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Filtering by: Creator Dickson, David J. Remove constraint Creator: Dickson, David J. Committee Member Tadepalli, Prasad Remove constraint Committee Member: Tadepalli, Prasad

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  • 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

  • Pedestrian distraction : pedestrian behaviors at midblock crossings considering geometric and environmental conditions

    Creator:
    Kautz, Julia Anne
    Abstract:
    Pedestrian distraction at roadway crossings has been correlated with a higher risk of pedestrian-vehicle collisions due to the pedestrian's cognitive, visual, and motor attention being drawn to a wide variety of secondary tasks. This study is different from previous field studies of pedestrian midblock crossings in that the geometric layout...
    Resource Type:
    Masters Thesis
    Full Text:
    : ______________________________________________________ David S. Hurwitz Pedestrian distraction at roadway crossings has been correlated with a

  • 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

  • Reaction Pathways of Oxo-Hydroxo Group 5 Clusters to Metal Oxide Thin Films

    Creator:
    Mansergh, Ryan H.
    Abstract:
    Oxo-hydroxo Group 5 metal clusters are an untapped resource to study and advance aqueous solution processing of metal oxide thin films. The tetramethylammonium (TMA) hexatantalate salt (TMA6[H2Ta6O19]) yields dense Ta2O5 films (~95% of the bulk ß-Ta2O5 density) with atomically smooth surfaces (<4 Å root mean square surface roughness). This same...
    Resource Type:
    Dissertation
    Full Text:
    . Abstract approved: _____________________________________________________ Douglas A. Keszler Brady J

  • Investigation of automatic construction of reactive controllers

    Creator:
    Westerberg, Caryl J.
    Abstract:
    In real-time control systems, the value of a control decision depends not only on the correctness of the decision but also on the time when that decision is available. Recent work in real-time decision making has used machine learning techniques to automatically construct reactive controllers, that is, controllers with little...
    Resource Type:
    Masters Thesis
    Full Text:
    controllers AN ABSTRACT OF THE THESIS OF Caryl J. Westerberg for the degree of Masters of Science in

  • Nonuniform Sampling Of Band-limited Functions

    Creator:
    Al-Hammali, Hussain Y.
    Abstract:
    In this thesis, we will study certain generalizations of the classical Shannon Sampling Theorem, which allows for the reconstruction of a pi-band-limited, square-integrable function from its samples on the integers. J. R. Higgins provided a generalization where the integers can be perturbed by less than 1/4, which includes nonuniform and...
    Resource Type:
    Dissertation
    Full Text:
    . J. R. Higgins provided a generalization where the integers can be perturbed by less than 1/4, which

  • Object highlighting : real-time boundary detection using a Bayesian network

    Creator:
    Jia, Jin
    Abstract:
    Image segmentation continues to be a fundamental problem in computer vision and image understanding. In this thesis, we present a Bayesian network that we use for object boundary detection in which the MPE (most probable explanation) before any evidence can produce multiple non-overlapping, non-self-intersecting closed contours and the MPE with...
    Resource Type:
    Masters Thesis
    Full Text:
    thank Professor Ron Metoyer, Professor Prasad Tadepalli and Professor David Birkes for being on my

  • Analytical Methods for Improving Causal Inference

    Creator:
    Sinha, Meghamala
    Abstract:
    Causal inference is an important analytical tool to bridge the gap between prediction and decision-making. However, learning a causal network solely from data is a challenging task. In this work, various techniques have been explored for a better and improved causal network learning from data. Firstly, the problem of learning...
    Resource Type:
    Dissertation
    Full Text:
    distribution of p after intervention is: p(V1, ..., Vn) = ∏ Vi∈Oe pi(Vi | Pa(Vi)) · ∏ Vj∈Ie p′j(Vj | Pa(Vj

  • A Distributed Scheme for Accelerating and Scaling PSPNet

    Creator:
    Krishna, Ajay
    Abstract:
    Advances in deep learning based image processing have led to their adoption for a wide range of applications, and in tow with these developments is a dramatic increase in the availability of high quality datasets. With this comes the need to accelerate and scale deep learning applications in order to...
    Resource Type:
    Masters Thesis
    Full Text:
    thesis committee, Dr. Prasad Tadepalli and Dr. David Roundy, for their insightful comments and timely