This is a Non-credit course. It is monitoring the progress of the PhD candidate’s thesis in order to evaluate the perspective and awareness of topic of interest which is offered by the candidate to the respective jury members.

Program of research leading to Ph.D. degree, arranged between a PhD Candidate and the supervisor. Students register to this course in all semesters starting from the second semester. The PhD candidate must report the conducted research within the semester at the end of each term to the appointed monitoring jury members in order to show the progress in the thesis.

Review of pipelined processor design and hierarchical memory design. Identification of parallelism in processes. Multiple diverse end functional units in a pipelined processor. Static, dynamic, and hybrid branch prediction techniques. Tomasulo Algorithm for efficient resolution of true data dependencies. Advanced data of techniques with and without speculative execution. Multiprocessor systems. Multi-threaded processors.

Discrete signal representation. Image representation. Filtering. Wavelet analysis. Mathematical analysis of image processing. Registration and sampling. Video formation and representation. Motion estimation and detection. 3D image representation, analysis, and processing.

Review of Neural Networks. Problem modeling. Neural network architecture. Supervised and unsupervised learning analysis. Hopefield model. Multi-layer perceptions analysis. Real-time neural network applications.

Optical network design. Optical network modeling, routing and wavelength assignment algorithms. Optical network simulation tools and techniques. Optical grid/cloud networks. Optical Burst Switching (OBS) and EPONs (Ethernet Passive Optical Networks).

Cryptographic Protocol Theory, Oblivious Transfer, Digital Cash, E-Voting Applications, Identity-Based Encryption, Information Theoretic Approach in the Security of Cryptographic Protocols, Cryptographic Engineering, Crypt-analytic Tools and Attacks, Quantum Cryptography, Secure Multi-Party Computation, Error- Correcting Codes and Cryptography

Principles of computer network design. Network design and optimization algorithms. Centralized network design, switching node location problems. Application of minimum spanning tree and shortest path algorithms to problems in network design. Static and dynamic routing algorithms. Network reliability analysis in design. Ad-hoc and cellular wireless network design. Case studies.

Design theory for relational databases. Database modeling, entities, data types, relations. Entity Relationship Diagrams, Relational Algebra. Table indexing. Database Queries, triggers, stored functions, stored procedures. Query optimization and data manipulation languages.

Brief information about programming languages. Variables, data types, control statements. Statement-level control structures. Graphical User Interface design with grid, flow, border and null layout. Object Oriented Programming with description of constructors, abstract data types, encapsulation, type compatibility, type checking, polymorphism. Exception handling. Multi-threaded applications, thread synchronization. File operations and management.

Software quality control management, processes, systems, methods, standards, certification, and measurement. Quality assurance standards and control processes. Cost-effective quality control system. Quality measurement metrics.

Design and develop applications by using the benefits of operating system and computer architecture. Threads and concurrent programming, TCP/UDP, RPC/IPC, System calls, remote procedure calls (RPC) and web services, xml and xml parsing, socket communication, logging.

The goal of this module is to introduce the students to advanced network programming concepts. They will study issues such as multitasking, multi-threading, processes, inter-process communications and network communications. Client-server communications for long term (e.g. large file transfer, multimedia streaming) and short term sessions (e.g. Web traffic) will be presented. P2P, RMI, applet-servlet, e-mail and multimedia mail will be introduced. The course will also address issues related to the programming of network equipment, including router architecture, network signaling, firewall and deep packet probes, network processors, network support for unicast, multicast and broadcast, and the use of techniques for dynamically changing router code, such as mobile agents and active networks

All operating systems provide services for programs they run. Typical services include executing a new program, opening a file, reading a file, allocating a region of memory, getting the current time of day, and so on. The focus of this course is to describe the services provided by various versions of the UNIX operating system. The course is starting with introduction to UNIX operating systems. Then UNIX shell programming, program development tools, utility routines, standard I/O routines, file and directory operations, signals, process concept and threads concept and programming, Inter Process Communication, sockets, semaphores, shared memory topics will be covered.

This course gives essential information for operating system and computer network security basics, risk analysis, security policies, concept of trusted computers and networks. Conventional and public key cryptography. Authentication and digital signatures. Authentication protocols and applications, certification, LINUX security issues. Data link layer, network layer and application level security. Firewalls and security tools. Secure payment systems. Case studies and programming projects.

This course will present an introduction to the principles of operation, design, testing, and implementation of the unimodal and multimodal biometric systems. Major and emerging biometric technologies (fingerprint, face, hand, iris, hand geometry, palmprint, keystroke, handwriting, signature, gait, voice etc.) performance and issues related to the security and privacy aspects of these systems will be addressed. Students will be introduced to a variety of methods used for processing data from various biometrics (especially signature biometric modality) and to statistical methods employed to achieve acceptable recognition performance rates (i.e. false accept rate, false reject rate, equal error rate and correct classification rates).

This course covers a number of advanced topics in database management systems and modern database applications. The specific topics include advanced concurrency control techniques, query processing and optimization strategies for relational database systems, advanced indexing methods, parallel and distributed database systems, next-generation data models, data mining on large databases, data on the web, and topics in data security and privacy.

Nowadays, there exists different alternatives for software development methods and tools to design an information system. The aim of this course is to provide students with the knowledge of the languages ​​that can be used for developing applications for desktop, web and mobile platforms. Besides, alternative databases that can be used for large architectures like relational, distributed and NoSQL databases will be discussed.