COURSES OFFERED IN ENGLISH

 

Faculty: TECHNOLOGICAL APPLICATIONS

 

Department: COMPUTER SCIENCE AND ENGINEERING

 

1st SEMESTER

Course Title

PROGRAMMING (C programming language)

ECTS

 6

Typical Semester

 1st

Hours/ Week

 4

Brief Description (5-6 lines)

 Introduction to computer programming with C, Conditional statements, Loops, Functions, Data structures, Array and string manipulation: sorting (bubble, selection, insertion), searching (sequential, binary)

Main Learning Goals (list up to 10)

  • Understanding the main issues concerning programming

  • Understanding the main issues concerning conditional and loop techniques

  • Understanding the main issues concerning functions, data structures, and arrays

  • Ability to correctly design a simple program

  • Ability to write simple programs in C

Lecture based

 

Reading course

 X

(mark with an “X” the appropriate box)

Student evaluation method/ grading1

Reading course: Project, Lab Exercises, Semi and Final Exams

 

Course Title

ANALOG ELECTRONICS 

ECTS

 6

Typical Semester

 1st

Hours/ Week

 4

Brief Description (5-6 lines)

Electricity, main concepts, Ohm, Kirchoff, Thevenin and Norton laws, equivalent circuits, units used in electricity. Voltage and Current sources (dependent and independent). Resistors combined in series and in parallel. Introduction to semiconductors. The PN contact and the features/usage of the diodes. Zener diodes and LEDs, applications. BJT transistors, operating mode, amplifiers. Operational Amplifiers. FET transistors. CMOS gates using MOSFETs

Video lectures available at the playlist:

https://www.youtube.com/playlist?list=PLXUuQj2gQ4s9FmYI0-YakxdMEU_RgC_6L

Main Learning Goals (list up to 10)

  • Comprehend the concepts of electricity and what the various units mean

  • Analysis of electrical circuits with passive components using the Ohm, Kirchoff, Thevenin, Norton laws

  • Analysis of electronic circuits with active components (diodes, transistors, opamps) in DC or AC, small signal and large signal analysis

  • Design of electronic circuits for the conversion of AC to DC

  • Design circuits with appropriate transistor bias

  • Design of amplifiers using BJT transistors or op-amps

  • Design of other applications using op-amps

  • Design of CMOS gates using MOSFET transistors

Lecture based

 

Reading course

X 

(mark with an “X” the appropriate box)

Student evaluation method/ grading2

Reading course : the students watch the videolectures or study the topics covered by the course. They can ask questions to the supervisor through email or by visiting his office during the time he is available for students.

The evaluation is performed by written final exams in English (100%). If the student selects to also attend the lab, he/she will also be evaluated by written final exams on the topics taught at the lab (100%).

 

Course Title

INTRODUCTION TO COMPUTER SCIENCE 

ECTS

 6

Typical Semester

 1st

Hours/ Week

4

Brief Description (5-6 lines)

This course is an introduction to Computer Science. Students will be introduced to fundamental topics in Informatics while developing a basic understanding of Information. Theory Its goal is to help the students develop problem-solving skills, computational thinking, and acquire the fundamental programming skills necessary during the rest of the curriculum. Introduction to the computer science, Architecture of computers: low-level data representation and instruction processing, Operating systems, Software development: problem decomposition, abstraction, data structures, implementation, debugging, testing, Computer systems: programming languages, compilers, operating systems, Algorithms: their design, specification and analysis, Computer Networks Computers in the real world: networks, security and cryptography, artificial intelligence, social issues.

Main Learning Goals (list up to 10)

  • Introduction to the computer science.

  • Architecture of computers: low-level data representation and instruction processing.

  • Operating systems

  • Software development: problem decomposition, abstraction, data structures, implementation, debugging, testing.

  • Computer systems: programming languages, compilers, operating systems.

  • Algorithms: their design, specification, and analysis.

  • Computer Networks

  • Computers in the real world: networks, security and cryptography, artificial intelligence, social issues.

Lecture based

 

Reading course

 X

(mark with an “X” the appropriate box)

Student evaluation method/ grading3

Reading course: Project, Lab Exercises, Semi and Final Exams

 

2nd SEMESTER

Course Title

ANALYSIS & DESIGN OF INFORMATION SYSTEMS 

ECTS

 6

Typical Semester

 2nd

Hours/ Week

 4

Brief Description (5-6 lines)

 Introduction to Information Systems (IS), Types and Structure of IS, Contribution and Function of Human Resources in the Creation and Maintenance of IS, Development Methodologies of IS, Lifecycle Development of IS, Analysis of IS, Design of IS, Modeling of the Process of Developing a IS, Functional Decomposition Diagrams and Data Flow Diagrams, Decision Tables and Decision Trees, Entity Life Histories, Entity-Relationships Diagrams

Main Learning Goals (list up to 10)

  • IS basic concepts

  • Ability to understand problems related to IS

  • Ability to distinguish the different tasks taking place in each phase of the IS development lifecycle

  • Ability to design Functional Decomposition Diagrams

  • Ability to design Data Flow Diagrams

  • Ability to design Entity-Relationship Diagrams

Lecture based

 

Reading course

 X

(mark with an “X” the appropriate box)

Student evaluation method/ grading

Reading course: Project, Lab Exercises, Final Exam

 

Course Title

NETWORKED CONTROL SYSTEMS – INDUSTRIAL NETWORKS

ECTS

 5

Typical Semester

 2nd

Hours/ Week

 4

Brief Description (5-6 lines)

Introduction to basic principles, composition, design, and operation of Network Control Systems (NCS) as well as to standard Industrial Computer Networks. System analysis and modeling methods in State-Space. Introduction to principles and concepts of real time systems and investigation of the consequence of the real time parameter on the operation of Network Control Systems and industrial processes. Reflecting on the most popular Industrial Field Networks such as Profibus, CANbus, ControlNet etc.

Main Learning Goals (list up to 10)

  • Become familiar with basic concepts and requirements of NCS

  • Become familiar with basic concepts and requirements of Real Time Systems

  • Ability to understand the functionality of popular Industrial Field Networks

  • Ability to understand issues related to real time industrial processes

  • Ability to apply Industrial Field Networks to real world problems

  • Ability to develop PLC programs in Ladder, SFC and FCB programming languages

Lecture based

 

Reading course

 X

(mark with an “X” the appropriate box)

Student evaluation method/ grading

Reading course: Project, Lab Exercises, Final Exam

 

Course Title

FILE AND DATA STRUCTURES

ECTS

 5

Typical Semester

 2nd

Hours/ Week

 4

Brief Description (5-6 lines)

 Text and binary files, Indexed files, Advanced sorting and searching techniques (quick and merge sort, hashing), Data structures: stack, queue, single and double linked lists, binary trees

Main Learning Goals (list up to 10)

  • Understanding advanced issues in file manipulation

  • Ability to write complex programs to manage files

  • Understanding data structures and their use

  • Ability to design and write programs using complex data structures

Lecture based

 

Reading course

X 

(mark with an “X” the appropriate box)

Student evaluation method/ grading

Reading course: Project, Lab Exercises, Semi and Final Exams

 

Course Title

DIGITAL SYSTEMS

ECTS

 6

Typical Semester

 2nd

Hours/ Week

 4

Brief Description (5-6 lines)

Boole algebra. Logic gates. Combinational logic. Logic functions. Digital combinational circuits. Karnaugh Maps. Sequential logic. Basic elements of sequential logic (flip-flops). Registers, counters, shift registers, memories. Design of sequential logic circuits.

Main Learning Goals (list up to 10)

  • Understanding of main concepts on digital logic and digital systems

  • To be able to simplify logic circuits using Karnaugh Maps

  • To be able to understand how the basic sequential and combinational logic elements work

  • to be able to simulate in a computer digital circuits 

Lecture based

 

Reading course

 X

(mark with an “X” the appropriate box)

Student evaluation method/ grading4

Lab Exercises (50 %) and Final Exams (50 %)

 

Course Title

INTRODUCTION TO PROBABILITY STATISTICS

ECTS

 6

Typical Semester

 2nd

Hours/ Week

 4

Brief Description (5-6 lines)

 Basic probability concepts and definitions, Combinatorial analysis, Random variables (discrete and continuous), Theoretical Probability distributions, The Binomial, Normal, Poisson, Bernoulli, Gamma, Exponential, etc. Basic concepts of Statistics, Estimation theory, Space of reliance, random variable functions.

Main Learning Goals (list up to 10)

  • Basic concepts of combinations

  • Definition of probability, discrete and continues random variables

  • Conditional probability, Bayes theorem

  • Theoretical probability distributions

  • Basic concepts of Statistics

Lecture based

 

Reading course

 X

(mark with an “X” the appropriate box)

Student evaluation method/ grading

Reading course: Project, Lab Exercises, Final Exam

 

Course Title

 COMMUNICATIONS PRINCIPLES

ECTS

 6

Typical Semester

 2nd

Hours/ Week

 4

Brief Description (5-6 lines)

The concept of Information, Probabilities and Information, Entropy, Information Sources, Information Channels, Channel Capacity, Shannon Theorems. Coding in Error-Free Environment, Shannon-Fano Code, Decoding, Coding in Error-Prone Environment, Error Detection and Correction, Parity Control bit, Linear Codes, Code Minimum Distance, and Hamming Codes

Main Learning Goals (list up to 10)

  • Introduction (Lossless Compression, Channel Coding, Lossy Compression)

  • Entropy, Relative Entropy, and Mutual Information

  • Asymptotic Equipartition Properties

  • Lossless Compression

  • Communication and Channel Capacity

  • Conditional and Joint Typicality

  • Lossy Compression & Rate Distortion Theory

  • Joint Source Channel Coding

Lecture based

 

Reading course

X 

(mark with an “X” the appropriate box)

Student evaluation method/ grading

Reading course: Project, Lab Exercises, Semi and Final Exams

 

Course Title

MATHEMATICS II 

ECTS

 6

Typical Semester

  2nd

Hours/ Week

  5

Brief Description (5-6 lines)

 Elements of Linear Algebra. Introduction to the theory of Graphs. Graph-theoretic Algorithms.

Main Learning Goals (list up to 10)

  • Determinant and Matrix operations

  • Use of determinants in solving linear systems of equations

  • Graph representations using matrices

  • graph morphisms

  • Hamilton paths and Euler circles

  • Different graph types (eg complete, bipartite, planar)

  • Connectedness and connected graph components

  • Equivalent definitions of Trees. K-ary trees

  • Basic graph-theoretic algorithms (search, spanning trees)

Lecture based

 

Reading course

(mark with an “X” the appropriate box)

Student evaluation method/ grading

  • Lecture based (if the number of students is adequate, it can be offered as a lecture based course)

  • Reading course

Bi-weekly student-professor meetings, reading assignments, take-home assignments, mid-term exam and final exam

Bibliography

J. Gross and J. Yellen: "Graph Theory and its Applications", 2nd edition, CRC Press, 2006.

 

3rd SEMESTER

Course Title

DATABASES I 

ECTS

 6

Typical Semester

 3rd

Hours/ Week

 5

Brief Description (5-6 lines)

 Introduction to Databases, Database Management Systems, Database Systems Architecture, Data Modeling, Relational Model, Relational Algebra, Functional Dependencies, Database Normalization, 1NF, 2NF, 3NF, BC-NF, Query Language SQL.

Main Learning Goals (list up to 10)

  • Understanding the main issues concerning databases

  • Understanding the main issues concerning Relational Database Models

  • Ability to correctly design a database

  • Ability to write SQL queries

  • Ability to write queries in relational algebra

Lecture based

 

Reading course

 X

(mark with an “X” the appropriate box)

Student evaluation method/ grading5

Reading course: Project, Lab Exercises, Semi and Final Exams

 

Course Title

BUSINESS ECONOMICS

ECTS

 6

Typical Semester

  3rd

Hours/ Week

 5

Brief Description (5-6 lines)

This course analyzes the basic economic theory that is need for the solution of business economic problems. Specific topics that are studied include: Introduction to the decision making process. Goals and criteria for decision making. Money value over time. Annuities. Evaluation of different investment plans. Sensitivity analysis. Risk analysis. Economic forecasting models. Theory and analysis of supply and demand. Theory and analysis of production. Cost analysis.  Mathematical programming for cost minimization or profit maximization.  

Main Learning Goals (list up to 10)

  • Understanding the main issues of money value over time

  • Understanding the main issues of evaluating alternate investment proposals

  • Theory of supply and demand

  • Profit maximization and cost minimization, etc

Lecture based

 

Reading course

 X

(mark with an “X” the appropriate box)

Student evaluation method/ grading6

Reading course: Project, Lab Exercises, Semi and Final Exams

 

Course Title

COMPUTER NETWORKS I 

ECTS

 5

Typical Semester

 3rd

Hours/ Week

 4

Brief Description (5-6 lines)

This module is introductory in the field of Telecommunications and Computer Networks aiming at the understanding of the fundamental principles of transmission and transmission media of information with emphasis on the telecommunication networks and services.

More specifically, a detailed analysis is carried out about characteristics of interconnections and transmission techniques, parameters of telephone networks and lines as well as approaches to meeting specific communication requirements.

Moreover, the OSI and TCP/IP reference models are presented in order for the students to familiarize and comprehend the multi-layer architecture and the mechanisms that represent each of these layers.

Finally, the module targets on the understanding of concepts and protocols that concern the physical layer and the data-link layer of Computer Networks with emphasis on the architectures of wired and wireless local area networks, access techniques as well as the Ethernet technology.

Main Learning Goals (list up to 10)

  • Introduction: Definition and history of communications, convergence, data communications, communication model.

  • Transmission Issues: Codes, transmission techniques, synchronization, multiplexing, error detection and correction, cyclic codes, ARQ retransmission techniques, compression.

  • Interconnections: Interconnection characteristic and examples (V.24, USB).

  • Transmission media: Twisted pair and coaxial cables, optical fiber. Telephone lines, parameters for telephone lines, dial-up/dedicated telephone lines, voiceband and baseband modems.

  • Transmission techniques: modulation of amplitude, frequency and phase, pulse code modulation (PCM), sampling theorem.

  • Telephony: Telephone network, telephone centers, signaling, voice encoders.

  • Network Architectures: Geographic classification, switching (circuit, message, packet), protocol layering, OSI and TCP/IP

  • reference models.

  • Local Area Networks: Definition, transmission medium, topologies and architectures (bus, star, ring, tree), medium access

  • techniques (CSMA/CD, CSMA/CA, token bus, ALOHA), Ethernet technology, wireless local area networks.

Lecture based

 

Reading course

 X

(mark with an “X” the appropriate box)

Student evaluation method/ grading

Reading course: Project, Lab Exercises, Final Exam

 

Course Title

 DIGITAL SIGNAL PROCESSING

ECTS

 5

Typical Semester

 3rd

Hours/ Week

 3

Brief Description (5-6 lines)

Signals, Parameters, Test Signals, Statistical Analysis of Signals, Sampling Theorem, Fourier Transform, Filters, Cross Correlation, Convolution, Digital Filters, FIR / IIR Filters, Applications in Digital Signal Processing.

Main Learning Goals (list up to 10)

  • Understanding basic and advanced issues related to Signals Parameters and Test Signals

  • Ability to understand problems related to Statistical Analysis of Signals

  • Understand problems related to Signals Sampling

  • Ability to understand problems related to Convolution and Correlation

  • Ability to understand problems related to Filters and Noise

  • Understand problems related to Digital Filters

  • Digital Signal Processing Platforms

  • Applications in Digital Signal Processing

Lecture based

 

Reading course

X 

(mark with an “X” the appropriate box)

Student evaluation method/ grading

Reading course: Project, Lab Exercises, Semi and Final Exams

 

4th SEMESTER

Course Title

COMPUTER NETWORKS II 

ECTS

 6

Typical Semester

 4th

Hours/ Week

 4

Brief Description (5-6 lines)

Study the TCP/IP reference model as well as issues associated with the Internet services specification and supply. More specifically, Internet addressing (subnet and supernet extensions, IPv4, ARP, IPv6 protocols), error reporting and correction (ICMP protocol.) Detail study of Routing and routing protocols (RIP, OSPF and BGP protocols). Furthermore, introduce issues related to delivery service for information packets, transmission, flow and congestion control (UDP and TCP protocols). Presentation of the most important Internet services and applications, such as Electronic mail, file transfer (FTP protocol), World Wide Web (WWW), domain naming (DNS), Internet telephony (VoIP).

Main Learning Goals (list up to 10)

  • Understanding the TCP/IP protocol

  • Understanding the main internetworking issues

  • Understanding the notion of routing and learn major routing algorithms

  • Ability to design and structure LAN και WAN networks utilizing simulation techniques

  • Ability to effectively combine transmission media, network devices and network protocols targeting to solve real problems for small and medium scale networks

Lecture based

 

Reading course

 X

(mark with an “X” the appropriate box)

Student evaluation method/ grading7

Reading course: Project, Lab Exercises, Semi and Final Exams

 

Course Title

COMMUNICATION SYSTEMS I

ECTS

 6

Typical Semester

 4th

Hours/ Week

 5

Brief Description (5-6 lines)

The course presents basic concepts in communication systems engineering, focusing on physical layer, point-to-point communications. Block diagram of a modern communication system. Linear systems, signals, representation in the time domain (input-output relation, impulse response) and frequency domain (Fourier transforms, transfer functions). A/D conversion and Nyquist sampling theorem. Analog amplitude modulations (AM, DSB, SSB, VSB, QAM). Analog angle modulations (phase PM, frequency FM). Design of transmitter/receiver modulator and demodulator structures. Multiplexing. Performance of modulation techniques in the presence of noise. Comparative evaluation of analog modulation and demodulation methods.

Main Learning Goals (list up to 10)

  • Understanding the key ideas underlying modern communication systems

  • Understanding analog-to-digital information conversion and its applications

  • Understanding analog modulation techniques

  • Ability to design and simulate a communication system

  • Ability to evaluate the performance of a communication link

Lecture based

 

Reading course

 X

(mark with an “X” the appropriate box)

Student evaluation method/ grading8

Reading course: Laboratory Assignments, Term Project, Final Exam

 

Course Title

CONTROL SYSTEMS & INDUSTRIAL INFORMATICS 

ECTS

 5

Typical Semester

4th

Hours/ Week

 3

Brief Description (5-6 lines)

Introduction to Control Systems, PID Controllers, Stability Criteria, PLCs, SCADA, DCS Large Scale Control Systems, Industrial Data Bases, Multivariable Control Systems, Linear and Non Linear Control Systems, On-Off Control, Distributed Control, Optimal Control, Control Safety and Alarms Management, Troubleshooting Control Systems

Main Learning Goals (list up to 10)

  • Understanding the main issues concerning Control Systems and Theory

  • Understanding the main issues concerning Industrial Controllers

  • Understanding the main issues concerning Classical Control Systems

  • Understanding Linear and Non Linear Control Systems

  • Understanding Multivariable Control Systems

  • Understanding Optimal Control

  • Applications in Control Systems

Lecture based

 

Reading course

 X

(mark with an “X” the appropriate box)

Student evaluation method/ grading9

Reading course: Project, Lab Exercises, Semi and Final Exams

 

Course Title

THEORY OF ALGORITHMS 

ECTS

  5

Typical Semester

  4th

Hours/ Week

  5

Brief Description (5-6 lines)

 Assymptotic analysis. Divide & Conquer, Dynamic Programming and Greedy algorithms. Complexity classes, reductions and NP-completeness

Main Learning Goals (list up to 10)

  • Computation of the complexity function, asymptotic analysis (Ο,Θ,Ω, ο, ω)

  • Recursive algorithms and complexity computation. Applications of the Master Theorem

  • Devising divide & conquer, dynamic and greedy algorithms to solve specific problems

  • Time complexity and complexity classes. The P vs NP problem

  • Reductions and NP-completeness

Lecture based

 

Reading course

(mark with an “X” the appropriate box)

Student evaluation method/ grading

  • Lecture based (if the number of students is adequate, it can be offered as a lecture based course)

  • Reading course

Bi-weekly student-professor meetings, reading assignments, take-home assignments, mid-term exam and final exam

Bibliography

T.H. Cormen et al, Introduction to Algorithms, Third edition, MIT Press, 2009

 

5th SEMESTER

Course Title

 DATABASES II

ECTS

 5

Typical Semester

 5th

Hours/ Week

 5

Brief Description (5-6 lines)

Multivalued Dependency, Join Dependency, 4NF and 5NF Normal Forms, Relational Calculus, Views, Recovery, Transactions, Concurrency, Security, Integrity-Triggers, Optimizing Database Systems

Main Learning Goals (list up to 10)

  • Understanding advanced issues related to databases

  • Ability to write security and integrity rules

  • Ability to write queries in relational calculus

  • Define views in SQL

  • Ability to understand problems related to transactions and concurrency control

Lecture based

 

Reading course

X 

(mark with an “X” the appropriate box)

Student evaluation method/ grading

Reading course: Project, Lab Exercises, Semi and Final Exams

 

Course Title

 NETWORK OPTIMIZATION

ECTS

 5

Typical Semester

 5th

Hours/ Week

 4

Brief Description (5-6 lines)

 The course studies from an optimization perspective, protocols, algorithms and techniques that aim to provide efficient network operation. Different layers of the protocol stack are examined: Physical layer and power control in CDMA wireless networks. Probabilistic access and protocols in the MAC layer. Spectrum sharing in cognitive radio networks. Optimal routing and shortest paths at the network layer. Flow control and variants of the TCP protocol at the transport layer. Joint cross-layer utility maximization in wireline and wireless networks. The syllabus includes a review of the fundamentals of convex and linear optimization, i.e. primal-dual formulations, Lagrange multipliers, and Kuhn-Tucker necessary conditions.

Main Learning Goals (list up to 10)

  • Understanding concepts related to network performance

  • Review key problems and important algorithms in networking

  • Understanding network protocols/algorithms as performance optimizers

  • Ability to formulate and solve optimization problems

  • Ability to understand complexity and scalability issues arising in large-scale optimization of communication networks

Lecture based

 

Reading course

X 

(mark with an “X” the appropriate box)

Student evaluation method/ grading

Reading course: Laboratory Assignments, Term Project, Final Exam

 

Course Title

ARTIFICIAL INTELLIGENCE

ECTS

 6

Typical Semester

5th

Hours/ Week

 5

Brief Description (5-6 lines)

Introduction to AI, Classical (Symbolic) AI: Problem Description, Search Algorithms (blind search, heuristic search, search in adversary games), Knowledge Representation, Knowledge Based Systems, Reasoning, Computational Intelligence: Genetic Algorithms, Fuzzy Reasoning, Neural Networks

Main Learning Goals (list up to 10)

  • Learn to describe a problem as a state-space search problem.

  • Learn the pros and cons of various blind and heuristic search algorithms as well as to select the proper one based on the given problem.

  • Learn the basic principles of knowledge based systems.

  • Learn to design and apply a genetic algorithm to solve optimization problems.

  • Learn to design a fuzzy, rule-based system.

  • Learn the basic principles of neural networks and multi layered perceptrons.

Lecture based

 

Reading Course

 X

(mark with an “X” the appropriate box)

Student evaluation method/ grading10

Reading course: lab exercises, assignments, on-line tests, final exams

 

Course Title

PATTERN RECOGNITION 

ECTS

 5

Typical Semester

 5th

Hours/ Week

 5

Brief Description (5-6 lines)

 Pattern recognition definition. Review of probability theory basics. Decision theory using Bayes theorem. The use of Naïve Bayes model in pattern recognition. Bayesian networks. Pattern recognition case studies.

Main Learning Goals (list up to 10)

  • Understanding of the meaning of pattern recognition

  • Understanding of the basic mathematical background to be used in pattern recognition

  • Understanding of Decision theory using Bayes theorem

  • Understanding of the use of Naïve Bayes model

  • Understanding of Bayesian networks

  • Understanding of examples of pattern recognition systems

Lecture based

 

Reading course

 X

(mark with an “X” the appropriate box)

Student evaluation method/ grading

Assignment (30 %) and Final Exams (70 %)

 

Course Title

CODING AND INFORMATION THEORY 

ECTS

 5

Typical Semester

 5th

Hours/ Week

 4

Brief Description (5-6 lines)

Main coding techniques in telecommunication systems. Difference between source coding and channel coding. Source coding, data compression, Shannon-Fano and Huffman algorithm. Channel coding, error detection and correction. Error correction using linear block codes, Hamming codes. Error correction using convolutional codes, trellis, state and tree diagram.

Main Learning Goals (list up to 10)

  • Understanding of the main coding techniques used for data compression and for noise reduction

  • Understanding of Shannon-Fano and Huffman algorithms

  • Understanding of error correction coding in telecommunication systems

  • Understanding of parity check matrix and generation matrix in a linear block code

  • Understanding of Hamming linear block code

  • Understanding of convolutional coding and trellis diagrams

Lecture based

 

Reading course

X 

(mark with an “X” the appropriate box)

Student evaluation method/ grading

Assignment (30 %) and Final Exams (70 %)

 

Course Title

 OPERATIONS RESEARCH

ECTS

 5

Typical Semester

 5th

Hours/ Week

 5

Brief Description (5-6 lines)

The course analyzes the use of quantitative methods in decision making problems. In particular focuses in the mathematical models used to describe business problems characterized as linear programming problems. Specific topics of linear programming that are studied include problem formulation, seeking the optimal solution through the graphical and the simplex method, economic interpretation of the final tableau and the duality problem. Other topics covered in the course include, the transportation and the assignment problem, basic networking problems and their algorithms for finding the optimal solution,(i.e. minimum spanning tree, shortest path, maximum capacity, PERT/CPM method) and queuing theory.

Main Learning Goals (list up to 10)

  • The model of linear programming, duality

  • Simplex, economic interpretation of final tableau

  • The transportation problem

  • Networking

  • Introduction to queuing theory

  • Introduction to inventory theory

Lecture based

 

Reading course

X 

(mark with an “X” the appropriate box)

Student evaluation method/ grading

Reading course: Project, Lab Exercises, Semi and Final Exams

 

Course Title

EMBEDDED SYSTEMS 

ECTS

 6

Typical Semester

 5th

Hours/ Week

 4

Brief Description (5-6 lines)

Embedded Systems: Special Features, architecture, specifications. Design Methods for Embedded Systems emphasizing on Hardware / Software Codesign, Partitioning and Co-Simulation. Microcontrollers: architecture, embedded memories(SRAM, Flash, EEPROM), peripheral circuits: GPIO, serial ports like RS232, I2C, SPI, USB, Ethernet, Timer/ Counters (Input Capture/Output Compare), interrupt handling, ADC/DAC, etc. Study of 8-bit AVR microcontrollers and 32-bit ARM. Hardware implementation through ASIC and FPGAs.

 

It is offered as Open Course, videos with English subtitles available at the playlists:

Lectures:

https://www.youtube.com/playlist?list=PLXUuQj2gQ4s_gPIIs96A3bbHOanikIiRF

Lab:

https://www.youtube.com/playlist?list=PLXUuQj2gQ4s9AmkDPE8gnfNALiyw-v6C8

 

Main Learning Goals (list up to 10)

  • Design of efficient embedded systems and special purpose computers

  • Design of microcomputers based on microcontrollers

  • Driver development for GPIOs, Timer/Counters, Interrupt Handling, Analog Comparators

  • Implementation of Flash/EEPROM programmers

  • Development of advanced drivers for Ethernet and USB

  • Development of embedded systems based on reconfigurable hardware

Lecture based

 

Reading course

X 

(mark with an “X” the appropriate box)

Student evaluation method/ grading11

Reading course : the students watch the open course videos that are subtitled in English and are directed to read relevant books, manuals, datasheets, tutorials if they require additional support. Moreover, they can ask questions to the supervisor through email or by visiting his office during the time he is available for students.

The evaluation is performed by written final exams in English (100%). If the student selects to also attend the lab, he/she will also be evaluated by written final exams on the topics taught at the lab (100%).

 

Course Title

 HIGH PERFORMANCE SYSTEMS

ECTS

 5

Typical Semester

 5th

Hours/ Week

 5

Brief Description (5-6 lines)

 Parallel Processing, Concepts and Terminology, von Neumann Architecture, Flynn Classification, Shared Memory, Distributed Memory, Distributed-Shared Memory, Parallel Programming Models, Parallel Programs Design, Communication, Synchronization, Data Dependencies, Load Balancing, Size, Input/Output, Parallel Processing Examples, Middleware, Virtual Machines, High Performance Systems Architectures, Power Consumption, Real Time Systems, General Programming of Graphics Processors Units.

Main Learning Goals (list up to 10)

  • Fundamentals of High Performance Computing

  • Ability to evaluate the performance and power consumption of High Performance Computers

  • Ability to write parallel programs

  • Ability to understand problems related to transactions and concurrency control

Lecture based

 

Reading course

X 

(mark with an “X” the appropriate box)

Student evaluation method/ grading

Reading course: Project, Lab Exercises, Semi and Final Exams

 

Course Title

DIGITAL IMAGE PROCESSING

ECTS

 4

Typical Semester

5th

Hours/ Week

 2

Brief Description (5-6 lines)

Images, Projection, Cameras, Image Acquisition, Linear and Non Linear Algorithms, Photometry, Colour, 2D and 3D Transforms, Fourier Transforms, Gabor Filters και wavelets, Fractals, Segmentation, Optical Flow, Hough Transforms, Radon Transforms, Scenes, Shadows, Image Statistics, 3D presentation, Industrial Vision, Image Processing Applications, Virtual and Augmented Reality Applications.

Main Learning Goals (list up to 10)

  • Basic concepts of Images

  • Ability to understand problems related to Image Processing

  • Understand Image Statistics

  • Ability to distinguish 2D spatial and Frequency Domains

  • 2D Transforms

  • Apply Industrial Vision

  • Solve Virtual and Augmented Reality Applications

  • Solve Image Processing Applications Problems

Lecture based

 

Reading course

 X

(mark with an “X” the appropriate box)

Student evaluation method/ grading

Reading course: Project, Lab Exercises, Final Exam

 

Course Title

LOGIC IN COMPUTER SCIENCE 

ECTS

  5

Typical Semester

  5th

Hours/ Week

  5

Brief Description (5-6 lines)

 Classical Propositional Logic (syntax, semantics, proof system). Elements of Modal Logic and Description Logics. Elements of Propositional Dynamic Logic and program verification. Elements of fixpoint logic (μ-Calculus). Applications of logic in AI.

Main Learning Goals (list up to 10)

  • Truth tables and tautologies

  • Model checking modal sentences

  • Conversion to normal forms

  • Using PDL for program verification

  • SAT algorithms

  • Proof construction using a Gentzen system

  • Tableaux construction

Lecture based

 

Reading course

 X

(mark with an “X” the appropriate box)

Student evaluation method/ grading

  • Lecture based (if the number of students is adequate, it can be offered as a lecture based course)

  • Reading course

Bi-weekly student-professor meetings, reading assignments, take-home assignments, mid-term exam and final exam

Bibliography

M. Huth and M. Ryan, Logic in Computer Science, Cambridge, 2004

 

6th SEMESTER

Course Title

Telecommunication Systems ΙΙ 

ECTS

 5

Typical Semester

 6th

Hours/ Week

 4

Brief Description (5-6 lines)

In this course the principles of digital communication systems are being introduced i.e. 1) information sources and respective coding methods, 2) the concept of entropy and the process of digitizing analog signals, 3) waveform coding mechanisms are presented next and in particular pulse code modulation (PCM), differential pulse code modulation (DPCM) and Delta modulation, 4) noise analysis and the problem of transmission over additive white Gauss noise (AWGN) channel, 5) baseband digital transmission techniques, 6) design of the optimal receiver for digital signals in the presence of Gauss shaped additive noise, 7) passband digital transmission and respective modulations, 8) calculation of error probability, 9) digital transmission over bandwidth limited AWGN channels and 10) AWGN channel capacity.

Main Learning Goals (list up to 10)

  • Analog to digital conversion

  • Additive white Gauss noise (AWGN) channel

  • Baseband digital transmission techniques

  • Optimal receiver

  • Passband digital transmission

  • Intersymbol interference (ISI)

  • Channel capacity

Lecture based

 

Reading course

 X

(mark with an “X” the appropriate box)

Student evaluation method/ grading12

Reading course: Project, Lab Exercises, Semi and Final Exams

 

Course Title

DISTRIBUTED AND PARALLEL PROGRAMMING 

ECTS

 6

Typical Semester

 6th

Hours/ Week

 5

Brief Description (5-6 lines)

 Introduction to distributed and parallel programming, Amdahl’s and Moore’s low, Flynn taxonomy of parallel systems, DAG and Gantt charts, speed up of parallel programs, granularity of programs

Distributed programming using Message Passing Interface (MPI), Peer to peer and broadcast and collective communications.

Parallel programming using OpenMP, for loops, directives, balancing the load of programs

Main Learning Goals (list up to 10)

  • Ability to design distributed / parallel programs using MP, OpenMP

  • Ability to understand parallel tasks and dependencies between them

  • Ability to design and implement programs combining distributed and parallel / multi-core techniques

Lecture based

 

Reading course

 X

(mark with an “X” the appropriate box)

Student evaluation method/ grading

Reading course: Project, Lab Exercises, Final Exam

 

Course Title

INTERNET APPLICATION PROGRAMMING

ECTS

 6

Typical Semester

 6th

Hours/ Week

 5

Brief Description (5-6 lines)

Introduction to the WWW, HTML for web content description, CSS for content formatting and positioning , JavaScript for RIAs (Rich Internet Applications), DOM (Document Object Model), PHP for server side scripting, PHP and MySQL, AJAX calls, basic SEO (Search Engine Optimization), Web CMS (WordPress)

Main Learning Goals (list up to 10)

  • Learn to use the HTML properly (tag semantics) for describing a web page's content.

  • Understand what HTML elements a CSS rule affects and learn to define focused CSS selectors according to the needs.

  • Understand the DOM and learn to build JavaScript form validators.

  • Learn to use PHP for programming secure CRUD operations on MySQL, login and user tracking, search forms and search results pagination, encryption, file upload and email sending.

  • Learn to make AJAX calls and handling the results with JavaScript.

  • Learn the basic SEO features and how to use them for building search engine friendly web pages.

  • Integrate all the above in a realistic site scenario.

Lecture based

 

Reading Course

 X

(mark with an “X” the appropriate box)

Student evaluation method/ grading13

Reading course: lab exercises, project, on-line tests, final exams

 

Course Title

MACHINE LEARNING

ECTS

 6

Typical Semester

6th

Hours/ Week

 5

Brief Description (5-6 lines)

Introduction, Types of Learning, Function Learning, Concept Learning, Case-Based Learning, Classification (Trees, k-NN, Naive Bayes), SVM, Clustering (k-Means), Association Rules, Regression, Reinforcement Learning, Deep Learning, Data Mining

Main Learning Goals (list up to 10)

  • Learn to define the parameters of a Machine Learning problem.

  • Learn the pros and cons of various Machine Learning Algorithms and how to apply them for problem solving.

  • Understand the role of Machine Learning in Knowledge Discovery/Data Mining

  • Get hands-on experience in knowledge discovery tasks.

  • Learn to evaluate the performance of trained models.

Lecture based

 

Reading Course

 X

(mark with an “X” the appropriate box)

Student evaluation method/ grading14

Reading course: lab exercises, assignments, final exams

 

Course Title

 WIRELESS COMMUNICATIONS

ECTS

 5

Typical Semester

 6th

Hours/ Week

 4

Brief Description (5-6 lines)

Earth wireless links. Basic elements of a wireless link, electromagnetic waves propagation. Fresnel zones. Transmitters and receivers, antennas. Design of microwave links, free space path lose calculation. Satellite wireless links, main elements, link budget calculation. Analysis of basic enabling technologies for 5G.

Main Learning Goals (list up to 10)

  • Understanding of the main concepts of earth wireless links

  • Understanding of the main concepts of satellite links

  • Understanding of antenna technology

  • Understanding of how electromagnetic waves propagate

  • Calculation of free space path losses and analysis of link budget of a wireless link

  • Understanding of the basic concepts of the forthcoming 5G technology

Lecture based

 

Reading course

X

(mark with an “X” the appropriate box)

Student evaluation method/grading

Assignment (30 %) and Final Exams (70 %)

 

Course Title

COMPUTER ARCHITECTURE II 

ECTS

 5

Typical Semester

 6th

Hours/ Week

 4

Brief Description (5-6 lines)

Review of the Computer Structure (CPU, main memory, RAM/ROM, SRAM, DRAM, SDRAM, I/O). Interconnection of the memory to the CPU through Address/Data Bus. Instruction/Machine/ Clock Cycles. Introduction to computer peripherals: parallel/serial ports, timer/counters, DMA. Cache memory, architecture, frame substitution policy, performance. Main memory: paging, segmentation, virtual memory. Pipeline, architecture, performance. Study of the Intel Pentium architecture (instruction pool, microoperations, retire unit, branch prediction, alias register table, priviledge levels, modes of operation, use of the stack during near/far calls and ISR, I/O access, FPU, etc). Introduction to multi-thread, multi-core or multi-processor systems

It is offered as Open Course, videos with English subtitles available at the playlists:

Lectures:

https://www.youtube.com/playlist?list=PLXUuQj2gQ4s8MExhzQrVw7eZHLm4jo7X5&spfreload=10

Main Learning Goals (list up to 10)

The students will be able to

  • Comprehend the architecture of simple and advanced general purpose computer systems

  • Design the interconnection between processors and any type of memory

  • Evaluate the efficiency of the Cache memory offered by a system

  • Evaluate the efficiency of paging and segmentation schemes offered by a computer system

  • Design or evaluate modern computer systems with advanced performance owed to features like pipeline, branch prediction, speculative execution, etc

Lecture based

 

Reading course

X 

(mark with an “X” the appropriate box)

Student evaluation method/ grading

Reading course: the students watch the open course videos that are subtitled in English and are directed to read relevant books, manuals, datasheets, tutorials if they require additional support. Moreover, they can ask questions to the supervisor through email or by visiting his office during the time he is available for students.

The evaluation is performed by written final exams in English (100%)

 

Course Title

DESIGN OF HARDWARE SYSTEMS

ECTS

 6

Typical Semester

 6th

Hours/ Week

 4

Brief Description (5-6 lines)

Methods for the design of hardware systems: ASICs and Reconfigurable hardware.

ASIC design: top level description using schematics, netlists and HDL. Top level simulation (transient, DC, Monte Carlo etc). Layout design. DRC and LVS validation methods. Post layout simulation. RCL extraction. Corner validation. IC fabrication. Packaging issues

Reconfigurable hardware: PLA/PAL, SPLD/CPLD, FPGAs. Architecture. Design methods

In the Lab, VHDL is used with CPLD development boards

Part of this lecture is covered by videolectures with English subtitles available at the playlists:

https://www.youtube.com/playlist?list=PLXUuQj2gQ4s_gPIIs96A3bbHOanikIiRF

Lab:

https://www.youtube.com/playlist?list=PLXUuQj2gQ4s9AmkDPE8gnfNALiyw-v6C8

Main Learning Goals (list up to 10)

The students will be able to

  • Comprehend the design and fabrication of integrated circuits in the form of ASICs

  • Comprehend the design with reconfigurable hardware and the trade offs between ASICs and FPGAs

  • Top level design appropriate for implementation with ASICs or FPGAs

  • Performance and cost issues associated with the design with ASICs and FPGAs

  • Familiarize with the design of digital systems using Hardware Description languages like VHDL

Lecture based

 

Reading course

X 

(mark with an “X” the appropriate box)

Student evaluation method/ grading

Reading course: the students can watch the open course videos that are subtitled in English and are directed to read relevant books, manuals, datasheets, tutorials if they require additional support. Moreover, they can ask questions to the supervisor through email or by visiting his office during the time he is available for students.

The evaluation is performed by written final exams in English (100%). If the student selects to also attend the lab, he will also be evaluated by written final exams on the topics studied at the lab (100%).

 

Course Title

ADVANCED TOPICS IN THE DESIGN OF DIGITAL SYSTEMS

ECTS

 5

Typical Semester

 6th

Hours/ Week

 4

Brief Description (5-6 lines)

Low power design issues in system level (eg, various types of sleep modes), transistor level (power consumed by BJT or MOSFET transistors connected in CMOS) and intermediate level like for example by memory decoders. Static and Dynamic power consumption. Capacitance charge and discharge. Connectivity between different types of gates. Linearity and power consumption by amplifiers of class A, B, AB and C

Testability issues including test and observation point selection, reasoning for testability (yield, fault coverage) BIST and boundary scan methods like JTAG

Main Learning Goals (list up to 10)

The students will be able to

  • Design efficient electronic systems in terms of performance and consumption

  • Comprehend sources of current leakage and increased power consumption

  • Select efficient gate families and reassure their connectivity

  • Comprehend the methods that allow good verification of the systems they define

Lecture based

 

Reading course

X 

(mark with an “X” the appropriate box)

Student evaluation method/ grading

Reading course: the students are directed to read relevant books, manuals, datasheets, tutorials if they require additional support. Moreover, they can ask questions to the supervisor through email or by visiting his office during the time he is available for students.

The evaluation is performed by written final exams in English (100%).

 

Course Title

Telecommunication Systems ΙΙ 

ECTS

 5

Typical Semester

 6th

Hours/ Week

 4

Brief Description (5-6 lines)

In this course the principles of digital communication systems are being introduced i.e. 1) information sources and respective coding methods, 2) the concept of entropy and the process of digitizing analog signals, 3) waveform coding mechanisms are presented next and in particular pulse code modulation (PCM), differential pulse code modulation (DPCM) and Delta modulation, 4) noise analysis and the problem of transmission over additive white Gauss noise (AWGN) channel, 5) baseband digital transmission techniques, 6) design of the optimal receiver for digital signals in the presence of Gauss shaped additive noise, 7) passband digital transmission and respective modulations, 8) calculation of error probability, 9) digital transmission over bandwidth limited AWGN channels and 10) AWGN channel capacity.

Main Learning Goals (list up to 10)

  • Analog to digital conversion

  • Additive white Gauss noise (AWGN) channel

  • Baseband digital transmission techniques

  • Optimal receiver

  • Passband digital transmission

  • Intersymbol interference (ISI)

  • Channel capacity

Lecture based

 

Reading course

 X

(mark with an “X” the appropriate box)

Student evaluation method/ grading15

Reading course: Project, Lab Exercises, Semi and Final Exams

 

Course Title

SENSORS  and ACTUATORS

ECTS

 4

Typical Semester

6th

Hours/ Week

 2

Brief Description (5-6 lines)

Sensors and Actuators, Technologies, Digital Interfaces, Applications, Sensors Classification, Mechanical, Electrical Sensors, Radiation Sensors, Biosensors, Analytical Sensors, Sound, Ultrasound, Relays, opto-couplers, Power Electronics, Displays and Recorders, Calibration, ADCs/DACs, Sensors Networks, Error Analysis.

Main Learning Goals (list up to 10)

  • Sensors and Actuators basic concepts

  • Install properly and overcome Sensors and Actuators problems

  • Select, Calibrate and Troubleshoot Sensors and Actuators

  • Connect Sensors and Actuators to the Computer and the Internet

  • Analyse Sensors and Actuators Errors in Systems

  • Ability to design Sensors and Actuators Applications

Lecture based

 

Reading course

 X

(mark with an “X” the appropriate box)

Student evaluation method/ grading

Reading course: Project, Lab Exercises, Final Exam

 

Course Title

NETWORK SECURITY AND ADMINISTRATION

ECTS

 5

Typical Semester

 6th

Hours/ Week

 5

Brief Description (5-6 lines)

 Basic Security Principles of Information Systems, Cryptography, History of Cryptography, Cryptography Basic Principles, Modern Cryptographic Algorithms, Cryptanalysis, Side Channel Attacks, Symmetric Key Cryptographic Algorithms, Public Key Cryptography, Digital Signatures, Message Authentication Codes, Hash Functions, Wired Network Security, Network Layer Security Protocols, Transport Layer Security Protocols, Application Layer Security Protocols, Attacks, Firewalls. Intrusion Detection Systems (IDS), Wireless Network Security, Security Protocols for WLAN, Mobile Telephony Network Security, Malware, Cybercrime, Financial Security, Secure Software Development, Secure Methodologies for Software Development, Operating Systems Security, Hardware Security, Information Security, Security Policies, Risk Management.

Main Learning Goals (list up to 10)

  • Understanding the main issues concerning cryptography

  • Understanding the main issues concerning network security and protocols

  • Ability to apply basic defensive measures against cyberattacks

Lecture based

 

Reading course

 X

(mark with an “X” the appropriate box)

Student evaluation method/ grading16

Reading course: Project, Lab Exercises, Semi and Final Exams

 

7th SEMESTER

Course Title

 WIRELESS SENSOR NETWORKS

ECTS

 5

Typical Semester

 7th

Hours/ Week

 5

Brief Description (5-6 lines)

Introduction to Wireless Sensor Networks (WSN), fundamental concepts and theoretical background.  Analysis of Wireless Sensors Networks in terms of structure, organization, functionality and development methodologies. Study the Idiosyncrasies of such networks and their differences with the Ad Hoc mobile networks. Investigate issues in relation to minimization of energy consumption, routing, secure connectivity and avoidance and congestion control. Examine security issues, simulation and application development environments.

Main Learning Goals (list up to 10)

  • Understanding basic concepts related to WSN

  • Understanding the differences between WSN and Ad hoc networks

  • Learn and apply the WSN protocol standards

  • Ability to design and realize WSN in simulation environments such as NS-2 and OMNET ++

  • Ability to employ WSN in real world applications

Lecture based

 

Reading course

X 

(mark with an “X” the appropriate box)

Student evaluation method/ grading

Reading course: Project, Lab Exercises, Semi and Final Exams

 

Course Title

 MOBILE COMMUNICATIONS

ECTS

 5

Typical Semester

 7th

Hours/ Week

 5

Brief Description (5-6 lines)

The aim of this course is to learn the fundamental principles governing wireless mobile communications. Initially we consider the issues of electromagnetic wave propagation and wireless channel modeling for the environment of mobile communications. We refer to both analytical and empirical models. The phenomena of small and large-scale fading in mobile networks and their modeling are studied next. Then we present the fundamentals of cellular communication systems design and we continue with dimensioning issues based on the volume of traffic and the degree of service. Then the lesson focuses on addressing the issues of noise and interference. Multiple access mechanisms and management of wireless resources are discussed in the next section. Finally we present the main components and features of mobile networks of the 2nd, 3rd and 4th generation and we study thoroughly the procedure of handover.

Main Learning Goals (list up to 10)

  • Electromagnetic wave propagation

  • Wireless channel modelling

  • fundamentals of cellular communication systems

  • Traffic engineering

  • noise and interference

  • Multiple access mechanisms

  • Architecture of mobile communication systems

Lecture based

 

Reading course

X 

(mark with an “X” the appropriate box)

Student evaluation method/ grading

Reading course: Project, Theoretical Exercises, Semi and Final Exams

 

Course Title

BROADBAND NETWORKS 

ECTS

 6

Typical Semester

 7th

Hours/ Week

 5

Brief Description (5-6 lines)

The course presents design principles, technologies, and industry standards that support high-rate (Mbps and Gbps) information delivery in broadband networks (wireline, wireless and optical). Digital Subscriber Line (DSL). CDMA wireless access. Rake receiver, cdma2000 and WCDMA cellular 3G standards. Orthogonal frequency division multiple access (OFDMA), 802.11a/b/g/n/ac wireless LAN standards. LTE 4G standards. Antennas and propagation in the wireless channel, multiple antennas (MIMO) transmit and receive diversity techniques. Selection combining, maximal ratio combining (MRC), Alamouti space-time codes.

Main Learning Goals (list up to 10)

  • Understanding fundamental principles of modern broadband networks

  • Understanding a wide range of industry standards, current technologies and future trends in high-speed communications

  • Ability to design and evaluate a broadband communication link

  • Ability to select market products for broadband connectivity

Lecture based

 

Reading course

 X

(mark with an “X” the appropriate box)

Student evaluation method/ grading17

Reading course: Laboratory Assignments, Term Project, Final Exam

 

Course Title

SPECIAL ISSUES IN WWW

ECTS

 6

Typical Semester

 7th

Hours/ Week

 5

Brief Description (5-6 lines)

Information Search and Retrieval in WWW, Crawlers, PageRank and HITS, Site Optimization, XML/DTD, JSON, RESTFull API design, Web APIs (Google Maps API), Web Content Extraction, Web Mining, Recommender Systems in e-Commerce (personalised and non-personalized recommendations), Open Data, Semantic Web

Main Learning Goals (list up to 10)

  • Learn the basic principles of a Search Engine and use this understanding in building SE-Optimized sites.

  • Learn to turn unstructured and semi-structured web data into structured content by means of web content extraction tools.

  • Learn to describe data in XML and JSON format.

  • Learn to design a RESTFull API.

  • Learn to use the Google Maps API for building map-based RIAs.

  • Learn to apply machine learning for building advanced web apps.

  • Understand the Open Linked Data movement and the Semantic Web

Lecture based

 

Reading Course

 X

(mark with an “X” the appropriate box)

Student evaluation method/ grading18

Reading course: lab exercises, assignments, project, final exams

 

Course Title

THEORY OF COMPUTING 

ECTS

  5

Typical Semester

  7th

Hours/ Week

  5

Brief Description (5-6 lines)

Regular languages and Finite automata. Pumping Lemma for regular languages. Pushdown automata and CFGs. Pumping Lemma for CFGs.

Turing Machines. Elements of Recursive Function Theory. Unsolvable problems. Reductions. Rice’s Theorem.

Main Learning Goals (list up to 10)

  • Designing finite autonata. Word and language recognition

  • Conversion of non-deterministic to deterministic automata

  • Use of the Pumping lemmas

  • Designing Turing machines for specific problems

  • Non-computability proofs via reductions

  • Non-computability proofs using Rice’s theorem

Lecture based

 

Reading course

(mark with an “X” the appropriate box)

Student evaluation method/ grading19

  • Lecture based (if the number of students is adequate, it can be offered as a lecture based course)

  • Reading course

Bi-weekly student-professor meetings, reading assignments, take-home assignments, mid-term exam and final exam

Bibliography

M. Sipser, Introduction to the Theory of Computation, 3rd Edition, Cengage Learning, 2013

 

Course Title

 MOBILE COMMUNICATIONS

ECTS

 5

Typical Semester

 7th

Hours/ Week

 5

Brief Description (5-6 lines)

The aim of this course is to learn the fundamental principles governing wireless mobile communications. Initially we consider the issues of electromagnetic wave propagation and wireless channel modeling for the environment of mobile communications. We refer to both analytical and empirical models. The phenomena of small and large-scale fading in mobile networks and their modeling are studied next. Then we present the fundamentals of cellular communication systems design and we continue with dimensioning issues based on the volume of traffic and the degree of service. Then the lesson focuses on addressing the issues of noise and interference. Multiple access mechanisms and management of wireless resources are discussed in the next section. Finally we present the main components and features of mobile networks of the 2nd, 3rd and 4th generation and we study thoroughly the procedure of handover.

Main Learning Goals (list up to 10)

  • Electromagnetic wave propagation

  • Wireless channel modelling

  • fundamentals of cellular communication systems

  • Traffic engineering

  • noise and interference

  • Multiple access mechanisms

  • Architecture of mobile communication systems

Lecture based

 

Reading course

X 

(mark with an “X” the appropriate box)

Student evaluation method/ grading

Reading course: Project, Theoretical Exercises, Semi and Final Exams

 

1 For all courses, grading scale: 0 -10. Passing grade: 5.00. Analytically: Grade: <5.00: Fail, 5.00 – 6.49: Good, 6.50 – 8.49: Very Good, 8.50 – 10.00: Excellent

2 For all courses, grading scale: 0 -10. Passing grade: 5.00. Analytically: Grade: <5.00: Fail, 5.00 – 6.49: Good, 6.50 – 8.49: Very Good, 8.50 – 10.00: Excellent

3 For all courses, grading scale: 0 -10. Passing grade: 5.00. Analytically: Grade: <5.00: Fail, 5.00 – 6.49: Good, 6.50 – 8.49: Very Good, 8.50 – 10.00: Excellent

4 For all courses, grading scale: 0 -10. Passing grade: 5.00. Analytically: Grade: <5.00: Fail, 5.00 – 6.49: Good, 6.50 – 8.49: Very Good, 8.50 – 10.00: Excellent

5 For all courses, grading scale: 0 -10. Passing grade: 5.00. Analytically: Grade: <5.00: Fail, 5.00 – 6.49: Good, 6.50 – 8.49: Very Good, 8.50 – 10.00: Excellent

6 For all courses, grading scale: 0 -10. Passing grade: 5.00. Analytically: Grade: <5.00: Fail, 5.00 – 6.49: Good, 6.50 – 8.49: Very Good, 8.50 – 10.00: Excellent

7 For all courses, grading scale: 0 -10. Passing grade: 5.00. Analytically: Grade: <5.00: Fail, 5.00 – 6.49: Good, 6.50 – 8.49: Very Good, 8.50 – 10.00: Excellent

8 For all courses, grading scale: 0 -10. Passing grade: 5.00. Analytically: Grade: <5.00: Fail, 5.00 – 6.49: Good, 6.50 – 8.49: Very Good, 8.50 – 10.00: Excellent

9 For all courses, grading scale: 0 -10. Passing grade: 5.00. Analytically: Grade: <5.00: Fail, 5.00 – 6.49: Good, 6.50 – 8.49: Very Good, 8.50 – 10.00: Excellent

10 For all courses, grading scale: 0 -10. Passing grade: 5.00. Analytically: Grade: <5.00: Fail, 5.00 – 6.49: Good, 6.50 – 8.49: Very Good, 8.50 – 10.00: Excellent

11 For all courses, grading scale: 0 -10. Passing grade: 5.00. Analytically: Grade: <5.00: Fail, 5.00 – 6.49: Good, 6.50 – 8.49: Very Good, 8.50 – 10.00: Excellent

12 For all courses, grading scale: 0 -10. Passing grade: 5.00. Analytically: Grade: <5.00: Fail, 5.00 – 6.49: Good, 6.50 – 8.49: Very Good, 8.50 – 10.00: Excellent

13 For all courses, grading scale: 0 -10. Passing grade: 5.00. Analytically: Grade: <5.00: Fail, 5.00 – 6.49: Good, 6.50 – 8.49: Very Good, 8.50 – 10.00: Excellent

14 For all courses, grading scale: 0 -10. Passing grade: 5.00. Analytically: Grade: <5.00: Fail, 5.00 – 6.49: Good, 6.50 – 8.49: Very Good, 8.50 – 10.00: Excellent

15 For all courses, grading scale: 0 -10. Passing grade: 5.00. Analytically: Grade: <5.00: Fail, 5.00 – 6.49: Good, 6.50 – 8.49: Very Good, 8.50 – 10.00: Excellent

16 For all courses, grading scale: 0 -10. Passing grade: 5.00. Analytically: Grade: <5.00: Fail, 5.00 – 6.49: Good, 6.50 – 8.49: Very Good, 8.50 – 10.00: Excellent

17 For all courses, grading scale: 0 -10. Passing grade: 5.00. Analytically: Grade: <5.00: Fail, 5.00 – 6.49: Good, 6.50 – 8.49: Very Good, 8.50 – 10.00: Excellent

18 For all courses, grading scale: 0 -10. Passing grade: 5.00. Analytically: Grade: <5.00: Fail, 5.00 – 6.49: Good, 6.50 – 8.49: Very Good, 8.50 – 10.00: Excellent

19 For all courses, grading scale: 0 -10. Passing grade: 5.00. Analytically: Grade: <5.00: Fail, 5.00 – 6.49: Good, 6.50 – 8.49: Very Good, 8.50 – 10.00: Excellent

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