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Course Criteria
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3.00 Credits
Credits: 3 Study of a selected area in systems engineering or C3I under the supervision of a faculty member. Written report required. Prerequisites Graduate standing, completion of at least two core courses, permission of instructor. Hours of Lecture or Seminar per week 3 Hours of Lab or Studio per week 0 When Offered F, S, SUM
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3.00 Credits
Credits: 3 Cross-Listed with OR 735 Special topics and recent developments in Monte Carlo simulation methodology for discrete-event stochastic systems. Contents vary; possible topics include statistical analysis of simulation output data, random number and random ariate generation, variance reduction techniques, sensitivity analysis and optimization of simulation models, distributed and parallel simulation, object-oriented simulation, and specialized applications. Prerequisites OR 635 or permission of instructor. Notes May be repeated for credit when topics are distinctly different. Hours of Lecture or Seminar per week 3 Hours of Lab or Studio per week 0
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3.00 Credits
Credits: 3 Special topics in the C4I area, with different content in different terms. Representative areas include quantitative evaluation of C4 systems, applications of artificial intelligence in C4 systems, and military communications systems. Prerequisites SYST 680. Hours of Lecture or Seminar per week 3 Hours of Lab or Studio per week 0
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3.00 Credits
Credits: 3 Cross-Listed with IT 763/OR 763 Examines alternative paradigms of scientific research and their applicability to research in information technology. Topics include fundamental elements of scientific investigation, basic principles of experimental design and statistical induction, philosophy of science and its relation to the information technology sciences, and case studies of information technology research. Prerequisites STAT 554. Hours of Lecture or Seminar per week 3 Hours of Lab or Studio per week 0
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3.00 Credits
Credits: 3 Cross-Listed with STAT 781 Statistical and computational methods and systems for deriving user-oriented knowledge from large databases and other information sources, and applying knowledge to support decision making. Information sources can be in numerical, textual, visual, or multimedia forms. Covers theoretical and practical aspects of current methods and selected systems for data mining, knowledge discovery, and knowledge management, including those for text mining, multimedia mining, and web mining. Prerequisites One of the following courses: CS 687, CS 650, INFS 614, STAT 663, STAT 664, or permission of the instructor. Hours of Lecture or Seminar per week 3 Hours of Lab or Studio per week 0
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3.00 Credits
Credits: 3 Capstone project course for MS/SE program. Key activity is completion of major applied team project resulting in an acceptable technical report, and oral briefing. Students should plan to take course in last semester of studies. Prerequisites 21 graduate credits, including SYST 611. Hours of Lecture or Seminar per week 0 Hours of Lab or Studio per week 0
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1.00 - 6.00 Credits
Credits: 1-6 Research project chosen and completed under the guidance of a graduate faculty member, which results in a technical report acceptable to a three-member faculty committee, and an oral defense. Prerequisites 21 graduate credits and permission of instructor. Hours of Lecture or Seminar per week 0 Hours of Lab or Studio per week 0
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3.00 Credits
Credits: 3 Cross-Listed with IT 842/OR 842 Survey of alternative views about how incomplete, inconclusive, and possibly unreliable evidence might be evaluated and combined. Discusses Bayesian, Baconian, Shafer-Dempster, and Fuzzy systems for probabilistic reasoning. Prerequisites STAT 544 or OR 681, or permission of the instructor. Hours of Lecture or Seminar per week 3 Hours of Lab or Studio per week 0
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3.00 Credits
Credits: 3 Cross-Listed with IT 850 Covers lifecycles; large systems comprising heterogeneous components; human, organizational, and technological basis for integration; societal and cultural basis; conceptual frameworks; structure, function, and purpose of industry; risk management; user requirements and functional specifications; bid and proposal process; systems integration and federal government; standards; integration of systems and federations of systems; integrated process and product development; architectures; systems management and cost estimation; reengineering; quality management; increasing returns to scale, network effects, and path dependency issues; and systems integration ecology and evolutionary systems integration Prerequisites SYST 510 or 520. Hours of Lecture or Seminar per week 3 Hours of Lab or Studio per week 0
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3.00 Credits
Credits: 3 Cross-Listed with ECE 753/IT 888/OR 888 Centralized and distributed estimation theory, hierarchical estimation, tracking and data association, multisensor multitarget tracking and fusion, distributed tracking in distributed sensor networks, track-to-track association and fusion, and Bayesian networks for fusion. Prerequisites ECE 734 or SYST 611. Hours of Lecture or Seminar per week 3 Hours of Lab or Studio per week 0
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