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Filtering by: Creator Prueitt, Sara C. Remove constraint Creator: Prueitt, Sara C. Academic Affiliation Electrical Engineering and Computer Science Remove constraint Academic Affiliation: Electrical Engineering and Computer Science

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  • The Impact of Network Topology on Software Defined Network Performance

    Creator:
    Alhamar, Sara N.
    Abstract:
    Software Defined Network (SDN) is a new networking concept in which the data plane is decoupled from the control plane. Due to the huge demand on network resources and the rapidly increasing numbers of devices needing to be connected to the network, SDN paradigm has emerged as a potential solution...
    Resource Type:
    Masters Thesis
    Full Text:
    Microsoft Word - Sara Alhamar Thesis-Final Draft-updated.docx

  • Quantum dots-fullerene based molecular beacons for highly sensitive DNA detection

    Creator:
    Liu, Ye
    Abstract:
    We demonstrated a low-cost and high-sensitivity DNA detection method using quantum dot-fullerene based molecular beacons (MBs) and magnetic nanoparticles. The MB tethered magnetic nanoparticles can be well dispersed in analytes for efficient DNA capture and concentrated by an external magnetic field for enhanced fluorescence signal detection. The detection requires only...
    Resource Type:
    Masters Thesis
    Full Text:
    illumination of the QD caused by FRET between Cy5 acceptors and a QD donor in a nanosensor assembly. (c

  • People Counting System Using MmWave MIMO Radar with 3D Convolutional Neural Network

    Creator:
    Shih, Cheng-Che
    Abstract:
    Recent advances in computing, communication, and artificial intelligence (AI) technologies have made our world more interconnected and data-rich than ever with the proliferation of smart devices and sensors. As a result, we are increasingly dependent on electronic devices and sensors to automate away life’s mundane parts. For example, in business...
    Resource Type:
    Masters Thesis
    Full Text:
    a temperature range from -20◦C to 60◦C. There are 4 receive and 3 transmit onboard antennas. Each

  • Imperative Programming with Variational Effects

    Creator:
    Grasley, Alexander B.
    Abstract:
    Variation is a commonly encountered element of modern software systems. Recent research into variation has led to increasing interest in the development of variational programming languages and corresponding variational models of execution. Variational imperative languages pose a particular challenge due to the complex interactions between side effects and variation. The...
    Resource Type:
    Masters Thesis
    Full Text:
    and foremost I want to thank my wife, Sara, without whom this certainly would not have been possible

  • Partitioning-Guided K-Means for Effective Empty Cluster Resolution in Extreme Model Compression

    Creator:
    Huang, Tianhong
    Abstract:
    Compactness in deep learning can be critical to a model’s viability in low-resource applications, and a common approach to extreme model compression is quantization. We consider Iterative Product Quantization (iPQ) with Quant-Noise [Fan et al., 2020] to be state-of-the-art in this area, but this quantization framework suffers from preventable inference...
    Resource Type:
    Masters Thesis
    Full Text:
    into some m vectors per column c, with m × c total vectors. All of these vectors share the same layer

  • Redesigning the Structure and Access Paths of Databases for Effective and Efficient Query Processing

    Creator:
    Ghadakchi, Vahid
    Abstract:
    Many database users are not familiar with formal query languages, the concept of schema, or the exact content of their database. Thus, it is challenging for these users to formulate their information needs over semi-structured and structured databases. To address this problem, researchers have proposed usable query interfaces over which...
    Resource Type:
    Dissertation
    Full Text:
    of query processing over large databases. c©Copyright by Vahid Ghadakchi December 10, 2019 All

  • Enabling Virtual Globes for A Visual-Auditory User Experience of Spatial Data

    Creator:
    Gune, Aditya N.
    Abstract:
    Geographical datasets are large, complex, and can be difficult for users to navigate and derive meaning from. These datasets, as well as the unique insights derived from them, provide tremendous opportunity for social change -- many of the global challenges humankind is currently facing can benefit from analytics or visualization...
    Resource Type:
    Masters Thesis
    Full Text:
    variety of datasets and application models to tackle a wide range of real-world challenges. c©Copyright

  • Causal Structure Learning from Experiments and Observations

    Creator:
    Sinha, Meghamala
    Abstract:
    In this research, we address the problem of learning a single causal network structure from multiple dataset generated from different experiments. The experiments can be observational or interventional. We assume that each dataset is generated by an unknown causal network altered under different experimental conditions (interventions, manipulation or perturbation). As...
    Resource Type:
    Masters Thesis
    Full Text:
    interventions. c©Copyright by Meghamala Sinha March 22, 2019 All Rights Reserved Causal Structure

  • Using Web Services for Image Processing in a Desktop Widgets Engine

    Creator:
    Le, Hien
    Abstract:
    Desktop widget engines have emerged as an alternative for completing simple tasks without the need for a full-blown application or constant user interaction. Widgets can simply display data in a compact and visually appealing manner (such as stock tickers, weather forecasts, and news notifications), or go so far as to...
    Resource Type:
    Capstone Project
    Full Text:
    decentralized system. c©Copyright by Hien Le June 14, 2007 All Rights Reserved Using Web Services for

  • 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:
    inhibitor); and (c) our method “Learn and Vote” analysed on the same experiments as in the middle panel (b