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Filtering by: Committee Member Bernell, David A. Remove constraint Committee Member: Bernell, David A. Academic Affiliation Electrical Engineering and Computer Science Remove constraint Academic Affiliation: Electrical Engineering and Computer Science

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  • Evaluating the seismic risk and resilience of an electrical power system

    Creator:
    Chalishazar, Vishvas H.
    Abstract:
    The Pacific Northwest is part of the "Ring of Fire," which is well-known for heavy seismic activity. Numerous active faults in the area have encouraged electric grid managers in the region to more deeply contemplate and proactively intervene to support grid resilience. This research introduces Monte Carlo (MC) based power...
    Resource Type:
    Dissertation
    Full Text:
    . David Bernell for the valuable inputs to my research. Thanks to all my friends, specially Dr. Anirban

  • Power Electric System Load and Generation Forecasting via ARMA, ARIMA, and K-Medoids Methods for Grid Expansion Purposes: A Comparison

    Creator:
    McLaughlin, Zachery D.
    Abstract:
    The electric power grids of countries across the globe rely on load and generation forecasting to know when, where, and how much resources need to be dispatched to sustain proper grid operation. Because of this, forecasting needs to be highly accurate to avoid unnecessary resource dispatch which can be costly....
    Resource Type:
    Capstone Project
    Full Text:
    -Medoids Methods for Grid Expansion Purposes: A Comparison. Abstract approved

  • Impacts of Prediction on Wave Energy Converter Control

    Creator:
    Comard, Colin Q.
    Abstract:
    Ocean waves provide a promising source of renewable energy for the North American electric grid. However, ideal control of wave energy converters (WECs) requires perfect forecasting of future wave conditions, and waves can be unpredictable. This paper presents a comparison of three different prediction methods and analyzes their performance in...
    Resource Type:
    Masters Thesis
    Full Text:
    provide a promising source of renewable energy for the North American electric grid. However, ideal

  • Machine Learning Methods for the Discovery and Analysis of MicroRNAs

    Creator:
    Bell, Jimmy D.
    Abstract:
    MicroRNAs are a highly conserved class of small endogenous RNA, about ~22nt in length, involved in post-transcriptional gene silencing and have prominent roles in disease and development. Though the process of microRNA discovery was once an arduous task, the advent of high throughput sequencing technology has resulted in novel microRNAs...
    Resource Type:
    Masters Thesis
    Full Text:
    : ______________________________________________________ David A. Hendrix MicroRNAs are a highly conserved class of small endogenous RNA, about

  • Improving and Understanding Deep Models for Natural Language Comprehension

    Creator:
    Ghaeini, Reza
    Abstract:
    Natural Language Comprehension is a challenging domain of Natural Language Processing. To improve a model’s language comprehension/understanding, one approach would be to enrich the structure of the model to enhance its capability in learning the latent rules of the language. In this dissertation, we will first introduce several deep models...
    Resource Type:
    Dissertation
    Full Text:
    . Fern Natural Language Comprehension is a challenging domain of Natural Language Pro- cessing. To

  • Event detection with forward-backward recurrent neural networks

    Creator:
    Ghaeini, Mohammad Reza
    Abstract:
    Automatic event extraction from natural text is an important and challenging task for natural language understanding. Traditional event detection methods heavily rely on manually engineered rich features. Recent deep learning approaches alleviate this problem by automatic feature engineering. But such efforts, like tradition methods, have so far only focused on...
    Resource Type:
    Masters Thesis
    Full Text:
    described with a phrase. In this thesis, we introduce and apply forward-backward recur- rent neural

  • Instability and temperature-dependence assessment of IGZO TFTs

    Creator:
    Hoshino, Ken
    Abstract:
    Amorphous oxide semiconductors (AOSs) are of great current interest for thin-film transistor (TFT) channel layer applications. In particular, indium gallium zinc oxide (IGZO) is under intense development for commercial applications because of its demonstrated high performance at low processing temperatures. The objective of the research presented in this thesis is...
    Resource Type:
    Masters Thesis
    Full Text:
    ) – VGS transfer curves in which the turn-on voltage, VON, moves to a more positive gate voltage with

  • Inorganic thin-film solar cells

    Creator:
    Spies, Jack Alexander
    Abstract:
    The primary objective of this thesis is to explore new absorber and p-type window layer materials for thin-film solar cell applications. A new thin-film electron beam deposition system has been installed, is now operational, and has been used to deposit several types of solar cell absorber layers. Material investigations include...
    Resource Type:
    Masters Thesis
    Full Text:
    to explore new absorber and p-type window layer materials for thin-film solar cell applications. A

  • Assessment of High Mobility Oxide Thin-Film Transistors

    Creator:
    Stewart, Kevin A.
    Abstract:
    The trend towards higher resolution, faster refresh rate active-matrix liquid-crystal displays (AMLCDs) as well as the emergence of active-matrix organic light-emitting diode (AMOLED) displays is driving the demand for amorphous oxide semiconductor thin-film transistors (AOS TFTs) with higher mobility. A physics-based model for carrier transport in an amorphous semiconductor is...
    Resource Type:
    Dissertation
    Full Text:
    AN ABSTRACT OF THE DISSERTATION OF Kevin A. Stewart for

  • Al-In-Sn-O thin-film transistors

    Creator:
    Stewart, Kevin A.
    Abstract:
    The aim of the research undertaken for this thesis was to develop a new high-performance amorphous oxide semiconductor (AOS) for use as a channel layer in a thin-film transistor (TFT). AOS TFTs offer higher electron mobility than the established amorphous silicon based technology. A new channel material comprised of aluminum...
    Resource Type:
    Masters Thesis
    Full Text:
    THESIS OF Kevin A. Stewart for the degree of Master of Science in Electrical and Computer Engineering