دليل المواد | الشئون الأكاديمية

This course describes the key aspects of a software project management including software project planning, software validation, verification and testing techniques and strategies, software quality assurance, process improvement, software evolution, estimating software cost and schedule, change and configuration management, risk engineering, and continuous process improvement. This course includes a project developed in a team.

This course is designed for senior level students in computer engineering. It gives them exposure to special topics in computer engineering. Topics may vary each time the course is offered. Details of the course including: prerequisites, textbook, objectives, and topics to be covered, course specific outcomes etc. should be posted on the course page of the department at the time of offering.

Approaches to the development of systems in computer engineering, the special problems and the issues, primarily through hands-on design experiences and development of professional skills. The course provides information about the principles, methods and skills that are essential to engineering design. Concept of a life-cycle, nature of life cycle models, and phases of typical life cycles. Ethics and legal issues. Quality issues, process and process improvement. Issue of teams, team selection, roles in teams, and elements of teamwork. Selection of design and design alternatives for experiments, selection of test cases, support tools, standards and emerging technologies. Techniques and approaches associated with the different phases, special problems of design and the issues associated with tradeoffs, special problems of hardware/software tradeoffs, specifications and requirements engineering, design and architecture, testing, integration, maintenance, oral and written technical communication.

This course contributes a capstone design experience in computer engineering. Typically it would require the student to build on the aggregated knowledge gained in previous years, designing their own experiments, and developing their own test cases. Students will have design experience involving hardware and/or software systems to meet the desired needs within realistic constraints such as economic, environment, social, political, ethical, health and safety, manufacturability, and sustainability. Use of skills in design tools and practices, integration, test plans, implementation, experimental validation, maintenance, functional teaming, oral and written technical communication.

Introduction to Digital Image Processing covering digital techniques for image representation, enhancement, compression and restoration. Students will learn the fundamentals behind image processing methods and algorithms. We assume students have an understanding of linear systems and calculus. In addition, it is also helpful to have a familiarity with elementary probability theory and linear algebra.

Machine learning, statistical pattern classification, feature extraction and selection, various learning algorithms, cluster analysis, image processing, syntactic approach and practical applications on analysis of various biomedical data, character recognition, and speech recognition.

Selected advanced Operating Systems topics; control of disks and other input/output devices; file-system structure and implementation; network structures; distributed system structures and file systems; introduction to distributed and real-time systems; distributed algorithms; logical clocks; reliability and security; case studies.

Selected topics in the area of software engineering such as emerging areas of research in software engineering; Object-oriented design and analysis; Configuration management; Software testing; Reverse engineering; Software reusability; Distributed and web-based software development; Fault-tolerant software development; Case tools for design and analysis, configuration management, and testing.

Three-dimensional transformations and perspective systems and techniques for displaying and shading solid areas, hidden-element removal, display device characteristics, device independent systems, and user interface design.

Introduction to the issues of privacy and data protection, information collection, cookies, profiling, traffic monitoring analysis, data mining, data matching, surveillance technology, censorship, encryption, identification, anonymity, codes and policies, law, privacy in workplace, and ethical issues.

This course concentrates on recent research in computing that affects future directions in science, engineering and technology, hence upon modern society. For example, studying standers (e.g., E- Commerce technologies, and software life cycle processes such as ISO/IEC 12207) have immense effect on industry and society. Students explore such topics through conducting research. The course introduces skills necessary for research including surveying, scrutinizing methods and outcomes, designing tools, and preparing technical manuscripts.

Introduction to AI. History of AI. Knowledge representation: First order logic, Predicate logic, and Semantic net. Blind search. Heuristic search. Machine planning. Machine learning. Agents. Natural language processing.

Advanced AI topics will be discussed in-depth. Student will survey recent research in topics such as, but not limited to, natural language processing, cognitive modeling techniques, machine learning techniques, evolutionary algorithms, fuzzy logic, expert systems, robotics, knowledge system engineering (knowledge-based software engineering), and neural network computing.

Database management systems architecture; conceptual database models; relational, semantic, object-oriented, and object-relational databases; implementation techniques for database systems; file organization and data placement techniques; query processing; concurrency control; rollback and recovery techniques; integrity and consistency; transaction processing.

Design and implementation of database management systems in support of advanced technologies and applications, such as: geographical information systems (GIS) temporal and spatial databases, multimedia databases data mining data warehousing, distributed database systems, or other advanced topics in the area of database and information systems. We will focus on current issues in database and information system design.