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Introduction to graphics systems: screens, input / output units, application coordinate systems, output primitives: points, lines, polygons, circles, ellipses, area filling, attributes of output primitives, colors, patterns, aliases, transformation: translation, scaling, rotation, reflection, clipping: windows and view ports, line clipping, area clipping, text clipping, segments: structures, creating, updating, deleting,. Interactive graphics systems: windows, icons, menus, virtual reality, 3D graphics: representation, transformation, computer animation, applications. Weekly practice in the lab.
Third year
Theory and techniques whereby diverse kinds of geographical data are processed into new knowledge. Map data structure, advanced analysis, map topologies, temporal and spatial data, quality of geographic data, geographic data modeling and presentation. The combination of theory, application and practical training, inputting, processing, and outputting geographic data within the scope of a GIS, case study.
Fundamentals of Information Systems; Types and levels of MIS; IT in Business;  Business Application of Information Technology; Managing Information Technology: global management, planning and information change; Security and protection issues. Weekly practice in the lab.
second year
This course explains and discusses key concepts of Multimedia networking, including:  Introduction: Digital Audio, Graphics and Video, voice over IP (VOIP); Characteristics of multimedia; Multimedia Perceptual Quality: Frame rate, Delay, Jitter, Loss; Compression standards; Real Time Multimedia Applications, Desk Top Conferencing, Video Conferencing, Video Mail, Distance Learning, Non-Real Time Multimedia Applications: World Wide Web, Multimedia Mail; Design of Networked Multimedia Applications; Transport layer multimedia: RTP protocol, RTCP protocol, SIP protocol; Quality of Service: Network layer support for multimedia, IntServ, DiffServ; Multimedia Multicasting; Multimedia programming, Future trends.
fourth year
Introduction, Data structure for image analysis; Shape representation; Image preprocessing; Image formats; Recognition; Feature extraction; Processing primitives; Modeling (e.g. quad applications); Local and global operations; Clustering: hierarchical and non-hierarchical methods, clustering using neural networks and genetic algorithms; Classifications; Nearest neighbors; Neural nets; Image enhancement; Segmentation application and measurement; Image storage and retrieval; Applications. Weekly practice in the lab.
fourth year