Introduction to the Unified Modeling Language (UML): Class and object modeling, class diagrams, interactions diagrams (sequence, collaboration), use cases, activity diagrams, state modeling. Advanced object-oriented programming principles covering object-oriented data structures and their associated algorithms, such as lazy evaluation. Implementation of heaps, self-balancing trees, graphs, sorting, and generative recursion via objects. Applications of software engineering principles such as abstract decomposition, decoupling, and command passing to large- and small- scale component-framework systems. Multi-threaded event-driven applications. Prerequisite: CEI 123 - Object Oriented Methodology and Programming (C++).

Prerequisites

EEI 133 Object-oriented Methodology and Programming with C++

Presentation of advanced uni-processor architectures and parallel architectures such as multi-processors and multi-cores. Advanced pipelining; dynamic scheduling, Scoreboarding and Tomasulo’s algorithms, out-of-order execution, precise interrupt handling. Multiple instruction issue in superscalar processors. Data, control and structural hazards minimization. Branch predictors and branch history tables. Techniques for exploiting sub-word parallelism, instruction-level parallelism and thread-level parallelism. Static parallel instruction scheduling in VLIW architectures, loop unrolling and software pipelining. Advanced memory system organization, interleaved memory, multiple cache architectures, virtual memory, TLBs. Storage systems, and reliability with RAID storage systems. Cache coherence protocols in multi-processors and multi-core architectures. Basic networks and interconnection networks, on- and off-chip. The course may include a hands-on project using academic or industrial architecture simulators.

Prerequisites: 

EEI 233 Computer Organization

Students are divided up into small groups to develop (analyze, specify, design, program, and document) a real-world software application with a client organization coming from the local market. The aim of the course is to gain experience in the various phases of software development and in different aspects of group working. Special attention is given to Project Management activities, such as scheduling, time and resource management, production of reports and deliverables, etc. The group develops abilities to "pick up" and use new development tools and environments without formal training. The final product is a fully operational software system which is installed at the client site with execution of professional user acceptance testing and appropriate training.

Prerequisite:

CEI 324 - Software Engineering

This course is an introduction to Cryptography and Computer Security. Emphasis will be given on understanding the basic principles of computer security and cryptography, specifically aiming to teach students on how to design and implement secure systems. This course covers the following topics: Fundamentals of computer security and networks security, objectives and basic principles of cryptography. Vulnerabilities, threats and attacks. Principles of designing secure computing systems. Privacy and Anonymity. In particular, the course provides an introduction to Cryptography, Pseudo Random Functions, Hash functions, Message Authentication Codes (ΜΑCs) and Digital signatures. Digital certificates and Public Key Infrastructures (PKI), certificate transparency and certificate revocation. Symmetric-key cryptography and cryptographic algorithms (Block Ciphers, Stream Ciphers). Asymmetric-key cryptography, Elliptic curves cryptography. Zero-Knowledge Proofs. Key generation and key exchange techniques and cryptographic protocols. Furthermore, this course will introduce the basic categories of malware, such as Viruses, Worms, Trojan horses, Backdoors, Rootkits as well as a view into botnet architectures. Methods of infection and replication, polymorphism and stealth techniques. Antiviruses and detection techniques. The course also introduces the most common types of attacks, such as Buffer Overflows, SQL Injection, Cross-site scripting, Denial of Service attacks, Social engineering and Phishing attacks, ClickJacking etc. Finally, we will explore detection and prevention techniques, as well as protection mechanisms.

The course aims to provide an introduction to the basic principles of Graphics and provide all the knowledge needed to create and visualize 2D and 3D virtual worlds, starting with simple basic principles of Geometry.

Students shall be able to integrate the following knowledge:

Basic concepts of 2D and 3D space and geometrical elements (points, lines, curves, triangles and polygon triangulation, planets - including complex polygons, freeform surfaces), Neighborhood of points, polygons: Voronoi diagram and basics. Delaunay triangulation and basic properties, incremental algorithm. Complex point clouds (from object digitization) and modeling. Geometric shapes and object modeling structures. Platonic solid bodies and 3D object reconstruction and reproduction, Computer Aided Design / Computer Aided Manufacturing - CAD / CAM. Collapse data and archive it. Simple examples in various areas and applications with programming.

Graphic and geometrical problems in different areas of life give us a good example of the variety of applications: Architecture, Archeology, Medicine, Engineering, Robotics, Simulations, Geographic Information Systems (GIS), Cinema, Video Production, etc.

Course Content

1. Basic and introductory concepts of graphics

2. Geometric elements of 2D and 3D space (points, lines, curves, triangles and polygon triangulation, planes)

3. Transformations and 2D viewing (PC screens)

4. Basic forms of object modeling structures

5. Simulation

6. Analysis and design of various applications and specialized examples

7. Planning and quality control

8. Graphics and application standards in industry

9. Computer Aided Design / Computer Aided Manufacturing - CAD / CAM.

The need to store and process massive amounts of data has led to the evolution of existing database systems while a new breed of data processing systems has emerged. This course covers a spectrum of topics from core techniques in relational data management to highly-scalable data processing using parallel database systems and MapReduce. First, the course covers the basic principles in database query processing and optimization, including index structures, sort and join processing, query rewrites, and physical plan selection. Next, the course covers topics from parallel and distributed databases, including data partitioning and distributed join algorithms. Finally, the course covers scalable data processing systems such as MapReduce and NoSQL databases (column, document, and key-value stores). The course material will be drawn from textbooks as well as recent research literature. Prerequisite background: Basic database knowledge.

Prerequisites

CEI 325 Databases

The aim of the course is to introduce the basic principles of Computer Interaction Science (HSC) and its application in the design of computer systems interfaces. In particular, the importance of properly implementing HSC principles and how they affect the efficiency and effectiveness of computer systems interfaces is presented. Design methodologies and evaluation methods are explained to understand their role in design usability.

Upon successful completion of the course students shall be able to:

• Recognize capabilities and limitations in the design of computer interfaces for humans
• Understand the tools and techniques available to design interfaces for web and mobile platforms
• Apply Principles of Human Computer Interaction through design of computer systems interfaces.
• Evaluate existing interfaces against recognized principles of human computer design and interaction

Course Content

A Historical Review of the Science of Human Computer Interaction

Importance of proper computer system design

The human factor - memory, attention, communication models - capabilities and limitations

Input and output devices for human-computer interaction

Gestalt rules and their application to web and mobile interface design - use MockFlow to design low-fidelity prototypes

Usability components and its importance in evaluating interfaces

Low, intermediate and high-fidelity prototypes

LUCID design methodology

Evaluating interface design using Nielsen's heuristic rules

Evaluation methods: controlled experiments against field evaluation

Introduction to user personalization and modeling

Course Purpose and Objectives

The aim of this course is to study and understand basic introductory but also some more advanced topics in the field of Computer Security and Cryptography. It analyzes all the basic introductory concepts of computer and network security in general and maps the current state in the field. In addition, emphasis is given on the basic principles of design and implementation of cryptographic systems, and all basic cryptographic algorithms and protocols and their main representatives are analyzed in conjunction with the recent developments in the field concerning introduction of new cryptographic algorithms and successful attacks on older ones. It also analyzes Internet security and the World Wide Web security, incorporating all the latest developments in Internet threats and attacks such as social engineering, clickjacking, tabnapping, and ransomware.  At the same time, the basic types of threats and malware such as viruses, worms, Trojan horses, backdoors, botnets etc. are analyzed thoroughly and in all respects, focusing especially on related vulnerabilities and attacks as well as methods of defense and protection.

Learning Outcomes

At the end of the course the student will have:  

1. Understood all the basic and some advanced concepts and their importance in computer and network security in their full dimension, beyond their IT aspect. 
2. Understood the modern range of threats to computer and network security and the current status quo in the field
3. Understood all basic types of cryptographic algorithms and their characteristics as well as the basic cryptographic protocols
4. Become able to analyze and evaluate computer and network security systems
5. Become able to design and implement secure systems and applications by adopting defense and protection measures against modern threats to computer and network security
6. Become able to evaluate the advantages and disadvantages of alternative cryptographic algorithms, protocols, architectures of security systems etc., making appropriate choices depending on the complexity, cost, value of the protected goods, etc.
7. Acquired all basic and some advanced knowledge of all basic types of malware in terms of vulnerabilities to be exploited, infection/replication, defense methods, and resulting attack effects.
8. Understood basic concepts of malware such as polymorphism and stealth techniques, while at the same time understanding basic malware protection practices.
9. Acquired all basic knowledge about the main types of vulnerabilities that enable initial infection and subsequent spread and replication of malicious software.
10. Understood the basic modern internet threats in the context of social media such as Clickjacking, Tabnapping, Ransomware, etc. and countermeasures against them
11. Acquire advanced knowledge for more specialized topics of the computer security area due to their projects.

Course Content

The course contains introductory but also advanced topics in the area of ​​ Computer Security and Cryptography. Emphasis is given on basic principles of designing and implementing cryptographic systems and on the security of the Internet and the World Wide Web.

This course covers the following topics: Objectives and basic principles of cryptography, computers security and networks security. Vulnerabilities, Threats, Attacks and Controls, Cybercrime and cybercriminals  Principles of designing secure computing systems. Privacy and Anonymity. Introduction to Cryptography. Hash functions, Message Authentication Codes (ΜΑCs) and Digital signatures. Digital certificates and Public Key Infrastructures (PKI). Symmetric-key cryptography and cryptographic algorithms  (Block Ciphers, Stream Ciphers). Asymmetric-key cryptography, Elliptic curves cryptography. Key generation and exchange. Cryptographic protocols.  Strategies for designing and implementing cryptogrpahic security systems (Hw/Sw), Implementation of security cryptographic systems in harware. Analytical study of all basic kind of malware and their subcategories: Virus, Worms, Trojans, Backdoors, Wrappers, Rootkits, Botnets architectures and detection methods etc. Methods of Replication, replication/ infection, countermeasures and damages from malware. Denial of Service attacks. Malware Polymorphism and stealth techniques.  Cross-site scripting, Buffer Overflow and other vulnerabilities. Internet and World Wide Web security, Social engineering and Phishing attacks, Spoofing, Spam, Spyware, Adware, Keyloggers, Packet sniffing etc..  ClickJacking. Tabnapping. Ransomware. Anti-virus and Firewalls. Trusted Computing. SQL injection. Smart cards. Physical Unclonable Functions (PUFs) and their applications in computer security. Commercial cryptographic security systems and protocols  SSL/TLS etc..

Course Purpose and Objectives

The main objectives of this course are:

• The study and in-depth understanding of the design goals of digital circuits and systems hardware implementations  (FPGAs, ASICs, ASIPs) in terms of speed, power consumption and implementation area etc.

• The study, in-depth understanding and subsequent practical application of the design flow and implementation flow of hardware circuits and systems as well as the analysis and comparative evaluation of the different alternative circuit design architectures.

• The in-depth understanding of the different strategies / methodologies for designing hardware designs.

• The study and application of optimization techniques for digital circuits and systems hardware design such as parallelism, pipelining and algorithmic loop unfolding,at system, algorithmic, register, circuit levels of the design flow for optimal digital designs implementation regarding the selected optimization factor (speed, power, area).

• The definition of functional specifications and the verification of the circuits' or systems' correct functionality.

• The description of digital circuits and systems using the VHDL hardware description language. 

• Acquiring hardware design experience through "lab training" homeworks ( with provided hardware synthesis and simulation tools) through weekly mini-tasks on the above topics.

• Introduction to the basic concepts of testing and testability of ICs, the valuation of ICs production lines (yield), the economics of ICs testing and so on.

•  Study and analysis of fault Models and faults detection as well as introduction to design for  testability(DFT) ICs.

• Introduction to logic fault simulators, test patterns generation and application as well as in techniques for circuit testing.

Learning Outcomes

Upon completion of the course the student will:

·       Understood in-depth the alternatives of digital systems hardware designs architectures and implementations and the corresponding required theory for designing high speed, low-power and low-integration area digital circuits and systems

·       Understood thoroughly the various design strategies, so as to choose the most suitable according to the needs of the algorithm or the application to be implemented in hardware

·       Be able to choose between different implementations or apply appropriate optimization techniques to design high-speed or low-power or limited integration area hardware designs according to the algorithmic  design constraints.

·       Be able to apply optimization techniques at all levels of the design flow (system, algorithm, register, circuit) for the efficient implementation of algorithms in hardware designs

·       Be thoroughly aware of the methods and techniques required to verify the correct functionality of VLSI circuits and systems.

·       Have acquired design experience on the above topics through weekly mini lab exercises homework. 

·       Have acquired extensive experience through weekly mini lab exercises homework in designing, describing and implementing digital hardware systems using the VHDL hardware description language

·       Understood the basic need for integrated circuits testing and the need for their design for increased testability taking in consideration  economic aspects of ICs design and implementations.

·       Have knowledge on how to detect and model faults at logic level in ICs.

·       Become experienced in generating and applying test vectors as well as in testing  techniques for ICs.

Prerequisites

EEN 212 and EEN 314  or CEI 122  and CEI 323

Course Content

Basic and advanced techniques for developing, designing and testing integrated circuits. Digital design optimization techniques in terms of various designs parameters (speed, power, area) as well as practical approaches in testing the designed Integrated Circuits. Analysis of digital hardware design flow, design levels and implementations, Top/Down and Bottom/Up hardware design approach with examples. Timing and optimizations, Pipelined Digital Design for high throughput, Parallel Digital Design for low area consumption, Parallel, Algorithmic Loop Unfolded and Pipelined Digital Designs for low area consumption, Testbences for hardware designs simulations, Challenges in 90nm Digital Hardware Design.  Digital Hardware Design with hardware description language VHDL. Extensive case study, analysis and optimized redesign of hardware designed cryptographic algorithm: Pipelined SHA-1 Hash function. Introduction to the need for testing, Failures, Defects and Fault Models, Stuck-at Faults, Simple and multiple stuck-at faults, Faults coverage, Bridging Faults, Logic fault simulation, Serial, parallel, deductive and concurrent fault simulators, Test patterns generation, Algebraic and algorithmic methods for test patterns generation, Design for testability, Observation and control points, Pseudoexhaustive testing, Scan path design technique.

The course covers an introduction to the field of production planning and monitoring, and product delivery. It investigates methods and algorithms for solving basic business problems related to production systems layout design, warehouse management, material planning, personnel staffing, production scheduling, and supply chain management. Following contemporary international practices, emphasis in given to qualitative analysis of the problems that are encountered within a supply chain – from the supply of raw materials to the production of the final products and services and their delivery to customers and end-users.

Το μάθημα εστιάζεται στον σχεδιασμό και χρονικό προγραμματισμό έργων με έμφαση στα έργα πληροφορικής. Οι φοιτητές διδάσκονται τις μεθοδολογίες, τις τεχνικές και τα αναγκαία εργαλεία για αποτελεσματική και αξιόπιστη διαχείριση έργων γενικά, αλλά και της διαχείρισης έργων πληροφορικής, ειδικότερα. Έμφαση δίδεται επίσης σε προηγμένα θέματα που αφορούν τη διαχείριση έργων με περιορισμούς πόρων. Η κρισιμότητα των περιορισμένων πόρων σε ένα έργο συζητείται διεξοδικά και αναλύεται τόσο πρακτικά όσο και θεωρητικά υπό την οπτική των επιστημονικών πεδίων της επιχειρησιακής έρευνας και της συνδυαστικής βελτιστοποίησης.

This course teaches advanced topics in Software Engineering revolving around the following four axes: (a) Software Testing, (b) Distributed Software Systems, (c) Software Reuse, (d) Software Project Management. The first axis analyses basic and advanced concepts of software testing, starting from basic behavioral properties and ending with techniques and methods for analysis and testing of specifications and code using structural coverage criteria, as well as data and control dependence graphs. The second axis is concentrated on design and implementation issues of distributed software systems, focusing on distributed, layered architectures, middleware and provision of software as a service. Topics in the third axis cover modern software development approaches based on reusability, describing how components and open source software may be reused and integrated, and discussing their advantages and limitations. Finally, the fourth axis emphasizes on software project management issues and particularly on human resources management and cost estimation.

This course delves into and the design and implementation principles of distributed and networked operating systems. We emphasize classic operating systems design principles and the description of modern systems that form the basis for the Internet and the World Wide Web infrastructure. The course syllabus includes the following. Virtual memory, process management and inter-process communication. The design of the Unix operating system. Upcalls. Remote-procedure calls. Log-structured file systems. Distributed file systems. Microkernels. Virtualization. End-to-end design principle and the philosophy of the internet architecture. Distributed Hash Tables. Large-scale key-value stores. Map-Reduce, Pregel and Spark. Time, clocks and the ordering of events. Distributed consensus with Paxos. Large scale synchronization (ZooKeeper). Distributed transactions and notifications. Content distribution networks. Software-defined-networking. At the end of the course, the students will be able to: a) describe the fundamental design principles of distributed systems; b) to describe and use widely-accepted techniques for large scale system implementation; c) to understand the operational principles of the computing infrastructure of Google, Yahoo, Amazon, Facebook and other large scale online services; d) to read and understand research articles on computing systems engineering; e) to understand the implementation of a complex distributed system, so that they can evaluate its performance and modify it.

This module is about learning from data, in order to gain useful predictions and insights. Separating signal from noise presents many computational and inferential challenges, which we approach from a perspective at the interface of computer science and statistics. Through real-world examples of wide interest, we introduce methods for: • data munging/scraping/sampling/cleaning in order to get an informative, manageable datasets; • data storage and management in order to be able to access data - especially big data - quickly and reliably during subsequent analysis; • exploratory data analysis to generate hypotheses and intuition about the data; • prediction based on statistical tools such as regression, classification, and clustering; and • communication of results through visualization, stories, and interpretable summaries. Syllabus The module comprises a theoretical part and a series of laboratory excercises. THEORETICAL PART • Introduction. What is data science? Why is it important? Who are we? • Exploratory Data Analysis. Data Types. Data Dimensions. Visual Attributes. Effective Visual Encodings. • Visualization Design Principles. Statistical Graphs. • Data Sources. Web Scraping. Data Cleanup. • Probability review. Statistical models. Parametric and nonparametric distributions. Bootstrap. • Bias and sampling. Forms of bias. Bias-variance tradeoff. • Classification and regression. • High-dimensional data. Parallel Coordinates. Glyphs. Dimensionality Reduction. PCA. SVD. MDS. • Cross-validation. Clustering. • Bayesian thinking and methods. Prior distributions, likelihood. • Simulation methods, Bayesian computation, Monte Carlo methods. • Basic machine learning. • Amazon EC2, AWS Datastore, MapReduce, MRJob • Network sampling, community detection. LABORATORY • Introduction to Python and Numpy Arrays • Web Scraping, Data cleaning, and Pandas • Viz, and Matplotlib • SciKit Learn and Statistics in Python • SciKit Learn: inference, and cross-validation • SciKit Learn: Bayesian Analysis • MCMC in Python • EC2 and MRJob • Theano and GPU-based acceleration

This course is an introduction to the modern science of complex networks (network science), which studies the common principles and mathematical laws governing the structure and dynamics of large networks such as the Internet, Social Networks, the Web, Biological Networks, Transportation Networks, etc., as well as the principles determining the efficient communication and information flow in these networks. The student will acquire a wide range of knowledge and skills, such as the use of mathematical tools for efficient analysis and prediction of the structure of real networks, up to the design of innovative algorithms for efficient data mining and information transport within large networks. The course includes the following: network theory and representation, statistical network characterization, random graphs, formation mechanisms of real networks and evolutionary models, network geometry, "Small World" networks: Social Networks and the experiment of Milgram, Internet: novel routing techniques and Power Law topologies, dynamic processes in networks: decentralized search, random walks, rumors, gossips, epidemics, applications in large Social Networks (Twitter, Facebook) and the Web, and efficient analysis of large-scale network data. Prerequisite Background: Basic probability theory.

Natural language processing (NLP) is a crucial part of artificial intelligence (AI), modelling how people share information. In recent years, deep learning approaches have obtained very high performance on many NLP tasks. In this course, students gain a thorough introduction to cutting-edge neural networks for NLP.

This course aims at students being able to:

a) To describe and classify the fundamental design principles of deep learning systems.

b) To describe and use widely accepted techniques for deep network implementation.

c) To evaluate research articles on Deep Learning.

e)  To be capapable of carrying out a full-cycle Deep Learning Project

Course Content:

•             The foundational principle of Learning Representations.

•             Word Vectors

•             Word Vectors 2 and Word Window Classification

•             Backprop and Neural Networks.

•             Dependency Parsing.

•             Sequence-to-sequence networks.

•             Machine Translation, Attention, Subword Models

•             Question Answering.

•             Natural Language Generation.

The need to store and process massive amounts of data has led to the evolution of existing database systems while a new breed of data processing systems has emerged. This course covers a spectrum of topics from core techniques in relational data management to highly-scalable data processing using parallel database systems and MapReduce. First, the course covers the basic principles in database query processing and optimization, including index structures, sort and join processing, query rewrites, and physical plan selection. Next, the course covers topics from parallel and distributed databases, including data partitioning and distributed join algorithms. Finally, the course covers scalable data processing systems such as MapReduce and NoSQL databases (column, document, and key-value stores). The course material will be drawn from textbooks as well as recent research literature. Prerequisite background: Basic database knowledge.

This course prepares students for their Masters Thesis. It is an introduction to methodologies and techniques used for conducting original research in Computer Engineering and Informations and for preparing publishable articles. The course includes a series of seminars in various state of the art research subjects and open problems in domains of interest of the department's faculty. The main goal of the course is to stimulate interest in various research areas so that students are aided in selecting their thesis topic, as well as to equip them for the application of the scientific method in addressing computing problems and in producing high quality scientific work.

Deep Learning is the most highly sought-after skill in Artificial Intelligence. In this module, you will learn the foundations of Deep Learning, understand how to build neural networks, and learn how to lead successful machine learning projects. You will learn about Convolutional networks, Recurrent Neural Networks, Transformers, Regularization, Adversarial Attacks, Deep Reinforcement Learning, Interpretability, as well as bleeding-edge Stochastic foundational regards.

This course aims at students being able to:

a) To describe and classify the fundamental design principles of deep learning systems.

b) To describe and use widely accepted techniques for deep network implementation.

c) To evaluate research articles on Deep Learning.

d)  To be capable of carrying out a full-cycle Deep Learning Project

Course Content:

•             Introduction to deep learning.

•             Neural Network Basics.

•             The foundational principle of Learning Representations.

•             Attacking neural networks with Adversarial Examples

•             Adversarial Robustness.

•             Hyperparameter Tuning, Batch Normalization.

•             Stochastic Gradient Descent Training.

•             Convolutional Layers.

•             Recurrent Layers.

•             Self-Attention Layers.

•             Generative networks: Variational autoencoders; generative adversarial networks.

•             Interpretability of Neural Networks.

•             Deep Reinforcement Learning.

•             Meta-learning.

This course is an introduction to security and privacy on the World Wide Web. After providing a historical overview and examining of the main technologies and architecture of the Internet (HTML, Javascript, DOM, Frames, HTTP(S), DNS, client-side and server-side technologies), this course will focus on security and privacy issues, with its main emphasis on potential attacks and user protection mechanisms. Some of the topics that this course will explore are: Access control and Authentication, Password-based authentication, WebAuthn. Cross-domain communications, session management and cookies, Same Origin Policy (SOP), Cross-Origin Resource Sharing (CORS), Content Security Policy (CSP). Client-side attacks (XSS, CSRF, etc.), denial-of-service attacks, phishing attacks. SQL injection attacks and server-side attacks (code injection). HTTPS, SSL/TLS, and X509 certificates. DNS attacks. Privacy and anonymity on the Web, as well as user tracking and fingerprinting techniques. 

 Τhis course aims:

- To equip students with the necessary theoretical knowledge and skills around the various phases in the design and implementation of high performance digital integrated systems.

- To familiarize students with design automation tools and material description languages, through a combination of lectures, exercises and workshops.

- To offer students comprehensive knowledge of the principles of image processing.

- To enable students to design and implement calculations for the analysis, compression, transfer and segmentation of two-dimensional and multidimensional digital signal (image and video).

Upon completion of the course, students are expected to have concrete knowledge of 2D signal processing, the basic concepts and application areas of digital image processing, to understand the operation of basic multimedia image coding standards, and to be able to use their programming experience for the development of video and video editing programs. They should also be able to use image processing algorithms and appropriate techniques to solve domain-specific problems.

This course includes topics from the broader area of Software Project Management with emphasis on modern development approaches. In this context subjects revolving around the following four axes will be covered: (a) Human resources, (b) Processes, (c) Tools, and (d) Metrics. More specifically, the lectures will teach introductory, as well as specialized concepts of the following topics: (1) Human resources management, (2) Software development processes, (3) Software project management tools, (4) Metrics and measurement of the software development process, (5) Vision and scope, (6) Resources management, (7) Time scheduling and project planning, (8) Planning documentation, (9) Activities and people, (10) Project planning and support, (11) Implementation of plans and human resources leadership, (12) Project monitoring and control, (13) Re-scheduling, (14) Product engineering. Prerequisite: The students must have successfully completed a classic undergraduate course on Software Engineering.

This course focuses on the planning and scheduling of projects with emphasis in IT projects. The students are taught how to use the concepts, methods and tools of project management to execute their organizations’ strategic initiatives efficiently, effectively and reliably. Emphasis is also given to advanced topics concerning the resource-constrained project scheduling using well-accepted OR and modern computational optimization methods from the field of meta-heuristics

The course covers an introduction to the field of production planning and monitoring, and product delivery. It investigates methods and algorithms for solving basic business problems related to production systems layout design, warehouse management, material planning, personnel staffing, production scheduling, and supply chain management. Following contemporary international practices, emphasis in given to qualitative analysis of the problems that are encountered within a supply chain – from the supply of raw materials to the production of the final products and services and their delivery to customers and end-users.

Course Purpose and Objectives

The purpose of the Calculus I course is to familiarize students with the basic concepts of differential and integral calculus and their applications to Science and Engineering.

Learning Outcomes

To understand the major theoretical background of functions, limits, derivatives and their application in engineering problems, integrals, techniques of integration and application of the integral.

Course Content

Functions. Composition of functions. Inverse functions. Limits. Continuity theorems of continuous functions. The derivative function definition of the derivative function, derivatives of trigonometric functions. Differentials. Applications of the derivative (maxima and minima, concavity, L’hospital’s rule). Integration. The indefinite and definite integral. Methods of integration. Applications of the definite integral (areas, volumes, lengths of plane curves, etc.). Complex numbers. Differential equations of first order. Sequences of real numbers. Convergence of a sequence. Infinite series. Convergence tests (the integral test, the comparison, ratio and root tests). Alternating series. Absolute and conditional convergence. Power series. Radius and interval of convergence. Maclaurin & Taylor series. Applications using Maclaurin series (sums, limits, solution of differential equations in series forms, etc.).

Course Purpose and Objectives

Introduction to Newton's laws. Applying Newton's Laws and Energy Methods. The course focuses on Newton’s Laws and Thermodynamics.

Learning Outcomes

In-depth knowledge of Newtonian Mechanics and basic knowledge in Thermodynamics.

Course Content

Kinematic, Newton's Laws, Projectile motions, Energy, Energy Conservation. Momentum and Collisions. Solid body rotation, rotating reference systems. Solid body movement. Gravitational attraction. Oscillations. Mechanics of fluids. Wave motion. Temperature. Ideal Gases, First Thermodynamic Law, Kinetic Gas Theory, Thermal Engines, Entropy, Second Thermodynamic Law, Third Thermodynamic Law.

Course Purpose and Objectives

To understand the importance and role of Calculus and Differential Equations in all the sciences and especially in Electrical Engineering, Computer Engineering and Computer Science, as well as to become fluent in the various of techniques for solving problems in these areas.

Learning Outcomes

It is expected that the student will be able to:

1. have full knowledge of the theoretical foundations of the subject (that is to be able to state and reproduce the definitions, the notation, the properties, the theorems),
2. translate the relations between different variable quantities in a specific problem into mathematical terms,
3. construct and solve the appropriate Differential Equation that governs a specific problem,
4. investigate the true meaning of the solution and
5. determine whether it is acceptable based on the fundamental laws of Physics,
6. define functions of many variables, graphically represent them, calculate their limits and determine whether they are continuous,
7. calculate partial derivatives of functions of many variables, and apply them to solve maximization and minimization problems,
8. calculate multiple integrals and use them to find areas and volumes, calculate the mean, find moments, centrifugal and surface areas.

Course Content

I. Differential Equations:

1. Basic characteristics of differential equations (DE).
2. Simple DE of first and second order, applications (Newton’s equations.)
3. General study of linear DE.
4. Linear DE with variable coefficients, method of power series (applications to Bessel and Legendre equations).

II. Calculus:

1. Functions of several variables.
2. Partial derivatives.
3. Applications of partial derivatives.
4. Multiple integrals.
5. Applications of integrals.

Course Purpose and Objectives

The course of Introduction to Computation and Programming aims to further enrich the knowledge of students in the organization of computer hardware (micro-processors and memory structures) and computation (Turing machines, finite machines Normal languages, grammar without context). Introduction to modular programming. Presentation of the process of development of functional and procedural software and introduction of the basic principles of programming and design of programs through the language C. General presentation of language C focusing on data types, structures control, repeating structures, functions, arrays, alphanumeric sequences, markers, and recursion. The course includes several programming exercises and a semester's work.

Learning Outcomes

• After the successful completion of the course, the learner should:
• Know the historical overview of computer development.
• Know the organization of computer hardware.
• To know the different methodologies and their differences in programming as well as the generations of programming languages.
• Be able to apply the theory to solve problems by writing programs correctly, effectively and maintainable.

Course Content

The topics to be examined include: Algorithms, C commands such as if, if/else, while, do/while, for etc.  Also functions, various libraries, header files, random numbers, storage classes and scope rules, recursion, Tables and fonts, multidimensional tables, indicators, revenue/expense formatting, and file processing.

This subject constitutes an introduction into object-oriented programming with C++. It commences with discussions of the basic principles involved in object –oriented programming like for example the definition of an object, a class, inheritance, input and output streams, pointers, types vs. classes, operator overloading. The following topics are covered in greater depth: Classes including derived classes, messaging. Classes about input/output streams. Abstract datatypes. Pointers. Inheritance (including virtual methods, static definitions, multiple inheritance). Operator Overloading. General abstract types. Knowledge of C is a necessary pre-requisite.

Prerequisites

EEI 132 Introduction to Computing and Programming (C) 

Course Purpose and Objectives

This course aims to further enrich students ' knowledge in object-oriented programming with C++. The course teaches C++ starting from simple concepts such as classes, objects, inheritance, I/O flow classes, reference to C++ types, markers, struct, etc. The concepts of complexity and overload of operators are Also taught.

MODULES-CAPITALS: Classes, derivative classes, input/output classes, substructs, pointers, inheritance, function and operator overload, complexity

Learning Outcomes

• After the successful completion of the course, the learner should:
• Know the difference between object-oriented and structured programming.
• Be aware of concepts such as classes, objects-member functions, and member data.
• Know the differences of access identifiers (public, private, protected) and what is constructor and destructor.
• Be able to write the classes in a different file to create project by separating the programs into interface, implementation and client for reusability purposes.
• Be aware of the concepts like encapsulation, inheritance, polymorphism and virtual methods.
• Can solve problems using control commands, with pointers, fonts, files, tables vectors, and functions.
• Know how to use most of the libraries available in C++.

Prerequisites

EEI 132 - Introduction to Computation and Programming

Course Content

The topics to be examined include: Classes and all general concepts of object-oriented programming such as encapsulation, inheritance, polymorphism, and virtual methods. All C++ commands, such as control commands, functions, various libraries, random numbers, storage classes and scope rules, recursion, tables and fonts, multi-dimensional tables, pointers, format input/output and files.

Course Purpose and Objectives

To understand the importance and role of Calculus and Differential Equations in all the sciences and especially in Electrical Engineering, Computer Engineering and Computer Science, as well as to become fluent in the various of techniques for solving problems in these areas.

Learning Outcomes

It is expected that the student will be able to:

1. have full knowledge of the theoretical foundations of the subject (that is to be able to state and reproduce the definitions, the notation, the properties, the theorems),
2. translate the relations between different variable quantities in a specific problem into mathematical terms,
3. construct and solve the appropriate Differential Equation that governs a specific problem,
4. investigate the true meaning of the solution and
5. determine whether it is acceptable based on the fundamental laws of Physics,
6. perform various algebraic operations between vectors (addition, subtraction, scalar multiplication, outer product, mixed product),
7. calculate derivatives and integrals (line and surface) of vector functions.
8. Solve problems (area calculation, mechanical work, flow) with natural quantities that are vectors.

Prerequisites

ΕΕΙ 103 – Advanced Mathematics II

Course Content

I. Differential Equations:

1. Linear systems of differential equations (DE) and matrix exponentials.
2. Laplace transformations and applications.
3. Fourier series. Fourier transformations.
4. Partial DE and applications

II. Calculus:

1. Vector functions.
2. Themes from vector calculus.

Course Objective

To prepare students to understand basic knowledge applicable to all species of living organisms and their areas of application at a more specialized level. Also, to familiarize students with the phenomena of life and biological problems.

Learning outcomes

Gaining basic knowledge in the major subjects of life sciences, so the students can apply them in the future to their own scientific objects.

Course Content

The following chapters are covered:

• The beginning of life, features of life
• Chemistry of life
• Enzymes and metabolism
• Cell
• Photosynthesis
• Cellular respiration
• Tissues and organs
• Expression of genetic material
• Cell cycle (mitosis – meiosis)
• Development and differentiation
• Infectious diseases
• Genetic diseases
• Cancer
• Genetics – Genetics Exercises
• Evolution and natural selection
• Synthetic biology

Course Purpose and Objectives

To give a wide knowledge to engineers as to basic concepts on signals and systems as well as the connected transformations, which can become tools for better understanding and solving related applications

Learning Outcomes

Acquisition of additional significant background for use in engineering applications.

Course Content

Introduction to signals, Introduction to systems, Fourier expansion and series, Fourier transform and applications, Fourier transform of discrete signals, Laplace transform and applications, z transform.

Course Goals

Introduce students to the basic concepts of Computer Organization.

Expected Results

Students shall have an in-depth knowledge of basic computer organization and structure, microprocessor structure and computer memory, as well as identifying methodologies for improving processor performance.

Content

The course covers fundamental operational structures of uni-processor computer systems and their basic building blocks: arithmetic and logical unit, control unit (FSM-based), memory system, I/O system, datapath. It also covers binary number systems, one’s and two’s complement arithmetic, floating point arithmetic, overflow and underflow, addition, subtraction, division and multiplication using binary numbers. Presentation of the RISC Central Processing Unit (CPU) using the MIPS architecture as a reference. RISC Instruction Set Architecture (ISA). Assembly programming in MIPS. Pipelining, data, control and structural hazards. Interrupt and exception handling. Random-Access Memory (RAM), cache memory organization (direct-mapped and set-associative), and virtual memory. CPU performance measurement and enhancements involving branch prediction and assembly instruction re-ordering. Storage systems such as hard disks and optical media. The course includes a weekly programming laboratory session for hands-on practice using the MIPS ISA assembly language.

Course Goals

Introduce students to the basic concepts of Computer Organization.

Expected Results

Students shall have an in-depth knowledge of basic computer organization and structure, microprocessor structure and computer memory, as well as identifying methodologies for improving processor performance.

Content

The course covers fundamental operational structures of uni-processor computer systems and their basic building blocks: arithmetic and logical unit, control unit (FSM-based), memory system, I/O system, datapath. It also covers binary number systems, one’s and two’s complement arithmetic, floating point arithmetic, overflow and underflow, addition, subtraction, division and multiplication using binary numbers. Presentation of the RISC Central Processing Unit (CPU) using the MIPS architecture as a reference. RISC Instruction Set Architecture (ISA). Assembly programming in MIPS. Pipelining, data, control and structural hazards. Interrupt and exception handling. Random-Access Memory (RAM), cache memory organization (direct-mapped and set-associative), and virtual memory. CPU performance measurement and enhancements involving branch prediction and assembly instruction re-ordering. Storage systems such as hard disks and optical media. The course includes a weekly programming laboratory session for hands-on practice using the MIPS ISA assembly language.

Course Purpose and Objectives

Understand the function and characteristics of operational amplifiers for specific applications. The student should fully analyze and design basic circuits with Op-Amps. Understand Digital Electronic Circuits

Learning Outcomes

Acquire comprehensive knowledge on the analysis, operation,  and implementation of Op-Amp circuits. Design of circuits with Op-Amps.Understanding and design of digital electronic circuits

Course Content

1) Inverting and Non Inverting Amplifier

2) Summing Amplifier, Integrator and Differentiator

3) Other Linear applications of Op-Amps

4) Comparators and Schmitt trigger

5) Other non-Linear applications of Op-Amps

6) Active filters and timing circuits

7) Waveform generators

8) Digital Electronic circuits

Course Purpose and Objectives

Basic information procedures for the electrical installation design about: safety, information, responsibilities and obligations of the designer, harmonization with the legal legislation and professional parties.

The course material aims at the understanding and consolidation of concepts related to transient phenomena and circuits, including RC, RL, RLC circuits, as well as of the methods for their analysis.

The course is based on the basic concepts of circuit elements of simple linear circuits and the methods for their analysis offered in the prerequisite course. The following topics are covered:

1. Laplace transformation, transfer functions
2. First and second-order circuits (RL, RC, and RLC) and analysis in the time domain
3. Circuit analysis - complex frequency domain
4. Oscillators and tuned circuits
5. Time response of circuits
6. Transient phenomena
7. Two-port elements and dependent sources
8. Operational amplifiers

Course Purpose and Objectives

The objectives of this course are:

• Study and understanding of the basic functional principles of Digital Systems and Circuits, their parameters, their design constraints and the technologies for their implementation and design.

• The thorough study and detailed understanding of the main issues and concepts for designing combinational and sequential logic circuits as well as their optimal design and the various implementation parameters.

• Understanding of the programmable logic devices with an emphasis on FPGAs and introduction to describing digital circuits and systems using HDLs 

• Analysis and design of counters (synchronous and asynchronous) and registers.

•Analytical study and understanding of State Diagrams design and implementation of the respective FSM State Machines.

• Analytical study and detailed understanding of the operations of basic types of RAM (SRAM, DRAM) and ROM.

Learning Outcomes

At the end of this course the students will have understood the basic principles, parameters and limitations of digital systems design and implementation of the corresponding circuits as well as how to evaluate and compare various designs and implementations.

Students will also have acquired the necessary knowledge to design and optimize digital systems, having studied extensively the design of combinational and sequential circuits, as well as FSM State Machines.

In addition, they will have understood the basic principles of various programmable logic devices, especially FPGAs, and will have acquired some basic knowledge of circuit design with HDL languages.

In addition, they will be able to design counters and registers according to the needs of their applications.

Finally, they will know the functions and operations of the basic types of semiconductor memories (RAMs, ROMs) and their specific characteristics.

Course Content

Integration Technology and Advantages, Integrated Circuits (ICs) Logic Families, Critical Path, Integration Area and Power Dissipation, Noise and Noise Margins, Fan-out, Logic Gates Implementation in TTL, CMOS, CMOS Logic Function Design and Power Consumption, CMOS Transistor Sizing, Transmission Gates, CMOS Physical Layout.

Combinational Logic: Design of Combinational circuits, Design with CAD tools and Hardware Description Languages(HDL), Basic Combinational logic functions and circuits: Adders (Ripple Carry Adder, Carry Look-Ahead Adder, Carry Select Adder), Subtractor, Add/Sub circuit, Multiplexers, Demultiplexers, Comparators, Priority Encoders, Decoders and other digital circuits, Combinational Logic ICs Hierarchical Design and Cascade Extension, Applications of Combinational Circuits.

Programmable Logic Devices: ROMs, PLAs, PALs, CPLDs, FPGAs and Digital Design Implementation, Design Simulation and Debugging, Performance Estimation and Implementation Area

Sequential Logic Circuits: Latches, Master-Slave, D, J-K and T Flip Flops, Set and Reset Signals (Synchronous and Asynchronous), Operating conditions  and Timing of Flip Flops, Special Design Issues for Flip Flops, Flip Flop ICs and Applications.

Synchronous and Asynchronous Counters: Binary, Decimal, Modulo-n, Methodology for Synchronous Counter Design: General Case, Counters ICs and Counting Extension (Cascade), Sequential Design with Hardware Descriptive Language (HDL).

Registers: Parallel Load, Shift Register, Serial or Parallel Input / Serial or Parallel Output, Multi-Function Shift Register, Registers-Counters (Johnson Counter)

Finite State Machines: State Diagram, Mealy and Moore State Machine Circuits, Design Methodology and Examples.

Semiconductor Memories: Typical Memory Internal Memory, Memory Features, Memory Storage Cells-Organization-Adressing-Read and Write Operations in SRAMs and DRAMs, Read-only memory, EEPROM, Flash.

Course Purpose and Objectives

Perform a series of experimental measurements with basic instruments in circuits including passive electrical elements. Make measurements of the various electrical signal parameters.

Learning Outcomes

Full understanding of experimental application techniques for electrical circuits.

Course Content

MEASURING INSTRUMENTS: Amp -Volt - Gen - Osc., CONNECTIONS ohm, WIRING resistor in series and parallel impedances WIRING, CIRCUIT IN SERIES RC, RL IN SERIES CIRCUIT, POWER AC POWER, COORDINATION OF SERIES & PARALLEL COORDINATION, TRANSIT FREQUENCY FILTERS 1st Class-RC, 2nd Class Low Frequency Pass Filter, 2nd Class High Frequency Pass Filter-LC FILTER.

Course Purpose and Objectives

Understand the function and characteristics of semiconductors for specific applications. The student should fully analyze the basic circuits with diodes and transistors

Learning Outcomes

Acquire comprehensive knowledge on the analysis, operation, design and implementation of circuits with diodes, and transistors.

Course Content

1) Semiconductor diodes

2) Bipolar junction transistors

3) Field effect transistors

4) Bias and stability

5) Small signal amplifiers

6) Differential Amplifiers

7) Power amplifiers

8) Frequency response

Course Purpose and Objectives

The objectives of this course are:

• Students to gain hands-on experience in digital circuit design and in usage of integrated ICs both in educational boards and with CAD tools in FPGAs.

• To acquire practical knowledge and to practice the necessary design approaches for designing systems such as reusability, hierarchical design, abstraction levels, etc.

• Students should acquire practical knowledge and practice simulation techniques and debugging both during the design phase.

• The study and understanding of the basic functional principles of Digital Systems and Circuits, their parameters, their design constraints and the technologies for their implementation and design, as well as the way of their interconnection.

• The use and understanding of the structure and utilization of FPGA devices, the schematic description of combinational and sequential logic circuits, as well as the introduction to the description of digital circuits and systems with hardware languages (HDL).

• Implementation in educational boards as well as with CAD tools in FPGAs, while understanding the basic operation principles, of combinational and sequential logic design, as well as their optimal design and the various implementation parameters.

• Analysis, design and implementation of counters (synchronous and asynchronous) both in educational boards and with CAD tools in FPGAs.

Learning Outcomes

At the end of this course the students will have learned to:

-Implement combinational and sequential logic circuits in both CAD tools (ALTERA QUARTUS II software) with final implementation in FPGAs as well as in  educational boards.

-Use the ALTERA QUARTUS II software to design and simulate digital circuits and to finally implement their designs in FPGA boards.

-Make excellent use of the laboratory equipment for their experimental designs such as breadboards, ICs, Signal generators, multimeters, digital oscilloscopes, etc.

-Use design techniques to efficiently implement large designs by managing the complexity of designs and assessing the advantages / disadvantages of each design approach.

-Perform efficiently simulations and debugging of their designs during the design phase.

-Design and implement ad-hoc counters (synchronous and asynchronous) on both FPGAs and educational boards, according to the needs of their applications.

-Design basic digital circuits using hardware description language (VHDL) and implement in FPGAs

Course Content

Introductory course to lab equipment, familiarization with basic logic gates and design and implementation of combinational circuits with SSI and MSI ICs ın breadboards. Familiarization with Flip Flops: S-R flıp flop, D flıp flop, J-K flıp flop. Preset and Clear functıons. Design and implementation of digital sequential circuits with SSI and MSI ICs in educational breadboards: Registers, Synchronous and Asynchronous Counters. Introductory course to design software ALTERA Quartus II, to programmable logic devices and implementations of digital circuits on FPGA. Design and FPGA implementation of combinational circuits: Adders, Comparators, Multiplexers, Encoders/Decoders, Hierarchical and Cascade Design. Design and FPGA implementation of sequential circuits: S-R flıp flop, D-Type flıp flop, J-K flıp flop, Asynchronous and Synchronous counters. Hierarchical design and FPGA implementation of Arithmetic and Logic Unit (ALU). Introduction to HDL. Design and FPGA implementation of combinational and sequential circuits with VHDL. Hierarchical design using HDL and FPGA implementation of Arithmetic and Logic Unit (ALU). Advantages and disadvantages of levels of abstraction: comparison of ALU alternative designs.

Prerequisites

EEI 132 -  Digital Systems 

Course Purpose and Objectives

The course covers the various imaging modalities (Ultrasound, MRI, X-rays, CT, SPECT and PET). It covers also various important topics in biomedical engineering (biomaterials, biosensors, medical devices, ECG, EEG, endoscopy etc)

Learning Outcomes

Introduction to the basic principles of biomedical engineering (imaging, materials, sensors, etc.).

Course Content

Basic principles of ultrasound and function of the central nervous system. Introduction to the emerging medical devices industry. Ultrasound Imaging, X-rays, computed tomography tomography (CT), MRI, positron tomography (PET), and the DICOM standard. Medical robotics. Wearable devices. Role of laser in surgery. Endoscopy, techniques, and therapies with the help of endoscopy. Cardiac devices (e.g. pacemaker). Understanding and analysis of the electrocardiogram, electroencephogram and electromyogram. Ablation techniques (RF, laser, microwave, Therapeutic ultrasound etc). Radiotherapy (linear accelerators). Procedures for the approval of medical devices. Introduction to telemedicine. Biomaterials, and biosensors. Introduction to 3D printing for biomedical use.  

Course Objective

That the student understands the operation of the control systems mentioned in the Course Content. To do the mathematical analysis of the systems mentioned in the Course Content.

Learning results

Acquiring comprehensive knowledge around the analysis, mathematical modeling and design of the systems referred to in the course content.

Course Content

Mathematical modeling of dynamic systems, State models, Linearization of nonlinear systems, Transfer functions, Stability of linear systems, Observability and controllability, Bode plots, The Nyquist stability criterion, Compensator design.

Course Objective

To perform a series of experiments with electronic circuits, diodes and amplifiers with transistors and measurements of the various parameters of the amplifiers.

Learning results

Thorough understanding of experimental application techniques for electrical circuits.

Course Content

AC VOLTAGE RECTIFICATION & SEMIRECTIFICATION, DESIGN IN ZENER DIODES APPLICATIONS AND VOLTAGE REGULATORS FROM AC SOURCE TO DC OUTPUT, BIPOLAR JOINT TRANSISTOR (BJT)- COMMON EMMITTER (CE) CONFIGURATION AND STATIC CHARACTERISTICS, COMMON-EMMITTER AMPLIFIERS WITH AC INPUT SIGNAL, WHEATSTONE BRIDGE CONSTRUCTION AND THE DIGITAL OSCILLATOR, PUSH-PULL AMPLIFIER, JFET (Junction Field Effect Transistor), SILICON CONTROLLED RECTIFIER (SCR) - PRACTICAL APPLICATION, OP-AMP 1: PARAMETERS, 2: SIMPLE APPLICATIONS (INTEGRATION AND SUMMATION), 3: SIMPLIFIED CIRCUIT DESIGN USING OP-AMP, WIEN-BRIDGE OSCILLATOR AND THE 555 TIMING CIRCUIT.

Course Purpose and Objectives

Understanding the main medical imaging categories such as ultrasound imaging, magnetic resonance imaging, X-rays, CT, SPECT and PET

Learning Outcomes

Basic knowledge of the main categories of medical imaging.

Course Content

The course examines the physical principles of the main types of medical imaging such as ultrasound imaging and magnetic resonance imaging. Ultrasound will focus on imaging (A-mode, B-mode, M-mode), tissue interaction (attenuation), transducer design, ultrasound device. Magnetic resonance imaging will focus on the basic functions of magnetic resonance imaging. X-rays, X-ray tube construction, X-ray interaction with tissues, computed tomography (CT), SPECT, PET.

Course Purpose and Objectives

Electromagnetism is a four hour per week course designed to give an understanding of the many facets of electromagnetism.

Learning Outcomes

Detailed knowledge of Electromagnetism.

Prerequisites
 
EEN_105 Physics II
 
Course Content

Vector analysis, Electric charges, Electric field intensity, Potential, Dielectrics, Capacitance, Poisson’s and Laplace's equations, Steady magnetic fields, Forces in steady magnetic fields, Magnetic circuits, Time - varying fields and Maxwell's Equations, Plane waves.

Course Purpose and Objectives

Introduction to analog and digital communication systems.

Learning Outcomes

Basic knowledge about communication systems.

Prerequisites

EEI 231 (Signals and Systems) or approval by the instructor.

Course Content

Signals and signal space: analysis and transmission of signals. Modulation and demodulation: amplitude (AM) and angle (FM). Sampling and analog-to-digital conversion. Principles of digital data transmission. Introduction to information theory and coding.

Course Purpose and Objectives

Students should assimilate the necessary theoretical and practical knowledge about the various phases in digital processing of one-dimensional and two-dimensional digital signals. Design and analysis of digital systems and their applications / implementations using programming. The course is offered through a combination of lectures, exercises and programming workshops.

Learning Outcomes

Gain comprehensive knowledge of signal analysis, specifications, operation, design, analysis and programming of digital systems. Also obtain knowledge of discrete-time systems and properties, continuous and discrete Fourier transform and applications. Introduction to the design of finite and infinity digital filters (FIR and IIR) impulse response.

Prerequisites

EEN_231 Signals and Systems

Course Content

The course is based on the basic elements of the analysis and processing of digital signals and systems, offered in the prerequisite course, and has as its main objectives the following:

• Recapitulation on signals, systems, sinusoidal sampling. Aliansing and folding. Sampling theorem.
• Discrete-time systems and properties. Impulse response. Convergence. Application in MATLAB environment.
• Series, Fourier transform and properties. System Frequency Response. Finite and Infinite Impact Response Systems (FIR, IIR). Applications in MATLAB environment.
• Frequency response of FIR and IIR systems. Linear phase.
• Frequency sampling. Discrete Fourier transform. Applications in MATLAB environment.
• Fourier discrete transform properties and applications. Signal spectrum analysis. Circular convolution.
• Introduction to digital filters. Design of FIR filters using windows. Applications in MATLAB environment.
• Design of FIR filters by frequency sampling.
• Z-Transform. Implementation in MATLAB environment.
• Design of IIR filters.
• Implementation of discrete time systems.
  
  The following chapters are covered:
• Sampling of sinusoids signals. Sampling theorem.
• Discrete-time systems and their properties.
• Fourier Series and Fourier Transform and Properties. Finite and Infinite convolution (Response) Systems (FIR, IIR).
• Frequency sampling. Discrete Fourier transform. Circular convolution.
• Introduction to digital filters. Design of FIR filters using windows and frequency sampling.
• Transformation Z.
• Design of IIR filters

Course Purpose and Objectives

The first part of this lab course aims at students familiarizing with the special characteristics of automatic control problems over a series of lab exercises. The lab is equipped with a number of electromechanical units (inverted pendulum, rectilinear mass system, gyroscope, magnetic levitation system, etc.) for the analysis and synthesis of linear and non-linear automatic control systems. 

The second half of this course is focused on performing various telecommunication experiments. Specifically, students will perform introductory experiments on Analog Communications and then will emphasize on experiments related to AM Transmission, AM Reception and Angle Modulation and Demodulation.

Learning Outcomes

At the end of this course the students will have understood the practical approach of the basic theoretical principles of digital logic analogue telecommunications and will be able to use the laboratory equipment to perform analogue transmission and reception of signals (AM, FM and PM) and to make voltage and power measurements so as evaluate transmission quality and power losses.

Course Content

Introduction to laboratory equipment for performing telecommunication experiments and relevant measurements, Introductory Laboratory and Measurements in Analog Telecommunications Experiments, Laboratory exercise on Amplitude Modulation and Demodulation, AM Transmission Laboratory Exercise, AM Reception Laboratory Exercise, Laboratory exercise on Angle Modulation and Demodulation, Frequency Modulation (FM) and Demodulation Laboratory Exercise, Phase Modulation (PM) and Demodulation Laboratory Exercise.

Prerequisites

EEN 311 Control Systems 

Course Purpose and Objectives

This course covers the fundamentals of power system modelling, structure, and basic characteristics. It helps the students to develop the skills required to analyse electric power systems, understand the functional characteristics and to develop models for component-level as well as system-level analysis. The basic power system components, such as synchronous machines, transmission lines, transformers, power flow equations (analytical), and loads, are analysed and their impact to the system is considered through real-life scenarios.

Learning Outcomes

On completion of this course, students should be able to:

• Explain the functioning and modelling of the main components in a power system;
• Be able to solve basic load flow calculations analytically;
• Understand the principles of planning and operation of power systems;
• Have an overview of future trends in power systems and smart grids;
• Appreciate, through basic case studies, the technical challenges in both the design and the operation of power systems.

Prerequisites

Electrical Circuit Analysis (or similar course)

Course Content

The course includes:

• Power system concepts: single- and three-phase systems, phasor representation in sinusoidal steady-state, real and reactive power, per unit system.
• Fundamentals and modelling of power system components: generators, loads, transformers, transmission lines, efficiency and power loss.
• Fundamentals of power system operation and smart grid technologies.

Course Purpose and Objectives

Provide students with a complete design experience, including the need to set design goals and objectives, integrate knowledge, practice engineering judgment, plan to meet a budget and timetable, do teamwork, and written communication.

Learning

Understand and achieve the objectives set out above and the potential for further understanding of applications.

Course Content

Integrated design courses provide the opportunity to apply the engineering knowledge and skills that have been accumulated so far and to learn new concepts in applied engineering. An engineering system design project is jointly agreed with a group of students and the supervising professor. The team studies the problem, develops design alternatives, and selects the most feasible solution. The prototype of the system is completed after obtaining all the necessary materials and then error checking and correction. Upon completion of the system the team presents the design and prototype of the system to a panel of judges for evaluation.

These courses put students in an environment completely opposite to the majority of the courses in their previous curriculum. They tackle aspects of applied engineering that have not been addressed in academic classroom discussions so far. There is a need to distribute responsibilities to team members and to support the work needed to successfully accomplish team goals with others. These and other aspects of group-member interactions are often regarded as valuable experiences gained through this course.

Course Purpose and Objectives

Provide students with a complete design experience, including the need to set design goals and objectives, integrate knowledge, practice engineering judgment, plan to meet a budget and timetable, do teamwork, and written communication.

Learning Outcomes

Understand and achieve the objectives set out above, complete the task and be able to further understand applications.

Prerequisites

EEN 411

Course Content

Integrated design courses provide the opportunity to apply the engineering knowledge and skills that have been accumulated so far and to learn new concepts in applied engineering. An engineering system design project is jointly agreed with a group of students and the supervising professor. The 

team studies the problem, develops design alternatives, and selects the most feasible solution. The prototype of the system is completed after obtaining all the necessary materials and then error checking and correction. Upon completion of the system the team presents the design and prototype of the system to a panel of judges for evaluation.

These courses put students in an environment completely opposite to the majority of the courses in their previous curriculum. They tackle aspects of applied engineering that have not been addressed in academic classroom discussions so far. There is a need to distribute responsibilities to team members and to support the work needed to successfully accomplish team goals with others. These and other aspects of group-member interactions are often regarded as valuable experiences gained through this course.

Course Purpose and Objectives

Photonics 441 is a four hour per week course designed to give an understanding of the many facets of photonics.

Learning Outcomes

Detailed knowledge of Photonics.

Prerequisites

Electromagnetism

Course Content

1. Introduction to Photonics and Optical Communication

Overview of photonics and the applications in different areas such as information technology and communications, healthcare, life sciences, optical sensing, lighting, energy and manufacturing. The evolution of light-wave systems will be discussed before the basics of optical communications systems will be introduced.

2. Nature of light and the production of EM radiation for photonics applications

i) Wave Nature of Light

Light waves in homogeneous media. Refractive index. Group velocity and group index. Magnetic field, Irradiance and Poynting vector. Snell's law and total internal reflection. Fresnel's equations. Multiple interference and optical resonators. Temporal and spatial coherence. Diffraction principles. Polarisation. Methods to define the characteristics of light mathematically (Stokes parameters, Jones vectors & matrices) and how to determine these characteristics.

ii) Optical sources and transmitters

Principles of light emission and amplification in semiconductors, light emitting diodes, semiconductor lasers (edge emitting lasers and VCSELs).

Semiconductor science and light emitting diodes (LED). Semiconductor concepts and energy bands. Direct and indirect band-gap semiconductors: E-k diagrams. P-n junction principles and band diagram. LED and materials. Heterojunction high intensity LED and characteristics. Steady state semiconductor rate equation. LED for Optical fibre communications. Single frequency solid state lasers. Quantum well devices. Optical amplifiers.

3. Optical waveguides

The propagation of light in optical waveguides.

Dielectric waveguides and optical fibres. Symmetric planar dielectric slab waveguide. Modal and waveguide dispersion in the planar waveguide. Step index fibre. Numerical aperture. Dispersion in single mode fibres. Bit-rate, dispersion and optical non-linearities, Electrical and optical bandwidth. Graded index optical fibre. Attenuation in optical fibres-light absorption and scattering. Fibre manufacture.

4. Optical detectors and receivers

The detection of light and the demodulation of light including 

photoconductors, photodiodes and receiver systems.

Principle of the p-n junction photodiode. External photocurrent. Absorption coefficient and photodiode materials. Quantum efficiency and responsivity. The pin, avalanche and heterojunction photodiodes. Phototransistors. Photoconductive detectors and photoconductive gain. Noise in photodetectors. Generic system issues: sources of noise and signal-to-noise ratio, limitations on temporal response and effective bandwidth.

5. Imparting information onto EM radiation & communication techniques

i) Basic modulation principles

Polarisation and modulation of light. Light propagation in anisotropic media: birefringence. Birefringent optical devices. Optical activity and circular birefringence. Electro-optic effects. Integrated optical modulators. Acousto-optic modulator. Magneto-optic effects. Non-linear optics and second harmonic generation.

ii) Modulation

Acousto-optic and electro-optic techniques, LED switching, analogue and digital techniques using lasers, AM, FM, phase modulation techniques

6. Applications for light-wave systems

A summary of important concepts of digital communication including base band and broadband digital transmission, bit error rate, bit group error rate and time division multiplexing (TDM) and wavelength division multiplexing (WDM). Trends and new directions in photonic applications

i) Noise and detection

Noise arising from the properties of fibres, transmitters, receivers and amplifiers as well as the determination of the bit error rate.

ii) Optical MUX and DEMUX

The operating principle of multiplexers and demultiplexers. Different optical devices, essential to optical networks, optical amplifiers, polarisation control devices, optical isolators, optical filters and diffraction gratings, modulators and switches.

iii) Optical systems design

Design process for a point-to-point optical links.

Course Objective

• For the student to understand the function and characteristics of power converters for specific applications
• To fully analyze the basic power electronic circuits
• To understand and prepare specifications
• To design assemblies that include power electronics at system-level
• To design power converters at circuit level
• To get to know and appreciate the new trends in power electronics

Learning results

Acquiring comprehensive knowledge about the analysis, specification, operation, design and implementation of Photovoltaic systems. Knowledge of Wind Turbines operation and the basic site selection parameters.

Ability to follow developments in their field.

Prerequisites

EEN 312 Electronics II

Course Content

Semiconductor Power Switches

Ideal power switch. Construction, operation and switching characteristics, transition delay from cut-off state to conduction state and vice versa of semiconductors: Rectifier Diode, Thyristor, Contact Transistor, Power MOSFET Transistor, IGBT and others. Power losses due to time delays.

Topology and Operation of Converters

Five basic Power Electronics circuits (AC/DC, DC/DC, DC/AC, AC/AC and Active Filters): Operation with reference to the modes and input-output voltage relationships and duty-cycle of semiconductors. Generation and description of relevant voltage and current waveforms.

Analysis (and PSICE/PSIM simulation) of Power Electronic Circuits

Voltage and current relationships at all points of the five basic circuits in the Permanent Response (Fourier – Switching Function). Extraction of input - output harmonics and average output value. Transient Response (simulation)

Output/input quality (mains pollution): Calculation of Power Factor, Distortion Factor, THD, Generation of input-output Frequency Spectrum.

Applications

Limited presentation of applications in Photovoltaic and wind turbine systems, FACTS

New Trends:

Description of new trends and new systems in Power Electronics

Course Purpose and Objectives

Students will integrate in this course the necessary theoretical and practical knowledge around the various phases in designing and implementing high performance digital image integration systems with design automation tools. This will be accomplished through ​​ a combination of lectures, exercises and workshops.

Learning Outcomes

Acquire comprehensive knowledge of the basics of image processing, analysis, compression, transfer and segmentation, for 2D and 3D digital signals (image and video). Design and analysis of 2D digital image filters.

Prerequisites

ΕΕΝ 318 – Digital Signal Processing

Course Content

The course is based on the basic elements of digital signal processing and analysis offered in the prerequisite course and has as its main objectives:

• Introduction to the basics of 1-dimensional and 2-dimensional digital signal theory and methods (image and video)
• use of programming in Python/Open CV environments to implement and design integrated systems for image analysis.
• gain full-time experience in the process of editing and analyzing digital image analysis systems using a computer, through laboratory exercises
• Upon completion of the course, students will be expected to have a good knowledge of 2-D signal analysis and processing, the basic concepts and application areas of digital image processing, to understand the operation of basic multimedia image coding standards and to be able to use their programming experience for the development of image and video editing programs. Also be able to use image processing algorithms and appropriate techniques to solve specific problems.

The following chapters are covered:

1. Course introduction: Recovery, storage, transfer, image editing. Image illustration geometry

2. Binary Image Processing

3. Image Histogram and Point Functions

4. Discrete Fourier Image Transformation

5. Linear Image Filtering and Image Transformations,

6. Nonlinear Picture Filtering

7. Image Compression, JPEG, PACS: Image Encoding, Compression Templates (MP3, JPEG, JPEG2000 etc.)

8. Image Analysis I: Image correction and segmentation, edge detection.

9. Image Analysis II and Introduction to Digital Video Editing

Course Objective

For the students to assimilate the necessary theoretical knowledge about the two basic renewable energy technologies related to Photovoltaics and Wind Turbines.

Learning results

Acquiring comprehensive knowledge about the analysis, specification, operation, design and implementation of Photovoltaic and Wind Turbine systems.

Course Content

Photovoltaic Power Plants and Installations

Conversion of Electrical Energy into Electricity - the photovoltaic effect, Photovoltaic Frames, electrical characteristics, Photovoltaic Arrays, Photovoltaic Parks, electronic devices and MPPT.

Wind Farms and Facilities

Wind Power, wind turbines, types, maximum power output, electronics and MPPT.

Electric machines

Alternating Current Electric Machines

Generation of Alternating Sine Voltage

Modern Generators-Construction Elements

Operating Principle- Modern Speed

Induced Voltage- Output Power

Equivalent Circuits

Synchronous Generator Parameters

Autonomous Mode of Synchronous Generator

Maximum Power

Operation of Generator Connected to Infinite Balance

Parallel Generators - Load Sharing Induced Voltage and Power Regulation

Solar energy – general features

Solar-thermal Power Plants – types of systems, simple thermodynamic cycles (S. Kalogirou)

Energy Storage:

Electric Accumulators, Supercapacitors, Flywheels, Pneumatic, Hydroelectric systems.

Course Purpose and Objectives

First introduction in the technological field of wireless communications

Learning Outcomes

Basic knowledge in the technological field of wireless communications

Course Content

Wireless communications is considered as one of the fastest growing technologies. A series of wireless communication systems, and in particular cellular systems, have had a dramatic influence in shaping the society of today. In the near future, new systems like wireless ad-hoc networks, wireless sensor networks and the Internet of Things are expected to have a significant impact on our daily lives. This course is a first introduction in the technological field of wireless communications. The course will cover a wide range of subjects including the basic principles, design and performance analysis of cellular systems, the modeling of radio propagation in the wireless channel and multiple access techniques (FDMA, TDMA, CDMA). Emphasis will be placed not so much on the description of the different technologies, but to the basic principles that are expected to continue to hold in the (relatively) distant future.

Multi-rate digital signal processing, Least squares method for system modeling and filter design, Forward and backward linear prediction, AR, MA and ARMA modeling, inverse systems and deconvolution, Weiner filters.

Course Purpose and Objectives

Design and performance analysis of the major parts of a modern digital communication system

Learning Outcomes

Basic knowledge in the design and performance analysis of the major parts of a modern digital communication system

Prerequisites

Undergraduate classes in telecommunication systems, signals and systems and probability theory

Course Content

The course covers the design and performance analysis of the major parts of a modern digital communication system. It also discusses some fundamental limits for transmission of digital information over noisy channels. The following topics will be covered: digital modulation schemes, performance analysis of digital communication systems in the presence of noise, optimum signal detection and optimum receivers for AWGN channels, source encoding and channel capacity, and error correcting codes.

Course Purpose and Objectives

This course extends the into the area of electric power systems based on the courses EEN 442. It focuses on the monitoring, control, and operation of electric power systems.

Learning Outcomes

On completion of this course, students should be able to:

• Understand the basic operational principles for optimal control of modern electric power systems
• Be familiar with the problems and solutions concerning the uncertainty in the sources and loads of the system.
• Be able to resolve and analyse basic operational and optimisation problems on real-life systems.

Prerequisites

Power Systems II

Course Content

The course includes:

• Control centre structure (data acquisition, SCADA, RTU, PMU)
• Reliability of electric power systems
• Automatic Generation Control
• Introduction to state estimation
• Unit commitment, economic dispatch
• Smart grid technologies

Τhe course aims to:

- Develop familiarity with Discrete Fourier Series. 

- Develop the mathematical skills for using the discrete Fourier transform and familiarization with its applications. 

- Develop evaluation and critical understanding capabilities of finite and infinite (FIR and IIR) digital response filter design methods. 

The students will be able to use digital signal processing methodologies in real problems. 

The students will gain the necessary theoretical and practical knowledge about the various phases in designing and implementing high-performance digital integrated systems with design automation tools and material description languages, through a combination of lectures, exercises and workshops. 

Upon completion of the course, students are expected to have a good knowledge of 2-D signal, the basic concepts and application areas of digital image processing, to understand the operation of basic multimedia image coding standards, and to be able to use their programming experience to the development of video and video editing programs. They will also be able to use image editing algorithms and appropriate techniques to solve specific problems. 

The goals of this course are:

• To familiarize students with advanced methods for modeling signal processing systems.
• The consolidation of the theoretical background and the appropriate use of filters.
• Learn propulsion and back linear forecasting techniques.
• Learn the methods of calculating the adaptive filter output.
• Comparative evaluation of power spectrum methods.

Students will be able to apply advanced digital signal processing methodologies to the solution of a wide range of real-world problems encountered in software applications and electronic systems.

Course Purpose and Objectives

To give a broad knowledge as to basic concepts of linear algebra in relation to matrices and solutions of linear systems as well as basic complex analysis, which can become tools of better understanding and solving related engineering applications.

Learning Outcomes

Acquisition of additional significant background for use in engineering applications.

Course Content

Matrix algebra: definitions, properties, special matrices, Determinants, Sarrus rule, cofactors, row reduction, Inverse matrix, systems of matrix equations, Systems of linear equations, Cramer’s rule, Gaussian reduction, matrix method, Vectors: definitions, properties, Linear spaces: subspaces, linear Independence, basis, rank and nullity, Linear transformations, The eigenvalue problem: eigenvalues, eigenvectors, quadratic forms, Linear algebra applications, Singular value decomposition, Complex numbers: algebra, geometry, coordinate systems, Complex functions: definitions, limits, differentiation, power series functions, integration, Contour integrals, residuals

Module Description

The course provides a broad and systematic introduction to the basic principles and advanced concepts of Probability Theory and Random Processes, with particular emphasis on the tools and applications needed in the field of Electrical Engineering and Computer Engineering and Informatics. 

Learning Outcomes

• Understand and apply Probability Theory concepts to solve practical and theoretical engineering problems 
• Use of theoretical tools to explore the properties of random variables
• Analysis of random processes and their application in many different areas such as signal processing in communication  systems, study of system reliability, automatic control, etc.

Module Description

Topics covered:

1. Basic concepts-probability axioms,  Introduction, Sample Space, Events, Acts with Facts, Mathematical Probability, Probability Axioms, Conditional Probability, Independence
2. One-dimensional Random Variables, Random variables, Distribution function, Discrete random     variables, continuous random variables, functions of random variables, mean value, dispersion
3. Important Random Variables and their Properties, Discrete Distributions: Bernoulli, Binomial, Poisson, Geometric, Hyper-geometric, Continuous Distributions: Uniform, Normal, Exponential,     Gamma,  Central Limit Theorem
4. Multidimensional Random Variables,  Two-dimensional random variables, covariance and correlation   coefficient
5. Conditional probabilities and independent random variables
6. Introduction to stochastic processes,   Random Signals, Mean Correlation and auto-covariance Functions. Poisson's process 
7.  Autocorrelation and power spectrum Power spectral density. Gauss stochastic process. Noise: Shot Noise, Thermal Noise, White Noise
8.  Response of linear systems to stochastic inputs

Course Purpose and Objectives

Introduction to the basic laws governing Electric and Magnetic Power. The course focuses on the concepts of Electricity, Magnetism, Electromagnetism in order to understand the creation and effect of electromagnetic fields and their related phenomena. In addition, it provides the basic elements of electromagnetic waves focusing on optics.

Learning Outcomes

In-depth knowledge of electromagnetism and optics.

Course Content

Electromagnetism and Optics. Electric fields, Coulomb's law, Gauss's law. Electrical potential, capacitors, dielectrics, current and resistance. Constant current circuits. Magnetic fields, magnetic field sources. The laws of Biot and Savart and of the Ampere. Faraday's Induction Law. Induction, AC circuits. Maxwell equations and electromagnetic waves. The nature of light and the geometric view. Lenses and reflectors. Contribution, diffraction and polarization of light.

Course Purpose and Objectives

Understanding the basic principles of Quantum Mechanics. Knowledge of applications in Quantum Mechanics.

Learning Outcomes

Basic knowledge of Quantum Mechanics.

Course Content

Essential elements of Atomic Physics and Optics, which led us to the threshold of Quantum Mechanics. The experiment of the two holes. The paradox of the observer's influence. Heisenberg Uncertainty Principle. The Schrödinger equation and the wave function. Statistical interpretation, wave function normalization. Position / momentum operators and Hamiltonian. Solutions of the Schrödinger equation for the following one-dimensional dynamics: Uninterrupted Well, Harmonic Oscillator, Free Particle, Delta Function, Finite Well. Scrambled states and scatter states. Transmission and reflection factors. Tunneling phenomenon. The hydrogen atom. Spin 1/2. Quantum Computer.

Course Purpose and Objectives

LCE 113 is a three-hour per week course, particularly designed to support Electrical Engineering Computer engineering and Informatics students’ studies. Its general objective is to enable students to communicate competently at a B1-B2 level of the Common European Framework of Reference (CEFR) for Languages on issues related to students’ social and student life (university, curriculum, field of study), as well as on issues related to their future professional careers (occupations, short CV, etc.). Computer Assisted Language Learning (CALL) and culture awareness development are done through communicative situations deriving from authentic-like communication situations students may experience in their lives, during their studies and professional careers. Language competence is acquired through the use of text types, scenarios, and roles which promote the production and understanding of spoken and written language related to the topics covered.The course is based on post communicative era method, a student-centered, blended learning approach, and aims to familiarize students with authentic reading material related (a) to general topics such as university student life, learning styles and language learning, (b) to academic topics such as how to study effectively, take notes and use the appropriate reference style and (c) to specific topics related to the field of Electrical Engineering Computer engineering and Informatics. This material is used to develop students’ skills in text comprehension and analysis, note taking and processing as well as acquaint students with writing styles, such as process, description and argumentation. It also develops students’ listening and speaking skills. Learners are expected in this way to develop their speaking and listening abilities by taking an active part in tasks such as dialogues, conversations, and oral presentations based on real life situations related to their academic and professional environments. The course is based on current learning theories, such as constructivism and social constructivism, and it aims at developing students’ language skills, as well as transferrable 21st century skills, such as communication, digital literacy, collaboration, creativity, innovation, critical thinking, intercultural awareness, autonomy and lifelong learning.

Learning Outcomes

1. Students will develop their language skills through communicative circumstances, scenarios and roles based on authentic situations of their social and student life (university, directions for access to university premises/buildings, field of study), as well as issues related to their future professional careers (workplace, potential professions, duties, and Electrical Engineer’s CV. Furthermore, students will also be able to communicate competently at a B1-B2 CEFR level (production and understanding of spoken and written language) on the aforementioned topics, through relevant and related text types, scenarios, and roles and for specific purposes
2. Students  will use grammatical structures i.e. tenses, syntax, relevant to topics and communication tasks in order to ddemonstrate awareness of the writing process and be able to produce coherent and grammatically correct language at various levels (from paragraph to more extended texts)
3. Students will write texts of different types (reports, summaries) and rhetoric styles (description, process) at an academic level, 
4. develop the ability to paraphrase, summarise, quote and avoid plagiarism.
5. Students will demonstrate their ability to listen and comprehend conversations, interviews, lectures and public speeches in order to identify the main points and respond appropriately by collecting and evaluating information from various sources (e.g. internet) before using it to support an argument in various forms of communication such as report writing, presentations etc.
6. Students will communicate effectively with the use of information and communication technologies. Students will also be able to demonstrate creativity, critical thinking and intercultural awareness though language use by applying 21st century skills, such as communication, digital literacy, collaboration, creativity, innovation, critical thinking, intercultural and global awareness and active citizenship, autonomy and lifelong learning.

Course Content

• Studying Electrical Εngineering- skills and competencies
• The Cyprus University of Technology – Identity/ Profile
• University student digital profile
• Careers in Electrical and Computer engineering
• How do we study best? Academic skills development
• Digital literacy
• The Information age
• Computer users
• Graphical User Interfaces
• Multimedia
• Networks
• The World Wide Web
• Communications systems
• Robotics
• Software Engineering
• Academic Articles in Electrical and Computer engineering
• Bibliographic references, paraphrasing and avoiding plagiarism
• Academic Skills: learning styles, text types, rhetorical modes, title types, introduction, paragraph and conclusion writing, cohesion, coherence & clarity,
• Library skills: bibliographical references, paraphrasing, summary, avoiding plagiarism
• Dictionary (monolingual, bilingual) skills

Course Purpose

LCE 114 is the second part of a three-hour per week course, particularly designed to support Electrical Engineering students’ studies. Its general objective is to enable students to communicate competently at a B1-B2 level of the Common European Framework of Reference (CEFR) for Languages on issues related to students’ social and student life (university, curriculum, field of study), as well as on issues related to their future professional careers (occupations, short CV, etc.). Computer Assisted Language Learning (CALL) and culture awareness development are done through communicative situations deriving from authentic-like communication situations students may experience in their lives, during their studies and professional careers. Language competence is acquired through the use of text types, scenarios, and roles which promote the production and understanding of spoken and written language related to the topics covered.

The course is based on post communicative era method, a student-centered, blended learning approach, and aims to familiarize students with authentic reading material related (a) to general topics such as university student life, learning styles and language learning, (b) to academic topics such as how to study effectively, take notes and use the appropriate reference style and (c) to specific topics related to the field of Electrical Engineering Computer engineering and Informatics. This material is used to develop students’ skills in text comprehension and analysis, note taking and processing as well as acquaint students with writing styles, such as process, description and argumentation. It also develops students’ listening and speaking skills. Learners are expected in this way to develop their speaking and listening abilities by taking an active part in tasks such as dialogues, conversations, and oral presentations based on real life situations related to their academic and professional environments. The course is based on current learning theories, such as constructivism and social constructivism, and it aims at developing students’ language skills, as well as transferrable 21st century skills, such as communication, digital literacy, collaboration, creativity, innovation, critical thinking, intercultural awareness, autonomy and lifelong learning.

Learning Outcomes

• Develop their language skills through communicative circumstances, scenarios and roles based on authentic situations of their social and student life (university, directions for access to university premises/buildings, field of study), as well as issues related to their future professional careers (workplace, potential professions and duties) and are  able to communicate competently at a B1-B2 CEFR level (production and understanding of spoken and written language) on the aforementioned topics, through relevant and related text types, scenarios, and roles and for specific purposes
• Produce coherent and grammatically correct language at various levels (from paragraph to more extended texts)  and are able to write texts of different types e.g. (reports, summaries) and rhetoric styles (description, process) at academic level.
• Collect and evaluate information from various sources (e.g. internet) before using it to support an argument in various forms of communication such as report writing, presentations etc.
• Communicate effectively with the use of information and communication technologies
• Demonstrate creativity, critical thinking and intercultural awareness though language use and apply 21st century skills, such as communication, digital literacy, collaboration, creativity, innovation, critical thinking, intercultural and global awareness and active citizenship, autonomy and lifelong learning

Prerequisites

LCE 113

Course Content

Studying Electrical and Computer engineering- skills and competencies

•     University student digital profile

•     Digital literacy

•     Electrical Power Generation and transmission and distribution

•     Signal Processing

•     Communications systems

• Signal Processing
• MEMS
• Virtual Reality

•     Academic Articles and academic writing for Electrical Engineers

•     Bibliographic references, paraphrasing and avoiding plagiarism

•     Academic Skills: learning styles, text types, rhetorical modes, title types, introduction, paragraph and conclusion writing, cohesion, coherence & clarity,

•     Library skills: bibliographical references, paraphrasing, summary, avoiding plagiarism

• Dictionary (monolingual, bilingual) skills

KCL and KVL node and mesh methods. Ideal and non-ideal sources. Thevenin and Norton equivalent circuits. Maximum Power Transfer Theorem. Transient analysis of first and second order circuits. Null input and state response. Sinusoidal steady state and power. Coordination. Balanced three-phase systems. Introduction to the Laplace transform.

Course Objectives

It will help Electrical Engineers to understand the basic principles of business management such as modern management methods, leadership, work organization, teamwork, management and quality systems, human resource utilization.

Additionally, the main purpose of the course is to provide students with knowledge about the structure, processes and financial management of business organizations as well as the rational understanding of the economic and social environment in which these businesses operate.

Learning results

Upon successful completion of the course, students will be able to:

1. Understand the basic principles of Management, Finance and the role of the Engineer. Recall the main terminologies, meanings and considerations of the economic and social business environment, the main scientific theories of management, the management of human resources, teamwork, leadership, and the management of the company's finances. 2. Know what standardization, certification, EU directives are and the importance of standards in Engineering. 3. Identify the main activities and what affects them, the options they have and be able to interpret how these can affect the efficiency and effectiveness of the business. Study and understand the basic financial characteristics of an investment and learn investment evaluation methods. 4. Discuss, using appropriate terminology and vocabulary, issues related to management, financial management and business behavior in engineering organizations. 5. Distinguish the different styles of financial management and recognize how they will contribute positively to effective management. 6. Give effective recommendations in solving specific administrative, financial and business problems taking into account the requirements of sustainability and corporate responsibility. 7. Understand and manage simple financial matters and calculations.

Course Content

Origin and development of modern management and modern business organization, Total Quality Management, Standardization and certification, Leadership, Economic management, Business environment, Investment plans and timing, Key features of investments, Financing, Equity capital, Reserve funds, Business Venture capital, Foreign and outside financing, Undertaking of merchandise receivables FACTORING, Forfaiting, Concession – Franchising, Cash flow– time relationship and equivalence, Applications of cash flow and time relationships, Price changes inflation, Risk Management, Business and corporate liability, Tax issues.

Course Objective

For students to assimilate the necessary theoretical and practical knowledge around the various phases in the design and implementation of digital integrated systems with high performance requirements with design automation tools and hardware description languages, through a combination of lectures, exercises and workshops.

Learning results

Gain comprehensive knowledge around the analysis, specification, operation, design and implementation of very large scale integration (VLSI) digital integrated systems with high performance requirements, with design automation tools and hardware description languages. It also offers an introductory refresher on basic digital logic concepts.

Course Content

The course builds on the fundamentals of logic circuit design offered in the prerequisite course and has as its main objectives:

• the introduction to the design of combinational and sequential digital circuits
• the use of the Verilog hardware description language for their modeling and simulation as well as their implementation
• the implementation of digital systems in programmable logic devices (CPLDs and FPGAs)
• the study of the different types of memory used in computer systems
• gaining experience in the full cycle of the process of designing, simulating and implementing digital systems using modern computer tools through laboratory exercises

The following sections-chapters are covered:

1. Logic gates, memory elements, combinational logic
2. Two-level/multi-level implementation of logic functions, Combinational circuits (multiplexers, encoders, decoders), numerical combinational circuits (fast adders, multipliers, dividers, sliders)
3. Sequential logic (registers, latches)
4. Serial circuits (counters, shift registers, parallel load registers)
5. Finite State Machines (FSMs).
6. Verilog language (basics, behavioral, register transfer layer, structured code style)
7. Representation of combinational circuits in Verilog
8. Representing sequential circuits in Verilog
9. Advanced Logic Design
10. Design digital circuits with schematic input
11. FPGA/ASIC Design Flow
12. Design Automation Tools
13. Simulation and verification of logic circuits (Verilog testbenches)
14. Logical Synthesis of combinational and sequential circuits
15. Placement and Routing
16. Error models
17. BJT and MOSFET models as switches
18. CMOS implementation, VLSI layout, stick diagrams
19. Redefining architectures, FPGA technology.
20. Integrated circuit technologies
21. Clocks, delays, distribution networks, synchronization, metastability issues
22. SRAM, DRAM, Buses
23. Piping, parallelism, performance gain

Course Purpose and Objectives

This course extends into the field of electric power systems based on the course EEN 320. It focuses on the use of computational methods for the analysis of electric power systems in steady-state as well as during symmetrical and asymmetrical faults.

Learning Outcomes

On completion of this course, students should be able to:

• Understand the fundamental computational methods to analyse the steady-state and under-fault operation of electric power systems.
• Have a basic understanding on the protection selection.

Prerequisites

Introduction to Electric Power Systems

Course Content

The course includes:

• Power system modelling
• Bus admittance matrix
• Power flow analysis
• Three-phase short circuit analysis
• Symmetrical components
• Asymmetrical fault analysis

Course Objective

Understanding and defining embedded systems. Understanding the challenges and issues in designing embedded computing systems. Development of embedded systems design methodology. Understanding of design and operation of embedded systems, at the level of software - hardware - systems architecture. Design with Verilog hardware description languages. High Abstraction Level Logic Synthesis (HLS) and design with C language. FPGA system design methodology. Modern FPGA technology and architecture. System-on-a-Chip Architecture. Embedded Linux for SoC. Hardware/software co-design with examples in compact control, automation and robotics systems.

Learning results

For students to assimilate the necessary theoretical knowledge and practical knowledge around the various phases in the design and implementation of embedded systems with FPGA SoC, through a combination of lectures, exercises and workshops.

Prerequisites

EEN 314, CEI 122

Content

The following sections-chapters are covered:

Introduction to Embedded Systems

FPGA/ASIC Design Methodology

Introduction to hardware description languages ​​and Verilog

Introduction to High Abstraction Logic Synthesis (HLS) with C

Modern FPGA and System-on-a-Chip (SoC) architecture and technology

Case study: Xilinx Zynq

Timing Issues – Synthesis, Placement and Routing in FPGAs

Design methodologies

Specifications, organization, performance analysis, implementation, control

Embedded Processors

Case study: ARM Cortex A9 processor, Hardware and Software

Communication in Embedded Systems

Buses (AMBA bus)

SoC design

Hardware/software sharing and co-design

Systems Reuse (IP)

Hardware and Software optimization process and techniques

Embedded Linux for SoC

Case study: PetaLinux

Multi-rate ψηφιακή επεξεργασία σημάτων, Μέθοδος ελαχίστων τετραγώνων για μοντελοποίηση συστημάτων και σχεδιασμό φίλτρων, Forward and backward linear prediction, μοντελοποίηση AR, MA και ARMA, αντίστροφα συστήματα και deconvolution, Φίλτρα Weiner.