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Filtering by: Creator Jacobson, David L. Remove constraint Creator: Jacobson, David L. Degree Field Computer Science Remove constraint Degree Field: Computer Science

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  • Effectiveness of index size reduction techniques

    Creator:
    Jacobson, Bryan L.
    Abstract:
    Index size savings from three techniques are measured. The three techniques are: 1) eliminating common, low information words found in a "stop list" (such as: of, the, at, etc.), 2) truncating terms by eliminating word stems (such as: -s, -ed, -ing, etc.), and 3) simple data compression. Savings are measured...
    Resource Type:
    Masters Thesis
    Full Text:
    Techniques by Bryan L. Jacobson A THESIS submitted to Oregon State University in partial fulfillment of

  • ASTEK : a multi-paradigm knowledge aquisition tool for complex structured knowledge

    Creator:
    Jacobson, Chris E.
    Abstract:
    Knowledge based systems can require large, highly complex and varied forms of knowledge. An effective knowledge acquisition tool to support such a system should allow the user to transfer and manipulate the different forms knowledge in a manner that is clear and intuitive. ASTEK is a knowledge acquisition tool that...
    Resource Type:
    Masters Thesis
    Full Text:
    complex structured knowledge AN ABSTRACT OF THE THESIS OF Chris E. Jacobson for the degree of Master of

  • 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

  • Position-Dependent Codon Usage Bias in the Human Transcriptome

    Creator:
    Subramanian, Kaavya
    Abstract:
    All life depends on the reliable translation of RNA to protein according to complex interactions between translation machinery and RNA sequence features. While ribosomal occupancy and codon frequencies vary across coding regions, well-established metrics for computing coding potential of RNA do not capture such positional dependence. Here, we investigate position-dependent...
    Resource Type:
    Honors College Thesis
    Full Text:
    :_____________________________________________________ David Hendrix All life depends on the reliable translation of RNA to protein according

  • 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

  • An enhanced version of Caesar supporting 45° geometries

    Creator:
    Lanfri, Ann R.
    Abstract:
    Caesar is an interactive graphic editor that is used to generate layouts for VLSI circuits. It runs on a VAX-11 /780 under the UNIX operating system with Berkeley extensions. Caesar has a unique and simple user interface. Phled is an enhanced version of Caesar that runs on a M68000-based engineering...
    Resource Type:
    Capstone Project
    Full Text:
    Department of Computer Science Date research paper is completed Apri l 1985 ----";:__ _______________

  • New Strategies to Develop Hidden Markov Models Combining KEGG and Pfam

    Creator:
    Gupta, Sonica
    Abstract:
    Profile Hidden Markov Models utilize the information stored in a multiple sequence alignment such as its residues and conserved regions to assign probabilities at each column. This indicates areas in the sequences where similar functionality is observed. These probability weights are then combined to assign a sequence score, which is...
    Resource Type:
    Honors College Thesis
    Full Text:
    . Abstract approved:_____________________________________________________ Maude David Profile

  • 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

  • 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