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 Lecturer(s) |
|
| 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;
|
| 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. |
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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 subjects specific to the Materials Engineering; the ability to apply theoretical and practical knowledge of these areas to solve complex engineering problems and to model and solve of materials systems | X | ||||
| 2 | Understanding of science and engineering principles related to the structures, properties, processing and performance of Materials systems | |||||
| 3 | Ability to identify, define, formulate and solve complex engineering problems; selecting and applying proper analysis and modeling techniques for this purpose | X | ||||
| 4 | Ability to design and choose proper materials for a complex system, process, device or product under realistic constraints and conditions to meet specific requirements; the ability to apply modern design and materials selection methods for this purpose | X | ||||
| 5 | Ability to develop, select and utilize modern techniques and tools essential for the analysis and solution of complex problems in Materails Engineering applications; the ability to utilize information technologies effectively | X | ||||
| 6 | Ability to design and conduct experiments, collect data, analyse and interpret results using statistical and computational methods for complex engineering problems or research topics specific to Materials Engineering | X | ||||
| 7 | Ability to work effectively in inter/inner disciplinary teams; ability to work individually | X | ||||
| 8 | Effective oral and written communication skills in Turkish; knowlegde of at least one foreign language; the ability to write effective reports and comprehend written reports, to prepare design and production reports, to make effective presentations, to give and receive clear and understandable instructions | X | ||||
| 9 | Recognition of the need for lifelong learning; the ability to access information; follow recent developments in science and technology with continuous self-development | X | ||||
| 10 | Ability to behave according to ethical principles, awareness of professional and ethical responsibility; knowledge of standards used in engineering applications | X | ||||
| 11 | Knowledge on business practices such as project management, risk management and change management; awareness in entrepreneurship and innovativeness; knowledge of sustainable development | X | ||||
| 12 | Knowledge of the effects of Materials Engineering applications on the universal and social dimensions of health, environment and safety, knowledge of modern age problems reflected on engineering; awareness of legal consequences of engineering solutions | X | ||||
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 | ||