İNÖNÜ UNIVERSITYFACULTY OF ENGINEERING

COMPUTER ENGINEERING DEPARTMENT PH.D DEGREE COURSE INFORMATION

EXISTINGPH.D COURSES

Sıra No / Dersin Kodu / Dersin Adı / Kredisi
1 / BM 551 / Advanced Graph Theory / 3-0-3
2 / BM 552 / Computational Intelligence / 3-0-3
3 / BM 553 / Distributed Database Systems / 3-0-3
4 / BM 554 / Sensor Networks / 3-0-3
5 / BM 555 / Autonomous Robots / 3-0-3
6 / BM 556 / Approximation Algorithms / 3-0-3
7 / BM 557 / Advanced Communication Systems / 3-0-3
8 / BM 558 / Advanced Data Mining / 3-0-3
9 / BM 559 / Convex Analysis and Optimization / 3-0-3
10 / BM 560 / Information Theory / 3-0-3
11 / BM 561 / Machine Vision / 3-0-3
12 / BM 562 / Multi-Channel Parallelism / 3-0-3
13 / BM 563 / Computational Statistics / 3-0-3
14 / BM 564 / Industrial Automation / 3-0-3
15 / BM 565 / Intelligent Control / 3-0-3
16 / BM 566 / Design Automation / 3-0-3
17 / BM 567 / Control of Systems with Parametric Uncertainty / 3-0-3
18 / BM 568 / Nonlinear Control Systems / 3-0-3
19 / BM 569 / Wireless Detector Networks / 3-0-3
20 / BM 570 / Network Optimization / 3-0-3
21 / BM 571 / Object Oriented Modelling and Design / 3-0-3
22 / BM 572 / Network Mining / 3-0-3
23 / BM 573 / Semantics and Applications of Natural Language / 3-0-3
24 / BM 574 / Fractional Order Systems / 3-0-3
24 / BM 575 / Nonlinear Fractional Order Systems / 3-0-3
25 / BM 524 / Scientific Research Techniques and Academic Ethics / 3-0-3
BM 700 / Expert Field Course
BM 800 / Seminar
BM 900 / Thesis Management

PH.D COURSES PROPOSED

Sıra No / Dersin Kodu / Dersin Adı / Kredisi
1 / BM 576 / Big Data Analytics / 3-0-3
2 / BM 577 / Advanced NOSQL Database Systems / 3-0-3
3 / BM 578 / Statistical Methods in Natural Language Processing / 3-0-3
4 / BM 579 / Quantum Computation / 3-0-3
5 / BM 580 / Data Compression / 3-0-3
6 / BM 581 / Computational Geometry / 3-0-3
7 / BM 582 / Digital Geometry Processing / 3-0-3
8 / BM 583 / Advanced Computer Graphics and User Interfaces / 3-0-3

DERSLERE AİT AKTS FORMLARI

COURSE PLAN
Course Title / Course Code / Semester / Hours/Week / Credits / ECTS
T / U / L
Advanced Graph Theory / BM 551 / 1 / 3 / 0 / 0 / 3 / 7,5
Prerequisities / None
Language of Instruction / Turkish
Course Level / Doctorate
Course Type / Elective
Instructors / -
Assistants / -
Goals / To teach advanced graph techniques and algorithms and to implement them.
Learning Outcomes / 1. To teach the basics of graph theory
2. To teach advanced topics in graph theory
3. To provide students to learn and apply algorithms of graph theory.
Content / Perfect graph, triangular graphs and features, recursive functions on triangular graphs. Comparison graphs, comparison invariants, preference and indifference, temporary conclusion and range algebra. Matrix eigenvalues and eigenvectors, mathematical topology, spectral graph theory, graph embedding and optimization, arbitrary and regular graph partitioning, spectral graph partitioning, VLSI plan criteria and graph drawing.
COURSE CONTENT
Week / Topics / Pre Study
1 / Perfect Graphs / Related topic should be studied from course note
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Related topic should be studied from course note
Related topic should be studied from course note
Related topic should be studied from course note
Related topic should be studied from course note
Related topic should be studied from course note
Related topic should be studied from course note
2 / Triangular graphs and features / Related topic should be studied from course note
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3 / Recursive algorithms on triangular graphs / Related topic should be studied from course note
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Related topic should be studied from course note
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Related topic should be studied from course note
4 / Comparison charts, comparison invariants, preference and indifference, temporary conclusion and interval algebra - I / Related topic should be studied from course note
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Related topic should be studied from course note
Related topic should be studied from course note
Related topic should be studied from course note
Related topic should be studied from course note
Related topic should be studied from course note
Related topic should be studied from course note
Related topic should be studied from course note
Related topic should be studied from course note
Related topic should be studied from course note
Related topic should be studied from course note
Related topic should be studied from course note
Related topic should be studied from course note
5 / Comparison charts, comparison invariants, preference and indifference, temporary conclusion and interval algebra - II / Related topic should be studied from course note
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Related topic should be studied from course note
Related topic should be studied from course note
Related topic should be studied from course note
Related topic should be studied from course note
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Related topic should be studied from course note
Related topic should be studied from course note
6 / Eigenvectors and eigenvalues of a matrix / Related topic should be studied from course note
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7 / Mathematical toplogy / Related topic should be studied from course note
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Related topic should be studied from course note
Related topic should be studied from course note
Related topic should be studied from course note
Related topic should be studied from course note
Related topic should be studied from course note
Related topic should be studied from course note
Related topic should be studied from course note
Related topic should be studied from course note
8 / Spectral Graph Theory – I / Related topic should be studied from course note
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Related topic should be studied from course note
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Related topic should be studied from course note
Related topic should be studied from course note
Related topic should be studied from course note
Related topic should be studied from course note
Related topic should be studied from course note
Related topic should be studied from course note
Related topic should be studied from course note
Related topic should be studied from course note
Related topic should be studied from course note
Related topic should be studied from course note
9 / Spectral Graph Theory – II / Related topic should be studied from course note
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Related topic should be studied from course note
Related topic should be studied from course note
Related topic should be studied from course note
Related topic should be studied from course note
Related topic should be studied from course note
Related topic should be studied from course note
Related topic should be studied from course note
Related topic should be studied from course note
Related topic should be studied from course note
Related topic should be studied from course note
Related topic should be studied from course note
Related topic should be studied from course note
10 / Graph embedding and optimization - I / Related topic should be studied from course note
Related topic should be studied from course note
Related topic should be studied from course note
Related topic should be studied from course note
Related topic should be studied from course note
Related topic should be studied from course note
Related topic should be studied from course note
Related topic should be studied from course note
Related topic should be studied from course note
Related topic should be studied from course note
Related topic should be studied from course note
Related topic should be studied from course note
Related topic should be studied from course note
Related topic should be studied from course note
11 / Graph embedding and optimization – II / Related topic should be studied from course note
Related topic should be studied from course note
Related topic should be studied from course note
Related topic should be studied from course note
Related topic should be studied from course note
Related topic should be studied from course note
Related topic should be studied from course note
Related topic should be studied from course note
Related topic should be studied from course note
Related topic should be studied from course note
Related topic should be studied from course note
Related topic should be studied from course note
Related topic should be studied from course note
Related topic should be studied from course note
12 / Arbitrary and regular graph partitioning / Related topic should be studied from course note
Related topic should be studied from course note
Related topic should be studied from course note
Related topic should be studied from course note
Related topic should be studied from course note
Related topic should be studied from course note
Related topic should be studied from course note
Related topic should be studied from course note
Related topic should be studied from course note
Related topic should be studied from course note
Related topic should be studied from course note
Related topic should be studied from course note
Related topic should be studied from course note
Related topic should be studied from course note
13 / Spectral graph partitioning / Related topic should be studied from course note
Related topic should be studied from course note
Related topic should be studied from course note
Related topic should be studied from course note
Related topic should be studied from course note
Related topic should be studied from course note
Related topic should be studied from course note
Related topic should be studied from course note
Related topic should be studied from course note
Related topic should be studied from course note
Related topic should be studied from course note
Related topic should be studied from course note
Related topic should be studied from course note
Related topic should be studied from course note
14 / VLSI plan criteria and graph drawing / Related topic should be studied from course note
Related topic should be studied from course note
Related topic should be studied from course note
Related topic should be studied from course note
Related topic should be studied from course note
Related topic should be studied from course note
Related topic should be studied from course note
Related topic should be studied from course note
Related topic should be studied from course note
Related topic should be studied from course note
Related topic should be studied from course note
Related topic should be studied from course note
Related topic should be studied from course note
Related topic should be studied from course note
RECOMMENDED SOURCES
MATERIAL SHARE
Documents
Assignments
Exams
ASSESSMENT
IN-TERM STUDIES / QUANTITY / PERCENTAGE
Mid-terms / 1 / %50
Final
Assignments/Presentations / 5 / %50
Total / 100
COURSE'S CONTRIBUTION TO PROGRAM
No / Program Learning Outcomes / Contribution
1 / 2 / 3 / 4 / 5
1 / To be able to produce solutions for any problem in the field by using scientific processes / X
2 / Be able to identify research problems related to current problems in the field / X
3 / Plan independent scientific research in the field / X
4 / Do independent scientific research in the field / X
5 / Apply quantitative, qualitative and mixed methods in the field research / X
6 / Having a comprehensive view of the research methods used in the field / X
7 / To be able to consult a scientific work carried out in the field
8 / Planning researches that can produce solutions to the problems of education system / X
9 / Preparation of scientific research or project proposal / X
10 / To have mastered the legislation related to research and publishing / X
11 / To know the ethical principles to be followed while writing research reports / X
12 / Identify ethical violations in research reports using plagiarism software programs / X
ECTS ALLOCATED BASED ON STUDENT WORKLOAD BY THE COURSE DESCRIPTION
Activities / Quantity / Duration
(Hour) / Total
Workload
(Hour)
Course Duration (Including the exam week: 14x) Total course hours)ders saati) / 14 / 3 / 42
Hours for off-the-classroom study (Pre-study, practice) / 14 / 7 / 98
Assignments - Presentations / 7 / 11 / 77
Midterms / 1 / 4 / 4
Final examination / 1 / 4 / 4
Total Work Load / 225
Total Work Load / 30 (h) / 7,5
ECTS Credit of the Course / 7,5
COURSE PLAN
Course Title / Course Code / Semester / Hours/Week / Credits / ECTS
T / U / L
Computational Intelligence / BM 552 / 1 / 3 / 0 / 0 / 3 / 7,5
Prerequisites / None
Language of Instruction / Turkish
Course Level / Doctorate
Course Type / Elective
Instructors / -
Assistants / -
Goals / Introducing various computational artificial intelligence techniques to our students and giving information about the applications of real life problems. At the same time, it is the practice of accounting intelligence.
Learning Outcomes / 1. To teach the basic techniques of computational techniques of artificial intelligence.
2. Encourage students to read some of the new work in the field of computational intelligence techniques.
3. The implementation of at least one of the computational intelligence techniques of every student.
Content / Traditional artificial intelligence and challenges. The definition of accounting intelligence. Definition and basic elements of soft computing. Computational learning theory. Synergism in computational intelligence. Computational intelligence in industrial applications. The development of computational intelligence. Concepts, design and realization of computational intelligence, involving a combination of different methodologies. Intelligent data management systems, rule-based systems, systems for intuitive problem solving, theoretical and practical use of computational intelligence for risk analysis and diagnostics.
COURSE CONTENT
Week / Topics / Pre Study
1 / Traditional artificial intelligence and challenges / Related topic should be studied from course note
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2 / Computational intelligence / Related topic should be studied from course note
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3 / Definition and basic elements of soft computing / Related topic should be studied from course note
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4 / Computational learning-I / Related topic should be studied from course note
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