ECTS Coordinator: Assoc.Prof. Dr. Hasan Şakir BİLGE
2
GENERAL INFORMATION
Computer engineering is a branch of engineering concerned with design, development, and application of
computer systems. The mission of the Department of Computer Engineering is to produce and disseminate
theory, principles, practice, design, evaluation, and improvement of computing systems in the contexts of
computer hardware and software. The aim of Computer Engineering Department is to provide each of its
graduates a solid educational foundation leading to successful and sustainable career in computer
engineering. All graduates of the Computer Engineering program should have:
the analysis, design, implementation and documentation skills to qualify them for employment in
technical areas of Computer Engineering.
Communications and interpersonal skills to enable them to participate in interdisciplinary engineering
teams.
the skills, confidence, and experience to enable them to assume positions of technical leadership.
a solid foundation in basic mathematics, science, and computer engineering that will enable them to
continue their professional development for a life-long career in computer engineering.
Research and Laboratories
Ongoing Projects:
National IPv6 Project
New Aproaches to Data Security and Defence Strategies
Re-Structuring the Traffic Auditing and Accident Services And Determining the Locations of Regional
Traffic Statıons with Performance-Based Resource Management System
Development of Applications on Malware and Protection in Mobile Environment
Development of Security Aware Intelligent Routing Protocol for Broadband Wireless Mobile
Networks
Feature extraction by using 3D discrete cosine transform for face recognition
Completed Projects:
Artificial Intelligence Based Query Optimized Open Source XML Database Server Software (Gazi
University Research Foundation)
Artificial Intelligence Education and Application Development Laboratory (Gazi University Research
Foundation)
Development of Turkey Medical Information Network with GSM/GPRS based wireless network (Gazi
University Research Foundation)
Digital Processing of Ultrasound Images (Gazi University Research Foundation)
GSM Based Scada System Design and Application (Gazi University Research Foundation)
Image Processing Laboratory (Gazi University Research Foundation)
Intelligent Software Development for Information and Computer Security (Gazi University Research
Foundation)
Operating Systems Laboratory (Gazi University Research Foundation)
Smart Microphone for Mobile Devices (Gazi University Research Foundation)
The Network of Excellence for Innovative Production Machines and Systems (I*PROMS)
Web Based Mobile Robot for Scientific and Educational Purposes (supported by Science Partnership
Programme of British Council Turkey)
Laboratories:
3
Computer Laboratories: There are 36 personal computers with high-speed network connection. These
laboratories are used for courses and other purposes. Microsoft software (MSDN AA) are running on
computers.
Computer Network Laboratory: There are some computer network equipments in this laboratory, e.g.
ATM backbone switches, ATM network cards and fiber optics cables.
Digital Design Laboratory: There are 50 FPGA development kits, 3 personal computers, and necessary
software in this laboratory. This laboratory is used for applications of advanced digital design course.
Related research projects are being conducted in this laboratory.
Hardware Laboratory: Undergraduate students are learning internal hardware components of computers in
this laboratory.
Security Laboratory: This laboratory is used for applications of information and computer security course.
Related research projects are being conducted in this laboratory.
Wireless Communication Laboratory: There are GSM/GPRS modems, related software, programmer sets,
and many different GSM/GPRS antennas in this laboratory. Related research projects are being conducted
in this laboratory.
Degrees Granted
Bachelor of Science in Computer Engineering 4 years * (8 semesters)
Master of Science in Computer Engineering (with thesis) 2 years ** (4 semesters)
Philosophy of Doctorate Degree 4 years *** (8 semesters)
* The course of study may be extended to 7 years or 14 semesters ** The course of study may be extended another 2 semesters for students who meet the requirements of the Institute of Science and Technology.
*** The course of study may be extended another 4 semesters for students who meet the requirements of the Institute of Science and Technology.
Academic Staff and Research Areas
Prof.Dr. Şeref SAĞIROĞLU:
Applications of artificial neural networks, intelligent antenna analysis and design, fuzzy logic, heuristic
approaches, computer and information security, intelligent system modelling, identification and control,
web based technologies, robotics, steganography, digital signal and image processing, biometric systems,
optimization techniques, mobile wireless technologies, web technologies, microcontrollers, smartcards
Assoc.Prof.Dr. Suat ÖZDEMİR:
Computer networks, wireless networks, sensor networks, network security, information security
Image processing, face recognition, signal processing, array signal processing, beamforming, ultrasonic imaging, digital design with hardware description languages
Assist.Prof.Dr. Hacar KARACAN:
Software engineering, human computer interaction, database management systems, expert systems
Instructor Dr. Murat HACIÖMEROĞLU:
3-D computer graphics, crowd simulations, Java
Instructor Dr. Muhammet Ünal:
Assoc.Prof.Dr. Hasan Şakir BİLGE:
4
Wireless Networks and Wireless Network Security, Data Security and Encryption, Parallel and Distributed
Programming, Multi-core Programming, Supercomputers, Computer Architectures, Embedded Systems
Instructor Dr. Oktay Yıldız:
Data Mining, Machine Learning, Bioinformatics
Graduate Courses:
Course Code Course Title
5011329 ARTIFICIAL NEURAL NETWORKS
5021329 APPLIED ARTIFICIAL INTELLIGENCE
5031329 ADVANCED DIGITAL DESIGN
5041329 COMPUTER VISION
5051329 INFORMATION AND COMPUTER SECURITY
5061329 IMAGE PROCESSING
5071329 INTELLIGENT OPTIMIZATION TECHNIQUES
5081329 APPLICATIONS OF FUZZY SETS IN ENGINEERING
5091329 HYBRID INTELLIGENT SYSTEMS
5101329 MOBILE AND WIRELESS NETWORKS
5111329 ADVANCED SOFTWARE ENGINEERING
5131329 WIRELESS SENSOR NETWORKS
5141329 ENTERPRISE INFORMATION SECURITY
5151329 INTERACTIVE SYSTEMS DESIGN
5161329 NEW GENERATION INTERNET TECHNOLOGIES
5171329 NEW GENERATION COMMUNICATIONS TECHNOLOGIES
Name of the Programme: DEPARTMENT OF COMPUTER ENGINEERING
Semester
Teaching Methods Credits
Lecture Recite Lab. Project Homework Other Total Credit ECTS Credit
2 42 15 - 112 19 - 188 3 7.5
Language Turkish
Compulsory / Elective
Elective
Prerequisites -
Course Contents
Concepts of Intelligence, Multiple Intelligence and Artificial Intelligence (AI). AI techniques: GA, TS, ES and ANNs. Concepts of ANNs. Structures: Multilayered perceptrons, hopfield networks, LVQ, RBFN. Training algorithms: Backpropagation, Genetic algorithm, Levenberg-Marquardt, Quickpropagation, Delta-Bar-Delta, Extended Delta-Bar-Delta, Directed Random Search. Applying techniques and methodologies of ANNs to industrial applications. ANN Research Application Projects.
Course Objectives
The purpose of this course is to provide the student with a clear presentation of the theory and application of the principles of artificial neural networks in computer science and to develop students’ ability to design ANN structure for problems.
Learning Outcomes and Competences
The main outcome of this course is to fullfil students with the skills of solving problems with the use of ANNs.
Textbook and /or References
1. Artificial Neural Networks: A Compherensive Foundation, S. Haykin, 1994. 2. Applications of Artificial Intelligence in Engineering I: Artificial Neural Networks, in Turkish, Ufuk Kitabevi, 2003.
Name of the Programme: DEPARTMENT OF COMPUTER ENGINEERING
Semester
Teaching Methods Credits
Lecture Recite Lab. Project Homework Other Total Credit ECTS Credit
2 42 15 - 112 19 - 188 3 7.5
Language Turkish
Compulsory / Elective
Elective
Prerequisites -
Course Contents
Concept of Intelligence and Artificial Intelligence and their techniques. Concepts of learning strategies, Problem solving and search strategies. Principles. Artificial Intelligence Tools. Knowledge Representation, Representation methods and techniques. Problem Analysis Techniques. Applications of LISP and PROLOG and their examples.
Course Objectives
The purpose of this course is to provide the student with a clear presentation of the theory and application of the principles of artificial intelligence in computer science and to develop students’ ability to design artificial intelligence structure for problems.
Learning Outcomes and Competences
The main outcome of this course is to fullfil students with the skills of solving problems with the use of artificial intelligence.
Textbook and /or References
Artificial Intelligence: A Modern Approach, S Russel, P. Norwig, Prentice Hall 2003.
Concept of Intelligence and Artificial Intelligence and their techniques. Concepts of learning strategies, Problem solving and search strategies. Problem solving and search strategies. Principles. Artificial Intelligence Tools. Artificial Intelligence Tools. Artificial Intelligence Tools. Knowledge Representation, Representation methods and techniques. Knowledge Representation, Representation methods and techniques.
8
11 12 13 14
Problem Analysis Techniques. Problem Analysis Techniques. Applications of LISP and PROLOG and their examples. Applications of LISP and PROLOG and their examples.
9
Course Title-Course Code: ADVANCED DIGITAL DESIGN - 5031329
Name of the Programme: DEPARTMENT OF COMPUTER ENGINEERING
Semester
Teaching Methods Credits
Lecture Recite Lab. Project Homework Other Total Credit ECTS Credit
2 42 34 56 - 56 188 3 7.5
Language Turkish
Compulsory / Elective
Elective
Prerequisites -
Course Contents
Programmable logic devices (FPGA, CPLD), digital design with hardware description languages (Verilog, VHDL), synthesis, simulation, validation, programmable device implementation, embedded processor design.
Course Objectives
Teaching of digital design with hardware description languages, simulation, implementation on FPGAs.
Learning Outcomes and Competences
Learning of digital design with hardware description languages, simulation, implementation on FPGAs.
Textbook and /or References
1. Verilog HDL : a guide to digital design, Samir Palnitkar, 1996. 2. VHDL: analysis and modeling of digital systems, Zainalabedin Navabi, McGraw-Hill, 1998.
Name of the Programme: DEPARTMENT OF COMPUTER ENGINEERING
Semester
Teaching Methods Credits
Lecture Recite Lab. Project Homework Other Total Credit ECTS Credit
2 42 11 56 56 23 188 3 7.5
Language Turkish
Compulsory / Elective
Elective
Prerequisites -
Course Contents
Image formation, feature extraction, region growing, boundary detection, texture analysis, stereo vision, sequence of images, motion estimation, two-dimensional and three-dimensional representation, matching.
Course Objectives
Understanding the role of computer vision in real problems. Improving practical problem solving skills in computer vision.
Learning Outcomes and Competences
Finding appropiate solutions to complex vision problems.
Textbook and /or References
1. Computer Vision: A Modern Approach, David A. Forsyth, Jean Ponce, Prentice Hall, 2003. 2. Computer Vision, Linda G. Shapiro, George C. Stockman, Prentice Hall, 2001.
two-dimensional and three-dimensional representation, matching.
13
Course Title-Course Code: INFORMATION AND COMPUTER SECURITY - 5051329
Name of the Programme: DEPARTMENT OF COMPUTER ENGINEERING
Semester
Teaching Methods Credits
Lecture Recite Lab. Project Homework Other Total Credit ECTS Credit
1 42 15 112 19 188 3 7.5
Language Turkish
Compulsory / Elective
Elective
Prerequisites -
Course Contents
Introduction to information, security and computer security. Security engineering. Techniques for achieving security. Cryptography. Symetric and asymetric algorithms. Digital signatures. Authentication and identification schemes. Public key Infrastructure. Intrusion detection. Formal models of computer security. Software protection. Security of electronic mail and the World Wide Web. Electronic commerce. Firewalls. Risk assessment. Standards in security. Research and application projects.
Course Objectives
Providing students to understand the theory and application of the principles of computer and information security in computer engineering and science. Let them to develop their own ability and awarness to design a secure environment in computer useage and installation.
Learning Outcomes and Competences
The main outcome of this course is to fullfil students with the skills of establishing secure electronic media protecting their own information.
Textbook and /or References
1. Security Engineering, R. Anderson, 0-471-38922-6, Willey, New York, 2001. 2. Cryptography And Network Security Principles And Practices" Stallings Will, Prentice Hall, 2003. 3. ―e-signature and PKI‖, Lecture Notes in Turkish, ġ. Sağıroğlu, 2005, Ankara.
Name of the Programme: DEPARTMENT OF COMPUTER ENGINEERING
Semester
Teaching Methods Credits
Lecture Recite Lab. Project Homework Other Total Credit ECTS Credit
1 42 19 56 71 188 3 7.5
Language Turkish
Compulsory / Elective
Elective
Prerequisites -
Course Contents
Introduction to digital image processing. Digital image fundamentals, sampling and quantization. Image enhancement, histogram processing, filters. The Fourier transform and the frequency Domain. Image restoration, noise models. Color image processing. Image compression. Morphological image processing.
Course Objectives
Teaching digital image processing, applications of image processing methods. Encouraging related studies.
Learning Outcomes and Competences
Understanding digital image processing, choosing appropiate methods when solving newly encountered problems. Obtaining necessary background for further studies.
Textbook and /or References
1. Digital Image Processing, 2. Edition, R.C. Gonzalez, R.E. Woods, Prentice Hall, 2002. 2. Digital Image Processing Using MATLAB, R.C. Gonzalez, R.E. Woods, S.L. Eddins, Prentice Hall, 2004.
Introduction to digital image processing. Digital image fundamentals, sampling and quantization. Image enhancement, Image enhancement, histogram processing, histogram processing, filters. The Fourier transform and the frequency Domain. Image restoration, noise models.
16
12 13 14
Color image processing. Image compression. Morphological image processing.
Name of the Programme: DEPARTMENT OF COMPUTER ENGINEERING
Semester
Teaching Methods Credits
Lecture Recite Lab. Project Homework Other Total Credit ECTS Credit
1-2 42 50 38 58 188 3 7.5
Language Turkish
Compulsory / Elective
Elective
Prerequisites -
Course Contents
Applications of intelligent optimization techniques in complex engineering problems. Genetic algorithms, simulated annealing, fuzzy logic, neural networks, tabu search, and ant algorithm techniques. Examples to problem solving using these techniques.
Course Objectives
Teaching intelligent optimization techniques which are genetic algorithm, simulated annealing, fuzzy logic, neural networks, tabu search, and ant algorithm. Teaching how to use this intelligent optimization techniques in complex engineering problems.
Learning Outcomes and Competences
Learning intelligent optimization techniques which are genetic algorithm, simulated annealing, fuzzy logic, neural networks, tabu search, and ant algorithm. Learning how to use this intelligent optimization techniques in complex engineering problems.
Textbook and /or References
1. How to Solve It: Modern Heuristics 2nd ed. Revised and Extended, Michalewicz Zbigniew, Fogel David B., Springer-Verlag, 2004. 2. Intelligent Optimization Techniques, Pham, D.T., Karaboga, D., Springer Verlag, 1999. 3. Elements of Artificial Neural Networks, Kishan Mehrotra, Chilukuri K. Mohan and Sanjay Ranka, MIT Press, 1996.
Ant Algorithm Genetic Algorithm Genetic Algorithm Neural Networks
19
Course Title-Course Code: APPLICATIONS OF FUZZY SETS IN ENGINEERING - 5081329
Name of the Programme: DEPARTMENT OF COMPUTER ENGINEERING
Semester
Teaching Methods Credits
Lecture Recite Lab. Project Homework Other Total Credit ECTS Credit
1 42 50 38 58 188 3 7.5
Language Turkish
Compulsory / Elective
Elective
Prerequisites -
Course Contents
Fuzzy set theory and fuzzy logic. Fuzzy operators and fuzzy relations. Applications of fuzzy sets in engineering. Examples to problem solving using fuzzy sets theory.
Course Objectives
Teaching fuzzy sets theory, fuzzy logic, fuzzy operators and fuzzy relations. Teaching fuzzy sets applications in engineering areas. Teaching examples to problem solving using fuzzy sets theory.
Learning Outcomes and Competences
Learning fuzzy sets theory, fuzzy logic, fuzzy operators and fuzzy relations. Learning fuzzy sets applications in engineering areas. Learning examples to problem solving using fuzzy sets theory.
Textbook and /or References
1. T.J.Ross, Fuzzy Logic with Engineering Applications, Addison Wesley, 1995. 2. Neuro-Fuzzy and Soft computing, Jiang, et al., Pearson Education, 1996. 3. Fuzzy Sets & Fuzzy Logic: Theory & Applications, George J. Klir , Bo Yuan, Pearson Education , 1995.
Neural Networks-Fuzzy Systems - Evolutionary Algorithms
Neural Networks-Fuzzy Systems - Evolutionary Algorithms
Neural Networks-Fuzzy Systems - Evolutionary Algorithms Hybrid systems Applications
Neural Networks-Fuzzy Systems - Evolutionary Algorithms Hybrid systems Applications
Term Projects
23
Course Title-Course Code: MOBILE AND WIRELESS NETWORKS - 5101329
Name of the Programme: DEPARTMENT OF COMPUTER ENGINEERING
Semester
Teaching Methods Credits
Lecture Recite Lab. Project Homework Other Total Credit ECTS Credit
1-2 42 50 38 58 188 3 7.5
Language Turkish
Compulsory / Elective
Elective
Prerequisites -
Course Contents
Fundamental techniques in design of second generation wireless networks: cellular network and protocols, access techniques, signaling and mobility management, wireless data processing, mobile internet and personal communication services (PCS). Third generation wideband systems, novel technologies.
Course Objectives
Teaching fundamental techniques in design of second generation wireless networks, cellular network and protocols, access techniques, signaling and mobility management, wireless data processing, mobile internet and personal communication services (PCS). Teaching third generation wideband systems, novel technologies.
Learning Outcomes and Competences
Learning fundamental techniques in design of second generation wireless networks, cellular network and protocols, access techniques, signaling and mobility management, wireless data processing, mobile internet and personal communication services (PCS). Learning third generation wideband systems, novel technologies.
Textbook and /or References
(1) Stallings, W., ―Wireless Communications & Networks (2nd Edition)‖, Prentice Hall, 2004. (2) Rappaport, T., ―Wireless Communications: Principles and Practice (2nd Edition)‖, Prentice Hall, 2002. (3) Haykin, S., Moher, M., ―Modern Wireless Communications‖, Prentice Hall, 2004. (4) Schiller, J., ―Mobile Communications Second Edition‖, Addison Wesley, 2003.
Introduction Fundamental techniques in design of second generation wireless networks Cellular network and protocols Cellular network and protocols Access techniques
24
6 7 8 9 10 11 12 13 14
Access techniques Signaling and mobility management Wireless data processing Wireless data processing Mobile internet and personal communication services (PCS) Mobile internet and personal communication services (PCS) Third generation wideband systems, Third generation wideband systems, Novel technologies
Lecture Recite Lab. Project Homework Other Total Credit ECTS Credit
1-2 42 50 38 58 188 3 7.5
Language Turkish
Compulsory / Elective
Elective
Prerequisites -
Course Contents
Concepts of software engineering: life cycle, planning, planning, realizing and test. Planning and realizing of large software systems. Determining software steps. Forming modular software structure. Coding principles. Planning tests. Maintenance of software. Management of large software projects. Real software examples. Term project.
Course Objectives
Teaching concepts of software engineering: life cycle, planning, planning, realizing and test. Teaching planning and realizing of large software systems. Teaching determining software steps and forming modular software structure. Teaching coding principles, planning tests and maintenance of software. Teaching management of large software projects. Teaching how to develop application projects.
Learning Outcomes and Competences
Learning concepts of software engineering: life cycle, planning, planning, realizing and test. Learning planning and realizing of large software systems. Learning determining software steps and forming modular software structure. Learning coding principles, planning tests and maintenance of software. Learning management of large software projects. Learning how to develop application projects.
Textbook and /or References
(1) Daniel H. Steinberg, Daniel W. Palmer, ―Extreme Software Engineering: A Hands-On Approach‖, Pearson Prentice Hall, 2004 (2) Kent Beck, ―eXtreme Programming Explained‖, Addison-Wesley, 1999. (3) Martin Fowler, Kent Beck, John Brant, William Opdyke, Don Roberts, Refactoring: Improving the Design of Existing Code, Addison-Wesley, 1999.
Life cycle Planning Software Requirements Software Design Software Development Test Methods Maintenance of software Management New Approach at Software Engineering Real software examples. Term project Term project
Name of the Programme: DEPARTMENT OF COMPUTER ENGINEERING
Semester
Teaching Methods Credits
Lecture Recite Lab. Project Homework Other Total Credit ECTS Credit
1 30 10 110 38 - 188 3 7.5
Language Turkish
Compulsory / Elective
Elective
Prerequisites None
Course Contents
This course will provide a comprehensive introduction to sensor networks, including the understanding of their unique characteristics and research challenges. Protocols at different network layers and their applications. Sensor network security. Data aggregation and false data detection in sensor networks.
Course Objectives
The purpose of this course is to introduce sensor networks to the students by surveying the state-of-the-art on sensor networks research so that the number of computer engineers in Turkey who are familiar with sensor networks is increased.
Learning Outcomes and Competences
The main outcome of this class is to introduce sensor networks to the students. Another important goal of the class is to train students to read research papers with a critical perspective.
Textbook and /or References
1. Sensor Network Operations, S. Phoha, T.F. La Porta, and C. Griffin (eds), pp. 422-441, ISBN: 0471719765, Wiley-IEEE Press, May 2006.
2. Security in Distributed, Grid, Mobile and Pervasive Computing", Edited by Prof. Yang Xiao, Auerbach Publications, CRC Press 2007.
3. Wireless Sensor Networks: An Information Processing Approach by Feng Zhao and Leonidas Guibas, Morgan Kaufmann Publishing (July 6, 2004), ISBN-10: 1558609148
Introduction and overview Applications Sensor and network architecture
Deployment and organization Transport protocols Routing and data dissemination protocols Localization and tracking protocols
28
8 9 10 11 12 13 14
Medium access protocols Data storage protocols Data aggregation protocols Security protocols Secure data aggregation protocols Research and application projects Research and application projects
29
Course Title-Course Code: ENTERPRISE INFORMATION SECURITY - 5141329
Name of the Programme: DEPARTMENT OF COMPUTER ENGINEERING
Semester
Teaching Methods Credits
Lecture Recite Lab. Project Homework Other Total Credit ECTS Credit
1 42 14 112 19 31 188 3 7.5
Language Turkish
Compulsory / Elective
Elective
Prerequisites None
Course Contents
Intro to Enterprise Information Security, up-to-date developments, encryption and decryption techniques and approaches, often faced vulnerabilities, Enterprise Information Security standards, ISO 17799, CC 15408, ISO 2700X, Evaluating information assests and risk managements, Security for Enterprise Networks and applications, penetration for Enterprise Networks, Enterprise Information Security and social engineering, tests for Enterprise Information Security, application and research projects.
Course Objectives
The purpose of this course is to provide the students with a clear presentation of the theory and application of the principles of Enterprise Information Security in computer science and
to develop students’ ability to improve their perceptions in understanding and applying Enterprise Information Security.
Learning Outcomes and Competences
The main outcome of this course is to fullfil students with the skills of understanting Enterprise Information Security and its technologies and use those in solving security
problem.
Textbook and /or References
1. Cole, E., Krutz, R., Conley, J.W., ―Security Assessments, Testing, and Evaluation‖, Network Security Bible, Wiley Publishing Inc., Indianapolis, 607-612 (2005).
2. Abrams, D., M., ―FAA System Security Testing and Evaluation‖, Mitre Center for Advanced Aviation System Development McLean, Virginia (2003).
3. Layton, P., T., ―Penetration Studies – A Technical Overview‖, SANS Institute 2002. 4. Mathew, T., ―Ethical Hacking and Countermeasures EC-Council E-Business
Intro to Enterprise Information Security, Enterprise Information Security and Social Engineering, Up-to-date developments, often faced vulnerabilities, Evaluating information assests and risk managements, Enterprise Information Security standards, ISO 17799, CC 15408, ISO 2700X, and other standarts Penetration for Enterprise Networks, tests for Enterprise Information Security, Information Security Management Systems and Applications Information Security Management Systems and Applications Information Security Management Systems and Applications Applications of Enterprise Information Security, Application and research projects. Application and research projects.
Application and research projects.
31
Course Title-Course Code:
INTERACTIVE SYSTEMS DESIGN–5151329
Name of the Programme:
DEPARTMENT OF COMPUTER
ENGINEERING
Semester
Teaching Methods Krediler
Lecture Recite Lab. Project Homework Other Total Credit ECTS
Credit
1 – 2 42 - - 146 - - 188 3 7,5
Language Turkish
Compulsory
/
Elective
Elective
Prerequisites -
Course
Contents
Interactive systems, user-centered design, perception and memory, navigation, task analysis,
design principles, iterative design cycle, user experiments, future design principles.
Course
Objectives
Develop a theoretical and empirical understanding of user-centered design of computer
interfaces, and their uses,
Develop valid and reliable usability evaluation plans for any information technology
Provide an understanding of the social, psychological, and ethical issues associated with
interactive systems design
Offer a set of first-hand experiences which augment conceptual understanding of course
content.
Learning
Outcomes
and
Competences
Gaining the ability to handle software and hardware engineering problems from a
different point of view with the help of the theoretical information about interactive
systems,
Evaluating Computer Engineering outcomes by considering the human factor,
Adapting a user-centered point of view on new technology development stages,
Understanding the structure of processes and different views on interactive system
design,
Conducting different usability tests for computer systems,
Designing innovative interactive systems.
Textbook
and
/or
References
Barnum, C.M. (2002). Usability Testing and Research. New York : Longman
Benyon, D. (2005).Designing interactive systems :people, activities, contexts, technology. New York : Addison-Wesley
Selected papers.
Assessment
Criteria
If
any,mark
as (X)
Percent
(%)
Midterm Exams X 30
Quizzes
Homeworks
Projects X 30
Term Paper
Laboratory Work
Other
Final Exam X 40
Instructors Assist.Prof.Dr. Hacer Karacan
32
Week Subject
1
2
3
4
5
6
7
8
9
10
11
12
13
14
Introduction
Human Perception and Mind Model
Requirements Analysis
Interactive Interface Design Theories
Interactive Web Design
Distance Education Systems Design
Virtual Reality Systems Design
Computer Systems Design and Evaluation Processes
Intelligent Devices
Usability Tests
Research on Interactive Systems
Project Presentations
Project Presentations
Project Presentations
33
NEW GENERATION INTERNET
TECHNOLOGIES - 5161329 DEPARTMENT OF COMPUTER ENGINEERING
Semester
Methods of Education Credits
Lecture Recit Lab. Other Total Credit ECTS
Credit
2 20 12 - 10 42 0 7.5
Language Turkish
Compulsory /
Elective Compulsory
Prerequisites -
Course
Contents
Introduction to Internet Communications, Voice Over IP, New Generation IP Technologies,
IPv6 Technologies, IPv6 Applications, IPv6 and Turkey Infrastructure, Internet ve Mobile
Communications Technologies, Power Line Communications, Cable TV and Internet
Applications, Wireless Technologies, MultiLanguages Domain Names, Next Generation
Domain Name
Course
Objectives
The purpose of this course is to provide the student with a clear presentation of the theory
and application of the principles of new generation of communications technologies in
computer science and to develop students’ ability to improve their perceptions in new
Technologies.
Learning
Outcomes
and
Competences
The main outcome of this course is to fullfil students with the skills of understanting new
generation communication technologies and use those in problem solving.
Textbook and
/or
References
1. IPv6 Essentials, by Silvia Hagen
2. Understanding IPv6 by Joseph Davies
3. IPv6 Network Administration by David Malone
4. Cisco Self-Study: Implementing Cisco IPv6 Networks (IPV6) by Regis Desmeules
5. Migrating to IPv6: A Practical Guide to Implementing IPv6 in Mobile and Fixed
Networks by Marc Blanchet
6. IPv6, Second Edition: Theory, Protocol, and Practice, 2nd Edition (The Morgan
Kaufmann Series in Networking) by Pete Loshin
7. Wireless Communication Technology, by Roy Blake
8. ADSL, VDSL, and Multicarrier Modulation
by John A. C. Bingham
9. Technologies for Next Generation Communications
Kenneth J. Turner (Editor), Evan H. Magill (Editor), David J. Marples (Editor)
Assessment Criteria
If
any,mark
as (X)
Percent
(%)
Midterm Exams X 30
Quizzes
Homeworks X 10
Projects X 60
Term Paper
Laboratory Work
Other
Final Exam
34
Instructors Assoc. Prof. Dr. Mustafa ALKAN
Weeks
Subjects
1
2
3
4
5
6
7
8
9
10
11
12
13
14
Introduction to Internet Communications
Voice Over IP
New Generation IP Technologies
IPv6 Technologies
IPv6 Applications
IPv6 and Turkey Infrastructure
Internet ve Mobile Communications Technologies
Power Line Communications
Cable TV and Internet Applications
Wireless Technologies
New Generation Domain Names
Native Domain Names
MultiLanguages Domain Names
Next Generation Technologies
35
NEW GENERATION COMMUNICATIONS TECHNOLOGIES - 5171329
DEPARTMENT OF COMPUTER ENGINEERING
Semester
Methods of Education Credits
Lecture Recit Lab. Other Total Credit ECTS Credit
2 20 12 - 10 42 0 7.5
Language Turkish
Compulsory / Elective
Compulsory
Prerequisites -
Catalog Description
Communications Technologies, Multimedia Data and Multimedia Communications, New Broadbant Communications Services, Advanced Communications Systems, GSM (Global System for Mobile Communications), ISDN-(Integrated Services Digital Network), xDSL (Digital Subsriber Line), UMTS, (Universal Mobile Telecommunications System), W-CDMA ve CDMA 2000, (Wideband Code Division Multiple Access), PDC ( Personel Digital Communication), HSCSD (High-Speed, Circuit-Switched Data), (Wireless Broadband Access Technologies) D-AMPS (Digital Advanced Mobile Phone System), WIMAX: Worldwide Ġnteroperability for Microwave Access, GPRS; General Packet Radio Service, EDGE; Enhanced Data GSM Environment,
Course Objectives
The purpose of this course is to provide the student with a clear presentation of the theory and application of the principles of new generation of communications technologies in computer science and to develop students’ ability to improve their perceptions in new Technologies.
Course Outcomes
The main outcome of this course is to fullfil students with the skills of understanting new generation communication technologies and use those in problem solving.
Textbook and /or
References
1.Multimedia Computer Communications Technologies Chwan Hwu Wu- J.David Irwin 2001, 2. Communicatinos Systems Simon Haykin 2003. 3. The Handbook of Multimedia Information Management 4. The Business of WĠMAX Pareek D. 2005 5. ISDN and SS7 Architctures for Digital Signaling Networks Uyless, B. 2002 6. DSL Global Solution For Ġnteractive Broadband Kingdom, S. 2005
Assessment Criteria
Quantity Percentage
Midterm Exams 1 30
Quizzes - -
Homeworks 7 10
Projects 2 60
Term Paper - -
Laboratory Work - -
Other - -
Final Exam - -
Course Category by Content (%)
Mathematics and Basic Sciences 30
Engineering Science 30
Engineering Design 20
Social Sciences 20
36
Instructors Assoc. Prof. Dr. Mustafa ALKAN
Courses
Weekly program
1
2
3
4
5
6
7
8
9
10
11
12
13
14
Communications Technologies,
Multimedia Data and Multimedia Communications,
New Broadbant Communications Services,
Advanced Communications Systems,
GSM (Global System for Mobile Communications),
ISDN-(Integrated Services Digital Network),xDSL (Digital SubsriberLine),
UMTS, (Universal Mobile Telecommunications System),
W-CDMA ve CDMA 2000, (Wideband Code Division Multiple Access),
PDC ( Personel Digital Communication),
HSCSD (High-Speed, Circuit-Switched Data),
Wireless Broadband Access Technologies
D-AMPS (Digital Advanced Mobile Phone System),
WIMAX: Worldwide İnteroperability for Microwave Access,
GPRS; General Packet Radio Service, EDGE; Enhanced Data GSM Environment,
Name of the Programme: DEPARTMENT OF COMPUTER ENGINEERING
Semester
Teaching Methods Credits
Lecture Recite Lab. Project Homework Other Total Credit ECTS Credit
1 42 34 56 - 56 188 3 7.5
Language Turkish
Compulsory / Elective
Elective
Prerequisites -
Course Contents
General concepts and Boolean algebra; Equivalence relations and Lattice structures; State reduction in completely specified sequential machines; Design of synchronous and asynchronous sequential circuits; State assignment in asynchronous sequential circuits; race-free state assignment methods and Fault tolerant analysis in logic circuits; Programming Languages using in Logic circuits; Programmable logic circuit components (SPLD, CPLD, FPGA); Digital design with Field Programmable Gate Arrays; Logic circuit design with Programmable logic controllers; Very large scale integrated logic circuits.
Course Objectives
Approaches and methods related to the design of asynchronous sequential circuits.
Learning Outcomes and Competences
State reduction in completely specified sequential machines. State reduction in incompletely specified sequential machines. State assignment in synchronous sequential circuits. Partitioning of sequential circuits. Design of asynchronous sequential circuits.
Istefanopulos, Boğaziçi Üniversitesi Döner Sermaye, 1994. 3. Bilgisayar Sistemleri Mimarisi, M. Morris Mano, Literatür Yayınları, Ġstanbul, Ekim 2002. 4. Maxfield C., ―Design Warriors Guide to FPGA‖, Mentor Graphics Corporation and Xilinx,
Inc., 2004. 5. S. Brown, Z. Vranesic, Fundamentals of Digital Logic with VHDL Design, McGraw-Hill,
General concepts and Boolean algebra Equivalence relations and Lattice structures State reduction in completely specified sequential machines State assignment in asynchronous sequential circuits Design of synchronous sequential circuits Design of asynchronous sequential circuits Race-free state assignment methods Fault tolerant analysis in logic circuits Midterm Exam Programs, hardware languages and application tools Digital design with Field Programmable Gate Arrays Programmable logic circuit components (SPLD, CPLD, FPGA) Logic circuit design with Programmable logic controllers Very large scale integrated logic circuits.
Understanding pattern recognition methods, obtaining the ability of effective use of feature selection and dimensionality reduction.
Learning Outcomes and Competences
Applying of classification methods in a sample problem successfully, obtaining the ability of effective use of feature selection and dimensionality reduction, understanding that pattern recognition can be applied to different problems in a similar way.
General introduction Classifiers based on Bayes decision theory Linear classifiers Linear discriminant functions Non linear classifiers Support vector machines Feature extraction Feature extraction Linear transformations Feature selection Feature selection Dimensionality reduction
40
13 14
Clustering Project presentations
41
Course Title-Course Code:
DATA MINING - 5201329
Name of the Programme: DEPARTMENT OF COMPUTER ENGINEERING
Semester Teaching Methods Credits
Lecture Recite Lab. Project HW Other Total Credit ECTS
Credit
Spring 42 34 - 56 - 56 188 3 7,5
Language Turkish
Compulsory /
Elective Elective
Prerequisites N one
Course Contents
Introduction to data mining, application areas of data mining. Stages of data mining process.
Exploring Data, Preprocessing of data, Classification: Basic Concepts, Decision Trees, and
Model Evaluation, Association Analysis: Basic Concepts and Algorithms, Cluster Analysis:
Basic Concepts and Algorithms, Anomaly Detection, Web mining, Stream Data Mining
Course
Objectives
The purpose of this course is to introduce data mining concepts to graduate students. By
learning the fundamental concepts, techniques and algorithms of data mining students are
expected to be able to design, develop, and use real world data warehouses.
Learning
Outcomes and
Competences
The main outcome of this class is to have students with knowledge data mining techniques
that are useful in real world applications.
Textbook and
/or References
• Jiawei Han, Micheline Kamber, Data Mining: Concepts and Techniques,
Morgan Kaufmann, Data mining, ISBN 1558604898,2006
• Ian H. Witten , Eibe Frank, Data Mining: Practical Machine Learning Tools
and Techniques, Second Edition (Morgan Kaufmann Series in Data Management
Systems), 2005
• Pang-Ning Tan, Michael Steinbach, Vipin Kumar (2005). Introduction to Data
Mining. Addison Wesley, ISBN: 0-321-32136-7
Assessment
Criteria If any, mark
as (X) (%)
Midterm Exams X 30
Quizzes - -
Homework - -
Projects X 30
Term Paper - -
Laboratory Work - -
Others - -
Final Exam X 40
Instructor Assist. Prof. Dr. Suat Özdemir
Week Subject
42
1
2
3
4
5
6
7
8
9
10
11
12
13
14
Introduction and overview of data mining
Application areas of data mining
Data warehouses and OLAP technology
Stages of data mining
Data and data preprocessing
Association rule analysis
Association rule analysis
Prediction and classification
Supervised learning: Classification algorithms
Unsupervised learning: Clustering algorithms
Unsupervised learning: Clustering algorithms
Data mining in complex data
Web mining
Stream data mining
43
Course Title-Course Code:
SEMANTIC WEB – 5211329
Name of the Programme:
DEPARTMENT OF COMPUTER ENGINEERING
Semester
Teaching Methods Krediler
Lecture Recite Lab. Project Homework Other Total Credit ECTS
Credit
1 – 2 42 - - 146 - - 188 3 7,5
Language Turkish
Compulsory /
Elective Elective
Prerequisites -
Course
Contents
Simple Ontologies in RDF and RDF Schema, RDF Formal Semantics, Ontologies in OWL, OWL
Formal Semantics, Ontologies and Rules, Query Languages, Ontology Engineering, Logic and Inference
Rules, Applications.
.
Course
Objectives
Develop a theoretical and empirical understanding of standardized knowledge representation
languages for modeling ontologies operating at the core of the semantic web
Offer a set of first-hand experiences which augment conceptual understanding of course content.
Learning
Outcomes and
Competences
Understanding the computational aspects of Information Extraction (IE) and Integration from
unstructured and semi-structured sources
Gaining the ability to build domain-specific Semantic Search Engines to improve Web
Searching
Designing and conducting different applications on course content
Textbook and
/or References
Hitzler, P., Krötzsch, M. & Rudolph, S. (2009). Foundations of Semantic Web Technologies,
Chapman & Hall/CRC.
Antoniou, G. & Van Harmelen, F. (2008). A semantic Web primer. Cambridge, Mass. : MIT
"Security and Cooperation in Wireless Networks", Levente Buttyan and Jean-Pierre Hubaux, , Cambridge University Press, ISBN 9780521873710 “Network Security: Private Communication in a Public World (2nd Edition)”, by Charlie Kaufman,Radia Perlman, and Mike Speciner, Prentice Hall, ISBN-10: 0130460192 "Guide to Wireless Network Security", John Vacca, Springer
5980029 SEMINAR DEPARTMENT OF COMPUTER ENGINEERING
Semester
Teaching Methods Credits
Seminar Library Studies
Project Presentation
Other Total Credit ECTS Credit
1-2 28 80 80 188 0 7.5
Language Turkish
Compulsory / Elective
Compulsory
Prerequisites Assignment of the supervisor
Course Contents
Presentation of the thesis work
Course Objectives
To give the ability of the oral presentation and discussion
To decide on the objectives of the thesis work and the strategy
Learning Outcomes and Competences
To have the ability of the oral presentation and discussion
To have an ability of determining the objectives and the strategy of a scientific work
Textbook and /or References
All the references related to the study.
Assessment Criteria
If any,mark
as (X)
Percent (%)
Seminar X
Quizzes
Homeworks
Projects / Presentation X
Term Paper
Laboratory/ Library Work X
Other
Final Exam
Instructors The supervisor
51
5001029 MS Thesis DEPARTMENT OF COMPUTER ENGINEERING
Semester
Teaching Methods Credits
Meeting Recitation/
Lab. Other Total Credit
ECTS Credit
1-2 14 200 36 250 0 10
Language Turkish
Compulsory / Elective
Compulsory
Prerequisites Assignment of the supervisor
Course Contents
MS thesis work
Course Objectives
To improve the ability of getting the scientific information, its evaluation and interpretation by conductive scientific research
Learning Outcomes and Competences
To have the ability of getting the scientific and technological information, and engaging in life-long learning
To have the ability of evaluation and interpretation
Textbook and/or References
All the references related to the study.
Assessment Criteria
If any,mark
as (X)
Percent (%)
Midterm Exams
Quizzes
Homeworks
Projects
Term Paper
Laboratory and Library Work / Applications X
Other ( Report, presentation) X
Final Exam
Instructors The supervisor
52
80*29DD SPECIAL TOPICS in MS DEPARTMENT OF COMPUTER ENGINEERING
Semester
Teaching Methods Credits
Theory Library/Lab./ Homework
Project /
Area studies
Other Total Credit ECTS Credit
1-2 42 150 30 28 250 0 10
Language Turkish
Compulsory / Elective
Compulsory
Prerequisites Assignment of the supervisor
Course Contents
Basic concepts and applications related to the thesis work
Course Objectives
To give the general knowledge related to the thesis work
To develop the ability of analytical thinking
Learning Outcomes and Competences
To have the general knowledge
To have the ability of making plans for the research work
Textbook and /or References
All the references related to the study.
Assessment Criteria
If any,mark
as (X)
Percent (%)
Midterm Exams
Quizzes
Homeworks
Projects / presentation X
Term Paper
Laboratory / Library Work X
Other
Final Exam
Instructors The supervisor
53
6001029 PhD Thesis DEPARTMENT OF COMPUTER ENGINEERING
Semester
Teaching Methods Credits
Meeting Recitation/ Lab.
Other Total Credit ECTS Credit
1-2 14 200 36 250 0 10
Language Turkish
Compulsory / Elective
Compulsory
Prerequisites Assignment of the supervisor
Course Contents PhD thesis work
Course Objectives
To give the ability of carrying out independent research,
To give the ability of deducing conclusions scientifically
To give the ability of determining progressive steps to reach new synthesis
Learning Outcomes and Competences
To gain ability for innovations in scientific approach or to develop a new scientific method or to apply obvious method to a new field.
Textbook and /or References
All the references related to the study.
Assessment Criteria
If any,mark
as (X)
Percent (%)
Midterm Exams
Quizzes
Homeworks
Projects
Term Paper
Laboratory and Library Work / Applications X
Other ( Report, presentation) X
Final Exam
Instructors The supervisor
54
8000029 DOCTORAL QUALIFYING EXAMINATION
DEPARTMENT OF COMPUTER ENGINEERING
Semester
Teaching Methods Credits
Individual work Other Total Credit ECTS Credit
I-II 400 38 438 0 17.5
Language Turkish
Compulsory / Elective
Compulsory
Prerequisites To complete the minimum course credit
Course Contents
The written and oral exams on basic subjects and related fields of the PhD thesis work
Course Objectives
To check the qualification on basic subjects and related fields of the PhD thesis work
Learning Outcomes and Competences
To have the qualification on basic subjects and related fields of the PhD thesis work
Textbook and /or References
All the references related to the study.
Assessment Criteria
If any,mark
as (X)
Percent (%)
Midterm Exams
Quizzes
Homeworks
Projects
Term Paper
Laboratory Work
Other
Qualıfying Exam
Instructors Qualification committee
55
8500029 PROGRESS IN THESIS DEPARTMENT OF COMPUTER ENGINEERING
Semester
Teaching Methods Credits
Report, Presentation
Measurement and
evaluation Other Total Credit
ECTS Credit
I-II 40 100 48 188 0 7.5
Language Turkish
Compulsory / Elective
Compulsory
Prerequisites Passing the qualification exam
Course Contents
Developing the research work
Course Objectives
To analyse the results obtained according to the work plan of PhD studies and make the work plan for the next period and contributing to the direction of the PhD work.
Learning Outcomes and Competences
To get an ability of making work plans on the basis of research objective and evaluating the results and presentation.
Textbook and /or References
All the references related to the study.
Assessment Criteria
If any,mark
as (X)
Percent (%)
Midterm Exams
Quizzes
Homework
Projects
Term Paper
Laboratory Work
Report and presentation X
Final Exam
Instructors Thesis committee
56
90*29DD SPECIAL TOPICS in PhD DEPARTMENT OF COMPUTER ENGINEERING
Semester
Teaching Methods Credits
Theory Library/Lab./ Homework
Project /
Area studies
Other Total Credit ECTS Credit
1-2 42 150 30 28 250 0 10
Language Turkish
Compulsory / Elective
Compulsory
Prerequisites Assignment of the supervisor
Course Contents
Basic concepts and applications related to the thesis work
Course Objectives
To give the general knowledge related to the thesis work
To develop the ability of analytical thinking
Learning Outcomes and Competences
To develope the ability of analytical thinking
To get the ability of evaluation, data analysis and making written/oral presentation
