Students can choose it only once during undergraduate studies (either the 7th or the 8th semester).
The purpose of the course is to highlight the necessity of a high-level framework, for the protection of personally identifiable information (PII) within information and communication technology (ICT) systems, general in nature, placing organizational, technical, and procedural aspects in an overall privacy framework. The privacy framework, according to ISO/IEC 29100:2011 and ISO/IEC 29101:2018, is intended to support organizations define their privacy safeguarding requirements related to PII within an ICT environment by defining the actors and their roles in processing PII, describing privacy safeguarding requirements, and referencing known privacy principles. According to ISO/IEC 2913:2017, guidelines are providing for conducting a Privacy Impact Assessment (PIA) as an instrument for assessing the potential impacts on privacy of a process, information system, program, software module, device, which processes PII. Privacy-by-Design critical issues are introduced. Moreover, privacy protection issues in cloud environments are described in detail, according to ISO/IEC 27018:2014.
In this context, the learning outcomes of the course, after its successful completion, are that the students will be able:
- to understand the basic concepts of privacy framework as well as how to recognize and analyze privacy requirements
- to realize the Privacy-By-Design principle
- to conduct a study for Privacy Impact Assessment
- to understand and deal with privacy protection issues in cloud environments.
- Privacy protection: Technical, legal, regulation, and ethical issues
- Privacy framework according to ISO/IEC 29100:2011 and ISO/IEC 29101:2018
- Privacy by Design critical issues
- Privacy Impact Assessment according to ISO/IEC 29134:2017
- Privacy protection countermeasures according to ISO/IEC 27701:2019
- Cloud computing and related Privacy protection issues according to ISO 27018:2014
- GDPR and ISO 27001 synergies of activities towards organization’s compliance
- Case study: Privacy in social media
- Lambrinoudakis, L. Mitrou, S. Gritzalis, S. Katsikas (2010), Privacy Protection and Information and Communication Technologies (Eds.), Papasotiriou Pubs. (in Greek)
- Acquisti, S. Gritzalis, C. Lambrinoudakis, S. De Capitani di Vimercati (Eds) (2008) Digital Privacy, Theory, Technology and Practices, Auerbach Publications.
- Tamo-Larrieux (2018), Designing for Privacy and its Legal Framework: Data Protection by Design and Default for the Internet of Things, Springer
- van der Sloot, A. de Groot, (2018) The Handbook of Privacy Studies, Amsterdam University Press
- ISO/IEC 29100:2011 Information Technology – Security Techniques – Privacy Framework
- ISO/IEC 29134:2017 Information Technology — Security Techniques — Guidelines for Privacy Impact Assessment
- ISO/IEC 27701:2019 Information Technology – Security Techniques – Extension to ISO 27002:2013 for Privacy Information Management – Requirements and Guidelines
- ISO/IEC 27018:2014 Information technology — Security techniques — Code of practice for protection of personally identifiable information (PII) in public clouds acting as PII processors
With the completion of the course, the student will be able:
- to know and understand the key concepts of exploiting digital technologies in teaching, learning and assessment of learning in K12 School Education.
- to analyse, assess, select and justify a pedagogically appropriate educational technologies to support different teaching strategies in K12 School Education.
- to design and create pedagogically grounded technology-supported teaching and learning scenarios for the K12 education.
The learning objectives of the course are aligned to the Greek State qualification framework for a teaching licence in K12 school education.
- 1. Technology-Supported and Technology-Enhanced Teaching and Learning in School Education: Theoretical Underpinnings
- 2. Integrating Technology in School Education (teaching, learning and assessment of learning): Models and Practice
- 3. Taxonomy of Educational Technologies in School Education
- 4. Educational Technologies for supporting different teaching and learning strategies
- 4.1. Tutorials
- 4.2. Drill and Practice
- 4.3. Problem solving
- 4.4. Modeling
- 4.5. Virtual Labs and Simulations
- 4.6. Inquiry-based Learning
- 4.7. Collaborative Learning
- 4.8. Assessment of Learning
- o 4.9. Educational Games
- 5. Digital School Infrastructure
- 5.1. Interactive Boards
- 5.2. ICT School Laboratory
- Textbook in Greek (provided for free)
- Additional Open Access Educational Resources available through the course management system
|The course is introducing students in telemedicine systems and applications that improve the quality of life and provide remote electronic health services. The curriculum includes background knowledge in the areas of coding and processing of biomedical data, analyzes the design and implementation issues of telemedicine systems and discusses the next generation telemedicine systems, which include context awareness and computational intelligence as additional features. During the course case studies will be presented and there will be project assigned to students.
Students, upon successful completion of the course, will be able to:
A) Understand basic methodologies of design and development of telemedicine systems
B) Be familiar with the main techniques for the coding and processing of biomedical signals and data
C) Know the coding standards for medical information
D) Design telemedicine systems according to special requirements and the type of medical information exchanged
E) Evaluate telemedicine systems
- Introduction to Telemedicine
- Biomedical Data Coding and Compression
- Biomedical Data Processing for Telemedicine Applications
- Video Communication for Telemedicine Applications
- Telemedicine Networks
- Home Care Systems
- Context Aware Telemedicine Systems
- Wireless Telemedicine and Ambient Assisted Living
- Wearable Systems
- Clinical Applications of Telemedicine
- Security in Telemedicine systems
- Case Studies – Project Assignments
- Medical Informatics, e-Health: Fundamentals and Applications (Health Informatics) Softcover reprint of the original 1st ed. 2014 Edition by Alain Venot (Editor), Anita Burgun (Editor), Catherine Quantin (Editor)
- Telemedicine Handbook, Pompidou Alain, Apostolakis I, Α., Ferrer – Roca Olga, Sosa – Iudicissa Marcelo, Allaert Francois, Della Mea Vincenzo, Kastania Anastasia N.
The objective of this course is to familiarize students with: (a) learning access methods for large data volumes for various data formats, as well as scalable writing, (b) efficient data storage and retrieval with appropriate indexing techniques, (c) the design and implementation of data processing algorithms aiming at the development of efficient applications that manage data.
Upon successful completion of the course, the students will be in position:
- to develop data-centric applications with emphasis in efficiency and scalability
- to use the most appropriate indexing methods for a given problem
- to evaluate and improve the parts of data processing algorithms that incur high computational load
- to apply the most suitable data processing techniques that match with data under analysis and for a given query workload
- to develop efficient data processing algorithms
- Operation of disk and main memory, serial and random access, cost and efficiency, data locality on disk and main-memory, direct and indirect access, main-memory data structures (arrays, priority queues, hashing)
- Data access techniques for structured, semi-structured and unstructured data: relational DBs, XML, RDF, text documents, web pages, web APIs, social networks.
- One-dimensional data and indexing, B-tree, variations (B+tree, B*tree), range queries, inverted indexes.
- Spatial data, spatial data types, spatial queries, approximation in representation, distance measures, extensions for multidimensional data.
- Spatial indexing techniques, grid file, spatial indexes (R-tree, QuadTree), space-filling curves (Hilbert, Z-order)
- Similarity search, k-nearest neighbor search, branch-and-bound algorithms, locality sensitive hashing (LSH), approximate k-nearest neighbor.
- Top-k search: algorithms based on pre-processing, online algorithms, Fagin’s algorithm, index-based algorithms.
- Join queries, spatial joins, top-k joins.
- Spatio-textual data, query types, indexing methods, processing algorithms.
- Ramakrishnan R. & Gehrke J. (2002): Database Management Systems (3rd Edition), McGraw Hill.
- N.Mamoulis (2011): Spatial Data Management, Synthesis Lectures on Data Management, Morgan & Claypool.
The course presents principles and methodologies on the design, evaluation and optimization of networks and services, complementing the basic knowledge of architecture, protocols and functions of communication networks.
Upon successful completion of the course, the students will be in position to:
- follow and utilize the approach of top-down network design, that is most commonly encountered on medium to large scale networking projects
- understand and evaluate alternative design options at every stage of data networks design, (e.g. requirement and specification definition, logical and physical design, selection of appropriate technologies and protocols, addressing and naming of network devices, implementation, testing and optimization)
- select and propose proper architectures, network technologies, protocols and politics, depending on the design, upgrade and/or optimization of the network at hand
- implement, control and readjust solutions on new or redesign existing network projects
- run and operate routing protocols simulation software and packet sniffing software
- Introduction to the design and performance evaluation of networks and services.
- Modelling and topological design of communication networks.
- Modelling of network services traffic and work load.
- Top-down network design under service requirements and various constraints.
- Selection of most appropriate link, network and transport layer protocols.
- Selection of most appropriate network architecture and network devices.
- Network optimization techniques and algorithms, network reliability.
- Performance measures.
- Quality of service assurance.
- Theoretical exercises and network design projects.
- Spiros Arsenis, “Network Design and Implementation”, Kleidarithmos Publications.
- Priscilla Oppenheimer, “Top-Down Network Design”, 2nd Edition, Cisco Press.
- James D. McCabe, “Network Analysis, Architecture and Design”, 2nd Edition, Morgan Kaufmann Publishers Inc.
- Thomas Robertazzi, “Planning Telecommunication Networks”, IEEE Press.
The course provides the basic principles of cellular mobile communication systems. It also provides the methodologies of analysis and design of these systems. By concluding the course, students are able to
- analyze and design basic mobile communication systems by emphasizing in physical layer techniques
- recognize, describe and distinguish the characteristics of several type of cells, communication channels and multiple access techniques
- analyze and design systems with different requirements of telecommunication traffic and quality links
- compute the thresholds of link performance,
- compare alternative implementation plans and evaluate the total performance of digital systems
The lab sessions aim to provide a deeper understanding of physical phenomena of propagation in the wireless channel and the simulation of cellular systems.
Initially, basic concepts of Mobile Communications Radiosystems are provided (cell types, communication channel types, basic cellular system operations). Basic Network Access Techniques (Multiple Access Techniques, Random Access Techniques) are discussed. Also, reference is made to the evolution of Wireless Communication Systems (1st, 2nd, 3rd, and 4th generation cellular systems, Wireless Telephony Systems, Paging Systems, WLANs, WPANs, PMRs). Students are introduced to the concept of cells and frequency reuse (elements from regular hexagon geometry, cellular systems design). Then the basic concepts of telecommunication traffic analysis and systems performance is provided (elements of Queuing Theory, Erlang B model, Erlang C model, spectral performance of cellular systems). In the following the main wireless propagation mechanisms are presented (multipath propagation, Doppler fading and shift, propagation loss, shadowing, coverage area definition, radio channel capacity limits). Interference types (co-channel interference and noise, neighboring channel interference) as well as handover and performance techniques (categorization of handover techniques, advantages and disadvantages of techniques, stable performance, dynamic performance, elastic performance) are discussed and compared. Techniques for improving spectral efficiency (sectoring, cell splitting) are then analyzed. Finally, elements and techniques of physical layer design (modulation and coding techniques, co-channel interference mitigation techniques) are presented and a presentation of standardized Mobile Communications Systems (GSM, GPRS, 3G and 4G) is presented.
In addition, extra content (in evdoxos.ds.unipi.gr) like articles, audiovisual lectures and Internet addresses, as well as exercises for student’s practice are posted electronically. Case studies, exemplary problems and methods for solving them are presented.
- “Mobile Communications Systems”, Book code in www.eudoxus.gr: 33154041, Edition: 2nd edition/2013, Authors: Kanatas Athanasios, Pantos Georgios, Costantinou Filippos, ISBN: 978-960-491-086-1, Publisher: A.Papasotiriou & Sia (1st Book)
- “Antennas and propagation for wireless communication systems”, Book code in www.eudoxus.gr: 59386401, Edition: 1st edition/2016, Authors: S. R. Saunders, A. Aragon-Zavala, Scient. Edit.: Dimosthenis Vougioukas, ISBN: 978-960-546-737-1, Publisher: Pedio S.A. (2nd Book)
Associated scientific Journals
- ΙΕΕΕ Transactions on Vehicular Technology
- ΙΕΕΕ Transactions on Wireless Communications
- ΙΕΕΕ Transactions on Antennas & Propagation
- ΙΕΕΕ Journal on Selected Areas in Communications
- IEEE Communications Magazine