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  • EECS 441: Internet Applications

    3.00 Credits
    Case Western Reserve University

    This course exposes students to research in building and scaling internet applications. Covered topics include Web services, scalable content delivery, applications of peer-to-peer networks, and performance analysis and measurements of internet application platforms. The course is based on a collection of research papers and protocol specifications. Students are required to read the materials, present a paper in class, prepare short summaries of discussed papers, and do a course project (team projects are encouraged). Prereq: EECS 325 or EECS 425.
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  • EECS 444: Computer Security

    3.00 Credits
    Case Western Reserve University

    General types of security attacks; approaches to prevention; secret key and public key cryptography; message authentication and hash functions; digital signatures and authentication protocols; information gathering; password cracking; spoofing; session hijacking; denial of service attacks; buffer overruns; viruses, worms, etc., principles of secure software design, threat modeling; access control; least privilege; storing secrets; socket security; RPC security; security testing; secure software installation; operating system security; database security; web security; email security; firewalls; intrusions. Recommended preparation: EECS 337.
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  • EECS 450: Operations and Systems Design

    3.00 Credits
    Case Western Reserve University

    Introduction to design, modeling, and optimization of operations and scheduling systems with applications to computer science and engineering problems. Topics include, forecasting and times series, strategic, tactical, and operational planning, life cycle analysis, learning curves, resources allocation, materials requirement and capacity planning, sequencing, scheduling, inventory control, project management and planning. Tools for analysis include: multi-objective optimization, queuing models, simulation, and artificial intelligence.
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  • EECS 451: Introduction to Digital Communications

    3.00 Credits
    Case Western Reserve University

    Analysis and design of modern digital communications systems: introduction to digital communication systems, review of basic analog and digital signal processing for both deterministic and stochastic signals, signal space representation, basis functions, projections and matched filters, pulse shaping, pulse amplitude modulation, quadrature amplitude modulation, deterministic performance and performance in noise, carrier frequency and phase tracking, symbol timing synchronization, source coding and channel coding. Extensive computer-based design exercises using Matlab and Simulink to design and test digital modems and communication systems. Prereq: STAT 332 or equivalent.
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  • EECS 452: Random Signals

    3.00 Credits
    Case Western Reserve University

    Fundamental concepts in probability. Probability distribution and density functions. Random variables, functions of random variables, mean, variance, higher moments, Gaussian random variables, random processes, stationary random processes, and ergodicity. Correlation functions and power spectral density. Orthogonal series representation of colored noise. Representation of bandpass noise and application to communication systems. Application to signals and noise in linear systems. Introduction to estimation, sampling, and prediction. Discussion of Poisson, Gaussian, and Markov processes.
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  • EECS 454: Analysis of Algorithms

    3.00 Credits
    Case Western Reserve University

    This course presents and analyzes a number of efficient algorithms. Problems are selected from such problem domains as sorting, searching, set manipulation, graph algorithms, matrix operations, polynomial manipulation, and fast Fourier transforms. Through specific examples and general techniques, the course covers the design of efficient algorithms as well as the analysis of the efficiency of particular algorithms. Certain important problems for which no efficient algorithms are known (NP-complete problems) are discussed in order to illustrate the intrinsic difficulty which can sometimes preclude efficient algorithmic solutions. Recommended preparation for EECS 454: MATH 304 and (EECS 340 or EECS 405). Offered as EECS 454 and OPRE 454.
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  • EECS 458: Introduction to Bioinformatics

    3.00 Credits
    Case Western Reserve University

    Fundamental algorithmic methods in computational molecular biology and bioinformatics discussed. Sequence analysis, pairwise and multiple alignment, probabilistic models, phylogenetic analysis, folding and structure prediction emphasized. Recommended preparation: EECS 340, EECS 233.
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  • EECS 459: Bioinformatics for Systems Biology

    3.00 Credits
    Case Western Reserve University

    Description of omic data (biological sequences, gene expression, protein-protein interactions, protein-DNA interactions, protein expression, metabolomics, biological ontologies), regulatory network inference, topology of regulatory networks, computational inference of protein-protein interactions, protein interaction databases, topology of protein interaction networks, module and protein complex discovery, network alignment and mining, computational models for network evolution, network-based functional inference, metabolic pathway databases, topology of metabolic pathways, flux models for analysis of metabolic networks, network integration, inference of domain-domain interactions, signaling pathway inference from protein interaction networks, network models and algorithms for disease gene identification, identification of dysregulated subnetworks network-based disease classification. Offered as EECS 459 and SYBB 459. Prereq: EECS 359 or EECS 458 or BIOL 250.
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  • EECS 460: Manufacturing and Automated Systems

    3.00 Credits
    Case Western Reserve University

    Formulation, modeling, planning, and control of manufacturing and automated systems with applications to computer science and engineering problems. Topics include, design of products and processes, location/spatial problems, transportation and assignment, product and process layout, group technology and clustering, cellular and network flow layouts, computer control systems, reliability and maintenance, and statistical quality control. Tools and analysis include: multi-objective optimization, artificial intelligence, and heuristics for combinatorial problems. Offered as EECS 360 and EECS 460.
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  • EECS 466: Computer Graphics

    3.00 Credits
    Case Western Reserve University

    Theory and practice of computer graphics: object and environment representation including coordinate transformations image extraction including perspective, hidden surface, and shading algorithms; and interaction. Covers a wide range of graphic display devices and systems with emphasis in interactive shaded graphics. Laboratory. Recommended preparation: EECS 233.
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