CLICK HERE FOR THE COURSE SYLLABUS (.pdf)


COURSE INTRODUCTION AND APPLICATION INFORMATION

 
Course Name
Code
Semester
Theory
(hour/week)
Application/Laboratory
(hour/week)
Local Credits
ECTS
Applied Homology, Computational Approach
MATH 669
Fall/Spring
3
0
3
7.5

Prerequisites
None

Course Language
English
Course Type
Elective
Course Level
Third Cycle
Course Coordinator -
Course Lecturer(s) -
Course Assistants -
Course Objectives To introduce basic methods of Homological Algebra with an emphasis on Computational Methods.
Course Learning Outcomes The students who succeeded in this course;
  • will be able to define homology,
  • will be able to compute homology,
  • will be able to apply homological methods,
  • will be able to transform nonlinear problems into homological problems,
  • will be able to use appropriate software for calculations.
Course Content The course will focus on the concepts and principles homology, especially on the computaitonal side. This core knowledge will enable attendees to apply homological methods to nonlinear problems, and provide sufficient characterization. Students will also learn how to use appropriate software.

 

WEEKLY SUBJECTS AND RELATED PREPARATION STUDIES

Week Subjects Related Preparation
1 Introductory Applications: Analyzing Images, Nonlinear Dynamics, Graphs “Computational Homology”, Kaczynski, T., Mischaikow, K., Mrozek, M., 2004, Springer.
2 Homology by Cubical Sets “Computational Homology”, Kaczynski, T., Mischaikow, K., Mrozek, M., 2004, Springer.
3 Computing Homologies “Computational Homology”, Kaczynski, T., Mischaikow, K., Mrozek, M., 2004, Springer.
4 Review of Matrix Algebra “Computational Homology”, Kaczynski, T., Mischaikow, K., Mrozek, M., 2004, Springer.
5 Chain Maps “Computational Homology”, Kaczynski, T., Mischaikow, K., Mrozek, M., 2004, Springer.
6 Interval Arithmetic and Maps, Chains “Computational Homology”, Kaczynski, T., Mischaikow, K., Mrozek, M., 2004, Springer.
7 Homology “Computational Homology”, Kaczynski, T., Mischaikow, K., Mrozek, M., 2004, Springer.
8 Algorithms for Homology Computations “Computational Homology”, Kaczynski, T., Mischaikow, K., Mrozek, M., 2004, Springer.
9 An Application: Image Processing “Computational Homology”, Kaczynski, T., Mischaikow, K., Mrozek, M., 2004, Springer.
10 Homological Algebra, Alternatives “Computational Homology”, Kaczynski, T., Mischaikow, K., Mrozek, M., 2004, Springer.
11 Applications: Nonlinear Dynamics “Computational Homology”, Kaczynski, T., Mischaikow, K., Mrozek, M., 2004, Springer.
12 Term Project: (Selected Applications) Fixed Point Theorems “Computational Homology”, Kaczynski, T., Mischaikow, K., Mrozek, M., 2004, Springer.
13 Term Project: (Selected Applications) Degree Theory “Computational Homology”, Kaczynski, T., Mischaikow, K., Mrozek, M., 2004, Springer.
14 Term Project: (Selected Applications) Chaotic Dynamics “Computational Homology”, Kaczynski, T., Mischaikow, K., Mrozek, M., 2004, Springer.
15 Comparison of Simplicial and Cubical Complexes. “Computational Homology”, Kaczynski, T., Mischaikow, K., Mrozek, M., 2004, Springer.
16 Review of the Semester  

 

SOURCES

Course Notes / Textbooks “Computational Homology”, Kaczynski, T., Mischaikow, K., Mrozek, M., 2004, Springer.
References “An Introduction to Homological Algebra”, Rotman, J.J., 2009, Springer. Various research papers from recent studies.

 

EVALUATION SYSTEM

Semester Requirements Number Percentage of Grade
Attendance/Participation
Laboratory
Application
Field Work
Special Course Internship (Work Placement)
Quizzes/Studio Critics
Homework Assignments
5
20
Presentation/Jury
Project
Seminar/Workshop
Midterms/Oral Exams
2
40
Final/Oral Exam
1
40
Total

PERCENTAGE OF SEMESTER WORK
60
PERCENTAGE OF FINAL WORK
40
Total

 

COURSE CATEGORY

Course Category

Core Courses
Major Area Courses
Supportive Courses
X
Media and Managment Skills Courses
Transferable Skill Courses

 

THE RELATIONSHIP BETWEEN COURSE LEARNING OUTCOMES AND PROGRAM QUALIFICATIONS

#
Program Qualifications / Outcomes
* Level of Contribution
1
2
3
4
5
1

To develop and deepen his/her knowledge on theories of mathematics and statistics and their applications in level of expertise, and to obtain unique definitions which bring innovations to the area, based on master level competencies,

X
2

To have the ability of original, independent and critical thinking in Mathematics and Statistics and to be able to develop theoretical concepts,

X
3

To have the ability of defining and verifying problems in Mathematics and Statistics,

X
4

With an interdisciplinary approach, to be able to apply theoretical and applied methods of mathematics and statistics in analyzing and solving new problems and to be able to discover his/her own potentials with respect to the application,

X
5

In nearly every fields that mathematics and statistics are used, to be able to execute, conclude and report a research, which requires expertise, independently,

X
6

To be able to evaluate and renew his/her abilities and knowledge acquired in the field of Applied Mathematics and Statistics with critical approach, and to be able to analyze, synthesize and evaluate complex thoughts in a critical way,

X
7

To be able to convey his/her analyses and methods in the field of Applied Mathematics and Statistics to the experts in a scientific way,

X
8

To be able to use national and international academic resources (English) efficiently, to update his/her knowledge, to communicate with his/her native and foreign colleagues easily, to follow the literature periodically, to contribute scientific meetings held in his/her own field and other fields systematically as written, oral and visual.

X
9

To be familiar with computer software commonly used in the fields of Applied Mathematics and Statistics and to be able to use at least two of them efficiently,

X
10

To contribute the transformation process of his/her own society into an information society and the sustainability of this process by introducing scientific, technological, social and cultural advances in the fields of Applied Mathematics and Statistics,

X
11

As having rich cultural background and social sensitivity with a global perspective, to be able to evaluate all processes efficiently, to be able to contribute the solutions of social, scientific, cultural and ethical problems and to support the development of these values,

X
12

As being competent in abstract thinking, to be able to connect abstract events to concrete events and to transfer solutions, to analyze results with scientific methods by designing experiment and collecting data and to interpret them,

X
13

To be able to produce strategies, policies and plans about systems and topics in which mathematics and statistics are used and to be able to interpret and develop results,

X
14

To be able to evaluate, argue and analyze prominent persons, events and phenomena, which play an important role in the development and combination of the fields of Mathematics and Statistics, within the perspective of the development of other fields of science,

X
15

In Applied Mathematics and Statistics, to be able to sustain scientific work as an individual or a group, to be effective in all phases of an independent work, to participate decision-making process and to make and execute necessary planning within an effective time schedule.

X

*1 Lowest, 2 Low, 3 Average, 4 High, 5 Highest

ECTS / WORKLOAD TABLE

Activities Number Duration (Hours) Total Workload
Course Hours (Including Exam Week: 16 x Total Hours)
16
3
Laboratory
Application
Special Course Internship (Work Placement)
Field Work
Study Hours Out of Class
15
5
Presentations / Seminar
Project
Homework Assignments
5
2
Quizzes
Midterms / Oral Exams
2
22
Final / Oral Exam
1
48
    Total Workload

CLICK HERE FOR THE COURSE SYLLABUS (.pdf)

 
 

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