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On-Line Student Orientation
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Prospective Students:
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(Fall, 2008)
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On-Grounds
Students:
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Course Offerings Available to On-Grounds Students
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Coordinators:
Handbook, handouts, brochure
Additional Programs:
Nanotechnology Certificate Program
National Institute of Aerospace (NIA)
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SYS 581 - ENGINEERING ECONOMIC SYSTEMS
This course is an introduction to the theory of the industrial organization from a game-theoretic perspective. Particular emphasis will be made in industries with strong engineering content (electricity, telecommunications, software & hardware, etc.). (Prerequisites: ECON 201, or equivalent background in introductory microeconomics)
SYS 582 - HUMAN COMPUTER INTERFACES
Basic aspects of human factors in the design of information support systems. Topics covered include: 1. basic human performance issues (physiology, memory, learning, problem-solving, human error); 2. the user interface design process (task analysis, product concept, functional requirements, prototype, design, and testing). Students will gain basic skills in the analysis and design of human-machine systems through in-class exercises and a course project. The course is also designed to help the student practice different communication skills (interviewing, written analysis, and oral presentation). (Prerequisite: Instructor approval)
SYS 601 - INTRODUCTION TO SYSTEMS ENGINEERING
An integrated introduction to systems methodology, design, and management. An overview of systems engineering as a professional and intellectual discipline, and its relation to other disciplines, such as operations research, management science, and economics. An introduction to selected techniques in systems and decision sciences,including mathematical modeling, decision analysis, risk analysis, and simulation modeling. Overview of contemporary topics relevant to systems engineering such as reengineering and total quality management. Elements of systems management, including decision styles, human information processing, organizational decision processes, and information system design for planning and decision support. Emphasizes relating theory to practice via written analyses and oral presentations of individual and group case studies. (Prerequisite: Admission to the graduate program)
SYS 602 - SYSTEMS INTEGRATION
Provides an introduction to the problems encountered when integrating large systems, and also presents a selection of specific technologies and methodologies used to address these problems. Includes actual case studies to demonstrate systems integration problems and solutions. A term project is used to provide students with the opportunity to apply techniques for dealing with systems integration. (Prerequisite: SYS 601 or instructor permission)
SYS 603 - MATHEMATICAL PROGRAMMING
Presents the foundations of mathematical modeling and optimization, with emphasis on problem formulation and solution techniques. Coverage includes linear programs, nonlinear programs, combinatorial models, optimality conditions, search strategies, and numerical algorithms. Topics are illustrated through classic problems such as service planning, operations management, manufacturing, transportation, and network flow. (Prerequisite: Two years of college mathematics, including linear algebra, and the ability to write computer programs)
SYS 605 - STOCHASTIC SYSTEMS
Covers basic stochastic processes with emphasis on model building and probabilistic reasoning. The approach is non-measure theoretic but otherwise rigorous. Topics include a review of elementary probability theory with particular attention to conditional expectations; Markov chains; optimal stopping; renewal theory and the Poisson process; martingales. Applications are considered in reliability theory, inventory theory, and queuing systems. (Prerequisite: Undergraduate probability and statistics,or equivalent background in applied probability and statistics)
SYS 613 - APPLIED MULTIVARIATE STATISTICS
This course covers the major methods for multivariate data analysis. Topics include multivariate Gaussian distribution, multivariate regression, MANOVA, principal components, factor analysis, canonical correlation, structure equation models, discriminant analysis, and logistic regression. The course illustrates the use of these methods using modern statistical software. (Prerequisite: SYS 605, 618, or equivalent)
SYS 614 - DECISION ANALYSIS
Principles and procedures of decision-making under uncertainty and with multiple objectives. Topics include representation of decision situations as decision trees, influence diagrams, and stochastic dynamic programming models; Bayesian decision analysis, subjective probability, utility theory, optimal decision procedures, value of information, multi-objective decision analysis, and group decision making. (Prerequisite: SYS 603, 605, or equivalent)
SYS 616 - KNOWLEDGE-BASED SYSTEMS
Introduces the fundamental concepts necessary for successful research in, and real-world application of, knowledge-based decision support systems. Emphasizes knowledge acquisition, system design principles, and testing systems with human subjects. Students are required to work through several design and testing exercises and develop a final project that applies principles learned in class. (Prerequisite: Instructor approval)
SYS 623 - COGNITIVE SYSTEMS ENGINEERING
Introduces the field of cognitive systems engineering, which seeks to characterize and support human-systems integration in complex systems environments. Covers key aspects of cognitive human factors in the design of human performance (memory, learning, problem-solving, expertise and human error); characterizes human performance in complex, socio-technical systems, including naturalistic decision making and team performance; reviews different types of decision support systems, with a particular focus on representation aiding systems; and covers the human-centered design process (task analysis, knowledge acquisition methods, product concept, functional requirements, prototype, design, and testing).
SYS 634 - DISCRETE-EVENT STOCHASTIC SIMULATION
A first graduate course on the theory and practice of discrete-event simulation. Coverage includes Monte Carlo methods, generating random numbers and variates, sampling distributions, and spreadsheet applications; the dynamics of discrete-event stochastic systems, simulation logic and computational issues,output analysis, experiment design, and model verification and validation. Emphasizes modern simulation programming languages. (Prerequisite: SYS 605 or equivalent)
SYS 650 - RISK ANALYSIS
A study of technological systems, where decisions are made under conditions of risk and uncertainty. Part I: Conceptualization: the nature of risk, the perception of risk,the epistemology of risk, and the process of risk assessment and management. Part II: Systems engineering tools for risk analysis: basic concepts in probability and decision analysis, event trees, decision trees, and multiobjective analysis. Part III: Methodologies for risk analysis: hierarchical holographic modeling, uncertainty taxonomy, risk of rare and extreme events, statistics of extremes, partitioned multiobjective risk method, multiobjective decision trees, fault trees, multiobjective impact analysis method, and uncertainty sensitivity index method, and filtering, ranking, and management method. Case studies. (Prerequisite: Undergraduate probability, network modeling and design, or equivalent)
SYS 654 - FINANCIAL ENGINEERING
Provides an introduction to basic topics in finance from an engineering and modeling perspective. Topics include the theory of interest, capital budgeting, valuation of firms, futures and forward contracts, options and other derivatives, and practical elements of investing and securities speculation. Emphasis is placed on the development and solution of mathematical models for problems in finance, such as capital budgeting, portfolio optimization, and options pricing; also predictive modeling as it is applied in credit risk management. One of the unique features of this course is a stock trading competition hosted on www.virtualstockexchange.com or a similar site. (Prerequisite: SYS 603, Mathematical Programming, or equivalent graduate- level optimization course. Students need not have any background in finance or investment.)
SYS 670 - ENVIRONMENTAL SYSTEMS ANALYSIS
Examines the constitution of environmental systems and the science underlying observed perturbations to these systems. Presents the main tools used to analyze the effect of perturbations to environmental systems and to frame policy interventions for mitigating the impacts of such disturbances. Begins with a treatment of technology design and the environment with a focus on automobiles, electric power, drinking water supply, wastewater and sewage treatment, and solid waste management. Moves to a study of modeling of environmental processes, and a focus on photochemical smog, PCBs in the aquatic environment, CFCs and the ozone hole, and global warming and the greenhouse effect. Progresses to a study of the tools in environmental systems analysis: lifecycle assessment, environment economics and natural resource accounting, benefit-cost analysis, risk analysis and environmental forecasting Includes an analysis of environmental justice and the role of stakeholders in environmental systems and closes with a synthesis of the course material in he context of sustainable development. (Prerequisites: CHEM 152, Introductory Chemistry, and PHYS 241, General Physics.
SYS 674 - TOTAL QUALITY ENGINEERING
Comprehensive study of quality engineering techniques; characterization of Total Quality Management philosophy and continuous improvement tools; statistical monitoring of processes using control charts; and process improvement using experimental design. (Prerequisites: Basic statistics or instructor permission)
SYS 681 - NETWORK OPTIMIZATION
Introduction to optimization models involving network structure: theory, algorithms, and applications. We start by analyzing shortest path problems and work our way toward network models with less special structure, including general linear programs and multicommodity flows. Emphasis on problem formulation and on the rigorous development of solution algorithms. (Prerequisite: Linear algebra or SYS 603)
SYS 727 - QUANTITATIVE MODELS OF HUMAN PERFORMANCE
This course provides an introduction to quantitative methods of measuring human performance in complex systems. The focus of the selected methodologies is based on providing insight into human performance in order to guide design and/or training. Assignments involve applying the methods to a human-machine system problem. In addition, each student will be responsible for presenting the concepts of at least one of the quantitative approaches presented in the readings. (Pre-requisites: Competency with linear regression techniques and experimental design preferred)
SYS 730 - TIME SERIES ANALYSIS AND FORECASTING
An in-depth study of time series analysis and forecasting models from a statistical and engineering perspective. Emphasizes the process of stochastic model building, including model identification, estimation, and model diagnostic checking Topics include smoothing and filtering,ARIMA models, frequency domain analysis, and vector processes.
7/2/08
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