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Filtering by: Creator Svejcar, Tony J. Remove constraint Creator: Svejcar, Tony J. Degree Field Computer Science Remove constraint Degree Field: Computer Science Rights Statement In Copyright Remove constraint Rights Statement: In Copyright

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  • Integrating a parallel computer and a heterogeneous workstation cluster into a metacomputer system

    Creator:
    Neff, Tony
    Abstract:
    Two types of parallel computers commonly used or solving large scientific problems are clusters of workstations and distributed-memory multicomputers. Each system has strengths and weaknesses for this task. Workstation clusters have a high performance to cost ratio and the advantage of the latest processors. Workstations are commonly under-utilized and can...
    Resource Type:
    Capstone Project
    Full Text:
    by Tony Neff December 15, 1995 ) Abstract Two types of parallel computers commonly used for

  • Parallelism in the SPI algorithm : an investigation

    Creator:
    Fountain, Tony
    Abstract:
    The Symbolic Probabilistic Inference (SPI) algorithm was developed by Bruce D' Ambrosio for efficient calculation of prior probabilities in belief nets [2]. Although the complexity of the SPI algorithm compares favorably with other approaches to probabilistic inference [5], its actual running time is still prohibitively long even for moderately sized...
    Resource Type:
    Capstone Project
    Full Text:
    Investigation By Tony Fountain A Research Paper submitted to Oregon State University in partial

  • AI, Robot: A Rhetorical Analysis of Jeopardy! Matches Featuring IBM’s Artificial Intelligence

    Creator:
    Steele, Evan T.
    Abstract:
    The relationship between the public and new technologies has historically been a tumultuous one, with public perceptions ranging from excited rapid adoption to standoffish pessimism. In 2011, IBM tried to use competition as a means of showcasing a new technology to the public. This thesis is a work of rhetorical...
    Resource Type:
    Masters Thesis
    Full Text:
    2007, IBM began development of the prototype of Watson, Blue J. This deep learning machine would be

  • Strengths and weaknesses of Dataparallel C

    Creator:
    S, Seetharamakrishnan
    Abstract:
    Dataparallel C is a SIMD style data-parallel programming language for MIMD com­puters. Dataparallel Chas been implemented on both shared memory (Sequent) and distributed memory (Intel and nCUBE) computers. Here we analyze the strengths and weaknesses of Dataparallel C by comparing the performance of compiled Data­parallel C programs with the performance...
    Resource Type:
    Capstone Project
    Full Text:
    queries whenever I barged into his room. Tony Lapadula of the University of New Hampshire, the author of

  • Hybrid visualization of asymmetric tensor fields : glyphs and hyperstreamlines

    Creator:
    Palke, Darrel
    Abstract:
    Asymmetric tensor fields are useful for understanding fluid flow and solid deformation. They present new challenges, however, for traditional tensor field visualization techniques such as hyperstreamline placement and glyph packing. This is because the physical behavior of tensors inside real domains where eigenvalues are real is fundamentally different from the...
    Resource Type:
    Masters Thesis
    Full Text:
    give more background information. A second-order tensor T can be represented by an N ×N matrix Ti j

  • Implementation of Entity Category Relationship data model on Macintosh

    Creator:
    Maithel, Neeraj
    Resource Type:
    Capstone Project
    Full Text:
    ~~:f ( Neeraj Maithel ) March, 1988. J ) J 1. Introduction This project implements a

  • Detection and Segmentation of Bird Song in Noisy Environments

    Creator:
    Neal, Lawrence W.
    Abstract:
    Recent work in machine learning concerns the detection and identification of bird species from audio recordings of their vocalizations. Such analysis can yield valuable ecological information concerning the activity and distribution of species in the wild. Current species-identification methods require individual syllables of bird audio as input, but field-collected audio...
    Resource Type:
    Honors College Thesis
    Full Text:
    Jones, Department of Geosciences Daniel J. Arp, University Honors College I understand that my thesis

  • Computational Elucidation of the Regulatory SNPs in the Non-Coding Regions of the Human Genome

    Creator:
    Yao, Yao
    Abstract:
    We describe a series of novel computational models, CERENKOV (Computational Elucidation of the REgulatory NonKOding Variome) and its successors CERENKOV2, CERENKOV3, and Convolutional CERENKOV3, for discriminating regulatory single nucleotide polymorphisms (rSNPs) from non-regulatory SNPs within non-coding genetic loci. The CERENKOV models are designed for recognizing rSNPs in the context of...
    Resource Type:
    Dissertation

  • The density signature

    Creator:
    Migler-VonDollen, Theresa
    Abstract:
    In real networks, identifying dense regions is of great importance. For example, in a network that represents academic collaboration, authors within the densest component of the graph tend to be the most prolific. Dense subgraphs often identify communities in social networks. And dense subgraphs can be used to discover regulatory...
    Resource Type:
    Dissertation
    Full Text:
    -element subsets of V . Regina Theresa Gabriel Laura Andrew Joseph Tony Julio Anna Elijah Rebecca

  • The Familiarity Hypothesis: Explaining the Behavior of Deep Learning Methods in Out-of-Distribution Detection

    Creator:
    Guyer, Alexander
    Abstract:
    Many object recognition applications require detecting and responding to objects drawn from a different distribution from that of the training data. This task is referred to as out-of-distribution (OOD) detection, and it is often formulated as an outlier detection problem wherein the probability distribution of the known data P(X) is...
    Resource Type:
    Masters Thesis
    Full Text:
    the blurring procedure. First, define cijk as the contribution of activation j Pt1, 2, ..., Du toward