Κατεύθυνση: Secondary Major in Networks or Telecommunications: Optional Courses

Learning Outcomes

he course presents simulation techniques with particular emphasis on discrete event simulation and applications in computer computational systems and communication networks.

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

• design system models with the required details level that serves better the problem at hand
• develop simulation programs in general purpose programming language (e.g C++) to simulate and evaluate the behavior of simpler systems
• use more sophisticated simulation software for the study and performance evaluation of more complex communication networks and computational systems (e.g network simulator ns3 and CloudSim for cloud computing systems)
• design experiments, collect measurements and interpret and evaluate simulation results

Course Contents

• Introduction to dynamic discrete event systems.
• Development of discrete system models, event-advance design, time-advance design, activity-based design.
• Pseudorandom number generation, random variables generation.
• Overview of simulation languages and platforms.
• Development of simulation programs using general purpose programming languages.
• Measurement techniques, traffic load and experiment design.
• Statistical analysis of simulation experiments, transient and steady state, data collection, confidence intervals, variation reduction techniques.
• Simulation exercises and examples of data networks and cloud computing systems. Theoretical results verification.

Recommended Readings

1. Roumeliotis and Souravlas, “Simulation Techniques”, Epikentro Publications.
2. Kouikoglou and Konstantas, “Simulation of Discrete Event Systems”, Disigma Publications, 2016.
3. Harry Perros, “Computer Simulation Techniques – The Definitive Introduction”, free download from https://people.engr.ncsu.edu/hp/files/simulation.pdf
4. Averill M. Law and W. David Kelton, “Simulation Modeling and Analysis”, McGraw-Hill, Inc.
5. NS manual and tutorials, https://www.nsnam.org/documentation/

Learning Outcomes

The students after the successful completion of the course will be able:

• to model and analyze data with appropriate analysis techniques, assess the quality of input
• to choose the appropriate exploratory and/or inferential method for analyzing data, and interpret the results contextually.
• to use supervised and unsupervised learning techniques for solving many analysis problems such as prediction, classification, segmentation.
• to apply methods for the evaluation of the data analysis results.

Course Contents

• Collection, preparation and representation of data for analysis
• Linear, logistic regression
• Classification Techniques (probabilistic classification, decision trees, support vector machines)
• Predictive analytics and neural networks
• Recommender systems
• Graph analysis (applications on social networks)
• Text mining – sentiment analysis
• Evaluation of data analysis results

Recommended Readings

• Mohammed J. Zaki, Wagner Meira Jr. (2018): Data Mining and Analysis Fundamental Concepts and Algorithms, Cambridge University Press.
• Jure Leskovec, Anand Rajaraman, Jeffrey David Ullman (2014): Mining massive datasets, Cambridge University Press.
• Top of Form.
• Bottom of Form.

Students can choose it only once during undergraduate studies (either the 7th or the 8th semester).

Learning Outcomes

The objective of this course is to present fundamentals concepts regarding Healthcare Information Systems (HIS). HIS are described at both conceptual and technical level and types of HIS are studied thoroughly. In addition, best practices regarding HIS architectural design, development methodologies and interoperability are analysed. Challenges and perspectives of HIS are presented with reference to modern digital technologies of data analytics and artificial intelligence. The course will incorporate a significant laboratory component with various digital tools (mainly open source) that allow student to implement HIS.

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

• Understand the connection between healthcare systems and healthcare information systems
• Define the users of information and decision support based on existing data
• Describe the general functions, objectives and advantages of HIS
• Describe contemporary architectural trends and HIS, in the form of services provided, for supporting important healthcare processes
• Compare various HIS characteristics and choose the most appropriate systems for specific needs and operational frameworks
• Develop HIS, by using open source tools, inventing innovative practices in the fields of medical data architecture and management for their multiple exploitation.

Course Content

1. Healthcare Information Systems: General characteristics. HIS evolution.
2. HIS analysis, design and implementation.
3. Patient-oriented HIS development.
4. Process-oriented healthcare organizations. Healthcare process and data management.
5. Specialized HIS. Contribution to provided healthcare services.
6. HIS architectures, integration and interoperability.
7. HIS security. Standards and security policies.
8. Presentation of well-known commercial HIS of the global market regarding electronic health records.
9. HIS challenges and perspectives. HIS in Greece.
10. HIS development (analysis, design, implementation, testing, operation, maintenance).

Suggested Bibliography

• Karen A. Wager, Frances W. Lee and John P. Glaser (2009): Health Care Information Systems: A Practical Approach for Health Care Management, Jossey-Bass.
• Joseph Tan (2010): Developments in Healthcare Information Systems and Healthcare Informatics: Improving Efficiency and Productivity, IGI Global.
• Charlotte A. Weaver, Marion J. Ball, George R. Kim, Joan M. Kiel, (2015): Healthcare Information Management Systems: Cases, Strategies, and Solutions, Springer.
• Sean P. Murphy, (2015), Healthcare Information Security and Privacy, McGraw-Hill Education.
• Pamela K Oachs, Amy Watters, (2016), Health Information Management: Concepts, Principles, and Practice, American Health Information Management Association.
• International Journal of Healthcare Information Systems and Informatics (IJHISI), IGI Global
• International Journal of Healthcare Technology and Management, Inderscience
• International Journal of Medical Informatics, Elsevier.

Learning Outcomes

The aim of this course is to support the students in learning the principles, concepts and applications of cryptography.
Upon successful completion of the course the student will be able:

• to handle the basic elements of numerical theory and modular arithmetic
• to manage cryptographic algorithms and their properties
• basic cryptographic functions, such as pseudo-random sequences, one-way hash functions, shift and displacement networks and feistel networks.
• the main features for symmetric and asymmetric cryptography are familiar
• to handle key management systems and digital signatures

Course Contents

• Basic definitions and concepts; information security.
• Symmetric cryptography.
• Digital signatures.
• Authentication.
• Public key cryptography.
• Hash functions.
• Integrity checking.
• Key management and random number generators.

Recommended Readings

• Schneier B. (1996): Applied Cryptography, 2nd Edition, John Wiley & Sons.
• Stallings W. (2006): Cryptography and Network Security, 4th Edition, Prentice Hall.

Learning Outcomes

This course is the basic introductory course in the field of computational analysis and synthesis of social networks.

The course material seeks to introduce the students to the basic concepts and algorithms for the study of social networks. The course focuses on answering questions related to the creation of social networks, their information properties and the interaction between their structure and the emergence of social processes related to information diffusion, strategic interaction and collective behavior. All theoretical results are presented in relation to their application in real problems in social computational environments such as Facebook of Google search.

The successful completion of the course will make students capable of:

• understanding the basic and important features of social networks in both an algorithmic and interaction level.
• knowing the major features of the tools and development methods for the creation of digital social networks and applications

Course Contents

• Conceptual features of social networks
• Elements of Graph Theory
• Social links
• Topics in Social Environments (Homophily, Group participation, Separation)
• Social Balancing
• Information Diffusion
• Elements of Game Theory
• Group Decision-Making
• Sharing frameworks

Recommended Readings

• Martin J. Osborne, An Introduction to Game Theory, Oxford, 2010
• Instructor Notes

Learning Outcomes

This course presents baselines on digital economy. With the completion of the course, the student will be in position:

• to understand and become familiar with the key concepts and principles of applications of e-business.
• to know the main characteristics of the e-business applications both in terms of development and in terms of provisioning of such applications.
• to be able to implement e-business applications, by applying the knowledge obtained from laboratory exercises in different application contexts / domains.

Course Contents

• e-Business introduction.
• e-Commerce presentation.
• Baselines on e-business micro-economy theory.
• Business requirements analysis for the design of e-commerce.
• Methodology for the design of successful web pages. Blogs.
• e-Stores, methodology for the design of e-stores.
• Design evaluation and faults detection through the use of web statistics applications.
• eGovernment, ebanking; ehealth; business-to-business applications.

Moreover, the EVDOXOS system is utilized to provide additional useful information to the students as well as exercises that respond to the corresponding thematic topics / sessions covered by the course.

Recommended Readings

• McGarvey R. & Campanelli M. (2005): Start Your own E-Business, Entrepreneur Press.
• Chaffey D. (2008): E-Business and E-Commerce Management, 3rd Edition, Prentice Hall.

This course offered by the Department of Business Administration of University of Piraeus.