CS 522 - Computer Architecture, Prof. Kanad Ghose - 3 cr.

Pipelined processors: basic theory, instruction pipelines, multifunction units, instruction scheduling, precise interrupts. Pipelined vector machines. Superscalar and VLIW architectures. High-speed memory system design. Overview of parallel architectures: SIMD/MIMD systems, interconnection networks, synchronization and cache coherence.
Prerequisites:   CS 325 - Advanced Computer Organization.

Course Syllabus

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CS 542 - PROGRAMMING DESIGN PATTERNS, Prof. Leslie Lander - 3 cr.

Fundamentals of object-oriented programming using the Smalltalk language and programming environment.  Patterns for program design, examples of patterns used in existing software libraries such as a windowing toolkit.  Exercises in programming with design patterns and communicating designs to other programmers using the language of patterns.  UML design notation.  Project using a compiled object oriented programming language.  Prerequisites:   CS 571 or CS 471-Programming Languages or equivalent experience.

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CS 565 - Artificial Intelligence, Prof. Walker Land- 3 Cr.  

An introduction to programming languages used in artificial intelligence and coverage of one particular language in depth.  Assorted topics in artificial intelligence, including search techniques for artificial intelligence applications, knowledge representation and expert systems.  Prerequisites: CS 533 - Algorithms.

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CS 575 -  DESIGN AND ANALYSIS OF COMPUTER ALGORITHMS,  Prof. Michal Cutler - 3 CR.  

Analysis of programs and review of design techniques. Lower bound theory and NP-completeness. Heuristic, approximation, probabilistic and parallel algorithms. Prerequisites: CS 373-Automata Theory and Formal Languages and CS333--Algorithms.

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EE 571 - Electronic Properties of Materials,  Prof. James Constable - 3 cr. 

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This is a graduate level course in semiconductor devices and integrated circuits.  Major topics include:  Basic principles of semiconductor physics; discussion of Moore's Law and whether it will crash in the near future; why CMOS circuits are the most common type of integrated circuit; description of the basics of bipolar and CMOS devices, highlights of other semiconductor devices; relationship between semiconductor technology and basic device physics.  This latter point will be emphasized throughout the course, because the technology is not understandable without the reasons for its development.   Prerequisites:  Undergraduate courses in electricity and magnetism and in semiconductor devices and/or device physics.

COURSE SYLLABUS

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Techniques for modeling, control, and performance analysis of asynchronous system driven by random events.  Main topics include Markov chain models, discrete event simulations, optimal parameter estimation and optimal control of networked systems.  Application areas to be discussed include computer networking, wireless communications, and supervisory control systems.  Prerequisites:  a course in linear systems and a course in probability.

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Study of the basic mechanical and electrical properties of the human body, including the dynamics of the cardiovascular system, the dynamics of limbs in locomotion and other activities; measurement of physiological parameters.  Anatomy and physiology of these biological systems.  Design of prosthetic devices.  Projects will be included which will stress the mathematical modeling and analysis of the dynamics of limbs and the cardiovascular system.  Prerequisites:  BS degree in engineering or physics, or consent of instructor.

Course Syllabus 

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ME 535 - Analytical Methods, Prof. Frank Cardullo - 3 cr.

A survey and discussion of some of the most important and useful analytical methods for analyzing a wide variety of engineering and scientific problems.  Topics include solution of partial differential equations, including methods for linear equations; eigenfunction expansions and separation of variables.  Prerequisites:  ordinary differential equations, ME 302 - Engineering Analysis or equivalent.

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Basic concepts in probability and statistics required in the modeling of random processes and uncertainty.  Bayes' formula.  Bayesian statistics, independent events; random variables and their descriptive statistics; distribution functions; Bernoulli, Binomial, Hyper geometric, poisson, normal, exponential, gamma.  Weibull and multinomial distributions; Chebyshev's theorem; central limit theorem; joint distributions; hypothesis testing; contigency tables, goodness of fit, non-parametric statistics, regression and correlation.  Prerequisite:  one year of calculus.

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Studies some of the fundamental theoretical results about logic and about the capacities and limitations of computing devices. Notion of computability is introduced by means of Turing machines, whose halting problem is shown to be unsolvable. Two other notions of computability, abacus computable functions and recursive functions, are also introduced and their interrelations discussed. The undecidability of first-order logic is also covered.  Prerequisite:  

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Introduction to health systems and health care delivery.  The application of industrial and systems engineering principles to continuous process improvement in the health care domain will be studied.  Concepts that will be addressed will include, but not be limited to, process mapping, optimization, scheduling, lean and flexible systems, quality enhancement, simulation, supply chain management, inventory control, and information management.  Prerequisite:  Graduate standing in SSIE or permission of instructor

COURSE SYLLABUS

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SSIE 561- QUALITY ASSURANCE FOR ENGINEERS, Prof. Susan Lu - 3 CR.

Statistical quality control, designing for quality, process control, vendor and customer quality issues, quality costs and production. Prerequisites: BS in engineering (any field), and probability and statistics coursework, or consent of department chair.

Course Syllabus  

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SSIE 578 - Processes for Electronic Manufacturing,
Prof. Lawrence Harvilchuck  - 3 CR.

The electrical content of manufactured products is increasing in all areas.  To prepare the engineer for manufacturing these electrical assemblies, this course has been structured to cover topics in soldering, wire bonding, TAB, printed wiring board production, PCB assembly and population processes (through hole and SMT), and associated environmental issues.   Prerequisite:  Undergraduate course in manufacturing processes, related experience, or consent of department chair.

Course Syllabus (requires Adobe Acrobat Reader - Free Download)

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SSIE 644 Foundations of Adaptive Optimization, Prof. Sarah Lam - 3 CR

This course is a survey of the newer, most common adaptive search methods.  This is a project and research oriented course designed to give graduate students a foundation from which to explore areas of their own interest.  Focused topics include simulated annealing, genetic algorithms, evolution strategies, tabu search, ant colony methods, and particle swarm optimization. Other search methods such as genetic programming, evolutionary programming and random search methods will be briefly covered. Major emphasis is on NP complete combinatorial problems found in engineering. Issues such as solution encodings, stochastic convergence, selection methods, local and global search methods are discussed.  Prerequisite:  SSIE 505 or equivalent, and knowledge of at least one programming language.

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