The University of Oklahoma

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Browsing The University of Oklahoma by Degree Discipline "D.Eng."

Now showing 1 - 5 of 5
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    Conceptual design of a five KW radioisotope-fueled power system for terrestrial applications /
    (The University of Oklahoma., 1969) Calvert, Floyd O.
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    Conversion of alicyclic compounds for improvement of fuel properties.
    (2006) Santikunaporn, Malee.; Resasco, Daniel E.,
    The presence of Pt improves the production of ring-contraction and ring-opening products from tetralin due to hydrogenation of tetralin to decalin. In addition, the location of metal (Pt) affects the ratio of RC/RO on the decalin reaction. The results show that the ratio of RC/RO increases over Pt located on the inside of the zeolite structure resulting from the enhancement of the RC desorption rate. Inversely, the ratio of RC/RO decreases over catalysts with high acidity.
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    Determination of pricing policy /
    (1968) Foster, Joseph William,
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    A microcomputer-aided drafting system /
    (1985) Humphreys, George Edward,
    This microcomputer-aided drafting system (MADS) is easily learned and used. Most of the communication with the user is done through menus and ample opportunity is provided for recovery from mistakes. It provides the user with a facility for generating high quality electronic schematics which can be easily changed or updated and scaled to fit various sizes of paper. A user who is familiar with electronic drafting can produce a usable drawing within an hour or two of his first introduction to the system. The general principle of operation for this system is to enter a schematic into the system with the keyboard and the graphic controls while the drawing is displayed on a video screen at various scale factors.
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    Uncertainty and sensitivity analysis in support vector machines: Robust optimization and uncertain programming approaches.
    (2006) Park, Jin.; Trafalis, Theodore,
    Noisy or uncertain data are common in machine learning and data mining applications. Noisy data can significantly affect the behavior of data mining and machine learning algorithms. Robust optimization and sensitivity analysis techniques are applied to the support vector machine (SVM) learning problems to develop a noise-immune solution, and suggest new approaches for dealing with noisy data. Perturbations of model parameters are considered as well as perturbation of input data. This approach determines how the levels of noise of data and model parameters influence the SVM solution, both in linear and nonlinear problems. Probability and scenario constrained approaches are also examined as alternatives to the robust optimization approach. Several examples illustrate the proposed methods. An application to real time traffic data for the prediction of the speed of a vehicle is also discussed. Tornado data analysis is illustrated in a probability constrained approach as well.