GENETICS AND BIOINFORMATICS
Bachelor	TR-NQF-HE: Level 6	QF-EHEA: First Cycle	EQF-LLL: Level 6

Course Introduction and Application Information

Course Code	Course Name	Semester	Theoretical	Practical	Credit	ECTS
CMP4221	Multimedia Systems and Communications	Spring	3	0	3	6

This catalog is for information purposes. Course status is determined by the relevant department at the beginning of semester.

Basic information

Language of instruction:	English
Type of course:	Non-Departmental Elective
Course Level:	Bachelor’s Degree (First Cycle)
Mode of Delivery:	Face to face
Course Coordinator :	Assist. Prof. HASSAN IMANI
Course Lecturer(s):	Assist. Prof. ÖVGÜ ÖZTÜRK ERGÜN
Recommended Optional Program Components:	None
Course Objectives:	This course teaches fundamental topics related to multimedia systems and analysis. A top-down analysis of video processing applications, algorithms, tools, and fundamentals. Applications include digital TV, computer games, cinema special effects, 3D TV, medical imaging, and forensics. Algorithms include motion estimation, filtering and restoration, de-interlacing and enhancement, interpolation and super-resolution, stereo and 3D video processing, coding, and compression standards.

Learning Outcomes

The students who have succeeded in this course;
I. To be able to use fundamental signal processing knowledge to solve problems in multimedia data processing
II. To acquire knowledge about working principles of various media devices and be able to combine them to build larger multi-media systems
III. To practice programming fundamentals for the design and control of digital data processing and apply them to real world problems
IV. To do research on theoretical concepts behind vision, imaging, colors and video by investigating basic processing techniques in detail
V. To evaluate and analyze the mechanism among multimedia devices, their communication principles, to investigate the usage of these devices, hence to analyze the needs of community
VI. To know the basic concepts in major fields of applied engineering ( computer vision, communications, data mining, sensors, human-computer interaction
VII. To know applications of multimedia systems, to face the challenges
and obtain a global view starting from theoretical concepts to big
applications used in our daily life.

Course Content

The teaching methods of the course are as follows:
Project
Lesson
Reading
Application
Simulation
Individual Study
Application

Weekly Detailed Course Contents

Week	Subject	Related Preparation
1)	Introduction to Multimedia Systems
2)	Introduction to Digital Images and multimedia protocols
3)	Image compression and Image Formats 1
4)	Image compression and Image Formats 2
5)	RGB images, Color spaces, Scaling, resizing, Arithmetic and Bitwise Operations, Binarization, Adaptive Thresholding, Dilation, Erosion Convolution, Image Filtering Techniques
6)	Dealing with video files in OpenCV Introduction to deep learning
7)	1st Midterm Exam	Exact midterm exam date will be announced
8)	Introduction to Generative AI for text, image and video (NLP, CV)
9)	Introduction to Information Theory and channel Coding
10)	Video Compression Techniques
11)	Basics of Computer Networks
12)	Streaming (MQTT)
13)	Video streaming with Gstreamer
14)	Semester review

Sources

Course Notes / Textbooks:	Digital Video Processing, A. Murat Tekalp, PEARSON Any other books related to subjects each week
References:	Digital Video Processing, A. Murat Tekalp, PEARSON Her hafta konularla ilgili başka kitaplar

Evaluation System

Semester Requirements	Number of Activities	Level of Contribution
Project	1	% 20
Midterms	1	% 40
Final	1	% 40
Total		% 100
PERCENTAGE OF SEMESTER WORK		% 40
PERCENTAGE OF FINAL WORK		% 60
Total		% 100

ECTS / Workload Table

Activities	Number of Activities	Workload
Course Hours	14	42
Project	8	64
Midterms	1	18
Final	1	36
Total Workload		160

Contribution of Learning Outcomes to Programme Outcomes

No Effect	1 Lowest	2 Low	3 Average	4 High	5 Highest

	Program Outcomes	Level of Contribution
1)	Acquire an ability to compile and analyze biological information, clearly present and discuss the conclusions, the inferred knowledge and the arguments behind them both in oral and written format.
2)	Detect biological problems, learn to make hypothesis and solve the hypothesis by using variety of experimental and observational methods.
3)	Develop effective communication skills and have competence in scientific speaking, reading and writing abilities in English and Turkish.
4)	Conduct research through paying attention to ethics, human values and rights. Pay special attention to confidentiality of information while working with human subjects.
5)	Utilize the wealth of information stored in computer databases to answer basic biological questions and solve problems such as diagnosis and treatment of diseases.	3
6)	Develop critical, creative and analytical thinking skills.	2
7)	Gain knowledge of different techniques and methods used in genetics and acquire the relevant laboratory skills.
8)	Gain knowledge of methods for collecting quantitative and qualitative data and obtain the related skills.	2
9)	Obtain basic concepts used in theory and practices of genetics and bioinformatics and establish associations between them.
10)	Search and use literature to improve himself/herself and follow recent developments in science and technology.	2
11)	Be aware of the national and international problems in the fields of genetics and bioinformatics and search for their solutions.