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Course Criteria
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3.00 Credits
Prerequisite: CSCI 4525 or consent of department. A study of the techniques, tools, and applications of expert systems. Topics include the architecture of expert systems, knowledge representation, drawing inferences, expert system tools, developing small and large knowledge systems, difficulties with expert system development, and the expert systems market. This course will also involve the design and implementation of a small expert system using a commercially available expert system shell.
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3.00 Credits
Prerequisite: Computer Science 2125, or consent of department. The course has two distinct parts. The first is mathematical logic, including Zero-Order Logic, First-Order Logic, semantic approaches and interpretations, and syntactic approaches and deductive apparati. The second part concentrates on the algorithms for performing logic, and covers resolution refutation proofs in Zero-and First- Order Logics.
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3.00 Credits
Prerequisite: CSCI 4621 and CSCI 4623 or consent of department. A graduate course in advanced network security and computer forensics, emphasizing the development and application of tools and techniques for securing computer networks and preservation and recovery of digital evidence in networked environments. Topics include: basic issues in network security, network intrusion detection, honeypots and honeynets, and network forensics analysis. The course will include a substantial lab component.
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3.00 Credits
Prerequisite: CSCI 4631. Commonly-used data structures for graphics displays and raster scan graphics algorithms for line and circle drawing; polygon filling; antialiasing; curve fitting; surface fitting; two- and three-dimensional clipping, including clipping to arbitrary convex volumes; hidden-line and hidden-surface removal, including ray tracing; rendering, including local and global illumination models, texture shadows, transparency, and color effects.
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3.00 Credits
Prerequisite: CSCI 4632. This course provides an overview of fundamental techniques for representing and recognizing visual patterns in two or three dimensions. Topics covered include segmentation and morphology, pattern recognition and classification, color- and text-based measures, motion analysis and optical flow, threedimensinal models from stereo imaging, knowledge-based systems and scene understanding.
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3.00 Credits
Prerequisite: CSCI 4631 or consent of department. An introduction to standard techniques for displaying, exploring, and understanding non-visual data from medical, scientific, engineering, financial, or other domains. Topics covered will include visualization models, data representation, color-mapping and contouring, volume rendering, data transformations, modeling, image processing techniques, animation and user interaction.
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3.00 Credits
Prerequisites: CSCI 4525 and MATH 2511 or consent of the instructor. A study of the concepts behind pattern recognition and classification with applications in the analysis of various types of data. Topics include: design of a pattern recognition system, Bayesian decision theory, Maximum-likelihood estimation, nonparametric techniques, linear discriminant analysis, multilayer neural networks, non-metric techniques, stochastic methods, unsupervised learning and clustering (including hierarchical and online clustering, component analysis, low dimensional representations).
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3.00 Credits
Prerequisite: CSCI 4101 or consent of department. Using the fields of pattern recognition, computer graphics, image processing, and algorithm design for source material, this course will concentrate on algoruthms and techniques for geometric computations. Topics include: computation of convex hulls, decomposition of polygons, polygon approximation, planar visibility, and other current topics of research. Students will be required to design and analyze a number of algorithms.
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3.00 Credits
Prerequisite: CSCI 4525 or consent of the department. An investigation of computational systems in which several intelligent agents or agents and humans, interact. Includes architectures for building intelligent agents, design and implementation of multi-agent systems, inter-agent communication languages and protocols, problem-solving, planning, learning and adaptation techniques in multi-agent systems.
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3.00 Credits
Prerequisite: consent of department. This is an advanced graduatelevel course whose topics change from semester to semester. The prerequisites change as dictated by the topic. This course may be repeated once for credit.
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