ECTS - Pattern Classification and Sensor Applications for Engineers

Pattern Classification and Sensor Applications for Engineers (EE449) Course Detail

Course Name Course Code Season Lecture Hours Application Hours Lab Hours Credit ECTS
Pattern Classification and Sensor Applications for Engineers EE449 Area Elective 3 0 0 3 5
Pre-requisite Course(s)
N/A
Course Language English
Course Type Elective Courses
Course Level Bachelor’s Degree (First Cycle)
Mode of Delivery Face To Face
Learning and Teaching Strategies Lecture, Discussion, Drill and Practice.
Course Coordinator
Course Lecturer(s)
  • Asst. Prof. Dr. Hakan TORA
Course Assistants
Course Objectives Sensors, general information about sensor types and sensor working principles. What is a pattern? Pattern classification applications. Theory and methods of pattern classification. Feature extraction and selection. MATLAB Classification Learner Tool. Analysis and performance of classifiers. RFID basics.
Course Learning Outcomes The students who succeeded in this course;
  • Know about sensors.
  • Design a classifier system.
  • Analyze the performance of classifiers.
  • Design and implement a project including sensors.
  • Use the MATLAB Classification Learner application tool.
Course Content Sensors, general information about sensor types and sensor working principles; what is a pattern; pattern classification applications; theory and methods of pattern classification; feature extraction and selection; MATLAB Classification Learner Tool; analysis and performance of classifiers; RFID basics.

Weekly Subjects and Releated Preparation Studies

Week Subjects Preparation
1 What is a sensor? Obtain the reference books.
2 Sensor types. Review last week’s topics
3 Working principles of sensors. Review last week’s topics
4 What is a pattern? Review last week’s topics
5 Theory of pattern classification Review last week’s topics
6 Feature extraction. Review last week’s topics
7 Feature selection. Review last week’s topics
8 Analysis and performance of classifiers. Review last week’s topics
9 Midterm Exam Review all topics up-to this week
10 Design of an interdisciplinary project Review all topics
11 Project work continued Review all topics
12 Implementation of the project. Review all topics
13 Implementation of the project Review all topics
14 Presentations Review the project

Sources

Course Book 1. Duda, R. O., & Hart, P. E. (2006). 2nd Edition, Pattern classification. John Wiley & Sons.

Evaluation System

Requirements Number Percentage of Grade
Attendance/Participation - -
Laboratory - -
Application - -
Field Work - -
Special Course Internship - -
Quizzes/Studio Critics - -
Homework Assignments 3 15
Presentation - -
Project 1 30
Report - -
Seminar - -
Midterms Exams/Midterms Jury 1 20
Final Exam/Final Jury 1 35
Toplam 6 100
Percentage of Semester Work
Percentage of Final Work 100
Total 100

Course Category

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

The Relation Between Course Learning Competencies and Program Qualifications

# Program Qualifications / Competencies Level of Contribution
1 2 3 4 5
1 Adequate knowledge in mathematics, science and engineering subjects pertaining to the relevant discipline; ability to use theoretical and applied knowledge in these areas in the solution of complex engineering problems.
2 Ability to formulate, and solve complex mechatronics engineering problems; ability to select and apply proper analysis and modeling methods for this purpose.
3 Ability to design a complex mechatronics engineering system, process, device or product under realistic constraints and conditions, in such a way as to meet the desired result; ability to apply modern design methods for this purpose.
4 Ability to select and use modern techniques and tools needed for analyzing and solving complex problems encountered in mechatronics engineering and robot technology practices; ability to employ information technologies effectively.
5 Ability to design and conduct experiments, gather data, analyze and interpret results for investigating complex mechatronics engineering and robot technology problems or research questions.
6 Ability to work efficiently in intra-disciplinary and multi-disciplinary teams; ability to work individually.
7 Ability to communicate effectively, both orally and in writing; knowledge of a minimum of one foreign language; ability to write effective reports and comprehend written reports, prepare design and production reports, make effective presentations, and give and receive clear and intelligible instructions.
8 Awareness of the need for lifelong learning; ability to access information, to follow developments in science and technology, and to continue to educate him/herself
9 a-) Knowledge on behavior according to ethical principles, professional and ethical responsibility b-) Knowledge on standards used in engineering practices.
10 a-) Knowledge about business life practices such as project management, risk management, and change management b-) Awareness in entrepreneurship, innovation; knowledge about sustainable development.
11 Knowledge about the global and social effects of engineering practices on health, environment, and safety, and contemporary issues of the century reflected into the field of engineering; awareness of the legal consequences of engineering solutions.
12 Competency on defining, analyzing and surveying databases and other sources, proposing solutions based on research work and scientific results and communicate and publish numerical and conceptual solutions in the field of mechatronics engineering.
13 Consciousness on the environment and social responsibility, competencies on observation, improvement and modify and implementation of projects for the society and social relations and be an individual within the society in such a way that planning, improving or changing the norms with a criticism.

ECTS/Workload Table

Activities Number Duration (Hours) Total Workload
Course Hours (Including Exam Week: 16 x Total Hours) 16 3 48
Laboratory
Application
Special Course Internship
Field Work
Study Hours Out of Class 16 3 48
Presentation/Seminar Prepration
Project 1 20 20
Report
Homework Assignments 3 3 9
Quizzes/Studio Critics
Prepration of Midterm Exams/Midterm Jury 1 3 3
Prepration of Final Exams/Final Jury 1 3 3
Total Workload 131