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Filtering by: Creator Chen, Tsung-Wen Remove constraint Creator: Chen, Tsung-Wen Decade 2020-2029 Remove constraint Decade: 2020-2029

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  • Predicting and Improving Throughput, Responsiveness and Battery Life of Computer Systems by Machine Learning

    Creator:
    Li, Yunfan
    Abstract:
    The Machine Learning (ML) algorithms are increasingly explored in varies of fields including designing and optimizing computer systems. Recent research, such as optimizing memory/cache prefetching by ML training or predicting traffic pattern in throughput processors, also exhibits a promising future of introducing ML into computer system design and optimization. Throughput...
    Resource Type:
    Dissertation
    Full Text:
    approved: Lizhong Chen The Machine Learning (ML) algorithms are increasingly explored in varies of

  • Mental Health in Eastern Europe during the COVID-19 Pandemic: A Systematic Review and Meta-Analysis of Depression and Anxiety

    Creator:
    Miller, Saylor O.
    Abstract:
    Objective: To perform a systematic review and meta-analysis on the prevalence rate of mental health disorders including anxiety, depression, and insomnia during the COVID-19 pandemic in Eastern Europe in the general population, as well as within select sub-populations (i.e., students, general healthcare workers, and frontline workers). Data sources: Articles in PubMed,...
    Resource Type:
    Honors College Thesis
    Full Text:
    -analysis study: Jiyao Chen, Stephen X. Zhang, Roger S. McIntyre, Wen Xu, Allen Yin, Bryan Z. Chen, Andrew

  • A case for application-based linear transformers : applied towards text-to-spectrogram

    Creator:
    Agostinelli, Victor
    Abstract:
    Various natural language processing (NLP) tasks necessitate deep models that are fast, efficient, and small based on their ultimate application at the edge or elsewhere. While significant investigation has furthered the efficiency and reduced the size of these models, reducing their downstream latency without significant trade-offs remains a difficult task....
    Resource Type:
    Masters Thesis
    Full Text:
    approved: Lizhong Chen Various natural language processing (NLP) tasks necessitate deep models that are

  • Chromium Phillips Catalyst on Tin Oxide Substrate: Deposition and Characterization

    Creator:
    Chen, Di
    Abstract:
    In order to synthesize polyethylene by the microreactor with a catalyst, this thesis prepares the chemical coating layers for the reactor channel. There are two layers in the channel: the Phillips catalysts and an antimony-doped tin oxide layer on glass substrate. The Phillips catalyst help to synthesize polyethylene in the...
    Resource Type:
    Masters Thesis
    Full Text:
    ABSTRACT OF THE THESIS OF Di Chen for the degree of Master of Science in Chemical Engineering

  • Towards Direct Simultaneous Speech Translation

    Creator:
    Chen, Junkun
    Abstract:
    Simultaneous speech translation (SimulST) is widely useful in many cross-lingual communication scenarios, including multinational conferences and international traveling. Since text-based simultaneous machine translation (SimulMT) has achieved great success in recent years. The conventional cascaded approach for SimulST uses a pipeline of streaming ASR followed by simultaneous MT but suffers from...
    Resource Type:
    Dissertation
    Full Text:
    AN ABSTRACT OF THE DISSERTATION OF Junkun Chen

  • Understanding Charge and Mass Transfer Phenomena in Functional Oxide Heterostructures

    Creator:
    Samarakoon, Widitha
    Abstract:
    Oxides are a versatile class of materials with a wide range of electronic, optical, and magnetic properties. This makes them ideal for use in a multitude of functional devices for oxide electronics, electrochemical conversion, and storage. The overall performance of these devices is governed by atomic scale charge and mass...
    Resource Type:
    Dissertation
    Full Text:
    committee members, Prof. Liney Arnadottir, Dr. Kelsey Stoerzinger and Dr. Tianyi Chen. Thank you very much

  • Care Team Burnout in Human and Veterinary Medicine

    Creator:
    Alshaiji, Rawan
    Abstract:
    Medical professionals experience higher rates of burnout than other professions due to the highly stressful nature of their environment. In 2018, 94 percent of physicians reported experiencing burnout – characterized by emotional fatigue, and feelings of depersonalization and low personal accomplishment – at some point in their careers. As emotional...
    Resource Type:
    Dissertation
    Full Text:
    , McCreery & Chen (2012)21

  • Graph Imitation Learning for Optimal Joint Beamforming and Antenna Selection

    Creator:
    Shrestha, Sagar
    Abstract:
    Transmit beamforming is an important technique employed to improve efficiency and signal quality in wireless communication systems by steering signals towards their in- tended users. It often arises jointly with the antenna selection problem due to various reasons, such as limited number of radio frequency (RF) chains and energy/resource effi-...
    Resource Type:
    Masters Thesis

  • A Novel CCRW Receiver with Variable Width Window for Mitigating Multipath and Ambiguity in GNSS Positioning

    Creator:
    Alhussein, Fahad
    Abstract:
    This work presents a novel CCRW receiver that utilizes a window of variable width, for e˙ectively mitigating multipath and ambiguity in both civil and military positioning applica-tions using Global Navigation Satellite Systems (GNSS). This CCRW receiver incorporates a single stroboscopic window, whose width is iteratively reduced until the e˙ect of...
    Resource Type:
    Dissertation

  • Leveraging Structures of the Data in Deep Learning

    Creator:
    Li, Xingyi
    Abstract:
    The performance of deep learning frameworks could be significantly improved through considering the particular underlying structures for each dataset. In this thesis, I summarize our three work about boosting the performance of deep learning models through leveraging structures of the data. In the first work, we theoretically justify that, for...
    Resource Type:
    Dissertation
    Full Text:
    , Xinyao Wang, Neale Ratzlaff, Xin Li, Bob DeBortoli, Hung Nguyen, Weikun Han, Wenxuan Wu, Zehuan Chen