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FACULTY OF COMPUTER SCIENCE & INFORMATION TECHNOLOGY, UNIVERSITY OF MALAYA

FACULTY OF COMPUTER SCIENCE & INFORMATION TECHNOLOGY, UNIVERSITY OF MALAYA. Vision. To be an internationally renowned centre of excellence in research and education in Computer Science and Information Technology. Mission.

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FACULTY OF COMPUTER SCIENCE & INFORMATION TECHNOLOGY, UNIVERSITY OF MALAYA

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  1. FACULTY OF COMPUTER SCIENCE & INFORMATION TECHNOLOGY, UNIVERSITY OF MALAYA

  2. Vision To be an internationally renowned centre of excellence in research and education in Computer Science and Information Technology. Mission To advance and disseminate knowledge through research, teaching and learning in Computer Science and Information Technology in line with the hopes and aspirations of the people and the nation.

  3. Objectives To sustain an outstanding faculty dedicated to excellence in undergraduate and postgraduate teaching, learning and research. To contribute towards the development of the nation through the production of quality research and publications. To provide innovative academic programs that can respond to the changing needs of society. To produce quality graduates who are equipped with advanced knowledge and skills of computer science and information technology.

  4. Academic Programs

  5. Bachelor’s Degree Programs

  6. Bachelor’s Degree Programs

  7. Bachelor of Computer Science Specializations

  8. Bachelor of Information Technology

  9. Postgraduate Programmes • Faculty currently offers • 3 Masters programs • Master of Computer Science (MCS) • Master of Software Engineering (MSE) • Master of Library & Information Science (MLIS) • Doctor of Philosophy (PhD)

  10. Master of Computer Science(MCS) • Offered through • Coursework & Dissertation (KD) • 56 credits • 3 core courses + 2 elective courses • Dissertation : 40 credits • Dissertation only (D) • Specialization in • Data Communication and Networking • Management Information Systems • Artificial Intelligence • Multimedia

  11. Master of Library & Information Science(MLIS) • Offered through: • Coursework & Dissertation (KD) • 56 credits • 4 core courses + 1 elective courses • Dissertation : 40 credits • Dissertation only (D)

  12. Master of Software Engineering(MSE) • Offered through: • Coursework & Dissertation (KD) • 56 credits • 3 core courses + 2 elective courses • Dissertation : 40 credits

  13. Doctor of Philosophy (PhD) • By full research only

  14. Added Value • Relations with industry • Cisco • Microsoft • Oracle • SUN –Java • Mimos • Malaysian Research Network

  15. The ICT Computational Science Cluster

  16. Existing Collaborative Project with Soton Natural Computation (Molecular Computing) : Designing self-organized computational devices using Ribonucleic Acids (RNA) as information processing substrate.

  17. Digital libraries,Open Access Repositories & Scholarly Communication Concern with populating the Web with scholarly contents and local heritage through DLI and OAI Open Archive Initiatives Country initiatives to preserve cultural heritage Country initiatives to preserve local collections Eprint Archives (Post-print/pre-print) Cultural heritage initiatives Popular collection initiatives

  18. Supportive laws, regulations and policies in OAI • Growth of repositories • Accessibility of information • Organization of information Community & Organizational Informatics Governance Info-structure Current focus is on scholarly communication to support the research community • Adoption & Adaptation • Appropriation of OAI • Awareness and current practices • Information competence • Knowledge-sharing ICT Readiness People Readiness A field of investigation and practice concerned with principle and norms related to ICT with a focus on the personal, social, professional, cultural or economic development of, within and by communities as well as organizations

  19. User’s Intention-based Search of Video Visual Content Spatial Concept Association Based Search (SCABS) provides interface for users to express their query visual intention (image in mind) in retrieving videos. Spatial Concepts Transition Based Search (SCTBS) search mechanism grasps semantic and episodic (change from one scene to another) expectations of a user in generating retrieval results.

  20. Educational Content Video Search based on Question Answering Technique and Collaborative Profile Semantic Web Send query to get relevant video Get domain specific video-content (hits) Record VQA Navigational History Collaborative Profile Input Video Links Repository Create & Update Collaborative Profile To improve content relevancy of the video source To promote interoperable VQA (semantic web-compliant) Expert/Local Repository

  21. Information Hiding Generally divided into two disciplines: Data Embedding Encryption Objectives A.1 High capacity A.2 Low distortion A.3 Low complexity A.4 Other requirements* Objectives A.1 High robustness A.2 Small bit stream size A.3 Low complexity Unify both disciplines

  22. Information Hiding Universal Method Goals: - Data embedding with scalable capacity - Scalable quality degradation • PTS • PCR • SCR • PES Withtemporal • System layer Movie • Header • Payload • TCP • IP • I-Frame prediction • Motion vector • FMO Network Packets • MNR • SMR • Psycho- • acoustic Audio Video • SCF • Bit-allocation • CABAC • CAVLC • Coefficient • Quantization scale • Pixel Image • Open space • UniCode • Edges • Zerorun • Half-toning Text

  23. A Support Environment for Novice Researches Using Semantic Approach 1 3 Identifying methods to support and enhance Scholarly Research Activity on the web. 4 2

  24. Question Answering and Document Retrieval Engine Using Logical Linguistic Approach This research focuses on retrieving the answer to the question posed as well as stating the source document in which the answer is derived from. The research also presented a new approach in creating semantic Skolem Indexing matrix based on logical linguistic approach for automatically indexing multiple documents into single knowledge representation. A framework on IR for QA that uses this semantic matrix as its knowledge representation has been designed and implemented. A1 A1 A2 B1 B1 B2 Design of the Indexing framework

  25. 0.7 Casio Kodak NikonS NikonD Avg. Diff. 0.6 0.5 0.4 Individual CP Features average value 0.3 0.2 0.1 0 0 10 20 30 40 50 60 70 80 CP Features Features Based Camera Model Identification To ensure the validity of the evidence, digital forensics help by providing essential information about an image. For example image forensics can be used to trace the source of a digital image. Figure 1: EXIF’s make and camera model information changed by using ExifTool software package • Inter-camera model • Intra-camera model * represents 0% Confusion matrix for original images.

  26. High Impact Research Project

  27. For more information Visit Faculty website: www.fsktm.um.edu.my

  28. Thank you • FCSIT Website http://www.fsktm.um.edu.my • University of Malaya Website http://www.um.edu.my

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