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Filtering by: Creator Slegers, Nathan J. Remove constraint Creator: Slegers, Nathan J. Degree Name Master of Science (M.S.) Remove constraint Degree Name: Master of Science (M.S.) License Attribution-NonCommercial 4.0 (CC BY-NC 4.0) Remove constraint License: Attribution-NonCommercial 4.0 (CC BY-NC 4.0)

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  • Using Machine Learning Models and SVD Dimension Reduction to Predict Cancer Outcomes

    Creator:
    Wofford, Rachel
    Abstract:
    Machine learning models are powerful tools which may aid in the prediction of survival outcomes of cancer patients. This study evaluated eight classification models and eight regression models on their ability to predict survival outcomes on breast cancer and prostate cancer data sets from the SEER database. The most accurate...
    Resource Type:
    Capstone Project
    Full Text:
    to Predict Cancer Outcomes Rachel Wofford Advisors: Dr. Nathan Gibson, Dr. Samantha Erwin Oregon

  • Parameter Estimation within a Kinematic Magnetohydrodynamics Framework

    Creator:
    Rajbhandari, Evan, Gibson, Nathan L., and Woodside, C. Rigel
    Abstract:
    We discuss the well-posedness of the forward problem for the magnetohydrodynamic system with the inclusion of the ion-slip parameter. We also demonstrate the convergence of a parameter estimation scheme. Focusing on power-generation, we implement and the validate a numerical model with an engineering multi-physics software, COMSOL, using ideal-power equations. We...
    Resource Type:
    Preprint
    Full Text:
    Magnetohydrodynamics Framework Evan Rajbhandari1, Nathan Gibson2, and C. Rigel Woodside3 1Department of Mathematics