ECTS - - Mechatronics Engineering Master of Science with Thesis

Compulsory Departmental Courses

MDES600 - Research Methodology and Communication Skills (3 + 0) 5

Rigorous, scholarly research, particularly theses or dissertations. Literature review, surveys, meta-analysis, empirical research design, formulating research questions, theory building, qualitative and quantitative data collection and analysis methods, validity, reliability, triangulation, building evidences, writing research proposal

MECE521 - Control Engineering I (3 + 0) 5

State space analysis of systems, state feedback, observers, Lyapunov stability theory, phase portraits, and the describing function analysis.

MECE522 - Control Engineering II (3 + 0) 5

Fundamentals of state observers, regulator and control systems design, stochastic systems, Kalman filtering, MatLab-Simulink utilization; projects and laboratory studies about modeling and control of dynamical systems in mechatronic systems laboratory.

MECE589 - Graduation Seminar (0 + 0) 5

Scholar presentations of current research topics in mechatronics engineering.

MECE597 - Master's Thesis (0 + 0) 80

Thesis topic as stated on the thesis protocol.

Elective Courses

CE566 - Advanced Mathematical Methods in Civil Engineering (3 + 0) 5

First-, second- and higher-order linear ordinary differential equations, system of differential equations, power series solution of differential equations, Laplace transforms, partial differential equations, numerical integration and derivation, numerical solution of differential equations.

CMPE466 - Soft Computing (3 + 0) 5

Biological and artificial neurons, perceptron and multilayer perceptron; ANN models and learning algorithms; fuzzy sets and fuzzy logic; basic fuzzy mathematics; fuzzy operators; fuzzy systems: fuzzifier, knowledge base, inference engine, and various inference mechanisms such as Sugeno, Mamdani, Larsen etc., composition and defuzzifier.

CMPE541 - Advanced Databases (3 + 0) 5

Database system concepts, transaction processing, concurrency control and database recovery, object-oriented and object-relational databases, semi-structured data and XML, parallel and distributed databases, advanced concepts of distributed databases, introduction to big data, temporal databases.

CMPE564 - Natural Computing (3 + 0) 5

Problem solving by search, hill climbing, simulated annealing, artificial neural networks, genetic algorithms, swarm intelligence (including ant colony optimization and particle swarm optimization), artificial immune systems.

EE222 - Microcontrollers (3 + 2) 7

Basic microcontroller structure, memory organisation and addressing, addressing modes, assembly language programming, C programming, interrupts, interrupt programming, interfacing with input and display devices, timers, capture, compare and PWM operations, serial communication, I2C interface, A/D conversion.

EE449 - Pattern Classification and Sensor Applications for Engineers (3 + 0) 5

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.

EE503 - Linear System Theory (3 + 0) 5

Review of linear algebra concepts, linear system representations, existence of solutions, state transition matrices, canonical realizations, controller designs, observer designs, introduction to multi-input multi-output systems.

EE504 - Introduction to Systems Analysis (3 + 0) 5

Review of linear algebra concepts, classifications of systems and system representations, continuous and discrete time systems, state space realizations, analysis techniques: frequency domain, Laplace and z-domain analyses, solutions of linear systems, stability analysis; assessment of the techniques by a computational tool such as MATLAB.

EE505 - Neural Networks and Applications (3 + 0) 5

An introduction to basic neurobiology, the main neural network architectures and learning algorithms, and a number of neural network applications, McCulloch Pitts neurons, single-layer perceptrons, multi-layer perceptrons, radial basis function networks, committee machines, Kohonen self-organising maps, and learning vector quantization.

EE506 - Computational Methods in Electrical and Electronics Engineering (3 + 0) 5

Root finding and numerical integration, fixed and floating point arithmetic and error standards, one and multidimensional interpolation and extrapolation, numerical optimization techniques, least squares, statistical methods (Monte Carlo), computational approaches to linear transformations (Karhunen-Loeve, discrete Fourier).

EE519 - Speech Processing and Its Applications (3 + 0) 5

Features of the speech signal; time-domain and frequency-domain analysis techniques; speech coding fundamentals; speech processing applications, speech recognition, speech synthesis, speaker verification.

EE525 - Embedded System Design with Field Programmable Gate Arrays (3 + 0) 5

Language constructs of Verilog, behavioral models of combinational and sequential logic; logic, RTL, and high-level synthesis of combinational and sequential logic; datapath controllers; programmable logic and storage devices, HDL architectures for basic digital processing implementations.

EE571 - Digital Signal Analysis (3 + 0) 5

Mathematical methods for signal processing, spectrum estimation, discrete Karhunen-Loeve transform, detection of a signal in noise, multiple signal classification (MUSIC), least mean square algorithm, classification systems, Kalman filters.

EE573 - Computer Vision (3 + 0) 5

Human vision, geometric camera models, image segmentation, object recognition, video signals and standards, vision system design, computer vision and digital video applications.

IE503 - System Analysis and Design (3 + 0) 5

Requirements engineering and modeling, structural modeling, system architecture and user interface design, documentation, testing and installation, traceability, project planning and management.

ISE542 - IT Security (3 + 0) 5

Introduction to IT security, security plans, security policies, security models: TCSEC, common criteria, ISE/IEC 27000, CIBIT, ITIL; security risk assessment and management; security solutions; IT services and security; personnel security; ethics in IT security.

MATH587 - Applied Mathematics (3 + 0) 5

Calculus of variations: Euler-Lagrange equation, the first and second variations, necessary and sufficient conditions for extrema, Hamilton`s principle, and applications to Sturm-Liouville problems and mechanics; integral equations: Fredholm and Volterra integral equations, the Green?s function, Hilbert-Schmidt theory, the Neumann series and Fredho

MDES610 - Mathematical Modeling via Differential and Difference Equations (3 + 0) 5

Differential equations and solutions, models of vertical motion, single-species population models, multiple-species population models, mechanical oscillators, modeling electric circuits, diffusion models, modeling by means of difference equations.

MDES615 - Analytical Probability Theory (3 + 0) 5

Sigma-algebra of sets, measure, integral with respect to measure; probability space; independent events and independent experiments; random variables and probability distributions; moments and numerical characteristics; random vectors and independent random variables; convergence of random variables; transform methods; sums of independent random v

MDES620 - Numerical Solution of Differential Equations (3 + 0) 5

Numerical solution of initial value problems; Euler, multistep and Runge-Kutta methods; numerical solution of boundary value problems; shooting and finite difference methods; stability, convergence and accuracy; numerical solution of partial differential equations; finite difference methods for parabolic, hyperbolic and elliptic equations; explic

MDES621 - Numerical Linear Algebra (3 + 0) 5

Floating point computations, vector and matrix norms, direct methods for the solution of linear systems, least squares problems, eigenvalue problems, singular value decomposition, iterative methods for linear systems.

MDES650 - Advanced System Simulation (3 + 0) 5

Discrete simulation models for complex systems, input probability distributions, random variable generation, statistical inferences, variance reduction, continuous processes, verification and validation, advanced models.

MDES655 - Linear Optimization (3 + 0) 5

Sets of linear equations, linear feasibility and optimization, local and global optima, the Simplex method and its variants, theory of duality and the dual-Simplex method, network-Simplex algorithms, computational complexity issues and interior-point algorithms.

MECE447 - Path Planning and Navigation (3 + 0) 5

Introduction, kinematic models for mobile robots, mobile robot control, robot attitude, robot navigation, path finding, obstacle mapping and its application to robot navigation, application of Kalman filtering.

MFGE420 - Project Management in Manufacturing (3 + 0) 5

Project management standards;project,portfolio,program and operation management concepts; managing participation,teamwork, and conflict;need identification and assessment,problem definition; creativity and idea generation;methods and tools of functional/physical/task decomposition;mind mapping;planning methods; cost estimation and budgeting;time management and scheduling;project quality management;resource allocation; project risk management techniques; project execution, monitoringtechniques

MFGE577 - Quality Control and Metrology (3 + 0) 5

Elementary metrology, linear-angular and comparative measurement, instruments and gauges for testing straightness, flatness, squareness, parallelism, limits, fits and gauges, inspection, quality function in industry, fundamentals of statistical concept in quality control, control charts in SQC, sampling inspection, operation characteristics (OC) cu

SE550 - Software Engineering (3 + 0) 5

Introduction to software engineering and related topics; software process and project metrics; project planning; scheduling and tracking; configuration management; software quality assurance; requirement analysis; data flow diagrams and related topics; design concepts and methods; implementation; testing methods and test strategies; object-oriented

SE573 - Applied Machine Learning in Data Analytics (3 + 0) 5

Data statistics; linear discriminant analysis; decision trees; artificial neural networks; Bayesian learning; distance measures; instance-based and reinforcement learning; clustering; regression; support vector machines.