CCMAS Course Search

Review of data structures; linear data structures; hashing; trees; graphs; recursion; Complexity classes; empirical measurements of performance; time and space tradeoffs analysis; Algorithmic strategies: Brute-force algorithms; greedy algorithms; divide-and-conquer; backtracking; branch-and-bound; minimum spanning tree; heuristics; pattern matching and string/text algorithms; numerical approximation algorithms; Tractable and intractable problems

Advanced computer architecture including discussion of instruction set design (RISC and CISC); virtual memory system design; memory hierarchies; cache memories; pipelining; vector processing; I/O subsystems; co-processors; and multiprocessor architectures; Case studies of current systems

Reflection models; Texture and models; texture and environment mapping; advanced ray tracing; radiosity method; volume rendering; advanced modelling techniques; simulation and animation

Analysis of advanced topics in automated reconstruction of imaged objects and computer interpretation of imaged objects; techniques for three-dimensional object reconstruction; computing motion parameters from sequences of images; computational frameworks for vision tasks such as regularization; and stochastic relaxation; approaches for autonomous navigation; Depth image analysis; novel imaging techniques and applications; and parallel architectures for computer vision

Quick review of the fundamental technologies: parsing; bytecodes; interpretive systems in general; and run-time support; especially memory management; Analysis and classification of existing embedded languages according to the language paradigms used and the features included; without reference to the implementations; Analysis of the implementations of existing embedded languages; Review and study of topical issues and current development in the area of Computer Science

Introduction to basic programming techniques of artificial intelligence (AI); Domain analysis; representation of Knowledge and strategies; control on inference and search; development of interactive intelligence CAI programs; the role of analogical reasoning; The main contents are symbol manipulations and AI problem solving techniques; Topics include LISP primitives; LISP objects and evaluation; recursion and iteration and data abstraction (association lists; properties and DESTRUCT); macros; object-centred programming; symbolic pattern matching and basic solving methods

In depth study of a few major areas historically considered to be part of artificial intelligence; In particular; detailed coverage will be given to the design considerations involved in the following applications: automatic theorem proving; natural language understanding and machine learning

Study of Forensics: Principles and practice of identification; Pattern matching and recognition; Computer Forensics: pattern recognition; data mining; machine learning algorithms; and visualization; Sequence alignment; applications to biological sciences - DNA; gene finding; genome assembly; drug design; drug discovery; protein structure alignment; protein structure prediction; prediction of gene expression and protein-protein interactions; genome-wide association studies and the modelling of evolution

Anatomy of a compiler; lexical analysis (scanning); syntax analysis (parsing); syntax-directed translation; semantic analysis; intermediate code generation; code generation and optimisation; Advanced topics include garbage collection; dynamic data structures; pointer analysis; aliasing; code scheduling; pipelining; dependence testing; loop level optimisation; superscalar optimisation; profile-driven optimisation; debugging support; incremental parsing; type inference; advanced parsing algorithms; practical attribute evaluation; function in-lining and partial evaluation

Channels and channel capacity; introduction to information theory; sharing network resources: telecommunication history; circuit switching and packet switching; multiplexing; FDM; TDM; statistical multiplexing; virtual circuits and datagrams; advantages and disadvantages; sharing the medium: Aloha; CSMA (persistent and non-persistent); CSMA-CD; token passing; CDMA; wireless LANs and simple performance analysis; dealing with errors: errors; coding and redundancy; hamming theory and codes; CRCs; ARQ protocols; CR selective retransmission and flow control; internetworking and the internet: ISPs; datagram forwarding; the DNS; IPv4; addressing and forwarding; encapsulation and address resolution; TCP and UDP; ports and congestion controls; example applications; modelling data networks: services and protocols; layered architectures; the OSI 7-layer model; introduction to queue theory; physical media; LANs and bridging; WANs and point-to-point links; routing; addressing and routing in the internet; end-to-end communication in the internet; and application protocols; Cyber space technology: Cyber Crime; Cyber Security and models of Cyber Solution