This course aims to give the student the basic rudiments of report writing. The rationale for report writing, the structure of reports, and such details as physical appearance and linguistic style will be discussed. In addition to writing reports, students will also be given supplementary exercises, as necessary, to enhance their general writing skills.
Computer crime and ethics, nature of computer crime, criminal and civil law overview, basis for protection against computer crimes, suitability and application of intellectual property to computers, application of patent to computers, copyright and its range of application ownership and third party rights, trade secrets and unfair competition, computer contracts and liability, privacy, viruses and other programmed threats, legal protection against viruses, global information networks and related legal aspects.
Sets, sequences, algorithms and pseudo codes, prepositional logic. Proof by induction. Matrices and Boolean matrices. Relations and functions. Graph theory. Posits lattices. Boolean algebra. Linear equations and matrices. Vector spaces. Inner product spaces. Linear transformations. Eigenvalues and eigenvectors. Canonical forms. Jordan forms.
Sample space, probability axioms, combinatorial techniques, conditional probability, independence and Bayes theorem. Random variables; distribution functions, moments and generating function. Some probability distributions. Joint distribution, the Chebychev inequality and the law of large numbers. The central limit theorem and sampling distributions.
Review of sampling theory and distributions. Estimation theory: Unbiasedness, efficiency, points estimates, confidence interval estimates (for means, proportions, differences, sums, variances, and variance ratios), maximum likelihood estimates. Tests of hypotheses and significance: Null hypothesis, type I and type II errors, level of significance, special tests of significance for large or for small samples, operating characteristic curves, quality control chart, fitting theoretical distributions to sample frequency distributions, goodness of fit. Curve fitting, regression and correlation: Method of least squares, multiple regression, (linear generalized and rank) correlation, correlation and dependence. Analysis of variance: Purpose, one-factor experiments, variation, linear mathematical models, F-test for the null hypothesis of equal means, modifications for unequal numbers of observations, two-factor experiments, experimental design.
Second and higher-order differential equations. Applications of second-order differential equations with constant coefficients. Systems of linear differential equations. Series solutions. Laplace transforms. Special functions. Partial differential equations. Boundary value problems. Fourier series and integrals. Diffusion, potentional and wave equations in rectangular, cylindrical, and spherical co-ordinates.
Abstract Data Types (ADT). Stacks: Definition and operations, implementation of stacks with array and records, applications of stacks. Queues: Definitions, implementation of circular queues, applications of queues. Linked lists: Singly linked lists, linked stacks, linked queues, doubly linked lists, application of linked lists. Tree structures, binary trees: binary tree traversals, binary tree search. Searching Definitions, sequential search. Sorting: Definitions, insertion sort, selection sort. Hashing: Hash functions, perfect Hash functions.
File processing environment: Overview of files, blocking and buffering, secondary storage devices. Sequential access: Sequential file organization, external sort/merge algorithms. Random access: Direct addressing, hashing, perfect hashing, Dynamic hashing. Tree-structured file organization: High-balanced binary search trees, B-tree, B+-tree, indexed sequential file organization. List-structured file organization: Multiple-key, and inverted files. The merits of these file organizations and the optimum choice for a given application.
