Course Description

 Basics of data communication, computer networks, ISO /OSI basic reference model, routing, flow control, congestion control, TCP/IP suite of protocols, data links, Internetworking, higher level protocols.

 Essentials of information security, determination of IT-security risks, specification of security objectives and security policy will be introduced. Furthermore, network packet capture and analysis, protocol decoding, security scanning, and attacks. Techniques and tools in penetration testing. Attends will learn to analyze security risks, design and test IT-security procedures and mechanisms, scan ?P networks, discover and monitor intrusions and vulnerability within a specific range of threats.

 Systems theory; management information; conceptual models of information in organizations; MIS; decision support systems; enterprise resource planning systems; information systems planning; organizing for information system projects; IS project lifecycle models; IS development and maintenance principles; organization, management and control of IS; IS outsourcing.

 Programming in C language. Structured problem solving and top-down analysis and design of solution algorithms. Control structures, data types, input output format, program structure, functions, recursion, files, pointers and dynamic data structures.

 Architectures for Multimedia Systems, Digital Audio, Video Technology and Image Compression, Computer Graphics, Multimedia Information Systems, Multimedia Communication Systems. Structure of the Internet, Methods of Storing and Accessing Data on the Internet.

 Introduction to database systems, data storage and retrieval problems, data definition, relational database management systems, Tables, Queries, Relationships. Entity-Relationship models. Introduction to Sequential Query Language (SQL), Writing queries in Visual environments, Embedded SQL. Database programming with Visual Basic and MS-ACCESS

 Preprocessing of datasets, feature reduction and selection approaches, statistical methods like bayes decision theory, discriminant functions, linear and non-linear classifiers, clustering and combining classifiers.

 Human brain and biological neurons, artificial neuron models, the perceptron and the perceptron learning algorithm, multi-layer perceptrons and backpropagation algorithm. Recurrent neural networks and time delay neural networks. Unsupervised learning. Recent advances about image processing applications. Combining neural networks.

 Abstraction, approaches to modular program design, principles of abstract data type, basic concept of objects: local variables and methods. Classes and objects. Class relationships, Inheritance. Polymorphism. Graphics and Graphical User Interface Components. Exception Handling. Multithreading. Files and Input/Output Streams. Multimedia and animations.

 This course will be about, primitive data structures. Binary and Decimal Integers, Real numbers, character strings, memory representation of information. Two and multi dimensional arrays. Structures. The stack, recursion, queues and lists, trees. Sorting, searching and graphs

 Software development process, project management, software requirements, software design, modularity, functional decomposition. Project metrics, project planning, scheduling, estimation. Software development, implementation issues, testing. Software process management, quality assurance.

 Exploring natural events, goal reduction, finding solution paths, games, logic, advanced knowledge representation, natural language of understanding, matching, applications.

 The concept, techniques, tools and processes of project management. Project selection. Project planning, organization and controlling. Budgeting and cost elimination. Scheduling. Resource allocation. Monitoring and information systems. Project auditing and termination.

 Basic concepts and philosophy of management; motivation theories, motivational techniques, management styles, management schools of thought, scientific management, decision making, responsibility and accountability, control mechanism; corporate culture, management systems, analysis, design and implementation, comparative management thoughts; the Turkish case.

 Historical perspective of management science, Operations Research study, problem solving, static and sequential decision making, scientific method, linear programming formulation and solution of linear programming problem, the graphical, algebraic, simplex methods, duality, parametric and sensitivity analysis, transportation, assignment problems and solutions, network analysis, integer programming, nonlinear programming, dynamic programming, waiting lines, inventory, Markov process, simulations, applications in business.

 Fuzzy sets and basic operations on fuzzy sets, further operations on fuzzy sets, fuzzy relations and the extension principle, linguistic variables and fuzzy if-then rules, fuzzy logic and approximate reasoning, fuzzy rule base and fuzzy inference engine, fuzzifiers and defuzzifiers, fuzzy systems as nonlinear mappings, approximation properties of fuzzy systems, design of fuzzy systems from input-output data, non adaptive and adaptive fuzzy control

 Fundamentals of distributed systems and algorithms, remote procedure call, security in channel and access control, fault tolerance, transactions, p2p systems, group communication, sensor networks, localization, adaptive applications, cluster computing and social networks.

 General concepts of systems. Discrete and continuous systems. State variables. Models, modeling and simulation of systems. Principles and techniques for system modeling and simulation. Comparison of analytical modeling and simulation modeling techniques. General structure of a simulation system. Probability aspects of simulation. Techniques and methods of generation of random numbers and random variants with the desired probability distribution. Simulation languages and packages. Transaction-oriented and event-oriented simulation. Queuing systems in simulation. Validation and verification of simulation models. Output analysis and representation of simulation results. (Statistically)

 Semantic Web: terminology, parties, history; Components. Semantic Web: principles and practice. URI naming; XML technologies., XML processing, RDF: model, syntax, semantics, RDF: Vocabulary Description Language, RDF: data access: query language; standards and case studies, Web ontology: OWL intro; Web-based ontologies, Integration and interoperability; OWL & DAML, OWL: syntax and semantics, flavors, OWL practice, Rules and rule markup, Web services; Web syndication: RSS and Atom/Echo, Semantic Web: best-practice case studies, Innovative applications; future directions.

 Overview of AI. Overview of knowledge-based systems. Knowledge acquisition methods. Knowledge representation techniques. Backward, forward and hybrid chaining in rule-based production systems. Conflict resolution. Treatment of uncertainty. Rule and decision-tree induction. Case studies.

 Review of hardware and software used in graphic systems. Introduction to programming with OpenGL. Graphic primitives. 2D and 3D geometric transformations. Two dimensional viewing: Viewing pipeline, clipping, and windowing. There dimensional viewing: Viewing pipeline, viewing parameters, projections, viewing transformations, clipping. Visible surface detection. Introduction to illumination models and surface rendering. Introduction to ray tracing.

 Discrete time signals, reconstruction, quantisation, digital image representation, image fundamentals, image transforms, image enhancement, image restoration, segmentation, description, sampling.

 Fundamentals of concurrent programming; multitasking operating systems with special emphasis on UNIX; mutual exclusion problem and critical sections; semaphores; ADA rendezvous; transporters; UNIX structure.