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Filtering by: Graduation year 2023 Remove constraint Graduation year: 2023 Academic Affiliation Electrical Engineering and Computer Science Remove constraint Academic Affiliation: Electrical Engineering and Computer Science Degree Level Master's Remove constraint Degree Level: Master's

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  • 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:
    15th, 2023. Title: Power Electric System Load and Generation Forecasting via ARMA, ARIMA, and K

  • SpotFinder

    Creator:
    Dhume, Shreya
    Abstract:
    SpotFinder is the mobile frontend of a parking system that helps drivers find a parking spot on campus. (The backend piece of the parking system was developed by others in the lab as part of a previous project.) Finding parking can be viewed as both a search problem and a...
    Resource Type:
    Capstone Project
    Full Text:
    of Science in Computer Science Presented August 25, 2023 Commencement 2023 ABSTRACT OF THE

  • Awgsome Fault Injection: In-Depth Analysis of Waveform Generation for Voltage Glitches

    Creator:
    Lyakhov, Stanislav
    Abstract:
    Voltage fault injection is a technique to disrupt power supply, such that the data or instruction flow in a microcontroller can be modified. Recently, a new class of voltage glitches was introduced termed arbitrary wave voltage glitches. Despite its demonstrated success in practical studies it comes with additional challenges, such...
    Resource Type:
    Masters Thesis
    Full Text:
    degree of Master of Science in Computer Science presented on May 31, 2023. Title: Awgsome Fault

  • On the domain generalizability of RF fingerprints through multifractal dimension representation

    Creator:
    Johnson, Benjamin
    Abstract:
    RF data-driven device fingerprinting through the use of deep learning has recently surfaced as a possible method for secure device identification and authentication. Traditional approaches are commonly susceptible to the domain adaptation problem where a model trained on data from one domain performs badly when tested on data from a...
    Resource Type:
    Masters Thesis
    Full Text:
    the degree of Master of Science in Electrical and Computer Engineering presented on July 24, 2023

  • Staying Consistent: Discipline-Specific Language Used in Introductory CS Curricula

    Creator:
    Weber, Jason
    Abstract:
    The understanding of Discipline-Specific Language is an important competency for students of any field to begin mastering early in their studies, since it serves as a prerequisite for both the analysis of expert text and precise communication. Therefore, an introductory curriculum should pay careful attention to how it incorporates, defines,...
    Resource Type:
    Masters Thesis
    Full Text:
    of Master of Science in Computer Science presented on June 13, 2023. Title: Staying Consistent

  • LabelFlicks

    Creator:
    Ruangrotsakun, Chalida
    Abstract:
    Using supervised machine learning (ML) to train a computer vision model typically requires human annotators to label objects in images and video. Given a large training dataset, this can be labor intensive, presenting a significant bottleneck in the model-development process. LabelFlicks is an open-source desktop application that aims to address...
    Resource Type:
    Capstone Project
    Full Text:
    of Master of Science in Computer Science Presented September 1, 2023 Commencement 2023 ABSTRACT

  • Characterizing spin-orbit torques in β-W/Ta/CoFeB/MgO devices

    Creator:
    Allen, Shane R.
    Abstract:
    Materials with a strong spin Hall effect and Rashba-Edelstein effect have the potential to improve the efficiency of solid-state magnetic memory technologies and other magnetic logic devices. Heavy metals have been identified as having these properties, including the beta crystal phase of tungsten. In this work, we determine the strength...
    Resource Type:
    Masters Thesis
    Full Text:
    for the degree of Master of Science in Electrical and Computer Engineering presented on March 9, 2023

  • Modeling of Wave Energy Converter via Instantaneous Frequency

    Creator:
    Kim, Inyong
    Abstract:
    A multidisciplinary perspective is necessitated for the analysis of wave energy conversion systems, spanning hydrodynamics, mechanics, electric power, and control systems. The complexity inherent in these scientific domains poses challenges for unified analysis. This paper addresses these challenges by connecting various domains through the application of circuit theory, characterizing the...
    Resource Type:
    Masters Thesis
    Full Text:
    of Master of Science in Electrical and Computer Engineering presented on December 6, 2023. Title

  • Systematic Codes for Correcting Deletion/Insertion of One Zero in Each and Every Bucket of Zeros

    Creator:
    Vu, Hoang
    Abstract:
    In this thesis, we propose a systematic code for correcting t = 1 insertion/deletion errors of the character ”0” that can occur between any two consecutive 1’s in a binary string. The code requires balanced input strings, where each word of length n contains ⌈n/2⌉ 0’s and ⌊n/2⌋ 1’s. This...
    Resource Type:
    Masters Thesis
    Full Text:
    degree of Master of Science in Computer Science presented on September 11, 2023. Title: Systematic

  • 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:
    degree of Master of Science in Computer Science presented on May 31, 2023. Title: Partitioning-Guided K