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Filtering by: Creator Fox, David S. Remove constraint Creator: Fox, David S. Academic Affiliation Electrical Engineering and Computer Science Remove constraint Academic Affiliation: Electrical Engineering and Computer Science Degree Field Computer Science Remove constraint Degree Field: Computer Science

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  • Effectiveness of using two and three-parameter distributions in place of "best-fit distributions" in discrete event simulation models of production lines

    Creator:
    Sharma, Akash
    Abstract:
    This study presents the results of using common two or three-parameter "default" distributions in place of "best fit distributions" in simulations of serial production lines with finite buffers and blocking. The default distributions used instead of the best-fit distribution are chosen such that they are non-negative, unbounded, and can match...
    Resource Type:
    Masters Thesis
    Full Text:
    Event Simulation Models of Production Lines. Abstract approved: David S. Kim This study presents the

  • Computational Approaches for RNA Structure Prediction with Dynamic Programming and Deep Neural Networks

    Creator:
    Deng, Dezhong
    Abstract:
    Our goal is to build a system to model the RNA sequences that reveals their structural information by using efficient dynamic programming algorithms and deep learning approaches. We aim to 1) achieve linear-time for RNA secondary structure prediction based on existing minimum free energy models; 2) utilize deep neural networks...
    Resource Type:
    Dissertation
    Full Text:
    Abstract approved: David A. Hendrix Our goal is to build a system to model the RNA sequences that reveals

  • Machine Learning Methods for the Discovery and Analysis of MicroRNAs

    Creator:
    Bell, Jimmy D.
    Abstract:
    MicroRNAs are a highly conserved class of small endogenous RNA, about ~22nt in length, involved in post-transcriptional gene silencing and have prominent roles in disease and development. Though the process of microRNA discovery was once an arduous task, the advent of high throughput sequencing technology has resulted in novel microRNAs...
    Resource Type:
    Masters Thesis
    Full Text:
    : ______________________________________________________ David A. Hendrix MicroRNAs are a highly conserved class of small endogenous RNA, about

  • Deep Learning for Human and Biological Languages

    Creator:
    Hong, Junki
    Abstract:
    We explore the application of deep learning to the disparate fields of natural language processing and computational biology. Both the sentences uttered by humans as well as the RNA and protein sequences found within the cells of their bodies can be considered formal languages in computer science, as sets of...
    Resource Type:
    Dissertation
    Full Text:
    Human and Biological Languages Abstract approved: David Hendrix and Liang Huang We explore the

  • Interpretable Machine Learning: Applications in Biology and Genomics

    Creator:
    Danaee, Padideh
    Abstract:
    Machine learning (ML) and deep learning (DL) models impact our daily lives with applications in natural language modeling, image analysis, healthcare, genomics, and bioinformatics. The exponential growth of biological sequence data necessitates accompanying advances in computational methods. Although deep learning is highly effective for detecting and classifying biological sequences, challenges...
    Resource Type:
    Dissertation
    Full Text:
    Machine Learning: Applications in Biology and Genomics Abstract approved: David A. Hendrix Machine

  • Type-correct changes — a safe approach to version control implementation

    Creator:
    Dagit, Jason
    Abstract:
    Ensuring correctness of real-world software applications is a challenging task. Testing can be used to find many bugs, but is typically not sufficient for proving correctness or even eliminating entire classes of bugs. However, formal proof and verification techniques tend to be very heavy weight and are simply not available...
    Resource Type:
    Masters Thesis
    Full Text:
    Implementation Abstract approved: David Roundy Martin Erwig Ensuring correctness of real-world software

  • Modeling programmer navigation : an empirical evaluation of predictive models

    Creator:
    Piorkowski, David
    Abstract:
    Software developers frequently need to perform code maintenance tasks, but doing so requires time-consuming navigation through code. A variety of tools are aimed at easing this navigation by using models to predict places in the code that a developer might want to visit, and then providing shortcuts so that the...
    Resource Type:
    Masters Thesis
    Full Text:
    Predictive Models AN ABSTRACT OF THE THESIS OF David Piorkowski for the degree of Master of

  • Information Foraging Theory as a Unifying Foundation for Software Engineering Research : Connecting the Dots

    Creator:
    Piorkowski, David
    Abstract:
    Empirical studies have shown that programmers spend up to one-third of their time navigating through code during debugging. Although researchers have conducted empirical studies to understand programmers’ navigation difficulties and developed tools to address those difficulties, the resulting findings tend to be loosely connected to each other. To address this...
    Resource Type:
    Dissertation
    Full Text:
    AN ABSTRACT OF THE DISSERTATION OF David Piorkowski for the degree of Doctor of Philosophy in

  • Evaluating social media attention interventions

    Creator:
    Gasper, David M.
    Abstract:
    Social media platforms use many techniques to engage users' attention with their platforms, including notifications, popups, and gamification elements. The impact of social media on physical and mental health has been studied, but limited publicly available research exists on how social media users can be helped to disengage from these...
    Resource Type:
    Honors College Thesis
    Full Text:
    by David Motz Gasper A THESIS submitted to Oregon State University Honors College in

  • Shape Modeling and GPU Based Image Warping

    Creator:
    Burri, David
    Abstract:
    This project addresses the problems of manually placing facial landmarks on a portrait and finding a fast way to warp the annotated image of a face. While there are many approaches to automatically find facial landmarks, most of them provide insufficient results in uncontrolled environments. Thus I introduce a method...
    Resource Type:
    Capstone Project
    Full Text:
    AN ABSTRACT OF THE PROJECT REPORT OF David Burri for the