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Course Criteria
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3.00 Credits
Complex system are composed of many independent parts, each endowed with behavioral rules that dictate its actions while the collective behavior of the overall system displays unpredictable, /emergent/ properties, thus the whole is indeed more than the sum of its parts. The course will examine the nature of complex systems as observed in many disciplines including biology, physics, economics, political science, ecology, sociology, and engineering systems. Agent-based modeling and simulation will be used as a tool for further understanding such systems.
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3.00 Credits
Presents the foundations of mathematical modeling and optimization, with emphasis on problem formulation and solution techniques. Includes applications of linear programs, nonlinear programs, and combinatorial models, as well as a practical introduction to algorithms for solving these types of problems. Topics are illustrated through classic problems such as service planning, operations management, manufacturing, transportation, and network flows. Prerequisites: Two years of college mathematics, including linear algebra, or instructor permission Note: This course cannot be applied toward completing the requirements for an M.S. or Ph.D. in Systems Engineering
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3.00 Credits
The goal of this course is to develop an operational understanding of the basic tools of probabilistic modeling, including (i) a review of undergraduate probability, (ii) introduction to Bernoulli and Poisson processes with applications, (iii) Markov chains and applications, and (iv) limit theorems. Homework and exams will emphasize the use of basic concepts of probability theory in applications. This course cannot be applied toward completing the requirements for an M.S. or Ph.D. in Systems Engineering.
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3.00 Credits
A study of technological systems, where decisions are made under conditions of risk and uncertainty. Topics include conceptualization (the nature, perception, and epistemology of risk, and the process of risk assessment and management) systems engineering tools for risk analysis (basic concepts in probability and decision analysis, event trees, decision trees, and multiobjective analysis), and 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, uncertainty sensitivity index method, and filtering, ranking, and management method). Case studies are examined.
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3.00 Credits
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.
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3.00 Credits
This topic covers principles of human factors engineering, understanding and designing systems that take into account human capabilities and limitations from cognitive, physical, and social perspectives. Models of human performance and human-machine interaction are covered as well as methods of design and evaluation.
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3.00 Credits
This course focuses on the infrastructure for the provision of drinking water, wastewater/sewage, and solid waste management services in the context of the environmental systems in which they are embedded and the institutional framework within which they must operate. It begins with coverage of the infrastructure design, operation, and maintenance, proceeds to a treatment of the concept of integrated sanitation systems, and then considers the major environmental issues relevant to these services, including global warming, the millenniu development goals, and sustainability. It also includes a study of the common tools in environmental systems analysis: lifecycle assessment, environmental economics, mass and energy balances, benefit-cost analysis, risk analysis, and environmental forecasting.
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3.00 Credits
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.
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1.00 - 12.00 Credits
For master’s students.
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3.00 Credits
Special Topics in Distance Learning
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