INTERNATIONAL BURCH UNIVERSITY FACULTY OF …

INTERNATIONAL BURCH UNIVERSITY

FACULTY OF ENGINEERING AND NATURAL SCIENCES

DEPARTMENT OF ELECTRICAL AND ELECTRONICS ENGINEERING

FIRST CYCLE STUDY PROGRAM SPECIFICATION

SARAJEVO

June 2021

2

TABLE OF CONTENTS

1. PROGRAM DESCRIPTION ......................................................................................................................... 3

1.1 General ..................................................................................................................................................... 3

1.2 Vision ....................................................................................................................................................... 3

1.3 Mission .................................................................................................................................................... 3

1.4 Program .................................................................................................................................................... 3

1.5 Internships ................................................................................................................................................ 4

1.6 Learning and Teaching ............................................................................................................................ 4

1.7 Teaching/learning methods and strategies ............................................................................................... 5

1.8 Assessment Protocols .............................................................................................................................. 5 1.8.1 Assessment ...................................................................................................................................... 5

1.9 Transferable skills .................................................................................................................................... 6

1.10 Skills and other attributes ...................................................................................................................... 6

1.11 Methods for Evaluating and Improving the Quality and Standards of Teaching and Learning ............ 6

1.12 Criteria for Admission ........................................................................................................................... 6

1.13 Job Opportunities ................................................................................................................................... 7

2. CURRICULUM OF DEPARTMENT OF ELECTRICAL AND ELECTRONICS ENGINEERING ......... 8

3

1. PROGRAM DESCRIPTION

1.1 General

Electrical and Electronics Engineering is the most important division of almost all of the science and

engineering applications. Because of its role in the improvement of civilization, this discipline became a

separate engineering profession. In today’s age of electronics, Electrical and Electronics Engineering is one

of the main branches of engineering that contribute through professional services towards more prosperous

and sustainable society.

1.2 Vision

Always to be a preferential department which is dynamic, interdisciplinary, ethic, enterprising, engrossing,

open to original concepts, environmentalist, active in social points, respectful to human dignity, high quality

in science and modern.

1.3 Mission

The mission of the Department of Electrical and Electronics Engineering is to educate the students to gain an

understanding of the fundamentals of science and engineering so that they can develop solutions to Electrical

and Electronics Engineering problems and enhance their skills on design methods of electrical or electronic

devices, microchips, computer hardware, robots, signal and image processing instruments, microwave,

communication, control, medical electronics, electric machines, power generation and transmission systems,

power equipment, dielectrics and insulation systems. It is aimed to especially emphasize teamwork,

independent and innovative thinking, leadership qualities and to educate high qualified engineers for this

purpose. In particular, Electrical and Electronics Engineering Program aims to:

• Train the students to have theoretical background in basic sciences and engineering and to be

equipped with necessary technical skills,

• Develop students' competency in reading, writing and oral communication,

• Provide practical experience which will enable students to utilize and enhance their engineering

knowledge,

• Promote students' self-discipline and self-assurance and the ability to learn on their own,

• Encourage team work, collaboration and development of interpersonal skills,

• Motivate the students towards contributing to the progress of science and technology,

• Teach the importance of ethical behavior in social and professional life,

• Produce graduates for the engineering and the business communities who are observant, inquisitive

and open to new technologies for developing better solutions,

• Produce graduates for the engineering and business communities with integrity, determination,

judgment, motivation, ability and education to assume a leadership role to meet the demanding

challenges of the society.

1.4 Program

Electrical and Electronics engineering involves in a wide variety of technology ranging from huge global

positioning systems which can pinpoint the location of a moving vehicle to gigantic electrical power

generators. Electrical and electronics engineers are responsible for synthesis of science, technology and

designing developing, testing as well supervising the production of electrical and electronic equipment and

machinery. Also developments as consumer products, electronic components, microchips, computers,

robots, electrical machines, power generating, controlling, and transmission devices used by electric utilities;

lighting, and wiring in buildings, as well as artificial intelligence, signal processing, microwave, and

telecommunication equipment. Considering the rapid developments in information technology, for example,

many opportunities and challenges have been created for the electrical and electronics engineer. In addition,

4

other electrical/electronic products have proliferated incredibly in recent years. Hence, electrical and

electronics engineering has gained an increasing importance and become more popular. It is also a field

responsible for a wide range of technologies where new developments are frequent and competition is

considerable.

The Electrical and Electronics Engineering Department offers a three years Bachelor Degree and two years

Masters Degree Program. The first year of the program is dedicated to the study of basic sciences and

mathematics which provide the student with engineering fundamentals. Program is designed firstly to

provide students with hands-on laboratory practice using state-of-the art equipment. In addition, since the

ability to design is an important part of electrical and electronics engineering, students are presented with

challenging design problems in several courses. The senior design project course also gives students an

opportunity to take on a large challenging project similar to the ones they will have once they are

employed. The Curriculum of the program includes elective courses, which give an opportunity to students

to improve their professional skills according to their interests. Some of them are nontechnical and free

elective courses, the remaining are technical electives. The requirements for a Diploma in Electrical and

Electronics Engineering include the completion of minimum of 180 ECTS credits of formal course work and

60 days of approved practical training. The students who completed the bachelor degree level can continue

to attend masters’ level on their demand and if they meet the minimum GPA of bachelor level conditions.

1.5 Internships

Internships for academic credit add a significant workplace experience to a student’s education. Students

earn a total of 4 ECTS hours of academic credit for their internships. They gain valuable “on the job” work

experience related to a chosen focus in information systems applications. In addition, internships permit

students to interact with professionals in the fields of work in which they may one day have careers.

1.6 Learning and Teaching

Learning and teaching methods provide high quality learning opportunities that enable students to

demonstrate achievement of the learning outcomes of the course and those of the modules which constitute

their chosen route of study.

The course aims to foster the development of independent study skills and autonomy of learning and

encourage a commitment to lifelong learning and continuous professional development. Teaching and

learning methods increasingly promote the capacity for students to assume responsibility for their own

learning and development. Progressive use of project learning, integrated assessment and product/problem

based learning allow students to take on greater self-direction of their learning. Emphasis is often placed on

group and team working throughout the study.

The course employs a wide range of learning opportunities and teaching methods, informed by curriculum

review, pedagogic research and continuous staff development. Particular methods for each module or cohort

are identified prior to delivery through the annual planning process. Innovative approaches to teaching,

learning and assessment are encouraged. The course seeks to expand the application of technology in the

delivery of teaching and learning support wherever appropriate.

Scheduled sessions will include the use of lectures, seminars and practical sessions. Advantage will be taken

of both technology and supportive activities to ensure that effective learning takes place. These activities

will include the use of simulations, role play, case studies, projects, practical work, work based learning,

workshops, peer group interaction, self managed teams and learner managed learning

5

1.7 Teaching/learning methods and strategies

Lectures/classes: offer information, literature review and illustrative application and present and explore

core ideas in the subject. A student will apply intellectual skills to prepare solutions to examples sheet

questions which will be discussed in a small class.

Practical sessions: computational methods are taught as a series of computer-based practicals with short

introductory lectures on theory. This enables a student to understand issues in application of computational

methods to simulated and real problems and also develop computing skills relevant to the rest of the course

including the research project. Practicals, computer-based and experimental lab based, provide an

opportunity for a student to consolidate the theory they have learned about in lectures and apply it to

problems.

Group project: provides an opportunity to study a real computer engineering problem in depth, practice

analytic and problem-solving skills, and work in a team.

Individual project: involves a literature review, problem specification and experiments/analysis written up

in a report. This enables a student to practice the application of techniques they have learned about to a

technology problem in some depth as well as put into practice general research skills.

Expert (guest) lectures and seminars: provide a student with the opportunity to hear internal speakers and

external speakers from industry. This enables a student to gain appreciation of some applications, needs and

roles of computer engineers as well as career opportunities.

1.8 Assessment Protocols

The purpose of outcomes-based learning assessment is to improve the quality of learning and teaching in

Information Technology department. The fundamental principles are:

• Student learning is the central focus of the department‘s efforts.

• Each student is unique and will express learning in a unique way.

• Students must be able to apply their learning beyond the classroom.

• Students should become effective, independent, lifelong learners as a result of their educational

experience.

Assessment of the IT Learning Outcomes (ITLOs) begins with the normal assessment process in the major

courses that are taken by students. Each course defines course outcomes and relates the course outcomes to

the ITLOs. Students also prepare portfolios that reflect their achievements and capabilities, and the

evaluation of the portfolios by a faculty committee represents the final assessment of a student‘s

achievement in the ITLOs.

1.8.1 Assessment

Assessment of knowledge and understanding is by:

Unseen written examinations

Written essay assignments

Assessment of practical work

Group project report write-up and team presentation

Individual project report and short presentation/viva

6

1.9 Transferable skills

By the end of the course a student will have developed a range of transferable skills including skills in:

• Managing their own learning and conducting independent thinking and study

• Problem specification and modelling

• Applying mathematical and computational methods to solve (engineering) problems

• Use of general electronics technology

• Managing a research project, including planning and time management

• Conducting an engineering-based research-based work, from hypothesis to report writing

• Working in a multi-disciplinary team

• Critical analysis

1.10 Skills and other attributes

• can effectively communicate information, arguments and analysis in a variety of forms to specialist

and non-specialist audiences, and deploy key techniques of the discipline effectively

• can undertake further training, develop existing skills and acquire new competences that will enable

them to assume significant responsibility within organisations

• have the qualities and transferable skills necessary for employment requiring the exercise of personal

responsibility and decision-making

1.11 Methods for Evaluating and Improving the Quality and Standards of Teaching and Learning

• Student Focus groups and the annual student survey

• Class room observation of Lecturers

• Advanced Professional Diploma in Teaching and Learning in Higher Education

• Membership of the Higher Education Academy

• External Examiners reports

• Accreditation Visits

• Curriculum Area Review

• Course Committees

• Annual and periodic review

Indicators of Quality and Standards

• Student feedback

• Retention and success rates for each level for each course

• Student Module Evaluations

• Annual Student Questionnaires

• First Destination Statistics

• Professional accreditation

• External Examiner reports

1.12 Criteria for Admission

The admissions policy for overall Scheme, in which the Electrical and Electronics course operates, is to

admit any applicant who is capable of benefiting from and successfully completing their chosen course.

Applicants meeting the scheme admissions profile or producing alternate evidence for Accreditation of Prior

Learning / Accreditation of Prior Experiential Learning at least equivalent to the scheme admissions profile

satisfy this judgement in practice. Where selection criteria are devised they will be tuned to satisfy the

7

widening participation agenda and equal opportunity policy of the University. Admissions profiles will be

reviewed annually as will selection criteria and will provide a fair and objective basis for selection to

oversubscribed courses. Admission with advanced standing will follow University Procedures. The Scheme

encourages non-standard and mature applicants, and applicants with advanced standing. These are

considered on an individual basis.

Students whose first language is not English, with certificated qualifications, professional qualifications and

or appropriate work experiences that are equivalent to those detailed above will be considered and

encouraged to apply. In addition to these, you will also have to demonstrate that your standard of English is

at IELTS, TOEFL or tests.

For all applicants we will be looking for evidence of personal skills and qualities through a personal

statement and references. Such skills and qualities include communication skills; literacy; numeracy; study

skills; subject and motivation; work experience and community involvement.

1.13 Job Opportunities

In the global industry, there is a strong demand for Electrical and Electronics Engineers particularly those

who combine technical skills with good communication skills and team-work ability. Some but not all of the

job opportunities can be summarized as follows:

• Working as lecturers or researchers for universities or research centers,

• Research, design, develop, test, and oversee the manufacture and installation of computer hardware,

including computer chips, circuit boards, computer systems, and related equipment.

• Design, develop, test, and supervise the manufacture of electrical equipment including electric

motors; machinery controls, lighting, and wiring in buildings; automobiles; aircraft; radar and

navigation systems; and power generation, control, and transmission devices used by electric utilities

• Responsible for a wide range of technologies, from portable music players to the global positioning

system (GPS), which can continuously provide the location

• Design, develop, test, and supervise the manufacture of electronic equipment such as broadcast and

communications systems.

• Developing devices and procedures that solve medical and health-related problems by combining

their knowledge of biology and medicine with engineering principles and practices.

8

2. CURRICULUM OF DEPARTMENT OF ELECTRICAL AND ELECTRONICS ENGINEERING

1. Semester

CODE COURSE NAME T P ECTS

MTH 101 Calculus I 3 2 6

MTH 103 Linear Algebra 3 2 5

PHY 101 General Physics I 3 2 6

CEN 111 Programming 1 3 2 6

ELT 117 Advanced Reading and Vocabulary I 2 2 5

XXX xxx University Level Elective 0 2 2

Total 14 12 30

2. Semester


EEE 102 Circuit Theory I 3 3 6

MTH 102 Calculus II 3 2 6

PHY 102 General Physics II 3 2 6

CEN 112 Programming 2 3 2 6

EEE 106 Fundamentals of Electrical Engineering 2 2 4

XXX xxx University Level Elective 0 2 2

Total 14 13 30

3. Semester


EEE 201 Circuit Theory II 3 3 6

EEE 205 Semiconductor Devices and Modeling 3 2 5

MTH 201 Differential Equations 2 2 5

EEE 395 Digital Design 3 2 5

EEE 314 Electrical Measurements and Instrumentation 2 2 5

XXX xxx University Level Elective 2 2/1 4

Total 15 13 30

.

4. Semester


EEE 202 Electromagnetic Field Theory 2 2 5

EEE 206 Electronics I 3 2 5

EEE 212 Signals and Systems 3 2 5

MTH 204 Numerical Analysis 2 2 5

MTH 205 Probability and Statistics for Engineers 3 2 5

CEN 382 Microprocessors and Microcomputing 3 2 5

Total 16 12 30

5. Semester


EEE 311 Electronics II 3 2 5

EEE390 Internship 0 20 5

XXX xxx Technical Elective I (Department Level Elective) 3 2 5

XXX xxx Technical Elective II (Department Level Elective) 3 2 5

XXX xxx Technical Elective III (Department Level Elective) 3 2 5

XXX xxx Technical Elective IV (Faculty Level Elective) 3/2 2 5

Total 15/14 30 30

9

6. Semester


EEE 382 Linear Control Systems 3 2 5

XXX xxx Technical Elective V (Department Level Elective) 3 2 5

XXX xxx Technical Elective VI (Department Level Elective) 3 2 5

XXX xxx Technical Elective VII (Department Level Elective) 3 2 5

XXX xxx Technical elective VIII (Faculty Level Elective) 3/2 2 5

EEE 392 Senior Design Project 0 10 5

Total 15/14 18 30

Department Elective Courses


EEE 310 Electromagnetic Wave Theory 2 2 5

EEE 320 Introduction to Energy Systems 2 2 5

EEE 321 Microwave Engineering 2 2 5

EEE 322 Antenna Engineering 2 2 5

EEE 324 Microwave Electronics 2 2 5

EEE 331 Telecommunications I 2 2 5

EEE 332 Telecommunications II 2 2 5

EEE 333 Digital Communication 2 2 5

EEE 334 Digital Signal Processing 3 2 5

EEE 336 Communication Electronics 2 2 5

EEE 337 Introduction to Wireless Communications 2 2 5

EEE 346 Introduction to VLSI Design 2 2 5

EEE 348 Introduction to Image Processing 2 2 5

EEE 349 Introduction to Optical Fiber Communications 2 2 5

EEE 360 Illumination 2 2 5

EEE 361 Electrical Machinery I 2 2 5

EEE 363 Renewable Electrical Energy Systems 3 2 5

EEE 364 Power System Analysis 3 2 5

EEE 366 Electrical Power Transmission 2 2 5

EEE 367 Power System Protection 2 2 5

EEE 369 Distribution Systems 3 2 5

EEE 370 Industrial Electronics 2 2 5

EEE 371 Static Power Conversion 2 2 5

EEE 372 Power Electronics 3 2 5

EEE 373 Low Voltage Power Systems 2 2 5

EEE 374 Computer Relaying in Power Systems 2 2 5

EEE 375 Power System Communication 2 2 5

EEE 376 Smart Grid 2 2 5

EEE 377 Sustainable Distributed Power Generation 2 2 5

EEE 378 Power System Quality 2 2 5

EEE 379 Industrial Utilization of Electrical Energy 2 2 5

EEE 380 Introduction to Robot Control 3 2 5

EEE 381 Process Control 2 2 5

EEE 383 Discrete Time Control System 2 2 5

EEE 384 Process Instrumentation and Control 2 2 5

EEE 391 HDL Based Logic Design 2 2 5

EEE 394 Embedded Systems 3 2 5

EEE 396 General Metrology 3 2 5

10

Faculty Level Elective Courses


GBE 307 Bioinformatics 2 2 5

GBE 321 Intelligent Systems 2 2 5

GBE 323 Biomedical Instrumentation 2 2 5

GBE 325 Biomedical Signals and Systems 2 2 5

GBE 330 Biosensors 2 2 5

CEN 221 Object Oriented Programming 2 2 5

CEN 254 Data Structures 2 2 5

CEN 263 Computer Networks 2 2 5

University Level Elective Courses


BOS 101 Bosnian/Croatian/Serbian Language I 0 2 2

TDE 101 Turkish Language I 0 2 2

GRM 101 German Language I 0 2 2

BOS 102 Bosnian/Croatian/Serbian Language II 0 2 2

TDE 102 Turkish Language II 0 2 2

GRM 102 German Language II 0 2 2

CE 113 Environment 1 0 2 2

CE 114 Environment 2 0 2 2

MAN 112 Business Communication Skills 0 2 2

MAN 309 Entrepreneurship 2 1 4

MAN 107 Introduction to Business 2 1 5

MAN 223 Leadership 2 1 5

MAN 321 Operations Research 2 2 5

Course Code: MTH 101 Course Name: CALCULUS I

Level: Undergraduate Year: I Semester: I ECTS Credits: 6

Status: Compulsory Hours/Week: 3+2 Total Hours: 45+30

Course Description

Use of calculus is widespread in science, engineering, medicine, business, industry, and many other fields. Calculus also

provides important tools in understanding functions and has led to the development of new areas of mathematics including real and

complex

analysis, topology, and non-Euclidean geometry.

Course Objectives Objectives of this course are to: expand understanding of mathematical topics that may have been previously studied; introduce

and explore topics that possibly have not been part of the student’s mathematical experience; develop an appreciation for the

development of mathematical thought; show the application of mathematics in real life problems and analyzing the results.

Course Content

Week 1: Functions. Week 2: Limits. Continuity

Week 3: Derivatives.

Week 4: Basic Differentiation Formulas. Chain Rule Week 5: Implicit Differentiation.

Week 6: Related Rates.

Week 7: Exponential Functions. Inverse Functions and Logarithms.

Week 8: MIDTERM EXAM

Week 9: Indeterminate Forms and L’Hospital’s Rule. Week 10: Maximum and Minimum Values.

Week 11: Curve Sketching.

Week 12: Optimization Problems. Week 13: Antiderivatives. The Definite Integral

Week 14: Fundamental Theorem of Calculus. Integration.

Week 15: Areas between curves. Week 16: FINAL EXAM

Week 1: Lab 1: Functions.

Week 2: Lab 2: Limits. Continuity Week 3: Lab 3: Derivatives.

Week 4: Lab 4: Basic Differentiation Formulas. Chain Rule

Week 5: Lab 5: Implicit Differentiation Week 6: Lab 6: Related Rates.

Week 7: Lab 7: Exponential Functions. Inverse Functions and

Logarithms. Week 8: MIDTERM EXAM

Week 9: Lab 8: Indeterminate Forms and L’Hospital’s Rule.

Week 10: Lab 9: Maximum and Minimum Values. Week 11: Lab 10: Curve Sketching.

Week 12: Lab 11: Optimization Problems.

Week 13: Lab 12: Antiderivatives. The Definite Integral Week 14: Lab 13: Fundamental Theorem of Calculus.

Integration.

Week 15: Lab 14: Areas between curves. Week 16: FINAL EXAM

Teaching Methods

Description

• Interactive lectures and communication with students

• Practical Sessions

Assessment Methods

Description (%)

Quiz 10 % Lab/Practical Exam 10 %

Homework 0 % Term Paper 0 %

Assignment 0 % Attendance 0 %

Midterm Exam 40 % Class Deliverables 0 %

Presentation 0 % Final Exam 40 %

Total 100 %

Learning Outcomes

After completion of this course, students should be able to: 1. Recognize properties of functions and their inverses.

2. Recall and use properties of polynomials, rational, exponential, logarithmic, trigonometric and inverse trigonometric functions.

3. Sketch graphs, using function, its first derivative, and the second derivative.

4. Use algebra of limits, and l’Hôspital’s rule to determine limits of simple expressions.

5. Apply the procedures of differentiation accurately, including implicit and logarithmic differentiation.

Prerequisite Course(s) -

Language of Instruction English

Mandatory Literature Essential Calculus, Early Transcendentals, 2nd edition by James Stewart

Recommended Literature Thomas's Calculus, Eleventh Edition, George B. Thomas

Calculus a Complete Course, Sixth Edition, Robert A. Adams

ECTS (ALLOCATED BASED ON STUDENT’S WORKLOAD)

Activities Quantity Duration Workload

Lecture (15 weeks x Lecture hours per week) 15 3 45

Laboratory / Practice (15 weeks x Laboratory / Practice hours per week) 15 2 30

Midterm Examination (1 week) 1 2 2

Final Examination (1 week) 1 2 2

Preparation for Midterm Examination 1 5 5

Preparation for Final Examination 1 5 5

Assignment / Homework / Project 1 65 65

Seminar / Presentation 0 0 0

12

Total Workload 155

ECTS Credit (Total Workload / 25) 6

Course Code : MTH 103 Course Name: LINEAR ALGEBRA


Status: Mandatory Hours/Week: 3+2 Total Hours: 45+30

Course Description

Introduction to matrices. Fields and vector spaces, linear transformations, change of basis. Linear equations, existence and

classification of solutions, Gaussian elimination and LU decomposition. Characteristic equation of a matrix: eigenvalues,

eigenvectors and the Jordan form. Numerical techniques for computing eigenvalues and eigenvectors. Inner product spaces, quadratic form.

Course Objectives

Linear Algebra is a Math of the systems of linear equations and their solutions. There are a variety of applications of Linear

Algebra. Sufficient knowledge in this field can assist students in learning other (more applicable) courses as Linear Programming Problems, Operations Research, Problems of Optimization,etc. The main objectives of the course are:

• To extend the students knowledge on the Systems of Linear Equations

• To realize the main areas of applicability of LA

Course Content

(weekly plan)

Week 1 Vectors Week 9 Linear Transformations Definition

Week 2 Lines, Systems of Linear Equations Week 10 Determinants

Week 3 Solving Linear Systems. Gauss elimination method. Echelon form of a Matrix

Week 11 Subspaces and basis

Week 4 Solving Linear Systems. Gauss elimination

method. Echelon form of a Matrix Week 12

Eigenvalues, Eigenvectors

Week 5 Spanning sets and linear independence Week 13 Eigenvalues, Eigenvectors for nxn matrices

Week 6 Matrices Week 14 Similarity and diagonalization

Week 7 Matrices, inverse of matrix Week 15 Final exam preparation

Week 8 Midterm Exam Week 16 Final exam

Tutorials

Week 1 Vectors Week 9 Linear Transformations Definition

Week 2 Lines, Systems of Linear Equations Week 10 Determinants

Week 3 Solving Linear Systems. Gauss elimination

method. Echelon form of a Matrix Week 11

Subspaces and basis

Week 4 Quiz 1 Week 12 Quiz 2

Week 5 Spanning sets and linear independence Week 13 Eigenvalues, Eigenvectors

Week 6 Matrices Week 14 Similarity and diagonalization

Week 7 Matrices, inverse of matrix Week 15 Final exam preparation

Week 8 Midterm Exam Week 16 Final exam

Teaching Methods

Description • Interactive lectures and communications with students • Discussions and group works and Presentations

Assessment Methods

Description (%)

Quiz 20% Lab/Practical Exam 0 %


Project 0 % Attendance 0 %



Total 100 %

Learning Outcomes

(please write 5-8 outcomes)

After a course, students are expected to be able to:

1. Solve linear equations by using Gauss elimination. 2. Perform matrix calculations.

3. Calculate the determinant of a matrix both by elementary row and column operations as well as by expanding by a row

or a column. 4. Understand the concept of vector and how to add a vectors and multiply them with scalar in a space of dimension 3,

both by using coordinates and in spaces without a given coordinate system.

5. Perform dot product of vectors, both using a given orthonormal coordinate system and without any coordinate system.

Instruction Language English Prerequisite courses

Mandatory Literature • Richard Hill: Elementary Linear Algebra Kenneth Hofman

Recommended Literature • Ray Kunze: Linear Algebra



14







Assignment / Homework / Project 25 25

Seminar / Presentation

Total Workload 129


Course Code: PHY101 Course Name: GENERAL PHYSICS I



Course Description

This course is the first semester of a calculus-based physics course primarily intended for engineering students. The course

introduces fundamental physical concepts as applied to engineering technology fields. Topics include systems of units,

problem-solving methods, graphical analysis, vectors, motion, forces, Newton's laws of motion, work, energy, power,

momentum, and properties of matter. Upon completion, students should be able to apply the principles studied to

applications in engineering technology fields.

Course Objectives Objective of the course is to give understanding the basic concepts of kinematics and dynamics relative to the practical use in

engineering.

Course Content (weekly

plan)

Week 1 Introduction to course / Measuring systems

and vectors Week 9 Rotation - Center of Mass and Linear

Momentum,

Week 2 Motion along a straight line Week 10 Rotation - Rolling, Torque, and Angular

Momentum

Week 3 Motion in 2D and 3D Week 11 Gravitation

Week 4 Force and motion Week 12 Oscillations

Week 5 Kinetic, potential energy and work Week 13 Waves

Week 6 Conservation of energy Week 14 Elasticity and vibration

Week 7 Preparation for midterm exam (Quiz 1) Week 15 Preparation for the final exam (Quiz 2)

Week 8 Midterm exam Week 16 Final exam

Week 1 Tutorial 1: Measuring systems and vectors Week 9 Tutorial 8: Rotation - Center of Mass and

Linear Momentum,

Week 2 Tutorial 2: Motion along a straight line Week 10 Tutorial 9: Rotation - Rolling, Torque, and

Angular Momentum

Week 3 Tutorial 3: Motion in 2D and 3D Week 11 Tutorial 10: Gravitation

Week 4 Tutorial 4: Force and motion Week 12 Tutorial 11: Oscillations

Week 5 Tutorial 5: Kinetic, potential energy and

work

Week 13 Tutorial 12: Waves

Week 6 Tutorial 6: Conservation of energy Week 14 Tutorial 13: Elasticity and vibration

Week 7 Tutorial 7: Preparation for midterm exam Week 15 Tutorial 14: Preparation for the final exam


Teaching Methods Description (list up to 4 methods)

• Lectures • Tutorials

• Experiments • Presentations

Assessment Methods

Description (%)






Total 100 %

Learning Outcomes (please write 5-8 outcomes)

1. Define phenomena, concepts and terminology of mechanics. 2. Gain experience in problem-solving in the field of mechanics. 3. Develop capabilities to present a topic in the field of mechanics. 4. Apply knowledge obtained to an engineering field. 5. Develop interpersonal and listening skills.


Mandatory Literature • Halliday, David, Robert Resnick, and Jearl Walker. Fundamentals of physics extended. John Wiley & Sons, 2013

(10th edition)

Recommended Literature • D.C. Giancoli: Physics for scientist and engineers, Prentice Hall, New Jersey, 2000 • The other sources from program fields. It is possible to use all books and Collection of problems on university level.

16










Seminar / Presentation 0 0

Total Workload 144


17

Course Code: CEN 111 Course Name: PROGRAMMING I


18


Course Description This course is designed to be an introduction to the fundamentals of programming. Students will design, write and debug computer programs. No knowledge of programming is assumed.

Course Objectives

Objectives of this course are to: introduce students to intermediate concept of programming; introduce students to basic

algorithm design principles; substantially strengthen students’ programming skills by requiring them to constantly program large number of small but challenging problems; encourage strive for excellence by introducing them to a competitive environment

where part of their performance will be based on performance of their peers.

Course Content

Week 1: Introduction. Software Development Life Cycle

Week 2: Variables, Expressions and Data Week 3: Functions (1)

Week 4: Operators, Expressions and Statements

Week 5: Functions (2) Week 6: Selections. Iterations (1)

Week 7: Iterations (2). Strings (1)

Week 8: MIDTERM EXAM Week 9: Strings (2)

Week 10: Lists

Week 11: Files Week 12: Dictionaries

Week 13: Recursion

Week 14: Object Oriented Programming (1) Week 15: Object Oriented Programming (2)

Week 16: FINAL EXAM

Week 1: Lab 1: Introduction. Software Development Life Cycle Week 2: Lab 2: Variables, Expressions and Data

Week 3: Lab 3: Functions (1)

Week 4: Lab 4: Operators, Expressions and Statements Week 5: Lab 5: Functions (2)

Week 6: Lab 6: Selections. Iterations (1)

Week 7: Lab 7: Iterations (2). Strings (1) Week 8: MIDTERM EXAM

Week 9: Lab 8: Strings (2)

Week 10: Lab 9: Lists Week 11: Lab 10: Files

Week 12: Lab 11: Dictionaries

Week 13: Lab 12: Recursion Week 14: Lab 13: Object Oriented Programming (1)

Week 15: Lab 14: Object Oriented Programming (2)

Week 16: FINAL EXAM

Teaching Methods

Description



Assessment Methods

Description (%)






Total 100 %

Learning Outcomes

After completion of this course, students should be able to: 1. Define basic terminology used in computer programming

2. Establish knowledge and understanding of intermediate Python programming concepts

3. Analyze, design, code, compile and debug programs in Python language.

4. Develop programs involving decision structures, loops and functions.

5. Use different data types in a computer program.



Mandatory Literature • Allen Downey: How to Think Like a Computer Scientist: Learning with Python

• Tony Gaddis: Starting out with Python

Recommended Literature











Total Workload 155


19

Course Code : ELT 117 Course Name: Advanced Reading and Vocabulary I

Level : Undergraduate Year : I Semester : I ECTS Credits : 4

Status : Compulsory Hours/Week : 2+2 Total Hours : 30+30

Course Description This course presents a wide range of authentic reading materials including

newspapers, journals, reviews and academic texts in order to comprehend contrasting

viewpoints and to predict and identify main ideas and to decode hidden clues. It also

aims to equip students with intensive and extensive reading habits. Critical thinking

skills such as synthesizing information or analyzing a problem as well as reacting on

the basis of evaluation are fostered. Such sub-skills of reading are employed by

students in their short writings on the topic. Students are expected to improve their

ability to communicate the information and concepts from course reading materials

continually and to improve and expand their vocabulary significantly.

Course Objectives Students will be able to read and comprehend different types of texts. They will have

also learned to acquire new vocabulary on their own and thus to improve their reading

and writing skills. In addition to the integration of reading with writing, research-

based instruction will be adopted, so that students will develop basic research skills

including library or internet search.

Course Content

(weekly plan) • 1st TOPIC Home and the homeless - Home and Travel

• Helping and Hating the Homeless; At home

• 2nd TOPIC: HEALTH Divided Sleep, Long life, Health and medicine

• 3rd TOPIC: History The Robber Barons, The Politics of Progressivism

• Message to Wall Street

• 4th TOPIC: CLOTHING The Necktie; A Young Man and his Kilt

• 5th TOPIC: FILM STUDIES One Hundred Years of Cinema

• Mid-term exam

• A Conversation with Leo Tolstoy on Film; An Interview with James Cameron

• 6th TOPIC: MEDIA STUDY Mind Control and the Internet

• The press and the media; The Use of Social Media in the Arab Spring

• 7th TOPIC: GREAT MINDS The Right-Brain, Left-Brain Controversy

• Artists as Scientists and Entrepreneurs

• 8th TOPIC: THE BRAIN AND MEMORY In Search of Memory

• The Brain and Human Memory Music and the Brain;

• 9TH TOPIC: LEISURE The Art of Paintball

• Final exam Teaching Methods

Description

(list up to 4 methods)

• Reading passages in the classroom.

• Comprehension studies on what is

read.

• Vocabulary exercises by topic and

short writing assignments on that topic

(both in-class and homework

assignments).

Assessment Methods

Description (%)






Total 100 %

Learning Outcomes

(please write 5-8

outcomes)

After completion of this course, students should be able to:

1. Read a variety of texts by using a range of strategies, including decoding and

guessing meaning in unfamiliar texts

2. Analyze extensive reading materials with sufficient comprehension to explain

and discuss critical-thinking elements such as author tone, viewpoint, purpose,

presumptions and underlying beliefs, character motivations, text connections to

students’ personal lives, and logical evaluation of text arguments

3. Recognize sentence and paragraph structures

4. Make logical inferences based on materials read and explain them orally and in

writing.

5. Acquire sufficient college-level vocabulary to comprehend the texts and use this

vocabulary in student writing and speaking assignments.

20

Prerequisite Course(s)

(if any)


Mandatory Literature • Rober F. Cohen and Judy L. Miller. Longman Academic Reading Series 4:

Reading Skills for College (LARS). Pearson Education. 2014. (Chapters 1-5)

• Fellag Linda Robinson. From Reading to Writing Level 3. Pearson

Education (FRTW). 2010. (Units 1-4)

• Michael McCarthy and Felicity O’Dell. English Vocabulary in Use.

Cambridge University Press (EVIU). 2001

Recommended

Literature • Mikulecky Beatrice S, and Jeffries Linda. Reading Power Series, Pearson

ESL, March 2007.


Activities Quantity Duration Worklo

ad









Total Workload 125


21

Course Code: BOS 101 Course Title: BOSNIAN/CROATIAN/SERBIAN LANGUAGE I


Status: Elective Hours/Week: 2 Total Hours: 30

COURSE DESCRIPTION The purpose of this course is to teach Bosnian language basics at the beginner level.

COURSE OBJECTIVES

Highly personalized course designed to improve knowledge of Bosnian language and

communication and language skills. The objective is to achieve the level of language

that would create confidence to communicate in Bosnian with clients, suppliers and

colleagues.

COURSE CONTENTS

1. Learn how to say „Hello“ and acquaint; the classes of nouns (muški, ženski,

srednji rod)

2. Personal pronouns (in the first case), introducing oneself: I'm from ...;

practicing personal pronouns by answering the questions Where are you

from? Where is he/she from? Where are they from?... Introducing verb to be

by questions: Are you from...? Is he from...?

3. Present tense of verb to be (positive, negative and question form); Answering

the question „What's your job?“; learning some of names of different jobs and

male and female form for that kind of nouns

4. Terminology about the faculty, exercise with cross-words; numbers 1-10 with

little short song about the numbers; first information about plural

5. Numbers 11-10.000; speaking exercise about numbers by phone number,

prices; demonstrative pronouns

6. Introducing the collocations about the speaker's attitude about the contents of

sentence and speaking on the scale from extremely kind to extremely unkind;

declarative, interrogative and exclamatory sentences

7. Place and sort of accent in Bosnian words; filling out the forms with basic

information (name, surname, date and place of birth...)

8. Introducing the question-word (what, where, when...); ordinal numbers and

classes of adjectives (muški, ženski, srednji rod)

9. Answering on questions What date is...? When it happened? and exercise for

ordinal numbers

10. SVO order in Bosnian language, order in declarative and interrogative

sentences

TEACHING/ASSESSMENT

Description

Teaching Methods Interactive lectures and communications with

students: Discussions and group works:

Presentations

Participation of different teaching

methods depends on the subject.

Description (%)

Student Assessment

Methods

Attendance

Midterm Examination

Final Examination

30%

30%

40%

Learning Outcomes Provide students with the ability to:

• Speak Bosnian with confidence

• Interact more confidently when visiting a Bosnian-speaking region or

dealing with Bosnian speakers

• Build rapport and strengthen relationships with Bosnian-speaking

colleagues and clients through a show of interest in the Bosnian language

and culture

• Demonstrate goodwill and facilitate international communication at both a

personal and organizational level

Language of Instruction Bosnian, English, Germani

Textbook(s) - Bosanki jezik kao strani jezik, Zenaida Karavdić, Sarajevo 2011. - Bosanski jezik, Priručnik za strance, Minela Kerla, Nermina Alihodžić-

Usejnovski, Sarajevo 2013. - Hrvatski za početnike 1, Udžbenik hrvatskog kao drugog stranog jezika,

Zagreb 2006.

22

23











Total Workload 50


24

Course Code : TDE 101 Course Name: TURKISH LANGUAGE I

Level : Undergraduate Year : 1 Semester : I ECTS Credits : 3

Status :Elective Hours/Week :2 Total Hours : 30

Course Description Türk dilini basit seviyede okuyup, yazma ve konuşma becerisi kazanmak.

Course Objectives

Türkçeyi metinler aracılığıyla öğretmek; Türkçe metinleri okuyup anlamayı kolaylaştırmak; metinler aracılığıyla Türk

kültürünün tanınmasını ve öğrencilerin kültürel söz varlığını zenginleştirmek; öğrencilerin günlük yaşamda

karşılaşabilecekleri sözcük gruplarını öğreterek Türkçeyi akıcı bir şekilde konuşmalarını sağlamak; dil öğretiminin iki ana

becerisi olan anlama ve anlatma becerilerinin gelişimi için gerekli olan dil bilgisi kurallarını öğretme, uygulamaya yönelik

öğretim gerçekleştirme.

Course Content

(weekly plan)

Selamlaşma ve Tanışma ; alfabe, ünlü uyumu

Okul ; koşaç tümcesi, sıralama (-inci), varoluş tümcesi ( Var /Yok) Günler Dersler; Şimdiki Zaman

Ev; Yönelme-Kalma-Çıkma Hali

Ülkeler; iyelik ekleri Akrabalar; belirtili ve belirtisiz isim tamlamaları

Meslekler; belirtili ve belirtisiz isim tamlamaları

Zaman; gelecek zaman öğretimi Meyveler Sebzeler; gelecek zaman öğretimi

Yiyecekler İçecekler; emir kipi, istek kipi

Yemekler; emir kipi, istek kipi Giyecekler; belirtme hali

Konuların Tekrar Edilmesi

Final Sınavı

Teaching Methods

Description



• Discussions and group work

• Presentations (at least 1 per student per semester)

Assessment Methods

Description (%)






Total 100 %

Learning Outcomes


Upon successful completion of the courses in this discipline, the student will have acquired the following knowledge and

skills:

1. Türkçe yazma, konuşma ve okuma becerisini kazanır. Kendini Türkçe tanıtır.

2. Ailesinden Türkçe bahsedebilir

3. Eşyaların Türkçe karşılığını söyleyebilir.

4. Dersler, günler ve ay isimlerini öğrenir.

5. Meslekler hakkında bilgi sahibi olur ve Türkçe meslek isimlerini bilir.

6. Pazar alışverişinde kullanılan terimlerin Türkçe karşılığını bilir. Yiyecek ve içeceklerin Türkçelerini bilir.

7. Basit seviyede Türkçe cümleler kurabilir.

8. Türkçe olarak adres tarifi vs. yapabilir.


(if any) -

Language of Instruction Türkçe

Mandatory Literature Lale Türkçe Kitabı Cilt 1

Recommended Literature Yeni Hitit, Yabancılara Türkçe Ders kitabı 1 (A1-A2), Ankara Üniversitesi-Tömer, 3.baskı, 1984.

Yeni Hitit, Yabancılara Türkçe Çalışma kitabı 1 (A1-A2), Ankara Üniversitesi-Tömer, 3.baskı, 1984.






25






Total Workload 57


Course Code : GRM 101 Course Name: GERMAN LANGUAGE I

Level : Undergraduate Year : 1 Semester : I ECTS Credits : 3

Status :Compulsory Hours/Week : 2 Total Hours : 30

Course Description

German language I course is organized in a way that it covers basic communication; structures and vocabulary necessary

to comprehend simple daily conversational dialogues and reading texts, and to engage in daily simple communication;

information about the culture of the German language.

Course Objectives

The course will enable participants to speak and understand the German language within one semester. Participants will

develop effective conversation skills to undertake the language content with confidence. The course will also provide

participants with an insight into the culture, customs, traditions and practices of the country.

Course Content

(weekly plan)

• Lektion 1 - Guten Tag. Mein Name ist...; Alphabet

• Grammatik – W-Frage, Personalpronomen, Verbkonjugation, Praposition aus

• Lektion 2 – Familie und Freunde; Zahlen; interview – Fragen zur Person

• Grammatik – Possessivartikel; Personalpronomen, Verbkonjugation, Praposition in

• Lektion 3 – Essen und Trinken

• Grammatik – Kennen Sie?; Nullartikel; Negativartikel; Verbkonjugation

• Lektion 4 – Meine Wohnung

• Midterm exam

• Grammatik – definiter Artikel; lokale Adverbien

• Lektion 5 – Mein Tag

• Grammatik – trennbare Verben; verbposition

• Lektion 6 – Freizeit

• Grammatik – Akkusativ; Ja-/Nein- Frage und Antwort

• Lektion 7 – ein Leben lang

• Grammatik – Modalverben; Satzklammer; Perfekt

• Final exam

Teaching Methods

Description





Assessment Methods

Description (%)






Total 100 %

Learning Outcomes



skills:

1. Demonstrate the confidence and listening/speaking skills necessary to participate successfully in spontaneous

aural/oral exchanges with native speakers of the German language in a variety of personal, professional, and/or

academic settings.

2. Demonstrate reading comprehension of German language texts intended for developmental (or higher level)

language courses.

3. Respond appropriately to written or spoken German language by writing paragraphs or short essays that

communicate ideas clearly.


(if any) -


Mandatory Literature • Schritte plus 1 – Kursbuch Daniela Niebisch, Franz Specht, Sylvette Penning-Hiemstra

Recommended Literature • Swick, Edward. The Everything Learning German Book: Speak,, Write and Understand Basic German in No

Time, Adams Media; 1st edition, 2003.






27






Total Workload 50


Course Code: EEE 102 Course Name: CIRCUIT THEORY I

Level: Undergraduate Year: I Semester: II ECTS Credits: 6


Course Description

The course has been designed to introduce fundamental principles of circuit theory commonly used in engineering research

and science applications. Techniques and principles of electrical circuit analysis including basic concepts such as voltage,

current, resistance, impedance, Ohm's and Kirchoff's law; basic electric circuit analysis techniques, Thevenin's theorem, Norton's theorem, resistive circuits, transient and steady-state responses of RLC circuits; First and second order RLC

circuits.

Course Objectives

To develop problem solving skills and understanding of circuit theory through the application of techniques and principles of electrical circuit analysis to common circuit problems. Course goals are:

1. To develop an understanding of the fundamental laws and elements of electric circuits.

2. To learn the energy properties of electric elements and the techniques to measure voltage and current. 3. To be able to analyse the electrical circuits and learn the time domain analysis methods.

Course Content

(weekly plan)

Week 1

Circuit Variables: System of Units, Charge,

Voltage, Current, Power and Energy. Week 9

Thevenin’s and Norton’s

Theorems, Maximum Power Transfer

Week 2

Electrical Circuit Elements: Voltage and

Current Sources, Electrical Resistance and

Ohm’s Law, capacitors and inductors

Week 10

Operational Amplifier and

Multi-terminal Algebraic

Components

Week 3

Simple Resistive Circuits: Ohm’s law,

Resistors in Series and Parallel, Voltage and Current Divider, Delta-Star transformation,

Equivalent Circuits.

Week 11

Capacitance: capacitance

calculation, series and parallel connection of

capacitance

Week 4

Techniques of Circuit Analysis: Kirchhoff’s Laws, Nodal Analysis, loop analysis

Week 12

Inductance: Self and Mutual Inductances,

calculation of inductances,

series and parallel connection of inductances

Week 5

Techniques of Circuit Analysis: Dependant

Sources analysis; (Nodal and loop analysis) Week 13

First-Order RC Circuits

response: Natural and Step Responses

Week 6

Techniques of Circuit Analysis: Source

transformation, Superposition Week 14

First-Order RL Circuits


Week 7

Midterm Review

Week 15

Second order RLC circuit


Week 8 Midterm Exam

Week 16 Final Exam

Tutorials

Week 1

Circuit Variables: System of Units, Charge,

Voltage, Current, Power and Energy. Week 9

Thevenin’s and Norton’s

Theorems, Maximum

Power Transfer

Week 2

Electrical Circuit Elements: Voltage and

Current Sources, Electrical Resistance and

Ohm’s Law, capacitors and inductors

Week 10

Operational Amplifier and

Multi-terminal Algebraic

Components

Week 3

Simple Resistive Circuits: Ohm’s law,

Resistors in Series and Parallel, Voltage and

Current Divider, Delta-Star transformation, Equivalent Circuits.

Week 11

Capacitance: capacitance

calculation, series and

parallel connection of capacitance

Week 4 Quiz 1

Week 12 Quiz 2

Week 5

Techniques of Circuit Analysis: Dependant

Sources analysis; (Nodal and loop analysis)

Week 13

Inductance: Self and

Mutual Inductances,

calculation of inductances, series and parallel

connection of inductances

First-Order RC Circuits response: Natural and Step

Responses

Week 6 Techniques of Circuit Analysis: Source transformation, Superposition Week 14

First-Order RL Circuits response: Natural and Step

Responses

Week 7 Midterm Review

Week 15 Second order RLC circuit response: Natural and Step

Responses

Week 8 Midterm Exam

Week 16 Final Exam

29

Laboratories

Week 1 Beginning of classes

Week 9

Week 2 Basic measurements

Week 10 Superposition, Thevenin’s

and Norton Theorems

Week 3 DC voltage measurement, DC current

measurement Week 11

Week 4 Ohm’s law application

Week 12 Power in DC circuits

Week 5 DC circuits, Kirchoff’s laws

Week 13 RC circuits

Week 6

Week 14 RL circuits

Week 7

Week 15 RLC circuits

Week 8 Midterm Exam

Week 16 Final Exam

Teaching Methods

Description


• Interactive lectures and communications with students


• Laboratory work

• Practice – problem solving

Assessment Methods

Description (%)






Total 100 %

Learning Outcomes


1. Explain the concepts and parameters associated with: voltage, current, power, energy, resistance, capacitance and

inductance.

2. Explain concepts in the mathematical model used for description of the circuits 3. Apply Kirchhoff's laws, linearity, superposition, in the design and analysis of circuits.

4. Analyze circuits made up of linear lumped elements.

5. Analyze circuits containing resistors and independent sources using techniques such as the node and mesh-current

methods.

6. To transform circuits using Thevenin and Norton equivalent.

7. Analyze AC circuits involving active circuit elements and elementary amplifiers.


Mandatory Literature • Electric Circuits, James W. Nilsson, Susan A. Riedel

Recommended Literature • Basic Engineering Circuit analysis, J. David Irwin, 8th edition, Wiley & Sons, Limited, John,











Total Workload 150


Course Code: MTH 102 Course Name: CALCULUS II



Course Description

Use of calculus is widespread in science, engineering, medicine, business, industry, and many other fields. Calculus also

provides important tools in understanding functions and has led to the development of new areas of mathematics including real and

complex

analysis, topology, and non-Euclidean geometry.

Course Objectives Objectives of this course are to: expand understanding of mathematical topics that may have been previously studied; introduce

and explore topics that possibly have not been part of the student’s mathematical experience; develop an appreciation for the

development of mathematical thought; show the application of mathematics in real life problems and analyzing the results.

Course Content

Week 1: Sequences. Series

Week 2: Convergence Tests. Power Series

Week 3: Taylor and Maclaurin Series Week 4: Parametric Curves

Week 5: Polar Coordinates

Week 6: Areas and Lengths in Polar Coordinates Week 7: Functions of Several Variables


Week 9: Partial Derivatives Week 10: Directional Derivative and the Gradient Vector

Week 11: Maximum and Minimum Values

Week 12: Lagrange Multipliers.

Week 13: Double Integrals

Week 14: Triple Integrals.

Week 15: Change of Variables in Multiple Integrals Week 16: FINAL EXAM

Week 1: Lab 1: Sequences. Series

Week 2: Lab 2: Convergence Tests. Power Series Week 3: Lab 3: Taylor and Maclaurin Series

Week 4: Lab 4: Parametric Curves

Week 5: Lab 5: Polar Coordinates Week 6: Lab 6: Areas and Lengths in Polar Coordinates

Week 7: Lab 7: Functions of Several Variables

Week 8: MIDTERM EXAM Week 9: Lab 8: Partial Derivatives

Week 10: Lab 9: Directional Derivative and the Gradient Vector

Week 11: Lab 10: Maximum and Minimum Values Week 12: Lab 11: Lagrange Multipliers.

Week 13: Lab 12: Double Integrals

Week 14: Lab 13: Triple Integrals Week 15: Lab 14: Change of Variables in Multiple Integrals

Week 16: FINAL EXAM

Teaching Methods

Description



Assessment Methods

Description (%)






Total 100 %

Learning Outcomes


6. Examine and determine convergence of series and sequences.

7. Use two and three dimensional Cartesian coordinate system. Use polar coordinates. 8. Work with multivariable functions, find their derivatives and integrals

9. Find partial derivatives using the properties of differentiable multivariable functions and basic rules



Mandatory Literature Essential Calculus, Early Transcendentals, 2nd edition by James Stewart

Recommended Literature Thomas's Calculus, 11th Edition, George B. Thomas

Calculus a Complete Course, 6th Edition, Robert A. Adams











Total Workload 155


Course Code: PHY 102 Course Name: GENERAL PHYSICS II



Course Description

This course is the second semester of a calculus-based physics course primarily intended for engineering students.

Emphasizes how to relate physical principles to mathematical techniques in problem solving. The course covers fluids,

including the first and second low of thermodynamics, optical systems and introduction to nuclear physics. The laboratory presents exercises that are designed to reinforce the concepts presented and discussed during the lectures.

Course Objectives Objective of the course is to give understanding the basic concepts of fluids, optics, atomic, and nuclear physics to the practical use in engineering.

Course Content

(weekly plan)

Week 1 Introduction to course Week 9 General optics, Images

Week 2 Fluids, Pressure and its measurement,

Pascal's principle Week 10

Wave optics, Interference and Diffraction

Week 3

Temperature and heat, Definition of temperature

Thermal expansion

Week 11

Applied optics

Week 4 Test 1, Specific heat, Heat transfer Week 12 Relativity

Week 5 First low of Thermodynamics Week 13 Photons and Matter Waves

Week 6 Heat applications, Second low of Thermodynamics, Entropy

Week 14 Nuclear Physics

Week 7 Thermal behaviour of gasses Week 15 Preparation for the Final exam

Week 8 Midterm Exam Week 16 Final Exam

Week 1 Beginning of classes Week 9 Tutorial 7: General optics, Images

Week 2 Tutorial 1: Fluids, Pressure and its

measurement, Pascal's principle Week 10

Tutorial 8: Wave optics, Interference and

Diffraction

Week 3

Tutorial 2: Temperature and heat, Definition of temperature

Thermal expansion

Week 11

Tutorial 9: Applied optics

Week 4 Tutorial 3: Specific heat, Heat transfer Week 12 Tutorial 10: Relativity

Week 5 Tutorial 4: First low of Thermodynamics Week 13 Tutorial 11: Photons and Matter Waves

Week 6 Tutorial 5: Heat applications, Second low of Thermodynamics, Entropy

Week 14 Tutorial 12: Nuclear Physics

Week 7 Tutorial 6: Thermal behaviour of gasses Week 15 Tutorial 13: Preparation for the Final exam


Teaching Methods

Description


• Lectures

• Recitation

• Experiments

• Presentations

Assessment Methods

Description (%)






Total 100 %

Learning Outcomes



1. Define phenomena, concepts and terminology of fluids, optics, atomic, and nuclear physics.

2. Gain experience in problem-solving in the field of fluids, optics, atomic, and nuclear physics.

3. Develop capabilities to present a topic in the field of fluids, optics, atomic, and nuclear physics.

4. Apply knowledge obtained to an engineering field.

5. Develop interpersonal and listening skills.


Mandatory Literature • Halliday, David, Robert Resnick, and Jearl Walker. Fundamentals of physics extended. John Wiley & Sons, 2013

(10th edition)

Recommended Literature • D.C. Giancoli: Physics for scientist and engineers, Prentice Hall, New Jersey, 2000

• The other sources from program fields. It is possible to use all books and Collection of problems on university level.



32









Total Workload 154


Course Code: CEN 112 Course Name: PROGRAMMING II



Course Description

The course fully covers the intermediate and advanced topics of programming in the “C/C++” programming. This course

provides students with a comprehensive study of the C/C++ programming language. Classroom lectures stress the strengths of C/C++,

which provide programmers with the means of writing efficient, maintainable, and portable code.

Course Objectives

Objectives of this course are to: introduce students to intermediate and advanced concept of programming; be able in principle to

program in an imperative (or procedural) programming language; learn good working practices: self-motivation, good time

management, making use of information sources, thinking and acting rationally, learning how to learn, and learning how to behave

and get the best from the adult environment of lecture room, laboratory and community of academics; increase the ability to learn

new programming languages; become effective problem solver.

Course Content

Week 1: Basics of C/C++. Flow Control.

Week 2: Expressions and Operators. Functions Week 3: The C Preprocessor. Arrays.

Week 4: Pointers. Local Memory.

Week 5: Reference Parameters. Heap Memory Week 6: Arrays and Pointers. Strings

Week 7: Recursion


Week 9: More on Pointers (1)

Week 10: 2D Arrays.

Week 11: More on Pointers (2) Week 12: Structures (1)

Week 13: Structures (2)

Week 14: Linked Lists (1) Week 15: Linked Lists (2)

Week 16: FINAL EXAM

Week 1: Lab 1: Basics of C/C++. Flow Control. Week 2: Lab 2: Expressions and Operators. Functions

Week 3: Lab 3: The C Preprocessor. Arrays.

Week 4: Lab 4: Pointers. Local Memory. Week 5: Lab 5: Reference Parameters. Heap Memory

Week 6: Lab 6: Arrays and Pointers. Strings

Week 7: Lab 7: Recursion Week 8: MIDTERM EXAM

Week 9: Lab 8: More on Pointers (1)

Week 10: Lab 9: 2D Arrays. Week 11: Lab 10: More on Pointers (2)

Week 12: Lab 11: Structures (1)

Week 13: Lab 12: Structures (2) Week 14: Lab 13: Linked Lists (1)

Week 15: Lab 14: Linked Lists (2)

Week 16: FINAL EXAM

Teaching Methods

Description



Assessment Methods

Description (%)






Total 100 %

Learning Outcomes

After completion of this course, students should be able to: 10. Create algorithms to solve intermediate and advanced programming problems.

11. Analyze, design, implement, test and debug programs that using advanced topics.

12. Understand and use current research and developments in the area of programming languages. 13. Examine the dynamics of memory by the use of pointers.

14. Use different data structures and create/update basic data files.

Prerequisite Course(s) Programming I


Mandatory Literature

• Kernighan & Ritchie, The C Programming Language

• Stephen Prata, “C Primer Plus”, 6th ed., 2013

• Deitel, “C How To Program 6th”, 6th ed., 2010











34


Total Workload 155


Course Code: EEE 106 Course Name: FUNDAMENTALS OF ELECTRICAL ENGINEERING



Course Description

Introduction to fundamental concepts and applications of electrical engineering. The course begins with a discussion of

electricity. The concept of charge is introduced, and the properties of electrical forces are compared with those of other familiar forces, such as gravitation. Coulomb's Law, along with the principle of superposition, allows for the calculation of

electrostatic forces from a given charge distribution. Basic calculation related to electrical field and Gauss Low will be

explained. Circuits and Magnetisms will be presented during the class.

Course Objectives • To understanding basic laws, principles and phenomena in the area of electrical engineering,

• To provide theoretical and practical preparation enabling students to apply the acquired knowledge and skills in

professional and specialist courses.

Course Content

(weekly plan)

Week 1: Introduction to course topics

Week 2: Introduction to electricity, electrical charges Week 3: Electric field and Gauss low

Week 4: Electric Potential and Electric Energy

Week 5: Test 1 Week 6: Electric Potential and Electric Potential Energy.

Week 7: Capacitors and Preparation for the midterm exam

Week 8: Midterm Exam Week 9: Circuit and Magnetism, Basic magnetic values and phenomena

Week 10: Magnetic Field, Magnetic field intensity and flux

Week 11: Magnetic field and magnetic force Week 12: Test 2

Week 13: Lenz's and Faraday's Laws

Week 14: Electromagnetic induction Week 15: Preparation for the final exam

Week 16: Final Exam

Week 1: Beginning of classes

Week 2: Tutorial 1: Introduction to electricity, electrical charges

Week 3: Tutorial 2: Electric field and Gauss low Week 4: Tutorial 3: Electric Potential and Electric Energy

Week 5: Tutorial 4: Solving problems from Test 1

Week 6: Tutorial 5: Electric Potential and Electric Potential Energy. Week 7: Tutorial 6: Capacitors and Preparation for the midterm exam

Week 8: Midterm Exam Week 9: Tutorial 7: Solving problems from Midterm exam and Circuit and Magnetism, Basic magnetic values and

phenomena

Week 10: Tutorial 8: Magnetic Field, Magnetic field intensity and flux

Week 11: Tutorial 9: Magnetic field and magnetic force

Week 12: Tutorial 10: Solving problems from Test 2

Week 13: Tutorial 11: Lenz's and Faraday's Laws Week 14: Tutorial 12: Electromagnetic induction

Week 15: Tutorial 13: Preparation for the final exam

Week 16: Final Exam

Teaching Methods

Description


• Lectures

• Recitation

• Experiments

• Presentations

Assessment Methods

Description (%)






Total 100 %

Learning Outcomes



6. define basic terms, values and laws in the area of electrostatics,

7. define basic terms, values and laws in the field of electromagnetism,

8. describe methods of implementing electrostatic and electromagnetic laws and phenomena in electric devices and

machines design,

9. recommend configuration of simple circuit/assembly for the set magnetic and electrical circuit parameters,

10. select engineering approach to problem solving based on the acquired physics and mathematical knowledge


Mandatory Literature •

Recommended Literature •




36








Total Workload 109


37

Course Code: BOS 102 Course Title: BOSNIAN/CROATIAN/SERBIAN LANGUAGE II


Status: Elective Hours/Week: 2 Total Hours: 30

Course Coordinator: Izudin Tatarević

COURSE DESCRIPTION The Bosnian course adopts a multi-level methodology that integrates the skills of

reading, writing, listening, grammar, vocabulary and conversation. These skills are

reinforced at all levels and Bosnian is the only teaching language used in the class,

except when it is necessary to facilitate the explanation of a grammar rule or lexical

phrase to a beginner.

COURSE OBJECTIVES The Bosnian Course seeks to develop in the students the basic linguistic skills, analytical

skills, and cultural and literary knowledge which will enable them to appreciate the

uniqueness of other cultures and to function in Bosnian speaking communities around

the world.

COURSE CONTENTS 1. Three ways of forming present tense in Bosnian language and recognizing what

way will be used with what verb; making simple sentences with verb in present

tense

2. Collocations to express doubt, uncertainty or ignorance about something

3. Collocations to ask about the way and where to find something; adverbs left,

right, straight, back; Genitive and some of its use (with prepositions iz, od, do)

4. Collocations about the Post office and Bank; Accusative and some of its use

(object in sentence, with prepositions za, na)

5. Collocations about the weather; formal/informal communications; present tense

of verb to have

6. Conversation in restaurant; meeting with Bosnian meals and names for

different kind of food (fruit, vegetable, meat, other); present tense of verb to

have

7. Present tense and use of verbs to buy, to sit, to tell; future tense compared with

present tense

8. Conversation in clothing store; clothes and words related to it (colors, size...);

imperative

9. Comparison of adjectives, phonetic rule jotovanje

10. Conversation about health and parts of body (with four-way cross-words)

TEACHING/ASSESSMENT

Description

Teaching Methods Interactive lectures, Discussions and group

work, Project, Presentations

Description (%)

Student Assessment

Methods

Attendance

Midterm Examination

Final Examination

30%

30%

40%

Learning outcomes Students should be able to:

- Understand Bosnian language

- Communicate in basic Bosnian language

- Appreciate and know a little about Bosnian culture

Language of Instruction Bosnian, English, German

Textbook(s) - Bosanki jezik kao strani jezik, Zenaida Karavdić, Sarajevo 2011. - Bosanski jezik, Priručnik za strance, Minela Kerla, Nermina Alihodžić-

Usejnovski, Sarajevo 2013. - Hrvatski za početnike 1, Udžbenik hrvatskog kao drugog stranog jezika,

Zagreb 2006.

38











Total Workload 50


39

Course Code : TDE 102 Course Name: TURKISH LANGUAGE II

Level : Undergraduate Year : 1 Semester : II ECTS Credits : 3

Status :Elective Hours/Week: 2 Total Hours : 30

Course Description Öğrenciler, Türk dili ve kültürü hakkında bilgi sahibi olur. Dili basit seviyede konuşur, yazar ve okur.

Öğrencilerde Türk diline ve kültüre karşı bir düşümce meydana gelir.

Course Objectives Türkçeyi doğru telaffuz ederek öğrenme; öğrenilen kelimeleri, dil bilgisi kurallarını sözlü iletişimde etkili bir şekilde

kullanabilme; öğrencinin ana dili konuşucuları ile etkili bir iletişime geçebilmesi için gerek duyduğu becerileri kazandırma

Course Content

(weekly plan)

• Etkinlikler; görülen geçmiş zaman öğretimi

• Portreler ve Fiziki Özellikler; görülen geçmiş zaman öğretimi

• İklim; pekiştirme sıfatları, ikilemeler

• Mekânlar; pekiştirme sıfatları, ikilemeler

• Ulaşım; geniş zaman öğretimi

• Spor; geniş zaman öğretimi

• Hayvanlar; geniş zaman öğretimi

• Kişilik Özellikleri; soru zarfları

• Özel Günler; gereklilik kipinin öğretimi

• Müzik; gereklilik kipinin öğretimi

• Problemler

• Ülke Tanıtımı

• Konuların Tekrar Edilmesi

Teaching Methods

Description





Assessment Methods

Description (%)






Total 100 %

Learning Outcomes



skills:

1. Türkçe yazma, konuşma ve okuma becerisini kazanır.

2. Kendini Türkçe tanıtır. Ailesinden Türkçe bahsedebilir

3. Eşyaların Türkçe karşılığını söyleyebilir.Dersler, günler ve ay isimlerini öğrenir.

4. Meslekler hakkında bilgi sahibi olur ve Türkçe meslek isimlerini bilir.

5. Pazar alışverişinde kullanılan terimlerin Türkçe karşılığını bilir. Yiyecek ve içeceklerin Türkçelerini bilir.

6. Orta seviyede Türkçe cümleler kurabilir.

7. Türkçe olarak adres tarifi vs. yapabilir.

8. Orta düzeyde kendini ifade edebilir ve iletişim kurabilecek düzeye gelir.


(if any) Turkish language I

Language of Instruction Türkçe


• Lale Türkçe Kitabı Cilt 2

• Lale Türkçe Çalışma Kitabı 2

Recommended Literature Yeni Hitit, Yabancılara Türkçe Ders kitabı 2 (B1), Ankara Üniversitesi-Tömer, 3.baskı, 1984.







40





Total Workload 57


Course Code : GRM 102 Course Name: GERMAN LANGUAGE II

Level : Undergraduate Year : 1 Semester : II ECTS Credits : 3

Status :Compulsory Hours/Week: 2 Total Hours : 30

Course Description

This is a continuation of German Language I course. Interactive communication; grammatical structures and vocabulary

commonly used in newspapers, magazines, extended dialogues, readings texts, and short stories; information about the

culture of the German language through authentic materials.

Course Objectives

This course emphasizes the use of the German language for active communication. It has the following objectives:

• the comprehension of formal and informal spoken language;

• the acquisition of vocabulary and a grasp of language structure to allow for the accurate reading of newspaper

and magazine articles as well as modern literature;

• the ability to compose expository passages;

• the ability to express ideas orally with accuracy and fluency. Students will also learn valuable test-taking

strategies and self-evaluative skills.

Course Content

(weekly plan)

• Lektion 8 – Beruf und Arbeit

• Grammatik – modale Praposition als; Prateritum; Wortbildung Nomen

• Lektion 9 – Amter und Behorden

• Grammatik – Modalverben; Satzklammer; Pronomen; Imperativ

• Lektion 10 – Gesundheit und Krankheit

• Grammatik – Possessivartikel; Modalverb; Satzklammer

• Lektion 11 – In der Stadt unterwegs

• Midterm exam

• Grammatik – Preposition mit, an, auf, bei, hinter, in, neben, uber, unter, vor, zwischen, zu, nach, in

• Lektion 12 – Kundenservice

• Grammatik – Verben mit verschiedenen Prafixen; temporale Prapositionen vor, nach, bein, in

• Lektion 13 – Neue Kleider

• Grammatik – Demonstrativpronomen; Frageartikel welch-; Verben mit Dativ

• Lektion 14 – Feste

• Grammatik – Ordinalzahlen; Personalpronomen im Akkusativ

• Final exam

Teaching Methods

Description





Assessment Methods

Description (%)






Total 100 %

Learning Outcomes



skills:

1. Demonstrate the confidence and listening/speaking skills necessary to participate successfully in spontaneous

aural/oral exchanges with native speakers of those particular languages.

2. Demonstrate reading comprehension of foreign language texts intended for developmental (or higher level)

foreign language courses.

3. Respond appropriately to written or spoken foreign language by writing paragraphs or short essays that

communicate ideas clearly.


(if any) German language I


Mandatory Literature • Schritte plus 2 Audio-CD zumArbeitsbuchmitinteraktivenÜbungen, Monika Bovermann, Daniela Niebisch,

Franz Specht, Sylvette Penning-Hiemstra

Recommended Literature • Swick, Edward. The Everything Learning German Book: Speak, Write and Understand Basic German in No

Time, Adams Media; 1st edition, 2003.




42








Total Workload 50


Course Code: EEE 201 Course Name: CIRCUIT THEORY II

Level: Undergraduate Year: II Semester: III ECTS Credits: 6

Status: Mandatory Hours/Week : 3+3 Total Hours: 45+45

Course Description

The course has been designed to introduce fundamental principles of circuit theory commonly used in engineering research

and science applications. Techniques and principles of electrical circuit analysis including second order circuits, sinusoids

and

phasors, single phase power, three phase power circuit analysis, frequency response analysis, resonance, laplace (transient

and steady state analysis), inverse laplace.

Course Objectives

The basic objective of this course is to introduce students to the fundamental theory and mathematics for the analysis of

Alternating Current (AC) electrical circuits, frequency response and transfer function of circuits. Course goals are: 1. To develop an understanding of the fundamental laws and elements of electric circuits,

3. To be able to analyse the electrical circuits and learn the time domain analysis methods,

3. To know, understand, and apply time and frequency domain analysis.

Course Content

(weekly plan)

Week 1 Sinusoidal steady-state analysis Week 9 The Laplace Transform in Circuit Analysis

Week 2 Kirchhoff’s Low in frequency domain

Week 10 Inverse transform techniques, Theorems for

Laplace transforms

Week 3 Complex Impedance, Thevenin and Norton Equivalent Circuits

Week 11 Frequency Selective Circuits

Week 4 Sinusoidal steady-state power calculations Week 12 High pass filters, Low pass filters

Week 5 Three Phase Systems Week 13 Active filter circuits

Week 6 Analysis of the Wye-Wye Circuit, Analysis of the Wye-Delta Circuit

Week 14 Two-port Circuits

Week 7 Introduction to Laplace transform Week 15 Final exam preparation


Tutorials

Week 1 Sinusoidal steady-state analysis Week 9 The Laplace Transform in Circuit Analysis

Week 2 Kirchhoff’s Low in frequency domain

Week 10 Inverse transform techniques, Theorems for

Laplace transforms

Week 3 Complex Impedance, Thevenin and Norton Equivalent Circuits

Week 11 Frequency Selective Circuits

Week 4 Quiz 1 Week 12 Quiz 2

Week 5 Sinusoidal steady-state power calculations, Three phase systems

Week 13 High pass filters, Low pass filters

Week 6 Analysis of the Wye-Wye Circuit,

Analysis of the Wye-Delta Circuit Week 14

Two-port Circuits

Week 7 Introduction to Laplace transform Week 15 Final exam preparation


Laboratories

Week 1 Beginning of classes Week 9 Introduction to MATLAB, Simulink

Week 2 Introduction to MATLAB Week 10 Modelling of the circuits in the Simulink

Week 3 AC circuits Week 11 Solving problems in MATLAB

Week 4 AC RLC circuit Week 12 Solving problems in MATLAB

Week 5 Introduction to MATLAB, Plotting,

Functions Week 13

Series resonant circuit

Week 6 Power in AC circuit Week 14 Parallel resonant circuit

Week 7 Introduction to MATLAB, Branching

statements Week 15


Teaching Methods

Description Interactive lectures and communication with students Discussions and group work

Laboratory work Practice – problem solving

Assessment Methods

Description (%)





44


Total 100 %

Learning Outcomes


1. To analyse single-phase sinusoidal circuits,

2. To calculate the average and complex power in single-phase sinusoidal circuits,

3. To analyse balanced three-phase circuits applying single-phase equivalent circuits,

4. To find functional and operation Laplace transform of different functions,

5. To understand core system-theory concepts and constructs such as the transfer function, frequency response, and

impulse response;

6. To obtain response of various types of passive filter circuits

7. To understand two -port network analysis and frequency -selective operational amplifier circuits

Instruction Language English Prerequisite courses Electrical Circuit I, Calculus I

Mandatory Literature Electric Circuits, James W. Nilsson, Susan A. Riedel

Recommended Literature Basic Engineering Circuit analysis, J. David Irwin, 8th edition, Wiley & Sons, Limited, John,










Lab/Practical exam 8 8

Total Workload 150


Course Code: EEE 205 Course Name: SEMICONDUCTOR DEVICES AND MODELING



Course Description Semiconductor physics. p-n junction devices. Tunnel diode. Impact avalanche transit-time. Junction transistor. Metal-

semiconductor devices. Metal-insulator-semiconductor devices. Surface field effect. Optoelectronic devices. Semiconductor

lasers. Epitaxial process. Diffusion. Oxidation. Ion implantation. Metalization. Integrated circuit fabrication.

Course Objectives The main object is to understand the application of the semiconducting materials; and to gain more information about

techniques of their preparations and measurements and interpretation of the results.

Course Content

(weekly plan)

Week 1: Introduction

Week 2: Physics and Properties of Semiconductors: crystal structure, energy bands, statistics, Fermi level, carrier

concentration at thermal equilibrium

Week 3: Carrier transport phenomena, Hall effect, recombination Week 4: Optical and thermal properties, basic properties for semiconductor operation.

Week 5: Device Processing Technology: oxidation, diffusion, ion-implantation, deposition

Week 6: Lithography, etching and interconnect Week 7: Midterm Review

Week 8: Midterm Exam Week 9: Postmidterm Review Week 10: p-n Junction: depletion region, diffusion, generation-recombination, current-voltage characteristics

Week 11: Junction breakdown, charge storage and transient behavior.

Week 12: Bipolar transistor: transistor action and dependence on device structure, charge control switching model Week 13: Ebers-Moll Model, current-voltage characteristics, non-ideal and limiting effects at extremes of bias.

Week 14: State-of-the-Art Bipolar Transistor Technology: poly-si emitters, narrow base, structural tradeoffs in optimizing

performance. Week 15: Final Review

Week 16: Final Exam


Week 2: Tutorial 1: Physics and Properties of Semiconductors: crystal structure, energy bands, statistics, Fermi level, carrier

concentration at thermal equilibrium Week 3: Tutorial 2: Carrier transport phenomena, Hall effect, recombination

Week 4: Tutorial 3: Optical and thermal properties, basic properties for semiconductor operation.

Week 5: Tutorial 4: Device Processing Technology: oxidation, diffusion, ion-implantation, deposition Week 6: Tutorial 5: Lithography, etching and interconnect

Week 7: Tutorial 6: Midterm Review

Week 8: Midterm Exam Week 9: Tutorial 7: Postmidterm Review

Week 10: Tutorial8: p-n Junction: depletion region, diffusion, generation-recombination, current-voltage characteristics

Week 11: Tutorial 9:Junction breakdown, charge storage and transient behavior.

Week 12: Tutorial 10: Bipolar transistor: transistor action and dependence on device structure, charge control switching

model Week 13: Tutorial 11: Ebers-Moll Model, current-voltage characteristics, non-ideal and limiting effects at extremes of bias.

Week 14: Tutorial 12: State-of-the-Art Bipolar Transistor Technology: poly-si emitters, narrow base, structural tradeoffs in

optimizing performance. Lab5: Transistor characteristics

Week 15: Tutorial 13: Final Review

Week 16: Final Exam


Week 2: Week 3:

Week 4: Lab 1: Diode characteristics

Week 5: Lab 2: Diode characteristics - MultiSIM Week 6: Lab 3: LED diode characteristics

Week 7: Lab 4: LED diode characteristics - MultiSIM

Week 8: Midterm Exam Week 9: Lab 5: Zenner diode characteristics

Week 10: Lab 6: Zenner diode characteristics - MultiSIM

Week 11: Lab 7: Rectifiers and Filters Week 12: Lab 8: Rectifiers and Filters - MultiSIM

Week 13: Lab 9: Transistor characteristics

Week 14: Lab 10: Transistor characteristics – MultiSIM Week 15:

Week 16: Final Exam

Teaching Methods

Description • Interactive lectures and communications with students • Tutorials

Assessment Methods

Description (%)






Total 100 %

46

Learning Outcomes


1. Explain and apply the semiconductor concepts of drift, diffusion, donors and acceptors, majority and minority

carriers, excess carriers, low level injection, minority carrier lifetime, quasi-neutrality, and quasi-statics; 2. Explain the underlying physics and principles of operation of p-n junction diodes, bipolar junction transistors

(BJTs), and describe and apply simple large signal circuit models for these devices which include charge storage

elements; 3. Explain how devices and integrated circuits are fabricated and describe discuss modern trends in the

microelectronics industry;

4. Explain, compare, and contrast the input, output, and gain characteristics of single-transistor 5. Determine the frequency range of simple electronic circuits and understand the high frequency limitations of

BJTs

6. Understand the limitations of the various device models, identify the appropriate model for a given problem or situation, and justify the selection; and

7. Design simple devices and circuits to meet stated operating specifications.


Mandatory Literature Robert L. Boylestad and Louis Nashelsky, “Electronic Devices and Circuit Theory,” 11th Edition, Pearson

Recommended Literature • P. Biljanović: Elektronički sklopovi, Školska knjiga, Zagreb, 1989.

• Dragoljub Milatović: Elektronski sklopovi, Svjetlost Sarajevo, 1986.











Total Workload 119


Course Code: MTH 201

Course Name: DIFFERENTIAL EQUATIONS



Course Description Differential Equations: First-order differential equations, second-order linear equations, change of parameters, homogeneous and non-homogeneous equations, series solutions, Laplace transform, systems of first-order linear equations, boundary value

problems.

Course Objectives

Objectives of this course are to: introduce students to the topics of the course through symbolic,numeric, and graphic methods; substantially strengthen students’ problem solving skills by requiring them to analyze problems and form

mathematical models for these problems; encourage strive for excellence by introducing them to a competitive environment

where part of their performance will be based on performance of their peers.

Course Content

Week 1: Introduction. Types of differential equations (DE).

Week 2: First order Ordinary Differential Equations: Separable and homogeneous linear DE.

Week 3: First order ODEs: Exact DEs

Week 4: First order ODEs: Solution by integrating factor Week 5: First order ODEs: Linear DE

Week 6: Second order linear ODE: Introduction. Some

definitions. Week 7: Linear independence. Boundary and initial value

problems

Week 8: MIDTERM EXAM Week 9: Higher Order Linear DEs

Week 10: Definition of the Laplace Transform. Step

Functions. Week 11: DEs with Discontinuous Forcing Functions

Week 12: Impulse Functions. Convolution Integral

Week 13: Systems of DEs Week 14: Systems of DEs. Complex Eigenvalues

Week 15: Systems of DEs. Repeated Eigenvalues

Week 16: FINAL EXAM

Week 1: Lab 1: Introduction. Types of differential equations

Week 2: Lab 2: First order Ordinary Differential Equations:

Separable and homogeneous linear DE. Week 3: Lab 3: First order ODEs: Exact DE

Week 4: Lab 4: First order ODEs: Solution by integrating

factor Week 5: Lab 5: First order ODEs: Linear DE

Week 6: Lab 6: Second order linear ODE: Introduction. Some

definitions. Week 7: Lab 7: Linear independence. Boundary and initial

value problems

Week 8: MIDTERM EXAM Week 9: Lab 8: Higher Order Linear DEs

Week 10: Lab 9: Definition of the Laplace Transform. Step

Functions. Week 11: Lab 10: DEs with Discontinuous Forcing Functions

Week 12: Lab 11: Impulse Functions. Convolution Integral

Week 13: Lab 12: Systems of DEs Week 14: Lab 13: Systems of DEs. Complex Eigenvalues

Week 15: Lab 14: Systems of DEs. Repeated Eigenvalues

Week 16: FINAL EXAM

Teaching Methods

Description



Assessment Methods

Description (%)






Total 100 %

Learning Outcomes

Upon completion of this course, the student should be able to: • classify differential equations by order, linearity, and homogeneity

• solve first order linear differential equations

• solve linear equations with constant coefficients • use separation of variables to solve differential equations

• solve exact differential equations

• use variation of parameters to solve differential equations • use the method of undetermined coefficients to solve differential equations

• determine whether a system of functions is linearly independent using the Wronksian

• model real-life applications using differential equations • use Laplace transforms and their inverses to solve differential equations

• solve systems of linear differential equations using matrix techniques and eigenvalues



Mandatory Literature W. E. Boyce and R. C. DiPrima, “Elementary Differential Equations and Boundary Value Problems”


Shepley L. Rose, “Differential Equations,” John Wiley & Son, Ltd.

C. Ray Wylie, “Differential Calculus,” Mc Graw Hill, 1979.







48





Total Workload 124


Course Code: EEE 395 Course Name: DIGITAL DESIGN



Course Description Boolean algebra, number systems, data representation, logic theorems, canonical forms, simplification techniques, logic

gates, design of combinational circuits, timing and timing problems, sequential circuits, design of sequential circuits and the

algorithmic state machine, programmable logic devices, register operations, basic computer organization and design.

Course Objectives

Objective of this course is to give students:

Understanding of digital logic at the gate and switch level including both combinational and sequential logic elements;

Understanding of the clocking methodologies necessary to manage the flow of information and preservation of circuit state.;

Appreciation for the specification methods used in designing digital logic and the basics of the compilation process that

transforms the specifications into logic networks.

Course Content

(weekly plan)

Week 1: Course overview/ Digital Systems and Binary Numbers

Week 2: Boolean Algebra and Logic Gates

Week 3: Boolean Algebra and Logic Gates

Week 4: Quiz Week 5: Gate Level Minimization

Week 6: Combinational Logic

Week 7: Combinational Logic Week 8: Midterm Exam Week 9: Synchronous Sequential Logic

Week 10: Synchronous Sequential Logic Week 11: Registers and Counters

Week 12: Registers and Counters

Week 13: Memory and Programmable Logic Week 14: Memory and Programmable Logic

Week 15: Design at the Register Level

Week 16: Final Exam


Week 2: Tutorial 1: Binary numbers Week 3: Tutorial 2: Boolean Algebra and Logic Gates

Week 4: Tutorial 3: Solving problems from Quiz

Week 5: Tutorial 4: Gate Level Minimization Week 6: Tutorial 5: Combinational Logic

Week 7: Tutorial 6: Combinational Logic

Week 8: Midterm Exam Week 9: Tutorial 7: Solving problems from Midterm exam

Week 10: Tutorial 8: Synchronous Sequential Logic Week 11: Tutorial 9: Registers and Counters

Week 12: Tutorial 10: Registers and Counters

Week 13: Tutorial 11: Memory and Programmable Logic Week 14: Tutorial 12: Memory and Programmable Logic

Week 15: Tutorial 13: Design at the Register Level

Week 16: Final Exam


Week 2: Lab 1: Introductory lab (getting familiar with devices and equipment) Week 3: Lab 2: Introduction to Quartus

Week 4: Lab 3: Comparator

Week 5: Lab 4: Comparator - Quartus Week 6: Lab 5: Adders and Subtractors

Week 7: Lab 6: Adders and Subtractors - Quartus

Week 8: Midterm Exam Week 9: Lab 7: Encoder and Decoder - Quartus

Week 10: Lab 8: Multiplexers and Demultiplexer

Week 11: Lab 9: Multiplexers and Demultiplexer - Quartus Week 12: Lab 10: Flip - Flops

Week 13: Lab 11: Flip – Flops - Quartus

Week 14: Lab 12: Counters Week 15: Lab 13: Counters - Quartus

Week 16: Final Exam

Teaching Methods

Description

• Interactive lectures and communications with students

• Tutorials • Labs

Assessment Methods

Description (%)






Total 100 %

50

Learning Outcomes



1. Describe the digital logic at the gate and switch level including both combinational and sequential logic elements. 2. Describe the clocking methodologies necessary to manage the flow of information and preservation of circuit state.

3. Define methods used in designing digital logic and apply them.

4. Acquire and demonstrate competency in technical skills applicable to digital design. 5. Analyze, synthesize, and develop probable solutions.


Mandatory Literature • M. Moris Mano and Charles R. Kime, Digital Design With An Introduction To a Verylog, Fifth Edition, Pearson,

2013.












Total Workload 125


Course Code : EEE 314 Course Name: ELECTRICAL MEASUREMENT AND INSTRUMENTATION

Level : Undergraduate Year : II Semester : III ECTS Credits : 5

Status : Mandatory Hours/Week: 2+2 Total Hours: 30+30

Course Description Units and principles of measurement. Error of measurement. Probability of error. Electronic measurements and electronic measuring instruments: Instrument amplifiers, signal sources, oscilloscopes, digital frequency meters, digital voltmeters. High

frequency and microwave measurement techniques.

Course Objectives

This course aims to: 1) Explain basic concepts and definitions in measurement.

2) Explain the operation and design of electronic instruments for parameter measurement

3) Explain the operation of oscilloscopes and the basic circuit blocks in the design of an oscilloscope. 4) Explain the circuitry and design of various function generators.

5) Explain the techniques used in signal analysis in time domain and frequency domain.

6) Explain the operation and design of counters. 7) Compare different ADC and DAC techniques and explain various circuits for conversion.

8) Explain the transmission line effects pertaining to linear and non-linear loads in the context of bounce diagrams.

Course Content

(weekly plan)


Week 2: Basic Concepts in Measurement

Week 3: Electronic Instruments for Parameter Measurement: AC/DC voltmeters, multimeters, digital voltmeter, component measurement, Q-meter, vector impedance meter

Week 4: Oscilloscopes: CRT’s, deflection systems, probes

Week 5: Function Generators: sine-wave generators, frequency synthesis, pulse generators

Week 6: Signal Analysis: Wave analysis, harmonic distortion analyzer, spectrum analyzer

Week 7: Midterm review

Week 8: Midterm exam

Week 9: Postmidterm review

Week 10: Counters

Week 11: A/D and D/A Conversion

Week 12: Measurement of Transmission Line Effects

Week 13: Bounce diagrams

Week 14: Linear and non-linear loads

Week 15: Final exam review

Week 16: Final exam


Week 2: Lab 1: Basic Concepts in Measurement

Week 3: Lab 2: Electronic Instruments for Parameter Measurement: AC/DC voltmeters, multimeters, digital voltmeter, component measurement, Q-meter, vector impedance meter

Week 4: Lab 3: Oscilloscopes: CRT’s, deflection systems, probes

Week 5: Lab 4: Function Generators: sine-wave generators, frequency synthesis, pulse generators

Week 6: Lab 5: Signal Analysis: Wave analysis, harmonic distortion analyzer, spectrum analyzer

Week 7: Tutorial 1: Midterm review

Week 8: Midterm exam

Week 9: Tutorial 2: Postmidterm review

Week 10: Lab 6: Counters

Week 11: Lab 7: A/D and D/A Conversion

Week 12: Lab 8: Measurement of Transmission Line Effects

Week 13: Lab 9: Bounce diagrams

Week 14: Lab 10: Linear and non-linear loads

Week 15: Tutorial 3: Final exam review

Week 16: Final exam

52

Teaching Methods

Description


1. Interactive

2. Discussions and group works 3. Tutorials and Labs

Assessment Methods

Description (%)






Total 100 %

Learning Outcomes



1. perform measurements in electronics on their own 2. select right equipment for different measurement tasks 3. perform D/A and A/D conversion of signals


(if any)

-


Mandatory Literature • A.D. Helfrick and W.D. Cooper, Modern Electronic Instrumentation and Measurement Techniques, Prentice-Hall, 1990


• D. Buchla and W. McLachen, Applied Electronic Instrumentation and Measurement, Maxwell Macmillan Int.

Publishing Group, 1992

• Alija Muharemović, Električna mjerenja, ETF Sarajevo 2005.

• Alija Muharemović, Irfan Turković, Električna mjerenja, Zbirka zadataka, Sarajevo 1996.











Total Workload 124


Course Code: EEE 202 Course Name: ELECTROMAGNETIC FIELD THEORY

Level: Undergraduate Year: II Semester: IV ECTS Credits: 5


Course Description Vector Analysis. Electrostatic and Magnetostatic forces and fields in vacuum and in material bodies. Energy and potential.

Steady electric current and conductors. Dielectric properties of materials. Boundary conditions for electrostatic and

magnetostatic fields. Poisson's and Laplace's Equations. Magnetic circuits and inductance.

Course Objectives The aim of this course is to learn the fundamentals of static electromagnetic field theory.

Course Content

(weekly plan)


Week 2: Cylindrical and spherical coordinate systems, Grad, Div and Curl

Week 3: Electrical field intensity, Gauss law and Electric potential Week 4: Work and energy in electrostatics and conductors

Week 5: Special techniques

Week 6: Polarization and the field of polarized objects Week 7: The electric displacement and linear dielectrics

Week 8: Midterm Exam Week 9: Magnetostatics Week 10: Magnetic field in matter

Week 11: Magnetic field in matter

Week 12: Electromotive force and electromagnetic induction Week 13: Maxwell’s equations

Week 14: Conservation law

Week 15: Magnetic circuits Week 16: Final Exam


Week 2: Tutorial 1: Cylindrical and spherical coordinate systems, Grad, Div and Curl

Week 3: Tutorial 2: Electrical field intensity, Gauss law and Electric potential Week 4: Tutorial 3: Work and energy in electrostatics and conductors

Week 5: Quiz 1

Week 6: Tutorial 4: Polarization and the field of polarized objects Week 7: Tutorial 5: The electric displacement and linear dielectrics

Week 8: Midterm Exam Week 9: Tutorial 6: Magnetostatics Week 10: Tutorial 7: Magnetic field in matter

Week 11: Tutorial 8: Electromotive force and electromagnetic induction

Week 12: Quiz 2 Week 13: Tutorial 9: Maxwell’s equations

Week 14: Tutorial 10: Conservation law

Week 15: Tutorial 11: Final review Week 16: Final Exam

Teaching Methods


Assessment Methods

Description (%)






Total 100 %

Learning Outcomes


When the students have passed the course, they shall be able to:

- have a good knowledge of vector analysis and be able to use analytical methods for solving field theory problems

- have a good understanding of the theory of electromagnetic fields and Maxwell's equations and be able to apply this to

solve problems

- have knowledge of various applications of electromagnetic theory - be able to solve both theoretical and applied tasks in the field of electromagnetic field theory


Mandatory Literature • Engineering Electromagnetics, W. H. Hayt, Jr., J. A. Buck - Seventh Edition, 2007, McGraw-Hill, ISBN: 007-124449-

2;


• Fundamentals of Engineering Electromagnetics, David K. Cheng - International Edition, Pearson, ISBN: 0-201-60071-

4;

• Ejup Hot i saradnici: Teorija elektromagnetnih polja, ETF Sarajevo 2002.

• Zijad Haznadar, Željko Štih: Elektromagnetizam, Sarajevo 1998.







54





Total Workload 125


Course Code: EEE 206 Course Name: ELECTRONICS I



Course Description

This course aims at providing a next step after semiconductors and basic electronics course, showing the application of

transistor-based circuits, dc and ac analysis of such circuits and providing a general framework for electronic analysis. The

course combines the knowledge students obtained from Signals and Systems, Semiconductors and Electrical Circuits in order to give them a full engineering apparatus for electronics.

Course Objectives After completion of this course the student will have theoretical and practical knowledge about analog electronics, with the

ability to design and analyse analog electronic circuits based on unipolar and bipolar transistors, as well as operational amplifiers. Students are also able to apply this knowledge in building of circuits for signal processing (filtering).

Course Content

(weekly plan)

Week 1 Introduction Week 9 FET frequency response

Week 2 BJT DC analysis Week 10 Operational amplifiers

Week 3 BJT DC analysis Week 11 Op-amp applications

Week 4 FET DC analysis Week 12 Filters

Week 5 BJT AC analysis Week 13 Feedback

Week 6 FET AC analysis Week 14 Oscillators

Week 7 BJT frequency response Week 15 A/D and D/A conversion


Laboratories

Week 1 Beginning of classes Week 9 Post midterm review

Week 2 BJT DC analysis Week 10 FET frequency response

Week 3 BJT DC analysis Week 11 Operational amplifiers

Week 4 FET DC analysis Week 12 Operational amplifiers

Week 5 BJT AC analysis Week 13 Op-amp applications

Week 6 FET AC analysis Week 14 Op-amp applications

Week 7 BJT frequency response Week 15 Preparation for Final exam


Teaching Methods

Description


• Interactive

• Discussions and group works • Tutorials and Labs

Assessment Methods

Description (%)



Project 0% Attendance 0 %



Total 100 %

Learning Outcomes


After this course, the student will be able to:

- analyse fairly complex analog electronical circuits both mathematically, using computer models and laboratory models - design fairly complex analog electronical circuits and test their functionality

- select analog electronical components for various applications according to design requests

- apply the knowledge in practical environment, e.g. sensor interfaces and signal processing


Mandatory Literature • Robert L. Boylestad, Louis Nashelsky, "Electronic Devices and Circuit Theory", Pearson 2013

Recommended Literature • Schaumann, Rolf. Design of analog filters. Oxford University Press, USA, 2001.








56



Total Workload 125


Course Code: EEE 212 Course Name: SIGNALS AND SYSTEMS



Course Description

The course presents and integrates the basic concepts for continuous-time signals and systems. Signal and system

representations are developed for both time and frequency domains. These representations are related through the Fourier

transform and its generalizations, which are explored in detail. Filter design and modulation for analog systems are discussed and illustrated.

Course Objectives The aim of this course is to provide fundamental concepts in signals and systems, as an introduction to analog and digital

signal processing. Signal processing represents a base upon which various engineering systems are build, including communication systems, digital systems, image processing, speech processing, consumer electronics, and data processing.

Course Content

(weekly plan)

Week 1: Introduction to signals and systems

Week 2: Continuous-Time Signals Week 3: Continuous-Time Signals

Week 4: Continuous-Time Systems

Week 5: Continuous-Time Systems Week 6: Direct Laplace Transform

Week 7: Midterm Review

Week 8: Midterm Exam Week 9: Post-midterm Review

Week 10: Inverse Laplace Transform

Week 11: The Fourier Series Week 12: The Fourier Series

Week 13: The Fourier Transform

Week 14: The Fourier Transform Week 15: Final Exam Review

Week 16: Final Exam


Week 2: Tutorial 1: Classification of signals

Week 3: Tutorial 2: Basic signal operations Week 4: Tutorial 3: System (impulse) response

Week 5: Lab 1: Basic plotting of signals - MATLAB

Week 6: Tutorial 4: Laplace Transform Week 7: Tutorial 5: Midterm Review

Week 8: Midterm Exam Week 9: Tutorial 6: Post-midterm Review Week 10: Lab 2: Laplace transform - MATLAB

Week 11: Tutorial 7: Fourier Series

Week 12: Lab 3: Fourier series - MATLAB

Week 13: Tutorial 8: The Fourier Transform

Week 14: Tutorial 9: The Fourier Transform of Some Useful Functions Week 15: Tutorial 10: Properties of Fourier Transform

Week 16: Final Exam

Teaching Methods

Description




Assessment Methods

Description (%)


Homework 0% Term Paper 0 %




Total 100 %

Learning Outcomes


• Describe the most important properties of LTI systems;

• Understand mathematical descriptions and representations of continuous signals and systems;

• Apply same useful operations to the signals, such as shifting, scaling and inversion. This means that student will be

able to manipulate with the signal to obtain a desired form;

• Understand the process of time and frequency convolution of two functions and how convolution affects the bandwidth

of the product of two signals;

• Familiarize with the idea of representing continuous time signals and LTI systems in the frequency domain;

• Understand spectral representation of signals via Fourier Series and Fourier Transform and their properties and

applications;

• Ability to solve differential equations using Fourier transforms;

• Improve the knowledge of mathematics and thus be more prepared for learning and mastering many other courses;


Mandatory Literature Luis F. Chaparro, “Signals and Systems using MATLAB”, Academic Press

Recommended Literature -



58









Total Workload 125


Course Code: MTH 204

Course Name: NUMERICAL ANALYSIS



Course Description

This course covers numerical methods for various types of linear systems of equations (full, triangular, banded), the least squares method for inconsistent systems, nonlinear equations (scalar and system), eigenvalue problem, integration, derivation,

interpolation and initial and boundary value problems for ODE. It introduces students to basic technologies for numerical

methods, such as linearization, discretization and extrapolation, and also to theoretical concepts such as order of accuracy, speed of convergence, complexity, condition and stability.

Course Objectives Objectives of this course are to: introduce students to the topics of the course through symbolic,numeric, and graphic

methods; substantially strengthen students’ problem solving skills by requiring them to analyze problems, and use appropriate technology for solving these problems.

Course Content

Week 1: MATLAB – Basics. Variables and Basic Data Structures

Week 2: Functions. Branching Statements Iteration.

Recursion Week 3: Complexity. Representation of Numbers

Week 4: Errors, Good Programming Practices, and

Debugging. Week 5: Visualization and Plotting

Week 6: Reading and Writing Data

Week 7: Linear algebra and systems of linear equations Week 8: MIDTERM EXAM

Week 9: Least Squares Regression

Week 10: Interpolation Week 11: Series

Week 12: Root Finding

Week 13: Numerical Differentiation Week 14: Numerical Integration

Week 15: Ordinary Differential Equations

Week 16: FINAL EXAM

Week 1: Lab 1: MATLAB – Basics. Variables and Basic Data

Structures Week 2: Lab 2: Functions. Branching Statements Iteration.

Recursion

Week 3: Lab 3: Complexity. Representation of Numbers Week 4: Lab 4: Errors, Good Programming Practices, and

Debugging.

Week 5: Lab 5: Visualization and Plotting order ODEs: Linear DE

Week 6: Lab 6: Reading and Writing Data

Week 7: Lab 7: Linear algebra and systems of linear equations Week 8: MIDTERM EXAM

Week 9: Lab 8: Least Squares Regression

Week 10: Lab 9: Interpolation Week 11: Lab 10: Series

Week 12: Lab 11: Root Finding

Week 13: Lab 12: Numerical Differentiation Week 14: Lab 13: Numerical Integration

Week 15: Lab 14: Ordinary Differential Equations

Week 16: FINAL EXAM

Teaching Methods

Description



Assessment Methods

Description (%)






Total 100 %

Learning Outcomes

Upon completion of this course, the student should be able to: 1. identify different mathematical problems and reformulate them in a way that is appropriate for numerical treatment

2. choose appropriate numerical method for treatment of the given problem

3. explain choice of method by accounting for advantages and limitations 4. choose an algorithm that implies efficient calculations and implement it in MATLAB

5. present the results in a relevant and illustrative way

6. estimate the reliability of the results 7. use functions from MATLAB for efficient calculations and visualisation



Mandatory Literature An Introduction to MATLAB Programming and Numerical Methods for Engineers, by Timmy Siauw and Alexandre M. Bayen

Recommended Literature Laurene V. Fausett, Applied Numerical Analysis Using MATLAB, Second Edition, Pearson, 2008











60

Total Workload 124


Course Code: MTH 205 Course Name: PROBABILITY AND STATISTICS FOR ENGINEERS



Course Description

Probability and Statistics for Engineers: Descriptive statistics. Sets, events, and probability. Random variables, discrete and

continuous distributions. Mathematical expectation and correlation analysis. Discrete probability and popular distributions,

Poisson process. Continuous probability distributions. Introduction to reliability theory and failure. Functions of random variables. Introduction to estimation theory. Simple and multiple regression and correlation, least squares. Statistics of

extreme events. Testing of hypothesis. Engineering application.

Course Objectives

This course introduces students to various aspects of statistical analysis. The objective is to expose the students to elements of probability and probability distributions, and statistical inference. We try to keep a balance between theory and

methodology. The students use differential and integral calculus to investigate different properties of random variables and

their functions. They also learn how to apply statistical analysis to solve real-life problems. Many examples are used to show the applicability of the probability theory and statistical analysis.

Course Content

(weekly plan)


Week 2: Set theory, events, sample space, definition and axioms of probability Week 3: Discrete, continuous and mixed random variables, probability mass functions, probability distribution functions

Week 4: Probability density functions, cumulative distribution functions, mean and variance

Week 5: Families of continuous and discrete random variables Week 6: Pairs of random variables and joint probability functions

Week 7: Random vectors and probability functions associated with them

Week 8: Midterm Exam Week 9: Applications of s and z transform

Week 10: Applications of s and z transform

Week 11: Gaussian probability density Week 12: Central limit theorem

Week 13: Stochastic processes, independent identically distributed random sequences, Poisson process

Week 14: Expected value and correlation, stationary and wide sense stationary processes, ergodicity, Cross correlation, Gaussian processes

Week 15: Markov Chains

Week 16: Final Exam


Week 2: Tutorial 1: Set theory, events, sample space, definition and axioms of probability Week 3: Tutorial 2: Discrete, continuous and mixed random variables, probability mass functions, probability distribution

functions

Week 4: Tutorial 3: Probability density functions, cumulative distribution functions, mean and variance and Quiz 1 Week 5: Tutorial 4: Families of continuous and discrete random variables

Week 6: Tutorial 5: Pairs of random variables and joint probability functions

Week 7: Tutorial 6: Random vectors and probability functions associated with them

Week 8: Midterm Exam Week 9: Tutorial 7: Applications of s and z transform Week 10: Tutorial 8: Applications of s and z transform

Week 11: Tutorial 9: Gaussian probability density

Week 12: Tutorial 10: Central limit theorem and Quiz 2 Week 13: Tutorial 11: Stochastic processes, independent identically distributed random sequences, Poisson process

Week 14: Tutorial 12: Expected value and correlation, stationary and wide sense stationary processes, ergodicity, Cross

correlation, Gaussian processes Week 15: Tutorial 13: Markov Chains

Week 16: Final Exam

Teaching Methods


Assessment Methods

Description (%)






Total 100 %

Learning Outcomes


After successfully completing the course, s students should be able to do the following:

1. Use statistical methodology and tools in the engineering problem - solving process. 2. Compute and interpret descriptive statistics using numerical and graphical techniques.

3. Understand the basic concept s of p probability, random variables, probability distribution, and joint probability

distribution. 4. Compute point estimation of parameters, explain sampling distributions, and understand the central limit theorem.

5. Construct confidence intervals on parameters for a single sample


Mandatory Literature • Probability, Statistics and Random Processes Dr.K.Murugesan & P.Gurusamy by Anuradha Agencies, Deepti

Publications.

Recommended Literature • Advanced Engineering Mathematics (Eighth edition), Erwin Kreyszig, John Wiley and Sons (ASIA) Pvt. Ltd., 2001.

• Probability and Statistics for Engineers: G.S.S.Bhishma Rao,sitech., Second edition 2005.

62











Total Workload 125


Course Code: CEN 382 Course Name: MICROPROCESSORS AND MICROCOMPUTING



Course Description Introduction of computer and microprocessor architecture, with focus on Altera\\\\'s Nios-II soft processor. Computer

organisation, design and synthesis are covered, as well as use of microcontrollers.

Course Objectives Student should be able to analyze and synthesize a computer system at a certain level of complexity and to use advantages of a particular architecture, implement assembly programs and assembly code snippets in C code.

Course Content

(weekly plan)

Week 1 Basic Structure of Computers Week 9 Pipelining

Week 2 Instruction Set Architecture Week 10 I/O Organisation

Week 3 Instruction Set Architecture Week 11 The Memory System

Week 4 The Altera Nios II Processor Week 12 The Memory System

Week 5 Basic I/O Week 13 Arithmetic

Week 6 Software Week 14 Arithmetic

Week 7 Basic Processing Unit Week 15 Embedded Systems

Week 8 Mid-term Examination Week 16 Final Exam


Week 9 Lab 7: Input/Output in an Embedded

System

Week 2 Lab 1: Introduction to FPGA and Assembler

Week 10 Lab 8: Using Interrupts with Assembly Code

Week 3 Lab 2: Using an Altera Nios II System

Week 11 Lab 9: Using C code with the Nios II

Processor

Week 4 Lab 3: Using Logic Instructions with the

Nios II Processor Week 12

Lab 10: Using Interrupts with C code

Week 5 Lab 4: Subroutines and Stacks

Week 13 Lab 11: Introduction to Graphics and Animation

Week 6 Lab 5: Recap Week 14 Lab 12: Recap

Week 7 Lab 6: Quiz Week 15 Lab 13: Quiz

Week 8 Mid-term Examination Week 16 Final Exam

Teaching Methods

Description


• Interactive Lectures


• Exercises

• Presentation

Assessment Methods

Description (%)






Total 100 %

Learning Outcomes



1. Describe the architecture of microprocessors. 2. Define instruction set for a particular microprocessor.

3. Use practicaly assembly language for Nios-II as well as C for Nios-II.

4. Outline the topics on the hardware, on which programs execute. 5. Define memory hierarchies, I/O interfaces, bus concepts, serial I/O devices, and interrupt control devices.


Mandatory Literature • Hamacher, Carl, Zvonko Vranesic, and Safwat Zaky. Computer organization. McGraw-Hill,2002.









64



Seminar / Presentation -

Total Workload 125


Course Code: EEE 311 Course Name: ELECTRONICS II

Level: Undergraduate Year: III Semester: V ECTS Credits: 5


Course Description This course provides a solid foundation in the digital electronics based on discrete and integrated circuits. Students will be

able to understand current devices, to design electronic structures and exploit them in novel applications.

Course Objectives After completion of this course the student will have theoretical and practical knowledge about digital logic circuits, based on discrete and integrated components. Students will be able to independently use, design, calculate and evaluate most

commonly used integrated circuits, such as logic circuits, multivibrators, timers, counters etc.

Course Content

(weekly plan)

Week 1 The Transistor as a Switch Week 9 Postmidterm Review

Week 2 The MOS Switch Week 10 Flip – Flops

Week 3 Multivibrators Based on Discrete

Components Week 11

Timing Circuit

Week 4 Multivibrators Based on OP-AMP: Week 12 Registers and Counters, Dynamic Logic

Week 5 Technology of Digital Integrated Circuits Week 13 Semiconductor Memories, ET Biasing

Week 6 Bipolar Logic Circuits

Week 14 ROM, PROM, EPROM, EEPROM

memories

Week 7 MOS Gates Week 15 PLA and PLD Structures



Week 9 Lab 6: Multivibrators based on discrete

components (CMOS) 2

Week 2 Lab 1: Components and instruments 1 Week 10 Lab 7: OP – AMP

Week 3 Lab 2: Components and instruments 2


components (OP – AMP)

Week 4 Lab 3: The Transistor as a switch Week 12 Lab 9: Integrator based on OP – AMP

Week 5 Lab 4: CMOS (NAND, NOR, OR, AND) Week 13 Lab 10: NE555


components (CMOS) Week 14

Lab 11: Multivibrators based on discrete

components (NE555)

Week 7 Preparation week Week 15 Preparation week


Teaching Methods

Description • Interactive


Assessment Methods

Description (%)



Project 0% Attendance 10 %



Total 100 %

Learning Outcomes



- analyse fairly complex digital circuits both mathematically, using computer models and laboratory models

- design fairly complex digital electronical circuits and test their functionality - select digital electronical components for various applications according to design requests

- apply the knowledge in practical environment, e.g. FPGA design, systems on chip


Mandatory Literature • Digital Integrated Circuits (2nd Edition): M. Rabaey, Anantha Chandrakasan, and Borivoje Nikolic

Recommended Literature • Digital integrated electronics: Herbert Taub, Donald Shilling

• Slides and Notes from Lectures







66





Total Workload 125


Course Code: EEE 390 Course Name: INTERNSHIP



Course Description

Students must complete a 30 business-day (6 weeks) summer practice in a company working in the field of electrical and

electronics engineering on a part-time basis (4 hours per day). If the company accepts a student for a total of 30 days (which

makes around 20 business-days), the student must work for at least 6 hours per day. At the end of the internship period, students are supposed to complete at least 120 hours.

Course Objectives

Internships for academic credit add a significant workplace experience to a student's education. Students earn a total of 5

ECTS of academic credit for their internships. They gain valuable "on the job" work experience related to a chosen focus in electrical and electronics engineering applications. In addition, internships permit students to interact with professionals in

the fields of work in which they may one day have careers.

Course Content

(weekly plan)

• WEEK 1 - 20 hours

• WEEK 2 – 20 hours









Teaching Methods

Description


• Industrial Training

• “On the job” work experience

Assessment Methods

Description (%)




Midterm Exam 0 % Class Deliverables (Forms) 20 %

Presentation (Notebook) 30 % Final Exam (Company Evaluation) 50 %

Total 100 %

Learning Outcomes


1. Begin to work effectively as part of a team, developing interpersonal, organisational and problem-solving skills within

a managed environment, exercising some personal responsibility.

2. Apply theory, techniques and relevant tools to the specification, analysis, design, implementation and testing of a

simple electrical engineering product;

3. Actively participate in, reflect on, and begin to take responsibility for, personal learning and development;







Laboratory / Practice (30 days x hours per day) 30 4 120







Total Workload 125


Course Code: EEE 382 Course Name: LINEAR CONTROL SYSTEMS

Level: Undergraduate Year: III Semester: VI ECTS Credits: 5


Course Description This course introduces the concepts of control and stability on top of concepts of signals and systems, time and frequency

analysis, differential equations and transfer functions introduced earlier. Course as such introduces the process control and

industrial control basics, helping the students see the application on control theory in practical environment.

Course Objectives After completion of this course, the student is able to design and/or analyse a control system, analyse stability of continuous

time systems described with transfer functions/differential equations, as well as intuitively predict the system behaviour

based on its structure.

Course Content

(weekly plan)


Week 2: Time and s domain

Week 3: Time and s domain Week 4: Block Algebra

Week 5: Block Algebra

Week 6: Bode and Nyquist Plots Week 7: Midterm review

Week 8: Midterm Exam

Week 9: Bode and Nyquist Plots Week 10: Stability

Week 11: Stability

Week 12: Practical examples Week 13: Root Locus Method

Week 14: Root Locus Method

Week 15: Final Review Week 16: Final Exam


Week 2: Tutorial 1: Time and s domain

Week 3: Lab 1: Time and s domain - MATLAB Week 4: Tutorial 2: Block Algebra

Week 5: Lab 2: Block Algebra - MATLAB

Week 6: Tutorial 3: Bode and Nyquist Plots Week 7: Lab 3: Introduction to FESTO, Level controlled system


Week 9: Lab 4: Bode and Nyquist Plots Week 10: Tutorial 4: Stability

Week 11: Lab 5: Stability - MATLAB

Week 12: Lab 6: FESTO - PID

Week 13: Tutorial 5: Root Locus Method

Week 14: Lab 7: Root Locus Method Week 15: Lab 8: FESTO – Flow controlled system

Week 16: Final Exam

Teaching Methods

Description

• Interactive


Assessment Methods

Description (%)






Total 100 %

Learning Outcomes



- analyse and design classic control loops

- assess system stability - tune control systems to suit the requirements

- build control systems using analog and digital electronics components

- build microprocessor based control systems


Mandatory Literature • James K. Roberge,"Operational Amplifiers: Theory and Practice", MIT Open CourseWare 2013

Recommended Literature • Mujo Hebibović, Teorija automatskog upravljanja, ETF u Sarajevu 2003.godine.

• Engelberg, Shlomo. A mathematical introduction to control theory. Vol. 2. Imperial College Press, 2005.






69






Total Workload 125


70

Course Code: EEE 392 Course Name: SENIOR DESIGN PROJECT

Level: Undergraduate Year: III Semester: VI ECTS Credits: 5

Status: Mandatory Hours/Week: 0+5 Total Hours : 0+75

Course Description

An independent study under the supervision of an advisor: Research on exploring and defining a potential study area suitable

for a senior design project. Identification of a specific problem from the selected study area in electrical and electronics

engineering. Results from this study are documented and presented in the form of a design project proposal. Design and implementation of the project proposed. Presentation of the results in both oral and written forms.

Course Objectives

• To do research trying to explore, define, and identify a specific electrical and electronics engineering problem.

• To document the research results with a proposal of a design project.

• To provide the student with the experience of conceiving, designing, and implementing a hardware project or

hardware-related design project proposed.

• To document the results.

• To present the implemented project orally.

Course Content

(weekly plan)

Week 1

Submission of Project Proposals by the

Faculty and Announcement of the Proposed Projects

Week 9

Submission of Project Progress Reports to the

Advisor copy

Week 2 Application for a Proposed Project, or

Proposing Student’s Own Project Week 10

Implementation of the project.

Week 3 Announcement of the Projects Assignments

to the Students Week 11


Advisor 1 copy

Week 4 Description of Project Requirements (in-class meeting) & Research

Week 12 Implementation of the project

Week 5 Doing Research

Week 13 Submission of Final Project Reports to the

Advisor 1 copy

Week 6

Submission of Project Proposals by the

Faculty and Announcement of the Proposed Projects

Week 14

Submission of Final Project Reports to the

Coordinator 3 copies

Week 7 Application for a Proposed Project, or

Proposing Student’s Own Project Week 15


Advisor copy

Week 8 Announcement of the Projects Assignments

to the Students Week 16

Implementation of the project.

Teaching Methods

Description


• Interactive

• Discussions • Individual work

Assessment Methods

Description (%)





Presentation 0 % Final Exam (Presentation) 20 %

Total 100 %

Learning Outcomes


1. Demonstrate knowledge of fundamental aspects of the theories, principles and practice of electrical engineering;

2. Apply theory, techniques and relevant tools to the specification, analysis, design, implementation and testing of a

simple electrical engineering product 3. Actively participate in, reflect on, and begin to take responsibility for, personal learning and development;

4. Evaluate theories, processes and outcomes within an ambiguous setting;

5. Present information in oral, written and graphic forms in order to communicate effectively with peers and tutors












71



Total Workload 125


72

Course Code: EEE 310 Course Name: ELECTROMAGNETIC WAVE THEORY

Level: Undergraduate Year: III Semester: V, VI ECTS Credits: 5

Status: Elective Hours/Week: 2+2 Total Hours: 30+30

Course Description Wave equations. Modelling of aerial lines and cables. Modal analysis of transmission lines. Power line carrier

communications. Mode coupling. Solution of transmission line transients using lattice, Fourier transform and time domain

methods.

Course Objectives

Obtain an understanding of Maxwell’s equations and be able to apply them to solving practical electromagnetic fields

problems. Fundamental concepts covered will include: laws governing electrodynamics, plane wave propagation in different

media, power flow, polarization, transmission and relection at an interface, transmission lines, microwave networks, waveguides, radiation and antennas, wireless systems design and examples.

Course Content

(weekly plan)

Week 1 Introduction Week 9 Postmidterm Review

Week 2 Maxwell's Equations Week 10 Guided waves

Week 3 Wave equations Week 11 Waveguides

Week 4 Electromagnetic waves Week 12 Transmission lines

Week 5 Time-Harmonic EM waves Week 13 Antennas and propagations – Part I

Week 6 Plane waves Week 14 Antennas and propagations – Part II

Week 7 Midterm Review Week 15 Final Review


Teaching Methods

Description


• Interactive lectures

• Presentations

• Problem solving

• Exercises

• Assignments

Assessment Methods

Description (%)






Total 100 %

Learning Outcomes


By the end of this course students will be able to:

1. Understand and adequately apply Maxwell’s equations;

2. Recognize and understand all forms of wave equations and wave propagations; 3. Demonstrate theoretical knowledge related to this course and be able to apply it in problem solving from

electromagnetic courses.


Mandatory Literature • "Field and Wave Electromagnetics" David K. Cheng

Recommended Literature • “Electromagnetic Wave Theory" J. A. Kong

• "Fundamentals of Electromagnetics with Engineering Applications" S.M. Wenthworth











Total Workload 125


73

Course Code: EEE 320 Course Name: INTRODUCTION TO ENERGY SYSTEMS

Level: Undergraduate Year: III Semester: V / VI ECTS Credits: 5


Course Description

It provides students with a comprehensive look at the history and nature of energy production and consumption. The course

provides students with an introduction to energy systems so that they may understand the physical processes that govern energy conversion into forms used by society. Current problems related to the energy supply, renewable sources of energy,

transformation of energy will be explained. Importance of energy strategies in Bosnia and EU will be presented. Students

will be introduced with basic characteristic about the renewable sources of energy and the other conventional energy resources, their characteristic’s, limits, reserves.

Course Objectives

This course is intended to give the students an understanding of energy systems fundamentals and operation. Basic electrical

terminology and concepts are explained in simple to understand terms with regard energy production and consumption, as well as transformation of energy. Furthermore, the objective of the course is to give understanding the basic concepts of

energy systems and new trends in energy consumption and politics.

Course Content

(weekly plan)

Week 1 Introduction to course topics.

Week 9 Renewable sources of energy II Wind energy

Week 2 What is energy system and its components?

Basic terms. Week 10

Conventional sources of energy

Week 3 Production of energy from different sources. Week 11 Transport of energy

Week 4 Problem of energy supply and classification of energy sources.

Week 12 Energy efficiency

Week 5 Energy transformation. Energy reserves. Week 13 Energy strategies

Week 6 Renewable sources of energy I

Solar energy Week 14

Energy and environment

Week 7 Preparation for the midterm exam Week 15 Preparation for the final exam


Teaching Methods

Description


• Lectures

• Recitation

• Experiments

• Presentations

Assessment Methods

Description (%)






Total 100 %

Learning Outcomes



11. Define basic energy terms.

12. Understand the importance of energy in our current technological society

13. Understand basic concept of energy transformation

14. Understand basic terms related to the different energy sources

15. Develop interpersonal and listening skills.


Mandatory Literature •

Recommended Literature •











Total Workload 129

74


75

Course Code : EEE 321 Course Name: MICROWAVE ENGINEERING



Course Description Microwave transmission, transmission lines and waveguides. Microwave circuits. Scattering parameters. Microwave resonators. Microwave using ferrites. Generation and amplification of microwaves. Klystrons, magnetrons, traveling wave

tubes. Semiconductors in microwaves

Course Objectives To introduce the high frequency behavior of circuit and network elements as well as the analysis and the design of passive microwave devices.

Course Content

(weekly plan)


Week 2 Review of basic electromagnetic theory.

Week 10 TE, TM and TEM waves in printed

transmission lines and waveguides.

Week 3 Introduction to guided waves (theory of general cylindrical waveguides).

Week 11 Microwave network analysis.

Week 4 Review of transmission line theory. Week 12 Impedance matching and tuning. – Part I

Week 5 Smith Chart Week 13 Impedance matching and tuning. – Part II

Week 6 Transients in transmission lines.

Week 14 Passive microwave circuit elements (Resonators, Power Dividers, Directional

Couplers, Hybrids, etc.).



Teaching Methods

Description


• Interactive

• Discussions and group work • Tutorials and Labs

Assessment Methods

Description (%)






Total 100 %

Learning Outcomes


After completion of this course, students should be able to: 1. analyze a microwave network 2. use microwave circuit elements 3. synthesize microwave networks and do impedance matching


Mandatory Literature • Robert S. Elliot, An Introduction to Guided Waves and Microwave Circuits, Prentice-Hall International, Inc. 1993,


• Peter A. Rizzi Microwave Engineering, Prentice-Hall International, Inc. 1988,

• R. E. Collin Foundations of Microwave Engineering, McGraw-Hill Book Company, 1966

• V. Lipovac, Osnove mikrovalnih komunikacija: komponente i aplikacije, Sveučilište u Dubrovniku, 2005.

• Z. Smrkić, Mikrovalna elektronika, Školska knjiga, Zagreb, 1990











Total Workload 125


76

Course Code : EEE 322 Course Name: ANTENNA ENGINEERING



Course Description Maxwell's equations, electric and magnetic field, radiation pattern, directivity, gain, matching techniques, wire antennas, array antennas, aperture antennas, Huygens's principles, microstrip antennas, reflector, antenna design, smart antenna systems.

Course Objectives The main objective of the course is to introduce some of the fundamental concepts of the analysis and design of antennas and

antenna systems.

Course Content

(weekly plan)

Week 1 Introduction, Antenna Types and Radiation

Mechanism Week 9

Matching Techniques

Week 2 Fundamental Parameters of Antennas Week 10 Broadband Antennas

Week 3 Radiation Integrals, Auxiliary Potential Functions, Duality and Reciprocity

Theorem

Week 11 Frequency Independent Antennas, Antenna Miniaturization and Fractal Antennas

Week 4 Linear Wire Antennas, Infinitesimal Dipole and Finite Length Dipoles

Week 12 Aperture Antennas and Equivalence Principle

Week 5 Loop Antennas Week 13 Microstrip Antennas and Reflectors

Week 6 Array Antennas: Linear, Planar and

Circular Arrays Week 14

Smart Antennas

Week 7 Antenna Synthesis and Continuous Sources Week 15 Antenna Measurements


Teaching Methods

Description

• Interactive


Assessment Methods

Description (%)






Total 100 %

Learning Outcomes

(please write 5-8

outcomes)

After completion of this course, students should be able to: 1. select proper antenna for an application 2. discuss advantages and disadvantages of typical solutions 3. calculate parameters of antennas


Mandatory Literature • Antenna Theory: Analysis and Design-Third Edition, Constantine A. Balanis, Wiley, 2005, ISBN: 0-471-66782-X;

Recommended

Literature

• Antennas: For All Applications-Third Edition, John D. Kraus and Ronald J. Marhefka, Mc Graw Hill, 2002, ISBN: 0-07-

232103-2;

• Foundations of Antenna Theory and Techniques, Vincent F. Fusco, Pearson, 2005, ISBN: 0-130-26267-6











Total Workload 125


77

Course Code : EEE 324 Course Name: MICROWAVE ELECTRONICS



Course Description

Techniques of analog circuit technology in the gigahertz high-frequency regime. Transmission lines and distributed circuit elements; S-parameter design of high-frequency active circuits; computer-aided analysis and design. Emphasis on design of

planar high-frequency integrated circuits employing CMOS and SiGe technology. Circuit building blocks for broadband

wired and wireless communication will be emphasized including oscillators, low-noise amplifiers, and power amplifiers.

Course Objectives This course aims at introducing concepts of microwave electronics within the general electronics framework

Course Content

(weekly plan)

Week 1 Introduction. Week 9 Amplifiers

Week 2 Analog circuit technology at gigahertz

frequencies. Week 10

Low-noise amplifiers

Week 3 Transmission lines and distributed circuit

elements. Week 11

Broadband amplifers

Week 4 Microstrip transmission lines. Week 12 Oscillators, VCOs

Week 5 S Parameters. Week 13 Mixers

Week 6 Smith chart and impedance matching. Week 14 Power Amplifers

Week 7 Computer-aided analysis and design. Week 15 Project presentations


Teaching Methods

Description


• Interactive


Assessment Methods

Description (%)






Total 100 %

Learning Outcomes


After completion of this course, students should be able to: 1. design electronic circuit taking into account microwave effects 2. do impedance matching in circuits 3. calculate microwave-related parameters


Mandatory Literature Microwave Engineering, David M. Pozar, 2nd ed., John Wiley & Sons,1998, ISBN 0-471-17096-8












Total Workload 125


78

Course Code : EEE 331 Course Name: TELECOMMUNICATIONS I



Course Description

This is the first course in the series of two senior level courses on telecommunications aiming to introduce the basic principles behind the analysis and design of modern communication systems. The main goal of this course is to introduce the

concepts of modulation and demodulation of information and the effect of noise on system performance. The topics that will

be covered are spectral analysis of signals and systems, baseband representation of carrier modulated signals, random processes, continuous wave modulation (AM and FM) and their noise analysis, pulse modulation and baseband digital

transmission.

Course Objectives Introduce the concepts: decibel, noise, modulation; analysis of the operation of analog and digital systems communication systems

Course Content

(weekly plan)


Week 2 Introduction to communication systems Week 10 Analog modulation

Week 3 Fourier analysis of signals and systems – Part

I Week 11

Analog to Digital Conversion

Week 4 Fourier analysis of signals and systems – Part

II Week 12

Data Compression

Week 5 Random processes – Part I Week 13 Baseband digital transmission – Part I

Week 6 Random processes – Part II Week 14 Baseband digital transmission – Part II



Teaching Methods

Description


• Interactive


Assessment Methods

Description (%)




Midterm

Exam

20 % Class Deliverables 0 %


Total 100 %

Learning Outcomes


After completion of this course, students should be able to: 1. differentiate between different modulation schemes 2. read properties of signals in frequency domain 3. design simple transmission schemes


Mandatory Literature • Leon W. Couch, Digital and Analog Communication Systems, 7th ed., Prentice Hall, 2007.


• John G. Proakis and Masoud Salehi, Communication Systems Engineering, 2nd edition, Prentice Hall, 2002.

• B. P. Lathi, Modern Digital and Analog Communication Systems, 3rd ed., Oxford University Press, 1998.

• Bruce Carlson, Paul B. Crilly, and Janet C. Rutledge, Communication Systems: An Introduction to Signals and Noise

in Electrical Communication, 4th ed., McGraw-Hill, 2001.

• M. Hadžialić, "Telekomunikacijske tehnike”, u pripremi

• N.Bilić, "Osnovni procesi i modulacioni postupci u digitalizaciji signala", Sarajevo 2005.











79

Total Workload 125


80

Course Code : EEE 332 Course Name: TELECOMMUNICATIONS II



Course Description

In this course, the basic concepts behind the design and analysis of digital communication systems will be introduced. Topics covered in class include sampling and quantization of analog information sources, digital pulse modulation

techniques, signal space representation and analysis of digital signals, digital baseband modulation and demodulation,

probability of error analysis, spectral shaping and intersymbol interference, digital bandpass transmission and error control coding.

Course Objectives Introduction to probability theory. Random processes. Review of modulation techniques. AM and FM systems performance

in presence of noise. Noise in digital communication systems. Optimal detection of signals and optimum receivers. Introduction to information theory. Error-correction codes.

Course Content

(weekly plan)


Week 2 Sampling and quantization of analog information sources

Week 10 Digital baseband modulation and demodulation,

Week 3 Digital pulse modulation techniques – Part I Week 11 Probability of error analysis,

Week 4 Digital pulse modulation techniques – Part II

Week 12 Spectral shaping and intersymbol

interference,

Week 5 Signal space representation Week 13 Digital bandpass transmission

Week 6 Analysis of digital signals Week 14 Error control coding.



Teaching Methods

Description

• Interactive


Assessment Methods

Description (%)






Total 100 %

Learning Outcomes


After completion of this course, students should be able to: 1. design and analyze digital communication schemes 2. use error control coding 3. choose digital modulation schemes for different applications


Mandatory Literature • Simon Haykin, Communication Systems, John Wiley & Sons, 2001.

Recommended Literature • M. Hadžialić, "Telekomunikacijske tehnike”, u pripremi











Total Workload 125


Course Code: EEE 333 Course Name: DIGITAL COMMUNICATION



Course Description

Random Signals, Bandwidth of Digital Data, Character Coding, Pulse Code Modulation, Uniform and Nonuniform Quantization, Correlative Coding, Detection of Binary Signals in Gaussian Noise, Intersymbol Interference, Equalization,

Coherent and Noncoherent Detection, Error Performance of Binary Systems, M-Ary Signaling and Performance, Waveform

Coding, Cyclic and Block Codes, Types of Error Control, Convolutional Encoding and Decoding Algorithms.

Course Objectives

This course introduces the fundamentals of digital signaling, information theory and coding, digital transmission and

reception. The goal is to equip the students with basic knowledge for design, analysis and comparison of digital

communication systems and for the physical layer of data communication networks including wireless networks and the internet.

Course Content

(weekly plan)

Week 1 Overview of digital communication systems:

Week 9 Analog-to-digital conversion: sampling

and Nyquist sampling theorem.

Week 2 Source coding and source coding theorem

Week 10 Quantization and signal-to quantization

noise ratio

Week 3 Introduction to error control coding,

Week 11 Pulse code modulation, bandwidth of digital signals,

Week 4 Syndrome decoding, cyclic codes Week 12 Differential PCM, delta modulation

Week 5 Channel capacity theorem

Week 13 Time-division multiplexing, baseband digital signaling

Week 6 Basic detection theory

Week 14 Partial response digital signaling, eye

pattern, baseband M-ary systems

Week 7 Detection of signals in additive white

Gaussian noise, matched filter receivers Week 15

Coherent and non-coherent reception of

digital modulation signals


Teaching Methods

Description


• Interactive


Assessment Methods

Description (%)






Total 100 %

Learning Outcomes


After completion of this course, students should be able to: 1. apply coding theory and detection theory to simple communication schemes 2. design a multiplexing scheme 3. observe and read eye patterns and other visual indicators of communication quality


Mandatory Literature • Simon Haykin, Digital Communications , John Wiley & Sons, 1988

Recommended Literature • Ivo M. Kostić, Digitalni Telekomunikacini sistemi I, Naučna Knjiga 1994, Beograd.











Total Workload 125


Course Code: EEE 334 Course Name: DIGITAL SIGNAL PROCESSING



Course Description In this course, we only study the fundamentals of discrete-time signals and systems. The course content includes the concept

and the classification of discrete-time signal, representations of signals in time, frequency, z- and discrete frequency

domains, representations and analyses of systems, and filter designs.

Course Objectives

The aim of this course is to provide fundamental concepts in digital signals and systems, as an introduction to advance

digital signal processing. Digital signal processing represents a base upon which various engineering systems are build,

including communication systems, image processing, speech processing, consumer electronics, and data processing. This course aims at preparing the student for basic DSP activities, focusing mostly on digital filter design, providing a solid

ground for upgrade and work on practical DSP devices, as well as general purpose hardware in role of DSP.

Course Content

(weekly plan)


Week 2: Sampling Theory – Part I

Week 3: Sampling Theory – Part II

Week 4: Discrete-Time S&S – Part I Week 5: Discrete-Time S&S – Part II

Week 6: The Z-Transform – Part I

Week 7: Midterm Review Week 8: Midterm Exam

Week 9: Post midterm Review

Week 10: The Z-Transform – Part II Week 11: Fourier Analysis of Discrete-Time S&S – Part I

Week 12: Fourier Analysis of Discrete-Time S&S – Part II

Week 13: Design of Discrete Filters – Part I Week 14: Design of Discrete Filters – Part II

Week 15: Final Review

Week 16: Final Exam


Week 2: Tutorial 1: Sampling Theory Week 3: Lab 1: Fourier Transform

Week 4: Tutorial 2: Discrete-Time S&S

Week 5: Lab 2: Filter Design in MATLAB Week 6: Tutorial 3: The Z-Transform – Part I

Week 7: Tutorial 4: Midterm Review


Week 9: Tutorial 5: Post midterm Review

Week 10: Tutorial 6: The Z-Transform – Part II

Week 11: Tutorial 7: Fourier Analysis of Discrete-Time S&S – Part I

Week 12: Tutorial 8: Fourier Analysis of Discrete-Time S&S – Part II

Week 13: Tutorial 9: Design of Discrete Filters – Part I Week 14: Lab 3: The more, the Fourier

Week 15: Tutorial 10: Final Review

Week 16: Final Exam

Teaching Methods

Description 1. Interactive Discussions and group works 2. Tutorials and Labs

Assessment Methods

Description (%)






Total 100 %

Learning Outcomes


1. Describe the properties of discrete LTI systems;

2. Understand mathematical descriptions and representations of discreet signals and systems and draw parallel with

continuous time signals and systems; 3. Understand how to sample the continuous time signal at hand;

4. Familiarize with the idea of representing discrete time signals and LTI systems in the Z domain;

5. Familiarize with the idea of representing discrete time signals and LTI systems in the frequency domain; 6. Understand spectral representation of signals via DTFT, DFT, and FFT, and their properties and applications;

7. Ability to solve difference equations;

8. Ability to design digital filters;


Mandatory Literature • Luis F. Chaparro, “Signals and Systems using MATLAB”, Academic Press.


• A.V. Oppenheim, R.W. Schafer and J.R. Buck, Discrete-Time Signal Processing, Prentice- Hall, 2nd ed., 1999.

• Sanjit K. Mitra, Digital Signal Processing, McGraw-Hill

• J.G. Proakis and D.G. Manolakis, Digital Signal Processing: Principles, Algorithms, and Applications, 4th ed.,

Prentice-Hall, 2007.



83









Total Workload 125


84

Course Code : EEE 336 Course Name: COMMUNICATION ELECTRONICS



Course Description

Nonlinear controlled sources: piecewise linear, square-law, exponential and differential pair characteristics. Low level amplitude modulation and analog multiplication. Narrow band transformer as a coupler. Nonlinear loading of tuned circuits.

Tuned large signal amplifiers and frequency multipliers. Phased locked loops. Sinusoidal oscillators. Frequency

synthesizers, mixers, modulators, and demodulators. Basic transmitters and receivers.

Course Objectives Nonlinearity. Nonlinear controlled sources. Amplitude modulation and analog multiplication. Narrow band transformer as a

coupler. Nonlinear loading of tuned circuits. Tuned amplifiers. Frequency multipliers. Sinusoidal oscillators. Phase locked

loops. Frequency synthesizers. Mixers. Modulators and demodulators. Basic transmitters and receivers.

Course Content

(weekly plan)

Week 1 Introduction Week 9 Frequency multipliers. Sinusoidal oscillators.

Week 2 Nonlinearity. Week 10 Sinusoidal oscillators, VCOs.

Week 3 Nonlinear controlled sources. Week 11 Phase locked loops.

Week 4 Amplitude modulation and analog

multiplication. Week 12

Frequency synthesizers.

Week 5 Narrow band transformer as a coupler. Week 13 Mixers.

Week 6 Nonlinear loading of tuned circuits Week 14 Modulators and demodulators

Week 7 Tuned amplifiers. Week 15 Basic transmitters and receivers.


Teaching Methods

Description

• Interactive


Assessment Methods

Description (%)






Total 100 %

Learning Outcomes


After completion of this course, students should be able to: 1. select and use controlled sources for communication purposes 2. design circuits with oscillators and amplifiers 3. select transmitters and receivers for particular applications


Mandatory Literature • Modern Electronic Communication, Jeffrey S. Beasley, Gary M. Miller

Recommended Literature • S. Tešić, D. Vasiljević: Osnovi elektronike, Građevinska knjiga, Beograd, 1997











Total Workload 125


85

Course Code : EEE 337 Course Name: INTRODUCTION TO WIRELESS COMMUNICATIONS

Level: Undergraduate Year: III Semester: VI, VI ECTS Credits: 5


Course Description

This course will cover the basic topics in wireless communications. It begins with the overview of existing wireless systems and standards. Then, the characterization of the wireless channel is done through the analysis of its basic properties.

Continuous and pulse modulations for wireless communication systems are presented and then, different diversity

techniques in fading channels are introduced. Afterwards, some basics concerning the cellular communications and its development are presented. Last part of the course will be devoted to the multi-user wireless communications and finally

multiple antenna and space-time communications over wireless channels will be analyzed.

Course Objectives

• Providing the students with basic knowledge concerning the wireless communications

• Introduction to the underlying principles and techniques in the current wireless communication systems

• Developing skills for understanding the technical issues and challenges in wireless communications

• Review of the current wireless communication systems and standards

Course Content

(weekly plan)


Week 2 Overview of Wireless Communication

Systems Week 10

Capacity of Wireless Channels

Week 3 Wireless Channel Week 11 Cellular concepts

Week 4 Modulation (Continuous Wave and Pulse) –

Part I Week 12

Multi-user Wireless Communications

Week 5 Modulation (Continuous Wave and Pulse) –

Part II Week 13

Multiple Antenna

Week 6 Diversity in Fading Channels Week 14 Space-time Communications



Teaching Methods

Description


• Interactive

• Discussions and group works • . Tutorials and Labs

Assessment Methods

Description (%)






Total 100 %

Learning Outcomes


After completion of this course, students should be able to: 1. design simple wireless communication schemes 2. select components according to the requirements 3. analyze parameters from wireless communication traffic


Mandatory Literature • J. G. Proakis, "Digital Communications," McGraw-Hill, New York, NY, USA, 3rd edition, 1995.

Recommended Literature • Simon O. Haykin, "Communication System," 4th edition, Wiley, 2000.

• David Tse and Pramod Viswanath, "Fundamentals of Wireless Communication," Cambridge University Press, 2005.











Total Workload 125


86

Course Code : EEE 346 Course Name: INTRODUCTION TO VLSI DESIGN



Course Description Size and complexity of integrated circuits (IC), IC design process. Trends in very large scale integrated (VLSI) circuit design. IC production process. Semiconductor processes. Design rules and process parameters. Layout techniques and

practical considerations. Device modeling, circuit simulation. Basic integrated circuit building blocks.

Course Objectives To learn VLSI physical design automation

Course Content

(weekly plan)


Week 2 Circuit Partitioning – Part I Week 10 Placement – Part I

Week 3 Circuit Partitioning – Part II Week 11 Placement – Part II

Week 4 Floor planning – Part I Week 12 Layout generation – Part I

Week 5 Floor planning – Part I Week 13 Layout generation – Part II

Week 6 Floor planning – Part III Week 14 Layout generation – Part III



Teaching Methods

Description


• Interactive

• Discussions and group works

• Tutorials and Labs

Assessment Methods

Description (%)






Total 100 %

Learning Outcomes


After completion of this course, students should be able to: 1. to design simple VLSI circuits 2. to analyze an existing VLSI design 3. to suggest improvements of existing VLSI design


Mandatory Literature • VLSI Physical Design Automation: Theory and Practice Authors: Sadiq M. Sait, Habib Youssef












Total Workload 125


87

Course Code : EEE 348 Course Name: INTRODUCTION TO IMAGE PROCESSING



Course Description Digital images, sampling and quantization of images. Arithmetic operations, gray scale manipulations, distance measures, connectivity. Image transforms. Image enhancement. Image restoration. Image Segmentation. Image representation and

description.

Course Objectives To learn fundamentals of image processing.

Course Content

(weekly plan)


Week 2 Image processing in MATLAB Week 10 Wavelets – Part I

Week 3 2D filter theory – Part I Week 11 Wavelets – Part II

Week 4 2D filter theory – Part II Week 12 Edge detection

Week 5 Image compression – Part I Week 13 Morphology

Week 6 Image compression – Part II Week 14 Tomography



Teaching Methods

Description

• Interactive


Assessment Methods

Description (%)




Midterm Exam



Total 100 %

Learning Outcomes

(please write 5-8

outcomes)

After completion of this course, students should be able to: 1. use MATLAB for image processing 2. program basic image processing algorithms 3. filter images in various ways


Mandatory Literature • Digital Image Processing, 3rd Edition Authors: Gonzalez & Woods Prentice Hall ISBN number: 9780131687288

Copyright: 2008

Recommended

Literature











Total Workload 125


88

Course Code : EEE 349 Course Name: INTRODUCTION TO OPTICAL FIBER COMMUNICATIONS



Course Description An introduction to optical communication systems. Optical fiber waveguides. Transmission characteristics of optical fibers. Optical fibers, cables and connections. Optical fiber measurements. Optical sources: Lasers, LEDs. Optical detectors.

Receiver noise considerations. Optical fiber communication systems.

Course Objectives The objectives of this course are to provide the students with a solid understanding on: Optical Fibers and their fabrication, signal degradation in optical fibers, optical sources, power launching and coupling, photodetectors, photodetectors, digital

and analog transmission systems, WDM concepts and components. Optical Amplifiers. Optical Networks.

Course Content

(weekly plan)

Week 1 Overview of Optical Fiber Communications Systems. Optical Fibers

Week 9 Photodetectors

Week 2 Fabrication of optical fibers; Types of Optical

Fibers Week 10

Optical Receivers

Week 3 Signal Degradation in Optical Fibers Week 11 Digital Transmission Systems

Week 4 Optical Sources: LEDs Week 12 Analog Systems

Week 5 Optical Sources: Laser Diodes Week 13 WDM Concepts and Components

Week 6 Power Launching and Coupling Week 14 Optical Amplifiers

Week 7 Fiber Splicing; Optical Fiber Connectors Week 15 Optical Networks


Teaching Methods

Description

• Interactive


Assessment Methods

Description (%)






Total 100 %

Learning Outcomes


After completion of this course, students should be able to: 1. design simple optical circuits 2. select components for optical networks 3. participate in manufacture of optical fibers


Mandatory Literature • Gerd Keiser, Optical Fiber Communications, McGraw-hill, New York, 3rd Ed.,2000.

Recommended Literature • D.Milatović, Optoelektronika, Sarajevo 1987.

• M.Cvijetić, Digitalne svjetlovodne telekomunikacije, Beograd 1988.











Total Workload 125


89

Course Code : EEE 360 Course Name: ILLUMINATION



Course Description

Light theories. Eye, sensitivity and vision types. Light reflection, absorption and transmission phenomenon. Definition of lighting terms. Lighting methods. Internal lighting systems and calculations. Lighting apparatus and armatures. Fotometric

measurements. Pre-project preparation fundamentals. Interior electrical installations, low current and high current systems

and drawings. Feeder, column and main-column line formation. Fundamentals of practical application project preparations. Low power-factor correction methods in internal installations. Voltage-drop calculation for lighting systems. Hardware

Equipment for Computer Aided Design. Representation of CAD Packet Program (AutoCAD). Usage of Primary Drawing

Commands. 2-Dimentional Drawing. Text Operations. Project Applications.

Course Objectives

Students will learn about interior lighting of various type buildings. Topics are: Light theories. Eye, sensitivity and vision

types. Light reflection, absorption and transmission phenomenon. Definition of lighting terms. Lighting methods. Internal

lighting systems and calculations. Lighting apparatus and armatures. Fotometric measurements. Pre-project preparation fundamentals. Interior electrical installations, low current and high current systems and drawings. Feeder, column and main-

column line formation. Fundamentals of practical application project preparations. Low power-factor correction methods in

internal installations. Voltage-drop calculation for lighting systems. Hardware Equipment for Computer Aided Design. Representation of CAD Packet Program (AutoCAD). Usage of Primary Drawing Commands. 2-Dimentional Drawing. Text

Operations.

Course Content

(weekly plan)

Week 1 Light theories. Eye, sensitivity and vision types

Week 9 Pre-project preparation fundamentals

Week 2 Reflection, absorbtion and transmission

phenomenon Week 10

Interior electrical installations, low current

and high current systems and drawings

Week 3 Definition of lighting terms

Week 11 Feeder, column and main-column line

formation.

Week 4 Lighting methods

Week 12 Fundamentals of practical application

project preparations.

Week 5 Internal lighting systems and calculations

Week 13 Low power-factor correction in internal installations.

Week 6 Lighting apparatus and armatures

Week 14 Hardware Equipment for Computer Aided

Design

Week 7 Measurements Week 15 Final Review


Teaching Methods

Description

• Interactive


Assessment Methods

Description (%)






Total 100 %

Learning Outcomes


After completion of this course, students should be able to: 1. design illumination for different objects 2. use CAD for illumination purposes 3. prepare an illumination project


Mandatory Literature • Gary Gordon, “Interior Lighting”, Wiley, Fourth Edition, January 10, 2003..

Recommended Literature • Mark Karlen, James R. Benya, “Lighting Design Basics”, Wiley, March 19, 2004.









90



Total Workload 125


91

Course Code : EEE 361 Course Name: ELECTRICAL MACHINERY I



Course Description Electromagnetic circuits; properties of ferromagnetic materials. Single-phase and three-phase transformers. Per Unit System. Principles of electromechanical energy conversion: Linear and nonlinear systems; singly and multiply excited, translational

and rotational systems. DC machines: Theory, generators, motors, speed control.

Course Objectives

The course objective is obtaining theoretical and practical insight about DC machines and transformers To be able to deal with basics of transformers; to be able to differentiate between DC machines and AC machines; To be able to deal

completely with both DC motors and DC generators; to know how to control the speed of DC motors and the voltage of the

DC generators

Course Content

(weekly plan)

Week 1

Introductory Background: Complex

numbers., Inductive impedance circuits and

Phasor diagrams, Faraday’s law, Lenz law, Magnetic force, Ampere’s law

Week 9

Per unit systems

Week 2

Magnetic Circuits: Ampere’s law and

magnetic circuits, B-H curve, Magnetization curve

Week 10

Fundamental of electromagnetic energy

conversion

Week 3 Magnetic Circuits: Magnetic circuit with air

gap, inductances, magnetic materials Week 11

Fundamentals of DC machines: Construction,

Commutation, Armature reaction

Week 4 Transformers: single phase transformers,

ideal transformers, practical transformers Week 12

DC generators: Separately excited, Shunt,

Compound, and series generators

Week 5 Transformers equivalent circuit, Open and short circuit tests

Week 13 DC motor: Separately excited, Shunt, Compound, and series generators

Week 6 Voltage regulation, efficiency, auto transformers

Week 14 Dc motors: Starting and braking

Week 7 Three phase transformers Week 15 DC motor speed control.


Teaching Methods

Description

1. Interactive 2. Discussions and group works 3. Tutorials and Labs

Assessment Methods

Description (%)






Total 100 %

Learning Outcomes


After completion of this course, students should be able to: 1. choose the best motors and generators for specific applications 2. control DC motors 3. design a circuit for electrical machines to be placed in


Mandatory Literature • Electric Machinary Fundamentals Fourth Edition Stephen J. Chapman ISBN:0072465239

Recommended Literature • Mačić: "Električni stojevi", Unverzitet u Sarajevu - Elektrotehnički fakultet u Sarajevu, Sarajevo 2005.

• R. Wolf: "Osnove električnih strojeva" školska knjiga Zagreb, 1995.

• M. Jadrić, B. Frančić: "Dinamika električnih strojeva"Graphis Zagreb, 1998.











92

Total Workload 125


93

Course Code: EEE363 Course Name: RENEWABLE ELECTRICAL ENERGY SYSTEMS



Course Description

This course introduce students to contemporary renewable energy technology, including sustainability and environmental

issues, energy resources, electric power generation from renewable energy sources, such as solar, wind, geothermal, wave,

tide, hydro and fuel cells. Understanding of energy storage and system integration is needed and, as an example, developments in electrical utilisation in electric and hybrid vehicles are also studied. Design techniques for renewable

energy systems are discussed in detail. Students are able to practise their design skills of renewable energy systems through

three assignments specified as system specification, analysis of options and system design, respectively. By studying this subject, students gain knowledge and essential skills to design a renewable energy system.

Course Objectives

Aim of this course is to make student understand and analyze energy conversion, utilization and storage for renewable

technologies such as wind, solar, biomass, fuel cells and hybrid systems and for more conventional fossil fuel-based technologies. Use the First and Second Laws of Thermodynamics and introductory transport phenomena to form the basis of

modeling renewable energy systems. Understand the environmental consequences of energy conversion and how renewable

energy can reduce air pollution and global climate change.

Course Content

(weekly plan)

Week 1 Introduction to energy Week 9 Water Energy

Week 2 Review of Thermodynamics Week 10 Hydropower resources

Week 3 Ocean Thermal Energy Converters Week 11 Fuel cells

Week 4 Solar radiation Week 12 Hydrogen production and storage

Week 5 Biomass Week 13 Thermionics

Week 6 Wind Energy Week 14 Practical Activity

Week 7 Practical Activity Week 15 Final Review


Week 1 Beginning of classes Week 9 Post midterm review

Week 2 Week 10 Lab 5: DigSilent PowerFactory

Week 3 Tutorial Week 11 Lab 6: Renewable energy sources in DigSilent

Week 4 Lab 1: PV system at IBU Week 12 Tutorial

Week 5 Lab 2: Measurement of the power of the PV system

Week 13 Tutorial

Week 6 Lab 3: Shadowing effect Week 14 Lab 7: Battery

Week 7 Lab 4: Modeling of PV panel in Matlab Week 15 Preparation for Final Exam


Teaching Methods

Description


• Interactive


Assessment Methods

Description (%)


Homework/Seminar 10 % Term Paper 0 %




Total 100 %

Learning Outcomes


1. Have a working knowledge of the emerging power generation technologies such as photovoltaic arrays, wind turbines,

and fuel cells. 2. Compare different renewable energy technologies and choose the most appropriate based on local conditions

3. Describe the main components of different renewable energy systems

4. Calculate the basic performance parameters of these systems, such as efficiency and cost. 5. Perform basic assessment and design of a renewable electrical energy system for a given application

6. Recognize the effects that current energy systems based on fossil fuels have over the environment and the society


Mandatory Literature • Renewable Energy: power for sustainable future edited by Godfrey Boyle, 3rd edition, Oxford university press 2012.

(ISBN: 9780199545339).

Recommended Literature • Renewable Energy: power for sustainable future edited by Godfrey Boyle, 3rd edition, Oxford university press 2012.

(ISBN: 9780199545339).


94








Seminar / Homework 1 10 10

Project 1 14 14

Total Workload 128


95

Course Code: EEE364 Course Name: POWER SYSTEM ANALYSIS



Course Description Basic structure of electrical power systems. Electrical characteristics of transmission lines, transformers and generators.

Representation of power systems. Per Unit System. Symmetrical three-phase faults. Symmetrical components.

Unsymmetrical faults.

Course Objectives

Students will gain the knowledge of power systems analysis. Introduction, review of phasors and three phase power

Transmission line parameter computation and analysis Models for transformers, generators, and loads Power flow analysis

and control Generation Control, economic dispatch and restructuring Short circuit analysis, including symmetrical components Transient stability System protection

Course Content

(weekly plan)

Week 1 Introduction to power systems Week 9 Postmidterm Review

Week 2 Basic concepts Week 10 Voltage drop, Losses

Week 3 The synchronous machine, Transformers Week 11 Fault analysis

Week 4 Modeling of power system components Week 12 Fault analysis, Thevenin equivalent

Week 5 Power line modeling Week 13 Power flow analysis

Week 6 Power line modeling Week 14 Power flow analysis

Week 7 Power system analysis and calculations Week 15 Final Review


Week 1 Beginning of classes Week 9 Lab 4: PSAT

Week 2 Tutorial: Two port networks, Pi model Week 10 Tutorial: Voltage drop

Week 3 Tutorial: Per unit system Week 11 Lab 5: Fault analysis

Week 4 Tutorial: Transformers Week 12 Tutorial: Fault calculation

Week 5 Tutorial: Power lines

Lab 1: Modelling of Transmission lines Week 13

Lab 6: Fault analysis

Week 6 Lab 2: Modelling of Transmission lines

Week 14 Tutorial: Power Flow – Gauss Siedel Lab 7: Power flow analysis

Week 7 Lab 3: Modelling of Transmission lines Week 15 Tutorial: Power Flow – Newton Raphson


Teaching Methods

Description

• Interactive


Assessment Methods

Description (%)






Total 100 %

Learning Outcomes


Upon completion of the course the student should be able to

1. apply methods for power system analysis in steady state operation and during grid faults, 2. explain the principles for regular power flow and optimal power flow methods,

3. use the main principles for modelling and analysis of power systems subject to symmetrical and unsymmetrical faults,

4. perform an optimal power flow for reactive power dispatching to decrease power losses 5. modelling of transformers, lines and cables in the positive, negative and zero sequences based on physical models,

6. analyze the system performance where there is an unbalanced fault, and also calculate the corresponding fault current


Mandatory Literature • Glover and Sarma, “Power System Analysis & Design”, Brooks/Cole publishing, 3rd ed., 2002

Recommended Literature • S.Sadović: Analiza elektroenergetskih sistema, ETF Sarajevo, 2004

• B.M. Weedy, B.J. Cory: "Electric Power Systems", 1998


96








Assignment / Homework 1 10 10

Quiz 1 11 11

Total Workload 125


97

Course Code : EEE366 Course Name:ELECTRICAL POWER TRANSMISSION



Course Description

This course explains the power system and discusses how to improve power transmission reliability in an effort to reduce the

occurrence of power outages. The course reviews the power system fundamentals that apply to generation, transmission and

distribution. It discusses the stability and reliability issues involved in an interconnected power system and the operation of the grid. The present regulatory environment is discussed and the measures to ensure stability are explained.

Course Objectives To provide a clear understanding of power system reliability through a step-by-step review of the power system elements

and analysis, concepts of real and reactive power and their utilization in power transmission, line protection and its importance in maintaining system stability, and the latest developments to enhance the bulk power system reliability.

Course Content

(weekly plan)


Week 2 Transmission Line Constants Week 10 Corona

Week 3 Overhead Lines – Part I Week 11 Substations – Part I

Week 4 Overhead Lines – Part I Week 12 Substations – Part II

Week 5 Performance of Transmission Lines – Part I Week 13 Extra High Voltage Transmission – Part I

Week 6 Performance of Transmission Lines – Part II Week 14 Extra High Voltage Transmission – Part II



Teaching Methods



Assessment Methods

Description (%)






Total 100 %

Learning Outcomes


1. Explain the use of different voltage levels in transmission of electrical power 2. Describe the fundamental definitions and concepts for reliability assessment

3. Categorize power lines by voltage and explain the applications

4. Explain functions of different parts of a power line 5. Explain the types of electrical power distribution systems and their characteristics


Mandatory Literature • Modern Power System Analysis: Nagrath and Kothari, TMH

Recommended Literature • A Course in Electrical Power Systems: Soni, Gupta, Bhatnagar

• HVDC Power Transmission System: K. R. Padiyar









Assignment / Homework / 1 10 10

Quiz 1 11 11

Total Workload 125


98

Course Code : EEE367 Course Name:POWER SYSTEM PROTECTION



Course Description

Power system protection is an integral part of every power system.All powerequipment including power generators,

step - up transformers, step-down transformers, transmission lines, power capacitors and electric motors and other loads

etc. need protection. The following topics will be included in the course: Investigation of current and voltage waveforms during faults and other conditions. Distance and carrier-aided distance protection. New protection schemes applicable to

high-speed protection. Digital relaying. Developments in integrated protection, control and measurement systems. The

course also gives a brief overview of overvoltage and system protection.

Course Objectives To provide an in-depth view of the methods and devices used in electric power system protection; protection systems, relay

types, protection of machines, transformers, buses and lines; instrument transformers; and modern trends in protection.

Course Content

(weekly plan)

Week 1 Primary and back up protection, current transformers for protection, potential

transformer

Week 9 Digital relaying algorithms

Week 2

Review of electromagnetic relays static relays.

Week 10

Differential equation technique, discrete fourier transform technique, walsh-hadamard

transform technique Rationalized harr

transform technique, removal of dc offset

Week 3

Over current relays time current characteristic,

current setting time setting, directional relay,

static over current relays

Week 11

Introduction to Microprocessors: review of

microprocessors and interfacing.

Week 4 Distance protection

Week 12 single chip microcomputers programmable

interval timer, A/D converter.

Week 5 Compensation for correct distance measurement, reduction of measuring units

switched schemes.

Week 13 Microprocessor based protective relays

Week 6 Pilot relaying schemes. Wire pilot protection, circulating current scheme

Week 14 Over current, directional, impedance, reactance relays

Week 7

Balanced voltage scheme, transley scheme ,

carrier current protection. Week 15

Generalized mathematical expressions for

distance relays, mho and offset mho relays, quadrilateral relay.


Teaching Methods

Description

• Interactive


Assessment Methods

Description (%)






Total 100 %

Learning Outcomes


1. calculation of both symmetrical and unsymmetrical fault current

2. understand the principles of operation of protective devices

3. understand the applications of protection devices in the design of protection systems for transmission lines and bus bars,

4. understand and design protection systems for transformers and generators, and

5. understand power quality problems and their mitigating techniques.


Mandatory Literature • Power system protection & switchgear by Badri Ram & Vishwakarma, TMH publication New Delhi 1995.

Recommended Literature • Power System Protection by Paul M. Anderson









99


Project 1 11 11

Total Workload 125


100

Course Code: EEE369 Course Name: DISTRIBUTION SYSTEMS



Course Description

Basic considerations. Load characteristics and forecasting methods. Distribution substations. Sub-transmission, primary and

secondary distribution. Choice of voltage levels. Operational characteristics of cables, aerial lines and transformers. System

voltage regulation. Power factor correction. Fusegear, switchgear, current and voltage transformers. Overcurrent and thermal protection. Reliability of distribution systems. Economics of distribution systems.

Course Objectives

This module imparts knowledge and skills to enable the learner to select and specify the components of an electrical

distribution system. The module introduces modelling and analysis of electrical power transmission systems, review of electric power distribution systems currently used by electric utility companies from the generating plant to the customer's

service, choice of voltage levels, operational characteristics of cables, aerial lines and transformers.

Course Content

(weekly plan)

Week 1 Introduction. overview of a complete power system

Week 9 Postmidtterm review

Week 2 Distribution system

Week 10 Distribution system

planning

Week 3 Consumers, Voltage drops and losses in

distribution network Week 11

Distribution system

protection

Week 4 Voltage regulation

Week 12 Distribution system protection

Week 5 Reconfiguration of the network. Genetic

Algorithm Week 13

Power quality

Week 6 Reliability Week 14 Power quality

Week 7 Reactive energy compensation

Week 15 Preparation for the final

exam.


Week 1 Introduction. overview of a complete power system

Week 9 Postmidterm review

Week 2 Lab 1: DigSilent PowerFactory

Week 10 Lab 7: Optimal capacitor

placement

Week 3 Lab 2: Modeling of the network

Week 11 Lab 8: Optimal capacitor

placement in DigSilent

Week 4 Lab 3: Modeling of the network in matpower Tutorial: Power losses

Week 12 Tutorial: Compensation of the energy

Week 5 Lab 4: Short circuit analysis of the network

Week 13 Lab 9: Over current

protection

Week 6 Lab 5: Genetic Algorithm

Tutorial: Voltage drops Week 14

Lab 10: Power quality

disturbances

Week 7 Lab 6: Reconfiguration of the network using Genetic Algorithm

Week 15 Tutorial: Reliability


Teaching Methods

Description




Assessment Methods

Description (%)






Total 100 %

Learning Outcomes


On completion of this course, the students will be able to:

1. Outline distribution practices for MV supplies and LV installations.

2. Analyse the operating parameters of an electrical energy distribution system 3. Apply analytic techniques pertaining to primary distribution systems.

4. Use basic design principles for distribution substations and facilities.

5. Discuss computational algorithms of distribution system analysis and operation. 6. Explain protective schemes and apply them to MV and LV protection

101


Mandatory Literature • Electric Power Distribution System Engineering, Turan Gönen, McGraw-Hill Publishers 1986

Recommended Literature A.S. Pabla, 2008, Electric Power Distribution, 11th Ed., McGraw Hill USA [ISBN: 9780070482852]










Project 1 11 11

Total Workload 125


102

Course Code : EEE370 Course Name:INDUSTRIAL ELECTRONICS



Course Description

Review of four layer devices and their applications. Gate control techniques in power switching elements and their

protection. Introduction to solid-state energy conversion. AC/DC, AC/AC, DC/AC and DC/DC converters. Introduction to

control of electrical drives. Industrial control systems: Relay circuits; ladder diagrams. Sequential control circuits. Case studies.

Course Objectives

This course aims to introduce the student to the electronic components and systems which they are likely to encounter in a

range of industries. They will learn to describe the operation of power conversion circuits and compare the advantages and disadvantages of different topologies, to select a power converter for a given drive system.

Explain how robots are used for industrial automation and for what purpose and compare the advantages and disadvantages

of different actuation systems (electrical, hydraulic and pnemautic).

Course Content

(weekly plan)


Week 2 Review of four layer devices and their applications

Week 10 Introduction to control of electrical drives

Week 3 Gate control techniques in power switching

elements and their Week 11

Industrial control systems; Relay circuits;

Week 4 Introduction to solid state energy conversion Week 12 Ladder diagrams

Week 5 AC/DC and AC/AC converters Week 13 Sequential control circuits

Week 6 DC/AC and DC/DC converters Week 14 Programmable Logic Controllers



Teaching Methods

Description


• Interactive


Assessment Methods

Description (%)






Total 100 %

Learning Outcomes


Upon successful completion of this course, the student will be able to: 1. Describe how electronic input and output circuits are used to control automated manufacturing and/or process systems;

2. Identify basic elements used for input, output, timing, and control;

3. Design the control programming using PLC that will perform a specified operation 4. Apply performance criteria in the design of basic amplifier circuits and verify that the criteria were met.

5. Demonstrate competency in the fundamental concepts of DC and AC Electronics through the construction, evaluation

and troubleshooting of typical DC and AC circuits


Mandatory Literature • M. H. Rashid; Power Electronics, Power Electronics: Circuits, Devices, and Applications, Prentice Hall, 1988











Project 1 11 11

Total Workload 125


103

Course Code : EEE371 Course Name:STATIC POWER CONVERSION



Course Description Power switches and their characteristics. Power converter definitions, classification. VTA method. Midpoint and bridge

rectifiers: non-ideal commutation, harmonics, input power factor, utility-factor, winding utilization and unbalances in

rectifier transformers. Applications.

Course Objectives

This course is designed to give seniors in Electrical and Electronics Engineering an ability to use modern power

semiconductor devices in power electronics applications and to integrate them into overall designs of static converters which

perform interconversion of electrical energy. Operation principles, terminal characteristic and technical features of line-commutated ac-to-dc converters are also presented within the scope of this course.

Course Content

(weekly plan)

Week 1 Introduction

Week 9 Modelling For Operation at Steady-State,

Modelling for Operation at Transient-State

Week 2 Classification and Historial evolution of power semiconductor devices Week 10

Line commuted rectifier circuits:Assumptions, definitions and circuit nomenclature.

Performance Parameters

Week 3

SCRs. Power Bipolar Junction Transistors

Week 11

Single-phase circuits. Uncontrolled half-wave.

Fully-controlled half-wave. Principles of

Freewheeling Operation

Week 4

Power Bipolar Junction Transistors. Power

MOSFETs Week 12

Bi-phase circuits.Fully-controlled half-wave.

Single-phase Bridge circuits.Uncontrolled,

half-controlled, fully-controlled

Week 5

Analysis and design of cooloing systems for

power electronics Week 13

Converter operation; Operation in

Reectification and Inversion modes by firing

angle control.

Week 6

The sources of power losses in power

semiconductors and Basic forms of heat

transfer

Week 14

Four-quadrant operation by the use of reverse

connected converters and firing angle control

Week 7

RL load supplied from a d.c. source via a

single thyristor. RL load supplied from a

single-phase ac source via back-to-back connected thyristor pair, Transient-free

switching.

Week 15

Overlap Phenomenon Voltage Regulation

Power Factor Rectifier Harmonics VTA

(Voltage Time Area) Method

Week 8 Midterm Exam

Week 16 Final Exam

Teaching Methods



Assessment Methods

Description (%)






Total 100 %

Learning Outcomes


1. Explain the principles underlying Static Power Conversion 2. Apply Power Conversion to find solutions to complex problems

3. Analyze parameter choices in the use of converters and inverters

4. Identify a switching power -pole as the basic building block and to use Pulse Width Modulation to

synthesize the desired output

5. Modelling of AC to DC converters

6. Modelling of DC to DC converters


Mandatory Literature • "Power Electronics: Circuits, Devices and Applications" Muhammed H. Rashid, 1993








104




Project 1 11 11

Total Workload 125


105

Course Code : EEE372 Course Name:POWER ELECTRONICS



Course Description

Electricity plays a vital role in supplying energy to computers, electronics, industrial processes, trains and many other

applications.This course provides in depth knowledge of power converter topologies, their characteristics and principles for

their control: Semiconductor power devices and switching circuits, Complementary components and systems, AC-to-DC converters, AC-to-AC converters, DC-to-DC converters, DC-to-AC converters, Switching power supplies.

Course Objectives To learn theory of power electronics and to obtain practical skills.To prepare students to know the characteristics of different

power electronicsswitches and selection of components for different applications. To develop students with an understanding of the switching behaviour anddesign of power electronics circuits such as AC/DC and DC/DC converters.

Course Content

(weekly plan)

Week 1 Introduction to power electronics. Week 9 DC to DC Boost Converter.

Week 2 Fundamentals: Fourier series, RLC Circuits Week 10 DC to DC Buck- Boost Converter.

Week 3 Diode, SCR Week 11 PWM-Inverters.

Week 4 Mosfet, IGBT Week 12 Resonant Pulse Inverters.

Week 5 Half-Wave Rectifiers. Week 13 Power Supplies.

Week 6 Full-Wave Rectifiers. Week 14 Passive filters.

Week 7 DC to DC Buck Converter Week 15 Final Review


Week 1 Beginning of classes Week 9 Postmidterm review

Week 2 Week 10 DC to DC Buck Converter

Week 3 Diode, SCR Week 11 DC to DC Boost Converter.

Week 4 Mosfet, IGBT Week 12 DC to DC Buck- Boost Converter.

Week 5 Half-Wave Rectifiers. Week 13 PWM-Inverters.

Week 6 Full-Wave Rectifiers. Week 14 Matlab examples

Week 7 Matlab examples Week 15 Final Review


Teaching Methods

Description


• Interactive


Assessment Methods

Description (%)




Midterm

Exam



Total 100 %

Learning Outcomes


After completion of this course, students will be able to:

1. Understand the components of power electronics and learn their key characteristics 2. Use steady-state, average, and small-signal models of PWM switch in power converter analysis and design.

3. Use various methods to analyse power electronics circuits.

4. To analyze and design an AC/DC rectifier circuit. 5. Understand the role power electronics play in the improvement of energy usage efficiency and the development of

renewable energy technologies.


Mandatory Literature • Power Electronic by Ned Mohan Power Electronics (Circuits, Devices, and Applications), Muhammed H. Rashid,

Prentice Hall 3’rd edition

Recommended Literature • M. Mahan, T. Undeland, W.P Robbins: "Power Electronics": Converters, Applications and Design, Wiley, 2004.

• J. Kassakian, M. Schlecht, G. Verghese: Osnove energetske elektronike I dio (prijevod), Graphis, 2000.




106







Project 1 11 11

Total Workload 125


107

Course Code : EEE373 Course Name:LOW VOLTAGE POWER SYSTEMS



Course Description Power calculations in distribution systems. Power measurements. Secondary networks and load characteristics. Voltage drop

and power loss calculation in networks. Voltage drop and power loss calculations for selection of conductor cross-sections.

Low voltage power distribution in buildings. Selection of fuses, contactors and power switches. Grounding.

Course Objectives

The objectives of this course are to learn the operation of low voltage power systems. Topics are: Introduction to energy

systems. Basic knowledge and electrical devices. Single phase and three phase power calculations. Power factor correction.

Power system modeling. Distribution and transmission cables. Short circuit calculations. Fuses, conductors and circuit breakers in power systems. Measurement methods in low voltage systems. Earthing, concepts and methods. Introduction to

touch and step voltages.

Course Content

(weekly plan)

Week 1 Introduction to energy systems. Week 9 Postmidterm Review

Week 2 Single phase and three phase power

calculations Week 10

Fuses

Week 3 Power factor correction

Week 11 Conductors and circuit breakers in power systems

Week 4 Power system modeling Week 12 Measurement methods in low voltage systems

Week 5 Distribution and transmission cables

Week 13 Voltage drop and power loss calculations for

selection of conductor cross-sections

Week 6 Short circuit calculations Week 14 Introduction to touch and step voltages.

Week 7 Load characteristics Week 15 Final Review


Teaching Methods

Description


• Interactive


Assessment Methods

Description (%)






Total 100 %

Learning Outcomes


After finishing this course the student will be able to

1. Explain operation of low voltage power system

2. Analyze low-voltage electric power systems. 3. Calculate single phase and three phase voltage, current and power in the system

4. Design and maintainlow-voltage electric power systems

5. Model low volatge electric power systems 6. Design a basic electrical distribution system for a building providing overload, short circuit and effective

protection in line with current regulations and good practice


Mandatory Literature • Analysis and Design of Low-Voltage Power Systems: An Engineer's Field Guide, Ismail Kaşıkçı, Wiley-VCH; 1

edition











Project 1 11 11

Total Workload 125

108


109

Course Code : EEE374 Course Name:COMPUTER RELAYING IN POWER SYSTEMS



Course Description

This course describes in detail the function block diagram of a computer relay and operating principles of different types of

relays. Also it gives main classification of relay types and their behavior, mathematical background for understanding

relaying algorithms and also examining line relaying algorithms and protection of transformers, machines and buses. It will be discussed about several hardware related question-such as the computer hierarchy in the substation, subsystems of a

computer relay and analog to digital converters as and system relaying and control.

Course Objectives

The goal of this course is to understand the function block diagram of a computer relay and operating principles of different types of relays. Learning about main classification of relay types and their behavior, mathematical background for

understanding relaying algorithms and also examining line relaying algorithms and protection of transformers, machines and

buses. It will be discussed about several hardware related question-such as the computer hierarchy in the substation, subsystems of a computer relay and analog to digital converters as and system relaying and control.

Course Content

(weekly plan)

Week 1 Introduction to computer relaying Week 9 Postmidterm Review

Week 2 Relaying practices I Week 10 Protection of transformers, machines and buses

Week 3 Relaying practices II Week 11 Hardware organization in integrated systems

Week 4 Mathematical basis for protective relaying algorithms

Week 12 System relaying and control

Week 5 Digital filters Week 13 Relaying applications of traveling waves

Week 6 Transmission line relaying Week 14 Wide area measurement application



Teaching Methods

Description


• Interactive


Assessment Methods

Description (%)




Midterm

Exam



Total 100 %

Learning Outcomes


1. Acquire a good understanding of digital relays 2. Design power system component protection systems using digital relays

3. Demonstrate knowledge of recent practices for relay testing, modeling and simulation

4. Apply and adapt applications of mathematics in the analysis, comparison, interpretation of various protection schemes 5. Demonstrate familiarity with the recent advances in the area of computer - based relaying ,substation automation and

wide area protection


Mandatory Literature • Arun G. Phadke and James S. Thorp, Computer Relaying for Power Systems, Second Edition, Wiley, 2009.











Project 1 11 11

Total Workload 125


110

Course Code : EEE 375 Course Name:POWER SYSTEM COMMUNICATION



Course Description

This course gives description to parallel and distributed processing techniques that are applied to power system optimization

and control. It will also give some briefing to load flow in power systems and basic theories about information system

architecture in modern power system control centers. Another feature of the course is learning about transmission congestion management, ancillary services management, state estimation and voltage/var optimization and control.

Course Objectives The objective of this course is to introduce the parallel and distributed processing techniques that are applied to power

system optimization and control. Understanding load flow in power systems. Learning about transmission congestion management, ancillary services management, state estimation and voltage/var optimization and control.

Course Content

(weekly plan)


Week 2 Parallel and Distributed Processing of Power Systems

Week 10 Parallel and Distributed State Estimation

Week 3 Information System for Control Centers Week 11 Distributed Power System Security Analysis

Week 4 Combinational Functions and Circuits

Week 12 Hierarchical and Distributed Control of

Voltage/VAR

Week 5 Common Information Model and Middleware

for Integration Week 13

Transmission Congestion Management Based

on Multi-Agent Theory

Week 6 Parallel and Distributed Load Flow Computation

Week 14 Special Topics in Power Systems Information system



Teaching Methods

Description • Interactive Discussions and group workS • Tutorials and Labs

Assessment Methods

Description (%)






Total 100 %

Learning Outcomes


After the course the student should be able to:

1. Describe the functions of the primary equipment in the power system that is relevant for protection, automation

and control. 2. Analyze substations and simple power systems in terms of reliability protection, automation and control needs.

3. Describe the function and architecture of information and control systems used for protection, automation and

control of power systems. 4. Describe the function and architecture of communication systems used for information & control systems for

power system control.

5. Describe the importance of information & control systems for the ability to connect large amounts of renewable power sources.

6. Analyze and develop basic systems for substation automation and protection.

7. Analyze and develop basic information & control systems for system-wide control from control rooms, e.g. SCADA systems and EMS applications.


Mandatory Literature • Mohammad Shahidehpour and Yaoyu Wang, Communication and Control in Electric Power Systems, Wiley, 2003.











111


Total Workload 125


112

Course Code : EEE 376 Course Name: SMART GRID



Course Description In the course Smart Electrical Networks and Systems you will apply your electrical engineering competence on projects that

are of high relevance in the field that is called ‘smart grids’. You will also get the basic concepts on evaluating the business

potential of different technical innovations.

Course Objectives The aim of this course is to examine a set of emerging concepts, technologies, applications, and business models, and the

complex trade off decisions related to transforming the nations century-old, centralized power grid into a more climate,

sustainable-energy, and consumer-friendly “Smart Grid”.

Course Content

(weekly plan)

Week 1 What Is The Smart Grid?

Week 9 The Smart Grid-Enabling Demand Response

The Energyport As Part Of The Smart Grid

Week 2 Electric Energy Efficiency In Power Production & Delivery

Week 10 Policies & Programs To Encourage End-Use Energy Efficiency

Week 3 Electric End-Use Energy Efficiency Week 11 Market Implementation

Week 4 Using Smart Grid To Evolve The Perfect

Power System Week 12

Efficient Electric End-Use Technology

Alternatives

Week 5 DC Distribution & The Smart Grid Week 13 Demand-Side Planning

Week 6 The Intelligridism Architecture For the Smart

Grid Week 14

Demand-Side Evaluation



Teaching Methods



Assessment Methods

Description (%)






Total 100 %

Learning Outcomes


1. describe the benefits and business opportunities that a smart grid will address

2. develop models for the impact of local generation on the voltage variations in a system

3. describe the innovation process of a product development project

4. analyze the influence of fast measurements and data acquisition on control and automation properties of the

electric power network

5. present the recent findings about smart electrical networks

6. judge the needs and business opportunities from a system perspective that future’s electrical networks must have

7. understand the different methods with which local generation can be installed in the power system

8. be aware on where and how information control systems and monitoring/diagnostic systems can be implemented

in the power grids;


Mandatory Literature • Clark W. Gellings, The Smart Grid Enabling Energy Efficiency And Demand Response, The Fairmont Press, 2009.












113

Total Workload 125


114

Course Code : EEE 377 Course Name:SUSTAINABLE DISTRIBUTED POWER GENERATION



Course Description

The first course part about heat and power technology brings up techniqes for large- and small scale electricity and heat

generation in power plants fired on biomass, oil, natural gas or coal. Thermodynamic power cycles and analysis,

combustion, boilers, emissions, life-cycle-cost and availability are all included in this course part. The second part of the course brings up nuclear reactor technology and nuclear power safety and focuses on BWR and PWR technologies. Here

material aspects, fuel cycles and plant control are included. Environment and security issues are brought up.

Course Objectives

The goal of this course is to provide students with solid basic understanding in following areas: introduction to unconventional sources of unconventional sources of electricity; energy conversion, generators selection, voltage levels

selection, storage of energy, regulators selection, power converters; economic implications of usage of non-conventional

energy sources; connecting to the power system network; management and regulation.

Course Content

(weekly plan)

Week 1 Introduction

Week 9 Principles of Control of Distributed Generation

Systems

Week 2 Distributed Generation: An Introduction

Week 10 Economic and Financial Aspects of Distributed Generation

Week 3 Combustion Engine Generator Sets Week 11 The regulatory Environment

Week 4 Combustion Turbines Week 12 Combined Heat and Power (CHP)

Week 5 Photovoltaic systems Week 13 Electric Power Distribution systems

Week 6 Microturbines Week 14 Installation and Interconnection

Week 7 Fuel Cells Week 15 Fuels

Week 8 Midterm Review Week 16 Final Exam

Teaching Methods

Description • Interactive Discussions and group works • Tutorials and Labs

Assessment Methods

Description (%)




Midterm

Exam



Total 100 %

Learning Outcomes


1. Understand the principles of different power generation methods, both conventional and renewable

2. Analyze the conventional power methods thermodynamically 3. Make a simple economical assessment of a power plant

4. Perform an environmental assessment and suggest measures for emission control in a power plant

5. Compare different power generation alternatives and choose the most suitable for given conditions 6. Understand physics of nuclear power and how such a system can be built up

7. Describe some of the components in a power plant


Mandatory Literature • Ann-Marie Borbely and Jan F. Kreider, Distributed Generation The Power Paradigm for the New Millenium, CRC

Press LLC, 2001












Total Workload 125


115

Course Code : EEE 378 Course Name:POWER SYSTEM QUALITY



Course Description This course will provide students with overall understanding of the power quality problems and how do they interact with

the system. In addition, possible measures to solve the power quality problems will also be discussed in this course.

Course Objectives

The aim of this course is to teach some theoretical and practical aspect of power quality and evaluations that are very difficult to organize the material in any cohesive manner. The evaluations can include everything from transmission system

fault studies to transient voltage surge suppression for computer data lines. To make the problem even more difficult, these

concerns need to be explained so that they can be understood by electric utility engineers, facility managers, equipment designers, and end users.

Course Content

(weekly plan)


Week 2 Terms and Definitions Week 10 Long Duration Voltage Variations

Week 3 Voltage Sages and Interruptions Week 11 Distributed Generation and Power Quality

Week 4 Transient Over Voltages Week 12 Wiring and grounding

Week 5 Fundamental of Harmonics Week 13 Monitoring power quality

Week 6 Harmonic Solutions Week 14 Voltage Unbalance



Teaching Methods

Description • Interactive Discussions and group works Tutorials and Labs

Assessment Methods

Description (%)






Total 100 %

Learning Outcomes


1. Explain the various power quality phenomenon 2. Analyse the characterization of voltage sag and short interruptions

3. Describe the voltage sag –equipment behavior and assessment methods

3. Discuss the mitigation techniques of voltage sag and interruptions 4. Explain the procedure of harmonic evaluation on the utility and end user facilities

5. Discuss the power quality issues with Distribution Generation integration.


Mandatory Literature • Roger C. Dugan, Mark F. McGranaghan, Surya Santoso, and H. Wayne Beaty, Electrical Power Systems Quality,

McGraw Hill, Second Edition, 2004












Total Workload 125


116

Course Code : EEE 379 Course Name:INDUSTRIAL UTILISATION OF ELECTRICAL ENERGY



Course Description

Extensive electricity utilization represents one of the hallmarks of a modern society. In this course, the basic concepts related

to use of electric energy in various industrial applications and important issues related to such usage will be examined. The

course also discusses issues related to economics of energy system usage and the concept of load management. Understanding the analytical methods and modern tools for solution of problems associated with utilization of electric

energy in industrial sectors.

Course Objectives

This course is designed to give seniors in Electrical and Electronics Engineering an ability to represent extensive electricity utilization for the hallmarks of a modern society. Use of electric energy in various industrial applications, issues related to

economics of energy system usage and the concept of load management are also presented within the scope of this course.

The primary objective of the course is to provide students with the skills to understand the analytical methods and modern tools for solution of problems associated with utilization of electric energy in industrial sectors.

Course Content

(weekly plan)


Week 2 Industrial Load Characteristic Week 10 Electrolytic Process

Week 3 Electrical Drives and Industrial Applications Week 11 Electric Traction

Week 4 Industrial Power Factor Control

Week 12 Economics of Electric Power Supply and Utilization

Week 5 Electric Heating and Welding Week 13 Demand Side Management – Part I

Week 6 Illumination Engineering Week 14 Demand Side Management – Part II



Teaching Methods

Description


• Interactive Discussions and group works Tutorials and Labs

Assessment Methods

Description (%)






Total 100 %

Learning Outcomes


After the course the student should be able to

1. describe different sources of primary energy and assess their environmental impact.

2. describe the utilisation of energy in the present day society.

3. understand and describe the function of passive systems. 4. Maintain various electric heating and welding equipments used in industries.

5. Maintain Electric Drive and elevator used in industries.

6. Maintain Electric Traction system. 7. Maintain various domestic electrical appliances.

8. Student will be able to design Illumination systems for variousapplications.


Mandatory Literature • E.R. Laithwaite and L. L. Freris, Electric Energy: Its Generation, Transmission and User, McGraw Hill Co., 1984.

Recommended Literature • C. L. Wadhwa, Generation, Distribution and Utilization of Electrical Energy, 2006

• C. O. Bjork, Industrial Load Management - Theory, Practice and Simulations, Elsevier,











117

Total Workload 125


118

Course Code : EEE 380 Course Name: INTRODUCTION TO ROBOT CONTROL



Course Description

Introduction to robotics. Robot kinematics: Position analysis, The Denavit-Hartenberg representation. Differential motions

and velocities: The manipulator Jacobian, derivation of the Jakobian, inverse Jakobian. Dynamic analysis and forces: A short

review of Lagrangian mechanics, dynamic equations for MDOF robots, static force analysis of robots. Trajectory planning. Actuators. Sensors. Image processing and analysis with vision systems. Robot control: Independent joint control,

multivariable control, force control, variable structure and adaptive control, fuzzy logic control.

Course Objectives

Dynamics: Review of Lagrangian dynamics, actuator and sensor dynamics. Trajectory planning: Cartesian space, joint space, interpolation methods. Position control: Independent joint control, PID and feed forward control, computing torque

and inverse dynamics, resolved motion control, control of orientation. Force Control: Stiffness and compliance, network

models.

Course Content

(weekly plan)


Week 2 Introductory Material and Review Week 10 Actuators

Week 3 Kinematics of Position Week 11 Sensors

Week 4 Differential Motions Week 12 Vision Systems

Week 5 Robot Dynamics and Force Control Week 13 Fuzzy Logic – Part I

Week 6 Path and Trajectory Planning Week 14 Fuzzy Logic – Part II



Teaching Methods


Assessment Methods

Description (%)






Total 100 %

Learning Outcomes


After this course, the candidate should be able to:

1. Design different applications of robotic systems 2. Describe mechanical robotic structures and systems

3. Derive the mathematics involved

4. Do path generation and control of simple robotic systems.


Mandatory Literature • “Introduction to Robotics – Analysis, Systems, Applications”, Saeed B. Niku, 2001, Prentice Hall. ISBN: 0-13-

061309-6.

Recommended Literature • “Robot Dynamics and Control”, M. W. Spong, Seth Hutchinson and M. Vidyasagar, 2006, John Wiley and Sons.

ISBN: 0-471-64990-2.











Total Workload 125


119

Course Code : EEE 381 Course Name:PROCESS CONTROL



Course Description

Introduction to process control. Analog and digital signal conditioning. Sensors: Thermal, mechanical, optical. Final control:

Industrial electronics, actuators, control elements. Discrete-state process control: Relay controllers and ladder diagram,

PLCs. Controller principles: Control system parameters, controller modes. Analog controllers. Digital control: Computers in digital control, process-control networks. Control-loop characteristics.

Course Objectives To provide an overview of process control and give introductory concepts. To provide the dynamic behavior of processes.

To consider feedback and feed-forward control methods for process control.

Course Content

(weekly plan)

Week 1 Introduction to Process Control Week 9 Control System Instrumentation

Week 2 Theoretical Models of Chemical Processes Week 10 Overview of Control System Design

Week 3 Laplace Transforms, Transfer Function and

State-Space Models Week 11

Dynamic Behavior and Stability of Closed-

Loop Control Systems

Week 4 Dynamic Behavior of First-Order and Second-

Order Processes Week 12

PID Controller Design, Tuning, and

Troubleshooting

Week 5 Dynamic Response Characteristics of More Complicated Processes

Week 13 Frequency Response Analysis

Week 6 Development of Empirical Models from

Process Data Week 14

Control System Design Based on Frequency

Response Analysis

Week 7 Feedback Controllers Week 15 Feed-forward and Ratio Control


Teaching Methods


Assessment Methods

Description (%)






Total 100 %

Learning Outcomes


1. Implement dynamic models with or without controllers and perform simulations

using computational tools. 2. Analyze process stability and dynamic responses.

3. Empirically determine process dynamics from step response data.

4. Evaluate dynamic performance of processes via benchmarks and statistics. 5. Read block diagrams and process and instrumentation diagrams.

6. Know frequency analysis of dynamic processes.

7. Design feed forward control, cascade control and Smith predictors. 8. Know MIMO process interactions.


Mandatory Literature • Process Dynamics and Control, D.E. Seborg, T.F. Edgar, D.A. Mellichamp, 2004, 2nd Edition, John Wiley & Sons,

Inc. ISBN: 978-0-471-00077-8. Book Web page: www.wiley.com/college/seborg

Recommended Literature • Practical Process Control Using Control Station 3.7, Doug J. Cooper, 2004, Control Station LLC. Book Web page:

www.controlstation.com











Total Workload 125

120


121

Course Code : EEE 383 Course Name:DISCRETE TIME CONTROL SYSTEMS



Course Description

Review of discrete-time systems and the z-transform. z-plane analysis of discrete-time control systems: Sampling and

reconstruction, the pulse transfer function, realization of digital controllers and digital filters. Stability analysis of closed-

loop systems in the z-plane, transient and steady-state response analysis. State-space analysis. Pole placement and observer design. Polynomial equations approach to control systems design. Quadratic optimal control systems.

Course Objectives

A working knowledge of representation, analysis and design of computer control systems. Time-domain representation of

discrete-systems, frequency domain analysis (z-transform), state space techniques and introduction to the design of computer controller schemes. To model and analyze computer-controlled systems using simulation tools like MATLAB. Emulating

real-time computer controlled systems with the use of analog computers, analog-to-digital and digital-to-analog converters.

To design, implement, and verify computer controlled systems with all these tools combined.

Course Content

(weekly plan)

Week 1

Introduction. Digital control systems.

Quantizing and quantization error. Week 9

Design based on the root-locus method. Design

based on the frequency-response method.

Analytical design method.

Week 2

Data acquisition, conversion, and distribution

systems. Week 10

Design based on the root-locus method. Design

based on the frequency-response method.

Analytical design method.

Week 3

Introduction. The z transform. z transforms of

elementary functions. Week 11

Introduction. State-space representations of

discrete-time systems. Solving discrete-time

state-space equations.

Week 4

Important properties and theorems of the z

transform. The inverse z transform. z transform

method for solving difference equations.

Week 12

Introduction. State-space representations of

discrete-time systems. Solving discrete-time

state-space equations.

Week 5

z-Plane Analysis of Discrete-Time Control

Systems Week 13

Pulse-transfer-function matrix. Discretization

of continuous-time state-space equations.

Liapunov stability analysis.

Week 6

Introduction. Mapping between the s plane and

the z plane. Stability analysis of closed-loop

systems in the z plane. Transient and steady-state response analysis.

Week 14

Pulse-transfer-function matrix. Discretization

of continuous-time state-space equations.

Liapunov stability analysis.

Week 7

Introduction. Mapping between the s plane and

the z plane. Stability analysis of closed-loop systems in the z plane. Transient and steady-

state response analysis.

Week 15

Final Review

Week 8 Midterm Exam

Week 16 Final Exam

Teaching Methods

Description



Assessment Methods

Description (%)






Total 100 %

Learning Outcomes


1. Distinguish mathematical models of linear discrete-time control systems using z domain transfer functions and

state-space models.

2. Analyze transient and steady state behaviors of linear discrete-time control systems. 3. Determine whether performance of linear discrete-time control systems meet specified design criteria

4. Do stability analysis in the z domain. 5. Design controllers for linear discrete-time control systems so that their performance meetspecified design criteria

6. Perform root locus design in z domain.

7. Perform frequency domain design. 8. Verify performance of linear discrete-time control systems using MATLAB and Simulink.


Mandatory Literature • Discrete-Time Control Systems, Katsuhiko Ogata, 2000, 2nd Edition, Prentice Hall. ISBN: 0-13-034281-5




122









Total Workload 125


123

Course Code : EEE 384 Course Name:PROCESS INSTRUMENTATION AND CONTROL



Course Description

This course focuses on the four major areas in automatic control systems: primary measurements, signal transmission,

automatic controllers, and the final control elements. Describing typical installations as applied in various pulp and

papermaking processes shows how these areas work together as systems. This course also provides a basic introduction to computers and their use in the paper industry.

Course Objectives

Students will demonstrate knowledge of process variables, elements, and instruments as related to process variables

measurement and control. Students will identify, define, and describe measuring devices, control loops, control loop elements, control valves and regulators. Students will demonstrate knowledge of symbology, process diagrams,

instrumentation, sketching and troubleshooting.

Course Content

(weekly plan)

Week 1 Course Introduction Week 9 Postmidterm Review

Week 2 Instrumentation and Control

Methods/Equipment – Part I Week 10

Signal Transmission – Part II

Week 3 Instrumentation and Control Methods/Equipment – Part II

Week 11 Automatic Control – Part I

Week 4 Different Process Measurements – Part I Week 12 Automatic Control – Part II

Week 5 Different Process Measurements – Part II Week 13 Final Control Elements

Week 6 Signal Transmission – Part I Week 14 Process Applications



Teaching Methods

Description



Assessment Methods

Description (%)






Total 100 %

Learning Outcomes


Upon successful completion of this course, the student should be able to:

1. Define primary measurement and signal transmission principles and equipment. 2. Define the use of automatic controllers in automated control systems.

3. Describe the use of final control elements in automated control systems.

4. Explain measurement, signal transmission, controller, and control element applications for common process variables


Mandatory Literature • Platt, George. Process Control - A Primer for the Nonspecialist, 2nd Ed., TAPPI Publications, 1998.

Recommended Literature • Smook, G.M. Handbook for Pulp and Paper Technologist, 3rd Ed., Atlanta, GA: TAPPI Publications, 2002. (Chapter

24: Process Control)











Total Workload 125


124

Course Code : EEE 391 Course Name:HDL BASED LOGIC CONTROL



Course Description

Introduction to electronic design automation. Hardware modeling in HDL. Event-driven simulation and testbenches. Logic

System, data types, and operators for modeling in HDL. User-defined primitives. Propagation delay models. Behavioral

descriptions in HDL. Synthesis of combinational logic. Synthesis of sequential logic. Synthesis of language constructs. Switch-level models. Rapid prototyping with FPGAs.

Course Objectives To learn HDL based logic design including event-driven simulation and testbenches, Logic system, data types, and operators

for modeling in HDL.

Course Content

(weekly plan)

Week 1 Introduction to course Week 9 Postmidterm Review

Week 2 Introduction to HDLs Week 10 Procedure in VHDL

Week 3 Combinatorial design with VHDL – Part I Week 11 Functions in VHDL – Part I

Week 4 Combinatorial design with VHDL – Part II Week 12 Functions in VHDL – Part II

Week 5 Process in VHDL – Part I Week 13 Case studies – Part I

Week 6 Process in VHDL – Part II Week 14 Case studies – Part II



Teaching Methods


Assessment Methods

Description (%)






Total 100 %

Learning Outcomes


1. Learn VHDL (Very high speed integrated circuit Hardware Description Language).

2. Utilize VHDL to design and analyze digital systems including arithmetic units and state machines. 3.Learn field programmable gate array (FPGA) technologies and utilize associated computer aided design (CAD) tools to

synthesize and analyze digital systems.

4. Learn testing strategies and construct testbenches. 5.Conduct laboratory experiments using an FPGA based development board to prototype digital systems and to confirm the

analysis done in class.


Mandatory Literature • VHDL Starters Guide Sudhakar Yalamanchili Publisher: Prentice Hall , ISBN: 0-13-145735-7 Copyright: 2005












Total Workload 125


125

Course Code : EEE 394 Course Name:EMBEDDED SYSTEMS



Course Description

This is practically-orientated and advanced course in the area of electronics design and applications. It is distinctive in that it

provides a strong digital technology core backed up with applications-led modules. Examples of these applications include

medical and electronics, e-health, intelligent building design, automotive electronics, retail and commerce. Another feature of the course is the substantial amounts of practical work, giving students the confidence with software and digital hardware

implementations using microcontrollers or general system-on-chip the methodology.

Course Objectives The aim of this course is to understand the basic issues related to embedded systems. Also to learn the application of embedded systems including medical and electronics, e-health, intelligent building design, automotive electronics, retail and

commerce.

Course Content

(weekly plan)

Week 1 Introduction

Week 9 Basic control theory: Principles of feedback, logic control and finite state machines.

Week 2

Embedded Microcontrollers: Choosing and

using microcontrollers for embedded system design.

Week 10

Software architectures for implementing

controllers.

Week 3

Development environments for embedded

software. Week 11

Real-time operating systems: Interrupts.

Shared data. Latency. Round-robin architectures.

Week 4

Sensors and Sensory processing: Software

aspects of sensory interfacing. Sampling. Analog acquisition.

Week 12

Single vs. multitasking. Semaphores. Real

time computation.

Week 5

Position and Velocity Measurements. Encoders.

Quadrature Decoding. Week 13

Communication protocols: Communicating

between multiple microcontrollers. RS232, I2C, CAN protocols.

Week 6

Actuators and interfacing: Pulse Width

Modulation (PWM). DC motors. Programming with actuators.

Week 14

Designing distributed applications.



Week 1 Beginning of classes Week 9 Lab 7: Arduino – RFID Module.

Week 2 Lab 1: Arduino – LED, RGB LED, Button Switch.

Week 10 Lab 8: Introduction to Raspberry Pi

Week 3 Lab 2: Arduino – Photoresistor. Servo Motor. Week 11 Lab 9: Implementation of Student Projects

Week 4 Lab 3: Arduino - LCD1602. Potentiometer. Week 12 Lab 10: Implementation of Student Projects

Week 5 Lab 4: Arduino - Ultrasonic Sensor. Infrared

Motion Sensor. Week 13

Lab 11: Implementation of Student Projects

Week 6 Lab 5: Arduino -.7-segment display, Joystick Module and Keypad Module

Week 14 Lab 12: Implementation of Student Projects

Week 7 Lab 6: Arduino - Buzzer Week 15 Lab 13: Presentation of Projects


Teaching Methods


Assessment Methods

Description (%)






Total 100 %

Learning Outcomes


1. describe the special requirements that are imposed on embedded systems

2. describe the key properties of microprocessor and digital signal processor 3. sketch a design of an embedded system around a microprocessor or DSP

4. explain how microprocessor, memory, peripheral components and buses interact in an embedded system

5. evaluate how architectural and implementation decisions influence performance and power dissipation

6. produce efficient code for embedded systems

126

7. point out the role of the compiler in the embedded system design process

8. summarize the basic properties of a real-time operating system 9. estimate if additional hardware can accelerate a system


Mandatory Literature • The 8051 Family of Microcontrollers, R.H. Barnett, 1995, Prentice Hall


• Programming and Interfacing the 8051, S.Yeralan, A. Ahluwalia, 1995 Addison Wesley

• Microprocessor and Microcontroller Fundamentals, William Kleitz, 1998, Prentice Hall

• Programming and Customizing the 8051 Microcontroller, Myke Predko, 1999, Mc Graw Hill











Total Workload 125


127

Course Code: EEE 396 Course Name: GENERAL METROLOGY



Course Description

Metrology (derived from the Greek word “metron” meaning measure, and logos meaning science, studying) represents a

basis for developing all scientific disciplines. Metrology development is related to human civilization development, which

required consistency of measurements in everyday life. This course will cover all essential topics for better understating the metrology topics and their importance in science through the international traceable and accepted measurement results.

Course Objectives

The main objective of this course is to provide the knowledge to the students regarding the metrology and its importance in

science, industry and everyday life, the international system of the units (SI) and practical realization for the seven base units from the metrology perspective, traceability of the measurement results, dissemination of the measurement results,

metrological infrastructure for the internationally accepted measurement results, and the role the international and national

metrological organizations in establishing and maintaining the metrological infrastructure for the uniform measurements.

Course Content

(weekly plan)

Week 1 Introduction to the topic Week 9 ISO/ IEC 17025 - Technical requirements

Week 2 International System of Units Week 10 Understanding the concept of the

measurement results

Week 3 Basic SI units, definitions, and realizations (Realization of the new SI units)

Week 11 Inter-laboratory comparisons and their importance

Week 4 Derived SI units and permitted units of

measurement outside the SI system Week 12 Statistics in Metrology

Week 5

International organizations in metrology (EU

classification of metrology (legal, scientific,

industrial), international organizations (BIPM, OIML, EURAMET)

Week 13 Measurement uncertainty (type A(statistical))

and type B(non-statistical))

Week 6

National organization in metrology (National

Metrology Institutes, National Accreditation

Bodies, National Standard Bodies)

Week 14

Typical uncertainty sources, estimation and

calculation of uncertainty, calibration procedures, examples from different technical

areas

Week 7 How to prove the metrological competences (National and International level)

Week 15 Quantifying the measurement uncertainty and representing the final measurement results


Teaching Methods

Description


• Discussion and Group Works

• Presentation

• Projects

Assessment Methods

Description (%)






Total 100 %

Learning Outcomes



• Understanding of metrological system, hierarchy of international organizations

• Develop interpersonal, organizational, and problem-solving skills within a managed environment

• Acquire knowledge regarding basic and other SI units, understand definitions, realizations and dissemination of

units, traceability to higher hierarchical levels

• Presentation of measurement results (uncertainty, correction, ...)

• Understanding and correctly solving measurement problems in practice



• Zijad Džemić, Alen Bošnjaković, Haris Memić.: Inspection of Medical Devices (Chapter: Regulations and

Directives - Past, Present and Chapter: Legal Metrology System - Past, Present, Future) Springer Verlag,

Singapore, 2018

• BIPM Evaluation of measurement data - Guide to the expression of uncertainty in measurement, JCGM 100:2008

• BIPM, International vocabulary of metrology – Basic and general concepts and associated terms (VIM), JCGM

200:2012

• Morris, A.S.: Measurement and Instrumentation: Theory and Application, ELSEVIER, 2011

• BIPM: "The International System of Units (SI)"

• ISO/IEC 17025 (General requirements for the competence of testing and calibration laboratories)


https://www.bipm.org/en/publications/

https://www.euramet.org/publications-media-centre/ https://www.oiml.org/en/publications/documents/publication_view?p_type=2&p_status=1

https://www.welmec.org/guides-and-publications/guides/


https://www.bipm.org/en/publications/

https://www.euramet.org/publications-media-centre/

https://www.oiml.org/en/publications/documents/publication_view?p_type=2&p_status=1

https://www.welmec.org/guides-and-publications/guides/

128










Total Workload 125


129

Course Code: GBE 307 Course Name: BIOINFORMATICS

Level: Undergraduate Year: 3 Semester: 5 ECTS Credits: 5


Course Description

The aim of the course is to establish a basic background in the significant and more emerging field of

bioinformatics. Its main subjects are PubMed and Medline databases, DNA- and protein-based bioinformatics tools, as well as several new and emerging information tools. Students are expected to have a working

knowledge of genetics and molecular biology concepts in order to fully benefit from utilization of available

information sources. The course is organized concurrently with a laboratory course in which students are applying bioinformatics in practice in order to analyze DNA, RNA, and protein sequences, as well as to study

phylogeny.

Course Objectives

The cognitive, affective and behavioral objectives of this course are following:

• Showing the importance of bioinformatics as a method to overcome modern biomedical research

problems.

• Enabling skill development in software using, critical evaluation of the results and their interpretation.

• Illustrating how to work with DNA sequences.

• Explaining how to work with protein sequences.

• Illustrating how to construct phylogenetic trees.

Course Content

(weekly plan)

Week 1: Introduction to bioinformatics

Week 2: PubMed

Week 3: Using nucleotide sequence databases

Week 4: Using protein and specialized sequence databases

Week 5: Working with a single DNA sequence

Week 6: Working with a single nucleotide sequence Week 7: Similarity searches on sequence databases

Week 8: MID-TERM EXAM WEEK

Week 9: Comparing two sequences Week 10: Building a multiple sequence alignment

Week 11: Editing and publishing alignments

Week 12: Working with protein 3D structures Week 13: Working with RNA

Week 14: Building phylogenetic trees: NJ method

Week 15: Building phylogenetic trees: UPGMA method Week 16: FINAL EXAM WEEK

LABORATORY CONTENT

Week 1: Beginning of classes Week 2, Lab 1: PubMed

Week 3, Lab 2: Using nucleotide sequence databases

Week 4, Lab 3: Using protein and specialized sequence databases Week 5, Lab 4: Working with a single DNA sequence

Week 6, Lab 5: Working with a single nucleotide sequence

Week 7, Lab 6: Similarity searches on sequence databases

Week 8:MID-TERM EXAM WEEK

Week 9, Lab 7: Comparing two sequences Week 10 Lab 8: Building a multiple sequence alignment

Week 11, Lab 9: Editing and publishing alignments

Week 12, Lab 10: Working with protein 3D structures Week 13, Lab 11: Building phylogenetic trees

Week 14: Preparation for practical exam

Week 15: Practical exam from lab course

Week 16: FINAL EXAM WEEK

Teaching Methods

Description



• Presentations

• Laboratory work

Assessment Methods Description

(%)






Total 100 %

Learning Outcomes

After completion of this course, students should be able to: 1. Use PubMed for article browsing

2. Employ NCBI for sequence analysis

3. Operate single DNA sequences 4. Perform similarity searches

5. Perform multiple sequence alignments

6. Discover different protein databases 7. Create phylogenetic trees

Prerequisite Course(s) None

130


Mandatory Literature Claverie, J. M. & Notredame, C. (2006). Bioinformatics for Dummies, 2nd ed. Hoboken, NJ, USA: Wiley

Recommended Literature Lesk, A. (2008). Introduction to Bioinformatics, 3rd ed. Oxford, UK: Oxford University Press Campbell, A. M. & Heyer, L. J. (2006). Discovering Genomics, Proteomics, and Bioinformatics, 2nd ed. San

Francisco, CA, USA: Benjamin Cummings











Total Workload 125


131

Course Code:GBE 321 Course Name: INTELLIGENT SYSTEMS

Level: Undergraduate Year: 3 Semester: 5, 6 ECTS Credits: 5


Course Description

This course will introduce students to the principles of fuzzy logic systems and artificial neural network systems. The focuses

are on using these methods for solving different problems in Bioengineering. Topic include neural networks architectures and

fuzzy systems, learning algorithms and application, Matlab software - Neural Network Toolbox and Fuzzy Logic Toolbox. Student will acquire knowledge various neural network and fuzzy systems models. Student is also expected to work

effectively as part of a team, to develop interpersonal, organizational, and problem solving skills within a managed

environment and to exercise some personal responsibility.

Course Objectives The cognitive, affective and behavioral objectives of this course are following:

• To provide students with an understanding of the fundamental theory of neural networks, fuzzy logic systems,

eule-based systems and expert system development.

Course Content

(weekly plan)

Week 1: Introduction: Characteristics of ANN and Fuzzy Systems, Biological Neuron, Artificial Neuron, Artificial Neural Networks

Week 2: Phases in ANN Operation, Network Classification

Week 3: Phases in ANN Operation, Network Classification; Week 4: Unsupervised Learning: Hebbian Learning, Competitive Learning & Boltzmann Learning

Week 5: Unsupervised Learning: Hebbian Learning, Competitive Learning & Boltzmann Learning

Week 6: Supervised Learning (Error-Correction learning) and Reinforcement Learning Week 7: Supervised Learning (Error-Correction learning) and Reinforcement Learning


Week 9: Perceptrons and Multilayer Perceptrons Week 10: Neural network Applications

Week 11: Neural network Applications

Week 12: Fuzzy Sets and Operations Week 13: Fuzzy Representation of Structured Knowledge

Week 14: Fuzzy System application and Fuzzy sense in ANN

Week 15: Expert systems based on fuzzy logic and artificial neural network Week 16: FINAL EXAM WEEK

LABORATORY CONTENTS:


Week 2, Lab 1: Introduction to nanotechnology

Week 3, Lab 2: Basic phenomena and ideas of nanoscience and nanotechnology Week 4, Lab 3: Basic concepts of nanostructures

Week 5, Lab 4: Nanostructured materials

Week 6, Lab 5: Quantum dots and quantum wells Week 7, Lab 6: Characterization of nanostructures


Week 9, Lab 7: Smart materials based on nanostructures Week 10 Lab 8: Introduction to sensors

Week 11, Lab 9: Introduction to nanosensors

Week 12, Lab 10: Application of nanosensors Week 13, Lab 11: Practical examples

Week 14: Preparation for practical exam



Teaching Methods

Description




• Consultations

Assessment Methods

Description (%)






Total 100 %

Learning Outcomes


On successful completion of this course, students should be able to:

1. Designing and applying fuzzy logic system to solve engineering control problems where only expert linguistic

knowledge is available, 2. Designing and applying artificial neural network for solving problems,

3. Different aspects and methods of applying fuzzy logic system and artificial neural network in Bioengineering,

4. The difference between the classical algorithmic way of solving the problems and the corresponding learning procedures of artificial neural networks,

5. Technical possibilities, the advantages and the limitations of the fuzzy logic systems, artificial nerual network

systems, 6. Usage of available software tools such as Matlab Neural Network Toolbox.

7. Developing Intelligent Expert Systems for solving complex problems in the Bioengineering area.


132



S. Kumar, “Neural Networks: A Classroom Approach,” McGraw Hill, 2005. J.M. Mendel, “Uncertain Rule-Based Fuzzy Logic Systems”, Prentice-Hall, 2001

Timothy Ross, Fuzzy Logic with Engineering Applications, John Wiley & Sons Inc., 2010.

Sandhya Samarasingh, Neural Networks for Applied Sciences and Engineering: From Fundamentals to Complex

Pattern Recognition, Auerbach Publications, 2006

S. Haykin, “Neural Networks: A Comprehensive Foundation”, 2nd Ed, Prentice-Hall,1999

L. Fausett, “Fundamentals of Neural Networks: Architectures, Algorithms, and Application s”, Prentice-Hall, 1994

Recommended Literature None











Total Workload 125


133

Course Code:GBE 323 Course Name: BIOMEDICAL INSTRUMENTATION



Course Description

This course will introduce the students to basic biomedical engineering technology so that they can understand and

evaluate (and perhaps design) systems and devices that can measure, test, and acquire biological information. The course

will encompass systems of human physiology as well as the bio-signals they generate. The focus will also be on biosensors, transducers, bio-electrodes used for acquisition, and amplifiers for measuring bio-potentials. Some bioethics

will be discussed as well. Introduction to fundamentals of biomedical instrumentation, biomedical sensors and

physiological transducers, biomedical recorders, patient monitoring systems, arrhythmia and ambulatory monitoring instruments, cardiac pacemakers, cardiac defibrillators, MRI and CT systems are the topics covered within the course.

Course Objectives


• Introduction to basic biomedical instrumentation.

• Explaining working principles of biomedical instrumentation.

• Familiarizing students with patients’ security.

• Giving an outline of regulations related to biomedical instrumentation.

Course Content

(weekly plan)

Week 1: Introduction to biomedical instrumentation

Week 2: Biomedical sensors and transducers and bioelectric amplifiers

Week 3:Electrocardiographs

Week 4:Blood pressure measurement and physiological pressure and other cardiovascular measurements and

devices Week 5:Instrumentation for measurement of brain parameters

Week 6:Biological impedance measurement

Week 7: Respiratory system and its measurement Week 8: MID-TERM EXAM WEEK

Week 9: Intensive and coronary care units and pacemakers and defibrillators

Week 10: Electrosurgery

Week 11:Lasers and medical imaging equipment

Week 12:Radiology and nuclear medicine equipment and medical ultrasound

Week 13: Magnetic resonance imaging Week 14: Computed tomography imaging

Week 15: Patients’ security and law


LABORATORY CONTENT:

Week 1-11: This course is designed so that the students get acquainted with all the instruments mentioned in the lectures through a series of virtual labs. Through these labs they will learn how to handle the instruments and, at the same time,

interpret the results they obtain.

Teaching Methods

Description


• Interactive lectures and communication with students,

• Discussions and group work,

• Consultation • Laboratory work

Assessment Methods

Description (%)






Total 100 %

Learning Outcomes


On successful completion of this course, students should be able to:

1. Recall basic terminology related to biomedical instrumentation

2. Recognize biomedical instrumentation

3. Practice on a huge area of biomedical instrumentation

4. Interpret principles of work of biomedical instrumentation

5. Evaluate patients' security and law


(if any) None


Mandatory Literature Raden, J.F. (2010). Handbook of Modern Sensors, Physics, Designs and Applications. New York, NY, USA: Springer-Verlag


Enderle, J. & Bronzino, J. (2011). Introduction to Biomedical Engineering,3rd ed. Burlington, MA, USA: Elsevier Academic Press

Webster, J.G. & Eren, H. (2014). Measurement, Instrumentation, and Sensors Handbook, 2nd ed. Boca Raton, FL, USA: CRC

Press



134









Total Workload 125


135

Course Code: GBE 325 Course Name: BIOMEDICAL SIGNALS AND SYSTEMS



Course Description

This course will introduce students to medical and biomedical engineering concepts. The focuses are on how signal analysis

can clarify the understanding of biomedical signal interpretation and diagnosis. Topics include EEGs, ECGs, EMGs,

respiratory and blood pressure (how they are generated and measured), biosignals as random processes, spectral analysis, wavelets, time-frequency functions, and signal processing for pattern recognition.

Course Objectives


• Introduction to the principles of biomedical signals and systems through ECG, EEG, EMG, NIBP, IBP and

respiratory examples.

• Explaining the importance of engineering in medicine.

• Giving an outline of characteristics of biomedical signals.

• Providing basic concepts about the human heart.

• Providing basic concepts about the respiratory system.

Course Content

(weekly plan)

Week 1: Summary and history of biomedical engineering

Week 2: Cell physiology, bio-potentials, membrane, and active potentials

Week 3: Bioelectrical phenomena, neurons, synaptic transmission

Week 4: Biomedical signals: ECG, EEG, EMG, EOG, respiratory signal, biomedical sensors, biomedical signals

processing

Week 5: Human heart, cardio-cycle, electrocardiogram, vectocardiogram, electrical field of the heart, methods of ECG signal acquisition

Week 6: Methods for acquisition, processing and visualization of ECG signal, heart’s rhythm diagnostic

Week 7: ECG waveform and significant segments, ECG interpretation and diagnostics, pacemaker WEEK 8: MID-TERM EXAM WEEK

Week 9: Respiratory signal, measurement, extraction from ECG, and measuring respiratory signals Week 10: Blood pressure, invasive and non-invasive measurement methods, biosensors and transducers

Week 11: Methods for acquisition, processing and visualization of EEG signal

Week 12: Recording and interpretation of EEG, basic concepts and EEG phenomena Week 13: Electrodes for bio-potential measurement, basic electrochemical processes in the cell and tissues, aspects and

methods of bioimpedance measurement

Week 14: Electrochemical sensors and dialysis: Chemical sensors, separation of the blood components Week 15: Preparation for the final exam

WEEK 16: FINAL EXAM WEEK

LABORATORY CONTENT:

Week 1-11: The laboratory course is designed so that the students go through a series of virtual labs and analyze the studied

equipment: their modes of functioning, components, and therapeutic importance in determining diagnosis.

Teaching Methods

Description




• Consultations • Laboratory work

Assessment Methods

Description (%)






Total 100 %

Learning Outcomes


On successful completion of this course, students should be able to: 1. Define biomedical system modeling

2. Assess different aspects and methods of applying engineering principles in medicine

3. Review characteristics of biomedical signals 4. Arrange principles of design and implementation of medical devices for physiological signal processing

5. Interpret results of ECG and EEG signals


(if any) None


Mandatory Literature Raden, J.F. (2010). Handbook of Modern Sensors, Physics, Designs and Applications. New York, NY, USA: Springer-

Verlag


Enderle, J. & Bronzino, J. (2011). Introduction to Biomedical Engineering, 3rd ed. Burlington, MA, USA: Elsevier

Academic Press

Webster, J.G. & Eren, H. (2014). Measurement, Instrumentation, and Sensors Handbook, 2nd ed. Boca Raton, FL, USA: CRC Press



136









Total Workload 125


137

Course Code: GBE 330 Course Name: BIOSENSORS


Status: Elective Hours/Week: 2 + 2 Total Hours: 30 + 30

Course Description

Biosensors have emerged as an exciting research area due to the integration of molecular biology with electronics to form

devices of modern time. This course will introduce fundamentals of microbiology and biochemistry from engineering

prospective and give a comprehensive introduction to the basic features of biosensors. Types of most common biological agents and the ways in which they can be interfaced with a variety of transducers to create a biosensor for biomedical

applications will be discussed. Focus will be on optical biosensors, immunobiosensors, and nanobiosensors. New

technologies, related research highlights, and main machine interface will also be covered.

Course Objectives


• Introduction to sensors, especially biosensor-technology to genetics and bioengineering students and the ones

who are interested in the subject.

• Explaining basic concepts in biosensing and bioelectronics.

• Clarifying typical problems in biosensing and bioelectronics.

Course Content

(weekly plan)

Week 1: Introduction/Overview of the field and applications of biosensors

Week 2: Measurement accuracy and sources of errors Week 3: Characteristics and operational modes of sensors

Week 4: Static and dynamic characteristics of biosensors

Week 5: Measurement standards Week 6: Sensor networks and communication

Week 7: Preparation for mid-term exam


Week 9: Biological sensing elements

Week 10: Calorimetric biosensors

Week 11: Potentiometric biosensors Week 12: Amperometric biosensors

Week 13: Optical biosensors

Week 14: Piezoelectric biosensors Week 15: Immunobiosensors


LABORATORY CONTENT


Week 2, Lab 1: Introduction/Overview of the field and applications of biosensors Week 3, Lab 2: Measurement accuracy and sources of errors

Week 4, Lab 3: Characteristics and operational modes of sensors

Week 5, Lab 4: Static and dynamic characteristics of biosensors

Week 6, Lab 5: Measurement standards

Week 7, Lab 6: Sensor networks and communication


Week 9, Lab 7: Biological sensing elements

Week 10 Lab 8: Calorimetric biosensors Week 11, Lab 9: Potentiometric and amperometric biosensors

Week 12, Lab 10: Optical biosensors

Week 13, Lab 11: Piezoelectric and immunobiosensors Week 14: Preparation for practical exam



Teaching Methods

Description



• Presentations

• Laboratory work

Assessment Methods

Description (%)






Total 100 %

Learning Outcomes


1. Describe physical operating principles of biosensors

2. Describe the biology of sensing elements 3. Differentiate a variety of biosensors

4. Recognize limitations of biosensors 5. Predict application areas for different types of biosensors

6. Distinguish measurement accuracy and sources of errors in biosensors

7. State technical characteristics of biosensors

8. Discuss measurement standards and sensors network and communication


(if any)

None.

138


Mandatory Literature Raden, J.F. (2010). Handbook of Modern Sensors, Physics, Designs and Applications. New York, NY, USA: Springer-Verlag


Enderle, J. & Bronzino, J. (2011). Introduction to Biomedical Engineering, 3rd ed. Burlington, MA, USA: Elsevier

Academic Press Webster, J.G. & Eren, H. (2014). Measurement, Instrumentation, and Sensors Handbook, 2nd ed. Boca Raton, FL, USA:

CRC Press











Total Workload 125


139

Course Code: CEN

221 Course Name: OBJECT ORIENTED PROGRAMMING


Status: Elective Hours/Week: 2+2 Total Hours: 30+30=60

Course Description

This course is intended to provide in-depth object-oriented problem solving. This class focuses on object-oriented design of

applications. While Java is the language used in the course, and you do much with Java, it is not specifically a Java course. Java

programming language will be used as a tool for implementation and for building graphical user interfaces. Students will

critically analyze and explore programming methodologies and apply their studies to the design and implementation of

contemporary software applications. Topics include objects, classes, methods, UML, inheritance, polymorphism, abstract classes

and interfaces, GUIs and event driven programming, and other advanced issues in OOP.

Course Objectives To give students an introduction to the object oriented programming paradig and equip them with practical application

development skills by usin OOP principles.

Course Content

(weekly plan)

Week 1 Introduction to Java Week 9 Polymorphism

Week 2 Elementary programming in Java Week 10 Abstract Classes and Interfaces

Week 3 Objects and Classes (UML, Identifying classes and

methods, encapsulation, information hiding) Week 11

Graphical User Interface (GUI)

Week 4 Objects and Classes (UML, Identifying classes and

methods, encapsulation, information hiding) Week 12

Event Driven Programming

Week 5 Thinking in Objects (has-a relationships, aggregation, composition, association, UML)

Week 13 Exceptions, Java I/O, Basic Design Patterns for OOD - Project Presentation

Week 6 Inheritance (Is-a relationships) Week 14 Projects

Week 7 Inheritance (Is-a relationships) Week 15 Preparation for final exam

Week 8 Midterm exam -

Teaching Methods

Description



• Practical sessions

• Problem solving or case studies

Assessment Methods

Description (%)






Total 100 %

Learning Outcomes


• Define and describe objects

• Implement programs using object oriented design

• Demonstrate an understanding of the fundamental principles of object-oriented programming

• Explain the difference between functional programming and object-oriented programming

• Demonstrate an understanding of software engineering principles

• Evaluate the quality of programs according to object oriented principles.


Instruction Language English

Mandatory Literature • Introduction to java programming comprehensive version, 9th edition international edition, Y. Daniel Liang

Recommended Liter.

• Java Software Solutions, International edition, 7th edition, Lewis and Loftus, 2012

• Object-Oriented Design & Patterns, 2nd edition, Cay Horstmann, 2006

• Object-Oriented Programming and Java, 2nd edition, Danny Poo et al. , Springer 2007




140







Preparation for Lab/Practical Exam 1 11 20

Total Workload 125


141

Course Code : CEN 254 Course Name: DATA STRUCTURES

Level: Undergraduate Year: 3 Semester: 6 ECTS Credits: 5


Course Description This course covers basic data structures that are used in programming. Implementation and applications of various data

structures together with analysis of algorithms are discussed.

Course Objectives Objective of the course is to introduce to students basic data structures and their implementations: array based lists, linked lists, stacks, queues, hash tables, trees, and graphs; programming techniques using recursion; various searching and sorting

methods such as insertion sort, merge sort, and quick sort and basic analysis of algorithms.

Course Content

(weekly plan)

• Introduction

• Review of Object-oriented programming

• Containers, array based list

• Linked Lists

• Recursion

• Stacks

• Midterm Review

• Midterm Exam

• Queues

• Trees

• Binary Trees, Binary Search Trees

• Graphs

• Graph Algorithms

• Hashing

• Final Review

• Final Exam

Teaching Methods

Description


• Interactivelectures

• Tutorial

Assessment Methods

Description (%)






Total 100 %

Learning Outcomes



1. Demonstrate an understanding of the basic data structures. 2. Explain the difference between various sorting algorithms.

3. Implement various data structures.

4. Demonstrate how data structures are used in programming. 5. Analyse computational complexity of basic algorithms.


(if any)

-


Mandatory Literature • D. S.Malik, Data Structures Using C++, 2nd Edition, Cengage Learning, 2010.


• M. A. Weiss, Data Structures and Algorithm Analysis in C++, Addison Wesley, 2006

• Peter Drake, Data Structures and Algorithms in Java, Prentice Hall, 2005.

• Frank Carrano, Data Structures and Abstractions with Java, 2E, Pearson, 2007.










Seminar / Presentation -

Total Workload 129


142

Course Code: CEN 263 Course Name: COMPUTER NETWORKS



Course Description

This course focuses on the principles and practice of computer networking, with emphasis on the Internet; the structure and

components of computer networks, packet switching, layered architectures, TCP/IP, physical layer, error control, window flow control, local area networks (Ethernet, Token Ring; FDDI), network layer, congestion control, quality of service,

multicast.

Course Objectives

The main objective of this course is to answer the basic question "how do computer networks and internets operate?" in the broadest sense. The course will provide a comprehensive, self-contained tour through all of networking from the lowest

levels of data transmission and wiring to the highest levels of application software. At each level, we will see how the

facilities and services provided by lower levels are used and extended in the next level.

Course Content

Week 1 Introduction to course Week 9 The Transport Layer (3)

Week 2 Computer Networks and The Internet (1) Week 10 The Network Layer (1)

Week 3 Computer Networks and The Internet (2) Week 11 The Network Layer (2)

Week 4 Application Layer (1) Week 12 The Network Layer (3)

Week 5 Application Layer (2) Week 13 The Link Layer (1)

Week 6 Transport Layer (1) Week 14 The Link Layer (2)

Week 7 Transport Layer (2) Week 15 The Physical Layer

Week 8 Midterm Exam -

Teaching Methods

Description • Interactive lectures

• Tutorial

Assessment Methods

Description (%)






Total 100 %

Learning Outcomes


• Discuss basic computer network technology.

• Discuss and explain Data Communications System and its components.

• Identify the different types of network topologies and protocols.

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

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

• Demonstrate the skills of subnetting and routing mechanisms.



Mandatory Literature • James F.Kurose, Keith W. Ross, Computer Networking- A top-down approach, Pearson, 2013


• Dr. K.V. Prasad, Principles of Digital Communication Systems and Computer Networks, Charles River Media, 2003

• Nader F. Mir, Computer and Communication Networks, Prentice Hall, 2006.

• Andrew S. Tanenbaum, Computer Networks, Fourth Edition, Prentice Hall, 2003.

• Diane Barrett and Todd King, Computer Networking Illuminated, Jones and Bartlett Publishers Inc., 2005.











Total Workload 120

143


144

Course Code: CE 113 Course Name: ENVIRONMENT 1



Course Description

The course has been designed to provide scientific knowledge and understanding of environmental issues.

This course seeks to provide basic environmental literacy, as well as to promote more holistic framework of environmental

issues and interdisciplinary approach. The course provides fundamental knowledge and understanding of global and local environmental challenges facing human societies and their future.

Course Objectives

To acquire and apply scientific knowledge about environmental issues.

The course is designed to develop a deeper understanding of interdisciplinary character of environmental issues , as well as to develop pro-environmental values and attitudes that foster environmental responsibility.

Course Content

(weekly plan)

Week 1: Introduction to Environmental science

Week 2:Science of environment Week 3: Evolution,biodiversity

Week 4: Ecosystems

Week 5: Structuring and functioning of ecosystems Week 6: Sustainable biodiversity

Week 7: Human population


Week 9: Natural resources ,land use

Week 10: Geology and minerals

Week 11: Water resources Week 12:Food production and environment

Week 13: Forest management

Week 14: Energy resources-nonrenewable energy Week 15: Renewable energy resources

Week 16: Final Exam

Teaching Methods

Description

• Interactive lectures and communication with

students


Assessment Methods

Description (%)

Quiz 0 % Lab/Practical Exam


Project 0 % Attendance


Presentation 15% Final Exam 40 %

Total 100 %

Learning Outcomes



- Define the principles of environmental science and sustainability -To understand and describe Earth systems( ecosystems, land, water,atmosphere)

- To describe the human population characteristics and growth

-To understand the forms of natural resources and their characteristics - To understand and describe energy resources , nonrenewable and renewable and their impact on environment



• Introduction to EnvironmentalScience;2 nd edition

Open Textbook

C.Zehnder,K.Manoylov, S.Mutiti et al Georgia College and State University


Basics of Environmental Science; 2 nd edition

M.Allaby

Routledge;London and New York; 2002.

Principles of EnvironmentalScience and Technology

K.Saravanan,S.Ramachandran; R.Baskar

New Age Int. Publishers; 2005.





145






Total Workload 54


146

Course Code: CE 114 Course Name: ENVIRONMENT 2



Course Description

The course has been designed to provide scientific knowledge and understanding of environmental issues, and it is

continuation of the course content Environment 1.

This course seeks to provide basic environmental literacy, as well as to promote more holistic framework of environmental issues and interdisciplinary approach. The course provides fundamental knowledge and understanding of environmental

issues , such as climate changes, air pollution, water and soil pollution and waste management.

Course Objectives

To acquire and apply scientific knowledge about environmental issues related to pollution. The course is designed to develop a deeper understanding of interdisciplinary character of environmental issues , as well as

to develop pro-environmental values and attitudes that foster environmental responsibility.

To introduce the basics of environmental and governmental policy related to environmental issues as well as sustainable life.

Course Content

(weekly plan)

Week 1: Introduction to Environment 2

Week 2: Energy resources- Nuclear energy

Week 3: Atmosphere; Air quality

Week 4: Air pollution Week 5: Climate

Week 6: Global climate change

Week 7: Water pollution Week 8: Midterm Exam

Week 9: Water purification technologies

Week 10.Soil pollution Week 11:Waste management

Week 12: Hazardous waste; waste minimization

Week 13: Environment hazards and human health

Week 14: Urban environment-sustainable cities

Week 15: Economy of environmental protection and environmental laws Week 16: Final Exam

Teaching Methods

Description

• Interactive lectures and communication with

students


Assessment Methods

Description (%)

Quiz 0 % Lab/Practical Exam 0%


Project 0 % Attendance 0%



Total 100 %

Learning Outcomes


After this course, the student will be able to: - Define the main environmentalissues

-To understand and describe basic scientific foundations of the quality of atmosphere

- To describe the processes of global climate change -To understand the forms of pollution of natural resources (water, soil)

- To understand and describe the basics of waste management

-To understand the basic economical and legal aspects of environmental issues



• Introduction to EnvironmentalScience;2 nd edition

Open Textbook

C.Zehnder,K.Manoylov, S.Mutiti et al

• Georgia College and State University


Basics of Environmental Science; 2 nd edition

M.Allaby

Routledge;London and New York; 2002.

Principles of EnvironmentalScience and Technology

K.Saravanan,S.Ramachandran; R.Baskar

• New Age Int. Publishers; 2005.




147







Total Workload 54


148

Course Code : MAN 112 Course Name: BUSINESS COMMUNICATION SKILLS

Level : Undergraduate Year : I Semester : I ECTS Credits : 2

Status : Compulsory Hours/Week : 2 Total Hours : 2 x 15 = 30hrs

Course Description

Communication skills are an essential element every employee and manager must have as part of their standard tool set. In this

course, through interactive lectures, self-assessments, role-playing activities and video simulations, students gain practical

experience passed on a flexible, genuine and self-confident approach. They also gain the skills to collaborate on written reports

and oral presentations honing their communications skills.

Course Objectives

This course is designed to help develop strong oral and written communication skills. The student will be given opportunities to

practice writing and editing professional correspondence. Additionally, the student will compose and deliver oral presentations.

Assignments will include the use of inductive and deductive approaches to conveying a variety of messages, and applying the

rules for proper grammar and punctuation.

Course Content

• Business Communication, Management and Success

• Adapting Your Message to Your Audience

• Making Oral Presentations

• Planning, Writing, and Revising

• Designing Documents, Slides, and Screens

• You-Attitude

• Midterm

• Positive Emphasis

• Formats for Letters and Memos and Informative and

Positive Messages

• Persuasive Messages

• E-Mail Messages, Web Writing, and Technology

• Researching Jobs

• Résumés

• Job Application Letters and Job Interviews

• Final Exam preparation

Teaching Methods

Description


• Discussions, presentations and group work

• Lectures and videos

• Problem solving, critical thinking and case studies

Assessment Methods

Description (%)



Project 0 % Attendance 0%


Presentation/Participation 30 % Final Exam 40 %

Total 100 %

Learning Outcomes


1. Determine the appropriate situations in which to use the deductive approach to convey information.

2. Determine the appropriate situations in which to use the inductive approach to convey information.

3. Compose concise and effectively written material (letters, memos, e-mail, reports, newsletters, news releases, and

business presentations) presented in accurately keyed format with correct grammar, usage, and rules of style.

4. Compose and present concise and effectively worded oral reports.

5. Work collaboratively in a team setting by sharing in collective decision-making, meeting deadlines, and presenting

group progress in an oral report.



Mandatory Literature Barbara G. Shwom, Lisa Gueldenzoph Snyder - Business Communication_ Polishing Your Professional Presence (2015,

Pearson)

Recommended Literature -




Laboratory / Practice (15 weeks x Laboratory / Practice hours per week)







Total Workload 56


149

Course Code: MAN 309 Course Name: ENTREPRENEURSHIP



Course Description

This course will provide students with an understanding of issues facing entrepreneurs and an exposure to the skills

involved in addressing them. We will explore how executives should approach making critical decisions during the different phases of an entrepreneurial company's life. Starting from the vantage point of the individual, we will put ourselves in the

shoes of decision makers ranging from technology entrepreneurs to venture capitalists, from real estate developers to

inventors.

Course Objectives

• This course aims to develop the following skills: understand entrepreneurship and the entrepreneurial process as a critical

part of economic system of a country or territory, assess the feasibility of new business concepts and ideas, develop the

ability to manage new business ventures including opportunity recognition, business model construction, market assessment, and financial planning. Identify resources and skills needed to grow a new venture business. Analyze various

exit strategies for new business ventures. Create business plans for development and financing of new business ventures.

Course Content

Week 1 Introduction to entrepreneurship its power and global impact

Week 9 Idea evaluation minimum viable product

Week 2 Opportunity analysis Week 10 Pitching and communicating ideas

Week 3 Entrepreneurial marketing Week 11 The business planning process

Week 4 Founding team and culture Week 12 Entrepreneurial finance: fundraising for

growth

Week 5 Customer discovery and validation Week 13 Financial statements and projections

Week 6 The business model canvas Week 14 Leadership and sustaining growth

Week 7 Operations in small business and managing

growth Week 15 Social entrpreneurship


Teaching Methods

Description • Interactive lectures and communication with students

• Discussions, presentations and group work

• Lectures and videos

• Problem solving, critical thinking and case studies

Assessment Methods

Description (%)






Total 100 %

Learning Outcomes


• Identify and evaluate potentially valuable new business opportunities.

• Develop marketing plan with very few resources leveraging knowledge of internet search engines, and other

digital and unconventional marketing methods.

• Understand how to manage an entrepreneurial organization once it has been established.

• Recognize what critical aspects are needed for a business to be a sustainable enterprise.

• Create a business plan and determine the business and financial model of your company.

• Understand the motivations and role of early investors and financing market.

• Analyze example case situations and recommend solutions to problems faced by the protagonists using

theoretical frameworks and unique but practical action plans.



Mandatory Literature Entrepreneurship, W.D. Bygrave & Zacharakis, 2011 2nd ed. John Wiley & Sons.











150


Total Workload 100


151

Course Code: MAN 107 Course Name: INTRODUCTION TO BUSINESS


Status: Elective Hours/Week: 1+1 Total Hours: 15+15 =30

Course Description This course presents a balanced view of business; the strengths, weaknesses, successes, failures, problems, and challenges.

It provides students a base for more advanced courses.

Course Objectives The objective of this course is to provide students a clear and complete description of the concepts underlying business and

illustrate the dynamism and liveliness of business organizations and people who operate them with real life examples.

Course Content

Week 1 Introduction: Motives and functions of a business Week 9 Managing effectively

Week 2 Business ethics and research responsibility Week 10 Organizational structure

Week 3 Assessing economic conditions (Part I) Week 11 Improving productivity and quality

Week 4 Assessing economic conditions (Part II) Week 12 Motivating employees

Week 5 Assessing global conditions Week 13 Hiring, training and evaluating employees

Week 6 Selecting a form of business ownership Week 14 Creating and pricing products

Week 7 Entrepreneurship and business planning Week 15 Distributing products

Week 8 Midterm exam

Teaching Methods

Description



• Problem solving or case studies

• Exercises

Assessment Methods

Description (%)






Total 100 %

Learning Outcomes


• Be intoduced with the general idea of business

• Be introduced with global conditions influencing the business development

• Understand organizational structure and functions fo its units

• Understand how to deal with employees in the business

• Understand how to set up marketable prices



Mandatory Literature Madura, J. (2005). Introduction to Business, 4 Edition, USA.












Total Workload 119


152

Course Code: MAN 223 Course Name: LEADERSHIP

Level: Undergraduate Year: III Semester: IV ECTS Credits: 3


Course Description The student are learning about theoretical aspects of leadership and how to implement that knowledge into practice.

Course Objectives Upon completion of this course the student will develop a working knowledge of leadership theory and practice. The student

will also develop self-knowledge of his or her leadership philosophy and preferred leadership styles along with a skill for

successful analysis of cases involving leadership.

Course Content

Week 1 Introduction: the nature Week 9 Dyadic relations, attributions

Week 2 Managerial traits and skills Week 10 Charismatic and transformational leadership

Week 3 The nature of managerial work Week 11 Leading change in organizations

Week 4 Perspectives on effective leadership behavior Week 12 Ethical, servant, spiritual

Week 5 Participative leadership, delegation and

empowerment Week 13 Leadership in teams and decision groups

Week 6 Early contingency theories of effective leadership Week 14 Strategic leadership by executives

Week 7 Power and influence – midterm Week 15 Developing leadership skills


Teaching Methods

Description

• Lectures

• Presentations

• Seminar

• Project

• Assignments

• Demonstration

Assessment Methods

Description (%)






Total 100 %

Learning Outcomes


• Understand the range of perspectives about leadership

• Become prepared as a potential leader to be more discerning about how you enact the role of leader within your

organization

• Increase your awareness in terms of your own strengths (or areas needing strength) as a leader

• Better appreciate which areas should be further developed to improve as a leader

• Be aware of the range of choice available in the enactment of the leadership role



Mandatory Literature Richard L. Hughes, Robert C. Ginnett, Gordon J. Curphy, Leadership enhancing the Lessons of Experience, 7th Ed.

Recommended Literature Yukl, Gary (2010) Leadership in Organizations, 7th Ed. Upper Saddle, NJ: Pearson- Prantice











Total Workload 119


153

Course Code: MAN 321 Course Name: OPERATIONS RESEARCH

Level: Undergraduate Year: III Semester: V-VI ECTS Credits: 5


Course Description

Operations research helps in solving problems in different environments that needs decisions. The

module converts topics that include: linear programming, Transportation, Assignment, and

CPM/MSPT techniques. Analytic techniques and computer packages will be used to solve problems

facing business managers in decision environments.

Course Objectives

This module aims to introduce students to use quantitative methods and techniques for effective

decisions–making; model formulation and applications that are used in solving business decision

problems.

Course Content

• Introduction to operations research (OR)

• Introduction to foundation mathematics

and statistics

• Linear programming (LP), LP and

allocation of resources, LP definition,

linearity requirement

• Maximization then minimization

problems.

• Graphical LP minimization solution,

introduction, simplex method definition,

formulating the simplex model.

• Mixed limitations

• Preparation for Midterm

• Midterm exam

• Example containing mixed constraints,

minimization example for similar

limitations.

• Sensitivity analysis: changes in objective

function, changes in RHS, the

transportation model

• Basic assumptions

• Solution methods:

• Feasible solution: the northwest method,

the lowest cost method;

• Optimal solution: the stepping stone

method, modified; distribution (MODI)

method.

• The assignment model: - basic

assumptions

Teaching Methods

Description


• Discussions and group works

• Project

• Presentations

• Guest Lectures

Assessment Methods

Description (%)






Total 100 %

Learning Outcomes


1. Knowledge and understanding

2. Be able to understand the characteristics of different types of decision-making

environments and the appropriate decision-making approaches and tools to be used in

each type.

3. Cognitive skills (thinking and analysis)

4. Be able to build and solve transportation models and assignment models.

5. Communication skills (personal and academic).

6. Be able to design new simple models, like: CPM, MSPT to improve decision –making

and develop critical thinking and objective analysis of decision problems.

7. Practical and subject specific skills (Transferable Skills).

8. Be able to implement practical cases, by using TORA, WinQSB

Prerequisite Course(s) /


Mandatory Literature Operations Research: Applications and Algorithms, Wayne L Winston, Publisher: Indian University, 4th edition, 2004

Recommended Literature Taha, Hamdy, Operations Research, 7th edition, (USA: Macmillan Publishing Company), 2003



154









Total Workload 129
