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Filtering by: Creator Swami, Nathan S. Remove constraint Creator: Swami, Nathan S. Academic Affiliation Mathematics Remove constraint Academic Affiliation: Mathematics

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  • Enhancing Facial Recognition: A Comparative Analysis of Image Preprocessing Techniques in PCA, KL Expansion and SVD

    Creator:
    Tuffour, Prince A.
    Abstract:
    Facial recognition has become increasingly important in recent years, due to the wide range of applications it has in fields such as security, surveillance, and human-computer interaction. Three popular methods for facial recognition are the Principal Component Analysis (PCA), Karhunen-Loeve Expansions, which is fundamentally a continuous form of PCA but...
    Resource Type:
    Capstone Project
    Full Text:
    : ∫ Γ(s, t)ϕi(s)ds = λiϕi(t) (8) where Γ(s, t) is the covariance function of X(t, ω) and λi are the

  • Predicting Conductivity Within a Resistive Unsteady MHD Channel

    Creator:
    Rajbhandari, Evan
    Abstract:
    The theory behind magnetohydrodynamics (MHD) is utilized to present a 3-D solution to how the induced magnetic field changes with respect to time. Several MHD-based assump- tions are made to simplify the coupling of Maxwell’s equations with two constitutive laws and Ohm’s law. The velocity field is assumed to be...
    Resource Type:
    Technical Report
    Full Text:
    dimensionality of the parameter space. References [1] R. HIXON, S.-H. SHIH, and R. R. MANKBADI. Numerical

  • Optimization under Uncertainty of a Magnetohydrodynamics Generator

    Creator:
    Rajbhandari, Evan
    Abstract:
    Within this dissertation, we develop tools and techniques to demonstrate the feasibility of real-time optimization of a magnetohydrodynamics generator. To ease computational complexity, we work on the kinematic magnetohydrodynamic system, prescribing the fluid-flow and model the material response of the system through an updated Generalized Ohm’s law. We focus on...
    Resource Type:
    Dissertation
    Full Text:
    Uncertainty of a Magnetohydrodynamics Generator Abstract approved: Nathan L. Gibson Within this

  • Electromagnetic Inverse Problem for Relaxation Time Distribution in the Time-Domain

    Creator:
    Armentrout, Megan
    Abstract:
    We consider wide bandwidth electromagnetic pulse interrogation problems for the determination of dielectric response parameters in complex dispersive materials. We couple Maxwell’s equations with an auxiliary ODE modeling dielectric polarization. A problem of particular interest is to identify parameters in a standard polarization model (e.g., Debye or Lorentz) using time-domain...
    Resource Type:
    Capstone Project
    Full Text:
    Distribution in the Time-Domain Megan J. Armentrout∗ Oregon State University Advisor: Professor Nathan L

  • Polynomial Chaos Expansions for Random Ordinary Differential Equations

    Creator:
    McKenzie, Brian
    Abstract:
    We consider numerical methods for finding approximate solutions to Ordinary Differential Equations (ODEs) with parameters distributed with some probability by the Generalized Polynomial Chaos (GPC) approach. In particular, we consider those with forcing functions that have a random parameter in both the scalar and vector case. We then consider linear...
    Resource Type:
    Capstone Project
    Full Text:
    Differential Equations Brian McKenzie Advisor: Dr. Nathan Gibson January 6, 2012 Abstract We consider

  • 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

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

    Creator:
    Wofford, Rachel E.
    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

  • Stochastic and Numerical Analysis for Optimization Problems

    Creator:
    Jiang, Huanqun
    Abstract:
    There are three chapters of manuscripts in this dissertation and all of them are talking about a specific theme: stochastic control, but with completely different perspectives. In the first manuscript, we solve the optimal barrier strategy for dividend distribution in a complicated Lévy system. In this system, the capital of...
    Resource Type:
    Dissertation
    Full Text:
    Numerical Analysis for Optimization Problems Abstract approved: Edward C. Waymire Nathan L. Gibson There

  • Compatible Discretizations for Maxwell's Equations with General Constitutive Laws

    Creator:
    McGregor, D. A.
    Abstract:
    In this thesis we construct compatible discretizations of Maxwell's equations. We use the term compatible to describe numerical methods for Maxwell's equations which obey many properties of vector Calculus in a discrete setting. Compatible discretizations preserve the exterior Calculus ensuring that the divergence of the curl and the curl of...
    Resource Type:
    Dissertation
    Full Text:
    Nathan L. Gibson In this thesis we construct compatible discretizations of Maxwell’s equations. We use

  • Model of heterogeneous microscale in SOFI for Monte Carlo simulations

    Creator:
    Gibson, Nathan Louis
    Abstract:
    We present a methodology for creating a simulated foam microstructure for use in forward simulations of wave equations to quantitatively analyze the expected scattering phenomenon primarily responsible for the attenuation of interrogating signals in Sprayed-On Foam Insulation (SOFI). Our approach builds off of the popular use of Voronoi Tessalations for...
    Resource Type:
    Technical Report
    Full Text:
    Nathan L. Gibson May 21, 2007 Abstract We present a methodology for creating a simulated foam