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Filtering by: Creator Muyanja, Andrew W. Remove constraint Creator: Muyanja, Andrew W. Academic Affiliation Electrical Engineering and Computer Science Remove constraint Academic Affiliation: Electrical Engineering and Computer Science

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  • Test fixture characterization for high-frequency silicon substrate parasitic extraction

    Creator:
    Tabalujan, Andrew R.
    Abstract:
    At frequencies exceeding 1-2 GHz, the reactive nature of a silicon substrate must be accounted in the substrate network models used in substrate coupling simulation. High-frequency substrate models, containing reactive components, must be validated through high-frequency network analyzer measurements. Prior fabricated test fixtures have been modified to enable high-frequency (up...
    Resource Type:
    Masters Thesis
    Full Text:
    AN ABSTRACT OF THE DISSERTATION OF Andrew R. Tabalujan for the

  • 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:
    AN ABSTRACT OF THE THESIS OF Andrew Emmott for the

  • 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:
    /thesis.dvi AN ABSTRACT OF THE THESIS OF Ethan W. Dereszynski for the degree of Masters of Science in

  • Open Set Learning with Counterfactual Images

    Creator:
    Neal, Lawrence W.
    Abstract:
    In open set recognition, a classifier must label instances of known classes while detecting instances of unknown classes not encountered during training. To detect unknown classes while still generalizing to new instances of existing classes, this thesis introduces a dataset augmentation technique called counterfactual image generation. This approach, based on...
    Resource Type:
    Masters Thesis
    Full Text:
    , Karen Simonyan, Oriol Vinyals, Alex Graves, Nal Kalchbrenner, Andrew W Senior, and Koray Kavukcuoglu

  • Toward computer vision for understanding American football in video

    Creator:
    Hess, Robin W.
    Abstract:
    In this work, I examine the problem of understanding American football in video. In particular, I present several mid-level computer vision algorithms that each accomplish a different sub-task within a larger system for annotating, interpreting, and analyzing collections of American football video. The analysis of football video is useful in...
    Resource Type:
    Dissertation
    Full Text:
    AN ABSTRACT OF THE DISSERTATION OF Robin W. Hess for the

  • Efficient Algorithms for Robust Spatiotemporal Data Analysis

    Creator:
    Moore, Travis W.
    Abstract:
    Many large-scale data analysis applications involve data that can vary over both time and space. Often the primary goal of analyzing spatiotemporal data is identifying trends, movements, and sudden changes with respect to time, location, or both. This can include a variety of applications in economics (housing prices, unemployment, job...
    Resource Type:
    Dissertation
    Full Text:
    update as Zt+1 = QtRt + v′Xi = Q t(Rt +w′Xi) (2.12) where w′ = (Qt)−1v′ = (Qt)′v′. Our goal is to turn

  • Random number generation on handheld devices for cryptographic applications

    Creator:
    Montville, Adam W.
    Abstract:
    Random number generation is important in many fields today. It is particularly important in the field of cryptography when generating nonce values, cryptographic keys, and other data required in many cryptographic applications. The proliferation of small, handheld devices that are typically connected to large networks via a wireless connection requires...
    Resource Type:
    Masters Thesis
    Full Text:
    AN ABSTRACT OF THE THESIS OF Adam W. Montville for the degree

  • 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

  • Automatic program generation for scientific computing

    Creator:
    Fu, Zhe
    Abstract:
    The code reuse problem is a common software engineering problem in scientific computing. As a prevailing programming language in many scientific fields, Fortran does not provide support to address this problem. One particular reason is that Fortran lacks the support for generic programming. By applying program-generation techniques, we developed two...
    Resource Type:
    Dissertation

  • Algorithms for massive biological datasets

    Creator:
    Bryant, Douglas W. (Douglas Wesley)
    Abstract:
    Within the past several years the technology of high-throughput sequencing has transformed the study of biology by offering unprecedented access to life's fundamental building block, DNA. With this transformation's potential a host of brand-new challenges have emerged, many of which lend themselves to being solved through computational methods. From de...
    Resource Type:
    Dissertation
    Full Text:
    AN ABSTRACT OF THE DISSERTATION OF Douglas W. Bryant, Jr. for