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Filtering by: Creator Gutmann, Ethan D. Remove constraint Creator: Gutmann, Ethan D. Degree Field Computer Science Remove constraint Degree Field: Computer Science

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  • A probabilistic model for anomaly detection in remote sensor streams

    Creator:
    Dereszynski, Ethan W.
    Abstract:
    Remote sensors are becoming the standard for observing and recording ecological data in the field. Such sensors can record data at fine temporal resolutions, and they can operate under extreme conditions prohibitive to human access. Unfortunately, sensor data streams exhibit many kinds of errors ranging from corrupt communications to partial...
    Resource Type:
    Masters Thesis
    Full Text:
    C:/Documents and Settings/Ethan/My Documents/MS_Thesis/writeup

  • Probabilistic models for quality control in environmental sensor networks

    Creator:
    Dereszynski, Ethan W.
    Abstract:
    Networks of distributed, remote sensors are providing ecological scientists with a view of our environment that is unprecedented in detail. However, these networks are subject to harsh conditions, which lead to malfunctions in individual sensors and failures in network communications. This behavior manifests as corrupt or missing measurements in the...
    Resource Type:
    Dissertation
    Full Text:
    AN ABSTRACT OF THE DISSERTATION OF Ethan W. Dereszynski for

  • The Development of Computational Methods for Studying Plant-Pathogen Interactions

    Creator:
    Pankow, Rebecca C.
    Abstract:
    Modern technology has enabled the advancement of biological research through the use of powerful machines and computers as well as innovative computer programs. Advances in sequencing technology and software enable us to make de novo assemblies of organism genomes, and the development of specialized computer programs can automate routine but...
    Resource Type:
    Honors College Thesis
    Full Text:
    soil bacterium with an integrated T3SS-encoding region (EtHAn), and EtHAn carrying the type III

  • Anomaly Detection and Probabilistic Diagnosis for Automated Data Quality Control

    Creator:
    Zemicheal, Tadesse H.
    Abstract:
    Advances in sensor technology are greatly expanding the range of quantities that can be measured while simultaneously reducing the cost. However, deployed sensors drift out of calibration and fail, so every sensor network requires quality control procedures to promptly detect these failures. To address these problems, we propose a two-level...
    Resource Type:
    Dissertation
    Full Text:
    capture, the interaction of different sensors at given weather station. 13 (d) Single variable over

  • Uncertainty in Deep Learning with Implicit Neural Networks

    Creator:
    Ratzlaff, Neale
    Abstract:
    The ability to extract uncertainties from predictions is crucial for the adoption of deep learning systems to safety-critical applications. Uncertainty estimates can be used as a failure signal, which is necessary for automating complex tasks where safety is a concern. Furthermore, current deep learning systems do not provide uncertainty estimates,...
    Resource Type:
    Dissertation
    Full Text:
    Diversity . . . . . . . . . . . . . . . . 33 4.3.3 1-D Regression

  • The Analysis of First Year Computer Science Design Documents

    Creator:
    Ernst, Shannon S.
    Abstract:
    Computer science is, at its core, about solving problems. The "Carry out the Plan" portion of problem solving is often examined and emphasized in CS 1 and CS 2, forgetting to emphasize the other important aspects of the problem solving process. This study focuses on the other problem-solving steps, which...
    Resource Type:
    Masters Thesis
    Full Text:
    ………………………………………………………………….. 40 Appendix D………………………………………………………………….. 47 LIST OF

  • Visualization and analysis of sensor data for detecting microclimate cold air pools

    Creator:
    Singh, Satpreet Harcharan
    Abstract:
    Cold air pools are spatiotemporal phenomena that occur when cold air from higher elevations roll down the slope to accumulate in lower elevations. Behaviors like this lead to microclimate anomalies such as the city of Corvallis (Oregon) experiencing persistent cold weather even on a sunny day. We analyze multivariate temperature...
    Resource Type:
    Masters Thesis

  • Incorporating and Learning Behavior Constraints for Sequential Decision Making

    Creator:
    Pinto, Jervis
    Abstract:
    Writing a program that performs well in a complex environment is a challenging task. In such problems, a method of deterministic programming combined with reinforcement learning (RL) can be helpful. However, current systems either force developers to encode knowledge in very specific forms (e.g., state-action features), or assume advanced RL...
    Resource Type:
    Dissertation
    Full Text:
    OSU. I’m very grateful to the occupants of KEC 2048 over the years: Neville Mehta, Ethan Dereszynski

  • Source-Routed Multicast Schemes for Large-Scale Cloud Data Center Networks

    Creator:
    Alqahtani, Jarallah Ali m
    Abstract:
    Data centers (DCs) have been witnessing unprecedented growth in size, number and complexity in recent years. They consist of tens of thousands of servers interconnected by fast network switches, hosting and enabling numerous applications with various traffic characteristics and requirements. As a result, DC networks have been presented with several...
    Resource Type:
    Dissertation
    Full Text:
    downstream traffic cost (d=5000): a) pod-based, b) leaf- based and c) random

  • A Benchmarking Study of Unsupervised Anomaly Detection Algorithms

    Creator:
    Emmott, Andrew F.
    Abstract:
    It is common practice in the unsupervised anomaly detection literature to create experimental benchmarks by sampling from existing supervised learning datasets. We seek to improve this practice by identifying four dimensions important to real-world anomaly detection applications --- point difficulty, clusteredness of anomalies, relevance of features, and relative frequency of...
    Resource Type:
    Masters Thesis
    Full Text:
    . . . . . . . . . . . . . . . 101 D Our Implementation of KLR . . . . . . . . . . . . . . . . . . . . . . . 102 E Parameterizing