srkrec.edu.insrkrec.edu.in/R16_MTECH.pdf · 9 DEPARTMENT OF CIVIL ENGINEERING M.TECH (STRUCTURAL ENGINEERING) Scheme of Instruction and Examination (Regulation:R16) (with effect from

9

DEPARTMENT OF CIVIL ENGINEERING

M.TECH (STRUCTURAL ENGINEERING)

Scheme of Instruction and Examination

(Regulation:R16)

(with effect from 2016-2017 admitted batch onwards)

I – SEMESTER

Code No. Course title Credits Lecture

Hrs

Lab

Hrs

Total

Contact

Hrs/Week

Sessional

Marks

Exam

Marks

Total

Marks

M16 ST

1101 Theory of Elasticity 4 4 -- 4 30 70 100

M16 ST

1102

Advanced Reinforced

Concrete Design 4 4 -- 4 30 70 100

M16 ST

1103

Matrix methods of

Structural Analysis 4 4 -- 4 30 70 100

M16 ST

1104 Structural Dynamics 4 4 -- 4 30 70 100

#1 Elective-I 4 4 -- 4 30 70 100

#2 Elective-II 4 4 -- 4 30 70 100

M16 ST

1111

Computer applications

in Structural

Engineering

2 -- 3 3 50 50 100

M16 ST

1112 Design of Structures 2 -- 3 3 50 50 100

Total 28 24 6 30 280 520 800

Course Code Course

#1-Elective-I

M16 ST 1105 Advanced Foundation Engineering

M16 ST 1106 Wind Analysis and Design of Tall Structures

M16 ST 1107 Experimental Stress Analysis

#2-Elective-II

M16 ST 1108 Advanced Concrete Technology

M16 ST 1109 Bridge Engineering

M16 ST 1110 Optimization Techniques

10

Code: M16 ST 1101

THEORY OF ELASTICITY

Theory : 4 Periods Sessionals : 30

Exam : 3 Hrs. Ext. Marks : 70

Credits : 4

COURSE OBJECTIVES:

1. This subject is taught to impart knowledge on theory of elasticity.

COURSE OUTCOMES:

Upon completion of this course, the student will be able to

1. Analyze the stresses and strains for two dimensional and three dimensional elements.

2. Understand the equilibrium and compatibility conditions.

3. Solve the problems on Torsion for different shaped bars.

SYLLABUS

Plane Stress and Plane Strain: Components of stress, Strain, Hookes law, Stress and strain at a

point. Plane stress, Plane strain, Equations of equilibrium, Boundary conditions, Compatibility

equations stress foundation.

Two Dimensional Problems in Rectangular Coordinates: Solution by polynomials, Saint

Vanant‟s principle determination of displacements, Bending of cantilever loaded at the end,

Bending of a beam by uniform load.

Two Dimensional Problem in Polar Coordinates: General equations of equilibrium, Stress

function and equation of compatibility with zero body forces. Analysis of thick cylindrical shells

with symmetrical leading about the axis, Pure bending of curves bars, Strain components in polar

coordinates, Rotating disks.

Three Dimensional State of Stress: Differential equations of equilibrium – Boundary

conditions for compatibility – Displacements – Equations of equilibrium in terms of

displacements – Principle of superposition – Uniqueness of solution.

Torsion: Torsion of straight bars – St.-Venant solution – Stress function, Warp function –

Elliptic cross section – Membrane analogy torsion of bar of narrow rectangular cross section.

Analysis of Stress and Strain in Three Dimensions: Introduction – Principal stresses, -

Determination of principal stress – Stress invariants – Maximum sheering stress strain at point.

TEXT BOOK:

1. “Theory of Elasticity” by Timoshenko and Goodier, McGraw Hill Company.

REFERENCE BOOKS:

1. “Theory of Elasticity” by Sadhu Singh, Khanna publisher

2. “Applied Elasticity” by C.T. Wang., McGraw Hill Company

3. “Advanced Strength of Materials” by Denhortog, Dover publications

11

Code: M16 ST 1102

ADVANCED REINFORCED CONCRETE DESIGN



Credits : 4

COURSE OBJECTIVES:

The main objectives of this Course is

1. To Estimate the crack width and deflection with regard to the serviceability.

2. To analyze and design a grid floor system.

3. To analyze and design a flat slab system.

4. To analyze and design bunkers, silos and chimneys.

5. To analyze and design of concrete structures against fire resistance, according to ISO 834

standards

COURSE OUTCOMES:

After completion of course the students should be ability to

1. Estimate the crack width and deflection with regard to the serviceability.

2. Analyze and design a grid floor system.

3. Analyze and design a flat slab system.

4. Analyze and design bunkers, silos and chimneys.

5. Analyze and design of concrete structures against fire resistance, according to ISO 834

standards.

SYLLABUS

Deflection of Reinforced Concrete Beams and Slabs: Introduction, Short-term deflection of

beams and slabs, Deflection due to imposed loads, Short-term deflection of beams due to applied

loads, Calculation of deflection by IS 456, Deflection of continuous beams by IS 456, Deflection

of slabs.

Estimation of Crack width in Reinforced Concrete Members: Introduction, Factors affecting

crack width in beams, Mechanisms of flexural cracking, Calculation of crack width, Simple

empirical method, Estimation of crack width in beams by IS 456, Shrinkage and thermal

cracking.

Redistribution of Moments in Reinforced Concrete Beams: Introduction, Redistribution of

moments in fixed beam, Positions of points of contra flexures, Conditions for moment

redistribution, Final shape of redistributed bending moment diagram, Moment redistribution for

a two-span continuous beam, Advantages and disadvantages of moment redistribution,

Modification of clear distance between bars in beams (for limiting crack width) with

redistribution, Moment-curvature (M - ), Relation of reinforced concrete sections.

Approximation Analysis of Grid Floors: Introduction, Analysis of flat grid floors, Analysis of

rectangular grid floors by Timoshenko‟s plate theory. Analysis of grid by stiffness matrix

method, Analysis of grid floors by equating joint deflections, Comparison of methods of

analysis, Detailing of steel in flat grids.

12

Design of Flat Slabs: Introduction, Proportioning of Flat Slabs, Determination of Bending

moment and Shear Force, Direct Design method, Equivalent Frame method, Slab Reinforcement.

Bunkers and Silos : Introduction, Design of Rectangular Bunkers, Design of Tension member,

Design of Circular Bunker, Design of Silos.

Chimneys : Introduction, Design factors, Stresses due to Self Weight and Wind load, Stress in

horizontal reinforcement, Temperature Stresses, Combined effect of Self Weight, Wind load and

Temperature, Temperature stresses in Hoop(Horizontal) Reinforcement.

Design of Reinforced Concrete Members for Fire Resistance: Introduction, ISO 834 standard

heating conditions, Grading or classifications, Effect of high temperature on steel and concrete,

Effect of high temperatures on different types of structural members, Fire resistance by structural

detailing from tabulated data, Analytical determination of the ultimate bending moment,

Capacity of reinforced concrete beams under fire, Other considerations.

TEXT BOOK:

1. “Advanced Reinforced Concrete Design” by P.C. Varghese, Prentice Hall India Learning

Private Limited.

REFERENCE BOOKS:

1. “Reinforced Concrete” by Park &Paulay, Wiley publications.

2. “Reinforced Concrete Limit state Design” - P. Dayaratnam, Oxford & IBH publications.

13

Code: M16 ST 1103

MATRIX METHODS OF STRUCTURAL ANALYSIS



Credits : 4

COURSE OBJECTIVES:


1. To prepare the students to have a basic knowledge in the matrix methods such as flexible

matrix method and Stiffness matrix method.

2. To prepare the students to analyze the beams by matrix methods.

3. To prepare the students to analyze the Plane truss problems by matrix methods.

4. To prepare the students to analyze the Plane Frames by matrix methods.

COURSE OUTCOMES:

After completion of course students should be able to

1. Analyze various beams by the matrix methods at different loading conditions.

2. Analyze various Plane truss problems by the matrix methods.

3. Analyze Plane Frames by the matrix methods at different loading conditions.

SYLLABUS

Introduction to Matrix methods: Introduction, coordinate systems, displacement and force

transformation matrices, element and structure stiffness matrices, Element and structure

flexibility matrices, equivalent joint loads, stiffness and flexibility approaches.

Matrix methods for beams: Analysis of beams, fixed and continuous beams by flexibility

method. Analysis of beams, fixed and continuous beams by stiffness method.

Matrix methods for Plane truss problems: Analysis of 2-D trusses by flexibility method.

Analysis of 2-D trusses by stiffness method

Matrix methods for Plane Frames: Analysis of 2-D frames by Flexibility matrix methods.

Analysis of 2-D frames by Stiffness matrix methods.

TEXT BOOKS:

1. Analysis of Inderminate structures – C.K Wang, McGraw Hill Co.

2. Matrix Analysis of framed Structures-W Weaver& Gere, Van Nostrand Reinhold Company

3. G.S.Pandit, S.P.Gupta, “Matrix methods of Structural Analysis”, TataMcGraw Hill Co..

4. William Weaver, James M. Gere, “Matrix Analysis and Framed Structures”, D. Van

Nostrand Co., 1980.

REFERENCE BOOKS:

1. DevdasMenon,"Advanced StructuralAnalysis", Narosa Publishing House, 2009.

2. AsslamKassimali,"Matrix Analysis of Structures", Brooks/Cole Publishing Co., USA, 1999.

14

Code: M16 ST 1104

STRUCTURAL DYNAMICS



Credits : 4

COURSE OBJECTIVES:


1. To find the behavior of structures subjected to dynamic loads such as wind, earthquake and

blast loads.

2. To study the different Dynamic analysis procedures for calculating the response of structures.

COURSE OUTCOMES:


1. Solve the problems on Single degree of freedom.

2. Understand the difference between harmonic loading and impulse loading and the related

analysis procedures.

3. Evaluate the structural properties, mode shapes for different structures.

SYLLABUS

One Degree Systems: Undamped systems, Various forcing functions damped systems,

Response to pulsating force, Support motion.

Lumped Mass Multidegree System: Direct determination of natural frequencies, Characteristic

shapes, Stodola-Vianelle method, Modified Rayleigh-Ritz method, Lagrange‟s equation, Model

analysis of multi degree systems, Multistorey rigid frames subjected to lateral loads, Damping in

multi degree systems.

Structures with distributed mass and load, Single span beams, Normal modes of vibration,

Forced vibrations of beams, Beams with variable cross-section and mass.

Approximate design methods, Idealized system, Transformation factors, Dynamic reactions

response calculations, Design example (RC beam, Steel beam and RC slab), Approximate design

of multi degree systems.

Matrix Approach: Coordinates and lumped masses, Consistent mass matrix, Undamped force

vibration of a system with one degree freedom, Response of single degree freedom undamped

system, Viscous damped vibration of a single degree freedom system, Undamped vibration of

multi degree freedom system, Orthogonality of natural nodes, Normal coordinates.

TEXT BOOK:

1. “Structural Dynamics” by John M. Biggs, McGraw Hill Co.

REFERENCE BOOKS:

1. “Structural Analysis” by A. Ghali& A.M. Neville, CRC Press

2. Dynamics of Structures by Anil Kumar Chopra, Pearson Prentice Hall

15

Code: M16 ST 1105

ADVANCED FOUNDATION ENGINEERING



Credits : 4

COURSE OBJECTIVES:


1. To enable participants select the best foundation solutions for different types of Civil

Engineering problems

2. To develop deeper understanding of foundation analysis.

3. To develop understanding of choice of design parameters.

4. To learn about advanced topics of foundation design and analysis.

5. Participants will be equipped with abilities to evaluate bearing capacity and settlement failure

conditions for shallow and deep foundations.

COURSE OUTCOMES:


1. The design of shallow and deep foundations to carry ultimate loads.

2. Interpretation and selection of appropriate soil parameters from site investigation data.

3. Field monitoring in geotechnical design.

4. Select the most appropriate foundation solution for a given situation; derive appropriate soil

parameters.

5. Distinguish between different foundation types and their appropriate use.

6. Synthesize foundation performance measurements from a range of test data reported in the

literature.

SYLLABUS

Foundations, Types of shear failures in foundation soils, Types of foundations,

Introduction: Principles of Design of Design Loads, Basic Concepts of safe and allowable

bearing capacity. Shallow Foundations

Bearing Capacity Analysis: Bearing capacity theories – Terzaghi, Meyerhof, Skempton,

Hansen, Vesic and IS Methods, Bearing capacity evaluation from Standard Penetration test and

Plate load test.

Settlement Analysis: Uniform and Differential Settlements, Elastic and Consolidation

Settlements, Settlement analysis in cohesion less soils by Schemartmann and Hartman method,

Penetration tests; Permissible settlements as per IS 1904-1978, causes of settlement, settlement

Control.

Proportioning of footings: Isolated column footings, Strip, combined Footings and Strap

Footing. Raft Foundations: Bearing capacity of raft foundation, floating raft, Types of rafts,

Beam on Elastic foundation and Conventional methods of Design, determination of modulus of

subgrade reaction.

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Deep Foundations : Pile Foundations: Types, load capacity- dynamic formulae, static formula;

pile load tests- Vertical load test, lateral load test, Cyclic load test; settlement of piles and pile

groups, negative skin friction on single pile and pile groups; laterally loaded piles - Broom‟s

Analysis, IS Code method; Under reamed piles – Load capacity, design and construction.

Well Foundations: Types, Bearing Capacity of well foundations, Construction of pneumatic

caissons, Tilts and Shifts: precautions, Remedial measures; Lateral stability analysis by

Terzaghi‟s Method, Design aspects of Components of well foundation.

Foundations in Expansive Solis : Introduction, Identification of expansive soils, Swell potential

and swelling pressure, Active depth, Foundation Problems, Foundation practices in expansive

soils, Soil Replacement and „CNS‟ concepts.

Foundations of Transmission Line Towers: Introduction, Necessary information, Forces on tower

foundations, General design criteria, Choice and type of foundation, Design procedure.

TEXT BOOKS:

1. Analysis and Design of Substructures by Swami Saran, Oxford &IBH Publishing Co.

2. Foundation Engineering by P.C. Vargheese, Prentice Hall of India

3. Basic and Applied Soil Mechanics by GopalRanjan and A.S.R. Rao, New Age International

Publications

REFERENCE BOOKS:

1. Foundation Analysis and Design by J.E. Bowles, McGraw Hill Publishing Co.

2. Foundation Design by W.C. Teng, John Wiley, New York.

17

Code: M16 ST 1106

WIND ANALYSIS AND DESIGN OF TALL STRUCTURES



Credits : 4

COURSE OBJECTIVES:


1. This course is intended to teach the concept of tall structures.

2. Various methods to analyze the tall structure will be explained in the classes.

COURSE OUTCOME:


1. Know the types of tall buildings.

2. Analyze the plane frame systems by different methods.

3. Design the shear wall system and in filled frame systems.

4. Design the RC chimney and Bunkers and Silos.

SYLLABUS

Introduction: Basic wind speed, Design wind speed, Design wind pressure, offshore wind

velocity, wind pressures and forces in buildings/structures, External pressure coefficients for

various roofs, dynamic effects.

Lateral load Analysis of Multistory Building Frames: Analysis of Multistory Building Frames

for lateral loads, Cantilever method, Portal method and Factor method.

Design of Shear Wall: Introduction, Types of shear walls, Behaviour of cantilever wall with

rectangular cross-section, flange cantilever shear walls, Moment-Axial load interaction for shear

wall section, Interaction of shear walls and rigid joined frames, Shear walls with openings,

Coupled shear walls.

Design of Chimneys (RCC): Introduction, Wind pressure, Stress in chimney shaft due to self

weight and wind, Stress in horizontal reinforcement due to wind shear, Stresses due to

temperature difference. Design of RC chimney.

Bunkers and Silos: Introduction, Differences between bunker and silo, Design of square or

rectangular bunkers, Design of circular bunkers, Design of silos, Silos for storage of cement.

Multistory Building Frames: Analysis of multistory frames, Method of substitute

frames,Bending moments in beams and columns.

TEXT BOOKS:

1. “Limit State Design of Reinforced Concrete” by Ashok Kumar Jain & B.C.Punmia,Laxmi

Publications.

2. “Tall Chimneys” by Manohar, S.N., Tata McGraw-Hill Pub. Co.

3. “Design of Steel Structures”byN.Subramanian, Oxford Publications.

REFERENCE BOOKS:

1. “Reinforced Concrete Structures” by Park, R. &Paulay, T, Wiley publications

2. “Advanced Reinforced Concrete Design”,byN.KrishnaRaju, TataMcGraw Hill Co..

18

Code: M16 ST 1107

EXPERIMENTAL STRESS ANALYSIS



Credits : 4

COURSE OBJECTIVES:

1. The main objectives of this Course is to impart knowledge about the instruments and its

applications.

COURSE OUTCOMES:


1. Know the working principle of strain gauges.

2. Do the model analysis using different theorems.

3. Know the concepts of photo elasticity and its applications.

4. Analysis of Stress, strain, Stress- Strain relation and theories of failure

SYLLABUS

Electrical Resistance Strain Gauges: Principle of operation and requirements, Types and their

uses, Materials for strain gauge. Calibration and temperature compensation, cross sensitivity,

Rosette analysis, Wheatstone bridge and potentiometer circuits for static and dynamic strain

measurements, strain indicators.

Photoelasticity: Two dimensional photo elasticity, Concept of light – photoelastic effects, stress

optic law, Interpretation of fringe pattern, Compensation and separation techniques, Photo elastic

materials. Introduction to three dimensional photo elasticity.

Brittle Coating And MoireMethods :Introduction to Moire techniques, brittle coating methods

and holography.

TEXT BOOK:

1. “Experimental Stress Analysis”, Srinath, L.S., Raghava, M.R., Lingaiah, K., Garagesha, G.,

Pant B., and Ramachandra, K., , Tata McGraw-Hill, New Delhi, 1984.

REFERENCE BOOK:

1. Dally, J.W., and Riley, W.F., “Experimental Stress Analysis”, McGraw-Hill Inc

19

Code: M16 ST 1108

ADVANCED CONCRETE TECHNOLOGY



Credits : 4

COURSE OBJECTIVES:

1. This course mainly aims to develop the knowledge about properties of cement concrete and

importance of admixtures in concrete.

COURSE OUTCOMES:


1. Know the various materials in concrete and admixtures.

2. Do the Mix design by different methods.

3. Get a thorough knowledge of various types of cement, aggregates and properties of special

concrete.

4. Know the different procedures for testing concrete

SYLLABUS

Durability of concrete and concrete construction: Durability concept, pore structure and

transport processes, reinforcement corrosion, fire resistance, frost damage, sulphate attack, alkali

silica reaction, delayed ettringite formation, methods of providing durable concrete, short-term

tests to assess long-term behaviour.

Mix design: Review of methods and philosophies of IS, BS and ACI methods, mix design for

special purposes. Acceptance criteria for compressive strength of concrete.

Special concretes: Lightweight concrete, autoclaved aerated concrete, no-fines concrete,

lightweight aggregate concrete and foamed concrete, High strength concrete, refractory concrete,

high density and radiation-shielding concrete, polymer concrete, fibre-reinforced concrete,

mortars, renders, recycled concrete, Ferro Cement, Self Compacting Concrete.

Special processes and technology for particular types of structure: Sprayed concrete,

underwater concrete, grouts, grouting and grouted concrete, mass concrete, slip form

construction, pumped concrete, concrete for liquid retaining structures, vacuum process, concrete

coatings and surface treatments.

Test methods: Analysis of fresh concrete, Accelerated testing methods, Tests on hardened

concrete, Core cutting and testing, partially destructive testing, Non-destructive testing of

concrete structures

TEXT BOOKS:

1. Properties of Concrete, A.M.Neville, Longman 1995.

2. Concrete Technology Theory and Practice, M.S.Shetty, S.Chand& Company Ltd, New

Delhi.

REFERENCE BOOKS:

1. Concrete micro-structure, Properties and Materials, P.K.Mehta, J.M.Monteiro, Printice Hall

INC & McGraw hill, USA.

2. Concrete Technology by M.L.Gambhir, Tata McGraw Hill publications.

20

Code: M16 ST 1109

BRIDGE ENGINEERING



Credits : 4

COURSE OBJECTIVE:

1. This subject is taught to impart the knowledge in the analyses and design of concrete bridges.

COURSE OUTCOMES:


1. Understood the load distribution and IRC standards.

2. Design the slab bridges.

3. Design the Arch bridges and

4. Design the bridge bearings, hinges and expansion joints.

SYLLABUS

Introduction to bridge engineering. Historical background of bridges and types.Bridge

aesthetics and proportioning. Design process. Review of applicable design codes. Loads on

bridges and force distribution.Bridge geometry.

Analysis and design of Slab Bridge, Skew slab bridge.

Analysis and design of T-beam bridge: Deck slab considering IRC loads, longitudinal

girders(Interior, Exterior), Cross girder.

Analysis and design of prestressed concrete girder and box girder bridges considering only

primary torsion, Design of end block.

Bridge Bearing: Types of bearings, Rocker bearing, Elastomeric bearing.

TEXT BOOKS:

1. “Essentials of Bridge Engineering”, D. Jhonson Victor, Oxford University Press.

2. “Design of Bridges”, N.KrishnaRaju, Oxford & IBH Publishing Co.Pvt.Ltd, New Delhi

REFERENCE BOOKS:

1. Concrete Bridge Practice-Analysis, Design and Economics By Dr. V.K.Raina, Shroff Pub &

Dist. Pvt. Ltd.

2. Bridge Engineering By S.Ponnu Swamy, McGraw Hill Education.

3. Bridge Engineering By K.S.Rangwala & P.S.Rangwala, JBA Publishers.

21

Code: M16 ST 1110

OPTIMIZATION TECHNIQUES



Credits : 4

COURSE OBJECTIVES:

1. To familiarize the student on various methods of optimization and design of structural

members.

COURSE OUTCOMES:

Students will be able to

1. Derive optimized structure using classical and modern methods of optimization.

2. Gain the knowledge on Formulation of Structural Optimization problems.

3. Gain the knowledge on the concept of classical methods of optimization for multivariable

4. With equality or inequality constraints: solution by method of Lagrange Multiplier -

Applications in structural engineering, Kuhn-Tucker conditions.

SYLLABUS

Introduction: Need and scope of optimization, Historical development, Statement of an

optimization problems, Objective function and its surface, design variables, constraints and

constraint surface. Classification of optimization problems, various functions (continuous,

discontinuous, and discrete) and Function behaviour (Monotonic, Non-Monotonic and Uni-

modal)

Classical Optimization Techniques: Differential calculus method, Multivariable optimization

by method of constrained variation and Lagrange multipliers (generalized problem). Kuhn-

Tucker conditions for optimality.

Fully stressed design and optimally criterion based algorithms, Introduction, Characteristics of

fully stressed design theoretical basis – Examples.

Non-linear Programming: Unconstrained minimization – Fibonacci, Golden section, Quadratic

and Cubic interpolation methods for a one-dimensional minimization and Univariate Method,

Powel‟s method, Newton‟s method and Davidon Fletcher Powell‟s method for multivariable

optimization. Constrained minimization – Cutting plane method, Zoutendijk‟s method and

penalty function methods.

Linear programming – Definitions and theorems – Simplex method – Duality in linear

programming.Plastic analysis and minimum weight design and rigid frame.

Introduction to quadratic programming, Geometric programming and Dynamic

programming.Design of beams and frame using dynamic programming technique.

TEXT BOOKS:

1. “Optimization Theory and Applications” by Rao, S.S., Wiley Eastern Ltd., New Delhi, 1978.

2. “Optimum Design of Structures” by Majid, K.I., Newnes-Butter Worths, London, 1974.

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REFERENCE BOOKS:

1. “Mathematical Foundations for Design: Civil Engg. Systems” by Robert, M. Stark and

Robert L. Nicholls, McGraw Hill Book Company, New York, 1972.

2. “Optimum Structural Design, Theory and Applications”, Edited by Gallegher, R.H. and

Zienkiewiez, O.C., John Wiley and Sons, New York, 1973.

23

Code: M16 ST 1111

COMPUTER APPLICATIONS IN STRUCTURAL ENGINEERING

(VIVA-VOCE)

Tutorial : 3 Periods Sessionals : 50


Credits : 2

COURSE OBJECTIVES:

1. To apply the civil engineering software to some of the structural engineering problems.

COURSE OUTCOMES:


1. Analyze the structural elements using software designs.

2. Design the structures fir the dynamic loads using software‟s.

3. Solve the finite elements application problems of structural engineering by software‟s.

SYLLABUS

Application of software‟s in Structural Engineering (by using STAAD Pro, ETABS STRAP,

STRUDS etc) for the following problems.

1. Analysis and Design of Beams.

2. Analysis and Design of Footings.

3. Analysis and Design of Trusses.

4. Analysis and Design of Two Dimensional Frames.

5. Analysis and Design of Three Dimensional Frames.

6. Analysis and Design of Water Tanks.

7. Analysis and Design of Steel Members.

8. Implementation of Concepts of FEM using a Computer Language.

REFERENCE BOOKS:

1. Computer Applications In Structural Engineering by David R.Jenkins, American Society of

Civil Engineers

2. Computer aided design-Software and Analytical tools by C.S. Krishnamoorthy & S. Rajesh.

3. Computer aided design in reinforced concete, V.L.Shah.

24

Code: M16 ST 1112

DESIGN OF STRUCTURES

(VIVA-VOCE)



Credits : 2

COURSE OBJECTIVES:

1. To Design of Folded Plates

2. To Elevated Service Reservoirs

3. To analysis and design Retaining walls

4. To design Grid floor

5. To design Flat slab

6. To design Pressed steel tank

7. To design Buried pipes

COURSE OUTCOMES:


1. Design of Folded Plates, Elevated Service Reservoirs, Analysis and design Retaining walls,

Design Grid floor, Design Flat slab, Design Pressed steel tank, Design Buried pipes

SYLLABUS

On any THREE of the following:

1. Design of Folded Plates

2. Elevated Service Reservoirs

3. Retaining walls

4. Grid floor

5. Flat slab

6. Pressed steel tank

7. Buried pipes

REFERENCE BOOKS:

1. “Advanced Reinforced Concrete Design” by P.C. Varghese., PHI Learning pvt. Ltd

2. “Reinforced Concrete Design” by S.Unnikrishna Pillai & Devadas Menonon Tata

McGrawhill education Pvt. Ltd.

3. “Advanced Reinforced Concrete Design” by N.Krishna Raju,CBS publishers & distributors

pvt Ltd.

4. “Design Of Reinforced Concrete Structures”, by N.Subramanian, Oxford University press

5. Limit State Design of Steel Structures by S.K.Duggal, Tata Mc.Graw Hills.

6. “Design Of Reinforced Concrete Structures”,by S.Ramamrutham, Dhanpat Rai Publishers.

25




(Regulation:R16)


II – SEMESTER

Code No. Course title Credit

s

Lecture

Hrs

Lab

Hrs

Total

Contact

Hrs/Week

Sessional

Marks

Exam

Marks

Total

Marks

M16 ST

1201

Theory of Plates and

Shells 4 4 -- 4 30 70 100

M16 ST

1202 Structural Stability 4 4 -- 4 30 70 100

M16 ST

1203

Finite Element Methods

of Analysis 4 4 -- 4 30 70 100

M16 ST

1204 Earthquake Engineering 4 4 -- 4 30 70 100

#3 Elective-III 4 4 -- 4 30 70 100

#4 Elective-IV 4 4 -- 4 30 70 100

M16 ST

1211

Repair and Rehabilitation

of Structures 2 -- 3 3 50 50 100

M16 ST

1212

Advanced Design of

Structures 2 -- 3 3 50 50 100

Total 28 24 6 30 280 520 800

Course Code Course

#3-Elective-III

M16 ST 1205 Reliability Analysis and Design

M16 ST 1206 Prestressed Concrete

M16 ST 1207 Ground Improvement Techniques

#4-Elective-IV

M16 ST 1208 Industrial Structures

M16 ST 1209 Design of steel bridges

M16 ST 1210 Inelastic Design of Slabs

26

Code: M16 ST 1201

THEORY OF PLATES AND SHELLS



Credits : 4

COURSE OBJECTIVES:

1. To familiarize with the concepts of plates and shells and designing of shells.

COURSE OUTCOMES:


1. Analyze and design for plates for different loadings.

2. Analyze and design of shells.

3. Explain the concept of curvature in shells.

4. Gain knowledge on beams, theory of cylindrical shells.

SYLLABUS

Bending of Long Rectangular Plates to a Cylindrical Surface: Differential equation for

cylindrical bending of plates – Uniformly leaded rectangular plates with simple supported edges

and with built in edges. Pure bending of plates slopes – Curvatures of bent plates – Relations

between bending moments and curvature – Particular cases – Strain energy in pure bending –

Limitations.

Symmetrical Bending of Circular Plates: Differential equation – Boundary conditions. Simply

supported rectangular plates under sinusoidal loading – Naviers solution and its application to

concentrated load – Levy‟s solution for uniformly distributed load or hydrostatic pressure –

Bending of rectangular plates by moments distributed along the edges – Differential equation of

rectangular plate within plane and lateral forces.

Membrane analysis:

a) Shells of revolution (axi-symmetrical loading), Spherical shells, Conical shells, Elliptical shell

of revolution, Torus, Hyperboloid of revolution of one sheet, Shells of uniform strength

membrane deformation.

b) Membrane analysis of shells of translation, Circular cylinder, Diretrix, Parabola, Cycloid,

Catenary and Membrane deformations.

c) Membrane analysis of shells of general shape: Anticlastic, Synclastic shells, Hyperbolic

paraboloid, Candella shells, Conoid, Elliptic paraboloid, Rotational paraboloid.

Bending analysis of cylindrical shell: Beam method, Schorer method, Finsterwalder

method.Classification analysis.

TEXT BOOK:

1. “Theory of Plates and Shells” by Timoshenko, S. and Wernewsky-Kriegar, McGraw Hill Co

REFERENCE BOOKS:

1. “Design of Reinforced Concrete Shells and Folded Plates” by P.C.Varghese, PHI

2. “Stresses in Shells” by Flugge, Springer

3. “Design and Construction of Shells” by Ramaswamy, G.S, Wiley Publicatations.

27

Code: M16 ST 1202

STRUCTURAL STABILITY



Credits : 4

COURSE OBJECTIVES:

1. To impart the knowledge on linear and nonlinear behaviour of structures.

2. To familiarize the student with stability of plates under combined loads.

COURSE OUTCOMES:


1. Analyze structures with linear and nonlinear behaviour.

2. Gain the knowledge on Stability of Continuous systems.

3. Distinguish elastic buckling and in elastic buckling.

SYLLABUS

Buckling of Columns: Method of neutral equilibrium, Critical load of the Euler column, Linear

column theory – An eigen value problem, Effective length concept, Higher order differential

equation for columns initially bent columns, Effect of shear stress on buckling, eccentrically

loaded columns, beam columns (Beam columns with concreted lateral load, distributed, load end

moment), Inelastic buckling of columns, Double modulus theory, Tangent modulus theory,

Shanley theory of inelastic column behaviour.

Approximate Methods of Analysis: Conservation of energy principles, Calculation of critical

loads using approximate deflection curve, Principle of stationary potential energy, Raleigh-Ritz

method, Buckling load of column with variable cross-section, Galerkin‟s method, Calculation of

critical load by finite differences, Unevenly spaced pivot points, Matrix stiffness method, Effect

of axial load on bending stiffness-slope deflection equations, Buckling of column loaded along

the length using energy methods.

Buckling of Frames: Modes of buckling, Critical load of a simple frame using neutral

equilibrium, Slope deflection equations and matrix analysis. Lateral buckling of cantilever and

simply supported beams of rectangular and I-sections and use of energy method and finite

differences.

Buckling of Plates: Differential equation, Strain energy of bending, Critical load, Finite

difference approach inelastic buckling of plates.

Matrix approach for Frames: Criterion for determination of critical loads, Stiffness influence

coefficients for members without axial load, Derivation of stability functions, Problem involving

Non-sways, Modified stiffness of beams, Frames with sway, Multi-bar frames.

TEXT BOOKS:

1. “Principles of Structural Stability Theory” by Alexander Chajes, Prentice Hall

2. “Theory of Elasticity Stability” by Timoshenko and Gere, McGraw Hill pub.

3. “Structural Stability of Columns and Plates”NGRIyengar,EWP affiliated EastWest Press.

REFERENCE BOOKS:

1. An introduction to elastic stability of structures,By G.J.Simitses,1976 Prentice Hall NJ.

2. Stability of Structures By ZP Bazant and L Cedolin,1990,Oxford University Press.

28

Code: M16 ST 1203

FINITE ELEMENT METHODS OF ANALYSIS



Credits : 4

COURSE OBJECTIVES:

1. To apply the concepts of Finite element method for solving structural Engineering problems.

COURSE OUTCOMES:


1. Understand the fundamentals of Finite element method.

2. Derive the solution of the problems of 1D and 2D by FEM.

3. Apply the concept of iso-parametric formulation for solving problems.

4. Derive the shape functions for higher order elements.

5. Determine solution for higher order elements problems by numerical techniques.

SYLLABUS

Introduction: A brief history of F.E.M. Need of the method, Review of basic principles of solid

mechanics- Equations of equilibrium, Boundary conditions, Compatibility, Strain displacement

relations, Constitutive relationship in matrix form, plane stress & plane strain and axisymmetric

bodies of revolution with axi-symmetric loading, Energy principles - Raleigh - Ritz method of

functional approximation.

Theory relating to the formulation of the finite element method, Coordinate system (local

and global), generalized coordinates, Concept of the element, Various element shapes,

Discretisation of a structure, Mesh refinement Vs. Higher order element, Interconnections at

nodes of displacement models, inter element compatibility, -shape functions.

Basic component – One dimensional FEM single bar element, Beam element : Derivation of

stiffness matrix, Assembly of stiffness, Matrix boundary conditions, shape functions for 1 D

elements, Initial strain and temperature effects, and trusses under axial forces.

Two dimensional FEM: Different types of elements for plane stress and plane strain analysis –

Displacement models Generation of element stiffness and nodal load matrices –static

condensation.

Isoperimetric representation and its formulation for 2d analysis.Formulation of 4-noded and 8-

noded isoparametric quadrilateral elements – Lagrangian elements-serendipity elements.

TEXT BOOKS : 1. Introduction to Finite element Method by TirupathichandraPatla and Belugundu, PHI

2. C.S.Krishnamoorthy, (2002), Finite Element Analysis, Tata McGraw Hill Publishing Co.

Ltd.

REFERENCE BOOKS : 1. The Finite Element Method in Engineering Science” by Zienkiewicz, P., McGraw Hill, 1971.

2. Introduction to Finite Element Method by Desai,C.S.and Abel, J.F.,VanNostrand, 1972.

29

Code: M16 ST 1204

EARTHQUAKE ENGINEERING



Credits : 4

COURSE OBJECTIVES:

1. To impart the knowledge of designing earthquake resistant structures and familiarize the

code provisions.

COURSE OUTCOMES:


1. Describe various terms of engineering seismology.

2. Design earthquake-resistant structures.

3. Gain the knowledge on seismic codal provisions and detailing.

4. Acquire the knowledge in structural irregularities in seismic planning and shear wall concept.

SYLLABUS

One Degree Systems: Undamped systems, Various forcing functions damped systems, Response

to pulsating force, Support motion. Lumped Mass Multidegree System: Direct determination of

natural frequencies, Characteristic shapes, Stodola-Vianelle method, Modified Rayleigh-Ritz

method, Lagrange‟s equation, Model analysis of multi degree systems, Multistorey rigid frames

subjected to lateral loads, Damping in multi degree systems.

Matrix Approach: Coordinates and lumped masses, Consistent mass matrix, Undamped force

vibration of a system with one degree freedom, Response of single degree freedom undamped

system, Viscous damped vibration of a single degree freedom system, Undamped vibration of

multi degree freedom system, Orthogonality of natural nodes, Normal coordinates.

Earthquakes, Epicenter, Hypocenter and earthquake waves, Measurement of ground motion,

Seismic regions, Intensity and Isoseismals of an earthquake, Magnitude and energy of an

earthquake, Consequences of earthquakes, Seismic zoning. Earthquake Response of Linear

Systems: Earthquake excitation, Equation of motion, Response quantities, Response history,

Response spectrum concept, Deformation, Pseudo-velocity, and Pseudo-acceleration, Response

spectra, Peak structural response from the response spectrum, Response spectrum characteristics,

Elastic design spectrum, Comparison of design and response spectra, Distinction between design

and response spectra.

Earthquake analysis of Multistorey buildings: By seismic coefficient method and Response

spectrum method, Base shear, Fundamental period of buildings, Distribution of forces along the

height.

Earthquake analysis of Water towers: Introduction, Behaviour under earthquake loads, Design

features, Water tower as a rigid jointed space frame, Hydrodynamic pressures in tanks.

Earthquake analysis of Stack like structures: Introduction, Fundamental period of vibration,

Dynamic bending moment, Shear diagram.

30

Earthquake analysis of dams: Hydrodynamic pressures on dams, Zanger‟s method, Vertical

component of reservoir load, Concrete or masonry gravity dams.

TEXT BOOKS:

1. “Elements of Earthquake Engineering” by Jaikrishna and Chandrasekharan,

SarithaPrakasham, Meerut.

2. “Dynamics of Structures, Theory and Applications to Earthquake Engineering” by Anil K.

Chopra, Prentice Hall of India.

3. “Earthquake resistant design of structures” by S.K.Duggal, Oxford University Press.

REFERENCE BOOKS:

1. “Structural Dynamics” by John M. Biggs, McGraw Hill Co.

2. “Structural Analysis” by A. Ghali& A.M. Neville, CRC press

3. “Earthquake resistant design of structures” by PankajAgarwal and Manish Shrikhande,

Prentice Hall of India Pvt. Ltd.

31

Code: M16 ST 1205

RELIABILITY ANALYSIS AND DESIGN



Credits : 4

COURSE OBJECTIVES:

1. To learn the importance of reliability in Civil engineering and concepts of computing

structural reliability.

COURSE OUTCOMES:


1. Understand the importance of reliability in Civil engineering.

2. Apply the concepts of computation of structural reliability for solving engineering problems.

3. Gain the knowledge of reliability based structural design.

SYLLABUS

Concepts of Structural Safety: General, Design methods.

Basic Statistics: Introduction, Data reduction, Histograms, Sample correlation.

Probability Theory: Introduction, Random events, Random variables, Functions of random

variables, Moments and expectation, Common probability distribution, Extremal distribution.

Resistance Distributions and Parameters: Introduction, Statistics of properties of concrete,

Statistics of properties of steel, Statistics of strength of bricks and mortar, Dimensional

variations, Characterization of variables, Allowable stresses based on specified reliability.

Probabilistic Analysis of Loads: Gravity loads, Wind load.

Basic Structural Reliability: Introduction, Computation of structural reliability. Monte Carlo

Study of Structural Safety: General, Monte Carlo method, Applications.

Level 2 Reliability Methods: Introduction, Basic variables and failure surface, First-order

second-moment methods (FOSM).

Reliability Based Design: Introduction, Determination of partial safety factors, Safety checking

formats, Development of reliability based design criteria, Optimal safety factors, Summary of

results of study for Indian standard – RCC design. Reliability of Structural Systems: Preliminary

concepts as applied to simple structures.

TEXT BOOK:

1. “Structural Reliability Analysis and Design” by Ranganatham, R., Jaico Publishing house.

REFERENCE BOOK:

1. “Structural Reliability” by Melchers, R.E., Wiley publications.

32

Code: M16 ST 1206

PRESTRESSED CONCRETE



Credits : 4

COURSE OBJECTIVES:

1. To impart the knowledge on pre-stressing techniques and materials required for pre-stressing.

2. To familiarize the student with the losses of pre-stress and design of beams and slabs.

COURSE OUTCOMES:


1. Analyze and design pre-stressed concrete members.

2. Gain the knowledge on materials, prestressing Systems, end anchorages.

3. Gain the knowledge on losses of pre-stress.

4. Analyze and design of sections for flexure.

5. Apply the concept of prestress for designing of slabs.

SYLLABUS

Introduction: Basic concepts of prestressing need for high strength steel and concrete,

advantages of prestressed concrete. Materials for prestressed concrete, high strength concrete and

high strength steel.

Prestressing systems and losses of prestress: (1) Freyssinet Anchorage System (2) Gifford

Udall System (3) Magnel-Blaton System, Tensioning devices, anchoring devices. (d)

Pretensioning and Post tensioning. Prestressing losses, Elastic shortening, loss due to shrinkage,

loss due to creep, loss due to friction, loss due to slip etc.I.S.code provisions.

Analysis of prestressed Concrete Beams: Assumptions, Analysis of prestress, Resultant

stresses at a section, pressure or thrust line, concept of load balancing, cable profile, kern

distance, stress in tendons as per IS 1343, cracking moment.

Shear and Torsional Resistance of Prestressed Concrete Members: Shear and Principal

Stresses, Ultimate Shear Resistance of Prestressed Concrete Members, Design of Shear

Reinforcements, Prestressed Concrete members In Torsion, Design of Reinforcements for

Torsion, Shear and Bending

Transfer of prestress in Pretensioned members: Transmission length, bond stress, Transverse

tensile stress, End Zone reinforcement, flexural bond stress, I.S. Code Provisions.

Anchorage zone in post tensioned members: Introduction, stress distribution in End block,

Investigation on Anchorage Zone Stresses- Magnel‟s method, Guyon‟s method of approach of

analysis of end block (Not more than 2 cables).

Deflection of Prestressed Concrete Members: Importance of Control of Deflections, Factors

Influencing Deflections, Short-Term Deflection of Uncracked members, Prediction of Long

Time Deflections, Deflection of Cracked Members, Requirements of various Codes of Practice.

33

TEXT BOOKS:

1. Prestressed Concrete by N.KrishnaRaju, TataMcGrawhill, NewDelhi

2. Design of Prestressed Concrete Structures by T.Y. Lin and Ned. H. Burns, JohnWilley &

sons.

REFERENCE BOOKS:

1. Prestressed Concrete by N.Rajagopalan, Alpha Science publications.

2. Prestressed Concrete by P. Dayaratnam, Delhi publications.

34

Code: M16 ST 1207

GROUND IMPROVEMENT TECHNIQUES



Credits : 4

COURSE OBJECTIVES:

1. To introduce the various types of improvement methods of engineering properties soils.

2. To introduce the application of engineering methods to ground improvement projects.

COURSE OUTCOMES:


1. Implement the stabilization methods

2. Apply grouting and dewatering techniques

3. Understand the concept of in-situ reinforcement

SYLLABUS

Compaction:Theory of compaction, Shallow Surface Compaction - Equipment, Placement

water content, factors affecting shallow compaction; Deep compaction: Methods -

Vibrofloatation, Terra probe method, Pounding, Blasting, Compaction piles; Compaction

Control.

Vertical Drains:Sand drains, Sand wicks, Rope drains, Design of vertical drains, Stone columns,

application of the techniques to Marine clays.

Stabilization:Introduction, objectives, Methods of stabilization – Mechanical, Cement, Lime,

Bituminous, Calcium chloride; construction methods, factors affecting stabilization of soils;

Deep Mixing methods – Soil lime Columns and Cement Lime Columns, applications.

Dewatering:Definition, necessity, Methods of dewatering – Interceptor ditch, Single, Multistage

and Vacuum well points, Horizontal wells, Electro-osmosis. Permanent drainage by Foundation

drains and Blanket drains.

Grouting: Definition, Objectives of grouting, Grouts and their properties, Categories of

Grouting, Grouting methods: Ascending, Descending and Stage Grouting in Soils,

Hydrofracture, Grouting Equipment, Post grouting tests. In-situ Reinforcement: Ground

Anchors, Tiebacks and Soil Nailing, Micropiles.

TEXT BOOK:

1. Ground Improvement Techniques by P. Purushothama Raj, Laksmi Publications, New Delhi.

REFERENCE BOOK:

1. Engineering Principles of Ground Modification by Monfred R Hausmann, McGraw Hill

Publishing Co.

35

Code: M16 ST 1208

INDUSTRIAL STRUCTURES



Credits : 4

COURSE OBJECTIVE:

1. This subject imparts a broad knowledge in the area of industrial structures.

COURSE OUTCOMES:


1. Know the requirements of various industries.

2. Get an idea about the materials used and planning.

3. Know the construction techniques.

4. Understood the functional requirements.

SYLLABUS

Plastic Analysis: Introduction, Limit analysis of steel structures, Mechanical properties of

structural steel, Plastic hinge, Moment curvature relations, Limit load, Coplanar load, Upper

lower bound theorems. Redistribution of moments continuous beams: Relevant or irrelevant

mechanisms, Types of mechanisms method for performing moment check. Portal frame,

Mechanisms, Combination of mechanisms, Moment check, Partial complete and over complete

collapse.

Light gauge steel structures: Local buckling of thin sections, Post packing of thin elements,

Light gauge steel columns and compression members, Form factor for columns and compression

members, Stiffened compression elements, Multiple stiffened compression elements, Unstiffened

compression elements effective length of light gauge steel compression members, Basic design

stress, Allowable design stress, Light gauge steel beams, Laterally supported light gauge steel

beams web crippling. Allowable design stress in beams, Beams subjected to combined axial end

bending stress, connections.

Analysis of Communication Towers: Analysis of Transmission line Towers: Loads on towers,

Sag (dip) and Tension in uniformly loaded conductors, Analysis of towers (analysis as coplanar

assembly), Design of members in towers, Design of foundation of towers. Design of Steel

Chimneys for wind and gravity loads. Design of gantry girder.

TEXT BOOKS:

1. “Comprehensive Design of Steel Structures”, B.C.Punmia,Ashok Kumar Jain, Arun Kumar

Jain, Laxmi Publications (P) Ltd.

2. Design of Steel Structures by Duggal S.K, Tata McGrawHill Education2000

REFERENCE BOOKS:

1. “Plastic Analysis of Structures” by Beedle, Wiley Publications.

2. “Design of Steel Structures” by Arya&Ajmani, Nemchand Publishers.

3. “Design of Steel Structures” Vol2 by Dr.Rama Chandra, Scientific Publications

36

Code: M16 ST 1209

DESIGN OF STEEL BRIDGES



Credits : 4

COURSE OBJECTIVES:

1. To learn relevant code of practice for the design of steel Bridges.

2. To analyze and design of Plate girder Bridges.

3. To analyze and design of truss girder Bridges.

4. To know Bearings.

COURSE OUTCOMES:


1. Apply the IS code of practice for the design of steel bridges.

2. Analyze and design of Plate girder Bridges.

3. Analyze and design of truss girder Bridges.

SYLLABUS

Steel Bridges: Introduction, classification of steel bridges, economical span, clearance

requirements, dimensions of rolling stock, width of roadway and footway

Loads: Live load for Railway, Highway and combined rail cum road bridges, Impact effect,

wind load, lateral force (racking force), longitudinal forces, centrifugal forces, seismic forces,

temperature effects.

Plate girder bridges: Introduction, types, general arrangement, wind load effects, analysis and

design of Deck type plate girder bridge for railways, analysis and design of Half-through plate

girder bridge for railways, analysis and design of Through type plate girder bridge for railways.

Truss girder bridges: Introduction, general arrangement of components of truss girder bridge,

self-weight of Truss girder bridge, wind load and wind effects, analysis of portal bracing,

analysis and design of through type truss girder bridge

Bearings : Introduction, IS code requirements for bearings, Types of bearings, plate bearing,

Rocker bearing, Roller bearing, Knuckle pin bearing, Railway board roller bearing

TEXT BOOKS:

1. Design of Steel structures by N. Subramanian, Oxford University Press.

2. Limit State Design of steel structures – Ramchandra and VirendraGehlot, Scientific

Publishers (India)

REFERENCE BOOKS:

1. Comprehensive design of steel structures-B.C.Punmia, Ashok Kumar Jain and Arun Kumar

Jain, Laxmi Publications (P) Ltd.

2. Design of Steel Structures by Duggal S.K, Tata McGrawHill Education2000

37

Code: M16 ST 1210

INELASTIC DESIGN OF SLABS



Credits : 4

COURSE OBJECTIVES:

1. To know elastic theory analysis.

2. To know the yield line theory.

3. To analyze the slabs by principle of virtual work.

4. To analyze the slabs by using equilibrium method.

5. To design the slabs for different edge conditions.

COURSE OUTCOMES:


1. Understand the elastic theory analysis.

2. Understand the yield line theory.

3. Analyze the slabs by principle of virtual work.

4. Analyze the slabs by using equilibrium method.

5. Design the slabs for different edge conditions.

SYLLABUS

Basic elastic theory Analysis: Classical plate theory, Lagrange‟s equation, moment-

deformation, shear-deformation relationships. Examples on square and rectangular plates

carrying uniformly distributed load for different edge conditions.

Principles of yield line theory: slab reinforcement, section behavior and conditions at ultimate

load. Yield lines as axes of rotation and basic rules for the determination of the pattern of yield

lines. Different yield line patterns for rectangular and non rectangular slabs supported on three

and four sides with different edge conditions.

Analysis by principle of virtual work: Derivation of virtual work equations for Isotropic and

Orthotropic two-way Square/ Rectangular slabs supported on four sides for different edge

conditions.

Analysis of rectangular/Square slabs supported on three sides with different edge conditions and

one edge is free (Balcony slabs) using virtual work principle.

Analysis of rectangular/Square slabs supported on three (Balcony slabs) and four sides with

different edge conditions using equilibrium method.

Design of rectangular/Square slabs supported on three (Balcony slabs) and four sides for

different edge conditions.

Derivation of virtual work equations only, for two-way slabs supported on four sides with

different edge conditions having openings at centre, central eccentric, corner, central short side

and central long side.

38

TEXT BOOKS:

1. “Reinforced Concrete Slabs”, Robert Park, William L Gamble, JOHN WILEY &SONS.

INC, New York, 2010.

2. “Ultimate Strength Design for Structural Concrete”. V.Ramakrishnan, P.D.Arthur. Wheeler

books.

REFERENCE BOOK:

1. R H Wood and LL Jones “Yield line Analysis of Slabs”. Thames and Hudson,

Chatto&Windus, London,1967

39

Code: M16 ST 1211

REPAIR AND REHABILITATION OF STRUCTURES

(VIVA-VOCE)



Credits : 2

COURSE OBJECTIVES:

1. To familiarize the students with various types of deteriorations and need for rehabilitation.

2. To familiarize the student with Non – destructive testing and repairs.

COURSE OUTCOMES:


1. Assess the damage intensity

2. Select proper rehabilitation and repair measures for different types of deteriorations.

3. Apply the Seismic Retrofitting techniques on reinforced concrete building.

SYLLABUS

Materials: Construction chemicals, Mineral admixtures, Composites, Fibre reinforced concrete,

High performance concrete, Polymer-impregnated concrete.

Techniques to Test the Existing Strengths: Destructive and non-destructive tests on concrete.

Repairs of Multi-storey Structures: Cracks in concrete, Possible damages to the structural

element beams, Slab, Column, Footing, etc., Repairing techniques like Jack Chu, Grouting,

External pre-stressing, Use of chemical admixtures, Repairs to the fire damaged structure.

Repairs to Masonry Structures & Temples: Damages to masonry structures – Repairing

techniques, Damages to temples – Repairing techniques.

Foundation Problems: Settlement of soils – Repairs, Sinking of piles – Repairs.

Corrosion of Reinforcement: Preventive measures – Coatings – Use of SBR modified

cementitious mortar, Epoxy resin mortar, Acrylic modified cementitious mortar, Flowing

concrete.

Temporary Structures: Need for temporary structures under any Hazard, Various temporary

structures, Case-studies.

Case Studies: At least 2 case studies per each student.

REFERENCE BOOKS:

1. “Renovation of Structures” by Perkins, E & FN Spon.

2. “Repairs of Fire Damaged Structures” by Jagadish, R, McGraw Hill Co.

3. “Forensic Engineering” by Raikar, R.N, McGraw Hill Co.

4. “Deterioration, Maintenance and Repair of Structures” by Johnson, McGraw Hill Co.

40

Code: M16 ST 1212

ADVANCED DESIGN OF STRUCTURES

(VIVA-VOCE)



Credits : 2

COURSE OBJECTIVES:

1. To Design of blast resistant structures.

2. To Design of berth structures.

3. To Design of Quay Walls.

4. To analyze & design of Pre-engineered buildings.

5. To analyze & design Bow string girder bridge.

6. To analyze & design balanced cantilever bridge.

7. To analyze & design Raft design.

8. To Design of Piles and pile caps.

COURSE OUTCOMES:


1. Design of blast resistant structures, Design of berth structures, Design of Quay Walls,

Analyze & design of Pre-engineered buildings, Analyze & design Bow string Girder Bridge,

Analyze & design balanced cantilever bridge, Analyze & design Raft design, Design of Piles

and pile caps.

SYLLABUS

On any THREE of the following:

1. Design of blast resistant structures

2. Design of berth structures

3. Design of Quay Walls

4. Pre-engineered buildings

5. Bow string girder bridge

6. Balanced cantilever bridge

7. Raft design

8. Design of Piles and pile caps

REFERENCE BOOKS:

1. “Essentials of Bridge Engineering” by Johnson victor, Oxford and IBH publishing Co.pvt

Ltd, New Delhi.

2. “Design of Bridges” by N.Krishna Raju, Oxford and IBH publishing Co.pvt Ltd, New Delhi.

3. “Principles and Practice of Bridge Engineering ” by S.P.Bindra, DanapthRai & Sons.

4. “Bridge Engineering ” by R.Rangwala, Charotar publishing House Pvt. Ltd

41




(Regulation:R16)


III SEMESTER

Code No Course title Credits Scheme of

Examination

Total

Marks

M16 ST 2101 Thesis Work-

Preliminary 10 Review 100

1. Candidates can do their thesis work within the department or in any industry/research

organization for two semesters (i.e. 3rd and 4th semesters). In case of thesis done in an

industry/research organization, one advisor (Guide) should be from the department and one

advisor (CO-Guide) should be from the industry/research organization.

2. The Thesis Work -Preliminary should be submitted at the end of 3rd semester and it will be

evaluated through Review by a committee consisting of Head of the Department, External

Examiner, PG coordinator and guide. The marks shall be awarded in the ratio of 20, 40, 20 and 20

percent by the members respectively.

42




(Regulation:R16)


IV SEMESTER

Course Code Course Title Credits Scheme of Examination Exam

Marks

Total

Marks

M16 ST 2201 Thesis Work- Final 14 Viva-voce 100 100

1. A publication of a paper on the thesis work in a National/International Journal at the end of 4th

semester is mandatory for the submission of thesis work.

2. The Thesis should be submitted at the end of 4th semester and it will be evaluated through

Viva–Voce examination by a committee consisting of Head of the Department, External

Examiner, PG coordinator and thesis guide. The marks shall be awarded in the ratio of 20, 40, 20

and 20 percent by the members respectively.

9

DEPARTMENT OF COMPUTER SCIENCE AND ENGINEERING

M.TECH (COMPUTER SCIENCE AND TECHNOLOGY)


(Regulation:R16)


I – SEMESTER


Hrs

Lab

Hrs

Total

Contact

Hrs/Week

Sessional

Marks

Exam

Marks

Total

Marks

M16 CST 1101

Mathematical

Foundations of

Computer Science 4 4 -- 4 30 70 100

M16 CST 1102 Data Structures &

Algorithms 4 4 -- 4 30 70 100

M16 CST 1103 Advanced Data Base

Management Systems 4 4 -- 4 30 70 100

M16 CST 1104 Advanced Operating

Systems 4 4 -- 4 30 70 100

#1 Elective-I 4 4 -- 4 30 70 100

#2 Elective-II 4 4 -- 4 30 70 100

M16 CST 1113 Data Structures &

Programming Lab 2 -- 3 3 50 50 100

M16 CST 1114 Database Management

Systems Lab 2 -- 3 3 50 50 100

Total 28 24 6 30 280 520 800

Course Code Course

#1-Elective-I

M16 CST 1105 Computer Organization & Architecture

M16 CST 1106 E-Commerce

M16 CST 1107 Embedded Systems

M16 CST 1108 Image Processing

#2-Elective-II

M16 CST 1109 Computer Networks

M16 CST 1110 Cloud Computing

M16 CST 1111 Grid Computing

M16 CST 1112 Computer Graphics & Visual Computing

10

Code: M16 CST 1101

MATHEMATICAL FOUNDATIONS OF COMPUTER SCIENCE

(Common for M.Tech (CST, IT))



Credits : 4

COURSE OBJECTIVES:

1. Presenting the theory of finite automata, as the first step towards learning advanced

topics, such as compiler design.

2. Applying the concepts learned in fundamental courses such as Discrete Mathematics, in a

theoretical setting; in particular, the application of proof techniques.

3. Discussing the applications of finite automata towards text processing.

4. Developing an understanding of computation through Turing Machines

COURSE OUTCOMES:

1. Critical, logical-mathematical reasoning

2. Ability to apply mathematical knowledge and logic in solving problems.

3. Understanding of formal grammar analysis and compilation.

SYLLABUS

Mathematical notions of sets, sequences and tuples, functions and relations, Primitive

recursive functions, computable functions, examples, graphs, strings and languages,

Boolean logic – properties and representation, theorems and types of proofs, deductive,

inductive, by construction, contradiction and counter-examples.

Introduction to Number theory, Divisibility, modular arithmetic (addition modulo and

multiplication modulo); Statements and applications of Euler and Fermat Theorems,

Primitive Roots, Discrete Logarithms, Primality Test, Finding Large primes, Definition of

Elliptic Curves and their applications to Cryptography.

Introduction To Finite Automata: Alphabets and languages- Deterministic Finite Automata –

Non- deterministic Finite Automata – Equivalence of Deterministic and Non-Finite Automata

– Languages Accepted by Finite Automata – Finite Automata and Regular Expressions –

Properties of Regular sets &Regular Languages and their applications.

Context Free Languages: Context –Free Grammar – Regular Languages and Context-Free

Grammar – Pushdown Automata – Pushdown Automata and Context-Free Grammar –

Properties of Context-Free Languages – pushdown automata and Equivalence with Context

Free Grammars.

Turing Machines: The Definition of Turing Machine – Computing with Turing Machines –

Combining Turing Machines, , programming techniques for Turing Machines,

Variants of Turing Machines, Restricted Turing Machines Universal Turing Machines. The

Halting Problem, Decidable & undecidable problems- Post Correspondence Problems

11

TEXT BOOKS:

1. Introduction to Automata Theory, Languages and Computations – J.E. Hopcroft, & J.D.

Ullman, Pearson Education Asia.

2. Cryptography and Network Security, William Stallings.(Second Edition)Pearson

Education Asia.

REFERENCE BOOKS:

1. Introduction to languages and theory of computation – John C. Martin (MGH)

2. Discrete Mathematical structures with application to Computer Science – J.P. Tremblay

and R. Manohar, McGraw Hill Publications

3. Introduction to Theory of Computation – Michael Sipser (Thomson Nrools/Cole)

4. Cryptanalysis of number theoretic Cyphers, Samuel S. Wagstaff Jr.Champan & Hall/CRC

Press 2003.

5. Network Security: The Complete Reference by Roberta Bragg, Mark Phodes –Ousley,

Keith Strassberg Tata McGraw-Hill.

12

Code: M16 CST 1102

DATA STRUCTURES & ALGORITHMS




Credits : 4

COURSE OBJECTIVES:

1. Student will learn about advanced data structures and the algorithms for manipulating

them, and how to analyze the time and memory requirements of them.

2. Student will master some complex searching and sorting algorithms and their data

structures, advanced types of trees, basic computational geometry procedures, and graph

representations and graph algorithms.

3. Student will learn when and how to use techniques for developing algorithms, such as

divide-and-conquer and dynamic programming.

4. Student will also become skilled in algorithmic analysis and algorithm development using

the latest techniques.

COURSE OUTCOMES:

1. Be able to write programs and class libraries given a specification;

2. Implement various data structures.

3. Implement and analyze various sorting algorithms.

4. Understand abstract data types and how they are implemented in „C‟ programming

language.

SYLLABUS

Algorithm Analysis: Overview of C++ classes, pointers, parameters passing, templates,

using Matrices, Basics of time complexity estimates, General norms for running time

calculation

Lists, Stacks & Queues: Abstract Data Types, Representation & implementation of ADT

list, Doubly linked list, Circular linked lists, Representation, Implementation and applications

of ADT stack and Queue.

Trees: Implementation and traversal of trees, Binary Trees and Binary search trees in C++,

Concepts of AVL Trees, Splay Trees and B-Trees.

Hashing: Hash Function, Separate chains, Open addressing, rehashing, Extendible Hashing.

Internal Sorting Algorithms: Sorting like insertion Sort, shell Sort, Heap Sort, Merge Sort,

Quick Sort and Simple external Sorting algorithm.

Disjoint Set: Equivalence Relations, Find and Union algorithms an dynamic sets, Path

compression and Union-by-Rank algorithm analysis.

Graph Algorithms: Representation of graph Topological Sort, shortest-path Algorithm,

Network flow problem, Minimum spanning tree algorithm, Applications of Depth – First

search, Introduction to NP-Completeness.

TEXT BOOK:

1. Data Structures & Algorithm Analysis in C++, Mark Allen Weiss. Second edition,

Pearson Edition. Asia.

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REFERENCE BOOKS:

1. Data Structures & Algorithm in C++, Adam Drozdek. Vikas publication House.

2. Data Structure, Algorithm and OOP, Gregory L. Heileman (Tata Mc Graw Hill Edition).

3. Data Structures, Algorithms and Applications in C++,Sartaj Sahni,Mc Graw-Hill

International Edition.

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Code: M16 CST 1103

ADVANCED DATA BASE MANAGEMENT SYSTEMS (Common for M.Tech (CST, IT))



Credits : 4

COURSE OBJECTIVES:

1. To interpret an entity relationship diagram (ERD) to express requirements and

demonstrate skills to model data requirements and create data models into normalized

designs

2. To use SQL to create database objects, populate tables, and retrieve data

3. To describe the causes of performance problems and how to improve database application

performance

4. To develop a working understanding of database systems theory in order to apply that

knowledge to any particular database implementation.

COURSE OUTCOMES:

1. Understanding of DBMS.

2. Design database using ER model and refine the design by enforcing functional

dependencies, integrity constraints and normalization

3. Write queries using SQL

4. Implement procedures and triggers

SYLLABUS

Database Systems: Introduction to the Database Systems, Concepts of Relational Models

and Relational Algebra. SQL: Introduction to SQL Queries, Integrity Constraints, Joins,

Views, Intermediate and Advanced SQL features and Triggers.

Database Design: Overview of the Design process, E-R Models, Functional dependencies

and other kinds of dependencies, Normal forms, Normalization and Schema Refinement.

Database Application Design and Development: User Interfaces and Tools, Embedded

SQL, Dynamic SQL, Cursors and Stored procedures, JDBC, Security and Authorization in

SQL, Internet Applications.

Query Evaluation: Overview, Query processing, Query optimization, Performance Tuning.

Database System Architectures: Centralized and Client-Server Architecture, Server system

Architecture, Parallel and Distributed database, Object based databases and XML. Advanced

data types in databases. Cloud based data storage systems.

Transaction Management: Overview of Transaction Management, Transactions,

Concurrency control, Recovery systems, Advanced Transaction Processing.

Case Studies: Postgre SQL, Oracle, IBM DB2 Universal Database, Microsoft SQL Server.

TEXT BOOK: 1. Database System Concepts, Avi Silberschatz , Henry F. Korth , S. Sudarshan

McGraw-Hill, Sixth Edition, ISBN 0-07-352332-1.

REFERENCE BOOK:

1. Database Management Systems, Raghu Ramakrishnan, Johannes Gehrke,McGraw-Hill.

http://www.cs.yale.edu/homes/avi

http://www.lehigh.edu/~hfk2/hfk2.html

http://www.cse.iitb.ac.in/~sudarsha

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Code: M16 CST 1104

ADVANCED OPERATING SYSTEMS (Common for M.Tech (CST, IT))



Credits : 4

COURSE OBJECTIVES:

1. To understand the concepts of distributed systems

2. To know networks and protocols, RPC

3. To understand Synchronization, Process and Processors, File and Directory Services,

shared memory in Distributed systems

COURSE OUTCOME:

1. Students understands the concept of Distributed systems, Process Synchronization, File

structure and shared memory in Distributes operating systems

SYLLABUS

Introduction To Operating Systems, Types Of Operating Systems, Operating System

Structures. Operating-System Services, System Calls, Virtual Machines, Operating System

Design And Implementation.

Process Management: Process Concepts, Operations On Processes, Cooperating Processes,

Threads, Inter Process Communication, Process Scheduling, Scheduling Algorithms,

Multiple -Processor Scheduling. Thread Scheduling.

Process Synchronization & Deadlocks: The Critical Section Problem, Semaphores, And

Classical Problems Of Synchronization, Critical Regions, Monitors, Deadlocks,-System

Model, Deadlocks Characterization, Methods For Handling Deadlocks, Deadlock-

Prevention, Avoidance, Detection,& Recovery from Deadlocks.

Memory Management & File System Implementation: Logical Versus Physical Address

Space, Paging And Segmentation, Virtual Memory, Demand Paging, Page Replacement

Algorithms, Thrashing, File System Implementation -Access Methods, Directory Structure,

Protection, File System Structure, Allocation Methods, Free Space Management, Directory

Management, Device Drivers

Distributed Operating Systems: Distributed System Goals, Types Of Distributed Systems,

Styles & Architecture Of Distributed Systems, Threads, Virtualization, Clients, Servers, Code

Migration, and Communication in Distributed Systems.

Distributed Systems & Synchronization: Clock Synchronization, Logical Clocks, Mutual

Exclusion, Global Positioning Of Nodes, Data-Centric Consistency Models, Client-Centric

Consistency Models, Consistency Protocols.

Fault Tolerance, Security: Introduction To Fault Tolerance, Process Resilience,, Reliable

Client-Server Communication, Reliable Group Communication, Distributed Commit,

Recovery, Secure Channels, Access Control, Security Management

TEXT BOOKS:

1. Silberschatz & Galvin, „Operating System Concepts‟, Wiley.

2. “DISTRIBUTED SYSTEMS”, Second edition, Andrew S.Tanenbaum, Maarten Van

teen., Pearson

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REFERENCE BOOKS:

1. William Stallings-“Operating Systems”- 5th Edition - PHI

2. Charles Crowley, „Operating Systems: A Design-Oriented Approach‟, Tata Hill Co., 1998

edition.

3. Andrew S.Tanenbaum, „Modern Operating Systems‟, 2nd edition, 1995, PHI.

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Code: M16 CST 1105

COMPUTER ORGANIZATION AND ARCHITECTURE



Credits : 4

COURSE OBJECTIVES:

1. To have a thorough understanding of the basic structure and operation of a digital

computer.

2. To discuss in detail the operation of the arithmetic unit including the algorithms &

implementation of fixed-point and floating-point addition, subtraction, multiplication &

division.

3. To study the different ways of communicating with I/O devices and standard I/O

interfaces.

4. To study the hierarchical memory system including cache memories and virtual memory

COURSE OUTCOMES:

Students will have thorough knowledge about

1. Basic structure of a digital computer

2. The organization of the Control unit, Arithmetic and Logical unit, Memory unit and the

I/O unit.

SYLLABUS

Register Transfer and Micro operations:Register Transfer Language, Register Transfer,

Bus and Memory Transfers, Arithmetic Micro operations, Logic Micro operations, Shift

Micro operations, Arithmetic Logic Shift Unit.

Basic Computer Organization and Design:Instruction Codes, Computer Registers,

Computer Instructions, Timing and Control, Instruction Cycle, Memory-Reference

Instructions, Input-Output and Interrupt, Complete Computer Description, Design of Basic

Computer, Design of Accumulator Logic.

Micro programmed Control:Control Memory, Address Sequencing, Micro program

Example, Design of Control Unit.

Central Processing Unit:Introduction, General Register Organization, Stack Organization,

Instruction Formats, Addressing Modes, Data Transfer and Manipulation, Program Control,

Reduced Instruction Set Computer(RISC)

Input/output Organization:Peripheral Devices, I/O interface, Asynchronous data transfer,

Modes of transfer, priority Interrupt, Direct memory access, Input-Output Processor (IOP),

Serial Communication.

Memory Organization:Memory Hierarchy, Main memory, Auxiliary memory, Associate

Memory, Cache Memory, and Virtual memory, Memory Management Hardware.

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Overview of Computer Architecture: Evolution of Computer Systems, Parallelism in Uni-

processor System, Parallel Computer Structures, Architectural Classification Schemes,

Parallel Processing Applications.

TEXT BOOKS: 1. Computer System Architecture, M. Morris Mano, Prentice Hall of India Pvt. Ltd., Third

Edition, Sept. 2008 .

2. Computer Architecture and Parallel Processing, Kai Hwang and Faye A. Briggs, McGraw

Hill, International Edition1985.

REFERENCE BOOKS:

1. Computer Architecture and Organization, William Stallings, PHI Pvt. Ltd., Eastern

Economy Edition, Sixth Edition, 2003.

2. “Computer System Architecture”, John. P. Hayes.

3. Computer Architecture A quantitative approach 3rd edition John L. Hennessy & David A.

Patterson Morgan Kufmann (An Imprint of Elsevier).

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Code: M16 CST 1106

E-COMMERCE



Credits : 4

COURSE OBJECTIVES:

1. To understand process models ,

2. E – payments

3. Credit Cards and smart cards

4. E.- documents and E- Business logic

COURSE OUTCOMES:

1. Will be able to analyze the concept of electronic market and market place.

2. Able to understand the business standards and security issues

3. Able understand e-commerce business models and applications, issues of e-commerce

business models.

.

SYLLABUS

Introduction: Electronic Commerce-Frame Work, Anatomy of E-Commerce Applications,

E-Commerce Consumer Applications, E-Commerce Organization Applications. Consumer

Oriented Electronic Commerce - Mercantile Process Models, Digital Economy and e-

business Models

Electronic Payment Systems – Types of Electronic Payment Systems, Digital Token-Based,

Smart Cards, Credit Cards, Risks in Electronic Payment Systems, Designing Electronic

Payment Systems Electronic Data Inter Change, Inter Organizational Commerce - EDI, EDI

Implementation, Value Added Networks.

Intra Organizational Commerce, Macro Forces And Internal Commerce, Work Flow

Automation and Coordination, Customization And Internal Commerce, Supply Chain

Management. Business Cases for Document Library, Digital Document Types, Corporate

Data Ware-Houses.

Advertising And Marketing: Information Based Marketing, Advertising On Internet,

Online Marketing Process, Market Research. Consumer Search and Resource Discovery,

Information Search and Retrieval, Commerce Catalogues, Information Filtering.

Multimedia-Key Multimedia Concepts, Digital Video and Electronic Commerce, Desktop

Video Processing, Desktop Video Conferencing.

Business to consumer e-commerce: On line Marketing and Selling, Information Goods,

Electronic Markets and Auctions on the Internet

E-Business Intelligence: Data Mining, Web Merchandising and Recommender Systems,

Intelligent Agents in e-commerce, Business-to-Business e-commerce and Supply Chain

Management

Security of Internet Hosts and Networks, Public Key Infrastructure, Safety of e-commerce

Applications.

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TEXT BOOK:

1. Frontiers of Electronic Commerce, Kalakata and Whinston, Pearson.

REFERENCE BOOKS :

1. E-Commerce fundamentals and Applications, Hendry Chan, Raymond Lee, Tharam

Dillon, Ellizabeth Chang, John Wiley.

2. E-Commerce, S.Jaiswal, Galgotia.

3. E-Commerce, Efrain Turbon, Jae Lee, David King, H.Michael Chang.

4. E-Commerce - Business, Technology and Society, Kenneth C.Taudon, Carol Guyerico

Traver.

21

Code: M16 CST 1107

EMBEDDED SYSTEMS



Credits : 4

COURSE OBJECTIVES:

1. To understand the architecture embedded systems

2. To know Embedded system software design

3. Design, execution and evaluation of experiments on embedded platforms.

4. Analysis, design and testing of systems that include both hardware and software.

5. Identification and synthesis of solutions for embedded system problems

COURSE OUTCOMES:

1. An ability to design systems, components, or processes for broadly-defined engineering

technology problems.

2. Implement combinatorial logic and sequential systems in terms of basic digital building

blocks using simulation software. You will be able to perform some optimisations.

3. Design, test and critically evaluate embedded solutions to real world situations using

digital components (sequential and combinatorial).

4. Recognize the key features of embedded systems in terms of computer hardware and be

able to discuss their functions. You will be aware of the key factors affecting computing

hardware evolution.

5. Develop software systems for embedded devices using assembler code

SYLLABUS

Examples of Embedded Systems – Typical Hardware – Memory – Microprocessors –

Busses – Direct Memory Access – Introduction to 8051 Microcontroller – Architecture-

Instruction set – Programming.

Microprocessor Architecture – Interrupt Basics – The Shared-Data problem – Interrupt

Latency.

Round–Robin Architecture - Round–Robin with Interrupts Architecture - Function-Queue-

Scheduling Architecture – Real-Time Operating Systems Architecture – Selection of

Architecture.

Tasks and Task States – Tasks and Data – Semaphores and Shared Data – Semaphore

Problems – Semaphore variants.

Message Queues – Mailboxes – Pipes – Timer Functions – Events – Memory Management –

Interrupt Routines in RTOS Environment.

RTOS design – Principles – Encapsulation Semaphores and Queues – Hard Real-Time

Scheduling Considerations – Saving Memory Space – Saving Power.

Host and Target Machines – Linker/Locator for Embedded Software- Getting Embedded

Software into the Target System.

Testing on your Host Machine – Instruction Set Simulators – Laboratory Tools used for

Debugging.

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TEXT BOOKS:

1. The 8051 Microcontroller Architecture, Programming & Applications, Kenneth J. Ayala,

Penram International.

2. An Embedded Software Primer, David E. Simon, Pearson Education , 2005.

REFERENCE BOOK:

1. Embedded Systems: Architecture , Programming and Design, Raj Kamal, Tata McGraw-

Hill Education, 2008

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Code: M16 CST 1108

IMAGE PROCESSING



Credits : 4

COURSE OBJECTIVES:

1. The course objectives include: overview of digital image processing field; understand the

fundamental digital image processing algorithms and implementation; gain experience in

applying image processing algorithms to real problems.

2. Cover the basic theory and algorithms that are widely used in digital image processing.

3. Expose students to current technologies and issues that are specific to image processing

systems

COURSE OUTCOMES:

1. Demonstrated understanding of the basic concepts of two-dimensional signal acquisition,

sampling, and quantization.

2. Demonstrated understanding of spatial filtering techniques, including linear and nonlinear

methods.

3. Demonstrated understanding of 2D Fourier transform concepts, including the 2D DFT

and FFT, and their use in frequency domain filtering.

4. Demonstrated understanding of the fundamental image enhancement algorithms such as

histogram modification, contrast manipulation, and edge detection.

SYLLABUS

Fundamentals of Image Processing: Image Acquisition, Image Model, Sampling,

Quantization, Relationship between Pixels, Distance Measures, Connectivity, Image

Geometry, Photographic Film. Histogram: Definition, Decision Of Contrast Basing On

Histogram, Operations Basing on Histograms Like Image Stretching, Image Sliding, Image

Classification. Definition and Algorithm of Histogram Equalization.

Image Transforms : A Detail Discussion On Fourier Transform, DFT,FFT, Properties

WALSH Trans Form , WFT, HADAMARD Transform, DCT

Image Enhancement :

a. Arithmetic and Logical Operations, Pixel or Point Operations, Size Operations,

b. Smoothing Filters-Mean, Median, Mode Filters – Comparative Study

c. Edge Enhancement Filters – Directorial Filters, Sobel, Laplacian, Robert, KIRSCH

Homogeneity

d. DIFF Filters, Prewitt Filter, Contrast Based Edge Enhancement Techniques –

Comparative Study

e. Low Pass Filters, High Pass Filters, Sharpening Filters. – Comparative Study

f. Colour Fundamentals and Colour Models

g. Colour Image Processing.

Image Enhancement: Design of Low Pass, High Pass, EDGE Enhancement, Smoothening

Filters in Frequency Domain. Butter Worth Filter, Homomorphic Filters in Frequency

Domain Advantages of Filters in Frequency Domain, Comparative Study of Filters in

Frequency, Domain and Spatial Domain.

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Image Compression: Run Length Encoding, Contour Coding, Huffman Code, Compression

Due to Change in Domain, Compression Due to Quantization Compression at the Time of

Image Transmission. Brief Discussion on:- Image Compression Standards.

Image Segmentation: Characteristics of Segmentation, Detection of Discontinuities,

Thresholding Pixel Based Segmentation Method. Region Based Segmentation Methods,

Segmentation by Pixel Aggregation, Segmentation by Sub Region Aggregation, Histogram

Based Segmentation, Spilt and Merge Technique, Motion in Segmentation

Morphology: Dilation, Erosion, Opening, Closing, Hit-And-Miss Transform, Boundary

Extraction, Region Filling, Connected Components, Thinning, Thickening, Skeletons,

Pruning Extensions to Gray – Scale Images Application of Morphology in I.P

Image, Video & Multimedia Communications: Multi-scale and multi-orientation

representation; Geometry and texture representation; Object based representation;

Hierarchical representation; Sparse representation, Multimedia with image and video content;

Multimedia event synchronization

TEXT BOOK:

1. Digital Image Processing, Rafael C. Gonzalez And Richard E. Woods, Addision Wesley

REFERENCE BOOKS:

1. Fundamentals Of Electronic Image Processing By Arthyr – R – Weeks, Jr.(PHI)

2. Image Processing, Analysis, and Machine Vision by Milan Sonka Vaclan Halavac Roger

Boyle, Vikas Publishing House.

3. Digital Image Processing, S. Jayaraman, S. Esakkirajan& T. Veera Kumar, TMH

4. Fundamentals of Digital Image Processing, Chris Solomon, Tobi Breckon, Wiley-

Blackwell

25

Code: M16 CST 1109

COMPUTER NETWORKS



Credits : 4

COURSE OBJECTIVES:

1. Build an understanding of the fundamental concepts of computer networking.

2. Familiarize the student with the basic taxonomy and terminology of the computer

networking area.

3. Introduce the student to advanced networking concepts, preparing the student for entry

Advanced courses in computer networking.

4. Allow the student to gain expertise in some specific areas of networking such as the

design and maintenance of individual networks.

COURSE OUTCOMES:

After completing this course the student able to demonstrate the knowledge and ability to:

1. Independently understand basic computer network technology.

2. Identify the different types of network topologies and protocols.

3. Enumerate the layers of the OSI model and TCP/IP. Explain the function(s) of each layer.

4. Identify the different types of network devices and their functions within a network

5. Familiarity with the basic protocols of computer networks, and how they can be used to

assist in network design and implementation.

6. Have an understanding of protocols in computer networks

7. Understand different protocols of different layers of computer networks.

SYLLABUS

Introduction to Computer Networks: Introduction, Network Hardware, Network Software,

Reference Models, Data Communication Services & Network Examples, Internet Based

Applications.

Data Communications: Transmission Media, Wireless Transmission, Multiplexing,

Switching, Transmission in ISDN, Broad Band ISDN , ATM Networks

Data Link Control, Error Detection & Correction, Sliding Window Protocols, LANs &

MANs: IEEE Standards for LANs & MANs-IEEE Standards 802.2, 802.3, 802.4, 802.5,

802.6, High Speed LANs.

Design Issues in Networks: Routing Algorithms, Congestion Control Algorithms, Net work

Layer in the Internet, IP Protocol, IP Address, Subnets, and Internetworking.

Internet Transport Protocols: TRANSPORT Service, Elements of Transport Protocols,

TCP and UDP Protocols, Quality of Service Model, Best Effort Model, Network

Performance Issues.

Over View of DNS, SNMP, Electronic Mail, FTP, TFTP, BOOTP, HTTP Protocols, World

Wide Web, Firewalls.

Network Devices: Over View of Repeaters, Bridges, Routers, Gateways, Multiprotocol

Routers, Brouters, Hubs, Switches, Modems, Channel Service Unit CSU, Data Service Units

DSU, NIC, Wireless Access Points, Transceivers, Firewalls, Proxies.

26

Advanced Concepts in Networks: Over View of Cellular Networks, Adhoc Networks,

Mobile Adhoc Networks, Sensor Networks, Virtual Private Networks .Delay Tolerant

Networks DTN, Ipvs.

TEXT BOOK:

1. Computer Networks, Andrews S Tanenbaum,, 5th

Edition , PHI, ISBN:-81-203-1165-5

REFERENCE BOOKS:

1. Data Communications and Networking , Behrouz A Forouzan , Tata McGraw-Hill Co Ltd

Second Edition.

2. Computer networks,Mayank Dave, CENGAGE.

3. Computer networks, A System Approach, 5th

ed, Larry L Peterson and Bruce S Davie,

Elsevier.

4. An Engineering Approach to Computer Networks-S.Keshav, 2nd

Edition, Pearson

Education.

5. Understanding communications and Networks, 3rd

Edition, W.A. Shay, Thomson.

27

Code: M16 CST 1110

CLOUD COMPUTING



Credits : 4

COURSE OBJECTIVES:

1. To impart fundamental concepts in the area of cloud computing.

2. To impart knowledge in applications of cloud computing.

COURSE OUTCOMES:

1. Understanding the systems, protocols and mechanisms to support cloud computing

2. Develop applications for cloud computing

3. Understanding the hardware necessary for cloud computing

4. Design and implement a novel cloud computing application

SYLLABUS

Cloud Computing Basics - Cloud Computing Overview, Applications, Intranets and the

Cloud, First Movers in the Cloud. The Business Case for Going to the Cloud - Cloud

Computing Services, Business Applications, Deleting Your Datacenter, Salesforce.com,

Thomson Reuters.

Organization and Cloud Computing - When You Can Use Cloud Computing, Benefits,

Limitations, Security Concerns, Regulatory Issues, Cloud Computing with the Titans -

Google, EMC, NetApp, Microsoft, Amazon, Salesforce.com, IBMPartnerships.

Hardware and Infrastructure - Clients, Security, Network, Services. Accessing the Cloud -

Platforms, Web Applications, Web APIs,Web Browsers. Cloud Storage - Overview, Cloud

Storage Providers, Standards - Application, Client, Infrastructure, Service.

Software as a Service - Overview, Driving Forces, Company Offerings, Industries Software

plus Services - Overview, Mobile Device Integration, Providers, Microsoft Online.

Developing Applications - Google, Microsoft, Intuit QuickBase, Cast Iron Cloud, Bungee

Connect, Development, Troubleshooting, Application Management.

Local Clouds and Thin Clients - Virtualization in Your Organization, Server Solutions,

Thin Clients, Case Study: McNeilus Steel.

Migrating to the Cloud - Cloud Services for Individuals, Cloud Services Aimed at the Mid-

Market, Enterprise-Class Cloud Offerings, Migration, Best Practices and the Future of Cloud

Computing - Analyze Your Service, Best Practices, How Cloud Computing Might Evolve.

TEXT BOOK:

1. Cloud Computing-A Practical Approach, Anthony T. Velte, Toby J. Velte, Robert

Elsenpeter. McGrawHill.

REFERENCE BOOK:

1. Mastering Cloud Computing- Raj Kumar Buyya, Christian Vecchiola and S.Tanurai

Selvi, TMH, 2012

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Code: M16 CST 1111

GRID COMPUTING



Credits : 4

COURSE OBJECTIVES:

1. Understand the need for and evolution of Grids in the context of processor- and data-

intensive applications

2. Be familiar with the fundamental components of Grid environments, such as

authentication, authorization, resource access, and resource discovery

3. Know architecture of grid computing

4. Be able to justify the applicability, or non-applicability, of Grid technologies for a

specific application

COURSE OUTCOMES:

1. To understand the genesis of grid computing

2. To know the application of grid computing

3. To learn the technology and tool kits for facilitating grid computing

SYLLABUS

Introduction: Introduction to Parallel, Distributed Computing, Cluster Computing and Grid

Computing, Characterization of Grids, Organizations and their Roles, Grid Computing Road

Maps.

Architecture: Architecture of Grid and Grid Computing, Review of Web Services-OGSA-

WSRF.

Grid Monitoring: Grid Monitoring Architecture (GMA) - An Overview of Grid Monitoring

Systems- GridICE - JAMM -MDS-Network Weather Service-R-GMA-Other Monitoring

Systems- Ganglia and GridM

Grid Middleware: List of globally available Middlewares - Case Studies-Recent version of

Globus Toolkit and gLite - Architecture, Components and Features.

Data Management And Grid Portals: Data Management, Categories and Origins of

Structured Data, Data Management Challenges, Architectural Approaches, Collective Data

Management Services, Federation Services, Grid Portals, First-Generation Grid Portals,

Second Generation Grid Portals.

Semantic Grid and Autonomic Computing: Meta data and Ontology in the Semantic Web,

Semantic Web services, Layered structure of the Semantic Grid, Semantic Grid activities,

Autonomic Computing

Grid Security and Resource Management: Grid Security, A Brief Security Primer, PKI-

X509 Certificates, Grid Security, Scheduling and Resource Management, Scheduling

Paradigms, Working principles of Scheduling, A Review of Condor, SGE, PBS and LSF-

Grid Scheduling with QoS.

TEXT BOOKS:

1. Grid Computing, Joshy Joseph and Craig Fellenstein, Pearson Education 2004.

2. The Grid Core Technologies, Maozhen Li, Mark Baker, John Wiley and Sons , 2005.

29

REFERENCE BOOKS:

1. The Grid 2 - Blueprint for a New Computing Infrastructure, Ian Foster and Carl

Kesselman, Morgan Kaufman - 2004.

2. Grid Computing: Making the Global Infrastructure a reality, Fran Berman, Geoffrey Fox,

Anthony J.G. Hey, John Wiley and sons

30

Code: M16 CST 1112

COMPUTER GRAPHICS & VISUAL COMPUTING



Credits : 4

COURSE OBJECTIVES:

1. To Learn basic and fundamental computer graphics techniques

2. To Learn image synthesis techniques

3. Examine applications of modeling, design and visualization

4. Learn different color modeling and computer animation

5. Learn hierarchical modeling and graphing file formats

6. Learn viewing pipeline and structures

7. To Learn visualization and computational and mathematical methods of visual computing

8. To understand visual transformation and projection

COURSE OUTCOMES:

Students able to

1. Learn basic and fundamental computer graphics techniques

2. Represent and implement images and objects using 3D representation.

3. Design develop surface detection using various detection methods

4. Choose various illumination models for provides effective standards of objects

5. Design of develop effective computer animations

6. Design of various projections

SYLLABUS

Introduction: Computer Graphics and their applications, Computer Aided Design-

Computer Art, Entertainment, Education and Training, Graphical User Interfaces; Over

view of Graphics systems: Video Display Devices, Raster Scan systems, random scan

systems, Graphics monitors and workstations, Input devices, hard copy devices, GUI

and Interactive Input Methods, Windows and Icons , Virtual Reality Environments,

Graphics software

Output primitives: Points and Lines, , Line and Curve Attributes-Color and Gray scale

levels Line Drawing Algorithms, Loading the Frame buffer, Line function, Circle

Generating Algorithms, Ellipse Generating Algorithms, Other Curves, Parallel Curve

Algorithms, Curve Functions , Pixel Addressing, Area Fill Attributes, Filled Area Primitives,

Filled Area Functions, Cell Array, Character Generation, Character Attributes, Bundled

Attributes, Inquiry Functions , Antialiasing

Three Dimensional Concepts and Object representations: 3D display methods-3D

Graphics, Polygon Surfaces, Curved Lines and Surfaces, Quadratic Surfaces, Super

Quadrics, Blobby Objects, Spline Representations , Cubic Spline methods, Bézier Curves and

Surfaces, B Spline Curves and Surfaces

Two & Three Dimensional Transformations: Two Dimensional Transformations: Basic

Transformations, Matrix Representations, Homogeneous Coordinates, Composite

Transformations, Other Transformations, Transformations between Coordinate Systems,

Affine Transformations -, Transformation Functions-, Raster methods for Transformation

Three Dimensional Transformations: Translation-, Rotation, scaling, Other Transformations,

Composite Transformations, 3D Transformation Functions , Modeling and Coordinate

Transformations

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Viewing Pipeline and structures : Viewing Coordinates, Projections , View

Volumes,General Projection Transformations,Clipping, Hardware Implementations,

Concepts of Structures and Basic models, Editing ,Hierarchical Modeling with Structures

Visualization: Three Dimensional Viewing, Visualization- Image Processing- The viewing

Pipeline, Viewing Coordinate Reference Frame, Window-to-Viewport Coordinate

Transformation, Two Dimensional Viewing Functions , Clipping Operations, Point

Clipping, Line Clipping, Polygon Clipping-Curve Clipping, Text and Exterior Clipping.

Visual Computing: Computational and mathematical methods for creating, capturing,

analyzing and manipulating digital photographs, Introductory Topics on computer graphics,

computer vision, and machine learning, Programming assignments intended to give hands-on

experience with creating graphical user interfaces, and with implementing programs for

synthesizing and manipulating photographs.

Visual Transformation & Projection: Graphics pipeline, perception and color models,

camera models, transformations and projection, projections, lighting, shading, global

illumination, texturing, sampling theorem, Fourier transforms, image representations,

convolution, linear filtering, diffusion, nonlinear filtering, edge detection, optical flow, image

and video compression, Creation of Visual Effects Optical Flow Video Compression, Radon

Transform Texture

TEXT BOOKS:

1. Computer Graphics C Version, Donald Hearn & M. Pauline Baker , Pearson

Education, New Delhi, 2004

2. D. Forsyth and J. Ponce, Computer Vision: A Modern Approach, Prentice Hall Inc., 2003

REFERENCE BOOKS:

1. Procedural Elements for Computer Graphics, David F. Rogers, Tata McGraw Hill Book

Company, New Delhi, 2003

2. Computer Graphics: Principles & Practice in C, J. D. Foley, S. K Feiner, A VanDam F.

H John Pearson Education, 2004

3. Computer Graphics us ing Open GL, Franscis S Hill Jr, Pearson Education, 2004.

4. Computer Vision and Image Processing: A Practical Approach using CVIPtools, S. E.

Umbaugh,, Prentice Hall, 1998

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Code: M16 CST 1113

DATA STRUCTURES& PROGRAMMING LAB (Common for M.Tech (CST, IT))

Lab : 3 Periods Sessionals : 50


Credits : 2

COURSE OBJECTIVES:

1. To introduce the graduate, simple linear & non-linear data structures.

2. To make the student write ADTs, for all data structures

3. To make the student learn different algorithm design techniques.

COURSE OUTCOMES:

At the end of this course student able to

1. Implement Linear data structures

2. Non-linear data structures

3. Sorting techniques Design of various projections

SYLLABUS

Implementation of Data Structures and Algorithms using C++

1. To perform various operations such as insertion, deletion, display on single linked lists.

2. To implement

(i) Stacks using linked list. (ii) Queues using linked list.

3. To perform different types of searching techniques on a given list

(i) Sequential search (ii) Binary search (iii) Fibonacci search

4. To perform different types of sortings on a given list

(i) Bubble sort (ii) Insertion sort (iii) Selection sort(iv) Merge sort


(i) Quick sort (ii) Shell sort (iii) Radix sort

6. To perform the following

(i) To convert the given infix expression to postfix expression

(ii) To evaluate the given postfix expression.

7. To perform various operations on graphs

(i) Vertex insertion. (ii) Vertex deletion.

(iii) Edge insertion. (iv) Edge deletion.

(v) Breadth First traversal. (vi) Depth First traversal.

8. To implement dictionaries using hashing technique

9. To perform various operations on binary heap.

10. To perform various operations on Binary search tree.

11. To perform operations on AVL trees.

12. To perform various operations on B-tree.

33

REFERENCE BOOKS:



3. Data Structures, Algorithms and Applications in C++, Sartaj Sahni, Mc Graw-Hill


34

Code: M16 CST 1114

DATA BASE MANAGEMENT LAB (Common for M.Tech (CST, IT))



Credits : 2

COURSE OBJECTIVES:

1. To practice SQL and PL/SQL in different commercial DBMS packages

2. Learn to design DBMS projects

3. Practice implementing DBMs projects

COURSE OUTCOMES:

1. Able to design DBMS projects including Normalization

2. Able to implement a DBMS project with appropriate triggers, procedures and front end.

SYLLABUS

Accessing the Database: The first laboratory exercise is to connect to a database, populate it

with data, and run very simple SQL queries. (Data Definition, Table Creation, Constraints,

Insert, Select Commands, Update & Delete Commands.)

Basic SQL: This lab covers simple SQL queries. (Inbuilt functions in RDBMS).

Intermediate SQL: This lab covers more complex SQL queries. (Nested Queries & Join

Queries, Control structures)

Advanced SQL: This lab covers even more complex SQL queries. (Procedures and

Functions, .PL/SQL, Cursors and Triggers)

Database Access from a Programming Language: This lab introduces you to database

access from a programming language such as Java or C#. Although phrased using

Java/JDBC, the exercise can be done using other languages, OBDC or ADO.NET APIs.

Building Web Applications: This lab introduces you to construction of Web applications.

Although phrased using the Java Servlet API, the exercise can be done using other languages

such as C# or PHP.

Project: Each student is assigned with a problem. The student is to develop a logical and

physical database design for the problem and develop Forms, Menu design and Reports.

A. The logical design performs the following tasks:

a) Map the ER/EER diagrams to a relational schema. Be sure to underline all primary

keys, include all necessary foreign keys and indicate referential integrity constraints.

b) Identify the functional dependencies in each relation

c) Normalize to the highest normal form possible

B. Perform physical design based above logical design using Oracle/MSSQL on Windows

platform and MySQL/PostgreSQL on Linux platform.

Sample Term Projects

1. Retailer database

2. Automobile sales database

3. Electronics vendor database

4. Package delivery database

5. Real estate database

35

REFERENCE BOOKS:

1. Database System Concepts, Avi Silberschatz, HenryF.Korth, S. Sudarshan ,McGraw-Hill,

Sixth Edition, ISBN 0-07-352332-1.

2. ORACLE PL/SQL by example. Benjamin Rosenzweig, Elena Silvestrova, Pearson

Education 3rd Edition

3. ORACLE Database Log PL/SQL Programming Scott Urman, TMG Hill.

4. SQL & PL/SQL for Oracle 10g, Black Book, Dr.P.S. Deshpande.

5. Oracle PL/SQL Programming, Steven Feuerstein, O‟Reilly Publishers.




36




(Regulation:R16)


II – SEMESTER


Hrs

Lab

Hrs

Total

Contact

Hrs/Week

Sessional

Marks

Exam

Marks

Total

Marks

M16 CST 1201 Artificial Intelligence 4 4 -- 4 30 70 100

M16 CST 1202 Object Oriented

Software Engineering 4 4 -- 4 30 70 100

M16 CST 1203 Compiler Design 4 4 -- 4 30 70 100

M16 CST 1204 Data Warehousing &

Data Mining 4 4 -- 4 30 70 100

#3 Elective III 4 4 -- 4 30 70 100

#4 Elective IV 4 4 -- 4 30 70 100

M16 CST 1213 Data Warehousing &

Mining Lab 2 -- 3 3 50 50 100

M16 CST 1214 OOSE Lab 2 -- 3 3 50 50 100

M16 CST 1215 Seminar 2 -- -- -- 100 -- 100

Total 30 24 6 30 380 520 900

Course Code Course

#3-Elective-III

M16 CST 1205 Parallel Programming

M16 CST 1206 Semantic Web

M16 CST 1207 Big Data Analytics

M16 CST 1208 Database Security

#4-Elective-IV

M16 CST 1209 Mobile Computing

M16 CST 1210 Soft Computing

M16 CST 1211 Cluster Computing

M16 CST 1212 Pervasive Computing

37

Code: M16 CST 1201

ARTIFICIAL INTELLIGENCE



Credits : 4

COURSE OBJECTIVES:

1. To introduce different artificial intelligence techniques

2. To learn different machine learning algorithms

3. Learn different recent algorithms in artificial intelligence

COURSE OUTCOMES:

1. Able to learn artificial intelligence techniques

2. Understand the concept of machine learning.

SYLLABUS

Introduction: Artificial Intelligence, AI Problems, AI Techniques, the Level of the Model,

Criteria for Success. Defining the Problem as a State Space Search, Problem Characteristics,

Production Systems, Search: Issues in The Design of Search Programs, Un-Informed Search,

BFS, DFS; Heuristic Search Techniques: Generate-And- Test, Hill Climbing, Best-First

Search, A* Algorithm, Problem Reduction, AO*Algorithm, Constraint Satisfaction, Means-

Ends Analysis.

Knowledge Representation: Procedural Vs Declarative Knowledge, Representations &

Approaches to Knowledge Representation, Forward Vs Backward Reasoning, Matching

Techniques, Partial Matching, Fuzzy Matching Algorithms and RETE Matching Algorithms;

Logic Based Programming- AI Programming languages: Overview of LISP, Search

Strategies in LISP, Pattern matching in LISP , An Expert system Shell in LISP, Over view of

Prolog, Production System using Prolog

Symbolic Logic: Propositional Logic, First Order Predicate Logic: Representing Instance

and is-a Relationships, Computable Functions and Predicates, Syntax & Semantics of FOPL,

Normal Forms, Unification &Resolution, Representation Using Rules, Natural Deduction;

Structured Representations of Knowledge: Semantic Nets, Partitioned Semantic Nets,

Frames, Conceptual Dependency, Conceptual Graphs, Scripts, CYC.

Reasoning under Uncertainty: Introduction to Non-Monotonic Reasoning, Truth

Maintenance Systems, Logics for Non-Monotonic Reasoning, Model and Temporal Logics;

Statistical Reasoning: Bayes Theorem, Certainty Factors and Rule-Based Systems, Bayesian

Probabilistic Inference, Bayesian Networks, Dempster-Shafer Theory, Fuzzy Logic: Crisp

Sets ,Fuzzy Sets, Fuzzy Logic Control, Fuzzy Inferences & Fuzzy Systems.

Experts Systems: Overview of an Expert System, Structure of an Expert Systems, Different

Types of Expert Systems- Rule Based, Model Based, Case Based and Hybrid Expert

Systems, Knowledge Acquisition and Validation Techniques, Black Board Architecture,

Knowledge Building System Tools, Expert System Shells, Fuzzy Expert systems.

Machine Learning: Knowledge and Learning, Learning by Advise, Examples, Learning in

problem Solving, Symbol Based Learning, Explanation Based Learning, Version Space, ID3

Decision Based Induction Algorithm, Unsupervised Learning, Reinforcement Learning,

Supervised Learning: Perceptron Learning, Back propagation Learning, Competitive

Learning, Hebbian Learning.

38

Natural Language Processing: Role of Knowledge in Language Understanding,

Approaches Natural Language Understanding, Steps in The Natural Language Processing,

Syntactic Processing and Augmented Transition Nets, Semantic Analysis, NLP

Understanding Systems; Planning: Components of a Planning System, Goal Stack Planning,

Hierarchical Planning, Reactive Systems

TEXT BOOKS:

1. Artificial Intelligence, George F Luger, Pearson Education Publications

2. Artificial Intelligence, Elaine Rich and Knight, Mcgraw-Hill Publications

REFERENCE BOOKS:

1. Introduction To Artificial Intelligence & Expert Systems, Patterson, PHI

2. Multi Agent systems- a modern approach to Distributed Artificial intelligence, Weiss.G,

MIT Press.

3. Artificial Intelligence : A modern Approach, Russell and Norvig, Printice Hall

39

Code: M16 CST 1202

OBJECT ORIENTED SOFTWARE ENGINEERING (Common for M.Tech (CST, IT))



Credits : 4

COURSE OBJECTIVES:

1. Students will learn the importance of following a process that is driven by the

requirements of the users of the system.

2. Showing how we apply the process of object-oriented analysis and design to software

development.

3. Pointing out the importance and function of each UML model throughout the process of

object oriented analysis and design and explaining the notation of various elements in

these models.

4. Providing students with the necessary knowledge and skills in using object-oriented

CASE tools

COURSE OUTCOMES:

1. Relate object oriented concepts representation through artifacts of UML.

2. Build and relate classes, their relationships and collaborations (CRC) (for any case study).

3. Generate the list and order of activities carried out for each behavior exhibited by any

system

4. Design advanced behavioral concepts to deploy the model

5. Apply the project development activities of software engineering

SYLLABUS

Introduction to Object Oriented Software Engineering Nature Of The Software, Types Of Software , Software Engineering Projects, Software

Engineering Activities, Software Quality, Introduction To Object Orientation, Concepts Of

Data Abstraction, Inheritance & Polymorphism, Software Process Models-Waterfall Model,

The Opportunistic Model , The Phased Released Model, The Spiral Model, Evolutionary

Model, The Concurrent Engineering Model

Requirements Engineering: Domain Analysis, Problem Definition And Scope,

Requirements Definition, Types Of Requirements, Techniques For Gathering And Analyzing

Requirements, Requirement Documents, Reviewing, Managing Change In Requirements.

Unified Modeling Language & Use Case Modeling: Introduction To UML, Modeling

Concepts, Types Of UML Diagrams With Examples; User-Centred Design, Characteristics

Of Users, Developing Use Case Models Of Systems, Use Case Diagram, Use Case

Descriptions, The Basics Of User Interface Design, Usability Principles, User Interfaces.

Class Design and Class Diagrams: Essentials Of UML Class Diagrams, Associations And

Multiplicity, Other Relationships, Generalization, Instance Diagrams, Advanced Features Of

Class Diagrams, Interaction And Behavioral Diagrams: Interaction Diagrams, State

Diagrams, Activity Diagrams, Component And Deployment Diagrams.

40

Software Design And Architecture: The Process Of Design, Principles Leading To Good

Design, Techniques For Making Good Design Decisions, Writing A Good Design

Document., Pattern Introduction, Design Patterns: The Abstraction-Occurrence Pattern,

General Hierarchical Pattern, The Play-Role Pattern, The Singleton Pattern, The Observer

Pattern, The Delegation Pattern, The Adaptor Pattern, The Façade Pattern, The Immutable

Pattern, The Read-Only Interface Pattern And The Proxy Pattern; Software Architecture

Contents Of An Architecture Model, Architectural Patterns: The Multilayer, Client-Server,

Broker, Transaction Processing, Pipe & Filter And MVC Architectural Patterns

Software Testing: Overview Of Testing, Testing Concepts, Testing Activities, Testing

Strategies, Unit Testing, Integration Testing, Function Testing, Structural Testing, Class

Based Testing Strategies, Use Case/Scenario Based Testing, Regression Testing,

Performance Testing, System Testing, Acceptance Testing, Installation Testing, OO Test

Design Issues, Test Case Design, Quality Assurance, Root Cause Analysis, Post-Mortem

Analysis.

Software Project Management: Introduction To Software Project Management, Activities

Of Software Project Management, Structure Of Project Plan, Software Engineering Teams,

Software Cost Estimation, Project Scheduling, Tracking And Monitoring.

Case Study:

a. Simple Chat Instant Messaging System

b. GPS Based Automobile Navigation System

c. Waste Management Inspection Tracking System (WMITS)

d. Geographical Information System

TEXT BOOK:

1. Object-Oriented Software Engineering Practical software development using UML and

Java by Timothy C. Lethbridge & Robert, Langaniere Mcgraw-Hill

REFERENCE BOOKS:

1. Object-Oriented Software Engineering: Using UML, Patterns and Java, Bernd Bruegge

and Allen H. Dutoit, 2nd Edition, Pearson Education Asia.

2. Software Engineering: A Practitioner's Approach, Roger S Pressman.

3. A Practical Guide to Testing Object-Oriented Software, John D. McGregor; David A.

Sykes, Addison-Wesley Professional.

41

Code: M16 CST 1203

COMPILER DESIGN



Credits : 4

COURSE OBJECTIVES:

1. To learn the various system software like assemblers, loaders, linkers and macro.

2. To study the features of design phases and parsing techniques of a Compiler.

3. To learn the various techniques of syntax directed translation & code optimization.

4. To introduce the major concept areas of language translation and compiler design.

5. To enrich the knowledge in various phases of compiler ant its use, code optimization

techniques, machine code generation, and use of symbol table.

6. To extend the knowledge of parser by parsing LL parser and LR parser.

COURSE OUTCOMES:

1. To acquire the knowledge of modern compiler & its features.

2. To learn the new code optimization techniques to improve the performance of a program

in terms of speed & space.

3. To use the knowledge of patterns, tokens & regular expressions

SYLLABUS

Introduction: Introduction to Compilers and Language processors, , Programming

Language basics, Extended Backus- Naur Form Syntax Notation, Applications of Compiler

Technology, Design of New Computer Architecture, Structure & Different Phases of a

Compiler, Review of Compiler Structure, Structure of Optimizing Compilation.

Finite Automata & Lexical Analysis: introduction to Lexical Analysis, Lexical Analyzers,

Approaches to design Lexical Analyzers, Language for specifying lexical analyzers,

Introduction to Finite automata, Regular Expressions & Languages, Recognition of Tokens,

Transition Diagrams, Look ahead Operator, Implementation of lexical analyzers, Lexical

Analyzer Generator LEX.

Syntax Analysis: Syntactic Specification of Programming Languages, Context Free

Grammars & Languages, Introduction to Parsers, Parser Generators, Yacc, Creating Yacc

Lexical Analyzer with LEX, Basic Parsing Techniques: Shift Reduce Parsing, Operator

Precedence Parsing, Top-down Parsing, Recursive Descent Parsing, Predictive Parsers, LR

Parsers: SLR, LALR & Canonical LR parsing, Construction of Parse Tree, Error Recovery in

Parsers.

Semantic Analysis: Semantic Actions, Syntax Directed Translations, Translation on the

parse Tree, Implementation of Syntax Directed Translator, Intermediate Codes, Syntax

Directed translation to Postfix code, Syntax Trees, Intermediate Code Generation, Three

Addr5ess Code-Translation of Expressions, Type Checking& Type Conversions.

Code Optimization: Principal sources of Code Optimization, Loop Optimization, Basic

Blocks& Flow Graphs, DAG Representation of Basic Blocks, Applications of DAG, Local

Optimization, Unreachable Code Elimination, Dead Code Elimination, Data Flow Analysis,

Data Flow Equations & Computations, Peep-Hole Optimization. Machine Dependent

Optimizations, Overview of Informal Compiler Algorithm Notation(ICAN), If

Simplification, Loop Simplification, Loop Inversion, Branch Optimization and Prediction

42

Code Generation: Issues in Code Generation, Input to Code Generator, Instruction

Selection, Register Allocation, Simple Target Machine Model, Program and Instruction

Costs, Register allocation & Assignments, Code Generation Algorithm, Code Generators,

Optimal Code Generation for Expressions, Code Generation From DAG.

Symbol Table Management, Contents of a Symbol Table, Data Structures for Symbol

Tables; Run time Environments, Implementation of a simple Stack allocation, Heap

Management, Block Structured Languages; Error Detection & Recovery, Lexical Phase

Errors, Syntactic & Semantic Errors, Error Handling Routines.

Code Scheduling & Case Studies: Instruction Scheduling, Speculative Loads & Boosting,

Speculative Scheduling, Software Pipe Lining, Trace Scheduling, Percolation Scheduling,

Case Studies: Sun Compilers, SPARC, IBM XL Compiler for the POWER& Power PC ,

Digital Equipment Compiler for Alpha, Intel Reference Compilers, Future Trends In

Compiler Design and Implementations.

TEXT BOOKS:

1. Principles of Compiler Design by Aho, D. Ullman, Lam and Ravi Sethi, Pearson

Education Second Edition

2. Advanced Compiler Design and Implementation, Steven Muchnic, Elsevier Publications

REFERENCE BOOKS:

1. Compiler Construction by Kenneth. C. Louden, Vikas Pub. House.

2. Compiler Design, A.A. Pentambekar, TechnicalPublications

3. Modern Compiler Design, Grune.D,Van Reeuwijk K, Bal H.E, Jacobs C J H, Langendoen

Springer,

43

Code: M16 CST 1204

DATA WAREHOUSING AND DATA MINING



Credits : 4

COURSE OBJECTIVES:

1. To differentiate OnLine Transaction Processing and OnLine Analytical processing

2. Learn Multidimensional schemas suitable for data warehousing

3. Understand various data mining functionalities

4. To Inculcate knowledge on data mining query languages.

5. To Know in detail about data mining algorithms

6. The objective of this course is to study various techniques involved in data mining, data

warehousing.

COURSE OUTCOMES:

1. Extract knowledge using data mining techniques

2. At the closing stage of the course, students will be able to analyze different operations

and techniques involved in data mining.

SYLLABUS

Introduction to Data Mining: Evolution of I T into DBMS, Motivation and importance

of Data Warehousing and Data Mining, Kinds of Patterns, Technologies, Basic Data

Analytics: Data Objects and Attributes Types, Statistical Descriptions of Data, Data

Visualization, Estimating Data Similarity and Dissimilarity, Major Issues in Data Mining.,

Data Mining Applications

Data Warehouse and OLAP Technology: Basic Concepts of Data warehouse, Data

Modeling using Cubes and OLAP, DWH Design and usage, Implementation using Data

Cubes and OLAPs, Data Generalization with AOI.

Data Mining Primitives & Data Cubes: Data Mining Primitives, Data Mining Tasks, Data

Mining Query Language, Designing Graphical user Interfaces based on a Data Mining Query

language, Preliminary Concepts of Data Cube Computation, Data Cube Computation

Methods: Multi-way Array Aggregation for Full Cube, BUC Computing for Iceberg Cubes,

Star-Cubing Using Dynamic Star-Tree Structure, Pre-computing Shell Fragments for Fast

High-Dimensional OLAPs.

Data Mining Concept Description: Data Preprocessing: Pre-processing the Data, Data

Cleaning, Data Integration, Data Reduction, Data Transformation, Discretization and

Concept Hierarchy Generation; Data Architectures of Data Mining Systems; Characterization

and Comparison, Concept Description, Data Generalization and Summarization; Analytical

Characterization: Analysis of Attribute Relevance, Mining Class Comparisons,

Discriminating between Different Classes, Mining Descriptive & Statistical Measures in

Large Databases.

Mining Frequent Patterns Based on Associations and Correlations: Basic Concepts,

Frequent Itemset Mining Methods: Apriori Algorithm, Association Rule Generation,

Improvements to A Priori, FP-Growth Approach, Mining Frequent Patterns using Vertical

Data Formats, Mining Closed and Max Patterns, Pattern Evaluation Methods

44

Classification: Basic Concepts, Decision Tree Induction, Bayes Classification, Rule-Based

Classification, Model Evaluation and Selection, Techniques to Improve Classification

Accuracy Advanced Methods: Classification by Back Propagation, SVM, Associative

Classification, Lazy Learning, Fuzzy Sets, Rough Sets, Genetic Algorithms, Multiclass

Classification, Semi-Supervised Classification

Cluster Analysis: Basic Concepts, Types of Data in Cluster Analysis, Partitioning Methods,

Hierarchical Methods, Density Based Methods, Grid Based Methods, Evaluation of

Clustering Solutions

TEXT BOOK:

1. Data Mining- Concepts and Techniques by Jiawei Han, Micheline Kamber and Jian Pei –

Morgan Kaufmann publishers – 3rd edition

REFERENCE BOOKS: 1. Data Mining Techniques, A.K.Pujari, University Press Data mining concepts by Tan,

Steinbech, and Vipin Kumar - Pearson Edu publishers

2. Data Mining – Introductory and Advanced by Margarett Dunham - Pearson Education

publishers

3. Data Warehousing for Real – world by Sam Annahory - Pearson Education publishers

45

Code: M16 CST 1205

PARALLEL PROGRAMMING



Credits : 4

COURSE OBJECTIVES:

1. To understand the scope, design and model of parallelism.

2. Know the parallel computing architecture.

3. Know the Characteristics, model and design of parallel algorithms.

4. Analytical modeling and performance of parallel programs.

5. Solve a complex problem with message passing model and programming with MPI.

COURSE OUTCOMES:

Students who complete this course successfully are expected to

1. Recall fundamental concepts of parallelism

2. Design and analyze the parallel algorithms for real world problems and implement them

on available parallel computer systems.

3. Reconstruction of emerging parallel algorithms with MPI.

4. Compute contemporary parallel algorithms.

SYLLABUS

Introduction to Parallel Computing: Parallel Programming and Parallel Computing,

Overview of Parallel Architectures and Parallel Programming Models, MIMD and SPMD

Models, Problems Unique to Parallel Programmin

Supercomputers and Grand Challenge Problems, Modern Parallel Computers, Data

Dependence Graph, Data Parallelism, Functional Parallelism, Pipelining and Data Clustering.

Interconnection Networks: Switch Network Topologies, Direct and Indirect Network

Topology, Bus, Star, Ring, Mesh, Tree, Binary Tree Network, Hyper Tree Network, Hybrid,

Hypercube, Perfect Shu E Network, Torus and Butterfly Network.

Performance Analysis: Introduction, Execution Time, Speedup, Linear and Super linear

Speedup, Efficacy and Efficiency, Amdahls Law and Amdahl Effect, Gustafson-Barsiss Law,

Minsky's Conjecture, The Karp-Flatt Metric, The Iso-Efficiency Metric, Iso-Efficiency

Relation, Cost and Scalability.

Parallel Computational Models: Flynns Taxonomy, PRAM, EREW, CREW, ERCW,

CRCW, Simulating CRCW, CREW and EREW, PRAM Algorithms.

Introduction to Parallel Algorithms: Parallel Programming Models, PVM, MPI Paradigms

Parallel Programming Languages: , Brents Theorem, Simple Parallel Programs in MPI

Environments, Parallel Algorithms on Network, Addition of Matrices, Multiplication of

Matrices.

TEXT BOOKS:

1. Computer Architecture and Parallel Processing, Hwang and Briggs, McGraw Hill.

2. Parallel Programming in C with MPI and Open MP, Michael J.Quinn, McGrawHill ,

2004

46

REFERENCE BOOKS:

1. Introduction to Distributed and Parallel Computing, Crichlow, PHI.

2. Designing Efficient Algorithms for Parallel Computers, M.J.Quinn, McGraw-Hill.

3. Introduction to Parallel Processing, Shashi Kumar M et al., PHI New Delhi.

4. Elements of Parallel Computing, V.Rajaraman, Prentice-Hall of India.

5. The Design and Analysis of Parallel Algorithms, S.G.Akl, PHI.

47

Code: M16 CST 1206

SEMANTIC WEB



Credits : 4

COURSE OBJECTIVES:

1. To teach the concepts, technologies and techniques underlying and making up the

Semantic Web.

2. Understand and use ontologies in the context of Computer Science and the semantic web

COURSE OUTCOMES:

1. Able to understand the rationale behind Semantic web.

2. Understand the concept structure of the semantic web technology and how this

technology revolutionizes the World Wide Web and its uses.

3. Able to model and query domain knowledge as ontologies defined using standards such

as RDF and OWL.

SYLLABUS

Introduction to Semantic Web: Introduction, Semantic Web, URI, RDF, Ontologies,

Inferences, DAML, Semantic Web Languages, Semantic Annotation, Classification,

Information Extraction, Ontology Assignment, XML, Syntax of XML,XML Schema,

Semantic Web Applications to E-Commerce, E-Government and E-Banking, Semantic Web

in Life Sciences, RIF Applications.

Semantic Web Structure: Semantic Web Layers Architecture, Different Layers, Match

Making, Multi Information Retrieving, Digital Signature, Semantic Memory, Semantic Web

Enabled Service Oriented Architecture (SESA), SESA Services, SESA Middle Ware.

Resource Descriptive Languages RDF: Introduction to RDF, Syntax of RDF, Advanced

Feature,Simple Ontologies in RDF Schema, Encoding Special Data Structures, Semantics

Model Theoritic Sentics for RDFs, Syntactic Reasoning with Deduction Rules Syntactic

Limits of RDFs

Web Ontology Languages: OWL Syntax, OWL Species, OWL2 Standards, OWL Formal

Semantics, Description Logics, Model Theoretic Semantics of OWL, SWRL, Semantic Web

Rules, Languages, Syntax of SWRL, Rules and Safety, Implementation & Applications.

Ontology Engineering: Requirement Analysis, Ontology Knowledge Creation, Ontologies

and Rules: Definition of a Rule, Datalog as First order Rule Language, Combining Rules with

OWDL, Rule Interchanging Formats RIF, Quality Assurance of Ontologies, Modular

Ontologies, Divide and Conquer, Software Tools.

Ontology Query Languages: Semantic Web Query Languages and Implementations, ROPS

( RDF OWL Processing Systems),SWOPS( SWRL Ontology Processing System, Bench

Marking Results, SPARQL, Query Languages for RDF, Conjunctive Queries for OWLDL.

Semantic Web Mining: Introduction, Concepts in Semantic Web Mining, XML, RDF &

Web Data Mining, Ontologies and Web Data Mining, Agents in Web Data Mining, Web

Mining and Semantic Web As a Data Base, semantic Interoperability and Web Mining Web

Mining Vs Semantic Web Mining

48

Semantic Web Tools & Applications: Web Data Exchange and Syndication, Semantic

WIKI‟s, Semantic Portals, Semantic Meta Data in Data formats, Semantic Web Services

Modeling Ontologies, Semantic Web Service Design Tools, Ontologies for Standardizations

WMO and SWMO Applications

TEXT BOOK:

1. Foundations of Semantic Web Technologies, Pascal Hitzler, Markus Krotzsch,

Sebastian Rudolph , CRC Press.

REFERENCE BOOKS:

1. Web Data Mining and Applications in Business Intelligence and Counter Terrorism,

Bavani Thuraisingham, CRC Press, June 2003

2. 2. Implementing Semantic Web Services-The SESA Frame Work, D. Fensel;M.Kerrigan;

M.Zaremba, Springer

3. 3. Enabling Semantic Web Services- The Web Service Modeling Ontology, Fensel,D;

Lausen,H;Pollers,ABruijn,J;Stollberg,M; Spriger

4. A Semantic Web Primer, Paul Groth, Frank van Harmelen, Rinke Hoekstra, The MIT

Press2012

5. Programming the Semantic Web, Toby Segaran, Colin Evans, Jamie Taylor Oreilly

Publications, July 2009

http://www.google.co.in/search?tbo=p&tbm=bks&q=inauthor:%22Pascal+Hitzler%22

http://www.google.co.in/search?tbo=p&tbm=bks&q=inauthor:%22Markus+Krotzsch%22

http://www.google.co.in/search?tbo=p&tbm=bks&q=inauthor:%22Sebastian+Rudolph%22



49

Code: M16 CST 1207

BIG DATA ANALYTICS



Credits : 4

COURSE OBJECTIVES:

1. To provide advanced knowledge and skills in the field of Computer Science and

Engineering.

2. Capable to quickly adapt to new technology in the field of Big Data, assimilate new

information, and solve real world problems.

3. To pursue applied research in the advance field of computer science and be committed to

life-long learning activities.

COURSE OUTCOMES:

1. To be able to apply the knowledge of computing tools and techniques in the field of Big

Data for solving real world problems encountered in the Software Industries.\

2. To be able to analyze the various technologies & tools associated with Big Data.

3. To be able to identify the challenges in Big Data with respect to IT Industry and pursue

quality research in this field with social relevance.

SYLLABUS

Introduction:, Velocity, Variety, Veracity; Drivers for Big Data, Sophisticated Consumers,

Automation, Monetization, Big Data Analytics Applications: Social Media Command

Center, Product Knowledge Hub, Infrastructure and Operations Studies, Product Selection,

Design and Engineering, Location-Based Services, Online Advertising, Risk Management

Architecture Components: Massively Parallel Processing (MPP) Platforms, Unstructured

Data Analytics and Reporting: Search and Count, Context-Sensitive and Domain-Specific

Searches, Categories and Ontology, Qualitative Comparisons, Data Privacy Protection, Real-

Time Adaptive Analytics and Decision Engines

Advanced Analytics Platform: Real-Time Architecture for Conversations, Orchestration

and Synthesis Using Analytics Engines, Entity Resolution, Model Management, .Discovery

Using Data at Rest, Integration Strategies

Implementation of Big Data Analytics: Revolutionary, Evolutionary, or Hybrid, Big Data

Governance, Integrating Big Data with MDM, Evolving Maturity Levels

Map-Reduce and the New Software Stack: Distributed File Systems .Physical

Organization of Compute Nodes, Large-Scale File-System Organization, Map-Reduce

features: Map Tasks, Grouping by Key, Reduce Tasks, Combiners, Map-Reduce Execution,

Coping With Node Failures, Algorithms Using Map-Reduce for Matrix multiplication,

Relational Algebra operations, Workflow Systems, Recursive Extensions to Map-Reduce

Communication Cost Models, Complexity Theory for Map-Reduce, Reducer Size and

Replication Rate, Graph Model and Mapping Schemas, Lower Bounds on Replication Rate

Mining Data Streams: Stream Data Mode l and Management Stream Source, Stream

Queries, and issues, Sampling Data in a Stream , Filtering Streams, Counting Distinct

Elements in a Stream, Estimating Moments, Counting Ones in a Window, Decaying

Windows

50

Link Analysis: Page Ranking in web search engines, Efficient Computation of PageRank

using Map-Reduce and other approaches, Topic-Sensitive PageRank , Link Spam, Hubs and

Authorities

TEXT BOOKS:

1. Big Data Analytics:Disruptive Technologies for Changing the Game, Dr. Arvind Sathi,,

First Edition October 2012, IBM Corporation

2. Mining of Massive Datasets, Anand Rajarama, Jure Leskovec, Jeffrey D. Ullman.E-book,

2013

REFERENCE BOOKS:

1. Big Data Imperatives, Soumendra Mohanty, Madhu Jagadeesh, Harsha Srivatsa, Apress,

e-book of 2012

51

Code: M16 CST 1208

DATABASE SECURITY



Credits : 4

COURSE OBJECTIVES:

1. To understand the basic concepts of database security.

2. To learn security issues and solutions

3. To understand threats to learn how to perform data encryption.

4. To understand Enterprise Security Policy

COURSE OUTCOMES:

1. Able to understand the database security framework

2. Will be able to learn database access control

3. Will be able to understand database security techniques.

4. Will be able to implement security for databases.

SYLLABUS

Introduction to Database Security: Fundamental Data Security Requirements, Data

Security Concerns, Compliance Mandates, Security Risks, Developing Enterprise Security

Policy, Defining a Security Policy, Implementing a Security Policy, Techniques to Enforce

Security

Database Access Control: User Authentication, Protecting Passwords, Creating Fixed

Database Links, Encrypting Database Link Passwords, Using Database Links Without

Credentials, Using Database Links And Changing Passwords, Auditing With Database Links,

Restricting A Database Link With Views, Trust Management & Negotiation

Database Security Issues: Database Security Basics, Security Checklist, Reducing

Administrative Effort, Applying Security Patches, Default Security Settings, Secure

Password Support, Enforcing Password Management, Protecting The Data Dictionary,

System and Object Privileges, Secure Data Outsourcing, Security in Advanced Database

Systems, Security in Data Warehousing and OLAP Systems, Managing Enterprise User

Security

Framework For Database Security,: Security for Workflow Systems, Secure Semantic

Web Services, Spatial Database Security, Security Reengineering, Strong Authentication,

Single Sign-On, Public Key Infrastructure (PKI) Tools, Configuring SSL on the Server,

Certificates, Using Kerberos for Authentication

Database Security Solutions: Maintaining Data Integrity, Protecting Data, Controlling Data

Access, Combining Optional Security Features, Compliance Scanner, Policy Trends in

Database Control, Watermarking: Copyright Protection, Trustworthy Record Retention and

Recovery, Privacy-Preserving Data Mining & Data Publishing. Privacy in Location-Based

Services

Database Auditing : Auditing Database Users, User Privileges And Objects: Monitoring for

Suspicious Activity, Standard Database Auditing, Setting the AUDIT_TRAIL, Specifying

Audit Options, Viewing Auditing Options, Auditing the SYSDBA Users, Audit to XML

Files, Value-Based Auditing, Auditing DML Statements, Triggering Audit Events,

Maintaining the Audit Trail

52

Database Privileges And Roles: Authorization, Privileges, Benefits of Roles, Using Proxy

Authentication With Roles, Creating An Enterprise Role, Securing Objects and Application

Roles, Data Masking Primitives And Routines, Privacy in Location- Based Services

Data Encryption For Database Security: Problems Solved by Encryption, Storing the Key

in Database, Key Management by User, Application-Based Encryption, Cipher Block

Modes , Hash and Message Authentication Code, Transparent Data Encryption (TDE) & File

Encryption Methods.

TEXT BOOKS: 1. Database Security, S.Castano, M. Fugini, G. Martella,P. Samarati, Addision-Wesley

2. Database Security By Alfred Basta, Melissa Zgola, Cengage Publication, 2012

REFERENCE BOOKS: 1. Database Security & Auditing By Hassan A Afyouni, Cengage Delmar Learning India

Pvt, 2009

2. Handbook Of Database Security: Applications and Trends, Michael Gertz, Sushil Jajodia,

Springer

53

Code: M16 CST 1209

MOBILE COMPUTING



Credits : 4

COURSE OBJECTIVES:

1. Introduction of an advanced element of learning in the field of wireless communication.

2. The students to the concepts of wireless devices and mobile computing.

3. To introduce wireless communication and networking principles, that support

connectivity to cellular networks, wireless internet and sensor devices.

COURSE OUTCOMES:

1. A working understanding of the characteristics and limitations of mobile hardware

devices including their user-interface modalities

2. The ability to develop applications that are mobile-device specific and demonstrate

current practice in mobile computing contexts.

3. A comprehension and appreciation of the design and development of context-aware

solutions for mobile devices.

SYLLABUS

Introduction to Mobile Computing, Overview of Mobile Technologies, Limitations, The

Ubiquitous Network, Architecture for Mobile Computing, Three-Tier Architecture, Design

Considerations for Mobile Computing, Mobile Computing Through Internet, Mobile Devises

and Mobile-Enabled Applications.

Introduction To Wireless Networking, Various Generations of Wireless Networks,

Wireless LANs, Advantages and Disadvantages of WLANs, Fixed Network Transmission

Hierarchy, Differences in Wireless and Fixed Telephone Networks, Traffic Routing in

Wireless Networks, WAN Link Connection Technologies, Cellular Networks.

WLAN Topologies, WLAN Standard IEEE 802.11, Comparison Of IEEE 802.11a, B, G and

N Standards, Wireless PANs, Hiper LAN, Wireless Local Loop, ATM, Virtual Private

Networks, Wireless Data Services, Common Channel Signaling, Various Networks for

Connecting to The Internet.

Emerging Technologies: Introduction - Bluetooth - Radio Frequency Identification (RFID),

WIMAX -Mobile IP - Ipv6 - Java Card, TCP/IP in the Mobile Setting, GSM and GPS

Data Management Issues, Data Replication For Mobile Computers, Adaptive Clustering for

Mobile Wireless Networks, File System, Disconnected Operations, Data Services in GPRS -

Applications for GPRS - Limitations - Billing and Charging.

Communications Asymmetry, Classification of New Data Delivery Mechanisms, Push-

Based Mechanisms, Pull-Based Mechanisms, Hybrid Mechanisms, Selective Tuning

(Indexing) Techniques. CDMA, GSM , Wireless Data, 3GNetworks and Applications

Introduction to Mobile IP, Introduction To Wireless Application Protocol, Application

Layer MMS - GPRS Applications, Short Message Service (SMS): Mobile Computing Over

SMS - SMS - Value Added Services Through SMS -Accessing the SMS Bearer.

54

TEXT BOOKS:

1. Mobile Computing - Technology Applications And Service Creation, Asoke K Talukder

and Roopa R.Yavagal, TMH 2006.

2. Mobile Cellular Communication, Gottapu Sasibhushana Rao,, Pearson Education, First

Edition, 2013.

REFERENCE BOOKS:

1. Principles Of Computing, Uwe Hansmann, Lother Merk, Martin S.Nicklous, Thomas

Staber, 2nd Ed., Springer International Edition.

2. Mobile Communications, J.Schiller, Addison-Wesley, 2003

3. Stojmenovic And Cacute, “Handbook Of Wireless Networks And Mobile Computing”,

Wiley, 2002.

55

Code: M16 CST 1210

SOFT COMPUTING



Credits : 4

COURSE OBJECTIVES:

1. Introduce students to soft computing concepts and techniques and foster their abilities in

designing and implementing soft computing based solutions for real-world and

engineering problems.

2. Explain the students about fuzzy sets and its operations,

3. Introduce students to fuzzy systems, fuzzy logic and its applications

4. Explain the students about Artificial Neural Networks and various categories of ANN.

COURSE OUTCOMES:

At the end of the course students

1. Able to understand genetic algorithm fundamentals and its operators and procedure

2. Understand artificial neural network model and its activation functions

3. Understand different operations of GA

SYLLABUS

Soft Computing: Introduction to Fuzzy Computing, Neural Computing, Genetic Algorithms,

Associative Memory, Adaptive Resonance Theory, Different Tools and Techniques,

Usefulness and Applications.

Fuzzy Sets and Fuzzy Logic: Introduction, Fuzzy Sets Versus Crisp Sets, Operations on

Fuzzy Sets, Extension Principle, Fuzzy Relations and Relation Equations, Fuzzy Numbers,

Linguistic Variables, Fuzzy Logic, Linguistic Hedges, Applications

Interference in fuzzy logic: fuzzy if-then rules, Fuzzy implications and Fuzzy algorithms,

Fuzzifications and Defuzzifications, Fuzzy Controller, Fuzzy Controllers, Fuzzy Pattern

Recognition, Fuzzy Image Processing, Fuzzy Database.

Artificial Neural Network: Introduction, Artificial Neuron and its model, activation

functions, Neural network architecture: single layer and multilayer feed forward networks, re-

current networks. Various learning techniques, perception and convergence rule, Auto-

associative and hetro-associative memory, Hebb's Learning, Adaline, Perceptron

Multilayer Feed Forward Network, Back Propagation Algorithms, Different Issues

Regarding Convergence of Multilayer Perceptron, Competitive Learning, Self-Organizing,

Feature Maps, Adaptive Resonance Theory, Associative Memories, Applications.

Evolutionary and Stochastic Techniques: Genetic Algorithm (GA), Genetic

Representations, (Encoding) Initialization and Selection, Different Operators of GA, Analysis

of Selection Operations, Hypothesis of Building Blocks, Schema Theorem and Convergence

of Genetic Algorithm, Simulated Annealing and Stochastic Models, Boltzmann Machine,

Applications.

Rough Set: Introduction, Imprecise Categories Approximations and Rough Sets, Reduction

of Knowledge, Decision Tables and Applications.

56

Hybrid Systems: Neural-Network-Based Fuzzy Systems, Fuzzy Logic-Based Neural

Networks, Genetic Algorithm for Neural Network Design and Learning, Fuzzy Logic and

Genetic Algorithm for Optimization, Applications

TEXT BOOKS: 1. Neural Networks, Fuzzy Logic and Genetic Algorithm: Synthesis and Applications, S.

Rajsekaran and G.A. Vijayalakshmi Pai, Prentice Hall of India.

2. Rough Sets, Z.Pawlak, Kluwer Academic Publisher, 1991.

3. Intelligent Hybrid Systems, D. Ruan, Kluwer Academic Publisher, 1997.

REFERENCE BOOKS: 1. Artificial Intelligence and Intelligent Systems, N.P.Padhy, Oxford University Press.

2. Neural Fuzzy Systems, Chin-Teng Lin & C. S. George Lee, Prentice Hall PTR. Addison-

Wesley

3. Learning and Soft Computing, V. Kecman, MIT Press, 2001

4. Fuzzy Sets and Fuzzy Logic, Klir & Yuan, PHI, 1997

57

Code: M16 CST 1211

CLUSTER COMPUTING



Credits : 4

COURSE OBJECTIVES:

1. The course will provide an insight for achieving cost efficient high performance system.

2. The course will deal with design and architecture of cluster computing.

COURSE OUTCOMES:

At the end of the course student will

1. Have knowledge of virtual technologies and Service-oriented architecture,

2. Have knowledge of Architecture for Cluster Computing, process scheduling and load

balancing.

SYLLABUS

Introduction: Overview of Cluster Computing, The Role of Clusters, Definition and

Taxonomy Of Parallel Computing, Hardware System Structure, Node Software, Resource

Management, Distributed Programming, Limitations

Cluster Planning, Architecture , Node Hardware and Node Software, Design Decisions

Network Hardware: Internet technologies, Ethernet, cLAN, QsNet, Infiniband, Packet

Format, NIC Architecture, hubs & Switches.

Network Software: TCP/IP, Sockets, Higher Level Protocols, Distributed File systems,

Remote Command Execution

Cluster Setup: Installation & Configuration, System Access Models, Assigning Names,

Installation of Node Software, Basic System Administration

Clusters Management: Cluster Workload Management Activities, Queuing, scheduling and

monitoring, Resource Management and Accounting

Virtualization technologies; Parallel and Virtual file systems, Introduction, Programming

with parallel File systems, Benchmarks

TEXT BOOK:

1. Beowulf Cluster Computing with Linux, 2nd Edition, edited by William Gropp, Ewing

Lusk, Thomas Sterling, MIT Press, 2003

REFERENCE BOOKS:

1. In Search of Clusters: The ongoing battle in Lowly Parallel Computing, Gregory F. P

Fister, Second Edition, Prentice Hall Publishing Company, 1998.

2. How to Build a Beowulf - A Guide to the Implementation and Application of PC

Clusters, Thomas Sterling, John Salmon, Donald J. Becker and Daniel F. Savarese, MIT

Press, 1999.

58

Code: M16 CST 1212

PERVASIVE COMPUTING



Credits : 4

COURSE OBJECTIVES:

1. Student can Understand underlying technologies and applied standards for building up

pervasive solutions.

2. This includes WAP, GPRS, Bluetooth, Infrared, Voice over IP, among others.

3. Expose students to latest technologies that relate to device technologies and pervasive

computing, such as wearable computing and smart identification.

COURSE OUTCOMES:

At the end of the course, students should be able to:

1. Identify distinguishing features of the different mobile device categories,

2. Understand the role of the Wireless Application Protocol inenabling mobile devices to

access the Internet

3. Able to understand elementary to medium-level (complexity-wise) user interface

applications for all three platforms.

SYLLABUS

Pervasive Computing : Introduction to Ubiquitous Computing (Popularly known as

Pervasive Computing), Evolution of Pervasive Computing, Pervasive Computing Principles :

Decentralization, Diversification, Connectivity, Simplicity, Pervasive Computing

Characteristics, Pervasive Information Technology

Pervasive Architecture: Background, Scalability and Availability, Pervasive Web

Application Architecture, Implementation Issues.

Pervasive Devices: Device Categories, Device Characteristics, Software Components in the

Device, Information Access Devices, Smart Identification, and Embedded Controls, Hand

Held Computers, Cellular Phones, Smart Phones, Smart Cards and Smart Appliances

Pervasive Connectivity: Protocols, Security, Network Management, Mobile Internet, WAN:

Cellular Basics, Major Digital Cellular Systems, Advanced Cellular Radio Standards, Short

Range Wireless Communication: DECT, Bluetooth, Irda, Home Networks.

Pervasive Applications : Home Services: System View, Communications, Home

Automation, Energy and Security Services, Remote Home Health Care Services, Business

Services, Healthcare Management, Consumer Services: Interactive Advertisement, Loyalty,

Shopping, Payment Services

Pervasive Synchronization: Definition of Synchronization, Models of Synchronization,

Challenges In Synchronizing Data, Industry Data Synchronization Standards: Infrared Mobile

Communications, WAP, Third Generation Partnership Program, Syncml, Synchronization

Solutions

Security Issues in Pervasive Computing: Importance of Security, Cryptographic Patterns

and Methods - Light Weight Cryptography -Light Weight Symmetric and Asymmetric

Cryptographic Algorithms, Cryptographic Tools - Hash, MAC, Digital Signatures

59

Mobile Internet and Web Services: WAP Architecture, Wireless Application Environment:

Wireless Markup Language, WAP Binary XML Content Format, WML Script, XHTML

Mobile Proile, I-Mode, Web Services Architecture: WSDL, ADDI, SOAP, Web Services

Security, Web Services For Remote Portals

TEXT BOOKS:

1. Pervasive Computing: The Mobile World by Uwe Hansmann, Lothar Merk

2. Pervasive Computing: Technology And Architecture of Mobile Internet Applications

Jochen Burkhardt, Horst Henn, Stefan Hepper, Klaus Rindtorff, Thomas Schaeck

REFERENCE BOOK:

1. Seng Loke, Context-Aware Computing Pervasive Systems, Auerbach Pub., New York,

2007.

http://www.amazon.com/dp/3540002189/ref=rdr_ext_tmb


http://www.amazon.com/s/ref=rdr_ext_aut?_encoding=UTF8&index=books&field-author=Lothar%20Merk

http://www.amazon.com/s/ref=ntt_athr_dp_sr_1/188-8313688-2368359?_encoding=UTF8&field-author=Jochen%20Burkhardt&search-alias=books&sort=relevancerank

60

Code: M16 CST 1213

DATA WAREHOUSING & MINING LAB



Credits : 2

COURSE OBJECTIVES:

1. Introduce data mining techniques including predictive, descriptive and visualization

modeling and their effective use in discovering interesting hidden patterns in large

volume of data generated by businesses, science, web, and other sources.

2. Focus is on the data preparation, classification, clustering, association analysis, and

pattern evaluation

COURSE OUTCOMES:




methods.





SYLLABUS

Scope: Lab Experiments using software like Clementine and Informatica or WeKa Tools

1. Demonstration of preprocessing on some datasets eg. Student.aarf/ labor.aarf/Iris/ loan/etc

2. Demonstration of Data Visualization using Weka/ SYSTAT/ R programming language

3. Demonstration of Association Rules extraction on Market basket data using apriori/ FP

Algorithms

4. Demonstration of Classification Rule extraction a bench mark dataset using j48/ID3

Algorithm

5. Demonstration of Classification Rule Process on any datasets using Navie Bayes

Algorithm

6. Demonstration of Classification Rule Process on any datasets using K-nearest Neighbor

classification Algorithm

7. Demonstration of partitional Clustering on any datasets using K-means Algorithm

8. Demonstration of Clustering on any datasets using simple K-medoids algorithm

9. Demonstration of Clustering rules process on any datasets of images using DB Scan

algorithm

10. Demonstration of Clustering rules process on any datasets using Birch Algorithm

TEXT BOOK:

1. Data Mining- Concepts and Techniques by Jiawei Han, Micheline Kamber and Jian

Pei – Morgan Kaufmann publishers – 3rd edition

61

REFERENCE BOOKS:

1. Data Mining Techniques, A.K.Pujari, University Press Data mining concepts by

Tan, Steinbech, and Vipin Kumar - Pearson Edu publishers

2. Data Mining – Introductory and Advanced by Margarett Dunham - Pearson Education

publishers

3. Data Warehousing for Real – world by Sam Annahory - Pearson Education publishers

62

Code: M16 CST 1214

OBJECT ORIENTED SOFTWARE ENGINEERING LAB (Common for M.Tech (CST, IT))



Credits : 2

COURSE OBJECTIVES:

1. To understand the Object oriented modelling using UML

2. To enable the student to get knowledge in SDLC

3. To give a detailed understanding of processes and techniques for building large object-

oriented software systems.

4. To develop skills to evolve object-oriented systems from analysis, to design, to

implementation

5. To develop skills to work as a team for developing a software project.

6. Introducing the various design approaches, models and metrics.

COURSE OUTCOMES:

1. Students can design and implement complex software solutions. and test and document

software.

2. They are capable of working as part of a software team and develop significant projects

SYLLABUS

1. The purpose of the Software Engineering Lab course is to familiarize the students with

modern software engineering methods and tools, Rational Products. The course is

realized as a project-like assignment that can, in principle, by a team of three/four

students working full time. Typically the assignments have been completed during the

semester requiring approximately 60-80 hours from each project team.

2. The goal of the Software Engineering Project is to have a walk through from the

requirements, design to implementing and testing. An emphasis is put on proper

documentation. Extensive hardware expertise is not necessary, so proportionate attention

can be given to the design methodology.

3. Despite its apparent simplicity, the problem allows plenty of alternative solutions and

should be a motivating and educating exercise. Demonstration of a properly functioning

system and sufficient documentation is proof of a completed assignment

4. Term projects are projects that a group student or might take through from initial

specification to implementation. The project deliverables include

Projects

1. Documentation including

a. A problem statement

b. A requirements document

2. A Requirements Analysis Document.

3. A System Requirements Specification.

4. A Software Requirements Specification.

5. A design document

a. A Software Design Description and a System Design Document.

6. A test specification.

63

7. Manuals/guides for

a. Users and associated help frames

b. Programmers

c. Administrators (installation instructions)

8. A project plan and schedule setting out milestones, resource usage and estimated

costs.

9. A quality plan setting out quality assurance procedures

10. An implementation.

REFERENCE BOOKS:

1. Project-based software engineering: An Object-oriented approach, Evelyn Stiller, Cathie

LeBlanc, Pearson Education

2. Visual Modelling with Rational Rose 2002 and UML, Terry Quatrini, Pearson

Education.

3. UML2 Toolkit, Hans -Erik Eriksson, etc; Wiley.

64

Code: M16 CST 1215

SEMINAR


Exam : 3 Hrs. Credits : 2

The viva-voce for the seminar shall be held with the faculty member, PG coordinator, and

Head of the Department. The marks shall be awarded in the ratio of 40, 20 and 40 percent by

the members respectively.

65




(Regulation:R16)


III SEMESTER


Marks

Total

Marks

M16CST2101 Thesis Work -

Preliminary 10 Review 100 100



industry/research organization, one advisor (Guide) should be from the department and

one advisor (CO-Guide) should be from the industry/research organization.

2. The Thesis Work -Preliminary should be submitted at the end of 3rd semester and it will

be evaluated through Review by a committee consisting of Head of the Department,

External Examiner, PG coordinator and guide. The marks shall be awarded in the ratio of

20, 40, 20 and 20 percent by the members respectively.

66




(Regulation:R16)


IV SEMESTER


Marks

Total

Marks

M16CST2201 Thesis Work-

Final 14 Viva-voce 100 100

1. A publication of a paper on the thesis work in a National/International Journal at the end

of 4th


2. The Thesis should be submitted at the end of 4th semester and it will be evaluated

through Viva–Voce examination by a committee consisting of Head of the Department,

External Examiner, PG coordinator and thesis guide. The marks shall be awarded in the

ratio of 20, 40, 20 and 20 percent by the members respectively.

9

DEPARTMENT OF ELECTRONICS AND COMMUNICATION ENGINEERING

M.TECH (COMMUNICATION SYSTEMS)


(Regulation:R16)


I - SEMESTER


Hrs

Lab

Hrs

Total

Contact

Hrs/

Week

Sessional

Marks

Exam

Marks

Total

Marks

M16 CS 1101 Communication

Theory 4 4 -- 4 30 70 100


Techniques 4 4 -- 4 30 70 100

M16 CS 1103 Satellite

Communication

and Phased Arrays

4 4 -- 4 30 70 100

M16 CS 1104 Digital signal

processing 4 4 -- 4 30 70 100

M16 CS 1105 Optical Fibers and

Applications 4 4

--

4 30 70 100

#1 Elective –I 4 4 --

4 30 70 100


Engineering Lab 2 - 4 4 50 50 100

M16 CS 1111 Seminar - I 2 - 3 3 100 -- 100

Total 28 24 7 31 330 470 800

Course Code Course

#1-Elective-I

M16 CS 1106 EMI/EMC

M16 CS 1107 Microwave Components and Networks

M16 CS 1108 Advanced Microprocessor

M16 CS 1109 Embedded Systems

10

Code: M16 CS 1101

COMMUNICATION THEORY



Credits : 4

COURSE OBJECTIVES:

1. To prepare mathematical background for communication signal analysis.

2. To understand the building blocks of Analog and digital communication system.

3. To understand and analyze the signal flow in Analog and digital communication system.

4. To present the essential digital communication concepts by understanding the elements of

digital communication system, fundamental concepts of sampling theorem.

5. To analyze error performance of a digital communication system in presence of noise and other

interferences.

6. To learn different estimation methods.

COURSE OUTCOMES:

Acquired knowledge about

1. AM transmission and reception

2. FM and PM transmission and reception, pulse modulation, noise

3. Digital communication, quantization, coding, digital modulation techniques, ISI

4. Different estimation methods.

SYLLABUS

Analog Communication: Mathematical treatment of Linear (AM, DSB-SC, SSB and VSB) and

exponential (PM and FM) modulation; spectra of angle modulated signals; Noise performance of

linear and exponential modulated signals; PE and DE in FM.

Pulse Modulation: Sampling of low-pass and band-pass signals, PAM, PWM, PPM,quantization,

PCM, DPCM, Delta modulation, base band digital communication; Nyquist pulse shaping, line

codes.

Digital Modulation Techniques: Representation of digital signal waveforms, Introduction to

digital modulation schemes- ASK, PSK and FSK; Digital demodulation and the optimal receiver,

performance of digital communication systems in the presence of noise, coherent quadrature

modulation techniques.

Detection and Estimation Theory: Binary hypothesis testing, Bayes, Minimax and Neyman-

Pearson tests; Bayesean parameter estimation, MMSE, MMAE and MAP estimation procedures.

11

TEXT BOOKS:

1. John G. Proakis and Masoud Salehi, ―Communication Systems Engineering,‖ Prentice-Hall,

2nd

Edition, 2002.

2. Fundamentals of Communication Systems, Proakis and Salehi, Prentice Hall

3. Simon Haykin, Communication Systems, John Wiley & Sons, NY 4th

edition 2001.

4. Herbert Taub & Donald L Schlling, Principles of Communication Systems, 3rd

edition, Tata

Mc Grawhill,2008.

REFERENCE BOOKS:

1. Communication Systems, Stern & Mahmoud, Prentice Hall

2. M. Simon, S. Hinedi, and W. Lindsey, ―Digital Communication Techniques,‖ Prentice-Hall,

1995

3. Bruce Carlson Communication Systems, 3rd

edition, Tata Mc Grawhill.

12

Code: M16 CS 1102

COMMUNICATION TECHNIQUES



Credits : 4

COURSE OBJECTIVES:

1. To understand the building blocks of digital communication system.

2. To prepare mathematical background for communication signal analysis.

3. To understand and analyze the signal flow in a digital communication system.

4. To present the essential digital communication concepts by understanding the elements of

digital communication system, fundamental concepts of sampling theorem and coding.

5. To analyze error performance of a digital communication system in presence of noise and other

interferences.

6. To understand concept of spread spectrum communication system.

7. To provide knowledge about error detection and correction, different types of channel coding

techniques such as linear block codes, cyclic code and convolution codes are to be discussed.

COURSE OUTCOMES:

After successfully completing the course students will be able to,

1. Analyze the performance of a baseband and pass band digital communication system in terms

of error rate and spectral efficiency.

2. Perform the time and frequency domain analysis of the signals in a digital communication

system.

3. Select the blocks in a design of digital communication system.

4. Select the relevant digital modulation technique for specific application.

5. Choose the coding technique for minimum errors in transmitting information.

6. Ability to use channel coding techniques (such as block & convolutional codes) in

communication systems. 7. Ability to use modulation techniques (such as frequency & phase-shift keying) in

communication systems.

8. Analyze Performance of spread spectrum communication system.

SYLLABUS

Channel Coding-I: Waveform coding and structured sequences-Types of error control, structured

sequences, Linear block codes –soft/hard decision decoding of linear block codes – Polynomial

representation of codes – Cyclic codes – Convolution codes – viterbi decoding algorithm.

Channel Coding-II: Non binary block codes and concatenated block codes - Reed Solomon codes

– Turbo codes.

13

Baseband Signaling Concepts: Signaling formats – RZ/NRZ, Duobinary splitphase (Manchester)

and high density bipolar coding – scrambling & unscrambling – channel equalization – tapped

delay line and traversal filters.

Synchronization: Receiver synchronization, costas loop, symbol synchronization, synchronization

with CPM – Data aided and Non aided synchronization- synchronization methods based on

properties of wide sense cyclo-stationary random process – Carrier recovery circuits – Symbol

clock estimation schemes.

Spread Spectrum Systems: PN sequences, DS spread spectrum systems; FH spread spectrum

systems and performance of FHSS in AWGN – Synchronization – Jamming considerations –

Commercial Applications – Cellular subsystems.

TEXT BOOKS:

1. Bernard sklar, ―Digital communications‖, Pearson Education Asia,2001.

2. Das,J Etal, ― Principles of Digital Communications and Spread spectrum Systems‖, Willey

Eastern Limited,1985.

3. Ziemer R E & Peterson R L, ―Digital Communication and Spread spectrum Systems‖,

McMillan publishing co., 1985.

REFERENCE BOOKS:

1. Proakis J G, ―Digital communications‖, McGraw Hill Inc, 1983.

2. Haykin,Simon.S. ,―Digital communications‖, John Wiley & Sons, 1988

14

Code: M16 CS 1103

SATELLITE COMMUNICATION AND PHASED ARRAYS



Credits : 4

COURSE OBJECTIVES:

1. To learn about the science behind the orbiting satellites, various multiplexing schemes and

earth station parameters used for satellite communication.

2. To learn about link budgets for uplink and downlink for both satellite communication and

mobile communication.

3. To understand knowledge regarding earth station equipment.

4. To know the operation of MSAT and VSAT networks and its applications.

5. To provide a brief introduction about phased array antennas.

COURSE OUTCOMES:

1. The students will learn the dynamics of the satellite in the orbit.

2. Understand communication satellite design and how analog and digital technologies are used

for satellite communication networks.

3. The students will be able to design satellite uplink and down link and calculate link budgets.

4. Understand the operation of Earth station equipment, MSAT and VSAT networks.

5. The students will understand the concept of phased arrays

SYLLABUS

Introduction: Kepler‘s Laws of motion, Orbital aspects of Satellite Communications, Look Angle

and Orbit determinations, Orbital effects in communication system Performance, Space craft

subsystems, AOCS, TTC&M, Power system, Satellite transponder, spacecraft Antennas,

Satellite Link Design-- System Noise temperature and G/T ratio - Design of downlink, Uplink -

Design of satellite links for specified C/N, Implementation of error Detection on satellite links.

Multiple Access: FDMA, TDMA, CDMA, SSMA- comparison of multiple access techniques,

Practical Demand Access systems, Multiple Access With on board processing.

Earth Station Technology: Earth Station Design, Design of Large Antennas, Tracking, Small

earth station Antennas, Equipment for earth station; Satellite Packet Communications- Message

transmission by FDMA: The M/G/1 Queue, Message transmission by TDMA - Pure ALOHA

Very small Aperture Terminal Networks: VSAT Technologies - Network Configurations,

Polling VSAT Networks; Mobile Satellite Networks--Operating Environment - MSAT Network

concept.

15

Phased Arrays in Radar and Communication Systems: System requirements for radar and

communication antennas, Array characterization for radar and communication systems,

Fundamental results from array theory.

TEXT BOOKS:

1. Satellite Communications by T. Pratt and C.W. Bostian, John Wiley & Sons

2. Digital Satellite Communication by Tri T. Ha , McGraw Hill Co.(2nd

edition )

3. Phased Array Antenna Hand Book – Robert J. Mailloux, Artech House, Boston, London,

1994.

REFERENCE BOOKS:

1. Satellite Communications - by Dr. D.C. Agarwal, khanna Publishers, NewDelhi

2. Electronic Communication Systems -by Tomasi. W, PHI

16

Code: M16 CS 1104

DIGITAL SIGNAL PROCESSING



Credits : 4

COURSE OBJECTIVES:

1. To learn about various optimization techniques used in designing the digital filters.

2. To learn about the sampling rate requirement in the digital signal applications

3. To learn about the need for prediction, filtering & smoothening of the signals to minimize the

mean-square error (MSE).

4. To learn different DSP algorithms used for DFT computation procedures.

5. To know the applications of DSP in real time.

COURSE OUTCOMES:

1. Using filter optimization techniques students will be able to design a filter with Least Mean

Square error.

2. Students will be able to solve research papers related to multirate signal processing— Data

Acquisition, Bandwidth reduction in a system etc.

3. Apply methods for prediction of real world signals, based on signal modeling and advanced

filtering techniques, such as Linear Predictive Filters and Optimal Linear Filters.

4. Apply fundamental principles, methodologies and techniques of the course to analyze and

design various problems encountered in academic research, industry and R&D practice.

5. This course is basis for understanding Adaptive signal processing, statistical signal processing

and wavelet transform subjects.

SYLLABUS

Advanced digital filter design techniques : Multiple band optimal FIR filters – design of filters

with simultaneous constraints in time and frequency response, optimization methods for designing

IIR filters, comparison of optimum FIR filters and delay equalized elliptic filters.

Multirate DSP : The basic sample rate alteration – time – domain characterization, frequency –

domain characterization : Cascade equivalences, filters in sampling rate alteration systems, digital

filter banks and their analysis and applications, multi level filter banks, estimations of spectra from

finite – duration observation of signals.

Linear prediction and optimum liner filters: forward and backward linear prediction, AR

Lattice and ARMA lattice – ladder filters, Wieners filters for filtering on prediction.

DSP Algorithms : The Goertzel algorithm, the chirp – z transform algorithm the Levinson –

Durbin algorithms, the Schur algorithm, and other algorithms, computations of the DFT, concept

of tunable digital filters.

17

Applications of DSP :

a) Speech : Model of speech production, speech analysis – synthesis system vocoder analyzers

and synthesizers, linear prediction of speech.

b) DTMF System

TEXT BOOKS :

1. Theory and applications of digital signal processing by Lawrence R. Rabiner and Bernard

Gold, PHI

2. Digital Signal Processing. Principles, algorithms, and applications by John G. Proakis and

Dimitris G. Manolakis, PHI, 1997.

3. Digital Signal Processing, A Computer – Based approach, by Sanjit K. Mitra, Tata Mc Graw-

Hill, 1998

REFERENCE BOOKS:

1. S.Salivahanan, A.Vallava Raj, C.Gnana Priya, Digital Signal Processing,TMH International

2007.

2. E.C.Ifeachor and B.W.Jervis ― Digital Signal Processing- A Practical approach‖, 2nd

edition

Pearson,2002.

18

Code: M16 CS 1105

OPTICAL FIBERS AND APPLICATIONS



Credits : 4

COURSE OBJECTIVES:

1. To expose the students to the basics of signal propagation through optical fibers, fiber

impairments, components and devices and system design.

2. To analyze the operation of LEDs, laser diodes, and PIN photo detectors (spectral properties,

bandwidth, and circuits) and apply in optical systems.

3. To explain the principles, compare and contrast single- and multi-mode optical fiber

characteristics.

4. To analyze and design optical communication and fiber optic sensor systems.

5. To design, build, and demonstrate optical fiber experiments in the laboratory.

6. To locate, read, and discuss current technical literature dealing with optical fiber systems.

COURSE OUTCOMES:

1. Recognize and classify the structures of Optical fiber and types.

2. Discuss the channel impairments like losses and dispersion.

3. Analyze various coupling losses.

4. Classify the Optical sources and detectors and to discuss their principle.

5. Familiar with Design considerations of fiber optic systems.

6. To perform characteristics of optical fiber, sources and detectors, design as well as conduct

experiments in software and hardware, analyze the results to provide valid conclusions.

SYLLABUS

Optic Fiber Waveguides: Step – Index Fiber, Graded – Index Fiber, Attenuation, Modes in Step-

Index Fibers, Modes in Graded – Index Fibers, Pulse Distortion and Information Rate in Optic

Fibers, Construction of Optic Fibers, Optic Fibers, Optic Fiber Cables.

Light Sources and Detectors : Light-Emitting Diodes, Light-Emitting – Diodes Operating

Characteristics, Laser Principles, Laser Diodes, Laser-Diode Operating Characteristics, Distributed

– Feedback Laser Diode, Optical Amplifiers, Fiber Laser, Vertical-Cavity Surface-Emitting Laser

Diode. Principles of Photo detection, Photomultiplier, Semiconductor Photodiode, PIN

Photodiode, Avalanche Photodiode.

Couplers and Connectors: Principles, Fiber end Preparation, Splices, Connectors, Source

Coupling, Distribution Networks and Fiber Components, Distribution Networks, Directional

Couplers, Star Couplers, Switches, Fiber Optical Isolator, Wavelength-Division Multiplexing,

Fiber Bragg Gratings, Other Components : Attenuator, Circulator and Polarization Controller.

19

Modulation, Noise and Detection: Light-Emitting-Diode Modulation and Circuits, Laser-Diode

Modulation and Circuits, Analog-Modulation Formats, Digital-Modulation Formats, Optic

Heterodyne Receivers, Thermal and Shot Noise, Signal-to-Noise Ratio, Error Rates, Modal Noise,

Amplifier Noise, Laser Noise, and Jitter, Additional Noise Contributors, receiver Circuit Design

System Design and Fiber Optical Applications: Analog System Design, Digital System Design,

Applications of Fiber Optics.

TEXT BOOK:

1. Fiber Optic Communications, Joseph. C. Palais, Pearson Education, Asia, 2002

REFERENCE BOOKS:

1. Fiber Optic Systems, John Powers, Irwin Publications, 1997

2. Optical Fiber Communication, Howes M.J., Morgen, D.V John Wiely

20

Code: M16 CS 1106

EMI / EMC



Credits : 4

COURSE OBJECTIVES:

1. To familiarize with the fundamentals those are essential for electronics industry in the field of

EMI / EMC

2. To understand EMI sources and its measurements.

3. To understand the various techniques for electromagnetic compatibility.

COURSE OUTCOMES:

At the end of the course the student will be able to learn the concepts of

1. Real-world EMC design constraints and make appropriate tradeoffs to achieve the most cost-

effective design that meets all requirements.

2. Designing electronic systems that function without errors or problems related to

electromagnetic compatibility

3. Diagnose and solve basic electromagnetic compatibility problems.

SYLLABUS

Introduction, Natural and Nuclear sources of EMI / EMC: Electromagnetic environment,

History, Concepts, Practical experiences and concerns, frequency spectrum conservations.

An overview of EMI / EMC, Natural and Nuclear sources of EMI.

EMI from apparatus, circuits and open area test sites: Electromagnetic emissions, noise from

relays and switches, non-linearities in circuits, passive intermodulation, cross talk in transmission

lines, transients in power supply lines, electromagnetic interference (EMI). Open area test sites and

measurements.

Radiated and conducted interference measurements and ESD: Anechoic chamber, TEM cell,

GH TEM Cell, characterization of conduction currents / voltages, conducted EM noise on power

lines, conducted EMI from equipment, Immunity to conducted EMI detectors and measurements.

ESD, Electrical fast transients / bursts, electrical surges.

Grounding, shielding, bonding and EMI filters :Principles and types of grounding, shielding

and bonding, characterization of filters, power lines filter design.

Cables, connectors, components and EMC standards :EMI suppression cables, EMC

connectors, EMC gaskets, Isolation transformers, optoisolators, National / International EMC

standards.

21

TEXT BOOKS:

1. Engineering Electromagnetic Compatibility by Dr. V.P. Kodali, IEEE Publication, Printed in

India by S. Chand & Co. Ltd., New Delhi, 2000.

2. Electromagnetic Interference and Compatibility IMPACT series, IIT –Delhi, Modules 1–9.

REFERENCE BOOKS:

1. Introduction to Electromagnetic Compatibility, Ny, John Wiley, 1992, by C.R. Pal.

2. EMI/EMC Computational modeling Hand book, 2nd

edition, Springer International series by

Archam Beault, Bruce,Ramahi,OmarM,Brench, Colin.

22

Code: M16 CS 1107

MICROWAVE COMPONENTS AND NETWORKS



Credits : 4

COURSE OBJECTIVES:

1. To explain the concepts of static electric fields, steady magnetic fields, Maxwell‘s Equations

and EM wave concepts.

2. To explain the operation of signal generators and waveguide components at Microwave

frequencies.

3. To analyze the operation of different waveguide components using scattering matrix.

4. To familiarize with the materials used and fabrication techniques of MMICs.

5. To gain an understanding with the experimental procedures involving measurements of

different Microwave parameters.

COURSE OUTCOMES:

After completing the course the student will be able to demonstrate the knowledge and will have

the ability to:

1. Explain the operation of different microwave signal generators and waveguide components.

2. Mathematically analyze the operation of different Signal generators.

3. Mathematically analyze the operation of different waveguide components using scattering

matrix.

4. Understand different fabrication techniques involving Microwave integrated circuits.

5. Understand and implement different experimental procedures involving measurement of

microwave parameters

SYLLABUS

Introduction: Microwaves and applications, advantages of microwaves, EM spectrum domain,

electric and magnetic fields static electric and magnetic fields, time varying electric and magnetic

fields, electromagnetic field equations, maxwell‘s equations for time-varying fields, meaning of

maxwell‘s equations, characteristics of free space, power flow by microwaves, expression for

propagation constant of a microwave in conductive medium, microwave applications, relation

between dB, dBm, dB.

Microwave Tubes: Limitation of conventional tubes, microwave tubes, velocity modulation,

method of producing the velocity modulation, principle of operation of two cavity klystron, reflex

klystron principle of operation, velocity modulation in reflex klystron, applegate diagram with gap

voltage for a reflex klystron. Principle of operation of magnetron, hull cutoff condition, advantages

of slow wave devices, principle of operation of TWT.

23

Microwave Semiconductor Devices: Microwave bipolar transistor, FET, Principle of Operation

and application of tunnel diode, Principle of operation of gunn diode, application of gunn diode

advantages of gunn diode, salient features of IMATT and TRAPATT diodes, applications of

IMATT and TRAPATT diodes, principle of operation of PIN diode, applications of PIN diode.

Scattering Matrix Parameters of microwave networks:Definition of scattering matrix,

characteristics of S-matrix, scattering matrix of a two-port network, salient features of S-matrix,

salient features of multiport network, losses in microwave circuits, return loss, insertion loss,

transmission loss, reflection loss, impedance matrix, short circuit admittance parameters of a -

network, S-matrix of series element in the transmission line, S-matrix for circulator, S-matrix for

isolator, S-matrix for E-plane Tee junction, S-matrix for H-plane Tee junctions, S-matrix for

directional coupler.

Microwave Passive components: Rectangular waveguides resonator isolator, types of attenuators,

fixed attenuators, step attenuators, variable attenuators, salient features of directional coupler,

parameters of directional coupler, coupling factor, directivity, applications of directional coupler.

Microwave Integrated Circuits: Salient features of MICs, types of electronic circuits, monolithic

microwave integrated circuits (MMICs), film integrated circuit, advantages of MMICs, Basic

materials used in MMIC fabrication, examples, characteristics and properties of substrate,

conductor, dielectric and resistive materials, MMIC fabrication techniques, diffusion and ion

implantation, oxidation and film deposition, epitaxial growth, lithography, etching and photo

resist, deposition methods, steps involved in the fabrication of MOSFET

Microwave measurements: Measurement of VSWR, attenuation, dielectric constant, calibration

of attenuator and Wave meter.

TEXT BOOKS:

1. ―Microwave Engineering‖ by Prof. GSN Raju, IK International Publishers, 2007

2. ―Microwave Engineering‖ by P.A. Rizzi, PHI, 1999.

REFERENCE BOOKS:

1. ―Microwave Engineering : Non-reciprocal active and passive circuits‖ by Joseph Helszajin,

McGraw Hill, 1992.

2. Microwave Engineering by David M.Pozar, 4th Edition, Wiley,2012.

24

Code: M16 CS 1108

ADVANCED MICROPROCESSOR



Credits : 4

COURSE OBJECTIVES:

1. To study about the architecture, pin configuration, timing diagrams and addressing modes of

8086.

2. To study about the instruction sets, Assembler Directives and operators and to acquire the

knowledge of programming.

3. To study about the Interrupts of 8086/8088.

4. To study about architecture, Pin-out of 80186 microprocessor, Timing (Read / Write cycles) of

80186.

5. To study about the introduction of 80386, 80486 and Pentium Processor.

COURSE OUTCOMES:

1. After completing of this subject students will learn the basics of 16 bit microprocessor.

2. Understanding the microprocessor architecture assembly language programming.

3. They are able to conclude the delays for 8086.

8086/8088 Microprocessor: Register organization of 8086,architecture, Physical memory

organization, I/O addressing capability, Minimum mode and Maximum mode system and timings,

addressing modes of 8086

8086/8088 Instruction set: Machine Language Instruction formats, Instruction set of 8086/8088,

Assembler Directives and operators, Machine level programming, assembly language

programming.

Special architectural features and related programming: Stack structure of 8086, Interrupts

and Interrupt service routines, Interrupt cycle of 8086/8088, Non maskable interrupts, maskable

interrupt (INTR), Interrupt Programming, MACROS, Timing and Delay

80186 and 80286 16 bit microprocessors: 80186/80188 architecture, Pin-out of 80186

microprocessor, Programming the 80186/80188 enhancements, 80186/80188 Timing (Read / Write

cycles) ,80186 programmable interrupt controller and DMA Controller , Internal Architecture of

80286

80386/80486 Microprocessors: Introduction to 80386 microprocessor, Special 80386 registers,

Memory management, moving to protected mode, Virtual 8086 mode, Memory paging

mechanism, Introduction to 80486 and Pentium Processor.

25

TEXT BOOKS:

1. Advanced microprocessors and peripherals, A.K.Ray & K.M.Bhurchandi, Tata McGraw Hill

publications co.ltd, New Delhi Twentieth reprint-2006

2. The INTEL Microprocessors , Barry B Bray,& C.R.Sarma, Pearson Education Ltd, New Delhi,

First Indian reprint-2005

REFERENCE BOOKS:

1. The Intel microprocessors 8088/80186,80188,80286,80386,80486,Pentium and Pentium- pro

processor Architecture , Programming and Interface by Barray B.Berry, 4th

Edition, PHI

2. Microprocessors and interfacing Programming and Applications by Douglas V.Hall, Mc

Graw Hill.

3. Microprocessors / Microcomputers Architecture, Software and Systems by A.J.Khambata,

John Wiely & Sons.

26

Code: M16 CS 1109

EMBEDDED SYSTEMS



Credits : 4

COURSE OBJECTIVES:

1. To introduce students to the modern embedded systems and to show how to understand and

program such systems using a concrete platform.

2. Students have knowledge about the basic functions of embedded systems.

3. Students have knowledge about the applications of embedded systems.

4. Students have knowledge about the development of embedded software.

COURSE OUTCOMES:

Students are able to

1. Describe the differences between the general computing system and the embedded system,

also recognize the classification of embedded systems.

2. Discuss the basics of embedded systems and the interface issues related to it.

3. Learn the different techniques on embedded systems.

4. Discuss the real time models, languages and operating systems.

5. Analyze real time examples.

SYLLABUS

Introduction to Embedded Systems : An embedded system – processor in the system –

Hardware units – software embedded into a system – exemplary embedded systems – embedded

system – on-chip and in VLSI circuit.

Processor and Memory Organization : structural units in a processor – processor selection for an

embedded system – memory devices – memory selection for an embedded system – allocation of

memory to program segments and blocks and memory map of a system – direct memory access –

interfacing processor, memories and I/O devices.

Devices & Buses for Device Networks : I/O devices – timer & counting devices – serial

communication using the ‗I2C‘, ‗CAN‘ and advanced I/O buses between the networked multiple

devices – host system or computer parallel communication between the networked I/O multiple

devices using the ISA, PCI, PCI-X and advanced buses.

Device Drivers and Interrupts Servicing Mechanism : Device drivers – parallel port device

drivers in a system – serial port device drivers in a system – device drivers for internal

programmable timing devices – interrupt servicing mechanism – context and the periods for

context switching, deadline and interrupt latency.

27

Programming Concepts and Embedded Programming in ‘C’ : Software programming in

assembly language (ALP) and in high level language ‗C‘ – ‗C‘ program elements : Header and

source files and preprocessor directives – program elements : macros and functions – data types,

data structures, modifiers, statements, loops and pointers – Queues – stacks – lists and ordered lists

– ‗C‘ program compiler and cross compiler – optimisation of memory needs.

Program modeling concepts in single and multiprocessor systems software-development

process: Modeling processor for software analysis before software implementation –

programming models for event controlled or response time constrained real time program –

modeling of multiprocessor systems.

TEXT BOOKS:

1. Embedded Systems : Architecture, programming and design by Raj Kamal, Tata McGraw Hill,

2003

REFERENCE BOOKS:

1. Embedded System Design : Real world design by Steve Heath, Butter – Worth Heinemann,

Newton Mass, USA, May 2002.

2. An introduction to the design of small scale embedded systems with examples from PIC, 8051

and 68HC 05/08 Micro controllers by Tin Wilmshurst, Palgrave, Great Britain, 2001.

3. The 8051 microcontroller and embedded systems by M. Ate Mazidi and J.G. Mazidi, Pearson

Education, 2002.

28

Code: M16 CS 1110

COMMUNICATION ENGINEERING LAB



Credits : 2

COURSE OBJECTIVES:

1. To practice the basic theories of communication system.

2. To provide hands‐on experience to the students, so that they are able to apply theoretical

concepts in practice.

3. To use computer simulation tools such as MATLAB to carry out design experiments as it is a

key analysis tool of engineering design.

4. To give a specific design problem to the students, which after completion they will verify using

the simulation software or hardware implementation.

COURSE OUTCOMES:

1. Graduate will demonstrate the ability to identify, formulate and solve Communication


2. Graduate will demonstrate the ability to design and conduct experiments, analyze and interpret

data.

3. Graduates will demonstrate the ability to design a Communication system or process as per

needs and specifications

4. Graduate will demonstrate the skills to use modern engineering tools, softwares and equipment

to analyze problem.

LIST OF EXPERIMENTS:

1. Time Division Multiplexing of signals & Framing in the TDM

2. Study of Manchester Coder – Decoder

3. Forming a PC to PC Communication Link using Optical Fider and RS 232 interface

4. Measurement of various losses in an Optical Fiber

5. Measure the Scattering parameters of the devices: Circulator & Hybrid TEE

6. Study of Antenna Radiation Patterns of E-Plane and H-Plane radiation patterns of a Pyramidal

Horn using a PC-based Antenna Trainer kit.

7. Measurement of Q-factor of cavity resonator

8. Simulation of Digital Communication Modulators/ Demodulators using MATLAB-

SIMULINK

9. Simulation of Channel coding/decoding using MATLAB- SIMULINK

10. Spectrum Analysis using Spectrum Analyzer

11. Study of Cellular communications Systems

12. Study of Satellite communication Receiver

29

REFERENCE BOOKS:

1. Communication Systems by Simon Haykin, Wiley.

2. Antenna Theory Analysis and Design by Constantine A Balanis, 3rd

edition, Wiley.

3. Microwave Engineering by GSN Raju, IK International Publishing House.

4. Satellite Communications 2nd

edition Timothy Pratt, Charles W.Bostian, Jeremy E.Allnutt,

Wiley.

5. Wireless Communication Principles and Practice by Theodore S. Rappaport, 2nd

edition,

Printice Hall.

30

Code: M16 CS 1111 SEMINAR-I



The viva-voce for the seminar shall be held with the faculty member, PG coordinator, and Head of

the Department. The marks shall be awarded in the ratio of 40, 20 and 40 percent by the members

respectively.

.

31




(Regulation:R16)


II – SEMESTER


Hrs

Lab

Hrs

Total

Contact

Hrs/

Week

Sessional

Marks

Exam

Marks

Total

Marks

M16 CS 1201 RF and Microwave

Engineering 4 4 -- 4 30 70 100

M16 CS 1202 Cellular and Mobile

Communications 4 4 -- 4 30 70 100

M16 CS 1203 GPS and

Applications 4 4 -- 4 30 70 100

M16 CS 1204 Telecommunication

Switching and

Networks

4 4 -- 4 30 70 100

#2 Elective - II 4 4 --

4 30 70 100

#3 Elective – III 4 4 --

4 30 70 100

M16 CS 1213 Digital Signal

Processing Lab 2 - 4 4 50 50 100

M16 CS 1214 Seminar - II 2 - 3 3 100 -- 100

Total 28 24 7 31 330 470 800

Course Code Course

#2-Elective-II

M16 CS 1205 Modeling and Simulation of Communication Systems

M16 CS 1206 Modern Radar Systems

M16 CS 1207 Digital Image Processing

M16 CS 1208 VLSI Design

#3-Elective-III

M16 CS 1209 Application Specific Integrated Circuits (ASIC)

M16 CS 1210 Multimedia Communication Systems

M16 CS 1211 Wavelet Transforms and Its Applications

M16 CS 1212 Statistical Signal Processing

32

Code: M16 CS 1201

RF AND MICROWAVE ENGINEERING



Credits : 4

COURSE OBJECTIVES:

1. RF and Microwave Engineering introduces the student to RF/microwave analysis methods and

design techniques. Scattering parameters are defined and used to characterize devices and

system behavior.

2. Passive and active devices commonly utilized in microwave subsystems are analyzed and

studied.

3. Design procedures are presented along with methods to evaluate Matching networks using

Smith chart.

4. Analytical techniques are presented for designing of Amplifiers and oscillators at RF and

microwave frequencies.

COURSE OUTCOMES:

1. Gain knowledge and understanding of microwave analysis methods.

2. Be able to apply analysis methods to determine circuit properties of passive/active microwave

devices.

3. Know how to model and determine the performance characteristics of a microwave circuit or

system using Smith chart..

4. Be able to design microwave amplifiers and oscillators for required parameters such as

stability, gain , noise.

SYLLABUS

Introduction to RF and Microwave concepts and applications: Introduction, Reasons for using

RF/Microwaves, RF/Microwave applications, Radio frequency waves, RF and Microwave circuit

design, The unchanging fundamentals versus the ever-evolving structure, General active circuit

block diagrams.

RF Electronics Concepts: Introduction, RF/Microwaves versus DC or low AC signals, EM

spectrum, Wave length and frequency, Introduction to component basics, Resonant circuits,

Analysis of a simple circuit in phasor domain, Impedance transformers, RF impedance matching,

Three element matching.

Smith Chart and its Applications: Introduction, A valuable graphical aid the smith chart,

Derivation of smith chart, Description of two types of smith charts, Smith charts circular scales,

Smith charts radial scales, The normalized impedance-admittance (ZY) smith chart introduction,

Applications of the smith chart, Distributed circuit applications, Lumped element circuit

applications.

33

RF and Microwave Amplifiers Small and Large Signal Design: Introduction, Types of

amplifiers, Small signal amplifiers, Design of different types of amplifiers, Multistage small signal

amplifier design. Introduction, High-power amplifiers, Large signal amplifier design, Microwave

power combining/dividing techniques, Signal distortion due to inter modulation products,

Multistage amplifiers, Large signal design.

Radio Frequency and Microwave Oscillator Design: Introduction, Oscillator versus amplifier

design, Oscillation conditions, Design of transistor oscillators, Generator-tuning networks.

TEXT BOOK:

1. ―Radio Frequency and Microwave Electronics‖, by Mathew M. Radmanesh, Pearson

Education Inc., New Delhi

REFERENCE BOOKS:

1. ―Microwave Engineering, Active and Non-reciprocal Circuits‖, by Joseph Helszain, McGraw

Hill International Edition, 1992

2. RF & Microwave Engineering : Fundamentals of wireless communications, Frank Gustrau

2012, Wiley.

34

Code: M16 CS 1202

CELLULAR AND MOBILE COMMUNICATIONS



Credits : 4

COURSE OBJECTIVES:

1. Understand the cellular radio concepts such as frequency reuse, handoff and how interference

between mobiles and base stations affects the capacity of cellular systems.

2. Identify the techno-political aspects of wireless and mobile communications such as the

allocation of the limited wireless spectrum by government regulatory agencies.

3. To have an overview of wireless and mobile communications in different generations.

4. To study the operation of basic cellular system and performance criterion, handoff mechanism.

5. To study the design of cellular mobile system.

6. Understand propagation effects such as fading, time delay spread, and Doppler spread, and

describe how to measure and model the impact that signal bandwidth and motion have on the

instantaneous received signal through the multipath channel.

7. Understand the information theoretical aspects (such as the capacity) of wireless channels and

basic spread spectrum techniques in mobile wireless systems

8. Describe current and future cellular mobile communication systems (GSM, IS95, WCDMA,

etc), wireless LANs, adhoc and sensor networks

9. To develop the ability to search, select, organize and present information on new technologies

in mobile and cellular communications

COURSE OUTCOMES:

1. Understand the cellular radio concepts such as frequency reuse, handoff and how interference

between mobiles and base stations affects the capacity of cellular systems.

2. Students are capable to analyze and solve problems in the field of telecommunications.

3. Students will have the understanding of different generations, operations and design of wireless

and mobile communications.

4. Understand the concept of frequency Reuse channels, Deduce the Co-channel interference

reduction factor.

5. Design of Antenna system to reduce Co-channel interference. Understand adjacent channel

interference, near end far end interference

6. Understand cell site and mobile antennas. Understand frequency management and channel

assignment strategies

7. Define Handoff, Distinguish types of handoffs and evaluation of dropped call rates.

8. Understand propagation effects such as fading, time delay spread, and Doppler spread, and

describe how to measure and model the impact that signal bandwidth and motion have on the

instantaneous received signal through the multipath channel.

9. Understand the information theoretical aspects (such as the capacity) of wireless channels and

basic spread spectrum techniques in mobile wireless systems

35

SYLLABUS

Introduction to wireless communications, examples of wireless communication system, the

Cellular concept and system design fundamentals, Frequency reuse, Channel assignment

strategies, Handoff strategies, Interfearance and system capacity, Trunk and grade services,

Methods for improving coverage and capacity in cellular system .

Multiple access techniques for wireless communications FDMA , TDMA , Spread spectrum

techniques, SDMA, Packet Radio, CSMA, Capacity of cellular CDMA with multiple cells and

capacity of SDMA.

Wireless systems and standards, AMPS, IS-94, GSM traffic, Examples of GSM cell, Frame

structure of GSM cell, details of forward and reverse CDMA channels.

Personal access communication systems, Personal Mobile satellite communications, Integrating

GEO, LEO, MEO Satellite and terrestrial mobile systems, Rake receiver

Mobile Radio propagation, Large scale path loss, Reflection, Diffraction, Scattering, Outdoor and

Indoor propagation models, Small signal fading and multi path , measurement of small scale path

loss, parameters of multi path channels, fading due to multi path, small scale fading models .

TEXT BOOKS:

1. Wireless Communications Principles and Practice, Second Edition, THEODORE

S.RAPPAPORT , PHI

2. Wireless Digital Communications, Dr. KAMILO FEHER, PHI

3. Electronic Communication System, WAYNE TOMASI, PHI

4. Wireless Communications, SANJY SHARMA, S.K Kataria & sons

REFERENCE BOOKS:

1. Mobile Cellular Tele Communications-W.C.Y.Lee TMH, 2nd

edition 2006.

2. Mobile Cellular Communication, G.Sasibhushan Rao,Pearson Pub.

36

Code: M16 CS 1203

GLOBAL POSITIONING SYSTEM AND APPLICATIONS



Credits : 4

COURSE OBJECTIVES:

1. To enable student to understand the basic principle of GPS

2. To enable student to understand the difference between GPS, GALILEO and GLONASS

3. To familiarize the student with the concepts of different co-ordinates system used in GPS

4. To enable student to know about the effect of ionosphere and troposphere on GPS position

determination

COURSE OUTCOMES:

1. Students can describe each of the 3 main segments of GPS/GNSS: Space (the three

components of the satellite signal), Control (worldwide control stations) and User (the

receiver).

2. Students can understand the history of NAVSTAR GPS and other GNSS systems and be able

to compare their characteristics: the number of operational satellites, number of orbital planes,

orbit shape, orbit inclination, orbital period and satellite altitude.

3. Students can understand how trilateration is used to determine a user‘s location with a GPS and

how to calculate pseudorange.

4. Students understand the different accuracies of consumer, mapping and survey grade GPS units

and their respective research applications.

SYLLABUS

Overview of GPS : Basic concept, system architecture, space segment, user segment, GPS aided

Geo-augmented navigation (GAGAN) architecture.

GPS Signals : Signal structure, anti spoofing (AS), selective availability, Difference between GPS

and GALILEO satellite construction.

GPS coordinate frames, Time references : Geodetic and Geo centric coordinate systems, ECEF

coordinate world geodetic 1984 (WGS 84), GPS time.

GPS orbits and satellite position determination : GPS orbital parameters, description of receiver

independent exchange format (RINEX) – Observation data and navigation message data

parameters, GPS position determination.

37

GPS Errors : GPS error sources – clock error, ionospheric error, tropospheric error, multipath,

ionospheric error estimation using dual frequency GPS receiver.

TEXT BOOK:

1. B. Hoffman – Wellenhof, H. Liehtenegger and J. Collins, ‗GPS – Theory and Practice‘,

Springer – Wien, New York (2001).

REFERENCE BOOKS:

1. James Ba – Yen Tsui, ‗Fundamentals of GPS receivers – A software approach‘, John Wiley &

Sons (2001).

2. Understanding GPS: Principles and Applications by Elliot D.Kaplan, Christopher.J.Hegarty 2nd

edition , Artech House.

38

Code: M16 CS 1204

TELECOMMUNICATION SWITCHING AND NETWORKS



Credits : 4

COURSE OBJECTIVES:

1. To learn basics of switching systems and design of different switching systems.

2. To understand and designing of multistage networks

3. To understand different switching systems such as electronic space division switching and time

division switching

4. To understand different signaling techniques and networks and topologies.

5. To understand the overall data communication and switching networks.

COURSE OUTCOMES:


1. Understand the complete switching system.

2. Understand the probabilistic methods and statistics to solve communication network problems.

3. Understand effectively the communication principles to design, develop and implement

communication networks.

4. Understand the complete system of communication and switching networks.

SYLLABUS

Resource sharing and need for switching: Circuit switching, Store and forward switching,

Packet switching, electronic space division switching, Need for networks, two stage networks,

three stage networks and n-stage networks.

Time Division Switching: Time switching, space switching, three stage combination switching, n-

stage combination switching; Traffic engineering: Hybrid switching, Erlang formula and signaling.

High speed digital access: DSL technology, Cable Modem, SONET.

Local area networks: Traditional ETHERNET, fast ETHERNET, Gigabit ETHERNET, Wireless

LAN, Bluetooth, Connecting LAN‘s, Backbone networks.

Integrated Services Digital Network: Network & protocol architecture, user network interfaces,

signaling, inter networking, expert systems in ISDN, Broadband ISDN.

TEXT BOOKS:

1. Telecommunication Switching Systems and Networks- Thiagarajan Viswanathan, Prentice

Hall, New Delhi, 2001.

2. Data Communications and Networking- B.A. Forouzan, Tata McGrawhill, Third Edn., 2004.

REFERENCE BOOKS:

1. J.E.Flood,‖Telecommunications Switching Traffic & Networks‖ Pearson.

2. John C. Bellamy, ―Digital Telephony‖, 3rd

edition, Wiley Publications.

39

Code: M16 CS 1205

MODELLING AND SIMULATION OF COMMUNICATION SYSTEMS



Credits : 4

COURSE OBJECTIVES:

1. Describe, investigate and analyze complex engineering systems and associated issues (using

systems thinking and modeling techniques)

2. Comprehend and apply advanced theory-based understanding of engineering fundamentals and

specialist bodies of knowledge in the selected discipline area to predict the effect of

engineering activities

3. Apply underpinning natural, physical and engineering sciences, mathematics, statistics,

computer and information sciences.

4. Develop creative and innovative solutions to engineering challenges.

COURSE OUTCOMES:

Upon successful completion of this course student should be able to

1. Characterize a given engineering system in terms of its essential elements, that is, purpose,

parameters, constraints, performance requirements, subsystems, interconnections and

environmental context.

2. Develop a modeling strategy for a real world engineering system, which considers prediction

and evaluation against design criteria, and integrates any required sub-system models.

3. Assess and select a model for an engineering system taking into consideration its suitability to

facilitate engineering decision making and predicted advantages over alternative models.

4. Interpret the simulation results of an engineering system model, within the context of its

capabilities and limitations, to address critical issues in an engineering project.

SYLLABUS

Simulation of Random Variables and Random Process: Univariate and multi-variate models,

Transformation of random variables, Bounds and approximation, Random process models-Markov

AND ARMA sequences, Sampling rate for simulation, Computer generation and testing of random

numbers.

Modeling of Communication Systems: Information Sources, Formatting/Source Coding, Digital

Waveforms, Line Coding, Channel Coding, Radio frequency and Optical Modulation,

Demodulation and Detection, Filtering, Multiplexing/Multiple Access, Synchronization,

Calibration of Simulations.

Communication Channels & Models: Fading & Multipath Channels, Almost Free-Space

Channels, Finite State Channel Models, Methodology for Simulating Communication Systems

Operating over Fading Channels, Reference Models for Mobile Channels: GSM, UMTS-IMT-

2000.

40

Estimation of Parameters in Simulation: Quality of an estimator, Estimating the Average Level

of a Waveform, Estimating the Average power of a waveform, Estimating the Power Spectral

Density of a process, Estimating the Delay and Phase.

Estimation of Performance Measures from Simulation: Estimation of SNR, Performance

Measures for Digital Systems, Importance sampling method, Efficient Simulation using

Importance Sampling, Quasi analytical Estimation. Case Studies: 16-QAM Equalized Line of

Sight Digital Radio Link, CDMA Cellular Radio System.

TEXT BOOKS:

1. William H. Tranter, K. Sam Shanmugan, Theodore S. Rappaport, Kurt L. Kosbar, ―Principles

of Communication Systems Simulation with Wireless Applications‖, Prentice Hall PTR, 2002.

2. John G. Proakis, Masoud Salehi, Gerhard Bauch, Bill Stenquist, Tom Ziolkowski,

―Contemporary Communication Systems Using MATLAB‖ Thomson-Engineering, 2 edition,

2002.

REFERENCE BOOKS:

1. M.C. Jeruchim, Philip Balaban and K.Sam Shanmugam, ―Simulation of Communication

Systems, Modeling, Methodology and Techniques‖, Kluwer Academic/Plenum Publishers,

New York, 2000.

2. C. Britton Rorabaugh, ―Simulating Wireless Communication Systems: Practical Models In

C++‖ Prentice Hall, 2004.

41

Code: M16 CS 1206

MODERN RADAR SYSTEMS



Credits : 4

COURSE OBJECTIVES:

1. To become familiar with fundamentals of RADAR.

2. To gain in depth knowledge about the different types of RADAR and their operations.

3. To explain signal detection in RADAR and various detection techniques.

4. To become familiar with RADAR navigation techniques.

COURSE OUTCOMES:

After completing the course the student will be able to

1. Explain fundamentals of Surveillance Radar and Design.

2. Understand and analyze the operation of different tracking Radars.

3. Understand and explain the waveform design concepts of Radars.

4. Explain Principles of Secondary Surveillance Radar.

SYLLABUS

Fundamentals of Surveillance Radar and Design :

Bandwidth considerations, prf, Unambiguious range and velocity, Pulse length and Sampling,

Radar Cross-section and Clutter.

Tracking Radar :

Tracking and Search Radars, Antenna beam shapes required, Radar guidance, Frequency agility,

Importance of Monopulse Radar.

Radar waveform design :

Bandwidth and pulse duration requirements, Range and Doppler accuracy uncertainty relation,

pulse compression and phase coding.

Principles of Secondary Surveillance Radar:

Radar studies of the atmosphere, OHR and Radar jamming, EC, ECC measures and stealth

applications.

TEXT BOOKS:

1. ―Understanding of Radar Systems‖, Simon Kingsley and Shaun Quegan, McGraw Hill, 1993.

2. Radar Handbook by Skolnik.

REFERENCE BOOKS:

1. M.A.Richards et al, Principles of modern Radar ,Basic Principles Vol1,1st editionScitech2010

2. Hamish Meikle, Modern Radar Systems, 2nd

edition, Artech House.

42

Code: M16 CS 1207

DIGITAL IMAGE PROCESSING



Credits : 4

COURSE OBJECTIVES:

1. To introduce techniques and tools for digital image processing.

2. To introduce image analysis techniques in the form of image segmentation.

3. To develop on-hand experience in applying tools to process images.

4. To develop engineering skills and intuitive understanding of the tools used in Image

Processing.

COURSE OUTCOMES:

At the end of the course, the student will be able to

1. Describe different modalities and current techniques in image acquisition

2. Describe how digital images are represented and stored efficiently depending on the desired

quality, color depth, dynamics

3. Use the mathematical principles of digital image enhancement

4. Describe and apply the concepts of feature detection and contour finding algorithms.

5. Analyze the constraints in image processing when dealing with larger data sets.

SYLLABUS

Digital Image Fundamentals : An image model – sampling & quantization – basic relation

between pixels : imaging geomentry.

Image Transforms: Properties of 2-D fourier transforms, FFT algorithm and other separable

image transforms, Walsh transforms, Hadamard, Cosine, Haar, Slant Transforms, RL Transforms

and their properties.

Image Enhancement & Restoration:Spatial domain methods, Frequency domain methods,

Histogram Modification technique, Neighborhood averaging, Median filtering, Low pass filtering,

Averaging of Multiple Images, Image sharpening by differentiation, High pass Filtering,

Degradation model for Continuous functions, Discrete Formulation, Diagonalization of Circulant

and Block – Circulant Matrices, Effects of Diagonalization, Constrained and unconstrained

Restorations Inverse filtering, Wiener Filter, Constrained least Square Restoration.

Image Encoding: Objective an subjective Fidelity Criteria, the encoding process, the Mapping,

the Quantizer and the Coder, Contour Encoding, Run length Encoding, Image Encoding relative to

a Fidelity Criterion, Differential Pulse Code Modulation, Transform Encoding.

43

Image Compression: Fundamentals, Image compression models, error free compression, lossy

compression, image compression standards.

Image Segmentation: The detection of Discontinuities, Point Line and Edge Detections, Gradient

Operators, Combined Detection, Thresholding.

Image Representation: Representation Schemes, Chain Codes, Polygon Approximation,

Boundary Descriptors, Simple Descriptors, Shape Numbers, Fourier Descriptors.

Image Construction from Projections: Radon Transforms, Convolution/filterback Projection.

TEXTBOOKS:

1. Gonzalez RC & Woods RE, Digital Image Processing, Addison Wesley Publishing Company.

2. Jain AK, Fundamentals of Digital Image Processing, PHI

3. Rosefeld & Kak AC, Digital Picture Processing Academic Press Inc.

REFERENCE BOOKS:

1. Kenneth R.Castleman, Digital Image Processing, Pearson 2006

2. William K.Pratt, Digital Image Processing, John Wiley, New York 2002

44

Code: M16 CS 1208

VLSI DESIGN



Credits : 4

COURSE OBJECTIVES:

1. To Study the basics of NMOS, PMOS AND CMOS technologies along with construction,

types, working, characteristics and fabrication and the combination of Bipolar and MOS

technology and design of logic gates using nMOS, pMOS, CMOS technologies, stick diagrams

and layouts.

2. To study Analog VLSI circuits, MOS Multipliers, MOS Resistors, Opamp design in CMOS

and Bipolar Configurations

3. To study the design of combinational circuits, power consumption in CMOS circuits, different

design techniques to reduce switching activity

4. To study the Data Path Operations ,Addition/Subtraction ,Parity Generators, Comparators,

Zero/One Detectors ,Binary Counters, ALUs, Multiplication ,Shifters- Memory elements,

control Finite-State Machines- Control Logic Implementation in CMOS sub system design

5. To study the Logic synthesis, simulation and testing, basic features of VHDL language, types

of simulations, boundary scan test- fault simulation- automatic test pattern generation.

COURSE OUTCOMES:

1. After completing of this subject, students will learn the basics of MOS and CMOS

technologies.

2. They will be able to design combinational logic circuits using MOS and CMOS technologies

and develop stick and layout diagrams with design rules.

3. They can also calculate equivalent resistances and capacitances of circuits and estimate power

consumption and delay.

4. They will be able to use Switch logic or Gate logic in their design projects.

5. They will be able to design the Combinational and Sequential circuits by using VHDL

Language.

SYLLABUS

Introduction To MOS Device: MOS Transistor-First Glance at the MOS device MOS Transistor

under static conditions-threshold voltage-Resistive operation-saturation region –channel length

modulation-velocity saturation-Hot carrier effect-drain current Vs voltage charts – sub threshold

conduction – equivalent resistance-MOS structure capacitance-Design A logic sates using NMOS

and PMOS and CMOS devices-Stick Diagram.

45

Analog VLSI Circuits: Continuous-Time Signal Processing: Primitive Analog Cells-Linear

Voltage-Current Converters-MOS Multipliers-MOS Resistors-Winner-Take-All Circuits-

Amplifier-Based Signal Processing. Low-Voltage Signal Processing: CMSO Operational

Amplifier Design-Bipolar Operational Amplifier.

Design of Combinational Logic Gates In CMOS: Static CMOS design-complementary CMOS –

static properties A complementary CMOS design-Power consumption in CMOS logic gates-

dynamic or glitching transitions – Design techniques to reduce switching activity – Radioed logic-

DC VSL - pass transistor logic – Differential pass transistor logic sizing of level restorer-sizing in

pass transistor-Dynamic CMOS design-Basic principles - Domino logic-optimization of Domino

logic-NPCMOS-How to choose a logic style -Designing logic for reduced supply voltages.

CMOS Sub System Design: Data Path Operations: Addition/Subtraction- Parity Generators-

Comparators- Zero/One Detectors- Binary Counters- ALUs- Multiplication- Shifters- Memory

elements- control: Finite-State Machines- Control Logic Implementation.

Logic Synthesis, Simulation and Testing: Basic features of VHDL language for behavioral

modeling and simulation- summary of VHDL data types- Dataflow and structural modeling-

VHDL and logic synthesis- types of simulation- boundary scan test- fault simulation- automatic

test pattern generation.

TEXT BOOKS:

1. Pucknell & Eshraghian : Basic VLSI Design, PHI, (3/e), 1996.

2. Jan.M.Rabaey, Anitha Chandrakasan Borivoje Nikolic, ―Digital Integrated Circuits‖ second

Edition, PHI

3. Neil H.E Weste and Kamran Eshraghian, "Principles of CMOS VLSI Design‖, 2nd Edition,

Addition Wesley, 1998.

REFERENCE BOOKS:

1. Jacob Backer, Harry W.Li and David E.Boyce, CMOS Circuit Design, Layout and simulation,

Prentice Hall of India, 1998.

2. Mohammed Ismail, Terri Fiez, ―Analog VLSI signal and Information Processing", McGraw-

Hill International Editons, 1994.

46

Code: M16 CS 1209

APPLICATION SPECIFIC INTEGRATED CIRCUITS (ASIC)



Credits : 4

COURSE OBJECTIVES:

1. The course focuses on the semi custom IC Design and introduces the principles of design logic

cells, I/O cells and interconnect architecture, with equal importance given to FPGA and ASIC

styles.

2. The entire FPGA and ASIC design flow is dealt with from the circuit and layout design point

of view

3. Deals with the supply circuit modules which are crucial modules in an IC design.

4. Clock generation circuits play a major role in High Speed Broad Band Communication

circuits, High Speed I/O‟s, Memory modules and Data Conversion Circuits.

5. This course focuses on the design aspect of Clock Generation circuits and their design

constraints.

COURSE OUTCOMES:

After completing this course:

1. The student would have gained knowledge in the circuit design aspects at the next transistor

and block level abstractions of FPGA and ASIC design. In combination with the course on

CAD for VLSI, the student would have gained sufficient theoretical knowledge for carrying

out FPGA and ASIC designs.

2. Essential know how to a designer to construct Supply reference circuits and Clock Generation

Circuits for given design specifications and aids the designer to understand the design

specifications related to Supply and Clock Generation Circuits.

SYLLABUS

Introduction to ASICs: Types of ASICs, Design flow, Economics of ASICs, ASIC cell libraries,

CMOS Logic, CMOS design rules, Logic cells, I/O cells, cell compilers.

ASIC Library Design: Transistors as resistors, Transistor parasitic capacitance, Logical effort,

Cell design, Programmable ASICs, Programmable ASIC logic cells, Programmable ASIC I/O

cells, Programmable ASIC interconnect, Programmable ASIC design software.

Low-level design entry: Schematic entry, low-level design languages, PLA tools, EDIF, An

overview of VHDL and verilog, Logic synthesis, Simulation.

ASIC construction, Floor planning and placement.

47

CMOS System Core Studies: Dynamic Warp Processors: Introduction, The problem, the

algorithm, a functional overview, detailed functional specification, structural floor plan, physical

design, fabrication, Hierarchical layout and design of single chip 32 bit CPU : Introduction, Design

methodology, Technology updatability and layout verification.

Practical Realities and Ground Rules: Further thoughts on floor plans/layout, floor plan layout

of the four bit processors, input/output (I/O) pads, ―Real estate‖, further thoughts on system delays,

ground rules for successful design, scaling of MOS circuits.

TEXT BOOK:

1. Application Specific Integrated Circuits by J.S. Smith, Addison Wesley, 1997.

REFERENCE BOOKS:

1. Basic VLSI Design : Systems and Circuits, Doublas A. Puckness & Kamran Eshraghian,

Prentice Hall of India Private Ltd., New Delhi, 1989.

2. Principles of CMOS VLSI Design : A system perspective, N. Westle & K. Eshraghian,

Addition – Wesley Pub. Co. 1985.

3. Introduction to VLSI System, C. Mead & L. Canway, Addison Wesley Pub Co. 1990.

4. The Design & Analysis of VLSI Circuits, L.A. Glassey & D.W. Dobbephl, Addison Wesley

Pub Co. 1985.

5. Introduction to NMOS & VLSI System Design, A. Mukharjee, Prentice Hall, 1986.

6. VLSI Design Techniques for analog and digital circuits, R.L. Geiger, P.E. Allen & N.R.

Streder, McGraw Hill Int. 1990.

7. Digital Integrated Circuits, A Design Perspective, Jan A. Rabey, Prentice Hall of India Pvt.

Ltd., 1997.

8. Application specific integrated circuits, J.S. Smith, Addison Wesley, 1997.

48

Code: M16 CS 1210

MULTIMEDIA COMMUNICATION SYSTEMS



Credits : 4

COURSE OBJECTIVES:

1. Understanding the multimedia communications systems, application and basic principles,

2. Analysis of the multimedia streaming,

3. Performing and establishing multimedia communication terminals,

4. Presentation of multimedia communications

. COURSE OUTCOMES:

1. On successful completion of this course, student should be able to

2. Describe technical characteristics and performance of multimedia system and terminals,

3. Design creative approach in application of multimedia devices, equipment and systems,

4. Carry out experiments and measurements on the multimedia systems in laboratory conditions

on real components and equipment,

5. Interpret and analyze measurement results obtained on the multimedia system and components,

6. Describe the development process and applications of the multimedia systems,

7. Test multimedia communication systems and equipment in real conditions.

SYLLABUS

Introduction: Introduction to Multimedia - Multimedia Authoring and Tools. Graphics and Image

Data Representations - Color in Image and Video- fundamental Concepts in Video

Audio Compression: Basic of Digital Audio - Basic Audio Compression Techniques - MPEG

Audio compression

Lossy and Lossless Compression: Lossless Compression Algorithms - Lossy Compression

Algorithms - Image Compression Standards

Video Compression: Basic Video Compression techniques- MPEG Video Coding I: MPEG 1 and

2 - MPEG Video Coding II: MPEG 4, 7 and beyond

Multimedia Networks: Computer and Multimedia Networks - Multimedia Network

Communications and Applications- Wireless Networks- Content-Based Retrieval in Digital

Libraries.

TEXT BOOKS:

1. Ze-Nian Li and Mark S.Drew, ―Fundamentals of Multimedia‖, Pearson Edition, 2004

2. Fred Halsall, ―Multimedia Systems‖, Pearson 3rd

Edition, 2005

49

REFERENCE BOOKS:

1. Khalid Sayood, ―Introduction to Data Compression‖ Morgan Kauffmann Publishers, Inc.

California, 2000.

2. Multimedia Communication Systems: Techniques, Standards and Networks by Kamisetty Ram

Mohan Rao, Z.S.Bojkovic, Dragorad A.Milovanovic,Prentice Hall PTR 2002.

50

Code: M16 CS 1211

WAVELET TRANSFORMS AND ITS APPLICATIONS



Credits : 4

COURSE OBJECTIVES:

1. To understand the basics of different transforms and to make students understand the basic

notion of joint time-frequency and time-scale representations of signals

2. To understand the mathematical basis of the Wavelet transform as a tool in signal and Image

analysis.

3. To introduce Multi Resolution Analysis (MRA) framework

4. To explore connections between Multi-rate DSP, Filter banks and Wavelet Transform

5. Extension to 2D, Bi-orthogonal wavelets and Wavelet packets

6. To study and appreciate Wavelet applications in Signal compression and De-noising

COURSE OUTCOMES:

Upon completion of the course, the student will be able to

1. Understand the various transforms and their applications.

2. Understand the relationship between various versions of Wavelet transform.

3. Apply Wavelet transforms to different applications.

SYLLABUS

Continuous And Discrete Wavelet Transform: Continuous time ;wavelets transform (CWT):

Definition, CWT as a correlation, Constant Q factor filtering interpretation and time frequency

resolution, CWT as an operator, Inverse CWT, Discrete Wavelet Transform: Approximations of

vectors in Nested Linear Vector Subspaces – Multiresolution analysis (MRA) with examples.

Orthonormal Wavelets And Filter Banks: Definition of an MRA- construction of a General

Orthonormal MRA – Wavelet Basis for the MRA-Digital filtering Interpretation- Examples of

orthonormal Basis – Generating Wavelets- Interpreting Orthonormal MRAs for Discrete – time

Signals Miscellaneous Issues Related to PRQMF Filter Banks-Generating Scaling Functions and

Wavelets from Filter Banks – Generating Scaling functions and Wavelets from Filter coefficients –

Problems.

Alternative Wavelet Transforms: Biorthogonal Wavelet Bases – Filtering Relations for

Orthogonal Filters-Examples of Biorthogonal Scaling Functions and Wavelets-Two Dimensional

Wavelets-Nonseperable Multidimensional Wavelets- Wavelet Packets – Transform Coding –

DTWT for Image Compression – Audio Compression – Video Coding Using Multiresolution

Techniques.

51

Applications of Wavelet Transforms: Wavelet Denoising – Speckle Removing – Edge Detection

and Object Isolation - Image Fusion-Object Detection by Wavelet Transforms of Projections –

Communication Applications – Scaling Functions as signaling pulses, Discrete Wavelet Multitone

Modulation.

TEXT BOOK:

1. Raghuveer M. Rao and Ajit S. Bopardikar, ―Wavelet Transforms – Introduction to Theory and

Applications‖ Addison Wesley Pearson Education Asia, 2000.

REFERENCE BOOKS:

1. C.Sidney Burrus, Ramesh A Gopinath, and Haitao Guo, ―Introduction to Wavelets and

Wavelet Transforms, A Primer ― PH International Editions, 1998.

2. Wavelet Transforms and their Applications by Debnath, Lokenath, Shah,Firdous. Birkhauser

Basel, 2015.

52

Code: M16 CS 1212

STATISTICAL SIGNAL PROCESSING



Credits : 4

COURSE OBJECTIVES:

1. Introduce the basic theory of signal detection and estimation.

2. Explain the Study of identifying the engineering problems that can be put into the frame of

statistical signal processing.

3. Explain the Study of solving the identified problems using the standard techniques learned

through this course.

4. Study the fundamental understanding of statistical signal processing that may help students

study advanced topics and consequently make significant contributions to the theory and the

practice of statistical signal processing.

COURSE OUTCOMES:

At the end of the course the student will have

1. Ability to characterize an estimator.

2. Ability to design statistical DSP algorithms to meet desired needs.

3. Ability to apply vector space methods to statistical signal processing problems.

4. Ability to understand Wiener filter theory and design discrete and continuous Wiener filters.

5. Ability to understand Kalman Filter theory and design discrete Kalman filters.

SYLLABUS

Estimating in Signal Processing: Mathematical Estimation Problem, Assessing Estimator

Performance, Minimum Variance Unbiased Estimation: Unbiased Estimators, Minimum Variance

Criterion, Existence of the Minimum Variance Unbiased Estimator, Finding the Minimum

Variance Unbiased Estimator, Cramer Rao Lower Bound, Estimator Accuracy considerations,

CRLB, CRLB for signals in White Gaussian Noise, Transformation of Parameters, Signal

Processing Examples.

Maximum Likelihood Estimation: Introduction, Finding the MLE, Properties of the MLE, MLE

for transformed parameters, Numerical Determination of the MLE, Asymptotic MLE, Signal

Processing Examples, Least Squares Estimation: Introduction, Least Squares Approach, Linear

Least Squares, Geometrical Interpretations, Order Recursive Least Squares, Signal Processing

Examples.

53

Bayesian Estimation: Introduction, Prior Knowledge and Estimation, Choosing a prior PDF,

Properties of the Gaussian PDF, Bayesian Linear Model, Nuisance Parameters, Bayesian

Estimation for Deterministic Parameters, Derivation of Conditional Gaussian PDF.

Statistical Decision Theory: Neyman - Pearson Theorem, Receiver Operating Characteristics,

Irrelevant Data, Minimum Probability of Error, Bayes Risk, Multiple Hypothesis Testing -

Composite Hypothesis Testing, Composite Hypothesis Testing Approaches, Performance of

GLRT, Multiple Hypothesis Testing.

Deterministic Signals, Matched Filters, Generalized Matched Filters, Multiple Signals, Linear

Model, Signal Processing Examples, Random Signals, Estimator Correlator, Linear Model,

Estimator Correlator for Large Data Records, General Gaussian Detection, Signal Processing

Example.

TEXT BOOKS:

1. Steven M. Kay, ―Fundamentals of Statistical Signal Processing Volume I Estimation Theory‖,

Prentice Hall PTR, 1993.

2. Steven M. Kay, ―Fundamentals of Statistical Signal Processing Volume II Detection Theory‖,

Prentice Hall PTR, 1998.

REFERENCE BOOKS:

1. Monson H. Hayes, ―Statistical Digital Signal Processing and Modeling‖, Wiley, 1996.

2. An Introduction to Statistical Signal Processing by Robert M.Gray and Lee D.Davisson,

Cambridge University Press 2004.

54

Code: M16 CS 1213

DIGITAL SIGNAL PROCESSING LAB


Exam : 3 Hrs. Ext. marks : 50

Credits : 2

COURSE OBJECTIVES:

1. Use the Fast Fourier Transform in a variety of applications including: signal analysis, fast

convolution, spectral and temporal interpolation, and filtering.

2. Quickly choose and design FIR and IIR digital filters

3. Estimate power spectral densities using a variety of techniques.

4. Perform the deconvolution of two signals

5. Construct & Simulate a simple digital communication system.

6. To learn LPC Speech coding, JPEG image compression, Image Encryption & Watermarking,

apply convolutional coding & Viterbi algorithm

COURSE OUTCOMES:

1. Analyze signals using the discrete Fourier transform (DFT)

2. Understand circular convolution, its relationship to linear convolution, and how linear

convolution can be achieved via the discrete Fourier transform.

3. Understand the Decimation in time and frequency FFT algorithms for efficient computation

of the DFT.

4. Alter the sampling rate of a signal using decimation and interpolation.

5. Design digital IIR filters by designing prototypical analog filters and then applying analog to

digital conversion techniques such as the bilinear transformation.

6. Design digital FIR filters using the window method.


1. Implementation of Edge Detection Techniques using DSP processor

2. Development of Digital Data Scrambler for speech signals

3. Development of Digital Data Descoraubler for speech an audio signal

4. Implementation of convolution encoder

5. Implementation of convolution veterbi decoder

6. Design and implementation of Digital Filters

7. Implementation of Digital filters for real time applications

8. Implementation JP&G algorithm for image compression

9. Implementation of Adaptive filters

10. Implementation real time system for biomedical signal using DSP processors

11. Application Development using DSP processor for Multi channel telephony system

12. Application Development for voice recognizing systems using DSP processors

55

REFERENCE BOOKS:

1. Digital Signal Processing using MATLab by Vinay k.Ingle, John G.Proakis, Vikas

Publishing House Pvt. Ltd.

2. Digital Signal Processing - A Computer based approach by Sanjit K.Mitra 3rd

edition,TMH.

3. Contemporary Communication Systems using MATLab and Simulink by John G. Proakis,

Masoud Salehi, Gerhard Bauch 2nd

edition, Thomson Brooks/Cole.

4. Digital Image Processing using MATLab by Rafael C.Gozalez, Richard E.Woods, Steven

L.Eddins 2nd

edition, TMH.

56

Code: M16 CS 1214 SEMINAR-II



The viva-voce for the seminar shall be held with the faculty member, PG coordinator, and Head

of the Department. The marks shall be awarded in the ratio of 40, 20 and 40 percent by the

members respectively.

57




(Regulation:R16)


III – SEMESTER


Marks

Total

Marks

M16 CS 2101 Thesis Work -





one advisor (CO-Guide) should be from the industry/research organization.





58




(Regulation:R16)


IV – SEMESTER


Marks

Total

Marks

M16 CS 2201 Thesis Work-



of 4th






9

DEPARTMENT OF ELECTRICAL AND ELECTRONICS ENGINEERING

M.TECH (POWER SYSTEMS AND AUTOMATION)


(Regulation: R16)


I - SEMESTER

Course Code Course Credits Lecture

hours

Lab

hours

Total

contact

hours

Sessional

Marks

Exam

Marks

Total

Marks

M16 PS 1101 Advanced Power System

Operation and Control 4 4 -- 4 30 70 100

M16 PS 1102 Optimization

Techniques 4 4 -- 4 30 70 100

M16 PS 1103 Advanced Drives and

Control 4 4 -- 4 30 70 100

M16 PS 1104 Advanced Control

System Design 4 4 -- 4 30 70 100

#1 Elective-I 4 4 -- 4 30 70 100

M16 PS 1108 Power System

Simulation Lab-I 2 -- 3 3 50 50 100

M16 PS 1109 Seminar-I 2 -- 3 3 100 -- 100

Total 24 20 6 26 300 400 700

Course Code Course

#1-Elective-I

M16 PS 1105 Renewable Energy Systems

M16 PS 1106 Power System Modeling

M16 PS 1107 Power System Planning

10

Code: M16 PS 1101

ADVANCED POWER SYSTEM OPERATION AND CONTROL



Credits : 4

COURSE OBJECTIVES:

1. To understand the economics of power system operation with thermal and hydro units

2. To realize the requirements and methods of real and reactive power control in power system

3. To be familiar with the power system security issues and contingency studies

COURSE OUTCOMES:

Upon completion of this course, students will be able to

1. Develop generation dispatching schemes for thermal and hydro units

2. Apply control and compensations schemes on a power system

3. Adopt contingency analysis and selection methods to improve system security

SYLLABUS

Economic operation: Economic dispatch problem of thermal units without and with losses–

Gradient method-Newton‟s method –Base point and participation factor method.

Unit Commitment Solution Methods:

Introduction to unit commitment, methods of unit commitment: Priority-List Methods, Dynamic-

Programming Solution, Forward DP Approach, Lagrange relaxation solution.

Hydro-thermal co-ordination: Hydro electric plant models–short term hydro thermal

scheduling problem-gradient approach.

Optimal Power Flow: Solution of OPF, gradient method, Newton‟s method, linear

programming method with only real power variables, linear programming with AC power flow

variables, security-constrained optimal power flow.

Power system security: Contingency analysis–linear sensitivity factors–AC power flow

methods–contingency selection – concentric relaxation – bounding-security constrained optimal

power flow.

The control problem: The two‐area system, Tie‐line Bias control; steady state Instabilities:

Torsional Oscillatory Modes‐Damper windings and negative damping, effect of AVR loop: AGC

Design using kalman method‐state variable form of the dynamic model, Optimum control Index,

state Trajectories, the RICCATTI equations, preventive and emergency control, computer

control.

11

TEXTBOOKS:

1. Allen J. Woodand Wollenberg B.F., „Power Generation Operation and control‟, John Wiley

& Sons, Second Edition,1996.

2. Electric Energy systems Theory ‐ An Introduction' OlleI Elgard, TMH Second Edition

REFERENCE BOOKS:

1. Kirchmayer L.K., „Economic Control of Interconnected Systems‟, John Wiley & Sons, 1959.

2. Nagrath, I.J. and Kothari D.P.,„Modern Power System Analysis‟,TMH, New Delhi,2006.

12

Code: M16 PS 1102

OPTIMIZATION TECHNIQUES



Credits : 4

COURSE OBJECTIVE:

1. To learn essential optimization techniques for applying to day to day problems.

COURSE OUTCOME:

1. After learning the techniques they can apply to engineering and other problems.

SYLLABUS

Introduction to Optimization: Introduction, Historical Development, Engineering Applications

of Optimization, Statement of Optimization Problem.

Classical Optimization Techniques: Introduction, Single variable optimization, Multi variable

optimization with no constraints; Multi variable optimization with Equality constraints–Solution

by Direct Substitution method, Method of constrained variation, Method of Lagrangian

multipliers; Multi variable optimization with in equality constraints: Kuhn‐Tucker conditions.

Linear Programming: Introduction, Applications of Linear Programming, Standard Form of a

Linear Programming, Basic Terminology and Definitions, Exceptional cases, Simplex method,

Big‐Mmethod, Two‐phase method, Revised Simplex method, Duality, Decomposition Principle.

Non-Linear Programming-I: Unconstrained optimization‐Univariate method, Pattern

Directions, Hookand Jeeves Method, Powell's method, Gradient of a function, Steepest descent

method, Conjugate Gradient Method, Newton‟s method, Marquardt Method,Quai‐Newton

Methods, Davidon‐Fletcher‐Powell Method, Broyden‐Fletcher‐Goldfarb‐ Shanno Method.

Non-Linear Programming-II: Constrained optimization‐Characteristics of a Constrained

Problem, Sequential linear programming, Basic approach in the methods off easible directions,

Zoutendijk‟s method off easible directions, Sequential Quadratic Programming. TEXT BOOKS:

1. Engineering Optimization: Theory and Applications 'By S.S. Rao, New Age International

Publishers, revised Third Edition 2005.

2. Optimization for Engineering Design (Algorithms & Examples)‟ by Kalyanmoy Deb, PHI

Pvt. Ltd, New Delhi.

REFERENCE BOOKS:

1. Optimization Techniques‟ by Chander Mohan, Kusum Deep, New Age International

Publishers, 2009.

2. Optimization Methods, Theory and Applications‟ by Honglei Xu, Song Wang , Soon-Yi Wu,

Springer, 2015.

http://www.amazon.in/s/ref=dp_byline_sr_book_1?ie=UTF8&field-author=Honglei+Xu&search-alias=stripbooks

http://www.amazon.in/s/ref=dp_byline_sr_book_2?ie=UTF8&field-author=Song+Wang&search-alias=stripbooks

http://www.amazon.in/s/ref=dp_byline_sr_book_3?ie=UTF8&field-author=Soon-Yi+Wu&search-alias=stripbooks

13

Code: M16 PS 1103

ADVANCED DRIVES & CONTROL



Credits : 4

COURSE OBJECTIVES:

1. To Study about the transfer functions of D.C motors

2. To Study about the dq equivalent circuits of induction and synchronous motors.

3. To introduce the P and PI Control for controlling the DC and AC Motors.

COURSE OUTCOMES:

1. Student can design the transfer functions and obtain the performance of d.c motors

2. Student can design the dq equivalent circuits of induction and synchronous motors and

evaluate the performance it. 3. Student can design the values of P and PI Controllers for controlling the DC and AC Motors

SYLLABUS

DC drives: System model, motor rating, motor mechanism dynamics, drive transfer function,

effect of armature current wave form, torque pulsations, adjustable speed drives, chopper fed and

single‐phase converter fed drives, effect of field weakening.

Induction Motor drives: Basic Principle of operation of 3 Phase motor, equivalent circuit,

MMF space harmonics due to fundamental current, fundamental spatial MMF distributions due

to time harmonics simulation, effect of time and space harmonics, speed control by varying

stator frequency and voltage, impact of non sinusoidal excitation on induction motors, variable

square wave VSI drives, variable frequency CSI drives, line frequency variable voltage drives.

Induction Motor drives: Review of induction motor equivalent circuit, effect of voltage,

frequency and stator current on performance of the machine, effect of harmonics, dynamic d-. q

model, small signal model, voltage and current fed scalar control, direct and indirect vector

control, sensor less vector control, direct torque and flux control.

Synchronous motor drives: Review of synchronous motor fundamental, equivalent circuit,

dynamic d‐ q model, synchronous reluctance, sinusoidal and trapezoidal back emf permanent

magnet motors, sinusoidal SPM machine drives, trapezoidal SPM machines drives, wound field

machine drives, switched reluctance motor drives.

Closed loop control: Motor transfer function‐P, PIand PID controllers, current control‐Design

procedure, phase locked loop (PLL) control‐microcomputer control.

TEXT BOOKS:

1. B. K. Bose, “Modern Power Electronics and AC drives”, Pearson Education, Asia, 2003.

2. M. H. Rashid, “Power Electronics”, Third Edition, PHI

3. G. K. Dubey, “Fundamentals of Electrical Drives”, Narosa Publishing house.

14

REFERENCE BOOKS:

1. V. Subrahmanyam, “Electric Drives‐Concepts and Applications”, TMH 2.G. K. Dubey,

“Power Semiconductor controlled drives”, PH 1989.

2. R. Krishnan, “Electric Motor Drives: Modelling, Analysis and Control”, PH, 1998.

3. P. Vas, “Sensor less vector and direct torque control”, Oxford Press, 1998.

4. W.Leonard,“ Control of ElectricDrives”, Springer Verlag,1985.

15

Code: M16 PS 1104

ADVANCED CONTROL SYSTEM DESIGN



Credits : 4

COURSE OBJECTIVES:

1. Design of Linear Control Systems

2. MIMO Control design

3. PID Controller

4. State space analysis

5. Integral square error compensation

6. State feedback compensation

7. Design of digital control system

COURSE OUTCOMES:


1. Design the controllers for linear continuous systems using frequency domain, time domain,

state feed compensation and ISE compensation

2. Design the controllers for discrete-time systems using Z-plane and W-plane method

3. Design the PID controller using Ziegler Nicholas tuning method

4. Design the MIMO Control design

SYLLABUS

Design of Linear Control Systems: Review of compensation techniques to obtain desired

performance, Reshaping of Bode & Root locus plots to obtain desired response, Initial

condition and forced response, a simple lag– lead design.

Integral-square error compensation: parameter optimization using Integral‐square error

criterion with and without constraints, principles of State variable Feedback compensation of

continuous‐time and discrete‐time systems, simple problems to understand the concept.

MIMO Control design: Principles of Linear Quadratic Optimal Regulators, Discrete Time

Optimal Regulators, Observer Design, Linear Optimal Filters, State Estimate Feedback, Transfer

Function Interpretation, simple problems to understand the concept.

PID Controller: PID controller, Simulation of multi‐loop control system using P, PI, PD, PID

controller, Standard compensator structures (P, PD, PI and PID control).

Design of digital control system: Protocol of Digital controller design, Classical Compensation

of Discrete‐time control systems: Forward path continuous, Forward‐path Digital Z‐plane

Synthesis approaches, Deadbeat performance.

16

TEXT BOOKS:

1. G. C. Goodwin, S. F. Graebe, M. E. Salgado, “Control System Design”, Prentice Hall of

India

2. Gupta and Hasdorf, 'Fundamentals of Automatic control Willey Eastern, 1970.

3. B.C. Kuo, Automatic control systems' (5th Edition), Prentice Hall of India, 1988.

REFERENCE BOOKS:

1. M. Gopal, “Digital Control and State Variable Method”, Tata McGraw Hill

2. HadiSaadat, “Computational Aids in Control System Using MATLAB”, McGraw Hill

International.

3. Ogata K.,“Modern Control Engineering”, 4th Edition, Prentice Hall

4. Norman S. Nise, “Control Systems Engineering”, 3rd Edition, Wiley

17

Code: M16 PS 1105

RENEWABLE ENERGY SYSTEMS



Credits : 4

COURSE OBJECTIVES:

1. To familiarize students regarding World Energy Scenario and Power Generation.

2. To familiarize students with Features of Conventional and Renewable Generation.

3. To Gain knowledge on Power balance /Frequency control of Renewable energy system.

4. To Study Renewable Energy generation in Power system.

5. To familiarize students with Power System Economics and the Electricity Market.

6. To understand the future towards a Sustainable Electricity supply.

COURSE OUTCOMES:

1. Students will be able to understand the World Energy Generation and consumption Over the

past and present;

2. Students will be able to outline the technologies that are used to harness the Energy from

Conventional and Non-conventional Sources.

3. Students will be able to understand power governing, dynamic frequency control of large

systems, Impact of Renewable generation on Frequency control

4. Students will be able to explain the Issues Regarding Renewable Energy System in Power

System

5. Students will be able to outline the Power system economics and Electricity Market

6. Students will have vision towards sustainable supply systems in Future.

SYLLABUS

Energy and Electricity: The World Energy Scene, The Environmental Impact of Energy Use,

Generating Electricity, The Electrical Power System

Features of Conventional and Renewable Generation: Introduction, Conventional Sources:

Coal, Gasand Nuclear, Hydroelectric Power, Wind Power, PV and Solar Thermal Electricity,

Tidal Power, Wave Power, Biomass, Summary of Power Generation Characteristics, Combining

Sources.

Power Balance/Frequency Control: Introduction, Electricity Demand, Power Governing,

Dynamic Frequency Control of Large Systems, Impact of Renewable Generation on Frequency

Control and Reliability, Frequency Response Services from Renewable, Frequency Control

Modelling, Energy Storage.

Renewable Energy Generation in Power Systems: Distributed Generation, Voltage Effects,

Thermal Limits, Other Embedded Generation Issues, Islanding, Fault Ride‐through, Generator

and Converter Characteristics.

18

Power System Economics and the Electricity Market: Introduction, The Costs of Electricity

Generation, Economic Optimization in Power Systems., External Costs, Effects of Embedded

Generation, Support Mechanisms for Renewable Energy, Electricity Trading.

The Future–Towards a Sustainable Electricity Supply System: Introduction, The Future of

Wind Power, The Future of Solar Power, The Future of Bio fuels, The Future of Hydro and

Marine Power, Distributed Generation and the Shape of Future Networks.

TEXT BOOKS:

1. Renewable Energy in Power Systems, BY Leon Freris, David Infield, WILEY

PUBLISHERS, July 2008

2. Our Energy Future: Resource, Alternatives and the Environment, by Christian Ngo, Joseph

Natowitz, Wiley Publishers, Aug 2009.

REFERENCE BOOKS:

1. Renewable Energy Resources‟ by John Twidell and Tony Weir, Taylor & Francis, Second

edition, 2006.

2. Renewable Energy Systems by Henrik Lund, Elsevier Inc. 2014.

19

Code: M16 PS 1106

POWER SYSTEM MODELING



Credits : 4

COURSE OBJECTIVES:

1. To enable the students to understanding of power system components.

2. To understand the concept of 2-axis representation of an Electrical machine.

3. To understand the importance of 3-phase to 2-phase conversion.

4. To know the representation of 3-phase induction motor in various reference frames

5. To know the modelling of 3-phase synch. Motor in 2- axis representation.

6. To know the modelling Transmission line, SVC and load

COURSE OUTCOMES:

At the end of the course student able to

1. Model the synchronous and induction machine by using different reference frame theories

2. Model the Transmission line, SVC and load

SYLLABUS

Modelling of Power System Components: The need for modelling of power system, Simplified

models of non‐ electrical components like boiler, steam & hydro‐turbine & governor system.

Transformer modelling such as auto‐ transformer, tap‐changing & phase‐shifting transformer. Reference Frame Theory: Static and rotating reference frames–transformation of variables–

reference frames –transformation between reference frames–transformation of a balanced set–

balanced steady state phasor and voltage equations –variables observed from several frames of

reference.

Synchronous machine modeling: Voltage and Torque Equation–voltage Equation in arbitrary

reference frame and rotor reference frame–Park equations‐rotor angle and angle between rotor–

steady state analysis– dynamic performances for torque variations‐dynamic performance for

three phase fault–transient stability limit – critical clearing time –computer simulation.

Transmission line, SVC and load modelling: Transmission line, d‐q transformation using µ‐b

variables, static VAR compensators, loads modelling.

Induction Machines: Voltage and toque equations–transformation for rotor circuits–voltage and

toque equations in reference frame variables–analysis of steady state operation–free acceleration

characteristics– dynamic performance for load and torque variations–dynamic performance for

three phase fault–computer simulation in arbitrary reference frame.

20

TEXT BOOKS:

1. Power Systems Dynamics – K.R. Padiyar, B.S. Publications

2. Power System Control and Stability – Vol. – I – Anderson & Foud, IEEE Press, New York.

REFERENCE BOOKS:

1. Power System Dynamics & Control– Kundur, IEEE Press, New York

2. Power System Operation & Control – P.S.R. Murthy, CRC press

3. “Electrical Energy System Theory– an introduction” by OlleElgerd. TMH Publishing

Company 2nd

Edition, New Delhi

4. “Power System Analysis”–John J .Granierand W.D. Stevenson Jr, 4thEdition, McGraw Hill

International student edition.

21

Code: M16 PS 1107

POWER SYSTEM PLANNING

Theory : 4 Periods Sessionals : 30 Exam : 3 Hrs. Ext. Marks : 70

Credits : 4

COURSE OBJECTIVES:

1. The course is designed to teach load forecasting, power system planning, and reliability

issues in power system.

2. It aims to arm the students with the concepts of evaluation of generation and transmission

system reliability and their impacts on system planning.

3. To learn the automation analysis for expansion of existing generation and transmission

system planning.

COURSE OUTCOMES:

After completing the Power System and Automation course,

1. Students will be able to perform load forecasting for better planning of system.

2. Graduates are able to know the reliability of power system and do planning accordingly.

3. Graduates can carry out overall energy planning by automation.

SYLLABUS

Introduction: The electric utility industry, generation systems and transmission systems.

Load forecasting: Classification and characteristics of loads, approaches to load forecasting,

load forecasting methodology, energy forecasting, peak demand forecasting, non‐weather

sensitive forecast (NWSF), weather sensitive forecast, total forecast.

Generation system reliability analysis: Probabilistic generating unit models, probabilistic load

models, effective load, reliability analysis of anisolated system and interconnected systems.

Generation system cost analysis: Cost analysis, corporate models, production analysis,

production costing, fuel inventories, energy transactions and off‐peak loading, environmental

cost.

Transmission system reliability analysis: Deterministic contingency analysis, probabilistic

transmission system, reliability analysis, capacity state classification by subsets, subset

decomposition for system LOLP and (DNS) calculations, single area and multi area reliability

analysis.

Automated transmission system expansion planning: Basic concepts, automated network

design, automated transmission planning, a DC method, automated transmission planning by

interactive graphics.

22

TEXT BOOKS:

1. Power system planning, R. Sullivan ,McGraw International book Co., New Yorkand New

Delhi (chapters1‐ 4,6,7of the text book).

2. Electric Power System Planning: Issues, Algorithms and Solutions‟ by Hossein

Seifi, Mohammad Sadegh Sepasian, Springer Science & Business Media, 2011.

3. Power System Engineering: Planning, Design, and Operation of Power Systems and

Equipment‟ by Juergen Schlabbach, Karl-Heinz Rofalski, John Wiley & Sons, 2014.

4. Smart and Sustainable Power Systems: Operations, Planning, and Economics of Insular

Electricity Grids‟ by João P. S. Catalão, CRC Press, 2015

REFERENCE BOOKS:

1. Power System Planning‟ by H.M.Merrill, CRC Press.

2. Probabilistic Methods for Planning and Operational Analysis, G.T. Heydt and P.W. Sauer.

https://www.google.co.in/search?tbo=p&tbm=bks&q=inauthor:%22Hossein+Seifi%22



https://www.google.co.in/search?tbo=p&tbm=bks&q=inauthor:%22Mohammad+Sadegh+Sepasian%22

https://www.google.co.in/search?tbo=p&tbm=bks&q=inauthor:%22Juergen+Schlabbach%22

https://www.google.co.in/search?tbo=p&tbm=bks&q=inauthor:%22Karl-Heinz+Rofalski%22

23

Code: M16 PS 1108

POWER SYSTEM SIMULATION LAB-I



Credits : 2

COURSE OBJECTIVES:

1. To practice the basic theories of Electrical Power system.

2. To provide hands‐on experience to the students, so that they are able to apply theoretical

concepts in practice.

3. To use computer simulation tools such as MATLAB to carry out design experiments as it is a

key analysis tool of engineering design.

4. To give a specific design problem to the students, which after completion they will verify

using the simulation software or hardware implementation.

COURSE OUTCOMES:

1. Graduate will demonstrate the ability to identify, formulate and solve Power System


2. Graduate will demonstrate the ability to design and conduct experiments, analyze and

interpret data.

3. Graduates will demonstrate the ability to design a electrical systems or process as per needs

and specifications

4. Graduate will demonstrate the skills to use modern engineering tools, softwares and

equipment to analyze problem.


1. Series RLC circuit

2. MATLAB Program to Simulate Ferranti Effect.

3. MATLAB Program to Model Transmission Lines.

4. MATLAB Program to Form Y bus by Singular Transformation

5. MATLAB Program to Solve Load Flow Equations by Gauss-Seidel Method

6. MATLAB Program to Find Optimum Loading of Generators Neglecting Transmission

Losses.

7. MATLAB Program to Find Optimum Loading of Generators with Penalty factors.

8. MATLAB Program to Solve Swing Equation.

9. Simulink Model of Single Area Load Frequency Control with and without PI Controller in

Simulink.

10. Simulink Model for Two Area Load Frequency Control

11. Simulink Model for Evaluating Transient Stability of Single Machines Connected to Infinite

Bus.

24

REFERENCE BOOKS:

1. Elements of Power System Analysis‟ by by William Stevenson, McGraw Hill Higher

Education; 4th Revised edition.

2. Power System Analysis Hadi Saadat, PSA Publishing, 2010.

3. Modern Power System Analysis‟ by D.P. Kothari and I.J. Nagrath, McGraw-Hill Companies,

Incorporated, 2006.

4. Getting Started with MATLAB: A Quick Introduction for Scientists and Engineers‟ by Rudra

Pratap, Oxford University Press, 2010

5. MATLAB: An Introduction with Applications, 5th Edition Amos Gilat, Wiley Global

Education, 2014.

1.

http://www.amazon.in/s/ref=dp_byline_sr_book_1?ie=UTF8&field-author=William+Stevenson&search-alias=stripbooks

https://www.google.co.in/search?tbo=p&tbm=bks&q=inauthor:%22Hadi+Saadat%22

https://www.google.co.in/search?tbo=p&tbm=bks&q=inauthor:%22Rudra+Pratap%22



https://www.google.co.in/search?tbo=p&tbm=bks&q=inauthor:%22Amos+Gilat%22&source=gbs_metadata_r&cad=3

25

Code: M16 PS 1109

SEMINAR-I






26




(Regulation: R16)


II – SEMESTER


hours

Lab

hours

Total

contact

hours

Sessional

Marks

Exam

Marks

Total

Marks

M16 PS 1201 Power System Dynamics

and Stability 4 4 -- 4 30 70 100

M16 PS 1202 Automation in Power

Systems 4 4 -- 4 30 70 100

M16 PS 1203 Intelligent Systems and

Control 4 4 -- 4 30 70 100

M16 PS 1204 Optimal Control Theory 4 4 -- 4 30 70 100

#2 Elective-II 4 4 -- 4 30 70 100

M16 PS 1208 Power System Simulation

Lab-II 2 -- 3 3 50 50 100

M16 PS 1209 Seminar-II 2 -- 3 3 100 -- 100

Total 24 20 6 26 300 400 700

Course Code Course

#2-Elective-II

M16 PS 1205 High Voltage AC/DC Transmission

M16 PS 1206 Power Quality

M16 PS 1207 Power Electronic Applications in Power Systems

27

Code: M16 PS 1201

POWER SYSTEM DYNAMICS AND STABILITY



Credits : 4

COURSE OBJECTIVES:

At the end of the course the student is expected to

1. Give basic knowledge about the dynamic mechanisms behind angle and voltage stability

problems in electric power systems, including physical phenomena and modelling issues.

2. Learn the concepts of Dynamics, Stability, Excitation and SMIB of Power Systems.

3. Learn the modeling of synchronous machine, Excitation systems and Transmission lines.

4. Do simulation of system dynamics.

5. Learn the requirements of power system modeling and stability

6. Learn problem solving techniques for existing problems in power systems.

COURSE OUTCOMES:

At the end of this course, Students will be able to analyse and understand the electromagnetic

and electromechanical phenomena taking place around the synchronous generator.

1. Will be able to solve the reactive power problems in power system

2. Will learn the concepts of Dynamics, Stability, Excitation and SMIB of Power Systems.

3. Will be able to do machine modeling.

4. Will do modeling of Excitation systems and Transmission lines.

5. Will be able to understand the effect of excitation system on small signal stability.

6. Understand the significance of power system stabilizer in power system stabilities.

SYLLABUS

Modelling: Basic concepts, Review of classical methods, modelling of synchronous machine,

Park‟s transformation, Analysis of steady state performance, Excitation system, excitation

system modelling, Excitation systems‐standard block diagram, System representation by state

equations, Prime mover control system, Transmission lines, SVC and Loads modelling, D‐Q

transformation using α‐β variables.

Dynamics of a Synchronous generator connected to infinite bus: System model, synchronous

machine model, Application model (1.1), Calculation of initial conditions, System simulation,

Consideration of other machine models, Inclusion of SVC model.

Small Signal Stability Analysis: Analysis of single machine system, small signal analysis with

block diagram representation, Characteristic equation and application of Routh‐Hurwitz

criterion, synchronizing and damping torque analysis, small signal model state equations.

Application of Power System Stabilizers: Introduction, Basic concepts in applying PSS,

Control signals, structure and tuning of PSS.

Analysis of Multi-machine system: As implified system model, detailed models, Case I and II,

Inclusion of load and SVC dynamics, modal analysis of large power systems.

28

TEXT BOOKS:

1. Power System Dynamics, stability and control by K.R. Padiyar, Interline Publishing private

limited, Bangalore, India.

2. Power system control and stability by P.M .Anderson and A. A. Fouad, Ezalgotia

publications

REFERENCE BOOKS:

1. Power System Stability, Vol-3, by Edward Wilson Kinbark, Wiley-Interscience, A John

wiley & Sons.

2. Power System Dynamics and Stability by Peter W. Sauer, M.A. Pai Prentice Hall, 1998

https://www.google.co.in/search?tbo=p&tbm=bks&q=inauthor:%22Peter+W.+Sauer%22

29

Code: M16 PS 1202

AUTOMATION IN POWER SYSTEMS



Credits : 4

COURSE OBJECTIVES:

1. To know what are the elements of automatic power control systems.

2. To clearly understand the role of central control room management and operations in the DA

solution.

3. To familiarize with Supervisory control and data acquisition (SCADA).

4. To gain the awareness of the problems and challenges of the present day distribution sector.

5. To gain the knowledge of Principles of Distribution Automation (DA)

6. To gain the knowledge of various communication technologies available for DA.

7. To clearly understand the Technical Benefits of automation of distribution system.

COURSE OUTCOMES:


1. Learn various activities of central control room management.

2. Understand about SCADA

3. Gain the knowledge on application of automation to distribution system.

SYLLABUS

Introduction: Purpose of automatic power control systems, elements of automatic power control

systems, automatic power control and controllers relays and relaying devices.

Operation and control: Operations environment of distribution networks, evolution of

distribution management systems, basic distribution management system functions, basis of a

real‐time control system (SCADA),data acquisition, monitoring and event processing, control

functions, data storage, archiving, and analysis, hardware system configurations, SCADA system

principles.

Distribution automation: Problems with existing distribution system, need for distribution

automation, characteristics of distribution system, distribution automation, feeder automation.

Substation automation: Definition, functions of substation automation state and trends of

substation automation, intelligent affordable substation monitoring and control.

Feeder automation: Losses in distribution systems, system losses and loss reduction, network

reconfiguration, improvement in voltage profile, capacitor placement for reactive power

compensation, Algorithm for location of capacitor.

30

TEXT BOOKS:

1. Automation in Electrical power systems by, P.I. Zabolotny, MIR Publishers, Moscow

2. Control and Automation of Electrical Power Distribution Systems (PowerEngineering) James

Northcote‐ GreenJames Northcote‐Green, Taylor & Francis,2007.

3. A Textbook of Electric Power Distribution Automation By Dr.M.K.Khedkar, Dr.G.M.Dhole,

university science press, NewDelhi 2010

REFERENCE BOOKS:

1. Sunil S. Rao, Switch gearand Protections, Khanna Publication

2. Stuart A Boyer: SCADA supervisory control and data acquisition, ISA

3. Gordan Clark, Deem Reynders, Practical Modem SCADA Protocols

31

Code: M16 PS 1203

INTELLIGENT SYSTEMS AND CONTROL



Credits : 4

COURSE OBJECTIVES:

1. To introduce the students with the concepts of learning methods.

2. To provide students with the artificial neural networks and their architecture.

3. To familiarize the students with the various applications of artificial neural networks.

4. To introduce the concepts of the fuzzy logic control and their real time applications.

COURSE OUTCOMES:

1. Define the advances in neural networks

2. Evaluate the design and control of fuzzy systems.

3. Articulate the applications of fuzzy control block sets.

4. Evaluate the design of various models in neural networks

5. Techniques for analyzing of various types of neural networks

6. Evaluate the design and control of associative memories

7. Techniques to Design fuzzy logic system

8. Learn the unified and exact mathematical basis as well as the general principles of various

soft computing techniques.

9. Provide detailed theoretical and practical aspects of intelligent modeling, optimization and

control of non-linear systems.

10. Prepare the students for developing intelligent systems through case studies, simulation

examples and experimental results.

SYLLABUS

Neural Networks: Artificial Neural Networks: Basic properties of Neurons, Neuron Models,

Feed forward networks–Perceptrons, Multilayer networks–Exact and approximate

representation, Back propagation algorithm, variants of Back propagation, Unsupervised and

Reinforcement learning; Competitive learning and self organizing networks, Hybrid Learning.

ANN based control: Introduction: Representation and identification, modelling the plant,

control structures– supervised control, Model reference control, Internal model control,

Predictive control, Case study‐application to electrical engineering.

Fuzzy Logic: Overview of classical logic, Fuzzy setsvs Crispset, Membership function, Methods

of Membership function, Value Assignment, Defuzzification–Methods of defuzzification, fuzzy

rule based and Approximation, Aggrigation of Fuzzy rules, Fuzzy inference system –Mamadani

and Sugeno methods.

Fuzzy Controllers: Preliminaries–Basic architecture and operation of Fuzzy controller–Analysis

of static properties of fuzzy controller–Analysis of dynamic properties of fuzzy controller–

simulation studies–case studies –application to electrical engineering.

32

Neuro–Fuzzy Controllers: Neuro–fuzzy systems: A unified approximate reasoning approach–

Construction of role bases by self learning: System structure and learning algorithm–A hybrid

neural network based Fuzzy controller with self learning teacher. Fuzzified CMAC and RBF

network based self‐learning controllers, case studies –application to electrical engineering

TEXT BOOKS:

1. Bose and Liang, Artificial Neural Networks, Tata Mcgraw Hill, 1996.

2. Kosco B, Neural Networks and Fuzzy Systems: A Dynamic Approach to Machine

Intelligence, Prentice Hall of India, New Delhi, 1992.

REFERENCE BOOKS:

1. Klir G.J and Folger T.A, Fuzzy sets, Uncertainty and Information, PHI, New Delhi 1994.

2. Simon Haykin, Neural Networks, ISA, Research Triangle Park,1995.

3. Bose, NirmalK.;Bose, N.K.; Liang, Ping, Neural Network Fundamentals with Graphs,

Algorithms, and Applications (McGraw‐Hill Series in Electrical & Computer Engineering)

4. Robert Fuller, Introduction to Neuro‐Fuzzy Systems, Springer,2000

5. J.‐S. R. Jang, C.‐T. Sun, and E. Mizutani , Neuro‐Fuzzy and Soft Computing

6. Berenji, Hamid R , Fuzzy and neural control (May 1, 1992)

7. Fuzzy logic with Fuzzy Applications– T.J. Ross – Mc Graw Hill Inc, 1997.

8. Fuzzysets, Fuzzylogic, fuzzy systems by – loft Asker Zadeh

9. TimothyJ Ross – Fuzzy Logic with Emergency Applications

10. Hans Jurgen Zimmerman –Fuzzy Theoryand its Applications

33

Code: M16 PS 1204

OPTIMAL CONTROL THEORY



Credits : 4

COURSE OBJECTIVES:

1. To give exposure to problem formulation and performance measures for different type of

optimal control problems.

2. To introduce concepts needed to solve optimal controller using Dynamic Programming

Approach and H-J-B equation.

3. To introduce concepts of functional, variation of functional, the fundamental theorem of

calculus of variation to solve simplest variational problem.

4. To introduce concepts needed to solve linear regulatory problem using Pontryagin‟s

minimum principle.

5. To introduce concept of iterative numerical techniques needed to solve two-point boundary

value problems using steepest descent algorithm.

COURSE OUTCOMES:

After completing this course the students should be able to:

1. Have familiarity with problem formulation and different forms of performance measures as

applied to variety of optimal control problems.

2. Apply optimal control law and dynamic programming computational procedure to solve

optimal control problems.

3. Apply Hamilton-Jacobi-Bellman equations to solve linear regulator problem

4. Have complete familiarity with Calculus of Variation.

5. Have familiarity with Pontryagin‟s minimum principle.

6. Apply numerical techniques like steepest descent algorithm to determine optimal trajectories.

SYLLABUS

Introduction: Problem formulation‐State variable representation of systems–Performance

measures for optimal control problems– selecting a performance measure.

Dynamic programming: The optimal control law‐principle of optimality and its

application‐optimal control system‐interpolation‐recurrence relation of dynamic

programming‐computational procedure for solving optimal control problems–characteristics of

dynamic programming solution‐analytical results‐discrete linear regulator problems‐ Hamilton‐ Jacobi‐Bellman equation‐continuous linear regulator problems.

The Calculus of variations: Fundamental concepts‐linearity of functional‐closeness of

functions‐the increment of a functional‐The variation of a functional‐maxima and minima of

functional‐the fundamental theorem of the calculus of variations‐ Functional of a single function‐ the simplest variational problem

34

The variational approach to optimal control problems: Necessary conditions for optimal

control‐Linear regulator problem‐Pontryagin's minimum principle and state inequality

constraints.

Iterative numerical techniques for finding optimal controls: Two‐point boundary‐value

problems‐The method of steepest descent‐Features of the steepest descent algorithm. TEXT BOOKS:

1. Optimal control theory‐An Introduction by Donald E. Kirk ‐Prentice Hall Networks series.

2. Optimal control: Linear Quadratic Method by B.D.O Anderson & J.B. Moor, PHI,1990.

REFERENCE BOOKS:

1. Optimal Control Systems by Desineni Subbaram Naidu, CRC Press.

2. Optimal control: An Introduction to the Theory and Its Applications, by Athans. M &

P.L.Flab.

35

Code: M16 PS 1205

HIGH VOLTAGE AC/DC TRANSMISSION



Credits : 4

COURSE OBJECTIVES:

1. To learn HVAC and HVDC transmission systems.

2. To analyse phenomenon‟s of Lightning, Travelling waves and switching Transients.

3. To have an idea about Protection Devices in HVAC Transmission.

4. To design filters for reduction of harmonics.

5. To Model and analyse AC and DC systems interaction.

COURSE OUTCOMES:

At the end of the course students will be able:

1. To understand the basic concepts of EHV AC and HVDC transmission.

2. To identify the electrical requirements for HVDC lines.

3. To identify the components used in AC to DC conversion.

4. To understand the operation of HVDC conversion technology.

5. To understand the fundamental requirements of HVDC transmission line design.

6. To identify factors affecting AC-DC transmission.

7. To Design Filters for reduction of harmonics and Become familiarize with the use of

protection equipment

SYLLABUS

EHVAC Transmission: Principles, configuration, special features of high voltage AC lines,

power transferability, reactive power compensation, audible noise, corona, electric field, right of

way, clearances in a tower, phase to phase, phase to ground, phase to tower, factors to be

considered, location of ground wire.

Lightning, Travelling waves and switching Transients: Mathematical model to represent

lightning‐Travelling wave in transmission lines‐Circuits with distributed constants‐Wave

equations‐Reflection and Refraction of travelling waves‐Travelling waves at different line

terminations‐effect of short length of cables‐Shape and attenuation and distortion of travelling

waves‐Switch intransient ‐the circuit closing transient‐the recovery transient initiated by the

removal of the short circuit.

Protective device in HVAC transmission: Basic ideas about protection–surge diverters‐surge

absorbers‐ ground fault neutralizers‐Protection of lines and stations by shielding‐Ground wires–

counterpoises‐Driven rods‐ Modern lightning arrestors.

36

HVDC Transmission: General aspects of HVDC transmission, HVD Clinks‐comparison–

Economic, Technical performance–Reliability–Limitations‐Properties of thyrist or converter

circuits‐assumptions‐Choice of best circuit for HVDC converters‐Transformer connections–

Analysis with gate control but no overlap less than 60 degrees‐ operation of inverters.

Bridge converters-Analysis, Control, Protection and Harmonics Filters: Converter/Inverter

circuits for HVDC Transmission‐basic means of control –Power reversal‐desired features

of control–actual control characteristics .Converter disturbance by pass action in

bridges‐commutation failure‐basics of protection‐DC Reactors‐Voltage and current

oscillations‐Circuit breakers‐Over voltage protection‐Characteristics and non‐ characteristic

harmonics‐design of ac and dc filters.

Modeling and analysis of AC and DC systems interaction: System models, application of

switching functions, torsional interactions with HVDC systems, harmonic interaction, control

interaction.

TEXT BOOKS:

1. Allen Greenwood,` Electrical Transients in power system‟, Wiley Inter science,1971

2. EHV AC Transmission by Rakosh Das Begamudre, New Age Publishers

3. Kim bark, E.W., `Direct current transmission‐Vol.1‟, Wiley Inter science, New York, 1971

REFERENCE BOOKS:

1. Arrilaga,J. ,`High Voltage Direct current transmission ‟,Peter Pereginver Ltd.,

London,UK.,1983

2. Diesendorf,W., `Over voltage on High voltage system‟ Rensselaer Book store, Troy, New

York,1971

3. Klaus Ragallea, `Surges and high voltage networks‟, Plenum Press, 1980.

4. Padiyar, K.R.,` HVDC Transmission system‟, Wiley Eastern Limited ., NewDelhi, 1992.

5. An Introduction to High Voltage Engineering by SubirRay, Prentice Hall of India Private

Limited, New Delhi – 110 001.

6. HVDC Transmission‐ Adamson C. Hingorani N.G.

7. Power Transmission by DC UhimannE.

8. HVAC and HVDC Transmission, Engineering and practice : S.Rao,Khanna Publisher, Delhi.

9. Electric Power Systems: B.M. Weddy and B.J. Cory, John Wiely and Sons,Fourth edition

(2002)

10. Power System Analysis and Design: J. Duncan Glover, Mulukutla S .Sarma, Thomson

Brooks/cole/Third Edition (2003)

11. Power System Analysis and Design, B.R. Gupta, S.Chand and Company (2004)

37

Code: M16 PS 1206

POWER QUALITY



Credits : 4

COURSE OBJECTIVES:

1. Understand the various power quality issues, their origin, and monitoring and mitigation

methods.

2. To understand the power quality problems like voltage sag, swell, flickers, harmonics etc

3. Understand the effects of various power quality phenomenon in various equipment.

4. To know the knowledge on voltage standard characteristics, PQ survey etc.

COURSE OUTCOMES:

1. Students are able to possess the necessary skills to understand and handle power quality

related problems.

2. Students are able to identifying the cause or source of the problem and assessing the severity

of each problem with respect to the vulnerability of the affected devices.

3. Students expected to be familiar with power quality terminologies, and ready to tackle power

quality related challenges.

4. Students will be able to identify the standard characteristics and PQ survey.

SYLLABUS

Introduction: Introduction of the Power Quality (PQ) problem, Terms used in PQ: Voltage,

Sag, Swell, Surges, Harmonics, over voltages, spikes, Voltage fluctuations, Transients,

Interruption, overview of power quality phenomenon, Remedies to improve power quality,

power quality monitoring

Long Interruptions: Interruptions–Definition–Difference between failure, outage,

Interruptions–causes of Long Interruptions–Origin of Interruptions–Limits for the Interruption

frequency–Limits for the interruption duration–costs of Interruption–Overview of Reliability

evaluation to power quality, comparison of observations and reliability evaluation.

Short Interruptions: Short interruptions – definition, origin of short interruptions, basic

principle, fuse saving, voltage magnitude events due to re‐closing, voltage during the

interruption, monitoring of short interruptions, difference between medium and low voltage

systems. Multiple events, single phase tripping– voltage and current during fault period, voltage

and current at post fault period, stochastic prediction of short interruptions.

Voltage sag–characterization–Single phase/Three-phase: Voltage sag–definition, causes of

voltage sag, voltage sag magnitude, monitoring, theoretical calculation of voltage sag magnitude,

voltage sag calculation in non radial systems, meshed systems, voltage sag duration. Three phase

faults, phase angle jumps, magnitude and phase angle jumps for three phase unbalanced sags,

load influence on voltage sags

Power Quality and EMC Standards: Introduction to standardization, IEC Electromagnetic

compatibility standards, European voltage characteristics standards, PQ surveys

38

TEXT BOOKS:

1. “Understanding Power Quality Problems” by Math H J Bollen. IEEEPress.

2. Power Quality in Electrical Systems‟ by Alexander Kusko, The McGraw-Hill Companies,

2007.

REFERENCE BOOKS:

1. Power Quality in Power System‟ by Mohammad A.S. Masoum, Ewald F.Fuchs, Elsevier,

Academic Press, 2015.

2. Electrical Power Systems Quality by Roger C.Dugan, Electrotek Concepts lnc.

39

Code: M16 PS 1207

POWER ELECTRONIC APPLICATIONS IN POWER SYSTEMS



Credits : 4

COURSE OBJECTIVES:

1. To enable the students acquire a comprehensive ideas on various aspects of FACTS systems.

2. To acquire the knowledge on Flexible AC Transmission System and its importance for

FACTS devices.

3. To understand the various FACTS controllers operation on FACTS systems.

4. To Gain Knowledge about STATCOM.

COURSE OUTCOMES:

After completion of the course, the student will be able to

1. Understand the importance of FACTS controllers and its benefits.

2. Know the objectives of shunt, series compensations and role of FACTS devices on system

stability, voltage control.

3. Analyze the functional operation and control of SVC and STATCOM.

4. Describe the principle, operation and control of SPST.

SYLLABUS

Introduction: Basics of Power Transmission Networks ‐ Control of Power Flow in AC

Transmission Line‐ Flexible AC Transmission System Controllers, Basic types of FACTS

Controllers, Brief Descriptions and Definitions of FACTS Controllers. Benefits from FACTS

technology, HVDC vs. FACTS.

Static shunt compensators: SVC and STATCOM:‐ Objectives of Shunt compensation,

Methods of controllable VAR generation, Static VAR compensators: SVC and STATCOM,

comparison between SVC and STATCOM, Static VAR systems.

Static Synchronous Compensator (STATCOM): Introduction‐Principle of Operation of

STATCOM‐A Simplified Analysis of a Three Phase Six Pulse STATCOM‐Analysis of a Six

Pulse VSC Using Switching Functions‐Multi‐pulse Converters Control of Type 2

Converters‐Control of Type1Converters‐Multi level Voltage Source Converters‐ Harmonic

Transfer and Resonance in VSC Applications of STATCOM

Static Phase Shifting Transformer: General‐Basic Principle of a PST‐Configurations of SPST

Improvement of Transient Stability Using SPST ‐Damping of Low Frequency Power

Oscillations ‐ Applications of SPST

Static Series compensators: GCSC, TSSC, TCSC and SSSC:‐ Objectives of series

compensation, Variable impedance type series compensators, Switching converter type series

compensators, External(System) Control for Series Reactive Compensators, Summery of

Characteristics and Features.

40

TEXT BOOKS:

1. N.G. Hingorani, „Understanding Facts‟, IEEE Press 1999.

2. K.R Padiyar, “FACTS Controllers in power transmission and distribution, New Age

International (P) Limited, Publishers,2007”

REFERENCE BOOKS:

1. Yomg Hua Song, „Flexible AC Transmission Systems‟ (FACTS) IEE Press, 1999.

2. E. Acha,V.G. Agelidis, O.Anaya‐Lara, T.J.E. Miller, „Power Electronic Control in Electrical

Systems‟ Newnes Power Engineering Series,Oxford,2002.

41

Code: M16 PS 1208

POWER SYSTEM SIMULATION LAB-II



Credits : 2

COURSE OBJECTIVES:

1. To Simulate and compare the various aspects economic load dispatch and load flows.

2. To Simulate and observe the stability studies of transient and steady state

3. To simulate and observe behaviour of a system during the Short circuit

4. To Conduct experiments on a given system to know performance when subjected to

various faults

5. To Conduct experiments on different types of relays

COURSE OUTCOMES:

1. The student will be able to validate the adaptability of economic load dispatch and load flow

for a given situation by simulation results.

2. Design a controller for FACTS application by simulation

3. Demonstrate the effects of different sequence reactance of a synchronous machine by

experimentation.

4. Acquainted with the characteristics of different relays by experimentation

5. Know how to use the simulation software to design a real time power system .


1. Implementing the newton Raphson method for load flow using matlab

2. Load flow analysis by Decoupled method using matlab

3. Load flow analysis by fast Decoupled method using matlab

4. Obtain positive and negative sequences under un symmetrical fault analysis using matlab

5. Solve the dynamics of synchronous machine using matlab

6. Obtain Swing curves of a synchronous machine for a 3 phase fault

7. Optimal load frequency control of a two area system

8. Obtain the transient and subtransients of a synchronous generators

9. Obtain the sequence impedences of the transmission lines

10. Improving voltage profile by using series compensation

11. Design of statcom

REFERENCE BOOKS:

1. Elements of Power System Analysis‟ by by William Stevenson, McGraw Hill Higher

Education; 4th Revised edition.

2. Power System Analysis Hadi Saadat, PSA Publishing, 2010.

3. Modern Power System Analysis‟ by D.P. Kothari and I.J. Nagrath, McGraw-Hill

Companies,Incorporated, 2006.

http://www.amazon.in/s/ref=dp_byline_sr_book_1?ie=UTF8&field-author=William+Stevenson&search-alias=stripbooks

https://www.google.co.in/search?tbo=p&tbm=bks&q=inauthor:%22Hadi+Saadat%22

42

4. Getting Started with MATLAB: A Quick Introduction for Scientists and Engineers‟ by Rudra

Pratap, Oxford University Press, 2010

5. MATLAB: An Introduction with Applications, 5th Edition Amos Gilat, Wiley Global

Education, 2014




https://www.google.co.in/search?tbo=p&tbm=bks&q=inauthor:%22Amos+Gilat%22&source=gbs_metadata_r&cad=3

43

Code: M16 PS 1209

SEMINAR-II






44




(Regulation: R16)


III – SEMESTER


Marks

Total

Marks

M16 PS 2101 Thesis Work -





one advisor (Co-Guide) should be from the industry/research organization.





45




(Regulation: R16)


IV – SEMESTER


Marks

Total

Marks

M16 PS 2201 Thesis Work-



of 4th






9

DEPARTMENT OF INFORMATION TECHNOLOGY

M.TECH (INFORMATION TECHNOLOGY)


(Regulation:R16)


I – SEMESTER


Hrs

Lab

Hrs

Total

Contact

Hrs/Week

Sessional

Marks

Exam

Marks

Total

Marks

M16 CST

1101

Mathematical

Foundations of

Computer Science

4 4 -- 4 30 70 100

M16 CST

1102

Data Structures &

Algorithms 4 4 -- 4 30 70 100

M16 CST

1103

Advanced Data Base

Management Systems 4 4 -- 4 30 70 100

M16 CST

1104

Advanced Operating

Systems 4 4 -- 4 30 70 100

#1 Elective-I 4 4 -- 4 30 70 100

#2 Elective-II 4 4 -- 4 30 70 100

M16 CST

1113

Data Structures &

Programming Lab 2 -- 3 3 50 50 100

M16 CST

1114

Database

Management Systems

Lab

2 -- 3 3 50 50 100

Total 28 24 6 30 280 520 800

Course Code Course

#1-Elective-I

M16 IT 1101 Computer Organization & Architecture

M16 IT 1102 E-Commerce

M16 IT 1103 Embedded Systems

M16 IT 1104 Image Processing

M16 IT 1105 Artificial Intelligence

M16 IT 1106 Compiler Design

#2-Elective-II

M16 IT 1107 Computer Networks

M16 IT 1108 Cloud Computing

M16 IT 1109 Grid Computing

M16 IT 1110 Computer Graphics & Visual Computing

M16 IT 1111 Parallel Programming

M16 IT 1112 Computer Vision

10

Code: M16 CST 1101

MATHEMATICAL FOUNDATIONS OF COMPUTER SCIENCE




Credits : 4

COURSE OBJECTIVES:

1. Presenting the theory of finite automata, as the first step towards learning advanced

topics, such as compiler design.

2. Applying the concepts learned in fundamental courses such as Discrete Mathematics, in a

theoretical setting; in particular, the application of proof techniques.

3. Discussing the applications of finite automata towards text processing.

4. Developing an understanding of computation through Turing Machines

COURSE OUTCOMES:

1. Critical, logical-mathematical reasoning

2. Ability to apply mathematical knowledge and logic in solving problems.

3. Understanding of formal grammar analysis and compilation.

SYLLABUS

Mathematical notions of sets, sequences and tuples, functions and relations, Primitive

recursive functions, computable functions, examples, graphs, strings and languages.

Boolean logic – properties and representation, theorems and types of proofs, deductive,

inductive, by construction, contradiction and counter-examples.

Introduction to Number theory, Divisibility, modular arithmetic (addition modulo and

multiplication modulo); Statements and applications of Euler and Fermat Theorems,

Primitive Roots, Discrete Logarithms, Primality Test, Finding Large primes, Definition of

Elliptic Curves and their applications to Cryptography.

Introduction To Finite Automata: Alphabets and languages- Deterministic Finite Automata –

Non- deterministic Finite Automata – Equivalence of Deterministic and Non-Finite Automata

– Languages Accepted by Finite Automata – Finite Automata and Regular Expressions –

Properties of Regular sets &Regular Languages and their applications.

Context Free Languages: Context –Free Grammar – Regular Languages and Context-Free

Grammar – Pushdown Automata – Pushdown Automata and Context-Free Grammar –

Properties of Context-Free Languages – pushdown automata and Equivalence with Context

Free Grammars.

Turing Machines: The Definition of Turing Machine – Computing with Turing Machines –

Combining Turing Machines, , programming techniques for Turing Machines.

Variants of Turing Machines, Restricted Turing Machines Universal Turing Machines. The

Halting Problem, Decidable & undecidable problems- Post Correspondence Problems

TEXT BOOKS:

1. Introduction to Automata Theory, Languages and Computations – J.E. Hopcroft, & J.D.

Ullman, Pearson Education Asia.

2. Cryptography and Network Security, William Stallings.(Second Edition)Pearson

Education Asia.

11

REFERENCE BOOKS:

1. Introduction to languages and theory of computation – John C. Martin (MGH)

2. Discrete Mathematical structures with application to Computer Science – J.P. Tremblay

and R. Manohar, Mcgraw Hill Education

3. Introduction to Theory of Computation – Michael Sipser (Thomson Nrools/Cole)

4. Cryptanalysis of number theoretic Cyphers, Samuel S. Wagstaff Jr.Champan & Hall/CRC

Press 2003.

5. Network Security: The Complete Reference by Roberta Bragg, Mark Phodes –Ousley,

Keith Strassberg Tata McGraw-Hill.

12

Code: M16 CST 1102

DATA STRUCTURES & ALGORITHMS




Credits : 4

COURSE OBJECTIVES:

1. Student will learn about advanced data structures and the algorithms for manipulating

them, and how to analyze the time and memory requirements of them.

2. Student will master some complex searching and sorting algorithms and their data

structures, advanced types of trees, basic computational geometry procedures, and graph

representations and graph algorithms.

3. Student will learn when and how to use techniques for developing algorithms, such as

divide-and-conquer and dynamic programming.

4. Student will also become skilled in algorithmic analysis and algorithm development using

the latest techniques.

COURSE OUTCOMES:

1. Be able to write programs and class libraries given a specification;

2. Implement various data structures.

3. Implement and analyze various sorting algorithms.

4. Understand abstract data types and how they are implemented in „C‟ programming

language.

SYLLABUS

Algorithm Analysis: Overview of C++ classes, pointers, parameters passing, templates,

using Matrices, Basics of time complexity estimates, General norms for running time

calculation

Lists, Stacks & Queues: Abstract Data Types, Representation & implementation of ADT

list, Doubly linked list, Circular linked lists, Representation, Implementation and applications

of ADT stack and Queue.

Trees: Implementation and traversal of trees, Binary Trees and Binary search trees in C++,

Concepts of AVL Trees, Splay Trees and B-Trees.

Hashing: Hash Function, Separate chains, Open addressing, rehashing, Extendible Hashing.

Internal Sorting Algorithms: Sorting like insertion Sort, shell Sort, Heap Sort, Merge Sort,

Quick Sort and Simple external Sorting algorithm.

Disjoint Set: Equivalence Relations, Find and Union algorithms an dynamic sets, Path

compression and Union-by-Rank algorithm analysis.

Graph Algorithms: Representation of graph Topological Sort, shortest-path Algorithm,

Network flow problem, Minimum spanning tree algorithm, Applications of Depth – First

search, Introduction to NP-Completeness.

13

TEXT BOOK: 1. Data Structures & Algorithm Analysis in C++, Mark Allen Weiss. Second edition,

Pearson Edition. Asia.

REFERENCE BOOKS:





14

Code: M16 CST 1103

ADVANCED DATA BASE MANAGEMENT SYSTEMS (Common for M.Tech (CST, IT))



Credits : 4

COURSE OBJECTIVES:

1. To interpret an entity relationship diagram (ERD) to express requirements and

demonstrate skills to model data requirements and create data models into normalized

designs

2. To use SQL to create database objects, populate tables, and retrieve data

3. To describe the causes of performance problems and how to improve database application

performance

4. To develop a working understanding of database systems theory in order to apply that

knowledge to any particular database implementation.

COURSE OUTCOMES:

1. Understanding of DBMS.

2. Design database using ER model and refine the design by enforcing functional

dependencies, integrity constraints and normalization

3. Write queries using SQL


SYLLABUS

Database Systems: Introduction to the Database Systems, Concepts of Relational Models

and Relational Algebra. SQL: Introduction to SQL Queries, Integrity Constraints, Joins,

Views, Intermediate and Advanced SQL features and Triggers.

Database Design: Overview of the Design process, E-R Models, Functional dependencies

and other kinds of dependencies, Normal forms, Normalization and Schema Refinement.

Database Application Design and Development: User Interfaces and Tools, Embedded

SQL, Dynamic SQL, Cursors and Stored procedures, JDBC, Security and Authorization in

SQL, Internet Applications.

Query Evaluation: Overview, Query processing, Query optimization, Performance Tuning.

Database System Architectures: Centralized and Client-Server Architecture, Server system

Architecture, Parallel and Distributed database, Object based databases and XML. Advanced

data types in databases. Cloud based data storage systems.

Transaction Management: Overview of Transaction Management, Transactions,

Concurrency control, Recovery systems, Advanced Transaction Processing.

Case Studies: Postgre SQL, Oracle, IBM DB2 Universal Database, Microsoft SQL Server.

TEXT BOOKS:

1. Database System Concepts, Avi Silberschatz, Henry F. Korth, S. Sudarshan McGraw-

Hill, Sixth Edition, ISBN 0-07-352332-1.

REFERENCE BOOKS:

1. Database Management Systems, Raghu Ramakrishnan, Johannes Gehrke,McGraw-Hill.




15

Code: M16 CST 1104

ADVANCED OPERATING SYSTEMS (Common for M.Tech (CST, IT))



Credits : 4

COURSE OBJECTIVES:

1. To understand the concepts of distributed systems

2. To know networks and protocols, RPC

3. To understand Synchronization, Process and Processors, File and Directory Services,

shared memory in Distributed systems

COURSE OUTCOMES:

Students understands the concept of Distributed systems, Process Synchronization, File

structure and shared memory in Distributes operating systems

SYLLABUS

Introduction To Operating Systems, Types Of Operating Systems, Operating System

Structures. Operating-System Services, System Calls, Virtual Machines, Operating System

Design And Implementation.

Process Management: Process Concepts, Operations On Processes, Cooperating Processes,

Threads, Inter Process Communication, Process Scheduling, Scheduling Algorithms,

Multiple -Processor Scheduling. Thread Scheduling.

Process Synchronization & Deadlocks: The Critical Section Problem, Semaphores, And

Classical Problems Of Synchronization, Critical Regions, Monitors, Deadlocks,-System

Model, Deadlocks Characterization, Methods For Handling Deadlocks, Deadlock-

Prevention, Avoidance, Detection,& Recovery from Deadlocks.

Memory Management & File System Implementation: Logical Versus Physical Address

Space, Paging And Segmentation, Virtual Memory, Demand Paging, Page Replacement

Algorithms, Thrashing, File System Implementation -Access Methods, Directory Structure,

Protection, File System Structure, Allocation Methods, Free Space Management, Directory

Management, Device Drivers

Distributed Operating Systems: Distributed System Goals, Types Of Distributed Systems,

Styles & Architecture Of Distributed Systems, Threads, Virtualization, Clients, Servers, Code

Migration, and Communication in Distributed Systems.

Distributed Systems & Synchronization: Clock Synchronization, Logical Clocks, Mutual

Exclusion, Global Positioning Of Nodes, Data-Centric Consistency Models, Client-Centric

Consistency Models, Consistency Protocols.

Fault Tolerance, Security: Introduction To Fault Tolerance, Process Resilience,, Reliable

Client-Server Communication, Reliable Group Communication, Distributed Commit,

Recovery, Secure Channels, Access Control, Security Management.

16

TEXT BOOKS:

1. Silberschatz & Galvin, „Operating System Concepts‟, Wiley.

2. “DISTRIBUTED SYSTEMS”, Second edition, Andrew S.Tanenbaum, Maarten Van teen,

Pearson

REFERENCE BOOKS:

1. William Stallings-“Operating Systems”- 5th Edition - PHI

2. Charles Crowley, „Operating Systems: A Design-Oriented Approach‟, Tata Hill Co., 1998

edition.

3. Andrew S. Tanenbaum, „Modern Operating Systems‟, 2nd edition, 1995, PHI.

17

Code: M16 IT 1101

COMPUTER ORGANIZATION AND ARCHITECTURE



Credits : 4

COURSE OBJECTIVES:

Understand the architecture of a modern computer with its various processing units. Also the

performance measurement of the computer system. In addition to this the memory

management system of computer.

COURSE OUTCOMES:

1. Students can understand the architecture of modern computer.

2. They can analyze the Performance of a computer using performance equation

3. Understanding of different instruction types.

4. Students can calculate the effective address of an operand by addressing modes

5. They can understand how computer stores positive and negative numbers.

6. Understanding of how a computer performs arithmetic operation of positive and negative

numbers.

7. Understanding of how computer stores floating point numbers in IEEE 754 standard.

8. Cache memory and its importance.

9. Students can understand how cache mapping occurs in computer and can solve various problems

related to this.

10. Secondary storage organization and problem solving

SYLLABUS

Register Transfer and Micro operations: Register Transfer Language, Register Transfer, Bus and Memory Transfers, Arithmetic

Micro operations, Logic Micro operations, Shift Micro operations, Arithmetic Logic Shift

Unit.

Basic Computer Organization and Design: Instruction Codes, Computer Registers, Computer Instructions, Timing and Control,

Instruction Cycle, Memory-Reference Instructions, Input-Output and Interrupt, Complete

Computer Description, Design of Basic Computer, Design of Accumulator Logic.

Micro programmed Control:

Control Memory, Address Sequencing, Micro program Example, Design of Control Unit.

Central Processing Unit: Introduction, General Register Organization, Stack Organization, Instruction Formats,

Addressing Modes, Data Transfer and Manipulation, Program Control, Reduced Instruction

Set Computer(RISC)

Input/output Organization: Peripheral Devices, I/O interface, Asynchronous data transfer, Modes of transfer, priority

Interrupt, Direct memory access, Input-Output Processor (IOP), Serial Communication.

18

Memory Organization:

Memory Hierarchy, Main memory, Auxiliary memory, Associate Memory, Cache Memory,

and Virtual memory, Memory Management Hardware.

Overview of Computer Architecture: Evolution of Computer Systems, Parallelism in Uni- processor System, Parallel Computer

Structures, Architectural Classification Schemes, Parallel Processing Applications.

TEXT BOOKS:

1. Computer System Architecture, M. Morris Mano, Prentice Hall of India Pvt. Ltd., Third

Edition, Sept. 2008 .

2. Computer Architecture and Parallel Processing, Kai Hwang and Faye A. Briggs, McGraw

Hill, International Edition1985.

REFERENCE BOOKS:

1. Computer Architecture and Organization, William Stallings, PHI Pvt. Ltd., Eastern

Economy Edition, Sixth Edition, 2003.

2. “Computer System Architecture”, John. P. Hayes.

3. Computer Architecture A quantitative approach 3rd edition John L. Hennessy & David A.

Patterson Morgan Kufmann (An Imprint of Elsevier).

19

Code: M16 IT 1102

E-COMMERCE



Credits : 4

COURSE OBJECTIVES:

1. To understand process models

2. E - payments

3. Credit Cards smart cards

4. E - documents

5. E - Business logic

COURSE OUTCOMES:

1. Student able to understand advertising, marketing process on the internet and be familiar

with the e-commerce services

SYLLABUS

Introduction: Electronic Commerce-Frame Work, Anatomy of E-Commerce Applications,

E-Commerce Consumer Applications, E-Commerce Organization Applications. Consumer

Oriented Electronic Commerce - Mercantile Process Models, Digital Economy and e-

business Models

Electronic Payment Systems – Types of Electronic Payment Systems, Digital Token-Based,

Smart Cards, Credit Cards, Risks in Electronic Payment Systems, Designing Electronic

Payment Systems Electronic Data Inter Change, Inter Organizational Commerce - EDI, EDI

Implementation, Value Added Networks.

Intra Organizational Commerce, Macro Forces and Internal Commerce, Work Flow

Automation and Coordination, Customization and Internal Commerce, Supply Chain

Management. Business Cases for Document Library, Digital Document Types, Corporate

Data Ware-Houses.

Advertising And Marketing: Information Based Marketing, Advertising On Internet,

Online Marketing Process, Market Research. Consumer Search and Resource Discovery,

Information Search and Retrieval, Commerce Catalogues, Information Filtering.

Multimedia-Key Multimedia Concepts, Digital Video and Electronic Commerce, Desktop

Video Processing, Desktop Video Conferencing.

Business to consumer e-commerce: On line Marketing and Selling, Information Goods,

Electronic Markets and Auctions on the Internet

E-Business Intelligence: Data Mining, Web Merchandising and Recommender Systems,

Intelligent Agents in e-commerce, Business-to-Business e-commerce and Supply Chain

Management

Security of Internet Hosts and Networks, Public Key Infrastructure, Safety of

e-commerce Applications

20

TEXT BOOKS:

1. Frontiers of Electronic Commerce, Kalakata and Whinston, Pearson.

REFERENCE BOOKS:

1. E-Commerce fundamentals and Applications, Hendry Chan, Raymond Lee, Tharam

Dillon, Ellizabeth Chang, John Wiley.

2. E-Commerce, S.Jaiswal, Galgotia.

3. E-Commerce, Efrain Turbon, Jae Lee, David King, H.Michael Chang.

4. E-Commerce - Business, Technology and Society, Kenneth C.Taudon, Carol Guyerico

Traver.

21

Code: M16 IT 1103

EMBEDDED SYSTEMS



Credits : 4

COURSE OBJECTIVES:

1. To understand the architecture embedded systems

2. To know Embedded system software design

3. Design, execution and evaluation of experiments on embedded platforms.

4. Analysis, design and testing of systems that include both hardware and software.

Identification and synthesis of solutions for embedded system problems

COURSE OUTCOMES:

1. An ability to design systems, components, or processes for broadly-defined engineering

technology problems.

2. Implement combinatorial logic and sequential systems in terms of basic digital building

blocks using simulation software. You will be able to perform some optimisations.

3. Design, test and critically evaluate embedded solutions to real world situations using

digital components (sequential and combinatorial).

4. Recognize the key features of embedded systems in terms of computer hardware and be

able to discuss their functions. You will be aware of the key factors affecting computing

hardware evolution.

5. Develop software systems for embedded devices using assembler code

SYLLABUS

Examples of Embedded Systems – Typical Hardware – Memory – Microprocessors –

Busses – Direct Memory Access – Introduction to 8051 Microcontroller – Architecture-

Instruction set – Programming.

Microprocessor Architecture – Interrupt Basics – The Shared-Data problem – Interrupt

Latency.

Round–Robin Architecture - Round–Robin with Interrupts Architecture - Function-Queue-

Scheduling Architecture – Real-Time Operating Systems Architecture – Selection of

Architecture.

Tasks and Task States – Tasks and Data – Semaphores and Shared Data – Semaphore

Problems – Semaphore variants.

Message Queues – Mailboxes – Pipes – Timer Functions – Events – Memory Management –

Interrupt Routines in RTOS Environment.

RTOS design – Principles – Encapsulation Semaphores and Queues – Hard Real-Time

Scheduling Considerations – Saving Memory Space – Saving Power.

Host and Target Machines – Linker/Locator for Embedded Software- Getting Embedded

Software into the Target System.

Testing on your Host Machine – Instruction Set Simulators – Laboratory Tools used for

Debugging.

22

TEXT BOOKS:

1. The 8051 Microcontroller Architecture, Programming & Applications, Kenneth J. Ayala,

Penram International.

2. An Embedded Software Primer, David E. Simon, Pearson Education , 2005.

REFERENCE BOOK:

1. Embedded Systems: Architecture , Programming and Design, Raj Kamal, Tata McGraw-

Hill Education, 2008

23

Code: M16 IT 1104

IMAGE PROCESSING



Credits : 4

COURSE OBJECTIVES:

1. The course objectives include: overview of digital image processing field; understand the

fundamental digital image processing algorithms and implementation; gain experience in

applying image processing algorithms to real problems.

2. Cover the basic theory and algorithms that are widely used in digital image processing

3. Expose students to current technologies and issues that are specific to image processing

systems

COURSE OUTCOMES:




methods.





SYLLABUS

Fundamentals of Image Processing: Image Acquisition, Image Model, Sampling,

Quantization, Relationship between Pixels, Distance Measures, Connectivity, Image

Geometry, Photographic Film. Histogram: Definition, Decision Of Contrast Basing On

Histogram, Operations Basing on Histograms Like Image Stretching, Image Sliding, Image

Classification. Definition and Algorithm of Histogram Equalization.

Image Transforms: A Detail Discussion On Fourier Transform, DFT,FFT, Properties

WALSH Trans Form , WFT, HADAMARD Transform, DCT.

Image Enhancement: a. Arithmetic and Logical Operations, Pixel or Point Operations, Size Operations,

b. Smoothing Filters-Mean, Median, Mode Filters – Comparative Study

c. Edge Enhancement Filters – Directorial Filters, Sobel, Laplacian, Robert, KIRSCH

Homogeneity

d. & DIFF Filters, Prewitt Filter, Contrast Based Edge Enhancement Techniques –

Comparative Study

e. Low Pass Filters, High Pass Filters, Sharpening Filters. – Comparative Study

f. Colour Fundamentals and Colour Models

g. Colour Image Processing.

Image Enhancement: Design of Low Pass, High Pass, EDGE Enhancement, Smoothening

Filters in Frequency Domain. Butter Worth Filter, Homomorphic Filters in Frequency

Domain Advantages of Filters in Frequency Domain, Comparative Study of Filters in

Frequency, Domain and Spatial Domain.

Image Compression: Run Length Encoding, Contour Coding, Huffman Code, Compression

Due to Change in Domain, Compression Due to Quantization Compression at the Time of

Image Transmission. Brief Discussion on:- Image Compression Standards.

24

Image Segmentation: Characteristics of Segmentation, Detection of Discontinuities,

Thresholding Pixel Based Segmentation Method. Region Based Segmentation Methods,

Segmentation by Pixel Aggregation, Segmentation by Sub Region Aggregation, Histogram

Based Segmentation, Spilt and Merge Technique, Motion in Segmentation

Morphology: Dilation, Erosion, Opening, Closing, Hit-And-Miss Transform, Boundary

Extraction, Region Filling, Connected Components, Thinning, Thickening, Skeletons ,

Pruning Extensions to Gray – Scale Images Application of Morphology in I.P

Image , Video & Multimedia Communications: Multi-scale and multi-orientation

representation; Geometry and texture representation; Object based representation;

Hierarchical representation; Sparse representation, Multimedia with image and video content;

Multimedia event synchronization.

TEXT BOOK:

1. Digital Image Processing, Rafael C. Gonzalez And Richard E. Woods, Addision Wesley

REFERENCE BOOKS:

1. Fundamentals Of Electronic Image Processing By Arthyr – R – Weeks, Jr.(PHI)

2. Image Processing, Analysis, and Machine Vision by Milan Sonka Vaclan Halavac Roger

Boyle, Vikas Publishing House.

3. Digital Image Processing, S. Jayaraman, S. Esakkirajan& T. Veera Kumar, TMH

4. Fundamentals of Digital Image Processing, Chris Solomon, Tobi Breckon, Wiley-

Blackwell

25

Code: M16 IT 1105

ARTIFICIAL INTELLIGENCE



Credits : 4

COURSE OBJECTIVES:

1. To introduce different artificial intelligence techniques

2. To learn different machine learning algorithms

3. Learn different recent algorithms in artificial intelligence

COURSE OUTCOMES:

1. Able to learn artificial intelligence techniques

2. Understand the concept of machine learning.

SYLLABUS

Introduction: Artificial Intelligence, AI Problems, AI Techniques, the Level of the Model,

Criteria for Success. Defining the Problem as a State Space Search, Problem Characteristics,

Production Systems, Search: Issues in The Design of Search Programs, Un-Informed Search,

BFS, DFS; Heuristic Search Techniques: Generate-And- Test, Hill Climbing, Best-First

Search, A* Algorithm, Problem Reduction, AO*Algorithm, Constraint Satisfaction, Means-

Ends Analysis.

Knowledge Representation: Procedural Vs Declarative Knowledge, Representations &

Approaches to Knowledge Representation, Forward Vs Backward Reasoning, Matching

Techniques, Partial Matching, Fuzzy Matching Algorithms and RETE Matching Algorithms;

Logic Based Programming- AI Programming languages: Overview of LISP, Search

Strategies in LISP, Pattern matching in LISP , An Expert system Shell in LISP, Over view of

Prolog, Production System using Prolog

Symbolic Logic: Propositional Logic, First Order Predicate Logic: Representing Instance

and is-a Relationships, Computable Functions and Predicates, Syntax & Semantics of FOPL,

Normal Forms, Unification &Resolution, Representation Using Rules, Natural Deduction;

Structured Representations of Knowledge: Semantic Nets, Partitioned Semantic Nets,

Frames, Conceptual Dependency, Conceptual Graphs, Scripts, CYC;.

Reasoning under Uncertainty: Introduction to Non-Monotonic Reasoning, Truth

Maintenance Systems, Logics for Non-Monotonic Reasoning, Model and Temporal Logics;

Statistical Reasoning: Bayes Theorem, Certainty Factors and Rule-Based Systems, Bayesian

Probabilistic Inference, Bayesian Networks, Dempster-Shafer Theory, Fuzzy Logic: Crisp

Sets ,Fuzzy Sets, Fuzzy Logic Control, Fuzzy Inferences & Fuzzy Systems.

Experts Systems: Overview of an Expert System, Structure of an Expert Systems, Different


Systems, Knowledge Acquisition and Validation Techniques, Black Board Architecture,

Knowledge Building System Tools, Expert System Shells, Fuzzy Expert systems.

Machine Learning: Knowledge and Learning, Learning by Advise, Examples, Learning in

problem Solving, Symbol Based Learning, Explanation Based Learning, Version Space, ID3

Decision Based Induction Algorithm, Unsupervised Learning, Reinforcement Learning,

Supervised Learning: Perceptron Learning, Back propagation Learning, Competitive

Learning, Hebbian Learning.

26

Natural Language Processing: Role of Knowledge in Language Understanding,

Approaches Natural Language Understanding, Steps in The Natural Language Processing,

Syntactic Processing and Augmented Transition Nets, Semantic Analysis, NLP

Understanding Systems; Planning: Components of a Planning System, Goal Stack Planning,

Hierarchical Planning, Reactive Systems

TEXT BOOKS:


2. Artificial Intelligence, Elaine Rich and Knight, Mcgraw-Hill Publications

REFERENCE BOOKS:



MIT Press.


27

Code: M16 IT 1106

COMPILER DESIGN



Credits : 4

COURSE OBJECTIVES:

1. To learn the various system software like assemblers, loaders, linkers and macro.

2. To study the features of design phases and parsing techniques of a Compiler.

3. To learn the various techniques of syntax directed translation & code optimization.

4. To introduce the major concept areas of language translation and compiler design.

5. To enrich the knowledge in various phases of compiler ant its use, code optimization

techniques, machine code generation, and use of symbol table.

6. To extend the knowledge of parser by parsing LL parser and LR parser.

COURSE OUTCOMES:

1. To acquire the knowledge of modern compiler & its features.

2. To learn the new code optimization techniques to improve the performance of a program

in terms of speed & space.

3. To use the knowledge of patterns, tokens & regular expressions

SYLLABUS

Introduction: Introduction to Compilers and Language processors, , Programming

Language basics, Extended Backus- Naur Form Syntax Notation, Applications of Compiler

Technology, Design of New Computer Architecture, Structure & Different Phases of a

Compiler, Review of Compiler Structure, Structure of Optimizing Compilation.

Finite Automata & Lexical Analysis: introduction to Lexical Analysis, Lexical Analyzers,

Approaches to design Lexical Analyzers, Language for specifying lexical analyzers,

Introduction to Finite automata, Regular Expressions & Languages, Recognition of Tokens,

Transition Diagrams, Look ahead Operator, Implementation of lexical analyzers, Lexical

Analyzer Generator LEX.

Syntax Analysis: Syntactic Specification of Programming Languages, Context Free

Grammars & Languages, Introduction to Parsers, Parser Generators, Yacc, Creating Yacc

Lexical Analyzer with LEX, Basic Parsing Techniques: Shift Reduce Parsing, Operator

Precedence Parsing, Top-down Parsing, Recursive Descent Parsing, Predictive Parsers, LR

Parsers: SLR, LALR & Canonical LR parsing, Construction of Parse Tree, Error Recovery in

Parsers.

Semantic Analysis: Semantic Actions, Syntax Directed Translations, Translation on the

parse Tree, Implementation of Syntax Directed Translator, Intermediate Codes, Syntax

Directed translation to Postfix code, Syntax Trees, Intermediate Code Generation, Three

Addr5ess Code-Translation of Expressions, Type Checking& Type Conversions.

Code Optimization: Principal sources of Code Optimization, Loop Optimization, Basic

Blocks& Flow Graphs, DAG Representation of Basic Blocks, Applications of DAG, Local

Optimization, Unreachable Code Elimination, Dead Code Elimination, Data Flow Analysis,

Data Flow Equations & Computations, Peep-Hole Optimization. Machine Dependent

Optimizations, Overview of Informal Compiler Algorithm Notation(ICAN), If

Simplification, Loop Simplification, Loop Inversion, Branch Optimization and Prediction,

28

Code Generation: Issues in Code Generation, Input to Code Generator, Instruction

Selection, Register Allocation, Simple Target Machine Model, Program and Instruction

Costs, Register allocation & Assignments, Code Generation Algorithm, Code Generators,

Optimal Code Generation for Expressions, Code Generation From DAG.

Symbol Table Management, Contents of a Symbol Table, Data Structures for Symbol

Tables; Run time Environments, Implementation of a simple Stack allocation, Heap

Management, Block Structured Languages; Error Detection & Recovery, Lexical Phase

Errors, Syntactic & Semantic Errors, Error Handling Routines.

Code Scheduling & Case Studies: Instruction Scheduling, Speculative Loads & Boosting,

Speculative Scheduling, Software Pipe Lining, Trace Scheduling, Percolation Scheduling,

Case Studies: Sun Compilers, SPARC, IBM XL Compiler for the POWER& Power PC ,

Digital Equipment Compiler for Alpha, Intel Reference Compilers, Future Trends In

Compiler Design and Implementations.

TEXT BOOKS:

1. Principles of Compiler Design by Aho, D. Ullman, Lam and Ravi Sethi, Pearson

Education Second Edition

2. Advanced Compiler Design and Implementation, Steven Muchnic, Elsevier Publications

REFERENCE BOOKS:

1. Compiler Construction by Kenneth. C. Louden, Vikas Pub. House.

2. Compiler Design, A.A. Pentambekar, Technical Publications

3. Modern Compiler Design, Grune.D,Van Reeuwijk K, Bal H.E, Jacobs C J H, Langendoen

Springer.

29

Code: M16 IT 1107

COMPUTER NETWORKS



Credits : 4

COURSE OBJECTIVES:

1. Build an understanding of the fundamental concepts of computer networking.

2. Familiarize the student with the basic taxonomy and terminology of the computer

networking area.

3. Introduce the student to advanced networking concepts, preparing the student for entry

Advanced courses in computer networking.

4. Allow the student to gain expertise in some specific areas of networking such as the

design and maintenance of individual networks.

COURSE OUTCOMES:

After completing this course the student able to demonstrate the knowledge and ability to:

1. Independently understand basic computer network technology.

2. Identify the different types of network topologies and protocols.

3. Enumerate the layers of the OSI model and TCP/IP. Explain the function(s) of each layer.

4. Identify the different types of network devices and their functions within a network

5. Familiarity with the basic protocols of computer networks, and how they can be used to

assist in network design and implementation.

SYLLABUS

Introduction to Computer Networks: Introduction, Network Hardware, Network Software,

Reference Models, Data Communication Services & Network Examples, Internet Based

Applications.

Data Communications: Transmission Media, Wireless Transmission, Multiplexing,

Switching, Transmission in ISDN, Broad Band ISDN , ATM Networks.

Data Link Control, Error Detection & Correction, Sliding Window Protocols, LANs &

MANs: IEEE Standards for LANs & MANs-IEEE Standards 802.2, 802.3, 802.4, 802.5,

802.6, High Speed LANs.

Design Issues in Networks: Routing Algorithms, Congestion Control Algorithms, Net work

Layer in the Internet, IP Protocol, IP Address, Subnets, and Internetworking.

Internet Transport Protocols: TRANSPORT Service, Elements of Transport Protocols,

TCP and UDP Protocols, Quality of Service Model, Best Effort Model, Network

Performance Issues.

Over View of DNS, SNMP, Electronic Mail, FTP, TFTP, BOOTP, HTTP Protocols, World

Wide Web, Firewalls.

Network Devices: Over View of Repeaters, Bridges, Routers, Gateways, Multiprotocol

Routers, Brouters, Hubs, Switches, Modems, Channel Service Unit CSU, Data Service Units

DSU, NIC, Wireless Access Points, Transceivers, Firewalls, Proxies.

Advanced Concepts in Networks: Over View of Cellular Networks, Adhoc Networks,

Mobile Adhoc Networks, Sensor Networks, Virtual Private Networks .Delay Tolerant

Networks DTN, Ipvs,.

30

TEXT BOOK:

1. Computer Networks, Andrews S Tanenbaum,, Edition 5, PHI, ISBN:-81-203-1165-5

REFERENCE BOOKS:

1. Data Communications and Networking , Behrouz A Forouzan , Tata McGraw-Hill Co

Ltd, Second Edition,

2. Computer networks, Mayank Dave, CENGAGE.

3. Computer networks, A System Approach, 5th ed, Larry L Peterson and Bruce S Davie,

Elsevier.

4. An Engineering Approach to Computer Networks-S.Keshav, 2nd Edition, Pearson

Education.

5. Understanding communications and Networks, 3rd Edition, W.A. Shay, Thomson.

31

Code: M16 IT 1108

CLOUD COMPUTING



Credits : 4

COURSE OBJECTIVES:

1. To impart fundamental concepts in the area of cloud computing

2. To impart knowledge in applications of cloud computing

COURSE OUTCOMES:

1. Understanding the systems, protocols and mechanisms to support cloud computing

2. Develop applications for cloud computing

3. Understanding the hardware necessary for cloud computing

4. Design and implement a novel cloud computing application

SYLLABUS

Cloud Computing Basics - Cloud Computing Overview, Applications, Intranets and the

Cloud, First Movers in the Cloud. The Business Case for Going to the Cloud - Cloud

Computing Services, Business Applications, Deleting Your Datacenter, Salesforce.com,

Thomson Reuters.

Organization and Cloud Computing - When You Can Use Cloud Computing, Benefits,

Limitations, Security Concerns, Regulatory Issues, Cloud Computing with the Titans -

Google, EMC, NetApp, Microsoft, Amazon, Salesforce.com, IBMPartnerships.

Hardware and Infrastructure - Clients, Security, Network, Services. Accessing the Cloud -

Platforms, Web Applications, Web APIs,Web Browsers. Cloud Storage - Overview, Cloud

Storage Providers, Standards - Application, Client, Infrastructure, Service.

Software as a Service - Overview, Driving Forces, Company Offerings, Industries Software

plus Services - Overview, Mobile Device Integration, Providers, Microsoft Online.

Developing Applications - Google, Microsoft, Intuit QuickBase, Cast Iron Cloud, Bungee

Connect, Development, Troubleshooting, Application Management.

Local Clouds and Thin Clients - Virtualization in Your Organization, Server Solutions,

Thin Clients, Case Study: McNeilus Steel.

Migrating to the Cloud - Cloud Services for Individuals, Cloud Services Aimed at the Mid-

Market, Enterprise-Class Cloud Offerings, Migration, Best Practices and the Future of Cloud

Computing - Analyze Your Service, Best Practices, How Cloud Computing Might Evolve.

TEXT BOOK:

1. Cloud Computing-A Practical Approach, Anthony T. Velte, Toby J. Velte, Robert

Elsenpeter. McGrawHill.

REFERENCE BOOK:

1. Mastering Cloud Computing- Raj Kumar Buyya, Christian Vecchiola and S.Tanurai

Selvi, TMH, 2012

32

Code: M16 IT 1109

GRID COMPUTING



Credits : 4

COURSE OBJECTIVES:

1. Understand the need for and evolution of Grids in the context of processor- and data-

intensive applications

2. Be familiar with the fundamental components of Grid environments, such as

authentication, authorization, resource access, and resource discovery

3. Know architecture of grid computing

4. Be able to justify the applicability, or non-applicability, of Grid technologies for a

specific application

COURSE OUTCOMES:

1. To understand the genesis of grid computing

2. To know the application of grid computing

3. To learn the technology and tool kits for facilitating grid computing

SYLLABUS

Introduction: Introduction to Parallel, Distributed Computing, Cluster Computing and Grid

Computing, Characterization of Grids, Organizations and their Roles, Grid Computing Road

Maps.

Architecture: Architecture of Grid and Grid Computing, Review of Web Services-OGSA-

WSRF.

Grid Monitoring: Grid Monitoring Architecture (GMA) - An Overview of Grid Monitoring

Systems- GridICE - JAMM -MDS-Network Weather Service-R-GMA-Other Monitoring

Systems- Ganglia and GridM

Grid Middleware: List of globally available Middlewares - Case Studies-Recent version of

Globus Toolkit and gLite - Architecture, Components and Features.

Data Management And Grid Portals: Data Management, Categories and Origins of

Structured Data, Data Management Challenges, Architectural Approaches, Collective Data

Management Services, Federation Services, Grid Portals, First-Generation Grid Portals,

Second Generation Grid Portals.

Semantic Grid and Autonomic Computing: Meta data and Ontology in the Semantic Web,

Semantic Web services, Layered structure of the Semantic Grid, Semantic Grid activities,

Autonomic Computing

Grid Security and Resource Management: Grid Security, A Brief Security Primer, PKI-

X509 Certificates, Grid Security, Scheduling and Resource Management, Scheduling

Paradigms, Working principles of Scheduling , A Review of Condor, SGE, PBS and LSF-

Grid Scheduling with QoS.

33

TEXT BOOKS:

1. Grid Computing, Joshy Joseph and Craig Fellenstein, Pearson Education 2004.

2. The Grid Core Technologies, Maozhen Li, Mark Baker, John Wiley and Sons , 2005.

REFERENCE BOOKS:

1. The Grid 2 - Blueprint for a New Computing Infrastructure, Ian Foster and Carl

Kesselman, Morgan Kaufman - 2004.

2. Grid Computing: Making the Global Infrastructure a reality, Fran Berman, Geoffrey Fox,

Anthony J.G. Hey, John Wiley and sons.

34

Code: M16 IT 1110

COMPUTER GRAPHICS & VISUAL COMPUTING



Credits : 4

COURSE OBJECTIVES:

1. To Learn basic and fundamental computer graphics techniques

2. To Learn image synthesis techniques

3. Examine applications of modeling, design and visualization

4. Learn different color modeling and computer animation

5. Learn hierarchical modeling and graphing file formats

6. Learn viewing pipeline and structures

7. To Learn visualization and computational and mathematical methods of visual computing

8. To understand visual transformation and projection

COURSE OUTCOMES:

Students able to

1. Learn basic and fundamental computer graphics techniques

2. Represent and implement images and objects using 3D representation.

3. Design develop surface detection using various detection methods

4. Choose various illumination models for provides effective standards of objects

5. Design of develop effective computer animations

6. Design of various projections

SYLLABUS

Introduction: Computer Graphics and their applications, Computer Aided Design-

Computer Art, Entertainment, Education and Training, Graphical User Interfaces; Over

view of Graphics systems: Video Display Devices, Raster Scan systems, random scan

systems, Graphics monitors and workstations, Input devices, hard copy devices, GUI

and Interactive Input Methods, Windows and Icons , Virtual Reality Environments,

Graphics software

Output primitives: Points and Lines, , Line and Curve Attributes-Color and Gray scale

levels Line Drawing Algorithms, Loading the Frame buffer, Line function, Circle

Generating Algorithms, Ellipse Generating Algorithms, Other Curves, Parallel Curve

Algorithms, Curve Functions , Pixel Addressing, Area Fill Attributes, Filled Area Primitives,

Filled Area Functions, Cell Array, Character Generation, Character Attributes, Bundled

Attributes, Inquiry Functions , Antialiasing

Three Dimensional Concepts and Object representations: 3D display methods-3D

Graphics, Polygon Surfaces, Curved Lines and Surfaces, Quadratic Surfaces, Super

Quadrics, Blobby Objects, Spline Representations , Cubic Spline methods, Bézier Curves and

Surfaces, B Spline Curves and Surfaces.

Two & Three Dimensional Transformations: Two Dimensional Transformations: Basic

Transformations, Matrix Representations, Homogeneous Coordinates, Composite

Transformations, Other Transformations, Transformations between Coordinate Systems,

Affine Transformations -, Transformation Functions-, Raster methods for Transformation

Three Dimensional Transformations: Translation-, Rotation, scaling, Other Transformations,

35

Composite Transformations , 3D Transformation Functions , Modeling and Coordinate

Transformations,

Viewing Pipeline and structures : Viewing Coordinates, Projections , View

Volumes, General Projection Transformations , Clipping-, Hardware

Implementations , Concepts of Structures and Basic models, Editing , Hierarchical

Modeling with Structures.

Visualization: Three Dimensional Viewing, Visualization- Image Processing- The viewing

Pipeline, Viewing Coordinate Reference Frame, Window-to-Viewport Coordinate

Transformation, Two Dimensional Viewing Functions , Clipping Operations, Point

Clipping, Line Clipping, Polygon Clipping-Curve Clipping, Text and Exterior Clipping.

Visual Computing: Computational and mathematical methods for creating, capturing,

analyzing and manipulating digital photographs, Introductory Topics on computer graphics,

computer vision, and machine learning, Programming assignments intended to give hands-on

experience with creating graphical user interfaces, and with implementing programs for

synthesizing and manipulating photographs.

Visual Transformation & Projection: Graphics pipeline, perception and color models,

camera models, transformations and projection, projections, lighting, shading, global

illumination, texturing, sampling theorem, Fourier transforms, image representations,

convolution, linear filtering, diffusion, nonlinear filtering, edge detection, optical flow, image

and video compression, Creation of Visual Effects Optical Flow Video Compression, Radon

Transform Texture.

TEXT BOOKS:

1. Computer Graphics C Version, Donald Hearn & M. Pauline Baker, Pearson Education,

New Delhi, 2004

2. D. Forsyth and J. Ponce, Computer Vision: A Modern Approach, Prentice Hall Inc., 2003

REFERENCE BOOKS:

1. Procedural Elements for Computer Graphics, David F. Rogers, Tata McGraw Hill Book

Company, New Delhi, 2003

2. Computer Graphics: Principles & Practice in C, J. D. Foley, S. K Feiner, A VanDam F.

H John Pearson Education, 2004

3. Computer Graphics us ing Open GL, Franscis S Hill Jr, Pearson Education, 2004.

4. Computer Vision and Image Processing: A Practical Approach using CVIPtools, S. E.

Umbaugh,, Prentice Hall, 1998

36

Code: M16 IT 1111

PARALLEL PROGRAMMING



Credits : 4

COURSE OBJECTIVES:

1. To understand the scope, design and model of parallelism.

2. Know the parallel computing architecture.

3. Know the Characteristics, model and design of parallel algorithms.

4. Analytical modeling and performance of parallel programs.

5. Solve a complex problem with message passing model and programming with MPI.

COURSE OUTCOMES:

Students who complete this course successfully are expected to

1. Recall fundamental concepts of parallelism

2. Design and analyze the parallel algorithms for real world problems and implement them

on available parallel computer systems.

3. Reconstruction of emerging parallel algorithms with MPI.Compute contemporary parallel

algorithms.

SYLLABUS

Introduction to Parallel Computing: Parallel Programming and Parallel Computing,

Overview of Parallel Architectures and Parallel Programming Models, MIMD and SPMD

Models, Problems Unique to Parallel Programming,

Supercomputers and Grand Challenge Problems, Modern Parallel Computers, Data

Dependence Graph, Data Parallelism, Functional Parallelism, Pipelining and Data Clustering.

Interconnection Networks: Switch Network Topologies, Direct and Indirect Network

Topology, Bus, Star, Ring, Mesh, Tree, Binary Tree Network, Hyper Tree Network, Hybrid,

Hypercube, Perfect Shu E Network, Torus and Butterfly Network.

Performance Analysis: Introduction, Execution Time, Speedup, Linear and Super linear

Speedup, Efficacy and Efficiency, Amdahls Law and Amdahl Effect, Gustafson-Barsiss Law,

Minsky's Conjecture, The Karp-Flatt Metric, The Iso-Efficiency Metric, Iso-Efficiency

Relation, Cost and Scalability.

Parallel Computational Models: Flynns Taxonomy, PRAM, EREW, CREW, ERCW,

CRCW, Simulating CRCW, CREW and EREW, PRAM Algorithms.

Introduction To Parallel Algorithms: Parallel Programming Models, PVM, MPI

Paradigms.

Parallel Programming Languages: , Brents Theorem, Simple Parallel Programs in MPI

Environments, Parallel Algorithms on Network, Addition of Matrices, Multiplication of

Matrices.

TEXT BOOKS:

1. Computer Architecture and Parallel Processing, Hwang and Briggs, McGraw Hill.

2. Parallel Programming in C with MPI and Open MP, Michael J.Quinn, McGrawHill ,

2004

37

REFERENCE BOOKS:

1. Introduction to Distributed and Parallel Computing, Crichlow, PHI.

2. Designing Efficient Algorithms for Parallel Computers, M.J.Quinn, McGraw-Hill.

3. Introduction to Parallel Processing, Shashi Kumar M et al., PHI New Delhi.

4. Elements of Parallel Computing, V.Rajaraman, Prentice-Hall of India.

5. The Design and Analysis of Parallel Algorithms, S.G.Akl, PHI.

38

Code: M16 IT 1112

COMPUTER VISION



Credits : 4

COURSE OBJECTIVES:

1. The fundamentals of Computer Vision.

2. Computer vision is to develop the theoretical and algorithmic basis by which useful

information about the world can be automatically extracted and analyzed from a single

image or a set of images.

3. Image processing techniques, feature extraction techniques, imaging models and camera

calibration techniques, stereo vision, and motion analysis.

COURSE OUTCOMES:

1. Students demonstrate a thorough understanding of fundamental concepts in computer

vision

2. Students must be able to design and conduct experimental validation for a computational

approach to a computer vision problem, and interpret the results to assess the performance

3. Students are familiar with methods used in various vision-based applications – image

feature detection, 3-D reconstruction, segmentation.

SYLLABUS

Fundamentals of Image Processing: Image Acquisition, Definitions of Pixel, Gray Value,

Sampling, Quantization, Histogram, Image Sliding, Image Stretching. Distance and

Connectivity. Image Smoothening Operations - Mean, Median, Mode Filters. Edge

Enhancement Filters - Directional Filters, Laplacian, Sobel, Robert. Definition of Image

Compression - Run Length Encoding Method, Contour Encoding Method. Definition of

Segmentation - Pixel based method of segmentation.

Morphological Operations: Definition of Thresholding, A few techniques of thresholding.

Importance of Binary Images. Erosion, Dilation, Opening, Closing, HIT -or -MISS

Transformation, Thinning, Thickening, Skeletons, Pruning, Con vex hull. Extensions to Gray

- Scale Images.Applications of Gray - Scale Morphology. Applications of Morphological

Operations in Pattern Analysis.

Shape Representation and Descriptions (Part - 1): Region Identification, Algorithms for

Region Identification, Shape Representation and Description - Chain Codes, Geometric

Border Representation - Boundary Length, Curvature, Bending Energy, Signature, Chord

Distribution, Fourier Transforms of Boundaries, Boundary Description using Segment

Sequences, B -Spline Representation, Shape invariants.

Shape Representation and Descriptions (Part - 2): Region - Based Methods - Area -

Algorithms for Calculation of Area. Euler‟s Number, Projections, Eccentricity,

Elongatedness, Rectangularity, Direction, Compactness. Detailed Discussion on - Moments.

Convex hull, Algorithms related to Convex hull. Graph Representation - Algorithm for

Skeleton, Algorithm for Graph Construction. Definitions of Region Decomposition, Region

Neighborhood Graphs, Shape Classes.

39

Object Recognition: Knowledge Representation, Statistical Pattern Recognition, -

Classification Principles, Classifier Setting, Classifier Learning. Syntactic Pattern

Recognition - Grammars, and Languages, Syntactic Analysis, Syntactic Classifier.

Recognition as Graph Matching - Isomorphism, Related Algorithms. Similarity of Graphs.

Cluster Analysis: Definition, Hierarchical Clustering, - Agglomerative Clustering

Algorithms, Single - Linkage Algorithm, Complete Linkage Algorithm, Average - Linkage

Algorithm, Ward‟s Method. Partitional Clustering - Definition, Forgy‟s Algorithm, K -

Means Algorithm, Isodata Algorithm. Applications in Pattern Analysis.

Artificial Neural Networks and Fuzzy Logic in Pattern Analysis: Introduction to

ANN,Architecture of ANN, Activation Functions, Training of ANN - Supervised,

Unsupervised, Reinforced, McCulloch - Pitts Model, HEBBNET, ADELINE ,Application of

ANN in Pattern Analysis. Definition and Brief Discussion about Fuzzy Logic, Fuzzy Sets.

Application in Pattern Analysis.

TEXT BOOKS:

1. Pattern R ecognition and Image Analysis, Earl Gose, Richard Johnsonbaugh, Steve Jost ,

PHI

2. Image Processing, Analysis and Machine Vision, Milan Sonka,Vaclav Hlavac, VIKAS

REFERENCE BOOK:

1. Introduction to Artificial Neural Networks, S.N. Sivanandam, M. Paul Raj ,VIKAS

40

Code: M16 CST 1113

DATA STRUCTURES& PROGRAMMING LAB (Common for M.Tech (CST, IT))



Credits : 2

COURSE OBJECTIVES:

1. To introduce the graduate, simple linear & non-linear data structures.

2. To make the student write ADTs, for all data structures

3. To make the student learn different algorithm design techniques.

COURSE OUTCOMES:

At the end of this course student able to implement

1. Linear data structures

2. Non-linear data structures

3. Sorting and searching techniques

SYLLABUS

Implementation of Data Structures and Algorithms using C++

1. To perform various operations such as insertion, deletion, display on single linked lists.

2. To implement

(i) Stacks using linked list. (ii) Queues using linked list.

3. To perform different types of searching techniques on a given list

(i) Sequential search (ii) Binary search (iii) Fibonacci search


(i) Bubble sort (ii) Insertion sort (iii) Selection sort(iv) Merge sort


(i) Quick sort (ii) Shell sort (iii) Radix sort

6. To perform the following

(i) To convert the given infix expression to postfix expression

(ii) To evaluate the given postfix expression.

7. To perform various operations on graphs

(i) Vertex insertion. (ii) Vertex deletion.

(iii) Edge insertion. (iv) Edge deletion.

(v) Breadth First traversal. (vi) Depth First traversal.

8. To implement dictionaries using hashing technique

9. To perform various operations on binary heap.

10. To perform various operations on Binary search tree.

11. To perform operations on AVL trees.

12. To perform various operations on B-tree.

41

REFERENCE BOOKS:





42

Code: M16 CST 1114

DATA BASE MANAGEMENT SYSTEMS LAB (Common for M.Tech (CST, IT))



Credits : 2

COURSE OBJECTIVES:

1. To teach the graduate database design and query and PL/SQL.

COURSE OUTCOMES:

Student able to

1. Create Small applications using databases, Retrieve information from databases by using

queries


SYLLABUS

Accessing the Database: The first laboratory exercise is to connect to a database, populate it

with data, and run very simple SQL queries. (Data Definition, Table Creation, Constraints,

Insert, Select Commands, Update & Delete Commands.)

Basic SQL: This lab covers simple SQL queries. (Inbuilt functions in RDBMS.)

Intermediate SQL: This lab covers more complex SQL queries. (Nested Queries & Join

Queries, Control structures)

Advanced SQL: This lab covers even more complex SQL queries. (Procedures and

Functions, .PL/SQL, Cursors and Triggers)

Database Access from a Programming Language: This lab introduces you to database

access from a programming language such as Java or C#. Although phrased using

Java/JDBC, the exercise can be done using other languages, OBDC or ADO.NET APIs.

Building Web Applications: This lab introduces you to construction of Web applications.

Although phrased using the Java Servlet API, the exercise can be done using other languages

such as C# or PHP.

Project: Each student is assigned with a problem. The student is to develop a logical and

physical database design for the problem and develop Forms, Menu design and Reports.

A. The logical design performs the following tasks:

1. Map the ER/EER diagrams to a relational schema. Be sure to underline all primary keys,

include all necessary foreign keys and indicate referential integrity constraints.

2. Identify the functional dependencies in each relation

3. Normalize to the highest normal form possible

B. Perform physical design based above logical design using Oracle/MSSQL on Windows

platform and MySQL/PostgreSQL on Linux platform.

SAMPLE TERM PROJECTS:

1. Retailer database

2. Automobile sales database

3. Electronics vendor database

4. Package delivery database

5. Real estate database

43

REFERENCE BOOKS:

1. Database System Concepts, Avi Silberschatz , Henry F. Korth , S. Sudarshan ,McGraw-

Hill, Sixth Edition, ISBN 0-07-352332-1.

2. ORACLE PL/SQL by example. Benjamin Rosenzweig, Elena Silvestrova, Pearson

Education 3rd Edition

3. ORACLE Database Log PL/SQL Programming Scott Urman, TMG Hill.

4. SQL & PL/SQL for Oracle 10g, Black Book, Dr.P.S. Deshpande.

5. Oracle PL/SQL Programming, Steven Feuerstein, O‟Reilly Publishers.




44




(Regulation:R16)


II – SEMESTER


Hrs

Lab

Hrs

Total

Contact

Hrs/Week

Sessional

Marks

Exam

Marks

Total

Marks

M16 IT 1201 Web Systems &

Technologies 4 4 - 4 30 70 100

M16 CST 1202 Object Oriented Software

Engineering 4 4 - 4 30 70 100

M16 IT 1202 Information Security &

Cryptography 4 4 - 4 30 70 100

M16 IT 1203 Wireless & Mobile

Networks 4 4 - 4 30 70 100

#3 Elective- III 4 4 - 4 30 70 100

#4 Elective -IV 4 4 - 4 30 70 100

M16 IT 1216 Network Programming &

Web Programming Lab 2 - 3 3 50 50 100

M16 CST 1214 OOSE Lab 2 - 3 3 50 50 100

M16 IT 1217 Seminar 2 - - - 100 - 100

Total 30 24 6 30 380 520 900

Course Code Course

#1-Elective-III

M16 IT 1204 Mathematics Of Internet Systems & Control

M16 IT 1205 IT Infrastructure Planning & Management

M16 IT 1206 Geo-Informatics

M16 IT 1207 Data Base Security

M16 IT 1208 Business Intelligence

M16 IT 1209 Big Data Analysis

#2-Elective-IV

M16 IT 1210 Mobile Computing

M16 IT 1211 Soft Computing

M16 IT 1212 Cluster Computing

M16 IT 1213 Pervasive Computing

M16 IT 1214 Semantic Web

M16 IT 1215 Data warehousing & Data Mining

45

Code: M16 IT 1201

WEB SYSTEMS &TECHNOLOGIES



Credits : 4

COURSE OBJECTIVES:

1. To understand the advanced technologies of java JDBC, ASP, Servlets, EJB etc.

2. To design and Develop Servlets to Handle Server-side Exceptions.

3. To design applications using databases

4. To design beans using EJB

COURSE OUTCOMES:

1. Student knows about the advanced Java and design applications using Database Design

Applications and web pages for personal, Educational and business purposes.

2. Develop mobile computing applications based on the paradigm of context aware

computing and wearable computing

SYLLABUS

Introduction: History of the Internet and world wide web and HTML, Basic Internet

Protocols-HTTP, SMTP,Pop3, Mime, IMAP, Introduction to scripting Languages-Java

Scripts, Object based Scripting for the web structures, functions, arrays and Objects,

Dynamic HTML with Java Script

Dynamic HTML: Introduction to Object references, Dynamic Style, Dynamic Position,

Frames, Navigators, Event Models, On Check, On load, Mouse operations, Adding

Shaddows, Creating Images, Creating Gradients, Creating Motion with Blur, Data binding,

Sorting Table data, Binding of Images And Table.

Introduction to PHP Programming: Introduction, Database Access with PHP, PHP

Interpreters, Security Issues, File Handling with PHP, Working with HTML and DHTML,

PHP User Authentication.

Java Beans: Introduction to Java Beans, Advantages of Java Beans, BDK; Introspection,

Using Bound properties, Bean Info Interface, Constrained properties; Persistence,

Customizes, Java Beans API, Introduction to EJB‟s

Multimedia: Audio and Video Speech, Synthesis and Recognition, E-Business Models,

Online Payments and Security, Web Servers, Client and Server side Scripting, Accessing

Web servers, Apache Web Server.

Database, ASP and XML: RDBMS Models, Overview of SQL, , ASP-Working of ASP,

objects, Session Tracking and Cookies, ADO, Accessing Data Base with ASP, Serverside

Active, X Components, Web resources, XML- Document type definition, XML Schemas,

Document Object model, Presenting XML, Using XML Processors: DOM and SAX, Syntax

of AJAX, Application Development using XML and AJAX.

Servlets and JSP: Introduction to Servelets: Servlet Overview Architecture, HTTP

package, Handling Http Request & Responses, Using Cookies-Session Tracking, Security

Issues, Multitier architecture, JSP Overview, , JSP Processing. JSP Application Design with

MVC Setting Up and JSP Environment.

46

JSP Application Development: Generating Dynamic Content, Using Scripting Elements

Implicit JSP Objects, Conditional Processing, Displaying Values Using an Expression to Set

an Attribute, Declaring Variables and Methods Error Handling and Debugging Sharing Data

Between JSP pages, Requests, and Users Passing Control and Date between Pages, Sharing

Session and Application Data – Memory Usage Considerations

TEXT BOOKS:

1. Web Programming, building internet applications, 2/e, Chris Bates, Wiley Dreamtech

2. The complete Reference Java 2 ,5/e, Patrick Naughton , Herbert Schildt. TMH

3. Programming world wide web-Sebesta, PEA

REFERENCE BOOKS:

1. Internet , World Wide Web , How to program, Dietel , Nieto, PHI/PEA

2. Jakarta Struts Cookbook , Bill Siggelkow, S P D O‟Reilly

3. Web Tehnologies, 2/e, Godbole, kahate, TMH,202,

4. An Introduction to web Design , Programming ,Wang,Thomson

5. Web Applications Technologies Concepts-Knuckles, John Wiley

47

Code: M16 CST 1202

OBJECT ORIENTED SOFTWARE ENGINEERING




Credits : 4

COURSE OBJECTIVES:


2. To enable the student to get knowledge in SDLC (Analysis design , code and testing)


4. Understanding of Software Project Management including Planning/scheduling.

5. Emphasis on Black box, white box testing strategies

COURSE OUTCOMES:

1. Student Knows about the techniques of planning and monitoring the progress of a

software project.

2. Project management and cost estimation techniques

3. Be familiar with software development team architectures

SYLLABUS

Introduction to Object Oriented Software Engineering:Nature Of The Software, Types Of

Software , Software Engineering Projects, Software Engineering Activities, Software Quality,

Introduction To Object Orientation, Concepts Of Data Abstraction, Inheritance &

Polymorphism, Software Process Models-Waterfall Model, The Opportunistic Model , The

Phased Released Model, The Spiral Model, Evolutionary Model, The Concurrent

Engineering Model

Requirements Engineering: Domain Analysis, Problem Definition And Scope,

Requirements Definition, Types Of Requirements, Techniques For Gathering And Analyzing

Requirements, Requirement Documents, Reviewing, Managing Change In Requirements.

Unified Modeling Language & Use Case Modeling: Introduction To UML, Modeling

Concepts, Types Of UML Diagrams With Examples; User-Centred Design, Characteristics

Of Users, Developing Use Case Models Of Systems, Use Case Diagram, Use Case

Descriptions, The Basics Of User Interface Design, Usability Principles, User Interfaces.

Class Design and Class Diagrams: Essentials Of UML Class Diagrams, Associations And

Multiplicity, Other Relationships, Generalization, Instance Diagrams, Advanced Features Of

Class Diagrams, Interaction And Behavioural Diagrams: Interaction Diagrams, State

Diagrams, Activity Diagrams, Component And Deployment Diagrams.

Software Design And Architecture:The Process Of Design, Principles Leading To Good

Design, Techniques For Making Good Design Decisions, Writing A Good Design

Document., Pattern Introduction, Design Patterns: The Abstraction-Occurrence Pattern,

General Hierarchical Pattern, The Play-Role Pattern, The Singleton Pattern, The Observer

Pattern, The Delegation Pattern, The Adaptor Pattern, The Façade Pattern, The Immutable

Pattern, The Read-Only Interface Pattern And The Proxy Pattern; Software Architecture

Contents Of An Architecture Model, Architectural Patterns: The Multilayer, Client-Server,

Broker, Transaction Processing, Pipe & Filter And MVC Architectural Patterns.

48

Software Testing:Overview Of Testing, Testing Concepts, Testing Activities, Testing

Strategies, Unit Testing, Integration Testing, Function Testing, Structural Testing, Class

Based Testing Strategies, Use Case/Scenario Based Testing, Regression Testing,

Performance Testing, System Testing, Acceptance Testing, Installation Testing, OO Test

Design Issues, Test Case Design, Quality Assurance, Root Cause Analysis, Post-Mortem

Analysis.

Software Project Management:Introduction To Software Project Management, Activities

Of Software Project Management, Structure Of Project Plan, Software Engineering Teams,

Software Cost Estimation, Project Scheduling, Tracking And Monitoring.

Case Study:

a. Simple Chat Instant Messaging System

b. GPS Based Automobile Navigation System

c. Waste Management Inspection Tracking System (WMITS)

d. Geographical Information System

TEXT BOOK:

1. Object-Oriented Software Engineering Practical software development using UML and

Java by Timothy C. Lethbridge & Robert, Langaniere Mcgraw-Hill

REFERENCE BOOKS:

1. Object-Oriented Software Engineering: Using UML, Patterns and Java, Bernd Bruegge

and Allen H. Dutoit, 2nd Edition, Pearson Education Asia.

2. Software Engineering: A Practitioner's Approach, Roger S Pressman.

3. A Practical Guide to Testing Object-Oriented Software, John D. McGregor; David A.

Sykes, Addison-Wesley Professional.

49

Code: M16 IT 1202

INFORMATION SECURITY AND CRYPTOGRAPHY



Credits : 4

COURSE OBJECTIVES:

1. Identify and prioritize information assets.

2. Identify and prioritize threats to information assets.

3. Define an information security strategy and architecture.

4. Plan for and respond to intruders in an information system

5. Describe implications of security and privacy issues.

6. Present a disaster recovery plan for recovery of information assets after an incident

COURSE OUTCOMES:

Student can know about

1. Identify and prioritize information assets, threats

2. Define an information security strategy and architecture.

3. Plan for and respond to intruders in an information system and plan for recovery of

information assets after an incident

SYLLABUS

Introduction: Introduction to Security, Security Approaches, Principles of Security; Security

Services and Mechanism-confidentiality, Confidentiality, Authentication, Integrity, Non-

repudiation, access Control and Availability; Conventional Encryption Principles,

Conventional encryption algorithms, cipher block modes of operation, location of encryption

devices, key distribution Approaches of Message Authentication, Secure Hash Functions and

HMAC.

Network Security: A model for Internetwork security, Internet Standards and RFCs, Buffer

overflow & format string vulnerabilities, Introduction to TCP/IP TCP , fire walls, session

hijacking, ARP attacks, route table modification, UDP hijacking, and man-in-the-middle

attacks, Virtual Private Networks, Brief Study on Cryptography and Security

User Authentication Mechanisms: Introduction, Authentication Basics, Passwords

authentication tokens, Certificate based authentications, Biometrics based authentication ,

Kerberos, X.509 Directory Authentication Service, SSO Approaches

Public Key Infrastructure: Public key cryptography principles and algorithms, digital

signatures, digital Certificates, Certificate Authority and key management, Public Key

Cryptography Standards, Private Key Management, The PRIX Model, XML,PKI and

Security

Symmetric Key Cryptographic Algorithms: Overview of symmetric Key Cryptography

Algorithm types and modes; DES, IDEA, RC5, BLOWFISH, AES Algorithms; Differential

and Linear Cryptanalysis.

Asymmetric Key Cryptographic Algorithms: Overview of Asymmetric Key cryptography,

RSA Algorithm, Symmetric and Asymmetric Key Cryptography Together, Digital Signature,

Knap sack Algorithm and other Algorithms.

50

IP Security and Fire walls: IP Security Overview, IP Security Architecture, Authentication

Header, Encapsulating Security Payload, Combining Security Associations and Key

Management, Firewall Design principles, Trusted Systems, Intrusion Detection Systems.

Practical Implementation of Cryptography & Security: Cryptographic Solutions using

Java, Cryptographic Solutions Using Microsoft, Cryptographic Tool Kit, Security and

Operating Systems Pretty Good Privacy (PGP) and S/MIME.

TEXT BOOKS:

1. Network Security Essentials :Applications and Standards, William Stallings PEA.

2. Cryptography and Network Security, Atul Kahate, Tata McGraw Hill

REFERENCE BOOKS:

1. Hack Proofing your network, Ryan Russell, Dan Kaminsky, Rain Forest Puppy, Joe

Grand, David Ahmad, Hal Flynn Ido Dubrawsky, Steve W.Manzuik, Ryan Permeh,

Wiley Dreamtech,

2. Fundamentals of Network Security, Eric Maiwald (Dreamtech press)

3. Network Security - Private Communication in a Public World, Charlie Kaufman,

Radia Perlman, Mike Speciner, PEA/PHI.

4. Principles of Information Security, Whitman, Thomson.

5. Cryptography and network Security, Third edition, Stallings, PHI/PEA

6. Network Security: The complete reference, Robert Bragg, Mark Rhodes, TMH

7. Introduction to Cryptography, Buchmann, Springer.

51

Code: M16 IT 1203

WIRELESS & MOBILE NETWORKS



Credits : 4

COURSE OBJECTIVES:

1. To understand the basics of Mobile wireless Networking

2. To learn the role of Wireless networks in Mobile

3. To expose to the concept of Adhoc networks

COURSE OUTCOMES:

At the end of the course the student should be able to

1. Know various mobile wireless network

2. Know different Adhoc networks

3. Know about mobile data network

4. Work out security measures in Adhoc

SYLLABUS

Introduction: Introduction to Wireless Networks, Various Generations of Wireless

Networks, Virtual Private Networks- Wireless Data Services, Common Channel Signaling,

Various Networks for Connecting to the Internet, Blue tooth Technology, Wifi-WiMax-

Radio Propagation mechanism , Pathloss Modeling and Signal Coverage

Wireless Local Area Networks: Introduction-WLAN topologies-IEEE 802.11 Standards,

MAC Protocols,Comparision of 802.11 a,b,g and n Standards, HIPER LAN , ZigBee

802.15.4, Wireless Local Loop

Wireless Adhoc Networks: Basics of Wireless Networks, Infrastructured Versus

Infrastructureless Networks – Properties of Wireless, AD hoc Networks, Types of Ad Hoc

Networks, Challenges in AD Hoc Networks –Applications of Wireless AD Hoc Networks

Routing Protcols for Ad Hoc Networks:Introduction-Proactive Routing Protocols- Reactive

Routing protocols-Hybrid Routing Protocols-QoS Metrics-Energy impact issues in Routing.

Other Wireless Technologies: Introduction, IEEE 802.15.4 and Zigbee, General

Architecture, Physical Layer, MAC layer, Zigbee, WiMAX and IEEE 802.16, Layers and

Architecture, Physical Layer, OFDM Physical layer.

Mobile Communications: Introduction to cellular concept, Frequency Reuse, Handoff,

GSM: Mobile services, System architecture, Radio interface, Protocols, Localization and

calling, Handover, Security, and New data services, Introduction to mobile computing, novel

applications, limitations, and architecture.

Mobile Data Networks: Location/mobility management, Mobile IP, Dynamic routing

protocols, Location-based protocols, Emerging topics: sensor networking, Data-Oriented

CDPD network, GPRS and higher data rates, Short messaging service in GSM.

52

Security in Ad Hoc Networks: Introduction- Security Attacks, Intrusion Detection System,

Intrusion Prevention system, Intrusion Response system, Wired Equivalent Privacy( WEP) -

A Security Protocol for Wireless Local Area Networks (WLANs), Security in MANETs.

TEXT BOOKS:

1. Principles of Wireless Networks , Kaveth Pahlavan, K. Prasanth Krishnamurthy, Pearson

Publications, Asia, 2002

2. Mobile Cellular Communications, G.Sasibhusan Rao, Pearson Publications.

REFERENCE BOOK:

1. Guide to Wireless Ad Hoc Networks: Series: Computer Communications and Networks,

Misra, Sudip; Woungang, Isaac; Misra, Subhas Chandra, 2009, Springer

http://www.springer.com/series/4198

53

Code: M16 IT 1204

MATHEMATICS OF INTERNET SYSTEMS & CONTROL



Credits : 4

COURSE OBJECTIVES:

Understands the basic network and its graphs of internet systems and helps to find out the

high throughput of a network. The student can learn different congestion control algorithms

and can know parallel and distributed computation techniques.

COURSE OUTCOMES:

1. Able to know web basics and algorithms

2. Able to understand structure of internet search engine

3. Able to know real-time sources

4. Able to compute real time search engine

SYLLABUS

Introduction : Basics of Networks & Graphs: Random growth of graphs, adjacency matrix

and power laws, The Internet Graph, The Web Graph, Graph Communities and the Web,

Basics of Probability and algorithms: Computational Complexity, Exponential problems,

decidability, compressing & hashing, Randomized algorithms, randomness and humans,

Resource sharing between elastic & inelastic users

Design and Control of communication networks: Randomly fluctuating demands and

failures by adapting rates, rerouting of network traffic & reallocating resources

Rate Control algorithms for Internet: Stability & fairness, economic issues, scalable

models for simulation, Concepts in Congestion avoidance & Control, Maximizing throughput

of network & Minimizing packet-loss ratio for Networks

Linear Analysis with Delay: Primal Controllers-High Throughput TCP and AVQ, Dual

Algorithm, Primal Dual Algorithm, Exponentially smoothed rate feedback, Proportionally-

fair controller

Congestion Control Algorithms for Internet: Algorithms for single link and single flow-

Window Flow Control,Random early detection (RED), explicit congestion

notification(ECN), High throughput TCP, stochastic and deterministic models in congestion

control, Resource allocation for congestion control

Anatomy of Internet Search Engine: Basic Data Structure, Crawling the Web, Page

Relevance and Ranking, Answering the user queries, Role of distributed & parallel

computing internet Browsers and search engines: Caching web pages, browsers and search

engines, DNS tree, File sharing on internet

Parallel and distributed Computation: Basic rules of cooperation, logical problems on

working in parallel, distributed world, routing methods

Real-time Sources and Distributed Control: Probing & Distributed Admission Control,

Queuing Model at Link Buffer, Diffusion Approximation-Brownian Motion Through a Queu

54

TEXT BOOKS:

1. Mathematical and Algorithmic Foundations of the Internet, Fabrizio Luccio, Linda Pagli

and Graham Steel, Chapman & Hall, 2011

2. The Mathematics of Internet Congestion Control (Systems and Control: foundations and

Applications), Birkhauser Boston, 2003

REFERENCE BOOK:

1. Linked: The New Science of Networks, Barabasi A.L,Perseus Publishing,Cambridge,

2002

55

Code: M16 IT 1205

IT INFRASTRUCTURE PLANNING AND MANAGEMENT



Credits : 4

COURSE OBJECTIVES:

1. Document the different phases in the life cycle of an IT infrastructure project.

2. Gather background information and research and describe its impact on the project.

3. Describe and explain the main features of project evaluation.

COURSE OUTCOMES:

At the end the course

1. Able to find out primary issues of a project. 2. Able to find out different operations in a project. 3. Able to handle a project without any problems.

SYLLABUS

Introduction to Infrastructure Planning and Management: Computer Basics, Network

and Internet, Computing Resources, Information Technology, IT Infrastructure Management,

Challenges in IT Infrastructure Management

Design Issues: Design Issues of IT organizations and IT Infrastructure, Determing Customer

Requirements, IT system Management Process, IT Services Management Process,

Information System Design Process, Patterns for IT Systems Managements, IT infrastructure

Library

Virtualization: Desktop Virtualization Applications, Remote Desktop Services, Terminal

Services, Server Virtualization, Selecting the right Virtualization Technology, Dynamic

Datacenter

System Center: System Center Service Manager, System Center Data Protection Manager,

System Center Virtual Machine Manager, System Center Operations Manager, System

Center Configuration Manager, Dynamic Datacenter

Storage Management: Introduction to Storage, Backup and Storage, Archive and Retrieve,

Disaster Recovery, Space Management, Database wand Application Protection, Bare

Machine Recovery, Data Retention, Microsoft SQL Server/Database Server

Desktop Scenarios: Windows Optimized Desktop Scenarios, Communication

&Collaboration Exchange Server, SharePoint Server

Security: Computer Security, Internet Security, Physical Security, Malware Response ,

Forefront Identity Manager, Forefront Unified Access Gateway, Selecting the Right NAP

Architecture

Case Study: Any Case Study Consisting of (Eg. Asset Network Incorporation)- IT Service

Continuity Management, Capacity Management, Availability Management, Configuration

Management, Incident Management, Problem Management, Storage Management, Identity

Management

56

TEXT BOOK:

1. IT Infrastructure & Its Management, Guptha, TMH

REFERENCE BOOKS:

1. Infrastructure planning and design-microsoft

2. Selecting the right virtualization Technology by-Microsoft inc

3. IPD in the Technet Library

4. IPD in the Microsoft Partner Network

5. Microsoft Solution Accelerator

57

Code: M16 IT 1206

GEO INFORMATICS



Credits : 4

COURSE OBJECTIVES:

1. To learn the basic concepts of geo-informatics in brief that includes Geographical

Information System (GIS), Remote Sensing (RS), and Global Positioning System (GPS).

2. To learn the data needs and database development analysis in GIS environment.

3. To understand various applications of GIS

COURSE OUTCOMES:

1. Graduates will demonstrate the ability to model and development of application in

Geospatial arena interpret and analyze data, and report results.

2. Graduates will demonstrate the ability to develop Geospatial system that meets desired

specifications and requirements

3. Graduates will demonstrate an understanding of their professional and ethical

responsibilities.

SYLLABUS

Introduction: Definition of GIS and Related Terminology-Evolution of GIS-Components of

GIS-Approaches to study of GIS Maps and GIS: Map Scale- Classes of maps-The mapping

Process-Plane coordinate systems and Transformations- Geographic Coordinate System of

Earth- Map Projection- Establishing a spatial framework for mapping Locations on Earth-

Geo-referencing-Acquisition of Spatial Data for the terrain- Topographic Mapping-Attribute

Data for Thematic Mapping

Digital Representation of Geographic Data: Technical Issues Pertaining to Digital

Representation of Geographic Data-Database creation and management-Raster Geographic

and Vector data representation-Object oriented Geographic Data representation-Relationship

between Data representation and Data Analysis in GIS Data Quality and Data Standards:

Concepts and Definitions of Data Quality-Components of Geographic Data Quality-

Assessment of Data Quality- Managing Spatial Data Errors-Geographic Data Standards-

Geographic Data Standards And GIS Development

Raster and Vector-Based GIS Data Processing: Acquiring and Handling Raster Data

Processing Cartographic Modeling- Characteristics of Vector- Based GIS Data

Processing Vector Data Input Functions Non-topological GIS Analysis Functions

Feature-Based Topological Functions Layer-Based Topological Functions Vector-Based

Output Functions Application Programming

Visualization of Geographic Information and Generation: Cartography in the Context

of GIS-Human-Computer Interaction and GIS- Visualization of Geographic Information

Principles of Cartographic Design in GIS-Generation of Information Products

Remote Sensing and GIS Integration: Principles of Electromagnetic Remote Sensing

System Classifications-Imaging Characteristics of Remote Sensing Systems-Extraction of

Metric Information from Remotely Sensed Images-Extraction of Thematic Information from

Remotely Sensed Images- Integration of Remote Sensing and GIS

58

Digital Terrain Modeling: Definitions and Terminology Approaches to Digital Terrain-

Data Sampling- Acquisition of Digital Terrain Data-Data Processing, Analysis, and

Visualization-Applications of Digital Terrain Models.

Spatial Analysis and Modeling: Descriptive Statistics-Spatial Auto Correlation- Quadratic

Counts and Nearest- Neighbor Analysis-Trend Surface Analysis-Gravity Models-Network

Analysis-GIS Modeling

GIS Implementation and Project Management: Software Engineering as Applied to GIS-

GIS Project Planning-Systems Analysis and User Requirements-Geographic Database

Design Methodology-GIS Application Software Design Methodology-Systems

Implementation and Technology Rollout-Systems Maintenance and Technical Support, GIS

Issues and Prospects: Issues of Implementing GIS-The Trend of GIS-Development

Frontiers of GIS Research.

TEXT BOOK:

1. Concepts and Techniques of Geographic Information Systems, by C. P. Lo & Albert K.

W. Yeung, Prentice Hall of India Ltd

REFERENCE BOOKS:

1. An Introduction to Geographical Information Systems, by Ian Heywood, Sarah

Cornelium & Steve Carver, Pearson Education

2. Introduction to Geographic Information Systems, by Kang-rsung Chang, Tata McGraw

Hill Publishing Company Limited

59

Code: M16 IT 1207

DATABASE SECURITY



Credits : 4

COURSE OBJECTIVES:

1. To understand the basic concepts of database security.

2. To learn security issues and solutions

3. To understand threats to learn how to perform data encryption. 4. To understand Enterprise Security Policy

COURSE OUTCOMES:

1. Able to understand the database security framework

2. Will be able to learn database access control

3. Will be able to understand database security techniques.

4. Will be able to implement security for databases.

SYLLABUS

Introduction To Database Security: Fundamental Data Security Requirements, Data

Security Concerns, Compliance Mandates, Security Risks, Developing Enterprise Security

Policy, Defining a Security Policy, Implementing a Security Policy, Techniques to Enforce

Security

Database Access Control: User Authentication, Protecting Passwords, Creating Fixed

Database Links, Encrypting Database Link Passwords, Using Database Links Without

Credentials, Using Database Links And Changing Passwords, Auditing With Database Links,

Restricting A Database Link With Views, Trust Management & Negotiation

Database Security Issues: Database Security Basics, Security Checklist, Reducing

Administrative Effort, Applying Security Patches, Default Security Settings, Secure

Password Support, Enforcing Password Management, Protecting The Data Dictionary,

System and Object Privileges, Secure Data Outsourcing, Security in Advanced Database

Systems, Security in Data Warehousing and OLAP Systems, Managing Enterprise User

Security

Framework For Database Security,: Security for Workflow Systems, Secure Semantic

Web Services, Spatial Database Security, Security Reengineering, Strong Authentication,

Single Sign-On, Public Key Infrastructure (PKI) Tools, Configuring SSL on the Server,

Certificates, Using Kerberos for Authentication

Database Security Solutions: Maintaining Data Integrity, Protecting Data, Controlling Data

Access, Combining Optional Security Features, Compliance Scanner, Policy Trends in

Database Control, Watermarking: Copyright Protection, Trustworthy Record Retention and

Recovery, Privacy-Preserving Data Mining & Data Publishing. Privacy in Location-Based

Services

Database Auditing : Auditing Database Users, User Privileges And Objects: Monitoring for

Suspicious Activity, Standard Database Auditing, Setting the AUDIT_TRAIL, Specifying

Audit Options, Viewing Auditing Options, Auditing the SYSDBA Users, Audit to XML

Files, Value-Based Auditing, Auditing DML Statements, Triggering Audit Events,

Maintaining the Audit Trail

60

Database Privileges And Roles: Authorization, Privileges, Benefits of Roles, Using Proxy

Authentication With Roles, Creating An Enterprise Role, Securing Objects and Application

Roles, Data Masking Primitives And Routines, Privacy in Location- Based Services

Data Encryption For Database Security: Problems Solved by Encryption, Storing the Key

in Database, Key Management by User, Application-Based Encryption, Cipher Block

Modes , Hash and Message Authentication Code, Transparent Data Encryption (TDE) & File

Encryption Methods.

TEXT BOOKS:

1. Database Security, S.Castano, M. Fugini, G. Martella,P. Samarati, Addision-Wesley

2. Database Security By Alfred Basta, Melissa Zgola, Cengage Publication, 2012

REFERENCE BOOKS:

1. Database Security & Auditing By Hassan A Afyouni, Cengage Delmar Learning India

Pvt. Ltd, 2009.

2. Handbook Of Database Security:Applications And Trends,Michael Gertz, Sushil Jajodia,

Springer.

61

Code: M16 IT 1208

BUSINESS INTELLIGENCE



Credits : 4

COURSE OBJECTIVES:

1. Use various symbolic knowledge representation to specify domains and reasoning tasks

of a situated software agent.

2. Use different logical systems for inference over formal domain representations, and trace

how a particular inference algorithm works on a given problem specification.

3. Understand the conceptual and computational trade-offs between the expressiveness of

different formal representations.

COURSE OUTCOMES:

1. Understand different types of AI agents

2. Know various AI search algorithms (uninformed, informed, heuristic, constraint

satisfaction, genetic algorithms)

3. Understand the fundamentals of knowledge representation (logic-based, frame-based,

semantic nets), inference and theorem proving

4. Ability to apply knowledge representation, reasoning, and machine learning techniques to

real-world problems

SYLLABUS

Introduction to Artificial Intelligence: Artificial Intelligence, AI Problems, AI Techniques,

Defining the Problem as a State Space Search, Problem Characteristics , Production Systems,

Search: Issues in The Design of Search Programs, Un-Informed Search and Heuristic Search

Techniques & Algorithms. AI Applications in Biology, Engineering, Technology and

Business

Knowledge Representation: Knowledge General concepts, Representations & Approaches

to Knowledge Representation, Forward Vs Backward Reasoning, Symbolic Logic:

Computable Functions and Predicates, FOPL Representation of knowledge, Normal Forms,

Unification and Resolution, Basic Inference Techniques; Structured Representation of

Knowledge: Semantic Nets, Partitioned Semantic Nets, Frames, Conceptual Dependency,

Conceptual Graphs, Scripts, CYC

AI Techniques & Programming: Logic Based Programming- AI Programming languages:

Overview of LISP & Prolog, Search Strategies in LISP, Production System using Prolog,

Fuzzy Logic: Crisp Sets, Fuzzy Sets, Fuzzy Logic Control, Fuzzy Inferences & Fuzzy

Systems. Matching Techniques, Partial Matching, Fuzzy Matching Algorithms and RETE

Matching Algorithms;, Pattern matching in LISP .

Overview Of Business Intelligence: Managerial, Strategic And Technical Issues Associated

With BI , Database Systems And Database Integration, Data Warehousing, Data Marts.

Query and Report Generation Technologies, Business Process Modeling & Analysis,

Planning: Components of a Planning System, Goal Stack Planning, Hierarchical Planning,

Reactive Systems

62

Business Analytics For BI: Data Ware House Architecture: OLAP, Data Cubes, Reporting

Tools, Balance Score card, Dash Board design and Implementations, Data Mining And

Analytical Tools, Multidimensional/Hyper Cubes , Enterprise Data – Enterprise Data And

Information Flow. Information Management and Regulatory Compliance Case Studies:

Experts Systems : Overview of an Expert System, Structure of an Expert Systems, Different


Systems, Concepts and Practice of DSS Modeling, Knowledge Acquisition and Validation

Techniques, Black Board Architecture, Knowledge Building System Tools, Expert System

Shells, Expert system Shell in LISP, Fuzzy Expert systems

BI Tools and Intelligent Agents: Overview of Intelligent agents, Design and

Implementation of Intelligent Agent system, languages and Tools, Multi-Agent systems;

Applications in Adaptive Information Retrieval systems, Decision Support Systems, BI

Reporting Tools-BIRT, Pentaho, Integration with mysql server, Knowledge Discovery

Systems, Agents in Computational Biology, Smart Systems and Robots.

Case Studies in Business Intelligence: :Business model development from marketing,

finance domains-Dimensional modeling, metrics, DataCube creation. Data visualization

through BI tools for OLAP operation. Publishing BI reports in Enterprise portals.`

TEXT BOOKS:


2. Decision Support and Business Intelligence Systems, Efraim Turban, Ramesh Sharda, Jay

Aronson, David King, , Pearson Education, 2009

REFERENCE BOOKS:



MIT Press.

3. Artificial Intelligence, Elaine Rich, Mcgraw-Hill Publications


5. The Savy Manager‟s Guide GettingOnboard with Emerging IT, David Loshin, Morgan

Kauffmann Publishers, 2009

63

Code: M16 IT 1209

BIG DATA ANALYTICS



Credits : 4

COURSE OBJECTIVES:

1. To provide advanced knowledge and skills in the field of Computer Science and

Engineering.

2. Capable to quickly adapt to new technology in the field of Big Data, assimilate new

information, and solve real world problems.

3. To pursue applied research in the advance field of computer science and be committed to

life-long learning activities.

COURSE OUTCOMES:

On completion of the programme the graduates will

1. Be able to apply the knowledge of computing tools and techniques in the field of

BigData For solving real world problems encountered in the Software Industries

2. Be able to analyze the various technologies & tools associated with Big Data.

3. Be able to identify the challenges in BigData with respect to IT Industry and pursue

quality research in this field with social relevance

SYLLABUS

Introduction:, Velocity, Variety, Veracity; Drivers for Big Data, Sophisticated Consumers,

Automation, Monetization, Big Data Analytics Applications: Social Media Command

Center, Product Knowledge Hub, Infrastructure and Operations Studies, Product Selection,

Design and Engineering, Location-Based Services, Online Advertising, Risk Management

Architecture Components: Massively Parallel Processing (MPP) Platforms, Unstructured

Data Analytics and Reporting: Search and Count, Context-Sensitive and Domain-Specific

Searches, Categories and Ontology, Qualitative Comparisons, Data Privacy Protection, Real-

Time Adaptive Analytics and Decision Engines

Advanced Analytics Platform: Real-Time Architecture for Conversations, Orchestration

and Synthesis Using Analytics Engines, Entity Resolution, Model Management, .Discovery

Using Data at Rest, Integration Strategies

Implementation of Big Data Analytics: Revolutionary, Evolutionary, or Hybrid, Big Data

Governance, Integrating Big Data with MDM, Evolving Maturity Levels

Map-Reduce and the New Software Stack: Distributed File Systems .Physical

Organization of Compute Nodes, Large-Scale File-System Organization, Map-Reduce

features: Map Tasks, Grouping by Key, Reduce Tasks, Combiners, Map-Reduce Execution,

Coping With Node Failures, Algorithms Using Map-Reduce for Matrix multiplication,

Relational Algebra operations, Workflow Systems, Recursive Extensions to Map-Reduce

Communication Cost Models, Complexity Theory for Map-Reduce, Reducer Size and

Replication Rate, Graph Model and Mapping Schemas, Lower Bounds on Replication Rate.

64

Mining Data Streams: Stream Data Mode l and Management Stream Source, Stream

Queries, and issues, Sampling Data in a Stream , Filtering Streams, Counting Distinct

Elements in a Stream, Estimating Moments, Counting Ones in a Window, Decaying

Windows

Link Analysis: PageRanking in web search engines, Efficient Computation of PageRank

using Map-Reduce and other approaches, Topic-Sensitive PageRank , Link Spam, Hubs and

Authorities

TEXT BOOKS:

1. Big Data Analytics:Disruptive Technologies for Changing the Game, Dr. Arvind Sathi,,

First Edition October 2012, IBM Corporation

2. Mining of Massive Datasets, Anand Rajarama, Jure Leskovec, Jeffrey D. Ullman.E-book,

2013

REFERENCE BOOK:

1. Big Data Imperatives, Soumendra Mohanty, Madhu Jagadeesh, Harsha Srivatsa, Apress,

e-book of 2012

65

Code: M16 IT 1210

MOBILE COMPUTING



Credits : 4

COURSE OBJECTIVES:

1. Introduction of an advanced element of learning in the field of wireless communication.

2. The students to the concepts of wireless devices and mobile computing.

3. To introduce wireless communication and networking principles, that support

connectivity to cellular networks, wireless internet and sensor devices.

COURSE OUTCOMES:

1. A working understanding of the characteristics and limitations of mobile hardware

devices including their user-interface modalities

2. The ability to develop applications that are mobile-device specific and demonstrate

current practice in mobile computing contexts.

3. A comprehension and appreciation of the design and development of context-aware

solutions for mobile devices.

SYLLABUS

Introduction to Mobile Computing, Overview of Mobile Technologies, Limitations, The

Ubiquitous Network, Architecture for Mobile Computing, Three-Tier Architecture, Design

Considerations for Mobile Computing, Mobile Computing Through Internet, Mobile Devises

and Mobile-Enabled Applications.

Introduction To Wireless Networking, Various Generations of Wireless Networks,

Wireless LANs, Advantages and Disadvantages of WLANs, Fixed Network Transmission

Hierarchy, Differences in Wireless and Fixed Telephone Networks, Traffic Routing in

Wireless Networks, WAN Link Connection Technologies, Cellular Networks.

WLAN Topologies, WLAN Standard IEEE 802.11, Comparison Of IEEE 802.11a, B, G and

N Standards, Wireless PANs, Hiper LAN, Wireless Local Loop, ATM, Virtual Private

Networks, Wireless Data Services, Common Channel Signaling, Various Networks for

Connecting to The Internet.

Emerging Technologies: Introduction - Bluetooth - Radio Frequency Identification (RFID),

WIMAX -Mobile IP - Ipv6 - Java Card, TCP/IP in the Mobile Setting, GSM and GPS

Data Management Issues, Data Replication For Mobile Computers, Adaptive Clustering for

Mobile Wireless Networks, File System, Disconnected Operations, Data Services in GPRS -

Applications for GPRS - Limitations - Billing and Charging.

Communications Asymmetry, Classification of New Data Delivery Mechanisms, Push-

Based Mechanisms, Pull-Based Mechanisms, Hybrid Mechanisms, Selective Tuning

(Indexing) Techniques. CDMA, GSM , Wireless Data, 3GNetworks and Applications.

Introduction to Mobile IP, Introduction To Wireless Application Protocol, Application

Layer MMS - GPRS Applications, Short Message Service (SMS): Mobile Computing Over

SMS - SMS - Value Added Services Through SMS -Accessing the SMS Bearer.

66

TEXT BOOKS:

1. Mobile Computing - Technology Applications And Service Creation, Asoke K Talukder

and Roopa R.Yavagal, TMH 2006.

2. Mobile Cellular Communication, Gottapu Sasibhushana Rao,, Pearson Education, First

Edition, 2013.

REFERENCE BOOKS:

1. Principles Of Computing, Uwe Hansmann, Lother Merk, Martin S.Nicklous, Thomas

Staber, 2nd Ed., Springer International Edition.

2. Mobile Communications, J.Schiller, Addison-Wesley, 2003

3. Stojmenovic And Cacute, “Handbook Of Wireless Networks And Mobile Computing”,

Wiley, 2002.

67

Code: M16 IT 1211

SOFT COMPUTING



Credits : 4

COURSE OBJECTIVES:

1. Introduce students to soft computing concepts and techniques and foster their abilities in

designing and implementing soft computing based solutions for real-world and


2. Explain the students about fuzzy sets and its operations,

3. Introduce students to fuzzy systems, fuzzy logic and its applications

4. Explain the students about Artificial Neural Networks and various categories of ANN.

COURSE OUTCOMES:

At the end of the course students

1. Able to understand genetic algorithm fundamentals and its operators and procedure

2. Understand artificial neural network model and its activation functions

3. Understand different operations of GA

SYLLABUS

Soft Computing: Introduction to Fuzzy Computing, Neural Computing, Genetic Algorithms,

Associative Memory, Adaptive Resonance Theory, Different Tools and Techniques,

Usefulness and Applications.

Fuzzy Sets and Fuzzy Logic: Introduction, Fuzzy Sets Versus Crisp Sets, Operations on

Fuzzy Sets, Extension Principle, Fuzzy Relations and Relation Equations, Fuzzy Numbers,

Linguistic Variables, Fuzzy Logic, Linguistic Hedges, Applications.

Interference in fuzzy logic: fuzzy if-then rules, Fuzzy implications and Fuzzy algorithms,

Fuzzifications and Defuzzificataions, Fuzzy Controller, Fuzzy Controllers, Fuzzy Pattern

Recognition, Fuzzy Image Processing, Fuzzy Database.

Artificial Neural Network: Introduction, Artificial Neuron and its model, activation

functions, Neural network architecture: single layer and multilayer feed forward networks, re-

current networks. Various learning techniques, perception and convergence rule, Auto-

associative and hetro-associative memory , Hebb's Learning, Adaline, Perceptron

Multilayer Feed Forward Network, Back Propagation Algorithms, Different Issues

Regarding Convergence of Multilayer Perceptron, Competitive Learning, Self-Organizing,

Feature Maps, Adaptive Resonance Theory, Associative Memories, Applications.

Evolutionary and Stochastic Techniques: Genetic Algorithm (GA), Genetic

Representations, (Encoding) Initialization and Selection, Different Operators of GA, Analysis

of Selection Operations, Hypothesis of Building Blocks, Schema Theorem and Convergence

of Genetic Algorithm, Simulated Annealing and Stochastic Models, Boltzmann Machine,

Applications.

Rough Set: Introduction, Imprecise Categories Approximations and Rough Sets, Reduction

of Knowledge, Decision Tables and Applications.

68

Hybrid Systems: Neural-Network-Based Fuzzy Systems, Fuzzy Logic-Based Neural

Networks, Genetic Algorithm for Neural Network Design and Learning, Fuzzy Logic and

Genetic Algorithm for Optimization, Applications

TEXT BOOKS:

1. Neural Networks, Fuzzy Logic and Genetic Algorithm: Synthesis and Applications, S.

Rajsekaran and G.A. Vijayalakshmi Pai, Prentice Hall of India.

2. Rough Sets, Z.Pawlak, Kluwer Academic Publisher, 1991.

3. Intelligent Hybrid Systems, D. Ruan, Kluwer Academic Publisher, 1997.

REFERENCE BOOKS:

1. Artificial Intelligence and Intelligent Systems, N.P.Padhy, Oxford University Press.

2. Neural Fuzzy Systems, Chin-Teng Lin & C. S. George Lee, Prentice Hall PTR. Addison-

Wesley

3. Learning and Soft Computing, V. Kecman, MIT Press, 2001

4. Fuzzy Sets and Fuzzy Logic, Klir & Yuan, PHI, 1997

69

Code: M16 IT 1212

CLUSTER COMPUTING



Credits : 4

COURSE OBJECTIVES:

1. The course will provide an insight for achieving cost efficient high performance system.

2. The course will deal with design and architecture of cluster computing.

COURSE OUTCOMES:

At the end of the course student will

1. Have knowledge of virtual technologies and Service-oriented architecture,

2. Have knowledge of Architecture for Cluster Computing, process scheduling and load

balancing.

SYLLABUS

Introduction: Overview of Cluster Computing, The Role of Clusters, Definition and

Taxonomy Of Parallel Computing, Hardware System Structure, Node Software, Resource

Management, Distributed Programming, Limitations

Cluster Planning, Architecture, Node Hardware and Node Software, Design Decisions

Network Hardware: Internet technologies, Ethernet, cLAN, QsNet, Infiniband, Packet

Format, NIC Architecture, hubs & Switches.

Network Software: TCP/IP, Sockets, Higher Level Protocols, Distributed File systems,

Remote Command Execution

Cluster Setup: Installation & Configuration, System Access Models, Assigning Names,

Installation of Node Software, Basic System Administration

Clusters Management: Cluster Workload Management Activities, Queuing, scheduling and

monitoring, Resource Management and Accounting

Virtualization technologies; Parallel and Virtual file systems, Introduction, Programming

with parallel File systems, Benchmarks

TEXT BOOK:

1. Beowulf Cluster Computing with Linux, 2nd Edition, edited by William Gropp, Ewing

Lusk, Thomas Sterling, MIT Press, 2003

REFERENCE BOOKS:

1. In Search of Clusters: The ongoing battle in Lowly Parallel Computing, Gregory F. P

Fister, Second Edition, Prentice Hall Publishing Company, 1998.

2. How to Build a Beowulf - A Guide to the Implementation and Application of PC Clusters,

Thomas Sterling, John Salmon, Donald J. Becker and Daniel F. Savarese, MIT Press,

1999

70

Code: M16 IT 1213

PERVASIVE COMPUTING



Credits : 4

COURSE OBJECTIVES:

1. Student can understand underlying technologies and applied standards for building up

pervasive solutions.

2. This includes WAP, GPRS, Bluetooth, Infrared, Voice over IP, among others.

3. Expose students to latest technologies that relate to device technologies and pervasive

computing, such as wearable computing and smart identification.

COURSE OUTCOMES:

At the end of the course, students should be able to:

1. Identify distinguishing features of the different mobile device categories,

2. Understand the role of the Wireless Application Protocol inenabling mobile devices to

access the Internet

3. Understand elementary to medium-level (complexity-wise) user interface applications for

all three platforms.

SYLLABUS

Pervasive Computing: Introduction to Ubiquitous Computing (Popularly known as

Pervasive Computing), Evolution of Pervasive Computing, Pervasive Computing Principles :

Decentralization, Diversification, Connectivity, Simplicity, Pervasive Computing

Characteristics, Pervasive Information Technology

Pervasive Architecture: Background, Scalability and Availability, Pervasive Web

Application Architecture, Implementation Issues.

Pervasive Devices: Device Categories, Device Characteristics, Software Components in the

Device, Information Access Devices, Smart Identification, and Embedded Controls, Hand

Held Computers, Cellular Phones, Smart Phones, Smart Cards and Smart Appliances

Pervasive Connectivity: Protocols, Security, Network Management, Mobile Internet, WAN:

Cellular Basics, Major Digital Cellular Systems, Advanced Cellular Radio Standards, Short

Range Wireless Communication: DECT, Bluetooth, Irda, Home Networks.

Pervasive Applications: Home Services: System View, Communications, Home

Automation, Energy and Security Services, Remote Home Health Care Services, Business

Services, Healthcare Management, Consumer Services: Interactive Advertisement, Loyalty,

Shopping, Payment Services

Pervasive Synchronization: Definition of Synchronization, Models of Synchronization,

Challenges In Synchronizing Data, Industry Data Synchronization Standards: Infrared Mobile

Communications, WAP, Third Generation Partnership Program, Syncml, Synchronization

Solutions

Security Issues in Pervasive Computing : Importance of Security, Cryptographic Patterns

And Methods - Light Weight Cryptography -Light Weight Symmetric and Asymmetric

Cryptographic Algorithms, Cryptographic Tools - Hash, MAC, Digital Signatures

71

Mobile Internet and Web Services: WAP Architecture, Wireless Application Environment:

Wireless Markup Language, WAP Binary XML Content Format, WML Script, XHTML

Mobile Proile, I-Mode, Web Services Architecture: WSDL, ADDI, SOAP, Web Services

Security, Web Services For Remote Portals

TEXT BOOKS:

1. Pervasive Computing: The Mobile World By Uwe Hansmann , Lothar Merk, Springer.

2. Pervasive Computing: Technology And Architecture of Mobile Internet Applications

Jochen Burkhardt , Horst Henn , Stefan Hepper , Klaus Rindtorff , Thomas Schaeck

REFERENCE BOOK:

1. Seng Loke, Context-Aware Computing Pervasive Systems, Auerbach Pub., New York,

2007.


http://www.amazon.com/s/ref=rdr_ext_aut?_encoding=UTF8&index=books&field-author=Uwe%20Hansmann

http://www.amazon.com/s/ref=rdr_ext_aut?_encoding=UTF8&index=books&field-author=Lothar%20Merk

http://www.amazon.com/s/ref=ntt_athr_dp_sr_1/188-8313688-2368359?_encoding=UTF8&field-author=Jochen%20Burkhardt&search-alias=books&sort=relevancerank

72

Code: M16 IT 1214

SEMANTIC WEB



Credits : 4

COURSE OBJECTIVES:

1. To teach the concepts, technologies and techniques underlying and making up the

Semantic Web.

2. Understand and use ontologies in the context of Computer Science and the semantic web

COURSE OUTCOMES:

1. Able to understand the rationale behind Semantic web.

2. Understand the concept structure of the semantic web technology and how this

technology revolutionizes the World Wide Web and its uses.

3. Able to model and query domain knowledge as ontologies defined using standards such

as RDF and OWL.

SYLLABUS

Introduction to Semantic Web: Introduction, Semantic Web, URI, RDF, Ontologies,

Inferences, DAML, Semantic Web Languages, Semantic Annotation, Classification,

Information Extraction, Ontology Assignment, XML, Syntax of XML,XML Schema,

Semantic Web Applications to E-Commerce, E-Government and E-Banking, Semantic Web

in Life Sciences, RIF Applications.

Semantic Web Structure: Semantic Web Layers Architecture, Different Layers, Match

Making, Multi Information Retrieving, Digital Signature, Semantic Memory, Semantic Web

Enabled Service Oriented Architecture (SESA), SESA Services, SESA Middle Ware.

Resource Descriptive Languages RDF: Introduction to RDF, Syntax of RDF, Advanced

Feature,Simple Ontologies in RDF Schema, Encoding Special Data Structures, Semantics

Model Theoritic Sentics for RDFs, Syntactic Reasoning with Deduction Rules Syntactic

Limits of RDFs

Web Ontology Languages: OWL Syntax, OWL Species, OWL2 Standards, OWL Formal

Semantics, Description Logics, Model Theoretic Semantics of OWL, SWRL, Semantic Web

Rules, Languages, Syntax of SWRL, Rules and Safety, Implementation & Applications.

Ontology Engineering: Requirement Analysis, Ontology Knowledge Creation, Ontologies

and Rules: Definition of a Rule, Datalog as First order Rule Language, Combining Rules with

OWDL, Rule Interchanging Formats RIF, Quality Assurance of Ontologies, Modular

Ontologies, Divide and Conquer, Software Tools.

Ontology Query Languages: Semantic Web Query Languages and Implementations, ROPS

(RDF OWL Processing Systems), SWOPS (SWRL Ontology Processing System, Bench

Marking Results, SPARQL, Query Languages for RDF, Conjunctive Queries for OWLDL.

Semantic Web Mining: Introduction, Concepts in Semantic Web Mining, XML, RDF &

Web Data Mining, Ontologies and Web Data Mining, Agents in Web Data Mining, Web

Mining and Semantic Web As a Data Base, semantic Interoperability and Web Mining Web

Mining Vs Semantic Web Mining

73

Semantic Web Tools & Applications: Web Data Exchange and Syndication, Semantic

WIKI‟s, Semantic Portals, Semantic Meta Data in Data formats, Semantic Web Services

Modeling Ontologies, Semantic Web Service Design Tools, Ontologies for Standardizations

WMO and SWMO Applications

TEXT BOOK:

1. Foundations of Semantic Web Technologies, Pascal Hitzler, Markus Krotzsch,

Sebastian Rudolph , CRC Press.

REFERENCE BOOKS:

1. Web Data Mining and Applications in Business Intelligence and Counter Terrorism,

Bavani Thuraisingham, CRC Press, June 2003

2. 2. Implementing Semantic Web Services-The SESA Frame Work, D. Fensel;M.Kerrigan;

M.Zaremba, Springer

3. 3. Enabling Semantic Web Services- The Web Service Modeling Ontology, Fensel,D;

Lausen,H;Pollers,ABruijn,J;Stollberg,M; Spriger

4. A Semantic Web Primer, Paul Groth, Frank van Harmelen, Rinke Hoekstra, The MIT

Press2012

5. Programming the Semantic Web, Toby Segaran, Colin Evans, Jamie Taylor Oreilly

Publications, July 2009

http://www.google.co.in/search?tbo=p&tbm=bks&q=inauthor:%22Pascal+Hitzler%22

http://www.google.co.in/search?tbo=p&tbm=bks&q=inauthor:%22Markus+Krotzsch%22




74

Code: M16 IT 1215

DATA WAREHOUSING & DATA MINING



Credits : 4

COURSE OBJECTIVES:

1. To differentiate OnLine Transaction Processing and OnLine Analytical processing

2. Learn Multidimensional schemas suitable for data warehousing

3. Understand various data mining functionalities

4. To Inculcate knowledge on data mining query languages.

5. To Know in detail about data mining algorithms

6. The objective of this course is to study various techniques involved in data mining, data

warehousing.

COURSE OUTCOMES:

1. Extract knowledge using data mining techniques

2. At the closing stage of the course, students will be able to analyze different operations

and techniques involved in data mining.

SYLLABUS

Introduction to Data Mining: Evolution of I T into DBMS, Motivation and importance

of Data Warehousing and Data Mining, Kinds of Patterns, Technologies, Basic Data

Analytics: Data Objects and Attributes Types, Statistical Descriptions of Data, Data

Visualization, Estimating Data Similarity and Dissimilarity, Major Issues in Data Mining.,

Data Mining Applications

Data Warehouse and OLAP Technology: Basic Concepts of Data warehouse, Data

Modeling using Cubes and OLAP, DWH Design and usage, Implementation using Data

Cubes and OLAPs, Data Generalization with AOI.

Data Mining Primitives & Data Cubes: Data Mining Primitives, Data Mining Tasks, Data

Mining Query Language, Designing Graphical user Interfaces based on a Data Mining Query

language, Preliminary Concepts of Data Cube Computation, Data Cube Computation

Methods: Multi-way Array Aggregation for Full Cube, BUC Computing for Iceberg Cubes,

Star-Cubing Using Dynamic Star-Tree Structure, Pre-computing Shell Fragments for Fast

High-Dimensional OLAPs.

Data Mining Concept Description: Data Preprocessing: Pre-processing the Data, Data

Cleaning, Data Integration, Data Reduction, Data Transformation, Discretization and

Concept Hierarchy Generation; Data Architectures of Data Mining Systems; Characterization

and Comparison, Concept Description, Data Generalization and Summarization; Analytical

Characterization: Analysis of Attribute Relevance, Mining Class Comparisons,

Discriminating between Different Classes, Mining Descriptive & Statistical Measures in

Large Databases.

Mining Frequent Patterns Based on Associations and Correlations: Basic Concepts,

Frequent Itemset Mining Methods: Apriori Algorithm, Association Rule Generation,

Improvements to A Priori, FP-Growth Approach, Mining Frequent Patterns using Vertical

Data Formats, Mining Closed and Max Patterns, Pattern Evaluation Methods

75

Classification: Basic Concepts, Decision Tree Induction, Bayes Classification, Rule-Based

Classification, Model Evaluation and Selection, Techniques to Improve Classification

Accuracy Advanced Methods: Classification by Back Propagation, SVM, Associative

Classification, Lazy Learning, Fuzzy Sets, Rough Sets, Genetic Algorithms, Multiclass

Classification, Semi-Supervised Classification

Cluster Analysis: Basic Concepts, Types of Data in Cluster Analysis, Partitioning Methods,

Hierarchical Methods, Density Based Methods, Grid Based Methods, Evaluation of

Clustering Solutions

TEXT BOOK:

1. Data Mining- Concepts and Techniques by Jiawei Han, Micheline Kamber and Jian Pei –

Morgan Kaufmann publishers –--3rd edition

REFERENCE BOOKS:

1. Data Mining Techniques, A.K.Pujari, University Press Data mining concepts by Tan,

Steinbech, and Vipin Kumar - Pearson Edu publishers

2. Data Mining –Introductory and Advanced by Margarett Dunham -- Pearson Education

publishers

3. Data Warehousing for Real –world by Sam Annahory-- Pearson Education publishers

76

Code: M16 IT 1216

NETWORK PROGRAMMING & WEB PROGRAMMING LAB



Credits : 2

COURSE OBJECTIVES:

1. To local and remote systems

2. To chat application for communication between the systems

3. To retrieve data from remote system

4. To transfer data, files between the systems.

5. To design and develop applications and Web pages HTML tags, Emphasis on CSS,

Servelets, cookies, JSP & EJB.

COURSE OUTCOMES:

1. Student able to design Mail Clients, HTTP server. And also data from remote systems.

2. Students design web pages using html tags.

3. Identify user and content goals of the proposed web site and create functional and formal

design specifications for a site.

SYLLABUS

Part I Networks Lab Experiments

1. Identifying well known ports on a Remote System :By trying to listen to the various

well known ports by opening client connections. If the exception does not occur then the

remote port is active else the remote port is inactive.

2. Writing a Chat application:

i). One-One: By opening socket connection and displaying what is written by one party to the

other.

ii). Many-Many (Broad cast): Each client opens a socket connection to the chat server and

writes to the socket. Whatever is written by one party can be seen by all other parties.

3. Data retrieval from a Remote database: At the remote database a server listens for client

connections. This server accepts SQL queries from the client, executes it on the database and

sends the response to the client.

4. Mail Client:

i). POP Client : Gives the server name , user name and password retrieve the mails and allow

manipulation of mail box using POP commands.

ii). SMTP Client : Gives the server name, send e-mail to the recipient using SMTP

commands-

5. Simulation of Telnet: Provide a user interface to contact well-known ports, so that client-

server interaction can be seen by the user.

6. Simple file transfer between two systems ( without protocols): By opening socket

connection to our server on one system and sending a file from one system to another.

7. TFTP- Client: To develop a TFTP client for file transfer. (Unix Network programming-

Stevens.)

77

8. HTTP-Server: Develop a HTTP server to implement the following commands. GET,

POST, HEAD, DELETE. The server must handle multiple clients.

Part II Web Programming Lab Experiments

9. Design of the Web pages using various features of HTML and DHTML

10. Client server programming using servlets, ASP and JSP on the server side and java script

on the client side

11. Web enabling of databases

12. Multimedia effects on web pages design using Flash.

REFERENCE BOOKS:

1. Java Network Programming, Harol, Orielly Publications

2. An Introduction to Computer Networking, Kenneth C. Mansfield Jr and James L.

Antonakos, Pearson Education Asia

3. Internet and Web Technologies by Raj Kamal, Tata McGraw-Hill

4. Programming the World Wide Web by Robert W. Sebesta, Pearson Education

78

Code: M16 CST 1214

OBJECT ORIENTED SOFTWARE ENGINEERING LAB (Common for M.Tech (CST, IT))



Credits : 2

COURSE OBJECTIVES:


2. To enable the student to get knowledge in SDLC

3. To give a detailed understanding of processes and techniques for building large object-

oriented software systems.

4. To develop skills to evolve object-oriented systems from analysis, to design, to

implementation

5. To develop skills to work as a team for developing a software project.


COURSE OUTCOMES:

1. Students can design and implement complex software solutions. and test and document

software.

2. They are capable of working as part of a software team and develop significant projects

SYLLABUS

1. The purpose of the Software Engineering Lab course is to familiarize the students with

modern software engineering methods and tools, Rational Products. The course is

realized as a project-like assignment that can, in principle, by a team of three/four

students working full time. Typically the assignments have been completed during the

semester requiring approximately 60-80 hours from each project team.

2. The goal of the Software Engineering Project is to have a walk through from the

requirements, design to implementing and testing. An emphasis is put on proper

documentation. Extensive hardware expertise is not necessary, so proportionate attention

can be given to the design methodology.

3. Despite its apparent simplicity, the problem allows plenty of alternative solutions and

should be a motivating and educating exercise. Demonstration of a properly functioning

system and sufficient documentation is proof of a completed assignment

4. Term projects are projects that a group student or might take through from initial

specification to implementation. The project deliverables include

Projects

1. Documentation including

a. A problem statement

b. A requirements document

2. A Requirements Analysis Document.

3. A System Requirements Specification.

4. A Software Requirements Specification.

5. A design document

a. A Software Design Description and a System Design Document.

6. A test specification.

79

7. Manuals/guides for

a. Users and associated help frames

b. Programmers

c. Administrators (installation instructions)

8. A project plan and schedule setting out milestones, resource usage and estimated

costs.

9. A quality plan setting out quality assurance procedures

10. An implementation.

REFERENCE BOOKS:

1. Project-based software engineering: An Object-oriented approach, Evelyn Stiller, Cathie

LeBlanc, Pearson Education

2. Visual Modelling with Rational Rose 2002 and UML, Terry Quatrini, Pearson

Education.

3. UML2 Toolkit, Hans -Erik Eriksson, etc; Wiley.

80

Code: M16 IT 1217

SEMINAR

Lab : 3 Periods Sessionals :100


The viva-voce for the seminar shall be held with the faculty member, PG coordinator, and

Head of the Department. The marks shall be awarded in the ratio of 40, 20 and 40 percent by

the members respectively.

81




(Regulation:R16)


III SEMESTER


Marks

Total

Marks

M16 IT 2101 Thesis Work -



organization for two semesters (i.e. 3rd and 4th semesters). In case of thesis done in

an industry/research organization, one advisor (Guide) should be from the department

and one advisor (Co-Guide) should be from the industry/research organization.

2. The Thesis Work -Preliminary should be submitted at the end of 3rd semester and it

will be evaluated through Review by a committee consisting of Head of the

Department, External Examiner, PG coordinator and guide. The marks shall be

awarded in the ratio of 20, 40, 20 and 20 percent by the members respectively.

82




(Regulation:R16)


IV SEMESTER


Marks

Total

Marks

M16 IT 2201 Thesis Work-


1. A publication of a paper on the thesis work in a National/International Journal at the

end of 4th



through Viva–Voce examination by a committee consisting of Head of the

Department, External Examiner, PG coordinator and thesis guide. The marks shall be

awarded in the ratio of 20, 40, 20 and 20 percent by the members respectively.

9

DEPARTMENT OF MECHANICAL ENGINEERING

M.TECH (CAD/CAM)


(Regulation:R16)


I – SEMESTER


hours

Lab

hours

Total

contact

hours

Sessional

Marks

Exam

Marks

Total

Marks

M16 CAD

1101

Computer

Graphics 4 4 -- 4 30 70 100

M16 CAD

1102

Integrated

Computer

Aided Design

4 4 -- 4 30 70 100

M16 CAD

1103

Computer

Numerical

Computer

Technology

4 4 -- 4 30 70 100

M16 CAD

1104 Robotics 4 4 -- 4 30 70 100

#1 Elective-I 4 4 - 4 30 70 100

#2 Elective-II 4 4 -- 4 30 70 100

M16 CAD

1111 CAD Lab 2 -- 3 3 50 50 100

M16 CAD

1112 Seminar-I 2 -- 3 3 100 -- 100

Total 28 24 6 30 330 470 800

Course Code Course

#1-Elective-I

M16 CAD 1105 Advanced Optimization Techniques

M16 CAD 1106 Neural Networks & Fuzzy Techniques

M16 CAD 1107 Tool Design

#2-Elective-II

M16 CAD 1108 Design of Hydraulic & Pneumatics Systems

M16 CAD 1109 Product Design

M16 CAD 1110 Advanced Numerical Methods

10

Code: M16 CAD 1101

COMPUTER GRAPHICS Theory : 4 Periods Sessionals : 30

Exam : 3 Hrs. Ext. Marks: 70

Credits : 4

COURSE OBJECTIVES:

1. This course is designed to provide a comprehensive introduction to computer graphics

leading to the ability to understand contemporary terminology, progress, issues, and trends.

2. A thorough introduction to computer graphics techniques, focusing on geometric

transformations, geometric algorithms, 3D object models (surface, volume and implicit),

visible surface algorithms, Shading and curve generation.

3. The interdisciplinary nature of computer graphics is emphasized in the wide variety of

examples and applications.

COURSE OUTCOMES

Upon completion of the subject, students will be able to

1. Understand the contemporary graphics hardware and terminology.

2. Implement graphics primitives, geometrical transformations and visibility detection.

3. Design and implement an application which illustrates the use of output primitives and 3D

viewing model.

4. Implement a method for the computer representation of objects.

SYLLABUS

Geometry and line generation: Line segments, Pixels and frame buffers, Bresenham's

algorithms: line, circle, ellipse generation. Graphics primitives: Primitive operations, The display-file interpreter, Display-file structure,

Display-file algorithms. Polygons: Polygons representation, An inside test, Filling polygons, Filling with a pattern.

Transformations: Scaling transformations, Reflection and zooming, Rotation, Homogeneous

coordinates and translation, Rotation about an arbitrary point. Segments: The segment table, Segment creation, Closing a segment, Deleting a segment.

Windowing and clipping: The viewing transformation, Clipping, The clipping of polygons,

Generalized clipping. Three dimensions: 3D geometry, 3D primitives, 3D transformations, Parallel projection,

Perspective projection, Isometric projections, Viewing parameters, Special projections. Hidden surfaces and lines: Back-face removal, Back -face algorithms, The Painter's algorithm,

Warnock's algorithm, Franklin algorithm, Hidden-line methods.

11

Light, color and shading: Point-source illumination, Shading algorithms, Shadows, Color

models. Curves and fractals: Curve generation, Interpolation, B splines, Curved surface patches, Bezier

curves, Fractals, Fractal lines, Fractal surfaces.

TEXT BOOK:

1. Computer Graphics - A Programming Approach by Steven Harrington, McGraw-Hill

International Edition, 1987.

REFERENCE BOOKS:

1. Schaum's Outline of Theory and Problems of Computer Graphics by Roy A. Plastock and

Gordon Kalley, McGraw-Hill Companies, Inc., 1986.

2. Mathematical Elements for Computer Graphics by David F. Rogersadn Adams.

12

Code: M16 CAD 1102

INTEGRATED COMPUTER AIDED DESIGN



Credits : 4

COURSE OBJECTIVES:

1. To understand the basic parametric fundamentals that is used to create and manipulate

geometric models.

2. To learn about the concepts of Geometric modelling and to acquire knowledge for generating

high quality images.

3. To learn about different tolerance methods, mass property calculations and animation

techniques used in designing.

COURSE OUTCOMES:

At the end of the course, the student shall be able to:

1. Understand geometric transformation techniques in CAD.

2. Develop mathematical models to represent lines, curves and surfaces used for engineering

applications.

3. Model engineering components using solid modelling techniques.

4. Design and analysis of engineering components.

SYLLABUS

Fundamentals of CAD: Introduction, Design process, Application of computer for design,

creating the manufacturing database, Benefits of CAD, Design work station, CAD hardware. Geometric modeling: Geometric modeling techniques - Multiple view 2D input, Wire frame

geometry, Surface models, Geometric entities - Curves and Surfaces, Solid modelers, Feature

recognition. Computer aided drafting: AutoCAD tools, 3D model building using solid primitives and

boolean operations, 3D model building using extrusion, Editing tools, Multiple views:

Orthogonal, Isometric. Visual realism: Shading solids, Coloring, Color models, Using interface for shading and

coloring. Graphic aids: Geometric modifiers, Naming scheme, Layers, Grids, Groups, Dragging and

rubber banding.

Computer animation: Conventional animation, Computer animation - Entertainment animation,

Engineering animation, Animation types, Animation techniques. Mechanical assembly: Assembly modeling, Part modeling, Mating conditions, Generation of

assembling sequences, Precedence diagram, Liaison-sequence analysis.

13

Mechanical tolerancing: Tolerance concepts, Geometric tolerancing, Types of geometric

tolerances, Location tolerances, Drafting practices in dimensioning and tolerancing, Tolerance

analysis. Mass property calculations: Geometrical property formulation - Curve length, Cross-sectional

area, Surface area, Mass property formulation - Mass, Centroid, Moments of inertia, Property

mapping. Properties of composite objects.

TEXT BOOK:

1. CAD/CAM Theory and Practice by Ibrahim Zeid.

REFERENCE BOOKS:

1. CAD/CAM Principles and Applications by P.N. Rao, Tata McGraw Hill Publishing

Company Ltd.

2. CAD/CAM Computer Aided Design and Manufacturing by Mikell P. Groover and Emory W.

Zimmer, Jr.

3. Computer Integrated Design and Manufacturing by David D. Bedworth, Mark R. Henderson,

Philip M. Wolfe.

14

Code: M16 CAD 1103

COMPUTER NUMERICAL CONTROL TECHNOLOGY



Credits : 4

COURSE OBJECTIVES:

1. To understand the importance of NC and CNC technology in manufacturing industry.

2. To understand the application of CAD/CAM systems in generating Part Programmes, in

particular for complex models.

3. To understand and apply the use of various transducers, encoders and feedback devices.

4. Identify and select proper NC tooling’s.

COURSE OUTCOMES:


1. Understand the principles of Numerical Control (NC) technology and describe the range of

machine tools to which it is applied.

2. Outline the various routs for part programming in NC and CNC.

3. Explain the application of CNC for Machining & Turning Centers

SYLLABUS

Introduction: NC, DNC, CNC, Programmed Automations, Machine control unit, Part program,

NC tooling. NC machine tools: Nomenclature of NC machine axes, Types of NC machine tools, Machining

centres, Automatic tool changes (ATC), Turning centres. Machine control unit & tooling: Functions of MCU, NC actuation systems, Part program to

command signal, MCU organization, Computerized numerical control, Transducers for NC

machine tools, Tooling for NC machining centres and NC turning machines, Tool presetting. Manual part programming: Part program instruction formats, Information codes: Preparatory

function, Miscellaneous functions, Tool code and tool length offset, Interpolations, Canned

cycles. Manual part programming for milling operations, Turning operations, Parametric

subroutines. Computer aided part programming: NC languages: APT, NELAPT, EXAPT, GNC, VNC,

Pre-processor, Post processor. APT programming: APT language structure, APT geometry: Definition of point, time, vector,

circle, plane, patterns and matrices. APT motion commands: setup commands, point-to-point

motion commands, continuous path motion commands. Post processor commands, complication

control commands. Macro subroutines. Part programming preparation for typical examples.

15

TEXT BOOK:

1. Numerical Control and Computer Aided Manufacturing by T.K. Kundra, P.N. Rao and N.K.

Tewari, Tata McGraw-Hill Company Limited, New Delhi.

REFERENCE BOOKS:

1. Numerical Control of Machine Tools by Yoram Koren and Joseph Ben-Uri, Khanna

Publishers, Delhi.


Company Ltd.

16

Code: M16 CAD 1104

ROBOTICS



Credits : 4

COURSE OBJECTIVES:

1. To familiarize the students with anatomy, kinematics, sensors and dynamics of a

programmable machine of a robot.

COURSE OUTCOMES:


1. Distinguish between fixed automation and programmable automation.

2. Identify various components of robot.

3. Select appropriate type of actuator for a joint.

4. Illustrate robot applications in manufacturing.

5. Analyze kinematics of a robot.

6. Derive equations of motion of a manipulator for a particular application.

SYLLABUS

Introduction: Basic concepts-Robot anatomy-robot configurations-Basic Robot motions-Types

of drives-Applications-Material Handling-Processing-Assembly and Inspection -Safety

considerations

Transformations and Kinematics: Vector operations-Translational transformations and

Rotational transformations-Properties of transformation matrices-Homogeneous transformations

and Manipulator-Forward solution-Inverse solution.

Controls and End Effectors: Control system concepts-Analysis-control of joints-Adaptive and

optimal control-End effectors-Classification- Mechanical-Magnetic-Vacuum-Adhesive-Drive

systems-Force analysis and Gripper design.

Robot Programming Methods: Languages-Computer control and Robot Software-VAL system

and Language.

Sensory Devices: Non optical and optical position sensors-Velocity and Acceleration-Range-

Proximity touch-Slip-Force-Torque- Machine vision-Image components-Representation -

Hardware Picture coding-Object recognition and categorization-Software consideration

TEXT BOOK:

1. Fu K.S.,Gonzalez R.C.., Lee C.S.G., "Robotics control,sensing,vision,and Intelligence",

McGraw Hill Book Co.,,1987.

17

REFERENCE BOOKS:

1. Klafter R.D., Cmielewski T.A. and Negin M , "Robot Engineering An Intergrated approach",

Prentice Hall of India,New Delhi.2,1994.

2. Deb S.R., "Robotics Technology and Flexible Automation", Tata McGraw Hill Publishing

Co., Ltd.,1994.

3. Craig J.J., "Introduction to Robotics Mechanics and Control", Addison Wesley,1999 5.

Groover M.P., "Industrial robotics Technology,programming and applications", McGraw

Hill Book Co.,1995.

18

Code: M16 CAD 1105

ADVANCED OPTIMIZATION TECHNIQUES



Credits : 4

COURSE OBJECTIVES:

1. To understand the theory of optimization methods and algorithms developed for solving

various types of optimization problems.

2. To apply the mathematical results and numerical techniques of optimization theory to

concrete Engineering problems.

3. To develop and promote research interest in applying optimization techniques in problems of

Engineering and Technology.

COURSE OUTCOMES:

1. Have a basic understanding of conventional and unconventional optimization algorithms.

2. Formulate engineering design problems as mathematical optimization problems and solve

them by using suitable optimization technique(s).

3. Use mathematical software for the solution of engineering problems.

4. Several homework assignments delving on core concepts and reinforcing analytical skills

learned in class.

SYLLABUS

Introduction: Statement of an optimization problem, Engineering Applications, Classification

of optimization problems

Geometric programming (G.P): Solution of an unconstrained geometric programming,

differential calculus method and arithmetic method. Primal dual relationship and sufficiency

conditions. Solution of a constrained geometric programming problem (G.P.P). Complementary

geometric programming (C.G.P), Simple applications of G.P

Dynamic programming (D.P): Multistage decision processes. Concepts of sub optimization,

computational procedure in dynamic programming calculus method and tabular methods. Linear

programming as a case of D.P. Continuous D.P, simple applications of D.P

Integer programming (I.P): Graphical representation. Gomory's cutting plane method. Bala's

algorithm for zero-one programming problem. Branch-and-bound method.

Stochastic programming (S.P): Basics concepts of probability theory, stochastic linear

programming

Unconventional optimization techniques: Multi-objective optimization - Lexicographic

method, Goal programming method, Genetic algorithms, A.N.N, Simulated Annealing

TEXT BOOK:

1. Engineering Optimization - Theory and Practice by Rao, S.S., New Age International (P)

Ltd. Publishers.

19

REFERENCE BOOKS:

1. Operations Research- Principles and Practice, Ravindran, Phillips and Solberg, John Wiely.

2. Introduction to Operations Research, Hiller and Lieberman, Mc Graw Hill.

3. Goal Programming and Extensions by James P. Ignizio, Lexigton Books.

4. Genetic Algorithms - In Search, Optimization and Machine Learning by David E. Goldberg,

Addison-Wesley Longman (Singapore) Pvt. Ltd.

20

Code: M16 CAD 1106

NEURAL NETWORKS AND FUZZY TECHNIQUES



Credits : 4

COURSE OBJECTIVES:

1. To conceptualize the working of human brain using Artificial Neural Network.

2. To become familiar with neural networks that can learn from available examples and

generalize to form appropriate rules for inference systems.

3. To introduce the ideas of fuzzy sets, fuzzy logic and use of heuristics based on human

experience.

COURSE OUTCOMES:


1. Analyze and appreciate the applications which can use Neural Network and fuzzy logic.

2. Identify and describe NNFL techniques and their roles in building intelligent machines.

3. Design inference systems for decision making in manufacturing industries.

4. Realize the difference between learning and programming and explore practical applications

of Neural networks (NN).

5. Demonstrate the use of Neuro-fuzzy network for various industry applications.

SYLLABUS

Neural networks and fuzzy systems: Neural and fuzzy machine intelligence, Fuzzy as

multivalence, The dynamical - Systems approach to machine intelligence, Intelligent behaviour

as adaptive model - Free estimation.

Neural dynamics-I: Activations and signals, Neurons as functions, Signal monotonicity,

Biological activations and signals, Neuron fields, Neuronal dynamical systems, Common signal

functions, Pulse-coded signal functions.

Neuronal dynamics -II: Activation models, Neuronal dynamical systems, Additive neuronal

dynamics, Additive neuronal feedback, Additive bivalent models, BAM connection matrices,

Additive dynamic and the noise - Saturation dilemma, General neuronal Activations: Cohen-

Grossberg and multiplicative models. Synaptic Dynamics I: Unsupervised learning, Learning as

encoding, change, and quantization, Four unsupervised learning laws, Probability spaces and

random processes, Stochastic unsupervised learning and stochastic equilibrium, Signal Hebbian

learning, Competitive learning, Differential Hebbian learning, Differential competitive leering.

Synaptic Dynamics II: Supervised learning, Supervised function estimation, Supervised

learning as operant conditioning, Supervised learning as stochastic pattern learning with known

class memberships, Supervised learning as stochastic approximation, The back propagation

algorithm. Fuzziness Versus: Probability fuzzy sets and systems, Fuzziness in a probabilistic

world, Randomness vs. ambiguity: Whether vs. how much, The universe as a fuzzy set, The

geometry of fuzzy set, The geometry of fuzzy sets: Sets as points. The fuzzy entropy theorem,

Thesubsethood theorem. The entropy-subsethood theorem.

21

Fuzzy associative memories: Fuzzy systems as between-cube mappings, Fuzzy and neural

function estimators, Fuzzy Hebb FAMs, Adaptive FAMs: Product-space clustering in FAM cells.

Applications in design and structural analysis.

TEXT BOOK:

1. Neural Networks & Fuzzy Systems by Bark Kosko, PHI Published in 1994.

REFERENCE BOOKS:

1. Neural Network Fundamentals with Graphs, Algorithms and Applications by B.K. Bose,

Tata- McGraw Hill.

2. Neural network Design by Hagan, Demuth and Beale, Vikas Publishing House.

3. Fundamentals of Artificial Neural Networks by Mohamad H Hassoum. PHI.

4. Fuzzy Set Theory & its Application by .J. Zimmerman Allied Published Ltd.

5. Algorithms and Applications of Neural Networks in Mechanical Engineering by M.

AnandaRao and J. Srinivas, Narosa Publishing House

22

Course Code: M16 CAD 1107

TOOL DESIGN



Credits : 4

COURSE OBJECTIVES:

1. To impart knowledge on tool engineering, mechanics of metal cutting and importance of tool

design in manufacturing.

2. To become familiarize with Design of Jigs and Fixtures, press tool dies and CNC machine

tools.

COURSE OUTCOMES:

After completion of the course student will be able to,

1. Classify different types of tools used for different manufacturing processes.

2. Design of Jigs and Fixtures, Press tool dies and tool design for CNC machines.

3. Design different machine tools considering static and dynamic loads.

SYLLABUS

Introduction to tool design Introduction –Tool Engineering – Tool Classifications– Tool Design

Objectives – Tool Design in manufacturing- Challenges and requirements- Standards in tool

design-Tool drawings -Surface finish – Fits and Tolerances - Tooling Materials- Ferrous and

Non ferrous Tooling Materials- Carbides, Ceramics and Diamond -Non metallic tool materials-

Designing with relation to heat treatment Design of cutting tools Mechanics of Metal cutting –Oblique and orthogonal cutting- Chip

formation and shear angle - Single-point cutting tools – Milling cutters – Hole making cutting

tools- Broaching Tools - Design of Form relieved and profile relieved cutters-Design of gear and

thread milling cutters Design of jigs and fixtures Introduction – Fixed Gages – Gage Tolerances –selection of material

for Gages – Indicating Gages – Automatic gages – Principles of location – Locating methods and

devices – Principles of clamping – Drill jigs – Chip formation in drilling – General

considerations in the design of drill jigs – Drill bushings – Methods of construction –Thrust and

Turning Moments in drilling - Drill jigs and modern manufacturing- Types of Fixtures – Vise

Fixtures – Milling Fixtures – Boring Fixtures – Broaching Fixtures – Lathe Fixtures – Grinding

Fixtures – Modular Fixtures – Cutting Force Calculations. Design of press tool dies Types of Dies –Method of Die operation–Clearance and cutting force

calculations- Blanking and Piercing die design – Pilots – Strippers and pressure pads- Presswork

materials – Strip layout – Short-run tooling for Piercing – Bending dies – Forming dies –

Drawing dies-Design and drafting.

23

Tool design for CNC machine tools Introduction –Tooling requirements for Numerical control

systems – Fixture design for CNC machine tools- Sub plate and tombstone fixtures-Universal

fixtures– Cutting tools– Tool holding methods– Automatic tool changers and tool positioners –

Tool presetting– General explanation of the Brown and Sharp machine.

TEXT BOOK:

1. Cyrll Donaldson, George H.LeCain, V.C. Goold, ―Tool Design‖, Tata McGraw Hill

Publishing Company Ltd., 2000.

REFERENCE BOOKS:

1. E.G.Hoffman,‖ Jig and Fixture Design‖, Thomson Asia Pvt Ltd, Singapore, 2004.

2. PrakashHiralal Joshi, ―Tooling data‖, Wheeler Publishing, 2000.

3. Venkataraman K., ―Design of Jigs, Fixtures and Press tools‖, TMH, 2005.

4. Haslehurst M., ―Manufacturing Technology‖, the ELBS, 1978

24

Code: M16 CAD 1108

DESIGN OF HYDRAULIC AND PNEUMATIC SYSTEMS



Credits : 4

COURSE OBJECTIVES:

1. To introduce the industrial hydraulics and pneumatics, their parts, functions and their

structure.

2. To give the required information about hydraulics and pneumatics and to teach the

fundamentals of hydraulic and pneumatic circuit design.

3. To teach the hydraulic and pneumatic automation and basics of PLC controls.

COURSE OUTCOMES:

The students who attend to this course

1. Can explain the similarities and differences of the electrical, pneumatic and hydraulic

systems

2. Can decide which system is better for a specific application.

3. Can explain the basic parts of the industrial hydraulic and pneumatic systems and their

functions.

4. Can design a hydraulic or pneumatic system circuit by using related software and make

simulations

5. Can design a hydraulic or pneumatic system and outline PLC control algorithm for a

predefined automation process

SYLLABUS

Oil hydraulic systems and hydraulic actuators specification of pumps, pump characteristics.

specification and characteristics. Hydraulic Power Generators – Selection and Linear and Rotary

Actuators – selection

Control and regulation elements Pressure - direction and flow control valves - relief valves, non-

return and safety valves - actuation systems. Hydraulic circuits Reciprocation, quick return, sequencing, synchronizing circuits - accumulator

circuits - industrial circuits - press circuits - hydraulic milling machine - grinding, planning,

copying, - forklift, earth mover circuits- design and selection of components - safety and

emergency mandrels.

Pneumatic systems and circuits Pneumatic fundamentals - control elements, position and

pressure sensing - logic circuits - switching circuits - fringe conditions modules and these

integration - sequential circuits - cascade methods - mapping methods - step counter method -

compound circuit design - combination circuit design.

Installation, maintenance and special circuits Pneumatic equipments- selection of components -

design calculations – application -fault finding - hydro pneumatic circuits - use of

microprocessors for sequencing - PLC, Low cost automation - Robotic circuits.

25

TEXT BOOK:

1. Antony Espossito, ―Fluid Power with Applications‖, Prentice Hall, 1980.

REFERENCE BOOKS:

1. Dudleyt, A. Pease and John J. Pippenger, ―Basic fluid power‖, Prentice Hall, 1987.

2. Andrew Parr, ―Hydraulic and Pneumatics‖ (HB), Jaico Publishing House, 1999.

3. Bolton. W., ―Pneumatic and Hydraulic Systems ―, Butterworth –Heinemann, 1997.

4. K.ShanmugaSundaram, ―Hydraulic and Pneumatic Controls: Understanding made Easy"

S.Chand& Co Book publishers, New Delhi, 2006 (Reprint 2009).

26

Code: M16 CAD 1109

PRODUCT DESIGN Theory : 4 Periods Sessionals : 30


Credits : 4

COURSE OBJECTIVES:

1. To impart the process of product design.

2. To expose the various factors influencing product design.

COURSE OUTCOMES:


1. Apply various tools of problem solving to arrive at a fruitful design.

2. Analyse the factors influencing the design.

3. Determine the risk and reliability aspects associated with product design.

4. Select appropriate manufacturing processes to realize the product design.

5. design an eco-friendly product.

SYLLABUS

Design philosophy: Design process, Problem formation, Introduction to product design, various

design models-Shigley model, Asimov model and Norton model, Need analysis, Strength

considerations -standardization. Creativity, Creative techniques, Material selections, Notches and

stress concentration, design for safety and Reliability Failure theories: Static failure theories, Distortion energy theory, Maximum shear stress theory,

Coulomb-Mohr’s theory, Modified Mohr’s theory, Fracture mechanics theory. Fatigue failure

theories, Fatigue mechanisms, Fatigue failure models, Fatigue failure criteria, Methods to reduce

fatigue, Design for fatigue, Modified Goodman Diagram, Gerber method, Soderberg line,

Surface failure models. Lubrication, friction and wear Product Design: Product strategies, Product value, Product planning, product specifications,

concept generation, concept selection, concept testing. Design for manufacturing: Forging design, Casting design, Design process for non metallic

parts, Plastics, Rubber, Ceramic, Wood, Glass parts.

Economic factors influencing design: Economic analysis, Break-even analysis, Human

engineering considerations, Ergonomics, Design of controls, Design of displays. Value

engineering, Material and process selection in value engineering, Modern approaches in design.

TEXT BOOK:

1. Product Design and Manufacturing by A.K. Chitale and R.C. Gupta, Prentice Hall.

27

REFERENCE BOOKS: 1. Mechanical Engineering Design by Joseph Shigley and Mischke. Sixth edition, Tata

McGraw Hill

2. Machine Design - An Integrated Approach by R.L. Norton, Prentice Hall.

3. Product design and development by Karl T. Ulrich and Steven D. Eppinger. Third edition,

Tata McGraw Hill.

28

Code: M16 CAD 1110

ADVANCED NUMERICAL METHODS



Credits : 4

COURSE OBJECTIVES:

1. To know how to solve system of equations, ordinary differential equations and partial

differential equations numerically

2. To impart the knowledge on finite difference and finite element methods used for

approximation.

COURSE OUTCOMES:


1. Find the solutions of system of linear and non linear equations.

2. Solve ordinary and partial differential equations numerically.

3. Find a approximation solution for engineering problems using finite difference and finite

element methods.

SYLLABUS

Algebraic equations: Systems of linear equations: Gauss Elimination method, pivoting

techniques, Thomas algorithm for tridiagonal system – Jacobi, Gauss Seidel, SOR iteration

methods - Systems of nonlinear equations: Fixed point iterations, Newton Method, Eigenvalue

problems: power method, inverse power method, Faddeev – Leverrier Method. Ordinary differential equations: RungeKutta Methods for system of IVPs, numerical stability,

Adams-Bashforth multistep method, solution of stiff ODEs, shooting method, BVP: Finite

difference method, orthogonal collocation method, orthogonal collocation with finite element

method, Galerkin finite element method. Finite difference method for time dependent partial differential equation parabolic

equations: explicit and implicit finite difference methods, weighted average approximation -

Dirichlet and Neumann conditions – Two dimensional parabolic equations – ADI method; First

order hyperbolic equations – method of characteristics, different explicit and implicit methods;

numerical stability analysis, method of lines – Wave equation: Explicit scheme- Stability of

above schemes. Finite difference methods for elliptic equations laplace and poisson’s equations in a

rectangular region: Five point finite difference schemes, Leibmann’s iterative methods,

Dirichlet and Neumann conditions – Laplace equation in polar coordinates: finite difference

schemes – approximation of derivatives near a curved boundary while using a square mesh. Finite element method partial differential equations – Finite element method - orthogonal

collocation method, orthogonal collocation with finite element method, Galerkin finite element

method.

29

TEXT BOOK:

1. Saumyen Guha and Rajesh Srivastava, ―Numerical methods for Engineering and Science‖,

Oxford Higher Education, New Delhi, 2010.

REFERENCE BOOKS:

1. Gupta S.K., ―Numerical Methods for Engineers‖, New Age Publishers, 1995.

2. Burden, R.L., and Faires, J.D., ―Numerical Analysis – Theory and Applications‖, Cengage

Learning, India Edition, New Delhi, 2009.

3. Jain M. K., Iyengar S. R., Kanchi M. B., Jain , ―Computational Methods for Partial

Differential Equations‖, New Age Publishers,1993.

4. Morton K.W. and Mayers D.F., ―Numerical solution of partial differential equations‖,

Cambridge University press, Cambridge, 2002.

30

Code: M16 CAD 1111

CAD LAB Lab : 3 Periods Sessionals : 50


Credits : 2

COURSE OBJECTIVES:

1. To impart training on SOLID WORKS for modelling of engine and automobile parts.

2. To impart training on ANSYS software for analyzing engineering problems.

COURSE OUTCOMES:


1. Model the automobile parts using modelling package like SOLID WORKS

2. Analyze different engineering problems using ANSYS software

SYLLABUS

2D and 3D modelling and assembly modelling using modelling packages like AutoCAD, Auto

Desk Mechanical desktop, Pro-Engineer, IDEAS.

Linear and non-linear static and dynamic analysis using any FEA package ANSYS / CAEFEM

/ NASTRAN.

REFERENCE BOOKS:

1. Solid Works Reference Guide by CADD Centre.

2. CAD/CAM Theory and Practice by Ibrahim Zeid.


Company Ltd.


Zimmer, Jr.

5. Computer Integrated Design and Manufacturing by David D. Bedworth, Mark R. Henderson,

Philip M. Wolfe.

31

Code: M16 CAD 1112

SEMINAR-I






32


M.TECH (CAD/CAM)


(Regulation:R16)


II – SEMESTER


hours

Lab

hours

Total

contact

hours

Sessional

Marks

Exam

Marks

Total

Marks

M16 CAD

1201

Computer

Integrated

Manufacturing

4 4 -- 4 30 70 100

M16 CAD

1202 Mechatronics 4 4 -- 4 30 70 100

M16 CAD

1203

Flexible

Manufacturing

Systems

4 4 -- 4 30 70 100

M16 CAD

1204

Finite Element

Analysis 4 4 -- 4 30 70 100

#3 Elective-III 4 4 - 4 30 70 100

#4 Elective-IV 4 4 -- 4 30 70 100

M16 CAD

1211 CAM Lab 2 -- 3 3 50 50 100

M16 CAD

1212 Seminar-II 2 -- 3 3 100 -- 100

Total 28 24 6 30 330 470 800

Course Code Course

#3-Elective-III

M16 CAD 1205 Vision Systems & Image Processing

M16 CAD 1206 Intelligent Manufacturing Systems

M16 CAD 1207 Concurrent Engineering

#4-Elective-IV

M16 CAD 1208 Signal Analysis & Condition Monitoring

M16 CAD 1209 Additive Manufacturing

M16 CAD 1210 Metrology and Non Destructive Testing

33

Code: M16 CAD 1201

COMPUTER INTEGRATED MANUFACTURING



Credits : 4

COURSE OBJECTIVES:

1. To impart the students the basic knowledge of automated production process.

2. To provide the knowledge of automated assembly operations.

3. To provide the knowledge of automated inspection, material handling operations.

4. To provide the knowledge of flexible manufacturing.

COURSE OUTCOMES:


1. Understand the effect of manufacturing automation strategies and derive production metrics.

2. Analyze automated flow lines and assembly systems, and balance the line.

3. Design automated material handling and storage systems for a typical production system.

4. Design a manufacturing cell and cellular manufacturing system.

5. Develop CAPP systems for rotational and prismatic parts.

SYLLABUS

Introduction: Scope of computer integrated manufacturing, Product cycle, Production

automation. Group technology: Role of group technology in CAD/CAM integration, Methods for

developing part families, Classification and coding, Examples of coding systems, Facility design

using group technology, Economics of group technology. Computer aided process planning: Approaches to process planning - Manual, Variant,

Generative approach, Process planning systems - CAPP, DCLASS, CMPP, Criteria for selecting

a CAPP system, Part feature recognition, Artificial intelligence in process planning. Integrative manufacturing planning and control: Role of integrative manufacturing in

CAD/CAM integration, Over view of production control - Forecasting, Master production

schedule, Capacity planning, M.R.P., Order release, Shop-floor control, Quality assurance,

Planning and control systems, Cellular manufacturing, JIT manufacturing philosophy. Computer aided quality control: Terminology in quality control, Contact inspection methods,

Noncontact inspection methods, Computer aided testing, Integration of CAQC with CAD/CAM. Computer integrated manufacturing systems: Types of manufacturing systems, Machine tools

and related equipment, Material handling systems, Computer control systems, FMS.

34

TEXT BOOK:

1. Automation, Production Systems and Computer Integrated Manufacturing by Mikell P.

Groover, Prentice Hall of India Pvt. Ltd.

REFERENCE BOOKS:


Company Ltd.


Zimmer, Jr.

3. Computer Integrated Design and Manufacturing by David D. Bedworth, Mark R.Henderson,

Philip M. Wolfe.

4. Principles of Computer Integrated Manufacturing by Vajapayee, Prentice Hall of India Pvt.

Ltd.

35

Code: M16 CAD 1202

MECHATRONICS



Credits : 4

COURSE OBJECTIVES:

1. To develop an ability to identify, formulate, and solve engineering problems.

2. To develop an ability to design a system, component, or process to meet desired needs within

realistic constraints.

3. To develop an ability to use the techniques, skills, and modern engineering tools necessary

for engineering practice.

COURSE OUTCOMES:

Upon completion of this course, students should able to:

1. Model and analyze electrical and mechanical systems and their interconnection.

2. Integrate mechanical, electronics, control and computer engineering in the design of

mechatronics systems.

3. Do the complete design building, interfacing and actuation of a mechatronic system for a set

of specifications.

SYLLABUS

Mechatronics system design: Introduction to Mechatronics: What is mechatronics, Integrated

design issues in mechatronics, Mechatronics key elements, the mechatronics design process,

Advanced approaches in mechatronics. Modelling and simulation of physical systems: Simulation and block diagrams, Analogies and

impedance diagrams, Electrical systems, Mechanical translational systems, Mechanical

rotational systems, Electromechanical coupling, Fluid systems. Sensors and transducers: An introduction to sensors and transducers, Sensors for motion and

position measurement, Force, torque and tactile sensors, Flow sensors, Temperature-sensing

devices. Actuating devices: Direct current motor, Permanent magnet stepper motor, Fluid power

actuation. Signals, systems and controls: Introduction to signals, systems and controls, System

representation, Linearization of nonlinear systems, Time delays. Real time interfacing: Introduction, Elements of a data acquisition and control system,

Overview of the I/O process, Installation of the I/O card and software. Advanced applications in mechatronics: Sensors for condition monitoring, Mechatronic

control in automated manufacturing, Artificial intelligence in mechatronics, Microsensors in

mechatronics.

36

TEXT BOOK:

1. Mechatronics System Design by Devdas Shetty and Richard A. Kolk, P.W.S. Publishing

Company, 2001.

REFERENCE BOOKS:

1. Mechatronics by W. Bolton, Pearson Education, Asia, II-Edition, 2001.

2. Introduction to Mechatronics and Measurement Systems by Michael B. Histand and David

G. Alciatore, Tata McGraw Hill Company Ltd.

37

Code: M16 CAD 1203

FLEXIBLE MANUFACTURING SYSTEMS



Credits : 4

COURSE OJECTIVES:

1. To impart the knowledge of flexible manufacturing.

2. To impart the knowledge of high level distributed data processing methods of various

industrial processes like assembly operations, material handling, buffer storage, tool and

fixtures and storage system.

3. To impart the knowledge of Computer Integrated data base and computer integrated

manufacturing.

COURSE OUTCOMES:


1. Classify and distinguish FMS and other manufacturing systems including job-shop and mass

production systems.

2. Explain processing stations and material handling systems used in FMS environments.

3. Design and analyze FMS using simulation and analytical techniques.

4. Understand tool management in FMS.

5. Analyze the production management problems in planning, loading, scheduling, routing and

breakdown in a typical FMS

SYLLABUS

Introduction: The economic justification of FMS, The basic components of FMS and their

integration in the data processing system, The concept of the 'total system'. Management decisions during FMS project planning, design and implementation:

Designing the FMS, Data processing design, FMS project and software documentation. Artificial intelligence in the design of FMS: LISP, PROLOG, Expert systems, Expert systems

in FMS design and control, Integrative aspects of AI languages. Distributed processing in FMS: Introduction to database management systems (DBMS) and

their application in CAD/CAM and FMS, Distributed systems in FMS. Distributed tool data bases in FMS: The distributed tool data structure with a general purpose

tool description facility, Implementation of the FMS tool data base, Application possibilities of

the FMS tool data base.

38

FMS database for clamping devices and fixtures: The FMS clamping device and fixture data

base, The analysis and calculation of pallet alignment and work mounting errors, Mating surface

description methods for automated design and robotised assembly, Application of industrial

robots in FMS, The application of automated guided vehicle (AGV) systems. Coordinate measuring machines in computer integrated systems: Overview of coordinate

measuring machine, Contact and non-contact inspection principles, Part programming coordinate

measuring machines, In-cycle gauging.

TEXT BOOK:

1. The Design and Operations of FMS by Dr. Paul Ranky, IFS (Publications) Ltd., UK, 1983.

REFERENCE BOOKS:

1. Flexible Manufacturing Systems in Practice by Joseph Talavage and Roger G. Hannam,

Marcel Dekker Inc., New York.

2. Robotics Technology and Flexible Automation by S.R. Deb, Tata McGraw Hill Company

Ltd.

39

Code: M16 CAD 1204

FINITE ELEMENT ANALYSIS



Credits : 4

COURSE OBJECTIVES:

1. To teach students the basic principles and basic implementation method of finite element

methods.

2. To teach students how to perform structural and Thermal analysis using finite element

methods.

COURSE OUTCOMES:


1. Understand the principles and concepts related to finite element methods.

2. Implement finite element methods for simple analysis of 1 -D problems such as bar, truss,

beam and 1 -D heat conduction either by hand calculation or by programming.

3. Numerically solve for deformation, stresses and strains of a structural component subjected

to axial, torsion, and bending loads.

4. Understand the basic knowledge about finite element methods for solving time- dependent

and/or nonlinear problems.

5. Use commercial software package to perform structural and thermal analysis and are able to

conduct engineering design.

SYLLABUS

Introduction to FEM, basic concepts, historical back ground, applications of FEM, general

description, comparison of FEM with other methods, variational approach, Glerkin’s Methods.

Coordinates, basic element shapes, interpolation function, Virtual energy principle, Rayleigh –

Ritz method, properties of stiffness matrix, treatment of boundary conditions, solution of system

of equations, shape functions and characteristics, Basic equations of elasticity, strain-

displacement relations.

1-D Structural Problems: Axial bar element – stiffness matrix, load vector, temperature effects,

Quadratic shape functions and problems. ANALYSIS OF TRUSSES : Plane Trusses and Space

Truss elements and problems. ANALYSIS OF BEAMS : Hermite shape functions – stiffness

matrix – Load vector – Problems.

2-D Problems: CST, LST, force terms, Stiffness matrix and load vectors, boundary conditions,

Isoparametric elements – quadrilateral element, shape functions – Numerical Integration. Finite

element modeling of Axi-symmetric solids subjected to Axi-symmetric loading with triangular

elements. 3-D PROBLEMS: Tetrahedran element – Jacobian matrix – Stiffness matrix.

40

Scalar Field Problems: 1-D Heat conduction-Slabs – fins - 2-D heat conduction problems –

Introduction to Torsional problems.

Dynamic considerations, Dynamic equations – consistent mass matrix – Eigen Values, Eigen

vector, natural frequencies – mode shapes – modal analysis.

TEXT BOOK:

1. Introduction to Finite Elements in Engineering, Chandrupatla, Ashok and Belegundu,

Prentice – Hall.

REFERENCE BOOKS:

1. The Finite Element Method by O.C. Zienkiewicz, Tata McGraw Hill Company Ltd.

2. The Finite Element Methods in Engineering by Rao, S.S.

3. Concepts and Applications of Finite Element Analysis by Cook, R.D.

4. Applied Finite Element Analysis by Segerland, L.J.

41

Code: M16 CAD 1205

VISION SYSTEMS AND IMAGE PROCESSING



Credits : 4

COURSE OBJECTIVES:

1. To acquire the fundamental concepts of a digital image processing system

2. To design and implement algorithms that perform basic image processing

3. To Develop Fourier transform for image processing in frequency domain

4. To Provide mathematical foundations for digital manipulation of images; image acquisition;

pre-processing; segmentation; Fourier domain processing; and compression

5. To Learn and understand the Image Enhancement in the Spatial Domain

6. To Learn and understand the Image Enhancement in the Frequency Domain.

7. To Understand the Image Restoration, Compression, Segmentation, Recognition,

Representation and Description.

COURSE OUTCOMES:

Upon completion of this course, students will be familiar with

1. Basic image processing techniques for solving real problems

2. Analyze general terminology of digital image processing

3. Understand fundamental concepts and theory of Discrete Fourier Series and Discrete Fourier

Transform.

4. Examine various types of images, intensity transformations and spatial filtering.

5. Have a good understanding of the mathematical foundations for digital manipulation of

images; image acquisition; pre-processing; segmentation; Fourier domain processing,

compression and analysis.

SYLLABUS

Machine vision - Vision sensors - Comparison with other types of sensors - Image acquisition

and recognition - Recognition of 3D objects - Lighting techniques - Machine vision applications.

Image representation - Application of image processing - Image sampling, Digitization and

quantization - Image transforms. Spatial domain techniques - Convolution, Correlation. Frequency domain operations - Fast

Fourier transforms, FFT, DFT, Investigation of spectra. Hough transform Image enhancement, Filtering, Restoration, Histogram equalisation, Segmentation, Region

growing. Image compression - Edge detection - Thresholding - Spatial smoothing - Boundary and Region

representation - Shape features - Scene matching and detection - Image classification.

42

TEXT BOOK:

1. Digital Image Processing by Gonzalez, R.C. and Woods, R.E., Addison Wesley Publications.

REFERENCE BOOKS:

1. Robot Vision by Prof. Alan Pugh (Editor), IFS Ltd., U.K.

2. Digital Image Processing by A. Rosenfled and A. Kak, Academic Press.

3. The Psychology of Computer Vision by P. Winstan, McGraw-Hill.

4. Algorithms for Graphics and Image Processing by T. Pavidis, Springer Verlag.

43

Code: M16 CAD 1206

INTELLIGENT MANUFATURING SYSTEMS



Credits : 4

COURSE OBJECTIVE:

1. To teach the student the principles and practices of intelligent product design and

manufacturing

COURSE OUTCOME:

1. At the end of this course the student will be able to apply Internet technology in

manufacturing Industry and use techniques of Knowledge Representation

SYLLABUS

Computer Integrated Manufacturing Systems Structure and functional areas of CIM system, -

CAD, CAPP, CAM, CAQC, ASRS. Advantages of CIM. Manufacturing Communication

Systems - MAP/TOP, OSI Model, Data Redundancy, Top- down and Bottom-up Approach,

Volume of Information. Intelligent Manufacturing System Components, System Architecture

and Data Flow, System Operation.

Components of Knowledge Based Systems - Basic Components of Knowledge Based Systems,

Knowledge Representation, Comparison of Knowledge Representation Schemes, Interference

Engine, Knowledge Acquisition.

Machine Learning - Concept of Artificial Intelligence, Conceptual Learning, Artificial Neural

Networks - Biological Neuron, Artificial Neuron, Types of Neural Networks, Applications in

Manufacturing.

Automated Process Planning - Variant Approach, Generative Approach, Expert Systems for

Process Planning, Feature Recognition, Phases of Process planning. Knowledge Based System

for Equipment Selection (KBSES) - Manufacturing system design. Equipment Selection

Problem, Modeling the Manufacturing Equipment Selection Problem, Problem Solving approach

in KBSES, Structure of the KRSES.

Group Technology: Models and Algorithms Visual Method, Coding Method, Cluster Analysis

Method, Matrix Formation - Similarity Coefficient Method, Sorting-based Algorithms, Bond

Energy Algorithm, Cost Based method, Cluster Identification Method, Extended CI Method.

Knowledge Based Group Technology - Group Technology in Automated Manufacturing System.

Structure of Knowledge based system for group technology (KBSCIT) — Data Base,

Knowledge Base, Clustering Algorithm.

44

TEXT BOOK:

1. Intelligent Manufacturing Systems/ Andrew Kusiak/Prentice Hall.

REFERENCE BOOKS:

1. Artificial Neural Networks/ Yagna Narayana/PHI/2006 .

2. Automation, Production Systems and CIM / Groover M.P./PHI/2007.

3. Neural networks: A comprehensive foundation/ Simon Hhaykin/ PHI.

4. Artificial neural networks/ B.Vegnanarayana/PHI.

5. Neural networks in Computer intelligence/ Li Min Fu/ TMH/2003’

6. Neural networks/ James A Freeman David M S kapura/ Pearson education/2004.

7. Introduction to Artificial Neural Systems/Jacek M. Zurada/JAICO Publishing House Ed.

2006.

45

Code: M16 CAD 1207

CONCURRENT ENGINEERING



Credits : 4

COURSE OBJECTIVES:

1. To study about concurrent engineering.

2. To learn about applications of concurrent engineering in product design and manufacturing.

3. To learn about automation of assembly workstations & fabrication systems.

COURSE OUTCOMES:


1. Understand the concepts of concurrent engineering and its application in design and

manufacturing of a product

2. Know how to solve issues arising during design and manufacturing of a product

3. Understand the importance of tolerances in product design and manufacturing

4. Understand how to automate a work station & fabrication system.

5. Understand the importance of human resource management

SYLLABUS

Introduction: Concurrent design of products and systems - Product design - Fabrication and

assembly system design - designing production systems for robustness and structure.

Strategic approach and technical aspects of product design: Steps in the strategic approach to

product design - Comparison to other product design methods - Assembly sequence generation -

Choosing a good assembly sequence - Tolerances and their relation to assembly - Design for

material handling and part mating - Creation and evaluation of testing strategies.

Basic issues in manufacturing system design: System design procedure - Design factors -

Intangibles - Assembly resource alternatives - Task assignment - Tools and tool changing - Part

feeding alternatives - Material handling alternatives - Floor layout and system architecture

alternatives.

Assembly workstation design: Strategic issues - Technical issues analysis.

Design of automated fabrication systems: Objectives of modern fabrication system design -

System design methodology - Preliminary system feasibility study - Perform detailed work

content analysis - Define alternative fabrication configurations - Configuration design and layout

- Human resource considerations - Evaluate technical performance of solution.

Case studies: Automobile air conditioning module - Robot assembly of automobile rear axles.

TEXT BOOK:

1. Concurrent Design of Product and Processes by James L. Nevins and Daniel E. Whitney,

McGraw-Hill Publishing Company, 1989.

REFERENCE BOOK:

1. Concurrent Engineering: Automation, Tools and Techniques by Andrew Kaushik, John Wilet

& Sons, 1993.

46

Code: M16 CAD 1208

SIGNAL ANALYSIS AND CONDITION MONITORING



Credits : 4

COURSE OBJECTIVES:

1. To acquire basic knowledge on signal analysis of stationary, continuous non-stationary

signals and transient signals.

2. To understand the maintenance scheme, their scope and limitations.

3. To apply the maintenance strategies to various problems in the industrial sectors.

COURSE OUTCOMES:


1. Understand the concepts of Fourier analysis and practical analysis of various signals.

2. Develop an appreciation for the need of modern technological approach for plant

maintenance to reduce the maintenance expenditure.

3. Analyze for machinery condition monitoring and explain how this compliments monitoring

the condition.

SYLLABUS

Introduction: Basic concepts, Fourier analysis. Bandwidth, Signal types, Convolution.

Signal analysis: Filter response time, Detectors, Recorders, Analog analyzer types.

Practical analysis of stationary signals: Stepped filter analysis, Swept filter analysis, High

speed analysis, Real-time analysis.

Practical analysis of continuous non-stationary signals: Choice of window type, Choice of

window length, Choice of incremental step, Practical details, Scaling of the results.

Practical analysis of transients: Analysis as a periodic signal, Analysis by repeated playback

(constant bandwidth).Analysis by repeated playback (variable bandwidth).

Condition monitoring in real systems: Diagnostic tools, Condition monitoring of two stage

compressor, Cement mill foundation, I.D. fan.Sugar centrifugal, Cooling tower fan, Air

separator, Preheater fan, Field balancing of rotors, ISO standards on vibrations.

TEXT BOOKS:

1. Frequency Analysis by R.B.Randall.

2. Condition Monitoring of Mechanical Systems by Kolacat.

REFERENCE BOOK:

1. Mechanical Vibrations Practice with Basic Theory by V. Ramamurti, Narosa Publishing

House.

47

Code: M16 CAD 1209

ADDITIVE MANUFACTURING



Credits : 4

COURSE OBJECTIVES:

1. To introduce Rapid Prototype tools and techniques and additive manufacturing techniques

for design and Manufacturing.

COURSE OUTCOMES:


1. Assess the need of RPT in Product development.

2. Judge the correct RP Process for Product/Prototype development.

3. Predict the technical challenges in 3D printing.

4. List the applications of RPT

SYLLABUS

Introduction: Need - Development of AM systems – AM process chain - Impact of AM on

Product Development - Virtual Prototyping- Rapid Tooling – RP to AM -Classification of AM

processes-Benefits- Applications. Reverse engineering and cad modeling: Basic concept- Digitization techniques – Model

reconstruction – Data Processing for Rapid Prototyping: CAD model preparation, Data

requirements – Geometric modeling techniques: Wire frame, surface and solid modeling – data

formats - Data interfacing, Part orientation and support generation, Support structure design,

Model Slicing, Tool path generation-Software for AM- Case studies. Liquid based and solid based additive manufacturing systems: Stereolithography Apparatus

(SLA): Principle, pre-build process, part-building and post-build processes, photo polymerization

of SL resins, part quality and process planning, recoating issues, materials, advantages,

limitations and applications. Solid Ground Curing (SGC): working principle, process, strengths,

weaknesses and applications. Fused deposition Modeling (FDM): Principle, details of processes,

process variables, types, products, materials and applications. Laminated Object Manufacturing

(LOM): Working Principles, details of processes, products, materials, advantages, limitations

and applications - Case studies. Powder based additive manufacturing systems: Selective Laser Sintering (SLS): Principle,

process, Indirect and direct SLS- powder structures, materials, post processing, surface deviation

and accuracy, Applications. Laser Engineered Net Shaping (LENS): Processes, materials,

products, advantages, limitations and applications– Case Studies.

48

Other additive manufacturing systems: Three dimensional Printing (3DP): Principle, basic

process, Physics of 3DP, types of printing, process capabilities, material system. Solid based,

Liquid based and powder based 3DP systems, strength and weakness, Applications and case

studies. Shape Deposition Manufacturing (SDM), Ballastic Particle Manufacturing (BPM),

Selective Laser Melting, Electron Beam Melting.

TEXT BOOK:

1. Gibson, I., Rosen, D.W. and Stucker, B., ―Additive Manufacturing Methodologies: Rapid

Prototyping to Direct Digital Manufacturing‖, Springer, 2010.

REFERENCE BOOKS:

1. Chua, C.K., Leong K.F. and Lim C.S., ―Rapid prototyping: Principles and applications‖,

second edition, World Scientific Publishers, 2010.

2. Gebhardt, A., ―Rapid prototyping‖, Hanser Gardener Publications, 2003.

3. Liou, L.W. and Liou, F.W., ―Rapid Prototyping and Engineering applications : A tool box for

prototype development‖, CRC Press, 2011.

4. Kamrani, A.K. and Nasr, E.A., ―Rapid Prototyping: Theory and practice‖, Springer, 2006.

5. Hilton, P.D. and Jacobs, P.F., Rapid Tooling: Technologies and Industrial Applications, CRC

press, 2005.

49

Code: M16 CAD 1210

METROLOGY AND NON DESTRUCTIVE TESTING



Credits : 4

COURSE OBJECTIVES:

1. To learn about various precision measuring instruments and their applications.

2. To learn about various statistical quality control tools and techniques to improve the quality

of the product

3. To provide understanding on basic NDT techniques and their importance.

COURSE OUTCOMES:


1. Know how to use different measuring instruments.

2. Understand the philosophy and basic concepts of quality improvement

3. Determine basic process capability, evaluate measurement error, and evaluate simple

acceptance sampling plans

4. Select and carryout appropriate NDT techniques in accordance with established procedures.

SYLLABUS

Measuring machines Tool Maker's microscope - Co-ordinate measuring machines - Universal

measuring machine - Laser viewers for production profile checks - Image shearing microscope -

Use of computers - Machine vision technology - Microprocessors in metrology.

Statistical Quality Control Data presentation - Statistical measures and tools - Process capability

- Confidence and tolerance limits - Control charts for variables and for fraction defectives -

Theory of probability - Sampling - ABC standard - Reliability and life testing.

Liquid penetrant and magnetic particle tests Characteristics of liquid Penetrants - different

washable systems - Developers - applications - Methods of production of magnetic fields -

Principles of operation of magnetic particle test - Applications - Advantages and limitations. RADIO GRAPHY Sources of ray-x-ray production - properties of d and x rays - film

characteristics - exposure charts - contrasts - operational characteristics of x ray equipment -

applications. Ultrasonic and acoustic emission techniques Production of ultrasonic waves - different types of

waves - general characteristics of waves - pulse echo method - A, B, C scans - Principles of

acoustic emission techniques - Advantages and limitations - Instrumentation - applications.

TEXT BOOKS:

1. JAIN, R.K. ―Engineering Metrology ", Khanna Publishers, 1997.

2. Barry Hull and Vernon John, " Non Destructive Testing", Mac Millan, 1988.

50

REFERENCE BOOKS:

1. American Society for Metals, ―Metals Hand Book ", Vol. II, 1976.

2. Progress in Acoustic Emission, ―Proceedings of 10th International Acoustic Emission

Symposium ", Japanese Society for NDI, 1990.

51

Code: M16 CAD 1211

CAM LAB



Credits : 2

COURSE OBJECTIVES:

1. To give a job oriented training on the CNC Lathe and CNC Milling Machine.

2. To study programming and machining on CNC Lathe and CNC Milling.

3. To study select/apply/implement tooling, machine setting, work holding techniques etc.

along with basic maintenance.

COURSE OUTCOMES:


1. Illustrate the importance of NC and CNC technology in manufacturing industry.

2. Generate Part Programming with application of CAD/CAM systems in particular for

complex models.

3. Identify and select proper NC toolings

SYLLABUS

Manual and computer assisted part programming exercises on CNC machine tools.

Surface generation, Tool selection, NC code generation and Tool path simulation for turning

and milling operations using CAM packages like CATIA, Gibbs CAM, Master CAM.

Robot programming off-line and on-line.

REFERENCE BOOKS:

1. Numerical Control and Computer Aided Manufacturing by T.K. Kundra, P.N. Rao and N.K.

Tewari, Tata McGraw-Hill Company Limited, New Delhi.

2. Numerical Control of Machine Tools by Yoram Koren and Joseph Ben-Uri, Khanna

Publishers, Delhi.


Company Ltd.

52

Code: M16 CAD 1212 SEMINAR-II






53


M.TECH (CAD/CAM)


(Regulation:R16)


III – SEMESTER


Marks

Total

Marks

M16 CAD

2101

Thesis Work-




industry/research organization, one advisor (Guide) should be from the department and one

advisor (Co-Guide) should be from the industry/research organization.

2. The Thesis Work -Preliminary should be submitted at the end of 3rd semester and it will be

evaluated through Review by a committee consisting of Head of the Department, External

Examiner, PG coordinator and guide. The marks shall be awarded in the ratio of 20, 40, 20

and 20 percent by the members respectively

54


M.TECH (CAD/CAM)


(Regulation:R16)


IV – SEMESTER


Marks

Total

Marks

M16 CAD

2201

Thesis Work -


1. A publication of a paper on the thesis work in a National/International Journal at the end of 4th


2. The Thesis should be submitted at the end of 4th semester and it will be evaluated through

Viva–Voce examination by a committee consisting of Head of the Department, External

Examiner, PG coordinator and thesis guide. The marks shall be awarded in the ratio of 20, 40, 20

and 20 percent by the members respectively.