Εξάμηνο: 7th semester

In the 7th semester, students beyond the final year project shall choose one (of the two) compulsory courses of the secondary major (CSM) of the (main) Major that they have chosen and three optional courses (Opt) through the list of the available courses of all majors.

Systems Interoperability

Learning Outcomes

The course’s material includes the basic concepts related to system interoperability, and international standards and initiatives on system interoperability. The European Interoperability Framework is analyzed and crrent technologies / standards / standards / specifications are presented for different domains (indicative: eGovernment, eProcurement, eInvoicing, eHealth).

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

  • Explain the key concepts related to system interoperability.
  • Explain the basic principles of the European Interoperability Framework.
  • Apply design methodology for interoperable digital services.
  • Evaluate and select the appropriate specifications to ensure interoperability of systems in various eGovernment domains.

Course Contents

  • Introduction to systems interoperability
  • Basic principles, definitions and benefits
  • Main approaches and requirements
  • International Standards and Initiatives
  • European Interoperability Framework
  • Interoperability at organizational, semantic and technical level
  • Methodology for designing interoperable digital services
  • Interoperable public services
  • Interoperability in eProcurement
  • Interoperability in eInvoicing
  • Interoperability in eHealth

Recommended Readings

  • Notes and course slides
  • Papers

Short Range Wireless Networks

Learning Outcomes

The objective of this course is to focus on short range communications with emphasis on wireless local area networks (WiFi), adhoc networks, wireless sensor networks and applications.

At the end of this course, students will have acquired advanced/in depth knowledge in the field of Short Range Communications, with particular emphasis on baseband processing physical layer techniques, and Medium Access Control design.

The students will be capable of performing numerical calculations of various wireless parameters, stochastic modelling of wireless transceivers and performance assessment by means of analytical evaluations and simulations. The students will also be capable of comprehending the design principle of Wireless Local Area Networks and Wireless Sensor Networks of Internet of Things applications.

Course Contents

  • WiFi techniques, technologies, protocols and standards.
  • Short range communications: Personal Area Networks (PAN), Body Area Networks (BAN), Ultra Wide Band communications.
  • AdHoc Networks: Physical layer and transceiver design, MAC layer design, connectivity, topologies and routing.
  • Wireless Sensor Networks: Information-theoretic bounds on sensor network performance, detection and estimation, cooperative transmission, localization and positioning, energy efficiency.
  • Applications: eCommerce, safety, digital home, eHealth.

Recommended Readings

  • Behrouz A. Forouzan, “Data Communications and Networking”, Fourth edition, McGraw-Hill, 2007.
  • W Stallings, Wireless Communciations and Networks, Pearson, 2004.
  • D. Tse, P. Viswanath, Fundamentals of Wireless Communciations, 2005.
  • T. S. Rappaport, Wireless communications – Principles and practices, Pearson, 2002.
  • Swami A. (Ed.) (2007): Wireless Sensor Networks: Signal Processing and Communications, John Wiley and Sons.
  • Kraemer R. & Katz M. (2008): Short-range wireless communications: Emerging technologies and applications, Wiley.
  • Andrea Goldsmith, Wireless Communications, Cambridge University Press, 2005.

Development of Telecommunication Systems

Learning Outcomes

The aim of this course is to familiarize students with best practices for the design and implementation of modern innovative telecom systems and applications. The main topics discussed include systematic multi-criteria requirement analysis, transformation of user requirements to architectural specifications and system functionality, design optimization for high performance and QoS, installation and deployment procedures, as well as system validation against initial requirements and specifications. The presented methodologies derive analytically from real case studies of innovative telecommunication systems and applications with extremely high added value and impact (e.g. the European Space Agency SATWAYS project in the field of Air Traffic Control). Students will further gain significant practical experience in the design and implementation of innovative telecommunication systems through exercise solving and development of small projects. Last but not least, the course presents an in-depth commercial feasibility analysis of the developed systems.

At the end of the course, students will be equipped with advanced expert and analytical knowledge for the consistent design, development and validation of innovative embedded telecommunication systems (see Course Content) meeting strict quality requirements regarding the provided telecommunication services. The obtained knowledge will allow the critical and analytical deepening as well as performing innovative research in the broad scientific domain of embedded telecommunication systems and applications.

Students will be capable of:

  • transforming user requirements to telecommunication systems architectural specifications and functionality.
  • specifying prototype embedded telecommunication systems, including their architectural layering (hardware, embedded software, software), according to specific QoS requirements for the provided services.
  • designing and specifying modern voice communication systems for next generation networks.
  • designing QoS models involving the end-to-end telecommunication transmission path from service provisioning to the end user, as well as extracting performance requirements and specifications for segments of the end-to-end transmission path.
  • optimizing the design of telecommunication systems for high performance and QoS.
  • explaining the details of the E-model adaptation and simplification of the discrete noise and advantage parameters in the demanding field of radio voice communications. The E-model (ITU-T Rec. G.107) is a transmission planning tool that provides a prediction of the expected voice quality, as perceived by a typical telephone user, for a complete end-to-end (i.e. mouth-to-ear) telephone connection under conversational conditions.
  • exploiting and solving the adapted voice QoS model for extracting system performance design parameters (e.g. for selecting appropriate voice codecs assuming a limited end-to-end delay and the constant values of delay parameters along the telecommunication transmission path segments).
  • compiling detailed plans for technical validation of system deliverables against the initial user requirements and system specifications.
  • analyzing the satellite link budget for the provisioning of telecommunication services and extracting requirements regarding the underlying telecommunication system.
  • analyzing the installation, deployment and operational details of the developed systems.
  • compiling workplans, work packages, time schedules, lists of technical deliverables and reports, critical paths, milestones and sample budgets involving R&D projects that design and develop innovative embedded telecommunication systems.
  • performing indicative techno-economic studies and commercial feasibility analysis regarding innovative embedded telecommunication systems, including a SWOT analysis (strengths, weaknesses, opportunities, threats).

Course Contents

  • Exemplary Innovative telecommunication systems and applications with high added value and impact.
  • Systematic multi-criteria requirement analysis.
  • Transformation of user requirements to architectural specifications and system functionality.
  • Design optimization for high performance and QoS.
  • Adaptation and validation of the E-model in the radio communications use case, including satellite transmission. The E-model (ITU-T Rec. G.107) is a transmission planning tool that provides a prediction of the expected voice quality, as perceived by a typical telephone user, for a complete end-to-end (i.e. mouth-to-ear) telephone connection under conversational conditions.
  • Exploitation of the voice QoS model for extracting system performance design parameters (e.g. for selecting appropriate voice codecs assuming a limited end-to-end delay and the constant values of delay parameters along the telecommunication transmission path segments).
  • Voice communications based on the NGN (Next Generation Network) standard.
  • Installation procedures and relevant issues.
  • System validation against initial requirements and specifications.
  • Commercial feasibility analysis.
  • Exercises and programming projects.

Recommended Readings

  • Apostolacos S. & Meliones Α. (2014): Satellite IP Radio Communications in Air Traffic Control: Design, Implementation and Evaluation of Telecommunication Systems (in Greek).
  • S. Apostolacos, A. Meliones, S. Badessi, G. Stassinopoulos, “Adaptation of the E-model for satellite internet protocol radio calls in Air Traffic Control”, IEEE Transactions on Aerospace and Electronic Systems, 50(1), January 2015.
  • S. Apostolacos, M. Manousos, A. Meliones, D. Kavadas, G. Lykakis, A. Manousarides, M. Kardaris, K. Simeakis, Design and Implementation of a Solution for the Provisioning of Converged Remote Tower and Facility Management Services over Satellite IP for Greek Heliports, IEEE Communications Magazine, 46(8), August 2008.

Pattern Recognition

Learning Outcomes

Pattern recognition is the scientific field that deals with the assignment of a label to a given input value. An example of pattern recognition is classification, which attempts to assign each input value to one of a given set of classes. The course aims to cover the most popular in the literature techniques for pattern recognition, as they are typically employed in a number of practical applications, such as speech and audio recognition, image and video analysis, biometrics and bioinformatics. The course covers the most commonly used classification algorithms, feature selection techniques, data transformation methods, and data clustering.

Students, upon successful completion of the course, will be able to:

A) Understand the key standards recognition methodologies

B) Analyze problems in various areas of application, such as voice and audio recognition, image and video analysis, biometrics and bioinformatics.

C) Choose the best classifiers, feature selection methods, data transformations, and clustering.

D) Evaluate standard pattern recognition systems

 

Course Contents

  • Introduction to Pattern recognition systems
  • Parametric estimation of probability density function (maximum Likelihood estimation, maximum a posteriori
  • Bayesian classifiers and Bayesian Networks
  • k-nearest neighbor
  • Non parametric estimation of probability density function (Parzen windows)
  • Linear classifiers, non linear classifiers. Perceptron algorithm. Multilayer neural networks, Deep Learning
  • Unsupervised Pattern recognition – Clustering
  • Feature generation: contour representation and contour tracing, chain code, polygon, signatures, linear transforms, Fourier Transform, regional features, image recognition, bias and variance, texture
  • Feature Selection and Kernels
  • Pattern recognition tools

Recommended Readings

  • Sergios Theodoridis and Konstantinos Koutroumbas. 2008. Pattern Recognition, Fourth Edition (4th ed.). Academic Press

Algorithms for Electronic Markets

Learning Outcomes

The course’s material includes the theory and practice that pertain to the design of economic mechanisms for automated trade exchanges, in modern digital platforms (auction websites, services provision and products retail websites, internet advertisement platforms). In particular, the course concerns the modern algorithmic techniques that facilitate the digital implementation of electronic markets.

Upon successful completion of the course, the students will be in position:

  • to understand the economic and algorithmic background that underlies the functionality of electronic markets.
  • to design electronic trade exchanges platforms, by choosing the appropriate economic mechanisms and the relevant algorithmic implementations.
  • to assess and evaluate the performance of economic mechanisms and their algorithmic implementations, relative to a given electronic market and its particulars.
  • to design, implement and evaluate automated pricing mechanisms.

Course Contents

  • Introduction to Game Theory: Strategies, Utility Functions
  • Strategic Games and Nash Equilibrium
  • Efficiency of Equilibria
  • Oligopoly Models
  • Auctions: First-Price, Second-Price, Multi-Unit Formats
  • Algorithmic Mechanism Design
  •  Sponsored Search Auctions
  • Combinatorial Auctions
  • Principles and Methods of Pricing
  • Prediction Techniques
  • Online Auctions

Recommended Readings

  • N. Nisan, T. Roughgarden, E. Tardos, V. Vazirani. Algorithmic Game Theory. Cambridge University Press, 2006.
  • T. Roughgarden. Twenty Lectures on Algorithmic Game Theory. Cambridge University Press, 2016.
  • M. J. Osborne. An Introduction to Game Theory. Oxford University Press, 2009.
  • R. Gibbons. A Primer in Game Theory. Financial Times / Prentice Hall, 1992.