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Full-Text Articles in Physical Sciences and Mathematics
Ceg 402/602-01: Computer Networks, Jack Jean
Ceg 402/602-01: Computer Networks, Jack Jean
Computer Science & Engineering Syllabi
No abstract provided.
Ceg 434/634-01: Concurrent Software Design, Thomas C. Hartrum
Ceg 434/634-01: Concurrent Software Design, Thomas C. Hartrum
Computer Science & Engineering Syllabi
This course provides an introduction to concurrent program design in the UNIX environment. Classical problems of synchronization, concurrency, and their solutions are examined through course projects and through readings on operating system design.
Ceg 460/660-01: Introduction To Software Computer Engineering, John A. Reisner
Ceg 460/660-01: Introduction To Software Computer Engineering, John A. Reisner
Computer Science & Engineering Syllabi
This course introduces established practices for engineering large-scale software systems. Emphasis is placed on both the technical and managerial aspects of software engineering, and the software development process. This includes techniques for requirements elicitation, analysis, design, testing, and project management. The course emphasizes object-oriented development with the Unified Modeling Language (UML). Hands-on experience is provided through individual homework problems and a partnered project.
Ceg 499/699-01: Scientific Visualization And Virtual Environments, Thomas Wischgoll
Ceg 499/699-01: Scientific Visualization And Virtual Environments, Thomas Wischgoll
Computer Science & Engineering Syllabi
By the end of this quarter, you will be familiar with techniques ed for visualizing various types of data sets, such as medical, vector or general data sets.
Ceg 720-01: Computer Architecture I, Soon M. Chung
Ceg 720-01: Computer Architecture I, Soon M. Chung
Computer Science & Engineering Syllabi
Review of sequential computer architecture and study of parallel computers. Topics include memory hierarchy, reduced instruction set computer, pipeline processing, multiprocessing, various parallel computers, interconnection networks, and fault-tolerant computing.
Ceg 724-01: Computer Vision I, Arthur A. Goshtasby
Ceg 724-01: Computer Vision I, Arthur A. Goshtasby
Computer Science & Engineering Syllabi
This course teaches basic techniques for low-level and mid-level vision. The techniques are to reduce image noise and segment images into objects or their parts. Other techniques covered in the course analyze and quantify texture, register images, and recover 3-D shapes from 2-D images.
Ceg 751-01: Microprocessors Ii, Jack Jean
Ceg 751-01: Microprocessors Ii, Jack Jean
Computer Science & Engineering Syllabi
No abstract provided.
Ceg 726-01: Pattern Recognition, Arthur A. Goshtasby
Ceg 726-01: Pattern Recognition, Arthur A. Goshtasby
Computer Science & Engineering Syllabi
This course will discuss fundamentals of Pattern Recognition. including supervised learning and clustering.
Ceg 760-01: Advanced Software Computer Engineering, Thomas C. Hartrum
Ceg 760-01: Advanced Software Computer Engineering, Thomas C. Hartrum
Computer Science & Engineering Syllabi
This course covers advanced topics in software engineering. Aspects of problem specification, design, verification, and evaluation are discussed. We will focus on design methods, including software patterns and software architecture, plus some advanced topics involving formal methods of software specification or evaluation using software metrics. Students will participate in team projects to apply the methods discussed.
Ceg 416-01: Matrix Computations, Ronald F. Taylor
Ceg 416-01: Matrix Computations, Ronald F. Taylor
Computer Science & Engineering Syllabi
This course is a survey of numerical methods in linear algebra for application to problems in engineering and the sciences. Emphasis is on using modern software tools on high performance computing systems. This course covers the mathematics of linear equations, eigenvalue problems, singular value decomposition, and least squares. Material covered will be relevant to applications areas such as structural analysis, heat transfer, neural networks, mechanical vibrations, and image processing in biomedical engineering. A familiarity with MATLAB is useful, and the ability to program in languages such as CIC++ or Fortran is very important. A basic knowledge of matrix algebra is …