 nm to 2.3 nm. Due to the partial
passivation of edges, the electrons, which do not participate in the bonding,
form new energy states located near the Fermi-level. Because of these
additional bands, some ABNCNRs exhibit metallic behavior, which is quite
uncommon in armchair nanoribbons. Our calculations reveal that metallic
behavior is observed for the following passivation patterns: (i) when the B atom
from one edge and the N atom from another edge are unpassivated. (ii) When
the N atoms from both the edges are unpassivated. (iii) When the C atom from
one edge and the N atom from another edge are unpassivated. Furthermore, spin
-polarization is also observed for certain passivation schemes, which is also
quite uncommon for armchair nanoribbons. Thus, our results suggest that the
ABNCNRs exhibit a wide range of electronic and magnetic properties in that
the fully edge-hydrogenated ABNCNRs are direct band gap semiconductors,
while the partially edge-hydrogenated ones are either semiconducting, or
metallic, while simultaneously exhibiting spin polarization, based on the nature
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of passivation. We also find that the ribbons with larger widths are more stable
as compared to the narrower ones.
Dr. Ayan Khan, Assistant Professor, Department of Physics
Khan, Ayan (2018). Electron-Hole Bilayer Systems in Semiconductors: A
Theoretical Perspective. Nanotechnology-Driven Engineered Materials New
Insights (pp. 141-172).
Abstract: In this generation of semiconductor based miniature gadgets, it is
always in intriguing issue to understand the underlying mechanism of these
highly. Sophisticated devices systematic exploration uncovers the fascinating
world of Nano-scale physics; however. A deeper probe actually unearths the
salient nature of electron hole interaction which is the soul of semiconductor
physics. In his essay we plan to shed some light on the interplay of different
interactions in electron hole system. This study is purely theoretic all, however.
We put forward recent experiment successes at suitable places. Here we
explicate the intricacies in electron (hole) - electron (hole) and electron hole
interaction in the realm of mean field theory to make our description
comprehensive and complete. We elaborate the theoretical analysis by mean of
both path integral formalism and canonical transformation method. The
discussion clearly suggest that the interplay of intra-layer and inter-layer
interactions result in the formation of serval exotic phase such as Sharma and
fulde- Ferrell- Larkin-Ovehinniov (FFLO) phase.
Khan, Ayan (2017). Effect of weak disorder on the BCS-BEC crossover in a two
-dimensional Fermi gas. International Journal of Modern Physics B, 1750066.
Abstract: In this paper, we study the two-dimensional (2D) ultracold Fermi gas
with weak impurity in the framework of mean field theory where the impurity is
introduced through Gaussian fluctuations. We have investigated the role of the
impurity by studying the experimentally accessible quantities such as condensate
fraction and equation of state of the ultracold systems. Our analysis reveals that
at the crossover, the disorder enhances superfluidity, which we attribute to the
unique nature of the unitary region and to the dimensional effect.
Keyword: BCS-BEC crossover, Lower Dimensional Systems, Disorder systems
Khan, Ayan (2017). Emerging novel phases of Bose-Einstein Condensate for
various topology. Journal of Physics: Conference Series, 875, 082009.
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Abstract: In this work, we realize the soliton’s negative mass regime, when a
Bose-Einstein condensate is subjected to a harmonic confinement. We also
discuss that this system is favorable for the formation of a bound state when an
additional species is considered. When a time modulated optical lattice potential
is introduced, the sinusoidal lattice modes lead to the generation of nonlinear
resonances. A classical dynamical phase transition is also identified in this case
through a superfluid to the insulating phase transition.
Keyword: Emerging novel phases, Bose-Einstein Condensate
Dr. Ayan Ray, Assistant Professor, Department of Physics
Ray, Ayan (2018). Unusual Li-Storage Behaviour of Two-Dimensional ReS2
Single Crystals. Batteries & Supercaps, 69-74.
Abstract: Unusual Li-storage properties are observed for two-dimensional
ReS2 compared to its analogue MoS2. First, we prepared ReS2 single crystals
(99.9% crystallinity) by chemical vapor transport with high yield and utmost
purity. Li-storage properties are assessed using a standard half-cell assembly
with metallic Li as the counter electrode. The highly crystalline ReS2 rendered
excellent electrochemical characteristics with interesting features. This logically
leads to further exploration of ReS2 towards Li-storage. Indeed, ReS2 could act
as efficient intercalation host for Li-ions with lower redox potential (~1.2 V vs.
Li) and decent reversibility (~0.4 mol Li). On the other hand, high reversibility
is registered while deep discharging of the active material. This eventually
obeys the perfect conversion pathway. Interestingly, electrochemically
activated ReS2 also rendered good reversibility and eventually serves as an
insertion host with a working potential of ~2 V vs. Li.
Dr. Bishnu P. Pal, Consulting Professor, Department of Physics
Pal, Bishnu P. (2017). Design of a Compact Polarization Rotator Based on a
Silicon Slot-Waveguide for Applications in Mid-IR. IEEE international
Workshop on Recent Advances in Photonics (pp. 1-3).
Abstract: We propose design of a compact and very efficient silicon-based
polarization rotator for mid-IR wavelength of 4.47 94.5% for both the
polarizations within a device length of just 0.576 mm.
Keyword: Polarization-selective devices, Slot waveguides, Integrated optics
devices
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Pal, Bishnu P. (2017). Highly Efficient Polarization Splitter Based on a Silicon-
on-Nitride Asymmetric Waveguide for Mid-IR. International conference on Appl
Opt. and Photon.
Abstract: A compact (-19um long) polarization splitter (PS) for mid-IR
wavelength of 3 pm based on silicon-on-nitride asymmetric direction coupler is
designed by exploiting evanescent coupling between two non-identical. Through
numerical simulations, we demonstrate that a relatively large extinction ration
(>25dB) with quite low insertion (<0.1 dB) is achievable without designed PS.
Keyword: Polarization splitter, Nitride Asymmetric Waveguide
Pal, Bishnu P. (2017). Stable Propagation of Self Similar Pulses Through A
Chirped-clad All-solid Bragg Fiber in the Mid-IR. International Workshop on
Specialty Optical Fibers.
Abstract: We report formation and improved stable propagation of self-similar
parabolic pulses through chalcogenide glass based chirped-clad Bragg fiber at 3
μm wavelength. We employ a longitudinally varying dispersion landscape with
close to zero average dispersion. OCIS codes: (190.4370) Nonlinear optics,
fibers; (320.7110) Ultrafast nonlinear optics; (060.5295) Photonic crystal fibers.
Keyword: Chirped-clad, Bragg Fiber, Mid-IR
Pal, Bishnu P. (2018). Design of a Highly Efficient Silicon Polarization
Rotator for Mid-IR. Workshop on Optics and Photonics: Theory and
Computational Techniques (pp. 71-83). IIT Roorkee.
Abstract: A highly efficient silicon-based polarization rotator (PR) for mid-IR
wavelength of 3 pm is presented. Through numerical estimations, we
demonstrate that with a length of just 0.522 mm of our designed PR achievable
power coupling efficiency is a high as 98% for both the polarization.
Keyword: Silicon Polarization, Rotator
Pal, Bishnu P. (2018). Single split gap resonator-based terahertz metamaterials
for refractive index sensing. Photonics West Opto 2018 Conference (pp. 58).
Abstract: We have numerically demonstrated refractive index sensing using
terahertz metamaterials comprised of single split gap resonators. Sensing
capabilities of odd and even order resonance modes are precisely investigated.
In this scheme the top surface of metamaterials array is covered with a thin
layer of polyimide who’s refractive could be changed manually. The sensitivity
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and corresponding figure of merit (FoM) of several lowest order modes are
examined with respect to the different thicknesses of the coated polyimide film.
We have investigated the electric field distributions at different resonances for
the MMs. Although we have mainly focused on refractive index sensing, but
this study could be extremely useful for the development of metamaterials-
based sensing devices, biosensors etc.
Keyword: Terahertz Metamaterial, Split Ring Resonator, Thin film Sensing,
Subwavelength Structures, Terahertz radiation
Pal, Bishnu P. (2017). Role of Resonance Modes on Terahertz Metamaterials
based Thin Film Sensors. Scientific Reports, 1-8.
Abstract: We investigate thin film sensing capabilities of a terahertz (THz)
metamaterial, which comprises of an array of single split gap ring resonators
(SRRs). The top surface of the proposed metamaterial is covered with a thin
layer of analyte in order to examine various sensing parameters. The sensitivity
and corresponding figure of merit (FoM) of the odd and even resonant modes are
analyzed with respect to different thicknesses of the coated analyte film. The
sensing parameters of different resonance modes are elaborated and explained
with appropriate physical explanations. We have also employed a semi analytical
transmission line model in order to validate our numerically simulated
observations. Such study should be very useful for the development of
metamaterials-based sensing devices, bio-sensors etc. in near future.
Pal, Bishnu P. (2017). Toward Self-Similar Propagation of Optical Pulses in a
Dispersion Tailored, Nonlinear, and Segmented Bragg-Fiber at 2.8 mu m. IEEE
Photonics Journal, 9(4), 1-12.
Abstract: We demonstrate self-similar stable propagation of parabolic optical
pulses through a highly nonlinear specialty Bragg fiber at 2.8 μm by a numerical
approach. To obtain such propagation characteristics over a longer length of a
Bragg fiber, we propose and verify a fiber design scheme that underpins passive
introduction of a rapidly varying group-velocity dispersion around its zero
dispersion wavelength and modulated nonlinear profile through suitable variation
in its diameter. To implement the proposed scheme, we design a segmented and
tapered chalcogenide Bragg fiber in which a Gaussian pulse is fed.
Transformation of such a launched pulse to a self-similar parabolic pulse with
full-width at-half-maxima of 4.12 ps and energy of ∼39 pJ is obtained at the
output. Furthermore, a linear chirp spanning across the entire pulse duration and
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3 dB spectral broadening of about 38 nm at the output are reported. In principle,
the proposed scheme could be implemented in any chosen set of materials.
Keyword: Fiber nonlinear optics, Pulse shaping
Pal, Bishnu P. (2018). Design of chip scale silicon rib slot waveguide for sub-
ppm detection of N2O gas at mid-IR band. Sensors and Actuators B: Chemical,
3409-3416.
Abstract: A chip-level silicon rib horizontal double-slot waveguide geometry
has been proposed and designed for trace gas sensing in mid-IR regime through
the evanescent field absorption-based sensing scheme. We have optimized the
structure at the 4.47 m mid-IR band for efficient detection of hazardous N2O
gas in the atmosphere at sub-ppm concentration level. Maximum achievable
evanescent field fraction (i.e. power confinement ()) in the sensing region is as
high as 68.0%, which leads to detection down to nearly 0.2 ppm level with 1.44
cm length of our designed waveguide even after including the waveguide
losses. With this optimum sensor design, we have also studied detectability of
CO and CH4 gases numerically at the wavelength of 4.6 m and, 3.67 m,
respectively, and have shown that minimum detectable concentrations for these
gases are nearly 0.44 ppm and 36 ppm, respectively. Fabrication tolerances of
the structure have shown that sensor has high tolerance to fabrication
imperfections.
Keyword: Integrated Photonic Sensors, Evanescent field absorption, Slot
waveguides, Silicon devices, mid infrared photonics
Dr. Gaurav Shukla, Assistant Professor, Department of Physics
Shukla, Gaurav (2017). Bullen's Parameter as a Seismic Observable for Spin
Crossovers in the Lower Mantle. Geophysical Research Letters, 9314-9320.
Abstract: Elastic anomalies produced by the spin crossover in ferro periclase
have been documented by both first-principles calculations and high pressure-
temperature experiments. The predicted signature of this spin crossover in the
lower mantle is, however, subtle and difficult to geo physically observe within
the mantle. Indeed, global seismic anomalies associated with spin transitions
have not yet been recognized in seismologic studies of the deep mantle. A
sensitive seismic parameter is needed to determine the presence and amplitude of
such a spin crossover signature. The effects of spin crossovers on Bullen’s
parameter, , are assessed here for a range of compositions, thermal profiles, and
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lateral variations in temperature within the lower mantle. Velocity anomalies
associated with the spin crossover in ferro periclase span a depth range near
1,000 km for typical mantle temperatures. Positive excursions of Bullen’s
parameter with a maximum amplitude of∼0.03 are calculated to be present over a
broad depth range within the middle-to-deep lower mantle: these are largest for
peridotite and harzburgitic compositions. These excursions are highest in
amplitude for model lower mantles with large lateral thermal variations and with
cold down welling’s having longer lateral length-scales relative to hot
upwellings. We conclude that predicted deviations in Bullen’s parameter due to
the spin crossover in ferro periclase for geo physically relevant compositions
may be sufficiently large to resolve in accurate seismic inversions of this
parameter and could shed light on both the lateral variations in temperature at
depth within the lower mantle, and the amount of ferropericlase seat depth.
Keyword: Seismic Observable, Spin Crossovers
Shukla, Gaurav (2019). Thermoelasticity of iron- and aluminum-bearing
MgSiO3 post-perovskite. Journal of Geophysical Research: Solid Earth, 124(3),
2417-2427.
Abstract: We present ab initio (LDA + Usc) studies of high-temperature and
high-pressure elastic properties of pure as well as iron- (ferrous, Fe2+; and ferric,
Fe3+) and aluminium -bearing MgSiO3 post-perovskite, the likely dominant
phase in the deep lower mantle of the Earth. Thermal dffects are addressed
within the quasi harmonic approximation by combining vibrational density of
states (VDoS) and static elastic coefficients. Aggregate elastic moduli and sound
velocities for the Mg-end members are successfully compared with scarce
experimental data available. Effects of iron (Fe) and aluminum (Al) substitutions
on elastic properties and their pressure and temperature dependence have been
thoroughly investigated. At the observed perovskite to post-perovskite transition
(P = 125 GPa and T = 2500 K), compressional and shear velocities increase by 0-
1% and 1.5-3.75%, respectively. This observation is consistent with some
seismic studies of the D00 discontinuity beneath the Caribbean, which suggests
that our robust estimates of elastic properties of the post-perovskite phase will be
very helpful to understand lateral velocity variations in the deep lower mantle
region and to constrain its com position and thermal structure.
Keyword: Thermoelasticity, Post-perovskite.
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Dr. Krishna Thyagarajan, Professor, Department of Physics
Thyagarajan, K. (2018). Second Harmonic Generation in Planar Waveguides
Using Slant Grating. WRAP - Workshop on Recent Advances in Photonics (pp.
1-3).
Abstract: In this paper, we propose a device based on planar waveguides with
multiple slanted quasi-phase-matching gratings to achieve a significant increase
in the bandwidth of second-harmonic generation. We show that an appropriate
device design can significantly flatten the efficiency of second-harmonic
generation as a function of input pump frequency. The design using slanted
gratings allows for the fundamental and second harmonic to be noncollinear and
thus makes the collection of the generated wave easy. Numerical simulations
are performed in a potassium titanyl phosphate (KTP) planar waveguide, and
we show the analysis and results for increased bandwidth using two, three, and
four gratings, which can be easily extended to more gratings without any loss of
generality.
Keyword: Harmonic Generation, Planar Waveguides
Thyagarajan, K. (2018). Direct generation of hybrid entangled photon pairs in
waveguides. Journal of the Optical Society of America B, 35, 790-796.
Abstract: In this paper, we propose a scheme for direct generation of hybrid
spatial modal–polarization entangled photon pairs using a type-II spontaneous
parametric down-conversion process and the electro-optic effect in a domain
engineered potassium titanyl phosphate nonlinear waveguide. Such hybrid
entangled states must find applications in quantum information processing using
integrated photonic circuits.
Keyword: Quantum optics, Nonlinear optics, Integrated optics, Waveguides
Thyagarajan, K. (2018). Photonic crystals: role of architecture and disorder on
spectral properties. J. Opt. Soc. Am. A, 35(3), 370-376.
Abstract: Many of the present-day optical devices use photonic crystals. These
are multilayers of dielectric media that control the reflection and transmission of
light falling on them. In this paper, we study the optical properties of periodic,
fractal, and aperiodic photonic crystals and compare them based on their
attributes. Our calculations of the band reflectivity and degree of robustness
reveal novel features, e.g., fractal photonic crystals are found to reflect the
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photonic crystals have the largest immunity to disorder. We believe that such
properties will be useful in a variety of applications in the field of optical
communication.
Keyword: Photonic crystals, Photonic bandgap materials, Multilayer design
Thyagarajan, K. (2018). Simultaneous sum-frequency and second-harmonic
generation in a planar waveguide. Applied Optics, 4402-4408.
Abstract: In this paper, we analyze second harmonic (SH) generation and sum-
frequency (SF) generation in a planar waveguide configuration using 2D quasi-
phase-matching (QPM) gratings and show possibility of simultaneous
generation of sum frequency and second harmonic. It is shown that it is
possible for the two generated frequencies to be non-collinear with respect to
the incident pump waves with the SF and SH frequencies exiting at different
angles along the planar waveguide, leading to ease of collection. Numerical
simulations are performed in a potassium titanyl phosphate planar waveguide,
and it is shown that the proposed planar waveguide configuration provides
wavelength tunability and has greater conversion efficiencies than bulk
configuration and larger bandwidth than channel waveguide configuration.
Keyword: Sum-frequency (SF) generation, Second harmonic (SH) generation,
planar waveguide
Thyagarajan, K. (2018). Wideband second harmonic generation using
multiple tilted gratings in a planar waveguide. Journal of the Optical Society of
America B-Optical Physics, 35(7), 1609-1614.
Abstract: In this paper, we propose a device based on planar waveguides with
multiple slanted quasi-phase-matching gratings to achieve a significant increase
in the bandwidth of second-harmonic generation. We show that an appropriate
device design can significantly flatten the efficiency of second-harmonic
generation as a function of input pump frequency. The design using slanted
gratings allows for the fundamental and second harmonic to be no collinear and
thus makes the collection of the generated wave easy. Numerical simulations
are performed in a potassium titanyl phosphate (KTP) planar waveguide, and
we show the analysis and results for increased bandwidth using two, three, and
four gratings, which can be easily extended to more gratings without any loss of
generality.
Keyword: Planar Waveguide, Second-harmonic generation (SHG)
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Pradyumn Mane, B.Tech Student, Department of Physics
Mane, Pradyumn (2019). Performance analysis of thermoelectric generator by
using lead telluride, perovskites, skutterudites and tetrahedrites. WEENTECH
Proceedings in Energy (pp. 566-78).
Abstract: In this research paper performance analysis of thermoelectric
generator by using lead telluride, perovskites, skutterudites and tetrahedrites has
been proposed. The performance of thermoelectric materials and thermoelectric
modules has been calculated. These thermoelectric materials were combined to
make thermoelectric couple which will be used in thermoelectric generator. The
performance analysis of these thermoelectric couples were simulated on
COMSOL Multiphysics 5.2 software. The results indicated that Pb1-
xMgxTe0.8Se0.2 and n-type PbTe, Pb1-xMgxTe0.8Se0.2 and CoSb3-xTex, Pb1-
xMgxTe0.8Se0.2 and CaMn0.98Nb0.02O3, Cu12Sb4S13 and CoSb3-xTex
indicated higher efficiency than other thermoelectric couples. The proposed
system can be utilized for varied range of applications for waste heat recovery
and renewable power generation in automotive, industrial, power plants and
space sector at an excellent efficiency and lower cost.
Keyword: Seebeck effect, Lead telluride, Perovskites, Skutterudites, Tetrahedrit
Mane, Pradyumn (2019). Optimization and analysis of novel thermoelectric
module. Vibroengineering Procedia, 29, 231-236.
Abstract: Optimization and analysis of novel thermoelectric module is proposed
in this research paper. The simulation for four thermoelectric modules were
performed in COMSOL Multiphysics 5.4 software and detailed analysis of these
thermoelectric modules were carried out. The three thermoelectric modules
showed the efficiency and power output above-average thermoelectric modules.
It also indicated that lead telluride based thermoelectric modules could be used in
isolated areas due to toxicity of lead whereas tetrahedrite based thermoelectric
module could be used in non-isolated areas due to its non-toxic properties. The
proposed thermoelectric modules can be utilized in applications such as
industries, deep space explorations, automobiles, thermal power plants,
renewable electricity generation, hybrid renewable systems, etc. in an
economically viable manner.
Keyword: Thermoelectric module, Lead telluride, Tetrahedrites, Skutterudites,
perovskites.
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Dr. Swarup K. Panda, Assistant Professor, Department of Physics
Panda, Swarup K. (2019). Charge disproportionate antiferromagnetism at the
verge of the insulator-metal transition in doped LaFeO3. Physical Review B, 99
(7), 75106.
Abstract: We explore the effects of electron doping in lanthanum ferrite,
LaFeO3 by doping Mo at the Fe sites. Based on magnetic, transport, scanning
tunneling spectroscopy, and x-ray photoelectron spectroscopy measurements, we
find that the large gap, charge-transfer, antiferromagnetic (AFM) insulator
LaFeO3 becomes a small gap AFM band insulator at low Mo doping. With
increasing doping concentration, Mo states, which appear around the Fermi level,
is broadened and become gapless at a critical doping of 20%. Using a
combination of calculations based on density functional theory plus Hubbard U
(DFT+U) and x-ray absorption spectroscopy measurements, we find that the
system shows charge disproportionation (CD) in Fe ions at 25% Mo doping,
where two distinct Fe sites, having Fe2+ and Fe3+ nominal charge states appear.
A local breathing-type lattice distortion induces the charge disproportionation at
the Fe site without destroying the antiferromagnetic order. Our combined
experimental and theoretical investigations establish that the Fe states form a CD
antiferromagnet at 25% Mo doping, which remains insulating, while the
appearance of Mo states around the Fermi level is showing an indication towards
the insulator-metal transition.
Keyword: Insulator – Metal, Antiferromagnetism
Panda, Swarup K. (2019). Pronounced 2/3 magnetization plateau in a frustrated
S = 1 isolated spin-triangle compound: Interplay between Heisenberg and
biquadratic exchange interactions. Physical Review B, 100(1), 1-12.
Abstract: We report the synthesis and characterization of a new quantum magnet
[2-[Bis(2-hydroxybenzyl) aminomethyl] pyridine] Ni (II)-trimer (BHAP-Ni3) in
single-crystalline form. Our combined experimental and theoretical
investigations reveal an exotic spin state that stabilizes a robust 2/3
magnetization plateau between 7 and 20 T in an external magnetic field. AC-
susceptibility measurements show the absence of any magnetic order/glassy state
down to 60 mK. The magnetic ground state is disordered, and specific-heat
measurements reveal the gapped nature of the spin excitations. (AFM)
interactions
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Most interestingly, our theoretical modeling suggests that the 2/3 magnetization plateau
emerges due to the interplay between antiferromagnetic Heisenberg and biquadratic
exchange interactions within nearly isolated spin S = 1 triangles.
Keyword: Magnetization plateau, Isolated spin-triangle, Antiferromagnetic
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Aafreen Collaco, Research Associate, School of Law
Collaco, Aafreen (2018). Open Source Policy: An Indian Perspective. Special
Issue NLIU Journal of Intellectual Property, 49.
Abstract: Internet of Things (IOT) and Artificial Intelligence (AI) are terms
which have suddenly captured the attention of many, especially the legal
fraternity with the India government rolling elaborate policies under the board
spectrum of achieving ‘Digital India’, it becomes imperative to examine the
impact of existing and new policies on research and development. The current
IP regime in India is undergoing tremendous changes. With the adoption of the
National IPR Policy in 2016, efforts are being made to make the IP regime
more innovator friendly. Today, the adoption of Open source Software (OSS) is
on a rise and has led to numerous innovations in the Information and
Communication Technology (ICT) sector. With stiff competition and new
developments, the chances of infringement also increase. It is not just the
private players who deal with these issues, but the local government too has
started realizing the importance of protection of computer software. With the
introduction of the Digital India programme and Start-up India, The
Department of Electronics and Information Technology (Deity) under the
Ministry of Communications and Information Technology has come out with
various policies which aim at achieving e- Governance in India. The aim and
objective of this paper is to examine the existing policies with the focus on the
recent National IPR Policy. The paper will also analyses the legal issues which
arise with the implementation of these policies. The main contours of legal
protection for computer technology have emerged in the past decade.
Conventionally, computer software was protected in the form of copyrights,
trade secrets and patents. But with the development of Open Source software
and copyright Licensing, the theories relating to IP protection of computer
software have undergone a drastic change. Hence, this paper will re-evaluate
and re-examine the existing concepts in IP protection of computer software and
will give an insight on the new developments revolving around OSS. The paper
will also examine the existing loopholes under different regimes regarding
computer software protection. It will suggest protection which will be suitable
to the Indian scenario keeping in mind the Start-Up milieu.
Keyword: Open source software, Internet of Things, National IPR Policy
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Ankit Dhotrekar, Assistant Professor, School of Law
Dhotrekar, Ankit (2019). Refugee Protection in India: The Conundrum of
Human Rights and State Sovereingity. The Journal of Law and Public Policy, 5
(2), 1-10.
Abstract: Refugees have been permitted to take abode in India for centuries.
However, there is no well-defined law on refugees in India. Ad-doc policies and
judicial pronouncements have provided some relief on case by case basis.
Refugees, therefore, are at the mercy of the discretion of the government and its
policies. Further, India has consistently declined to sign the Convention Relating
to the Status of Refugees, 1951 and its protocol but has signed several other
international instruments pertaining to human rights. There is no specific policy
in India that shows its ideology towards the refugees and while this is suggestive
of its desire to protect it sovereignty amongst other reasons, the principle of non-
refoulement neutralizes the effect. “Sovereignty” and “human rights” are placed
in the same basket when one studies refugee protection laws. The paper
highlights that the absence of specific law on safety and rights of the refugees in
India has consequently accentuated the refusal to grant even the basic rights to
the refugees. In light of this sovereignty concerns, the paper provides an
overview of the India’s policy (or absence thereof) on protection and
advancement of the human rights of the refugees. The paper also provides a
scrutiny of India’s position on the Convention Relating to the Status of Refugees,
1951 and its protocol along with the recent Global Compact on Refugees, 2018.
Keyword: Refugee, International Law, Human Rights
Dr. Ashita Allamaraju, Assistant Professor, School of Law
Allamaraju, Ashita (2017). Do MSMEs Engage in Cartels? A Brief Anti-trust
Perspective from India. The Delhi University Journal of the Humanities and the
Social Sciences, 4, 57-78.
Abstract: One of the primary objectives of a competition agency is to prohibit
cartels since they injure customers by raising prices and restricting supply, thus
making goods and services completely unavailable to some purchasers and
unnecessarily expensive for others. Section 3(3) of the Indian Competition Act
prohibits agreements in respect of production, supply, distribution, storage,
acquisition or control of goods or provision of services, which causes or is likely
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to cause an Appreciable Adverse Effect on Competition (AAEC) within India.
However, co-operation agreements among the SME are often considered a means
of ensuring survival and offsetting structural disadvantages. Forms of co-
operation whose sole purpose and intent is the restriction of competition are not
exempt from a general ban on cartels. Given the above, the paper considers the
recent anti-trust cases in India which involved SMEs and looks at the forms of
cooperation between them and the specific need for advocacy on competition
issues for the SME sector.
Keyword: Competition Act, MSME, Cartel, Bid-Rigging, Trade Association,
Horizontal Agreements
Allamaraju, Ashita (2019). MPLADS: To Scrap or To Re-Invent?. Journal of
Governance & Public Policy, 9(1), 118-124.
Abstract: Member of Parliament Local Area Development Scheme (MPLADS)
is a centrally sponsored program funded by the Government of India. It was
initiated to empower the Members of Parliament (MPs) to develop their
respective constituencies based on the local needs. This paper attempts to
understand MPLADS and suggest that there is a need to reformulate the scheme
to help MPs do their developmental duties more efficiently. The paper is divided
into five sections. The first section attempts to throw light on the basics of
MPLADS as a scheme – objective of the programme and working of MPLADS.
The second section discusses the past trends about the utilization of funds. The
third section discusses the opinions in support of scrapping this scheme. The
fourth section focuses on the need to have structured underlying research in an
attempt to reinvent the program. The concluding section suggests that there is a
need for a more structured approach towards collecting evidence at the level of
the constituency.
Keyword: Constituency, MPLADS, Development, Scheme
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Bhumika Nanda, Assistant Professor, School of Law
Nanda, Bhumika (2018). Role of Media in the Criminal Justice system-
analyzing the Rajasthan orinance & the Talwar acquittal case. In Kiran Gardner
(ed.), Lex Et Societatis - Contemporary Legal Issues (pp. 357-365).
Abstract: In a democracy it is important that the citizenry is informed of events
which happen within and without their nation. In the absence of news agencies
which can provide accurate information citizens are unable to exercise their
right in an effective manner and make informed choices in their lives. The
importance of the right of information provided by the media has been
appreciated by the Supreme Court in several landmark judgement. In Raj
Narain the court observed: In a Government of responsibility like ours. Where
all the agents of the public must be responsible for their conduct. There can be
put few secrets. The people of this country have a right to know every public
Act, everything that is done in a public way, by their public functionaries.
Similarly in S.P. Gupta the Apex Court observed; the concept of an open
government in the direct emanation from the right of now which seen to be
implicit in the right to free speech and expression guaranteed under Article 19
(1) (a) therefore, disclosure of information in regard to the functioning of the
Government must be rule and secrecy an exception.
Keyword: Criminal justice system, Rajasthan ordinance, Media trials
Dr. Garima Tiwari, Assistant Professor, School of Law
Tiwari, Garima (2018). Gendered Decision Making: The Engagement of the
Supreme Court of India with International Norms in the area of women’s rights.
VRÜ Verfassung und Recht in Übersee, 51, 499-513.
Abstract: This paper explores the engagement of the Supreme Court of India
with various international instruments (binding and non-binding) to protect and
promote the rights of women. While normally the type of legal system (monist
or dualist) creates differences in the application of international law, in the
Indian context, judicial activism has on many occasions bridged this difference.
The paper studies how international law has served both the traditional statist
protectionist position and the modern substantive equality approach. Further, in
a domestic setting, the Supreme Court has made women an apparent subject of
international law. From direct incorporation of international law to making
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adequate use of its persuasive value, the Supreme Court has used different
methodologies in its reasoning and decisions. Without using any specific
approach in enforcing international law in India, the court has cherry picked the
catalogue of international instruments to place itself in the larger international
legal community. All these judgments have been justified within the
constitutional limits and therefore, it forges a positive and legitimate
relationship between international and domestic law.
Keyword: International Law, Gender, India, Supreme Court of India
Tiwari, Garima (2019). Activation of ICC’s Jurisdiction Over the Crime of
Aggression: Fusion and Fission of Jus in Bello and Jus Ad Bellum. Indian
Journal of Law and International Affairs, 3(1), 1-14.
Abstract: The jurisdiction of the International Criminal Court over the crime of
aggression got activated on 17th July 2018. While there are critical issues
pertaining to its scope and application, the significant feature of the crime of
aggression lies in its very nature of combining, just in bello (international
humanitarian law) and jus ad bellum (law in warfare), which have been kept
separate in other crimes enlisted in the Rome Statute. The paper gives an
understanding of how the crime of aggression merges the two diverging
segments of law from definitional, jurisdictional and conceptual perspectives.
The paper also observes how the requirement of manifest violation creates
similar concerns. With reference to the war on terror and just war concept, there
is a further fueling of the idea that jus ad bellum should impact jus in Bello.
Previous international judicial decisions, particularly those of the International
Criminal Court, The Special Court for Sierra Leone and the International
Criminal Tribunal for Yugoslavia have consistently articulated the two fields as
distinct. Thus, the actual consequences of allowing a single court to adjudicate on
the crime of aggression-a crime that merges jus in bello and jus ad bellum under
its fold- requires deeper analysis and further study. Thus, the paper explores the
basic contours of the relationship between the jus ad bellum and the jus in Bello
with reference to the crime of aggression.
Keyword: International Law, Aggression, International Criminal Law
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Tiwari, Garima (2019). Crime of Aggression: Demystifying the Rough Edges
from Kampala to Rome. Indian Society of International Law-ISIL Yearbook of
International Humanitarian and Refugee Law, 84.
Abstract: On 1 7 ' July 2018 when International Criminal Court assumes and
activates its jurisdiction over the crime of aggression and with this the
controversy over the meaning and interpretation of the definition will again come
to debate. While the real impact will be visible with courts decision-making
exercise, a theoretical and critical analysis on the subject is of urgent importance.
With the new definition making it state centric crime, it has already excluded the
non-state actors and it floats in political waters with General Assembly
Resolution 3314 and Nuremberg Charter as its predecessor. It has also departed
from the core idea of international criminal law based on individual criminal
responsibility. The paper will critically analyse all the limbs of this consensus-
born definition including the acts of commission: planning, preparation, initiation
or execution; the issue of aggression as a leadership crime and the trigger
pertaining to the character, gravity and scale as the qualifiers to manifest
violation of the United Nations Charter. The paper also discusses the effect of the
opt-in and opt-out conditions on the amendment. With the chaotic list of acts
amounting to aggression coupled with the excessive power granted to the
Security Council, the definition has already lost its viable legal value of
neutrality. Further, since it merges the idea of jus in Bello and jus ad bellum the
interpretation and decision-making process of the court would replicate a
complex politicized agenda. It is proposed that crime of aggression in its present
form presupposes certain inherent limitations for the exercise of jurisdiction by
the ICC.
Keyword: International Criminal Law, Aggression
Tiwari, Garima (2019). Refugee Protection in India: The Conundrum of Human
Rights and State Sovereingity. The Journal of Law and Public Policy, 5(2), 1-10.
Abstract: Refugees have been permitted to take abode in India for centuries.
However, there is no well-defined law on refugees in India. Ad-doc policies and
judicial pronouncements have provided some relief on case by case basis.
Refugees, therefore, are at the mercy of the discretion of the government and its
policies. Further, India has consistently declined to sign the Convention Relating
to the Status of Refugees, 1951 and its protocol but has signed several other
international instruments pertaining to human rights. There is no specific policy
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in India that shows its ideology towards the refugees and while this is suggestive
of its desire to protect it sovereignty amongst other reasons, the principle of non-
refoulement neutralizes the effect. “Sovereignty” and “human rights” are placed
in the same basket when one studies refugee protection laws. The paper
highlights that the absence of specific law on safety and rights of the refugees in
India has consequently accentuated the refusal to grant even the basic rights to
the refugees. In light of this sovereignty concerns, the paper provides an
overview of the India’s policy (or absence thereof) on protection and
advancement of the human rights of the refugees. The paper also provides a
scrutiny of India’s position on the Convention Relating to the Status of Refugees,
1951 and its protocol along with the recent Global Compact on Refugees, 2018.
Keyword: Refugee, International Law, Human Rights
Jacob George Panickasseril, Assistant Professor, School of Law
Panickasseril, Jacob George, (2018). Role of Media in the Criminal Justice
system-analyzing the Rajasthan orinance & the Talwar acquittal case. In Kiran
Gardner (ed.), Lex Et Societatis - Contemporary Legal Issues (pp. 357-365).
Abstract: In a democracy it is important that the citizenry is informed of events
which happen within and without their nation. In the absence of news agencies
which can provide accurate information citizens are unable to exercise their
right in an effective manner and make informed choices in their lives. The
importance of the right of information provided by the media has been
appreciated by the Supreme Court in several landmark judgement. In Raj
Narain the court observed: In a Government of responsibility like ours. Where
all the agents of the public must be responsible for their conduct. There can be
put few secrets. The people of this country have a right to know every public
Act, everything that is done in a public way, by their public functionaries.
Similarly in S.P. Gupta the Apex Court observed; the concept of an open
government in the direct emanation from the right of now which seen to be
implicit in the right to free speech and expression guaranteed under Article 19
(1) (a) therefore, disclosure of information in regard to the functioning of the
Government must be rule and secrecy an exception.
Keyword: Criminal justice system, Rajasthan ordinance, media trials
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Madhav Mallya, Research Associate, School of Law
Mallya, Madhav (2018). Anthea Roberts: Is international law international?
Oxford University Press, New York, 2017, xxvi + 406 pp, Hardcover, ISBN:
9780190696412. Indian Journal of International Law, 58517–520
Abstract: Anthea Roberts’ monograph Is International Law International? Is an
analysis of the approaches of both practitioners and academics towards public
international law in the five permanent member states of the United Nations
Security Council? She studies the historical, geopolitical, educational and socio
-economic factors which have played a role not only in the evolution of
research and study of public international law in these states, but also in
defining the vastly different and often parochial understanding of the subject by
international law practitioners and academics in these states.
Keyword: Anthea Roberts
Prachi Tyagi, Assistant Professor, School of Law
Tyagi, Prachi (2018). Independence and Impartiality of arbitrators in
International commercial arbitration. NSS Journal, 1, 274.
Abstract: The research paper starts with introduction reciting the various of
ADR and importance of commercial dispute. Later paper describes the concept
of impartiality and independence and how they overlap each other.
Independence and impartiality are qualities that must be maintained throughout
the arbitral process. The secrecy of the tribunal’s deliberations is the
fundamental to the arbitral process, explaining in detail that how impartiality is
needed to ensure that justice is done, and independence is needed to ensure that
justice is seen to be done. Then paper talks about the need and importance of an
importance of an independent and impartial. Arbitration is grounded on truth;
therefore, the arbitrator’s respect of professional ethics acquires great
importance for the respectfulness of the arbitral institution itself as an
alternative dispute resolution mechanism. In the same way, judicial
independence is acknowledged to be a key element for preserving the integrity,
credibility and legitimacy of international courts and tribunals. Thus, it has been
argued that an arbitrator, besides his intellectual and professional credentials,
must comply with the moral integrity of a judge. The independence and
impartiality of the judges is an intrinsic feature of the judicial process. The
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extended part of the sub-topic talks about why and when does arbitrators turns
partial and dependent. Then paper discusses about how arbitration is a tool to
promote and aid international trade and investment by providing a neutral,
independent and impartial method of resolving international commercial
disputes through effective and reasonably predictable procedures describing the
ethics and objectives of ICA. Next part of the paper defines the prerequisite
condition of impartiality and independence that are widely highlighted and
emphasized in the rules and codes of most arbitral institutions and formulating
agencies like UNCITRAL, ICC, ICSID and LCIA, AAA and IBA. The non-
exhaustive list which is provided by IBA guideline which consists of red list
(waivable and non- waivable), orange list and green list. The four- point test
provided by ICSID comprising of following factors: proximity, Intensity,
Dependence and Materiality, Paper also talks about the disclosure requirement
wherein all rules impose duty on a prospective arbitrator to disclose all facts
and circumstances which might give rise to suspicions and doubts as to his
impartiality and independence, even if not in his own eyes. Lastly some
tentative conclusions and suggestions in relation to the differing concepts of
party autonomy and concept of impartiality and independence.
Keyword: International Commercial Arbitration, Impartiality, Independence,
Ethics, Arbitrator, Disclosure, UNCITRAL
Tyagi, Prachi (2018). Why is my Hijab Your problem: A Jurisprudential
Analysis of women behind the Veil?. NLUA Law Review, 3(1).
Abstract: The socio-cultural development of any society is judged on the basis
of the status of the women in the society. Better the say and rights of women in
the society, better is the socio-cultural status of the society. The same can be
easily said if we look at status of any women in any section of the society. And
depending upon the disparity of the women rights and status, the cultures are
valued and discussed upon. Hijab is one such aspect of the women which has
attracted the attention of two different extreme opinions as far as the status of
women in society is concerned. One major set the Islamic countries which
associate hijab with modesty of female and claim it as a practice the keep
women at bay from the lustful eyes of the society. It has been made
synonymous to the integrity of the female. And the fact that the society as
changed, does not mean that the female should shed away to meet the western
concepts of liberty. On the other hand, there is a viewpoint which symbolizes
hijab with torment and shacking of women through such customary practices
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and a way to put women at bay from the wave of development. The argument
that the status of the women in society cannot be prejudiced to subside the
interest and growth of the women in the society is heavily relied upon. The fact
that the world is divided on these lines and few countries like France and
Belgium have put a ban on hijab and some Islamic countries are adamant and
strictly following the concept of hijab. Both set of viewpoints have been the
reason of the implementation of their set of laws. Amidst all the, real and
crucial point of discussion is eclipsed i.e. the choice of women, her will and
whether the concept of hijab is against the development of women. The status
of women, with or without hijab cannot be decided by the extreme notion of the
concept of hijab. This article is jurisprudential analysis of this debate on the
analogies of Jeremy Bentham who supports the concept of hedonism and
Rebert Nozick who values the ideals of individual liberty.
Keyword: Socio-cultural development, Women rights, Development of
women
Dr. Sudha Jha Pathak, Assistant professor, School of Law
Pathak, Sudha Jha (2019). The Forgotten Women of the revolutionary
nationalist movement. Understanding Nationalism and Patriotism. The
contemporary world (pp. 138-147). NLU Delhi: Centre for human right and
Subaltern Studies.
Abstract: The nationalist movement in India was one with multiple layers,
dimensions, and diverse perspectives incorporating various sections of people
with varied aims, objectives and visions. Revolutionary nationalism was one of
the divergent strands that went into shaping the national movement. The
strongholds of the movement were in Bengal, Maharashtra and Punjab where a
network of revolutionary societies existed who often collaborated with each other
for the cause of the independence of the country.
Pathak, Sudha Jha (2018). Women in ecological movements: an overview.
Women Link, 24(3), 45-52.
Abstract: There exist a dynamic and close relationship between the human and
physical environment
Keyword: Ecological Movements
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Dr. Suman Luhach, Assistant Professor, School of Law
Luhach, Suman (2018). Facilitating Online Collaborative Writing Tutorials for
Tertiary Learners Through Learning Management System. Modern approaches
to English Language, Literature, & Feminism Studies (pp. 47). Chandigarh.
Abstract: Importance of writing skills at tertiary level: Effective writing skills
are internal to master communication skills in any language learning. Besides
listening, speaking and reading skills, writing is an essential tool for learning a
discipline. This includes learning to write effectively and also knowing the
process of writing which involves writing, editing, rewriting and proofreading.
Despite the importance of writing skills, it has been increasingly observed that
students hate writing well is a major cognitive challenge. Sunder (2013)
emphasises that when student finish their school education and enter college
they should be well versed in basic language skills like speaking and writing as
the aim of college education is to inculcate analytical and critical thinking
among students which need a command over essential language skills. Jacobs
and Karliner (1977) share, “A substantial proportion of freshmen who come to
our schools are ‘literate’ in that they can write reasonably correct English but
are handicapped by their inability to demonstrate thought onpaper”(p.489).
Keyword: LMS
Dr. V.C Vivekanandan, Professor, School of Law
Vivekanandan, V. C. (2019). Right to Access for Visually Impaired Persons as
a Human Right Obligation: an overview of Marrakesh Treaty. In V K Ahuja
(Ed.), Human Right Contemporary Issues (Festschrift in the Honor of Professor
Upendra Baxi) (pp. 178-192). Eastern Book Company.
Abstract: The evolution of intellectual property (IP) regime in the last two
centuries as a regime complex has created a new dichotomy of “knows-know-
nots” slicing through the “haves and have-nots” of the traditional property
system. The Knowledge creation and dissemination in print and digital platform
is key to the knowledge economy of the world. Such “access” is encapsulated by
a regime complex of “copyright” controlled by holders and assignees and is
based on return on investments. Though, there is a window of free access by
instruments of “fair dealing” or “fair use”, the legal quagmire makes it a difficult
terrain for those who do not have the economic means. In such milieu, a
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considerable section of world population falling in the category of visually
impaired is more vulnerable.
Keyword: Human rights, inclusion in society, knowledge economy
Dr. Vikas Kathuria, Assistant Professor, School of Law
Kathuria, Vikas (2018). Restrictive Conditions in patent law and the
competition law interface. Journal of World Intellectual Property, 21, 256-268.
Abstract: This article examines a little discussed section of the New Zealand
Patents Act 1953 (s 66), which dealt with “restrictive conditions.” It discusses
the repeal of the section and the resultant situation in New Zealand, particularly
vis-à-vis the competition law regime and its exemptions for certain behavior
regarding intellectual property. A comparison of the patent-law and competition
-law interface is made with respect to the UK, Australia, and India. The article
finds that New Zealand's statutory regime potentially offer the most patent
friendly environment when it comes to a patentee's ability to extend his/her
reach beyond the scope of patent rights. At the same time, policy- and
lawmakers have largely ignored the relationship between patent law and
competition law, which may prove to be counterproductive against New
Zealand's desire to be innovative and-connected to this-unfavorable for New
Zealand consumers.
Keyword: Competition, Patents, Restrictive conditions, New Zealand
Kathuria, Vikas (2018). User review portability: Why and how?. Computer
Law and Security Review, 34(6), 1291-1299.
Abstract: User reviews of products on the e-commerce platforms are a critical
determinant of intraplatform competition, as a large number of consumers base
their purchasing choices on the related reviews written by other users. The
network effects between the number of reviews and new users give a
sustainable competitive advantage to incumbent platforms. While business
literature has recognized the commercial value of the user reviews, legal
scholarship has paid little attention to levelling the playing field between
incumbents and new e-commerce platforms by exploring the portability of user
reviews. This paper bridges this gap. We explore the possibility of porting user
reviews through two legal mechanisms—first, traditional Intellectual Property
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law; second, the new Right to Data Portability (RtDP) as enshrined in the
GDPR. After recognizing the limitations of these mechanisms in enabling the
portability of reviews, we suggest that pure data aggregators, such as Personal
Information Management Services (PIMS), are best placed to make user
reviews available to multiple platforms.
Keyword: Management Services (PIMS), e-commerce
Kathuria, Vikas (2018). Validity of Non-Disclosure Agreements in SEP
Licensing. European Intellectual Property Review, 40(6), 1-19.
Abstract: Requiring a Non-Disclosure Agreements (NDAs) is a common
business practice used to safeguard the commercial interests of a licensor and a
licensee in intellectual property licensing matters. The recent litigation
involving Standard Essential Patents (SEP) has, however, raised doubts over
the practice of patentees requiring NDAs before licensing SEPs to putative
licensees. It has been argued that the inclusion of royalty rates in NDAs leads to
discriminatory pricing of technology — a violation of the commitment to
licence under fair, reasonable and non-discriminatory (FRAND) terms. That is,
licensees cannot know if they receive non-discriminatory terms, if they cannot
compare their licences due to NDAs. This article examines this issue from both
theoretical and practical perspectives, and concludes that the inclusion of
royalty rates in NDAs may be justified in view of the technological and
commercial realities involved in SEP licensing.
Keyword: SEPs, Non-Disclosure Agreements (NDAs), FRAND, Royalty,
Discrimination, Competition Commission of India
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Dr. Abhinav Chaturvedi, Assistant Professor, Center for Innovation &
Entrepreneurship
Chaturvedi, Abhinav (2019). Choosing the Right Institution of Higher
Education Could Really Be Tough!. New Age Admissions Strategies in Business
Schools-Edited Book (pp. 150-169).
Abstract: The chapter is a sneak peek into the possible complexity there can be
in decision making, especially if it is about selecting one’s future path in life. The
authors attempt by way of exploratory research method of case study to bring out
the process model idiosyncrasies in decision making while selecting an institute
of higher education. The chapter also provides insight into the possible factors
which can play an important role in the entire process of choice making. The
authors try to reason that such decision-making processes are highly complex,
and this complexity increases as the information circle of a student grow. Also,
the student makes a satisficing choice and not that of an optimal one
Keyword: Higher Education
Chaturvedi, Abhinav (2017). The Concept of “Jugaad”: Evidence from
Innovations at the Bottom of the Pyramid in India. 3rd Academy of Business and
Emerging Markets (ABEM) Conference Proceedings (pp. 122- 132).
Abstract: Jugaad is always referred as a creative improvisation, quick fix, and
has many other positive and negative connotations attached to it. Many different
views are given in respect to what is Jugaad, many links it with frugality, some
say it’s the mind set which is all about flexibility, making breakthrough
innovation; many regard it as makeshift arrangements and so on. How the
ingenious individual is able to come up with ideas, which are nowadays on the
verge of being patented in countries like India, is an interesting phenomenon.
However, the interesting bit is how Jugaad originated and what is its concept is
an areas important to explore. In this paper we try to with the help of content
analysis of common examples try to bring out the concept. The result of the study
based on qualitative methodology help to explain Jugaad as a confluence of the
constructs: (1) bounded situation, (2) Cognitive style, and (3) Improvised
Artefact.
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Chaturvedi, Abhinav (2019). Women Entrepreneurs & Work Life Balance:
Intrinsic Challenges of Family Support, Stress and Health. Jour of Adv Research
in Dynamical & Control Systems, 11(4), 1951-1958.
Abstract: Today, India is witnessing the emergence of a considerable number of
women entrepreneurs, which has broken the myth that entrepreneurship is a male
prerogative. But, despite changing socio-cultural environment and paradigm shift
in terms of better access to higher education, employment, empowerment, and
economic independence to women; female entrepreneurship in India is still at its
nascent stage, while there is potential for many more. The reasons: The hurdles
and hindrances that women face to walk the extra mile and their struggles that
hamper the entry and growth of women entrepreneurs need to be explored. While
women experience the same phases of entrepreneurship as do men: Setting up a
venture, its sustainability and growth; unlike their male counterparts, they face
several intrinsic barriers that first block their entrance as businesspeople, and
later their survival and growth as women entrepreneur. The main obstacle in their
journey of entrepreneurship is to maintain balance between Work and family life:
Family support, stress, and health. The purpose of this research is to understand
these challenges. This exploratory report is the result of a survey that has been
conducted on a sample size of 150 businesswomen. A Quantitative research
method is being used for gathering the data. Findings of the study indicate that
the significance value is 0.0001 (i.e., p = .0001), which is less than 0.05. And,
therefore, there is a statistically significant difference between the variables. (p
value is .007) i.e. P>0.05. Therefore, we accept the null hypothesis and can say
that, for women entrepreneurs, to maintain Work and life balance is stressful and
that it impacts their entrepreneurial success. The research in this field is limited
and the Area needs to be explored.
Keyword: Women, Work and Family Life, Entrepreneur
Ajay Batra, Director, Center for Innovation & Entrepreneurship (CIE)
Batra, Ajay (2017). StartUps and Beyond - Building Enduring Organizations.
AuthorsUpFront.
Abstract: In a Volatile and hyper-competitive world, startup as well as existing
enterprises, are continually challenged to remain relevant. They face questions
such as: How do we create effective products, services and business models?
Which approaches are the best for attracting and retaining talent? How do we
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achieve profitable growth? What are the best ways to compete on innovation?
Whether you are an entrepreneur, corporate executive or growth consultant,
Strartups and Beyond: Building Enduring Organizations provides practical
answers to these challenges and more. At the heart of the book is the Maturity
Model for Building Enduring Organizations- a framework that offers a 5- stage
roadmap towards building organizations that are successful, ethical and resilient.
A global first, this holistic framework has been curated with best practices from
Entrepreneurship, Design Thinking, Operations and Human Capital Management
from over 100 organizations worldwide. Startups and Beyond: Building
Enduring Organizations Brings to the fore new mindset and tools for founders
and business leaders. With detailed practices and examples, it serves as a
comprehensive field guide for launching viable startups, and for creating lasting
enterprises.
Keyword: StartUps and Beyond, Building Enduring
Dr. Vinod Shastri, Associate Professor & Head Academics, Center for
Innovation & Entrepreneurship
Shastri, Vinod (2019). Restless to Relentless: Flower cycling® Success. Start-
Up Marketing Strategies in India, Emerald Publishing (pp. 163–183).
Abstract: Every year, tons of flower waste from religious places is dumped into
India’s holiest river Ganges, polluting it to virtual death. Pesticides and
insecticides used in growing these flowers mix with the water, affecting millions
of lives through water-borne diseases. Most others may just lament these facts,
Ankit Agarwal and Karan Rastogi, childhood friends from Kanpur, used them as
inspiration to innovate. Two years of relentless experimentation led to a brilliant
idea; that of recycling the flower waste. They founded Help Us Green® in 2014
to convert the waste into biofertilizers and lifestyle products. Widely appreciated
and heavily awarded now, success has not come easy for this well-educated duo.
Help Us Green® processes hundreds of kilos of flower waste, creating
employment for hundreds of underprivileged women. An entirely bootstrapped
project with no carbon footprint, the venture hopes to revive the Ganges through
Flower cycling®. Currently at 8.5 tons per day and at the tipping point of scaling,
Help Us Green® hopes to process over 50 tons of flower waste per day by 2020.
Apart from the environmental impact, Help Us Green® has achieved huge
societal impact, employing over a thousand women who did not previously have
formal employment. What also makes the social entrepreneurs stand apart is their
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entrepreneurial market savviness. They have positioned their products not at the
sympathy market but at the high-end premium market. Their products sell under
the name ‘Phool’. Help Us Green® has set its eyes firmly on spreading
operations across 2,000 kilometers along the Ganges and creating over 25,000
jobs for women.
Keyword: Marketing Strategies, Startup
Shastri, Vinod (2019). A Study of India’s Unemployment Conundrum. 13th
RSEP International Conference on Business, Economics & Finance, Kadir Has
University, 11-13 June 2019 (pp. 126-142). Istanbul, Turkey.
Abstract: On May 23, 2019, the day of completion of this Paper, India
completed the world's largest ever democratic election process to re-elect the
incumbent National Democratic Alliance (NDA) government under the Prime
Minister ship of Narendra Modi, frequently referred to as 'NaMo' in popular
media. Narendra Modi's victory is so resounding, that it is being touted as a 'Tsu
NaMo', washing away in its wake, even the grand old party of India, the Indian
National Congress, and many other dynastic political parties. However, brutally
criticized for failing to live up to its promise of creating millions of jobs during
its first term, the NDA 2.0 government will have its task cut out, when it comes
to tackling India's severe unemployment crisis. A story titled 'Blueprint 2.0:
Here's what the new government's first big decisions are likely to be' in
Economic Times, clearly identified the possibility of substantive work on job
creation. The story also identified three large scale job-creating sectors, that are
likely to see radical reforms. While it might be fine to bring reforms in such
specific sectors in the short and medium terms to facilitate quick large-scale
employment,
Keyword: Unemployment, Entrepreneurship development, Job creation, Job
creators
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Dr. Deepika Dhingra, Assistant Professor, School of Management
Dhingra, Deepika (2019). Demystifying Machine Learning & its impact on
Financial services. Advances in Economics and business Management, 6(6), 557-
561.
Abstract: Machine Learning (ML) is nothing but an application of Artificial
Intelligence. It provides systems with an ability to automatically learn and
improve with experience without being explicitly machine learning and artificial
intelligence are often used interchangeably, but the former is an advanced subset
of the latter just because something is artificially intelligent doesn’t necessarily
mean it can learn. Machine learning teaching can adjust to a variety of situations
and learn as it goes forward it mainly focuses on the development of computer
programs that can access data and use it to learn for themselves. Giants like
Amazon, Google and many more tech platforms are using it to its utmost
potential. Be it finding out specification for a product to suit current market to
investing in global market, it can help us in making decisions with high level of
accuracy. Machine learning and artificial intelligence are set to alter the banking
industry owing to the accessibility to accessibility to enormous expanses of data
and more reasonable computing power. Prime banks and financial services are
positioning Artificial intelligence technology, with machine learning to
restructure their procedures, optimize portfolios, provide legal advices and
sanction loans amongst other things, financial services providers have begun to
use vast amounts of data build frameworks for better decision making tailor
services, and improve risk management. The success of machine learning project
more on structuring infrastructure collecting suitable datasets and applying the
right algorithms. ML technology has exhibited an important role in many stages
of the financial ecosystem, from approving loans and carrying out credit scores,
managing assets and evaluating risk to distinguishing fake legal documents from
genuine documents. According to the Mckinsey global institute this could
generate value of more than $250 billion banking industry. This research article
way in machine learning is altering the financial services landscape. It also
discusses the various applications of machine learning in finance specifically in
India.
Keyword: Demystifying, Machine Learning
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Dr. Khanindra Ch Das, Assistant Professor, School of Management
Das, Khanindra Ch (2018). India in the International Production Network:
The Role of Outward FDI. Globalization of Technology (pp. 47-62).
Abstract: Outward FDI from India has expanded manifold since liberalization
of policy regime. The phenomenon is expected to improve India’s involvement
in international production network. The paper examines the role of outward
FDI in the manufacturing sector on production-network-related trade over the
period 2008-2014. The impact of bilateral outward FDI on export of parts and
components to FDI-host countries is investigated using within-transformed
fixed effects, and fixed-effects Poisson quasi-maximum likelihood method. The
results reveal a positive and significant impact of outward FDI on production-
network-related trade, suggesting to crucial role that manufacturing outward
FDI can play in expanding the outreach of Indian manufacturing in the global
economy. Towards this end. Promotion of outward FDI in the manufacturing
sector needs to be accompanied by policy coordination with respect to inward
FDI and trade facilitation in order to integrate manufacturing facilities in India
with production hubs in the international production network for deriving
benefits of global value chains.
Keyword: Parts and components. Production network. Global Value chain.
Outward FDI. India
Dr. Mayank Dhaundiyal, Assistant Professor, School of Management
Dhaundiyal, Mayank (2016). Investigating the effects of shyness and sociability
on customer impulse buying tendencies: The moderating effect of age and
gender. International Journal of Retail and Distribution Management, 44(9), 923
-939.
Abstract: Purpose – The effect of personality traits on impulse purchase is not
well understood. The purpose of this paper is to investigate how two such traits,
shyness and sociability, impact on impulse buying tendency. Understanding
drivers of impulse purchase, a significant source of retail sales, is important to
succeed in the challenging environment that store-based retailers face. Design/
methodology/approach – A customer intercept approach was taken to collect 194
responses from two locations in a busy city centre shopping street in Dublin,
Ireland, and the hypotheses were tested using covariance-based structural
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equation modelling. Findings – Sociability has a significant positive effect on
both affective and cognitive impulse buying tendencies whereas shyness has a
positive effect on cognitive impulse buying tendencies only. Age was found to be
a significant moderator of these effects. Research limitations/implications – This
study uses an in vivo street-intercept approach and hence the results may differ
for other data collection approaches. The lack of discriminant validity of the sub-
scales for impulse buying tendencies has implications for future research.
Practical implications – The findings suggest that retailers should factor
customers’ psychological traits into their decision making. Individuals with high
levels of sociability and shyness are prone to buying on impulse but in different
ways. Younger people are more likely to exhibit these behaviours. Originality/
value – This paper meets a need for research on how customers’ traits affect their
impulse purchase tendencies and offers retailers advice on how to attract and
serve customers with these traits.
Keyword: Age, Impulse buying tendency, Sociability, Shyness Paper type
Dr. Milind Shrikant Padalkar, Professor, School of Management
Padalkar, Milind (2016). Six decades of project management research:
Thematic trends and future opportunities. International Journal of Project
Management, 34(7), 1305-1321.
Abstract: Project management as a discipline possesses a rich body of literature
characterized by early determinism and later expansion to broader contexts aided
by paradigmatic, thematic, and methodological diversity. The dynamic nature of
research entails many parallel streams of enquiry under differing perspectives
without convergence to parsimonious theories. We argue that an integrated view
of project management research in terms of its thematic evolution and trends is
necessary for an understanding of future directions. Our study fills this gap by
tracing the evolution of themes in project management research, trends, and
future opportunities through a systematic review of literature. We find the
research to be dominated by empirical and deterministic perspectives while non-
deterministic research enquiry remains weak and sporadic. We contend that
stronger focus on non-deterministic perspective and a methodological
convergence is necessary for the research to meaningfully advance towards
theory building and discuss potential avenues for further research.
Keyword: Project Management, Research trends, Literature review
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Dr. Nakul Parameswar, Assistant Professor, School of Management
Parameswar, Nakul (2018). Post termination interaction in international joint
ventures (IJV). Foresight, 21(2), 200-215.
Abstract: Purpose-This paper aims to explore dynamics of post termination
interaction between international joint venture (IJV) partners and empirically
examines IJV level and dyad level factors that influence the choice of post IJV
termination interaction as supplier, complement or competitor. Design/
methodology/approach – In-depth literature review is undertaken to identify
IJV and dyad level that could influence the choice of post termination
interaction between terminated IJV partners. Hypotheses are empirically
validated using multinomial logistic regression on data collected on terminated
IJV head quartered in India. Findings – The results denote that the choice of
post-IJV termination interaction between IJV partners as supplier, complement
or competitor is influenced by interdependence, bargaining power, foreign
partner’s purpose of IJV, complementarity and type of IJV termination.
Research limitations/implications – This paper explores an under researched
area in extant IJV literature that could be taken up for study by academicians.
The paper upholds and strengthens the dynamic capabilities view of strategic
management in IJV context. Practical implications – This paper examines a
practice adopted by businesses in emerging markets and determines important
factors that influence the choice of interaction post IJV termination between
partners. Practitioners will be encouraged to understand and plan post
termination dynamics with their terminated IJV partner. Originality/value – The
paper undertakes examination of a practical business phenomena, i.e.
interaction post termination between terminated IJV partners.
Keyword: Interdependence, International joint ventures
Parameswar, Nakul (2018). Purpose of international joint venture and
interaction post termination. Journal for Global Business Advancement, 11(6),
687-705.
Abstract: International joint ventures (IJV) are a prominent mode to enter and
exploit a new market and have attracted several researchers to explore various
phases and actions undertaken in IJV. Few studies in the literature discuss the
effect of IJV experience on parent firms interaction post termination of their
IJV. This study attempts to explore the effect of purpose of IJV for domestic
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and foreign firms - resource seeking, capital seeking, market seeking and
strategic asset seeking on the choice of interaction post IJV termination as
supplier-buyer, complement or competitor. Empirical analysis is conducted on
data of 180 terminated two-partner IJVs headquartered in India during 2000-
2016 time period using multinomial logistics regression (MLR). Results
suggest that both the domestic firm's and the foreign firm's purpose of IJV
influences the choice of interaction post IJV termination.
Keyword: IJV, International joint venture, International joint venture
termination, Purpose of IJV, Resource seeking, Market seeking, Capital
seeking, Strategic asset seeking, MLR, Multinomial logistics regression,
interaction post termination, Joint venture, Motives
Parameswar, Nakul (2019). Global marketplace strategy and choice of
interaction after termination of international joint venture. Strategic Change, 28
(3), 177-184.
Abstract: Foreign partner's global marketplace strategy significantly influences
the choice of interaction after international joint venture (IJV) termination as
supplier–buyer, complement, or competitor between terminated IJV partners. The
domestic partner in IJV enables foreign firms to pursue its global marketplace
strategy—transnational, multidomestic, global, or international. On IJV
termination, foreign partner's perceived value creation from IJV shall be rendered
void and is required to either look for a new domestic firm to collaborate or form
an interaction after IJV termination with IJV's domestic partner. This study
examines the role of foreign firm's global marketplace strategy on the choice of
interaction after IJV termination as supplier–buyer, complement, or competitor
using data on terminated two partner IJV headquartered in India.
Keyword: Global strategy, International joint venture
Dr. Nidhi Sinha, Assistant Professor, School of Management
Sinha, Nidhi (2018). Academic Social Networks for Knowledge Sharing: An
Explanatory Study. In E. Rama Reddy (Ed.), International Conference on
Convergence: Content, Media and Technology (pp. 128-135).
Abstract: Social media has gathered enough attention in recent years. Every
other person now owns an individual account on various social media networks.
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The social media may be casual like Facebook, Twitter, etc., as well as specific
academic social networks (ASNs) focused on the needs of the academic
community, like Academia.edu, ResearchGate, etc. Purpose of this research is
to highlight the growth of social networks over the past few years, the need and
importance of knowledge sharing over academic social networks. This study
also examines various similar as well as comparative features of these academic
social networks. Given the exponential rise over the documents as well as
information shared over these networks, it is essential to highlight the issues
and challenges concerning the use of academic social networks regarding
information dissemination. This study gives a detailed study of importance,
features as well as issues related to the knowledge sharing using various
academic social networks.
Keyword: Academic Social Networks, Social Media, Knowledge Sharing,
Social Media Convergence
Dr. Nilanjan Banik, Professor, School of Management
Banik, Nilanjan (2018). Political Economy of Resources and Infrastructure in
India. In Rama P. Kanngo, Chris Rowley & Anurag N. Banerjee (Eds.),
Changing the Indian Economy: Renewal, Reform and Revival (pp. 1-19).
Abstract: This chapter examines the political dimensions of strategic resource
challenges in India. Natural resource endowments (i.e. land, oil, gas and
minerals) can serve as potent drivers of development. For better or worse
energy, transport, mineral and land markets in India are shaped by national
interest and do not behave as traditional goods markets, especially because of
the lack of well-defined property rights. Therefore, while markets are an
essential part of any response to tighter resource supplies, governments also
play a key role as a preeminent domain in this incomplete market setup. This
has led to challenges concerning how local resource users are subject to
exclusion and dispossession in the national interest of economic growth. For
example, there has been an increase in the number of legal contests regarding
land, water and mining rights which has increased inequality and local
insecurities. Thus a ‘paradox of plenty’ exists in resource-rich countries such as
India, where recent history has demonstrated that extractive endowments can
disappoint if they are not well-managed.
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This chapter discusses the problems related to land acquisition and water
resources and the possible solutions.
Keyword: Indian Economy, Renewal, Reform and Revival, Problems with
land acquisition, Resources and Infrastructure
Banik, Nilanjan (2017). Demand for Household Sanitation in India using NFHS
-3 data. Empirical Economics, 1-21.
Abstract: India has the highest number of people defecating in the open, and the
Indian Government is trying to eradicate by constructing toilets for its citizens.
This paper is about whether the government is likely to succeed in its cleanliness
drive mission by a supply-side policy. We examine the household preference and
other the factors leading to open defecation in India. We examine preference for
having a toilet in the household over the preference of other household durable
goods. Our results suggest toilets get a lower preference ranked 12, out of 21
different types of consumer durables we investigate. The results also indicate a
strong case for imparting education and public awareness, especially, among the
female cohort. We find the odds of having toilets in a household with an
educated woman (18 years of schooling) is 3.1 times more than a household with
illiterate or preschool educated women. Among other factors households living in
urban areas are 19 times more likely to have toilets in comparison with their rural
counterparts.
Keyword: Household sanitation, India · Toilets · Preference ranking
Banik, Nilanjan (2017). Demystifying the role of barriers at and behind borders
in India: A Case of Indian Pharmaceutical Products. Barriers to Medicine Trade,
1-21.
Abstract: With the significant reduction of tariff barriers to international trade,
other forms of barriers, such as barriers at the border and behind borders are
considered as the major challenge to the growth of global trade. These barriers
are often high in developing countries as compared to developed ones and arise
due to divergent regulatory frameworks, inefficient customs procedures,
cumbersome export import procedures, administrative hassles, hidden taxes,
congestion fee and sub-optimal trade infrastructure. Against this backdrop, this
Discussion Paper attempts to understand the role of different types of barriers in
the import pharmaceutical products in India. It analyses the effect of three main
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barriers: tariff barriers; non-tariff barriers; and barriers at the border with a
particular focus on understanding the role of procedural and regulatory
impediments.
Keyword: Demystifying, tariff barriers, non-tariff barriers
Banik, Nilanjan (2017). Farmer suicides in India and the Weather God.
Procedia Computer Science, 122, 10-16.
Abstract: This paper examines the reasons for farmer suicides in India. Inability
to get the right price, crop failures, and insurmountable debt are the factors that
may drive the farmers to take this extreme step. A key factor for farmers being
unable to get market prices is inefficient agriculture supply chain management.
We find that the reasons for inefficient supply chain management include lack of
reforms in the Agricultural Produce Market Committee (APMC) Act, low
bargaining power due to small farm size, and lack of warehousing facilities. Crop
failures happen because of poor irrigation facilities. Considering agricultural
output and rainfall data from four different states in India we find evidence in
favor of association between the cyclical component of agricultural output and
rainfall data. Understanding this linkage is important from the perspective of
formulating demand management policies (read, intervention by the government
and central bank).
Keyword: Agriculture output, Beveridge-Nelson Decomposition, APMC Act,
Rainfall
Banik, Nilanjan (2017). Farmer suicides in India and Weather God. Asia-Pacific
Research and Training Network on Trade Working, 161, 10-16.
Abstract: This paper examines the reasons for farmer suicides in India. Inability
to get the right price, crop failures, and insurmountable debt are the factors that
may drive the farmers to take this extreme step. A key factor for farmers being
unable to get market prices is inefficient agriculture supply chain management.
We find that the reasons for inefficient supply chain management include lack of
reforms in the Agricultural Produce Market Committee (APMC) Act, low
bargaining power due to small farm size, and lack of warehousing facilities. Crop
failures happen because of poor irrigation facilities. Considering agricultural
output and rainfall data from four different states in India we find evidence in
favor of association between the cyclical component of agricultural output and
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rainfall data. Understanding this linkage is important from the perspective of
formulating demand management policies (read, intervention by the government
and central bank).
Keyword: Farmer suicides, Agriculture output, Beveridge-Nelson
Decomposition, APMC Act, Rainfall
Banik, Nilanjan (2018). Are Loan Waivers a Panacea for Rural Distress?.
Economic & Political Weekly, 53(47), 14-16.
Abstract: Small and marginal farmers are not the real beneficiaries of loan
waivers. In the year following loan waivers, small farmers lose out on three
counts: lower access to formal loans, falling agricultural revenue because of
higher informal loan costs, and falling agricultural productivity. Instead, supply
-side interventions could make a real difference in farmers’ lives as a long-term
alternative to loan waivers.
Keyword: Loan Waivers
Banik, Nilanjan (2018). Farmer distress: Analysis of Interventions addressing
farmer distress in Andhra Pradesh, Cost-Benefit Analysis. Andhra Pradesh
Priorities, Copenhagen Consensus Center, 1-35.
Abstract: During the fiscal year 2016-2017, the contribution of the agricultural
and related sectors was 14% of Gross Domestic Product (GDP), even though
58% of the population are dependent on the sectors for their livelihood. India
has around 260 million people living in poverty and 80% of them live in the
countryside. The median annual wage for a farmer in India is INR 18,850
(including the implied value of the food they consume). This is equivalent to
two months’ minimum wage in Mumbai – the commercial capital of India. It is
therefore unsurprising that there was a spike in farmer protests during 2017-18
in various parts of the country.
Keyword: Gross Domestic Product (GDP), FARMER DISTRESS
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Banik, Nilanjan (2018). Is Loan Waiver a Panacea for Rural Distress. ARTNeT
- Policy brief, 56, 1-9.
Abstract: On the eve of elections in India, farm loan waiver became one of the
major election promises. Recently, the winning Janata Dal party in the state of
Karnataka, India fulfilled its pre-poll promise and announced a farm loan
waiver of up to $4.79 billion (with a cap of $2,817 per family). Starting last
year, Karnataka is the fifth state (after Uttar Pradesh, Punjab, Maharashtra, and
Andhra Pradesh) to have implemented farm loan waiver programmes. Another
poll-bound state Rajasthan also announced farm loan waivers, while in
Chhattishgarh, the main opposition party Indian National Congress promised
farm loan waivers if voted to power. As a result of farm loan waivers, there is a
likelihood that during fiscal 2018-2019, India’s fiscal deficit may widen to
$16.17 billion. During 2016-17, the total amount of debt relief programmes
announced by governments of Uttar Pradesh, Maharashtra and Punjab
amounted to $10.85 billion or 0.5% of India’s GDP in 2016-17 (Kundu, 2017).
If all the states in India were to waive 50% of their farm debt, it would cost 1%
of India’s GDP (in 2016-17 prices).
Banik, Nilanjan (2018). Why Free Trade is Good for Your Health. IFT, 5-21.
Abstract: Much of the public discourse about free trade focuses on the
supposed dangers it poses to the environment, to vulnerable communities
around the world and to our health. IFT has teamed up with the Geneva
Network to produce this short pamphlet explaining the role of open trade in
improving public health. We expand on the following arguments: The
economic dividend of free trade - higher individual and average incomes - helps
improve health in three main ways: Higher standards of living mean people can
afford things that increase health and keep disease at bay, like more nutritious
diets and safer heating methods. A more open economy means a bigger public
sector, which translates to more public health spending on things like clean
water and vaccination programmes Growth in incomes creates larger markets
and larger potential rewards for investors, meaning an increase in money spent
on health-related R&D. Knowledge spillovers: When trade happens more
freely, it is easier to disseminate domestic know-how to other countries, and
medical technologies like antibiotics developed in richer countries can reach the
rest of the world more quickly. Intellectual property rights: Often thought to be
an obstacle to the broad dissemination of new medicines, stronger IP
protections are actually associated with speedier in-country launches of new
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drugs. Patents are simply not relevant to the majority of healthcare issues faced
by people in low- and middle-income countries. Food standards: WTO rules
ensure that the UK will always be able to guarantee that imported food sold in
Britain meets local health and safety standards, even under a free trade
agreement. Nowadays many food standards are actually being employed in
place of tariffs as a way of protecting domestic producers, without any genuine
public health justification.
Keyword: Trade and Health, Economic growth, Knowledge Spillovers,
Intellectual property rights
Dr. Palakh Jain, Assistant Professor, School of Management
Jain, Palakh (2019). Effects of information sources for new customers and
suppliers on the immediate innovation output of firms. European Journal of
Innovation Management, 22(4), 1460-1060.
Abstract: The purpose of this paper is to propose a typology of the information
sources for new customers or suppliers on the basis of their existing relational
linkage with the acquiring firm and to further explore whether various types of
information sources for new customers and suppliers have any differential effect
on a firm’s immediate innovation output. The research sample was taken from
the data collected by WB enterprise surveys (2005). The WB enterprise survey is
considerably comprehensive for firm-level data. Relevant questions for the study
were extracted from the survey. Simultaneously, EFA, CFA and SEM using
AMOS 6.0 was run for the analysis. The findings confirm that sources for a new
customer and supplier with a strong relational aspect have a significant positive
effect on a firm’s innovation output in the immediately following period.
Research limitations/implications – The research acknowledges the need to
measure the effect of new supplier/customer on innovation depending on the type
of information sources separately for product and process innovation as one of
the major limitations. This research can help managers obtain information of
holistic and critical nature to incorporate in decision making for improving firm
performance in innovation. Customers and suppliers are well established external
sources of innovation ideas and information. But to what extant new customers
or suppliers may be effective resources for innovation may depend largely on the
sources through which they themselves are acquired by a firm, which is relatively
unexplored. This study addresses the gap is the first of its kind to explore the role
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of the sources of information for new customer/supplier on a firm’s innovation
output in the immediately following period.
Keyword: Firms’ performance, Innovation output, Shared relational identity
Jain, Palakh (2019). MPLADS: To Scrap or To Re-Invent?. Journal of
Governance & Public Policy, 9(1), 118-124.
Abstract: Member of Parliament Local Area Development Scheme (MPLADS)
is a centrally sponsored program funded by the Government of India. It was
initiated to empower the Members of Parliament (MPs) to develop their
respective constituencies based on the local needs. This paper attempts to
understand MPLADS and suggest that there is a need to reformulate the scheme
to help MPs do their developmental duties more efficiently. The paper is divided
into five sections. The first section attempts to throw light on the basics of
MPLADS as a scheme – objective of the programme and working of MPLADS.
The second section discusses the past trends about the utilization of funds. The
third section discusses the opinions in support of scrapping this scheme. The
fourth section focuses on the need to have structured underlying research in an
attempt to reinvent the program. The concluding section suggests that there is a
need for a more structured approach towards collecting evidence at the level of
the constituency.
Keyword: Constituency, MPLADS, Development, Scheme
Dr. Pankaj Kumar Medhi, Assistant Professor, School of Management
Medhi, Pankaj Kumar (2019). Effects of information sources for new
customers and suppliers on the immediate innovation output of firms. European
Journal of Innovation Management, 22(4), 1460-1060.
Abstract: The purpose of this paper is to propose a typology of the information
sources for new customers or suppliers on the basis of their existing relational
linkage with the acquiring firm and to further explore whether various types of
information sources for new customers and suppliers have any differential effect
on a firm’s immediate innovation output. The research sample was taken from
the data collected by WB enterprise surveys (2005). The WB enterprise survey is
considerably comprehensive for firm-level data. Relevant questions for the study
were extracted from the survey. Simultaneously, EFA, CFA and SEM using
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AMOS 6.0 was run for the analysis. The findings confirm that sources for a new
customer and supplier with a strong relational aspect have a significant positive
effect on a firm’s innovation output in the immediately following period.
Research limitations/implications – The research acknowledges the need to
measure the effect of new supplier/customer on innovation depending on the type
of information sources separately for product and process innovation as one of
the major limitations. This research can help managers obtain information of
holistic and critical nature to incorporate in decision making for improving firm
performance in innovation. Customers and suppliers are well established external
sources of innovation ideas and information. But to what extant new customers
or suppliers may be effective resources for innovation may depend largely on the
sources through which they themselves are acquired by a firm, which is relatively
unexplored. This study addresses the gap is the first of its kind to explore the role
of the sources of information for new customer/supplier on a firm’s innovation
output in the immediately following period.
Keyword: Firms’ performance, Innovation output, Shared relational identity
Parakash Chander, Assistant Professor, School of Management
Chander, Parakash (2018). A political economy analysis of the Southeast
Asian Haze. Singapore Economic Review, 63(5), 105-110.
Abstract: This paper studies the political economy of the Southeast Asian haze
and discusses the obstacles that, unless overcome, can prevent a permanent and
effective solution to the transboundary pollution problem, which originates in
Indonesia. Following a cost-benefit analysis of the problem, the paper takes
note of the weaknesses in Indonesia’s governance structure, which make it
difficult to enforce national policies aimed at curbing the haze problem. The
paper also puts forward a number of suggestions for strengthening the current
policy regime for tackling the problem.
Keyword: Transboundary haze, Cost-benefit analysis, Eco-label, Consumer
boycotts
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Chander, Parakash (2018). The core of a strategic game. B.E.Journal of
Theoretical Economics, 1-18.
Abstract: In this paper, I introduce and study the -core of a general strategic
game. I first show that the -core of an arbitrary strategic game is smaller than
the conventional - and - cores. I then consider the partition function form of
a general strategic game and show that a prominent class of partition function
games admit nonempty -cores. Finally, I show that each -core payoff vector
(a cooperative solution) can be supported as an equilibrium outcome of an
intuitive non-cooperative game and the grand coalition is the unique
equilibrium outcome if and only if the -core is non-empty.
Keyword: Strategic game, Core, Partition function, Repeated game, Nash
program
Dr. Sangeeta Shukla, Associate Professor, School of Management
Shukla, Sangeeta (2017). Communicative sensitivity in palliative care: a case
on the “Happiness Angels” of Rajbala Foundation. Emerald Emerging Markets
Case Studies, 7(2), 1-20.
Abstract: The subject areas are business communication, human resource
management and health care. The case was designed for use in a first-year MBA-
level course in business communication but would serve well in a course for
executives or for advanced undergraduates. It might also be assigned in general
management courses to evoke discussion on communication skills required in
sensitive and critical situations; human resource courses; and course on health
care.
Palliative care is a specialized medical care focussing on improving the quality
of life of patients suffering from life-threatening illnesses. It addresses symptom
management and psychosocial and spiritual concerns of the patient and its
caregivers. With the intent to alleviate the sufferings of terminally ill patients,
Rajbala Foundation, a non-government organization (NGO), works at the
psychosocial and spiritual levels. While training their volunteers in effective
palliative care communication, it often encounters challenges such as socio-
cultural variations, organizational challenges, appropriate verbal and nonverbal
communication, etc. This teaching case focuses on the communication
challenges faced by the volunteers of Rajbala Foundation. It would lead to a
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broader discussion on communicating empathically during critical situations.
The case has a focus on NGOs, and non-profit organizations, public sector
management, health-care management and human resources management. There
is significant literature on communication skills for medical practitioners in
palliative care. As an increasing number of NGOs step in to provide the second
level of care to critically ill patients in non-physical domains, there is a need to
understand the role of effective communication for such care providers. This
case deals with non-medical care providers in palliative care; the issues of
communication they face as they interact with patients; and the skills they
require to address the emotional and spiritual needs of patients and their families.
The aim of this case is to raise awareness of the complexities involved in the
communication process during an emotional and sensitive interaction. It aims to
encourage volunteers involved in palliative care to reflect on good
communication practices when communicating with patients and family
members. After reading this case, the students should be able to discuss the
complexities involved in the communication process when communicating in
situations with high emotional involvement; understand the core elements of
emotional interactions for effective practice; and emphasize the need for the
development of communication skills within palliative care.
Keywords: Human resource management, Employee communications, Health
and safety.
Shukla, Sangeeta (2018). Public Apologies in India - Semantics, Sentiment
and Emotion. 9th Global WordNet Conference (pp. 1-17).
Abstract: This paper reports a pilot study related to public apologies in India,
with reference to certain keywords found in them. The study is of importance as
the choice of lexical items holds importance which goes beyond the surface
meaning of the words. The analysis of the lexical items has been done using
interlinked digital lexical resources which, in future, can lend this study to
computational tasks related to opinion mining, sentiment analysis and
document classification. The study attempts an in-depth psycholinguistic
analysis of whether the apology conveys a sincerity of intent or is it a mere
ritualistic exercise to control and repair damage.
Keyword: SentiWordNet, WordNet-Affect, corporate apologies, corporate
communication
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Tarun Sharma, BBA Student, School of Management
Sharma, Tarun (2019). Demystifying Machine Learning & its impact on
Financial services. Advances in Economics and business Management, 6(6), 557-
561.
Abstract: Machine Learning (ML) is nothing but an application of Artificial
Intelligence. It provides systems with an ability to automatically learn and
improve with experience without being explicitly machine learning and artificial
intelligence are often used interchangeably, but the former is an advanced subset
of the latter just because something is artificially intelligent doesn’t necessarily
mean it can learn. Machine learning teaching can adjust to a variety of situations
and learn as it goes forward it mainly focuses on the development of computer
programs that can access data and use it to learn for themselves. Giants like
Amazon, Google and many more tech platforms are using it to its utmost
potential. Be it finding out specification for a product to suit current market to
investing in global market, it can help us in making decisions with high level of
accuracy. Machine learning and artificial intelligence are set to alter the banking
industry owing to the accessibility to accessibility to enormous expanses of data
and more reasonable computing power. Prime banks and financial services are
positioning Artificial intelligence technology, with machine learning to
restructure their procedures, optimize portfolios, provide legal advices and
sanction loans amongst other things, financial services providers have begun to
use vast amounts of data build frameworks for better decision making tailor
services, and improve risk management. The success of machine learning project
more on structuring infrastructure collecting suitable datasets and applying the
right algorithms. ML technology has exhibited an important role in many stages
of the financial ecosystem, from approving loans and carrying out credit scores,
managing assets and evaluating risk to distinguishing fake legal documents from
genuine documents. According to the Mckinsey global institute this could
generate value of more than $250 billion banking industry. This research article
way in machine learning is altering the financial services landscape. It also
discusses the various applications of machine learning in finance specifically in
India.
Keyword: Demystifying, Machine Learning
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Dr. Teena Bharti, Assistant Professor, School of Management
Bharti, Teena (2019). Emotional intelligence strategies to achieve subjective
career success: implications for learning and development in knowledge
industry. Development and Learning in Organizations: An International Journal.
doi.org/10.1108/DLO-10-2019-0229
Abstract: Purpose This paper exemplifies the role of emotional intelligence (EI)
achieving subjective career success in the global knowledge industry. Design/
methodology/approach Discussion based on the literature, report, and industry
experts. Findings EI can be used as an effective tool to influence the attributes of
subjective career success such as job satisfaction, new skill acquisition, work-life
balance, healthy relationship with peers and pride in work. Employees feel
empowered and successful in their careers if their social ability, emotionality,
self-control, well-being and, expressed behavior are properly taken care of by
their organizations. Originality/value This paper introduces a new factor
expressed behavior in EI model and suggests various strategies to enhance EI and
achieve subjective career success in the knowledge industry.
Keywords: Emotional Intelligence, Sociability, Emotionality, Expressed
Behaviour, subjective Career Success
Dr. Y. Medury, Professor, School of Management
Medury, Y. (2016). An analysis of India's need of capacity building for E-
governance. Prabandhan: Indian Journal of Management, 9(6), 47-59.
Abstract: Capacity building of municipal functionaries is recognized as an
approach to make strong municipal work practices and to improve the
achievements of municipalities in India. The main purpose of this paper was to
describe the social, economic, and educational status of the people and evaluate
their readiness for the e- governance practices and capacity building
requirements for the community. The paper attempted to throw light on the need
and approaches of the community development by building their capacity. The
findings of this research are based on the perceptions of personal observation of
the ground realities. The study is an attempt to point that the capacity building
initiative is a must for the people in almost all the states local municipalities.
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People in India need to be empowered by adequate training and education. This
paper is based on a randomly selected population scattered geographically in six
Northern Indian states. In every state, 150questioners were distributed; there
were a total of 900 questioners distributed among the population, out of which
only 710 questioners with a 78.9% response rate were received back. The
analysis presents the picture of the demographic status of the citizens. So, at the
end, it is concluded that the Central and State government should put extra
efforts to find out and tackle the growing needs of municipalities in order to have
a greater impact of e-governance.
Keyword: E-governance, Local governance
Medury, Y. (2016). Status of user-centric E-governance practices in North India.
Prabandhan: Indian Journal of Management, 9(4), 18-29.
Abstract: Information and communication technologies (leT) suggest to the
government new possibilities for providing citizens better and more efficient
services according to their convenience. In the modem age of online services, the
citizens may expect better services from the government. The user centric
approaches of the government services motivate the user to utilize and avoid
criticism. The user needs to be placed at the center of development, and
provisions need to be in place for electronic public services. Simultaneously, it is
required to check the impact of the new services on customers. User satisfaction
may have a definite decisive influence on large-scale adoption and use of E-
government services. This paper attempted to find out the extent of use and
impact of e-governance on the welfare services of the government in six Indian
states- Chhattisgarh, Haryana, Himachal Pradesh, Punjab, and Uttarakhand.
Keyword: ICT based services, E-Governance
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Dr. Nithin Kalorth, Assistant Professor, Times School of Media
Kalorth, Nithin (2018). Ruling the Men’s Den: Crime, Outrage, and Indian
Women Gang Leaders. In George S. Larke‐Wals (Ed.) A Companion to the
Gangster Film (pp. 413-429).
Abstract: The Hindi film industry, popularly known as Bollywood, is
predominantly a male‐dominated industry. However, evidence of gradual social
transformation and the industry’s consequent need to develop new cinema has
provided some innovative screen space for female artists. Until recently, Hindi
cinema has tended to portray women with seductive yet graceful beauty, and
many female characters personify endurance and patience as well as a high
degree of emotional control. Historically, Indian cinema does not have its fair
share of movies that are women oriented (Gokulsing and Dissanayake, 1998)
and in part this is because Indian literature does not supply enough female
protagonists or antagonists to be adapted to cinema. Influenced by this bleak
legacy, screenwriters have also avoided women‐centered narratives. Characters
written for women in the early days of Indian cinema were either too hazy to
make any social or even commercial impact or were restricted to portrayals as
“attractive companions,” which resulted in the woman’s frailty and behavioral
patterns being presented in sharp contrast to the depiction of masculine virility
(Chakravorty, 2002). However, there have been some modest attempts to create
female characters that include some of the social attributes of female liberation
through the introduction of rebellious characters in social dramas and crime
films (Datta, 2000). This chapter analyzes the role of female gangsters and
villains in Indian films by discussing the construction of these characters, the
social reasons for the origin of such roles, and the development of the role of
female gangsters through a comparative analysis against Indian male gangsters.
Keyword: Hindi film industry
Kalorth, Nithin (2017). Questioning and answering on Quora: Science
communication in the age of User Generated Content Experiences. Rajasthan
Science Congress 2017.
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Abstract: The equations of human and mass communication drastically changed
post social media. The principles, pattern, verification and validation of
communication gone through various paradigm shifts. Apart from Facebook,
Twitter etc. there are various specific social media websites which makes
changes in the way we communication and reach others. Quora is such a social
media platform in which people can post questions and find answers. Users can
also contribute to the questions. Quora became popular when it redefined the
concept of online public forum which was largely depended on anonymous users.
This paper is focusing on science communication Question and Answer section
in Quora. The study aimed to understand how a user generated content platform
can contribute to the field of science and science communication. This study will
also address to the larger ongoing debate on credibility of social media. The
paper is designed to study opinion of Quora users and analyse selected contents
on Quora.
Keyword: Quora, UGC (user generated content), Social media
Kalorth, Nithin (2018). Online media, Digital Public Sphere and the Voice of
Women. National Seminar on Trending- Disciplinary Convergence in Media
Studies.
Abstract: Online media has been revitalizing the communication sphere all
over the world. The unique features of the online digital communication media
like interactivity, de-centralised architecture, costless reproduction and sharing,
hyper textuality etc. have stirred discourses on the possibilities of this novel
medium in the strengthening of democratic communication. Here this paper
intends to portray the online media platforms in the context of digital public
sphere. A public sphere can be seen as a space distinct from both state and the
market. Public sphere is an integral outcome of the democratic discourses
where freedom of expression, inclusivity and access to all sections of the people
is crucial and perennial. The traditional media systems like the print and
broadcast media are highly commercialized and functions according to the
whims and fancies of the rulers and business barons. They provide a little space
for the deliberative democratic discourses due to their commitment towards the
state and the market. The new online digital media offers immense possibilities
in the formation and sustenance of a digital public sphere. It is formed through
discussion about a domain of common interest. Also, it represents a new space
of discussion for many who had previously been excluded. The last aspect is
that ideas presented in the public sphere are considered on the basis of their
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merits, disregarding social status. German philosopher Jurgen Habermas
emphasizes the universal access from all classes of people as key to the public
sphere. Here this paper places digital public sphere as a prospective space for
discourses relating to women. The digital media offers a heteropian space
where women can voice their voice. The paper includes Habermasian and post-
habermasian conceptions regarding public sphere and counter publics. This
paper tries to focus on the role of new online digital media especially social
media as a medium in protecting and promoting women’s rights in India.
Keyword: New media, Public Sphere, Social Media, Habermas, Counter
Publics
Kalorth, Nithin (2018). Possibilities and Problems in Digital Ethnography:
Mapping language, structure and disclosures in Sub-Groups. International
Conference on Digitality and Communication.
Abstract: Varis (2016) noted that online environments studied cannot be taken
as self-explanatory contexts but need to be investigated for locally specific
meanings and appropriations. This is to extend the views of Dijck (2013) that
the shape of any platform does not determine the way in which people will use
it for their communicative purposes, the design of the site will influence
interactions. Defaults in digital environments, are not just technical but also
ideological manoeuv rings which is formed by algorithms, protocols, and
defaults profoundly shape the cultural experiences of people active on social
media platforms
Keyword: Social media, Language, Digital ethnography
Kalorth, Nithin (2018). Anatomy of Fake News: On (Mis) information and
Belief in the Age of Social Media. Journal of Content, Community &
Communication, 14(8), 9-14.
Abstract: Within the context of technological and digital communication boom
in India, the concern of fake news and misinformation plays a muted role in
democratic and social welfare process; the current research focuses on
narratives of social media users from Achrol and Chandwa ji villages (Jaipur,
Rajasthan). This paper tries to understand the logic of social media engagement
and participation of users within the framework of understanding cultural turn
in fake news and belief among the users. The paper tries to argue that the fake
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information disseminated in form of news becomes more complicated when it
passes through filters of anonymity and identity misinterpretation in social
media. The logic of information consumption and dissemination should be
studied with the changing communication patterns and business models of
modem India. The current research is part of social research project carried over
after 2016 Indian banknote demonetization to understand the derivations of fake
news and its evolution in daily life of Indian users.
Keyword: Fake news, Social Media, Narrative Analysis
Kalorth, Nithin (2018). Mass Communication Research: A Question of
Method. Amity Journal of Media & Communication Studies, 8(1), 5-6.
Abstract: The application of methods in mass communication research is a
topic of debate for more than five decades. Mass communication has its give
and take from social science and pure science research methods and practices.
For the same reason the methods involved in mass communication research is
also adapted from the foresaid. The debate in appropriate methods in mass
communication research methods circles with qualitative and quantitative.
Notwithstanding, the importance of both methods, studies in mass
communication often end up in perplexed outcome. In a boarder sense, studies
in mass communication and media focuses on theory building and exploration.
Keyword: Mass Communication Research, Communication
Kalorth, Nithin (2018). Photojournalism for Environmental Activism:
Analysing the Works of Madhuraj. Journal of Media and Communication, 1(2),
24-34.
Abstract: This study critically analyses the works of prominent photographer
Madhuraj from the Indian state of Kerala. His news photographs on Plachimada
and endosulfan victims led to widespread social and political movements. This
paper performs a descriptive analysis of the works of Madhuraj to understand
their roles in impelling and sustaining social movements.
Keyword: Photojournalism, Activism, environment, Political movements
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Kalorth, Nithin (2018). Social Media Experiences and Narratives Formation of
Opinions in the Age of Post -Truth. International Journal of Creative Research
Thoughts (IJCRT), 6(1).
Abstract: The emotion and opinion become the pillars of facts and figures in
post – truth political condition. The rise of social media and the phenomenon of
"my opinion is worth more than the facts" are fundamentals of post-truth.
Everybody can publish their opinion and furnish that as facts. The role and
structure of public opinion and leaders need to be revisited in this context. In
the wake of digitalization and digitization, the social media users become part
of big data through which power controllers reshape the policies and
democratic values. This paper focuses on narratives of eighteen social media
users from Achrol village (Jaipur, Rajasthan) and tries to understand the logic
of social media engagement and participation. The paper tries to argue that the
big data is subjective and what it quantifies is not closer to objective truth
through the narratives of individual datum (users). The paper builds its
argument on “opportunities to improve on the truth” (Keyes, 2004) where the
anonymity and identity catastrophe in social media helps to disseminate the
opinions as facts.
Keyword: Post – truth, Social media, Rural India, Public opinion, Human
rights, Digital life
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Jamil Ahmed, Assistant Librarian, Learning Resource Centre
Ahmed, Jamil (2017). Managing an E-Library and the Quester with Open
Source Software. Knowledge Generation, Discovery and Networking.
Abstract: Reading eBooks and collecting them is almost common for an
individual but the issue arise when a peculiar item is retrieved from its e
collections. Not only recalling but even managing eBook is a major challenge,
especially when user quest is fetched by multiple reading devices at a time. This
paper explains the use of open source software ‘Calibre’ for managing and
searching of eBooks. The article helps to get an idea of creating and studying
open books with the help of Calibre. It also assist user to read open books on any
eReader platform.
Keyword: E-Library, Open Source Software, Quester,
Ahmed, Jamil (2018). Managing Electronic Resources through Open Source
Software Calibre. ETTLIS 2018 Conference Proceedings (pp. 26-30).
Abstract: The new trend of e-collections with new technologies has given
readers ample alternatives to experience the novel ways of reading it. Where an
ease for users has been produced with e-resources; the challenge arises for
managing e-collections has puzzled for libraries. It becomes more complicated
when libraries need to develop E-Resource Management Systems (ERMS) not
only for carrying off e-collections throughout their life cycle but also for aiding
collection-development decision making. Therefore, to provide a resolution to
libraries based on cost-effectiveness for managing e-collections and an easy
way for users to utilize it, this paper introduces an open source software Calibre
as an ERMS. Caliber helps to acquire, create, manage and also assists the user
to read open books on any eReader.
Keyword: eBooks, eReaders, eCollections, eLibrary, Calibre, DRM, ERMS
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Priyanka C. Bhatt, Professional Assistant, Learning Resource Centre
Bhatt, Priyanka C. (2019). Mobile Application Development: A comprehensive
and systematic literature review. Proceedings of the International Conference on
Industrial Engineering and Operations Management (pp. 2354-2360). Pilsen,
Czech Republic.
Abstract: In the present age of e-commerce, mobile penetration has risen to a
significant level and can be seen as it grows exponentially in the past decade.
The mobile application has opened up a new sense of customer service. With an
increase of these applications, researchers have inclined their interest towards
development and identify various issues linked to it. This study focuses on
accumulating a vast academic literature in a time frame of the last ten years. A
comprehensive and systematic literature review was done in the emerging area of
mobile application development. After the process of reviewing the extensive
literature from the biggest database ‘Scopus’, a total of 26 relevant journal
papers were considered for the review after multiple steps of filtrations. This
paper gives the scope and the direction in the field of mobile development and
helps the organization to have a vast knowledge regarding the same. The
findings of this study provide valuable insights and future recommendations in
this developing field.
Keywords: Mobile Application, Collaborative System, Online Services,
Android Operating System, framework.
Dr. Sanjay Kataria, Librarian, Learning Resource Centre
Kataria, Sanjay. (Ed.). (2018). Proceedings of IEEE 5th International
Symposium: Emerging Trends and Technologies in Libraries and Information
Service. IEEE.
Abstract: Emerging Trends and Technologies in Libraries and Information
Services has become an inevitable topic of discussion among the Library
professionals for the past several Years. The unprecedented developments in
the field of ICT and the rapid advancements in internet and telecommunication
technologies have kept this topic current and vibrant all the time. Persistent
advancements in internet technologies along with increasing awareness and
improvements of the social networks, digital content delivery, virtual access
and mobile technologies are part of the development that captivate the new
digital eco system. Keeping these developments as the focal point ETTLIS has
once again proved its continued commitment to provide a platform for healthy
dialogue and discourse to harness the research impetus of the information
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scientists. The symposium on Emerging Trends and Technologies in Libraries
and Information Services is a celebration and showcasing of the deliberations of
the information scientists whose contributions pave way for innovative service
delivery in information sectors. This volume is a profusion of such intellectual
discourse carefully selected and presented to the Information Science fraternity
to have a glimpse of what is in store for them in their profession. The eighty
papers which adorn this book reflect the meticulous research most of the
authors have carried out to reflect their finding for the entire community to
benefit.
In the past Years Libraries and Information centres have transformed
themselves as portals of knowledge warehouses where people converge to share
information and depart with knowledge. Emerging Technologies have proved
yet again that its services which were only a dram of the past can be effectively
implemented in libraries so that the quest for knowledge can be easily
augmented. The future of information ecosystem and the digital Iandscape,
especially the production, organization and dissemination of information and
the practise and techniques used to achieve the desired results, need constant
reminder and rekindling of such skills. The cornucopia of ideas presented in
this book is divided into seven broad sections for quick access and easy reading.
The papers capture the essence of the emerging technologies in all its different
dimension and disseminate the results in a more authentic fashion. Emerging
new semantic web technologies, New data Models, Cloud Computing, Mobile
Computing, Web Analytic Tools, Knowledge Management Tools and the
emergence of Alternative Metrics to analyse the impact of knowledge
dissemination are dealt in detail in these seven sections of intellectual discourse.
The binding vine of the entire gamut of this collection is the emerging trends
and technologies which work for the betterment of the society.
ETTLIS as a brand is committed towards bringing together various role players
in the information eco-system. This collection of research output is the result of
such persistent support to the discussions on Emerging Trends in Libraries and
Information Services. ETTLIS, as always, believe that survival in this digital
ecosystem depends mainly in networking and exchange of ideas which in turn
provide ample scope for interoperability and exchange; the transition from
classis isolated fields of expertise to widespread knowledge exploration.
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This magnum opus is a result of one such network and collaboration where
hundreds of international and national experts have shared a common platform
at 5th IEEE-ETTLIS Symposium with their expertise and proficiency to
demonstrate their contribution towards Information Science.
Keyword: ETTLIS, Semantic web technologies, Emerging Trends, Technology
Kataria, Sanjay (2018). Academic Social Networks for Knowledge Sharing:
An Explanatory Study. In E. Rama Reddy (Ed.), International Conference on
Convergence: Content, Media and Technology (pp. 128-135).
Abstract: Social media has gathered enough attention in recent years. Every
other person now owns an individual account on various social media networks.
The social media may be casual like Facebook, Twitter, etc., as well as specific
academic social networks (ASNs) focused on the needs of the academic
community, like Academia.edu, ResearchGate, etc. Purpose of this research is
to highlight the growth of social networks over the past few years, the need and
importance of knowledge sharing over academic social networks. This study
also examines various similar as well as comparative features of these academic
social networks. Given the exponential rise over the documents as well as
information shared over these networks, it is essential to highlight the issues
and challenges concerning the use of academic social networks regarding
information dissemination. This study gives a detailed study of importance,
features as well as issues related to the knowledge sharing using various
academic social networks.
Keyword: Academic Social Networks, Social Media, Knowledge Sharing,
Social Media Convergence
Kataria, Sanjay (2018). Bibliometric analysis of the Proceedings of the
Emerging Trends and Technologies in Libraries and Information Services
(ETTLIS) A Study. ETTLIS 2018 Conference Proceedings (pp. 386-391).
Abstract: This paper provides a Bibliometric analysis of all the proceedings of
the Emerging trends and technologies in Libraries and Information Services
(ETTLIS). An analysis of 439 articles which are published in ETTLIS in the
four international symposiums in the year 2008, 2010, 2012 and 2015 was
carried out. The focus of the present study is to explore the category-wise
distribution of contributions, authorship patterns, and country-wise distribution
of contributions, keyword distribution etc.
Keyword: Bibliometric, ETTLIS, JIIT, JUIT, JEUT, JU,
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Kataria, Sanjay (2018). Emerging Trends in Mobile OPACs Options and
Solutions in Creating Mobile Optimized Library Catalogues. ETTLIS 2018
Conference Proceedings (pp. 1-6).
Abstract: The proliferation of mobile phones had made providing library
services through mobile phones a mandatory service in libraries. For any library
its catalogue is the primary focus of material search for its patrons. Hence
OPACs have been an integral part of libraries for a long time. With the mobile
revolution the provision of OPAC services for mobile phones have been in the
spotlight. Though many Integrated Library Systems (ILS) provide a separate
OPAC application for mobile users it always comes as a standalone product.
The common practice seems to be in linking the library OPAC to the mobile
websites which provide a number of problems in terms of display and results.
This paper is an attempt to look at the mobile OPAC standards and also the
factors which determine the optimum mobile OPACS are discussed display.
Various options and solutions to provide mobile OPAC has been discussed in
this article. A flowchart to determine how to go about deciding on the mobile
OPAC and the design considerations for mobile OPAC has also been provided.
Keyword: MOPAC, Mobile OPAC, OPAC, Online Public Access Catalogue,
Mobile Libraries,
Kataria, Sanjay (2018). Mapping the Research Collaboration between India
and USA during 2007-2016. ETTLIS 2018 Conference Proceedings (pp. 338-
343).
Abstract: The research collaboration trend between India and USA during
2007-2016 was evaluated on the basis of research publications indexed in
Scopus database. Research collaboration of 55607 documents has been
analyzed to see the international collaboration pattern between India and USA
during the period. The trend of research publications in collaboration was
assessed by analyzing; year-wise collaboration pattern, year-wise collaboration
with other countries, growth trend in collaboration with USA, types of
documents used for publishing research results, top institutes/universities which
are associated with research collaboration, top source titles based on the number
of publications, subject categories in research collaboration, etc. International
collaboration patterns institutions and countries have been studied in the paper.
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The results of the study showed that major areas of collaboration between India
and USA are in the field of medicines, followed by physics and astronomy,
biochemistry, genetics and molecular biology during 2007-2016.
Keyword: Research collaboration, scientometrics, educational collaboration,
India-USA collaboration, academic collaboration, mapping research
Kataria, Sanjay (2018). Satisfaction Levels of Media Professionals with their
Library Resources and Services. ETTLIS 2018 Conference Proceedings (pp.
272-279).
Abstract: This study explores the satisfaction level of the media professionals
with existing sources of information available in their media libraries. The
study was conducted using a self- structured questionnaire. 350 respondents
from fourteen different newspapers and news channels in Delhi-NCR were
chosen for the study. The study looks at the library staff support, and Library
services provided by the libraries, the level of satisfaction the users have in their
library and the availability of resources in these libraries.
Keyword: Media Professionals, Information Seeking Behaviour, Satisfaction
level, Information Sources, Mass Media, Newspapers journalists, Satisfaction
level of Media Professionals
Kataria, Sanjay (2018). Mobile Application for Library Services: Case with
Uniswa Library. International Journal of Information Library and Society, 6
(2), 33-42.
Abstract: The increasing advancements in the field of Information and
Communication Technology, especially in the Mobile communication system
has prompted many libraries to provide services which are predominantly
mobile based. While there is no doubt that there are a number of initiatives in
libraries to provide a number of mobile based services creating a complete
application for the library is still at its infant stage. While most of the activities
in the library can be integrated through the library this article looks at providing
a complete mobile application as a comprehensive single mobile. This article
looks at the basic approach needed to develop a mobile library application by
taking the case of the University of Swaziland Library as a Case Study.
Keyword: Information and Communication Technologies, Library Services, Mobile
Application, ICT
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Dr. Shiv Singh, Assistant Librarian, Learning Resource Centre
Singh, Shiv (2019). Biophysics Research Trends in India: Special Reference to
Indian Universities. International Journal of Innovative Technology and
Exploring Engineering (IJITEE), 9(1), 508-511.
Abstract: Biophysics is an effervescent scientific field where scientists from
many areas including chemistry, physics, zoology etc, use their skills to explore
and develop new tools for understanding how the life sciences work. The
objective of this paper is to present the preliminary results and to identify the
growth and development of Indian research in Biophysics. The data was
collected from Online Union Catalogue of Indian Universities. The catalogue has
4,36,967 Ph.D theses from 317 Indian universities. Indicators regarding the
distribution records of Biophysics thesis, as well as the subject, supervisor, top
University, state wise, keywords was analyzed with modular Scientometrics
information system. The data comprises of 569 theses out of which the majority
was from West Bengal followed by Karnataka.
Keywords: Biophysics, Indian Universities, Bibliometric, Physics, IndCat
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Au t h o r I n de x
Name of Author Page No.
Aafreen Collaco 240
Abhinav Chaturvedi 253,254
Abhishek Mishra 170
Adil Ashraf Bhukhari 170
Aditya Abburi 110
Ajay Batra 254
Akshaj Kulshreshtha 171
Akshay Kumar Goel 20
Alok Shukla 226,227,228
Amit Kumar Singh 172,173
Amit Singhal 110,111,112
Ankit Dhotrekar 241
Anurag Goswami 20,21,22,23,24,25
Apoorva Mishra 25,26
Arjun Kumar 113
Arnab Bose 173
Arpit Bhardwaj 27,28
Ashish Kumar (ECE) 114,115,116,117,118,119,120,121,122,123
Ashish Kumar (ME) 174,175
Ashish Saurabh 175
Ashita Allamraju 241,242
Ayan Khan 229
Ayan Ray 230
B. R. Dattu 28
Baij Nath Singh 176
Bhumika Nanda 243
Bishnu P Pal 230,231,232,233
Deepak Garg 29,30,31,32,33
Deepali Atheaya 177,178,179,180,181,182,183
Deepika Dhingra 257
Devottam Gaurav 33,34
Ganesh Naik Guguloth 183
Garima Tiwari 243,244,245
Gaurav Shukla 233,234
Gaurav Singal 34,35,36,37,38,39,40,41
Hiren Kumar Thakkar 42
Indrajeet Gupta 43
Jacob George Panickasseril 246
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Jai Prakash Gupta 44
Jamil Ahmed 280
Joy PAL 13,14
Krishna Thyagarajan 235,236
Kanad Kishore Biswas 44,45,46,47,48
Kanak Manjari 49
Karan Singh 49
Kaushik Saha 184,185
Khanindra Ch Das 258
Kuldeep Chaurasia 50,51
Madhav Mallya 247
Madhushi Verma 51,52,53
Madhusmita Mohanta 186
Manish Chauhan 187
Manjeet Kumar 123,124,125,126,127,128,129,130,131,132,133,134,135,136
Mayank Dhaundiyal 258
Mayank Swarnkar 54
Milind Padalkar 259
Mohammad Danish 188,189
Mohit Agarwal 55,56
Nakul Parameswar 260,261
Neelanchali Asija Bhalla 190,191
Nidhi Sinha 261
Nilanjan Banik 262,263,264,265,266
Nisha Ahuja 57
Nithin Kalorth 275,276,277,278,279
Palakh Jain 267,268
Pankaj Kumar Medhi 268
Parakash Chander 269,270
Pawan Mishra 192
Prabhakar Sathujoda 193,194,195
Prachi Tyagi 247,248
Pradyumn Mane 237
Pratik Narang 58
Priyanka C. Bhatt 281
Pushpendra Singh 137,138,139,140,141,142,143,144
R Shashidhara 59
Rachna Sable 60
Rahul Mukherjee 145
Rajinder Singh Chauhan 1,2,3,4,5
Rajita Shukla 60,61
Rajnesh Tyagi 196,197
Rama S Komaragiri 145,146,147,148,149,150,151,152,153,154,155,156,157,158,159
Ramana Ranganatham 160
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Rishav Singh 61,62
Rishi Dutt Sharma 62
Rohan Sharma 63
Rohit Kumar Kaliyar 63,64,65,66,67
Rupak Chakraborty 68,69
Sabyasachi Souguny 197
Sai Manoj Katakam 197,198,199
Samayveer Singh 70,71,72,73,74,75,76,77
Sangeeta Shukla 270,271
Sanjay Kataria 281,182,283,284,285
Sarika Goyal 167,168,169
Saurabh Jyoti Sarma 5,6,7,8,9,10
Seung-Hwa Chung 78
Shiv Singh 286
Shivam Yadav 199,200
Shivani Goel 79,80,81,82,83,84,85,86,87,88,89,91
Shubham Agarwal 200
Shyam Singh Rajput 91,92
Siva Skandha Sanagala 93
Sridhar Swaminathan 93,94,95,96
Srijna Singh 201,202
Srinivasa Reddy Bode 202
Suchi Kumari 96
Sudha Jha Pathak 249
Sudhir Chandra 161,162,163,164
Suman Luhach 250
Sumit Sharma 10,11
Suneet Kumar Gupta 97,98,99,100
Suneet Tuli 164,165,166
Susheel Reddy Aligireddy 202,203,204
Swarup K Panda 238,239
Tushar Bansal 15
Tanmay Bhowmik 101
Tanveer Ahmed 101,102
Tapas Badal 103
Tarun Sharma 272
Teena Bharti 273
Urvashi Arora 169
V C Vivekanandan 250
Vijay Kumar Bohat 104
Vikas Kathuria 251,252
Vimal Chauhan 204,205
Vinayak Gupta 11,12
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Vinayak Ranjan 205,206,207,208,209,210,211,212,213,214,215,216,217,218,219,220,221,222
Vinit Jakhetiya 104,105,106
Vinod Shastri 255,256
Vipul Kumar Mishra 107,108,109
Visalakshi Talakokula 16,17,18,19
Waseem Shameer 222
Y Medury 273,274
Yash Guptaa 223,224
Yash Jaiman 225
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