Digital Commons Network^™

A Framework For Reliable Domain Ai: Knowledge-Grounded Data And Logic-Graph Reasoning, Yangxiao Bai

Electronic Theses and Dissertations

Large language models (LLMs) perform well on general tasks, yet their deployment in specialized, high-stakes domains such as public health remains unreliable. Models hallucinate facts, combine multi-step evidence incorrectly, and retrieve context that corrupts downstream reasoning. Three root causes underlie these failures: training data that underrepresents rare but critical domain themes, reasoning that is opaque and unverifiable, and evidence use that cannot be re-checked when the evidence changes. This dissertation addresses all three. First, we introduce HDBSCAN_SSA, a coarse-to-fine topic-modeling pipeline that couples density-based clustering with a novel Semantic Seed Aggregation algorithm. Using samples drawn from a larger corpus of …

Spatio-Temporal Demand Forecasting For Optimizing Electric Vehicle Charging Network Operations, Subhamyu Mani Nepal

Electronic Theses and Dissertations

The primary objective of this thesis is to create a framework for modeling, forecasting Electric Vehicle load demand and optimizing the EV charging network operation for Charging network operators. As EV’s popularity grows accurate forecasting of EV charging demand and its effect on the distribution network is critical for the efficient planning and operation of charging infrastructure, as well as for enabling Charging Network Operators to participate effectively in wholesale electricity markets. The first part of the work develops Mt /M/1 & Mt /M/c queuing models calibrated using real-world EV charging data to characterize station-level operations under time-varying arrival rates. …

Page Evidence Promotion For Open-Domain Multimodal Document Question Answering, Abdolhossein Erfanshekooh

Electronic Theses and Dissertations

Open-domain multimodal document question answering requires retrieving a small set of answer-bearing pages from a large document collection before a vision-language model can generate an answer. Although modern retrieval systems may return hundreds or thousands of candidate pages, the answer model typically receives only the highest-ranked few. Consequently, relevant evidence may already be present in the candidate pool yet remain unavailable to the answer model because it is ranked below the reader cutoff. This thesis identifies this retrieval-to-reader gap as a page evidence promotion problem and proposes a framework for diagnosing and addressing it. First, page-level pseudo-supervision is derived from …

Integration Of Ders Volt-Var Dynamic Constraint Into Time-Coupled Optimal Power Flow For System Stability, Shadrack T. Asiedu

Electronic Theses and Dissertations

The transition toward power systems with higher levels of inverter-based generation requires operating models that account for the dynamic support available from distribution-connected resources. Although inverter-based DERs can provide fast reactive-power support through functions such as Volt–VAR control, conventional optimal power flow models generally represent these resources as static power injections. In addition, transmission-level dispatch commonly represents the downstream distribution system as an aggregated load and does not explicitly consider the voltage at the point of common coupling. Consequently, an OPF solution may satisfy the transmission-bus voltage constraints while producing an operating point at which the downstream DERs do not …

Computational Fluid Dynamics Simulation Of In-Situ Plasma- Assisted Cold Spray, Lucas Degen

Electronic Theses and Dissertations

Cold spray is a solid-state form of additive manufacturing with high versatility and widespread applicability, especially in relation to metal coatings. Many applications exist within the fields of aerospace, defense and energy systems to obtain sustainable, temperature and corrosion resistant, robust coatings. High-strength alloys and refractory metals generally encounter challenges with regards to cold spray coating adhesion and overall deposition efficiency. Heat induced methods of post-processing or in-situ treatment have been explored to encourage particle softening in the cold spray plume, as well as coating recrystallization to enhance material properties. These approaches have primarily been limited to an experimental approach, …

Fast And Sustainable Video Anomaly Detection With Continual Learning, Preethi Amasa

Electronic Theses and Dissertations

Real-time video anomaly detection systems deployed in surveillance, healthcare, and industrial environments face continuous distribution shifts in lighting, viewpoint, and activity patterns. Existing models often experience performance degradation under these conditions and may suffer catastrophic forgetting when adapting to new environments. This thesis proposes RegiGrow, a parameter-efficient continual adaptation framework built on the Flashback retrieval pipeline. RegiGrow integrates Mixture-of-Experts Low-Rank Adaptation into a frozen ImageBind encoder, enabling sequential domain adaptation without modifying the pretrained backbone. A lightweight router maps visual regime features to a distribution over LoRA experts, each specializing in a distinct normal operating regime. The central contribution is …

The Spacetime Finite Element Method For Investigations Into Physics Ghost Systems And Time Parallel Preconditioning, Jax Wysong

Electronic Theses and Dissertations

This work operates on two fronts, focusing on interesting physical phenomena before turning our attention to an interesting numerical math problem. First, using the spacetime finite element method (FEM), we investigate a PDE system consisting of two Klein Gordon equations, which are coupled nonlinearly through the potential energy. The system contains a ghost (negative kinetic energy term). Systems such as these are generally deemed physically unstable, resulting in infinite energy in finite time. However, recent work has shown that this is not always the case. We investigate multiple scenarios arising from different initial conditions to characterize if/when a ghost system …

Feasibility Study For Lithium Mining In South Dakota, Neha Karna

Electronic Theses and Dissertations

The increasing demand for lithium in the battery manufacturing industry, boosted by the growth of electric vehicles and smartphones, has led to concern over its sustainable supply chain in the United States. Historically, South Dakota has played a significant role in U.S. lithium production. The recent surge of interest in lithium exploration in South Dakota, specifically Black Hills, underscores the importance of evaluating the feasibility of lithium mining in Black Hills. This research aims to study the economic feasibility of a lithium mining operation in Black Hills, South Dakota. Our specific objective is to estimate cut-off grade using Lane’s model …

Bridging Language And Game Worlds: Semantic Representations And Text-Driven Terrain Generation For Procedural Content, Zhongyu Xie

Electronic Theses and Dissertations

Procedural Content Generation (PCG) systems produce vast quantities of game levels, terrain, and environments, but lack semantic interfaces: no shared vocabulary exists between natural language, designer intent, and the structured representations generators operate on. This thesis addresses the language-content grounding gap in PCG through two complementary studies spanning semantic analysis and semantic synthesis. The first study introduces a group-supervised contrastive learning framework for semantic representation of symbolic PCG maps under many-to-one semantics, where visually distinct maps may share the same design intent. The framework combines parameter-guided semantic grouping, LLM-based caption augmentation, and a multi-positive contrastive objective that aligns language with …

Towards Energy Access For All: Developing The Lived Energy Experience Index (Leei), Kentina Annie Ishimwe

Electronic Theses and Dissertations

Energy is the fuel that powers the engine of civilization. Energy access metrics ensure that nations continuously work towards providing access for all. However, the prevalent binary indicator fails to consider that energy needs to be usable, accessible, affordable, and reliable. As a result, numerous tiered and multidimensional metrics, such as the Multi-Tier Framework, came about to bridge the gap but proved to be complex and complicated to implement. This study presents the existing literature review, assesses the limitations of current energy access measurement frameworks, and compares household energy needs with reported access statistics. Based on the findings, the Lived …

Sustainable State: A Location-Based Analysis Of Recycling Habits On A University Campus, Valentyna Labrie

Electronic Theses and Dissertations

Universities are mini communities for the younger generation. Their role in advancing sustainable waste management practices is very valuable. That is why it is crucial to promote pro-environmental behavior, monitor consistent sorting accuracy, and maintain positive recycling indicators such as contamination and diversion rates. The research aim was to explore the impact of spatial context and visual communication strategies on recycling accuracy, contamination, and diversion rates at South Dakota State University (SDSU). The research analysed the impact of proximity to food service areas on waste composition. Another research interest was the impact of educational signage and stickers on recycling behavior …

Holding The Line On Academic Freedom In Law School Clinics, Ty Alper, Praveen Kosuri, Beth Lyon, Alicia E. Plerhoples, Laura Riley, Robin Walker Sterling

Georgetown Law Faculty Publications and Other Works

Since the emergence of modern clinical legal education, law school clinics have periodically faced political interference in their selection of clients and cases, interference that threatens clinics’ essential dual missions of training practice-ready lawyers and providing legal services to marginalized clients who would otherwise lack representation. While such pressure is not new, contemporary threats differ in scale and institutional form. Today, funding, oversight, and enforcement mechanisms are weaponized in an attempt to discipline universities, heightening institutional anxiety and prompting some universities to contemplate preemptive constraints on clinic autonomy in the name of risk management and reputational protection. This shift to …

Assessing Physiological Arousal During A Standard Versus Inverted Vigilance Task Using Heart Rate Variability, Taha Riaz

Honors Undergraduate Theses

Background: Vigilance tasks require sustained attention over long periods of time while monitoring for rare critical signals. Inverted or reverse vigilance/sustained attention response tasks (SART) may impose greater response-control demands. Although prior studies have compared these tasks behaviorally, there are fewer investigations examining whether they differ in physiological arousal as indexed by heart rate variability (HRV).

Method: Undergraduate students from UCF completed a variation of either the X-CPT (standard vigilance task) or the CPT-3 (inverted/SART) task. Electrocardiogram data was recorded continuously. Data from 40 participants were analyzed. HRV was indexed using frequency domain analysis using the low-frequency to high-frequency ratio …

Texels: A Programmable Textile Interface For Replicating Textures, Maya E. Eusebio

Honors Undergraduate Theses

Self-moving fabric interfaces have massive potential for applications in fields ranging from art to haptic feedback to deployable space structures. However, current systems of implementation face the impracticalities of bulkiness, burnout, and energy consumption on top of limiting designs that can only contract uniformly or create one pre-programmed shape. For this technology to bring the change that it promises, we must break the barriers of usability and sustainability to make it a practical choice. This thesis aims to develop a scalable model of fabric that designers, programmers, and anyone else can acquire or create with accessible materials, integrate into design …

Performance Analysis Of Sparse Neural Networks In Brain Abnormality Detection, Megan Danh

Honors Undergraduate Theses

Neuroimages have held the capability of revealing to medical professionals patterns for brain abnormalities since their development. However, more recently, these professionals and researchers are looking to use neural networks to identify these brain abnormalities through neuroimages for early detection that would allow more effective treatment. Neuroimage datasets, specifically functional magnetic resonance imaging (fMRI), are extremely large in size. This would result in their processing and training to be computationally expensive, even with smaller neural networks. Fortunately, recent pruning methods have recently emerged, where network weights and neurons are pruned to reduce computational cost without compromising too much accuracy. By …

Immigration Securitization And Educational Access: The Impact Of U.S. Immigration Policy On International Students, Cossir Carter

Honors Undergraduate Theses

This study examines the securitization of international students within the broader transformation of United States immigration policy from the post-9/11 era to the present administration. Following the September 11 attacks, immigration governance was increasingly reorganized under a national security framework, significantly altering the regulatory environment surrounding student visas. Subsequent policy shifts have intensified monitoring mechanisms and administrative controls that directly shape international students’ access to education and mobility. Given the sensitivity of immigration-related participation in the current political climate, this research employs qualitative policy analysis rather than direct student surveys. Under the Trump administration, this securitization intensified through stricter visa …

Effects Of Hydrogen Enrichment And Premixing On Flame Stability In A High-Pressure Axial-Stage Combustor, Alexandre Fernandes C. Santiago Filho

Honors Undergraduate Theses

The addition of hydrogen to conventional fuels enhances reactivity and can increase the risk of flashback in premixed gas turbine combustors. This study investigates the effects of premixing length and hydrogen concentration on flame stability in a high-pressure axial-stage combustor. Experiments were conducted at the UCF Propulsion and Energy Research Laboratory using a two-stage configuration, where the primary stage provided a high-temperature vitiated crossflow using a hydrogen-piloted, premixed methane–air mixture, and hydrogen-enriched methane–air mixtures were injected through a concentric fuel-tube injector in the axial stage. Premixing length was varied for pure hydrogen flames, and hydrogen concentration was varied at a …

Effect Of Plant-Based Vs. Standard American Diet On Cardiovascular Parameters In College Students, Timothy J. Horanic

Honors Undergraduate Theses

This study examines how adherence to different dietary patterns—specifically a plant-based diet compared to the standard American diet—can influence physiological indicators tied to cardiovascular health, including heart rate variability (HRV), blood pressure (BP), and heart rate (HR). Among these markers, HRV is considered especially sensitive to autonomic nervous system (ANS) regulation and may offer earlier insight into physiological stress or dysfunction than HR or BP alone. Although nutritional habits are widely believed to impact heart health, few investigations have focused on how specific long-term diets affect autonomic and cardiovascular metrics in healthy, college-aged adults. This study aims to investigate if …

Evaluation Of The Long-Term Sealability Performance Of Aramid Fiber Nitrile-Based Gaskets, Salome Ramirez

Honors Undergraduate Theses

The reliability of sealed, oil-filled containers is critical for maintaining the operation of high-voltage energy systems, in which the sensitive electronics need to be isolated from the cyclic conditions associated with outdoor environments. New materials bring the possibility of extending service lifetimes and maintenance intervals. Aramid fiber nitrile-based gaskets are an attractive alternative to conventional gasket choices due to their long-term stability in various environments and compatibility with porcelain, metals, and plastics. For newly designed porcelain-to-metal fittings, understanding the behavior of the candidate gasket material under realistic loading conditions is essential to ensure long-term seal integrity and equipment safety. Traditional …

Discomfort In Silence: Investigating Workplace Discrimination In Relation To Employee Disclosure Of Menopausal Health Issues, Alysia Furbish

Honors Undergraduate Theses

Menopause is a universal developmental transition for women that often coincides with peak career years, yet it remains underexamined in organizational research and is frequently treated as a private or taboo workplace topic. This lack of visibility shapes whether women feel able to disclose menopause-related challenges, seek accommodations, and access organizational support. Drawing on literature related to pregnancy and motherhood discrimination, menopause stereotypes, and disclosure literature, this study examines how symptom burden, ideal worker norms, and stigma-related identity management contribute to anticipated workplace discrimination and disclosure decisions. Data were collected via an online survey of 106 working women recruited through …

To Print A Remake: An Analysis Of Hollywood Remakes And Their Cultural Value, Connor F. Seaton

Honors Undergraduate Theses

In recent years, audiences and movie critics have expressed concern that Hollywood’s growing reliance on remakes, sequels, franchises, and similar adaptations has led to a broader worry that originality is fading from modern cinema and that the industry is instead focused on using adaptations to maximize profits. Although adaptation is often seen as a commercially driven framework for reproducing existing intellectual property in a new media format, this thesis argues that it should be recognized as an autonomous cultural category with its own artistic, historical, and social significance and merit. By analyzing adaptation scholarship and reviewing its complex historical development, …

The Role Of The Amygdala In Huntington Disease-Associated Aggression, Luis Torres

Honors Undergraduate Theses

Huntington disease (HD) is a fatal neurodegenerative disorder caused by a trinucleotide CAG expansion in the huntingtin gene (HTT). HD is characterized by motor, cognitive, and psychiatric symptoms that significantly impact patient and caregiver quality of life. Psychiatric symptoms, including depression, anxiety, and irritability, are common manifestations of HD and can emerge years before the onset is clinically diagnosed. Aggression is a common and challenging psychiatric symptom in HD, often misunderstood and associated with caregiver stress, early institutionalization, and reduced quality of life. Despite its clinical impact, aggression in HD lacks effective, targeted treatment options. Similar to HD …

Multi-Period Coordinated Planning Of Xfcs In Coupled Tn-Pdn Networks: Integrating Demand Charge Reduction And Pre-Existing Infrastructure, Waqas Ur Rehman, Siyuan Wang, Liheng Lv, Jonathan W. Kimball, Rui Bo

Electrical and Computer Engineering Faculty Research & Creative Works

The widespread adoption of electric vehicles (EVs) and transportation electrification is encumbered by two chief barriers: i) the limited driving range of EVs in the market today and ii) inadequate charging infrastructure support. This paper aims to address the latter bottleneck and proposes a strategic multi-period coordinated planning model to optimally site and size battery energy storage system (BESS) assisted extreme fast charging stations in a highway transportation network and solar systems in a power distribution network. The proposed approach accounts for pre-existing charging stations, the increasing EV penetration levels, decreasing technology costs, and technological advancements in the future and …

Temperature Compensation In Loop And Patch Fss Strain Sensors: Analysis And Experimental Validation, Swathi Muthyala Ramesh, Kristen M. Donnell

Electrical and Computer Engineering Faculty Research & Creative Works

Frequency selective surfaces (FSSs) are arrays of conductive elements or apertures that exhibit frequency-dependent reflection and transmission properties. Their electromagnetic response is influenced by geometry and environmental conditions, making them attractive for wireless strain-sensing applications. However, temperature variations can produce frequency shifts similar to those caused by strain, reducing measurement accuracy. This work investigates the effects of intrinsic temperature compensation on two common FSS unit cell geometries—loop and patch—through comprehensive simulation analysis. The results show that loop-based cells offer superior thermal stability, while patch-based cells provide greater strain sensitivity, illustrating the trade-off between thermal robustness and mechanical responsiveness. A patch-type …

Mitigating Hysteresis In Metal-Coated Fibers Via Optimized Thermal Treatment For Advanced Distributed High-Temperature Sensing Applications, Koustav Dey, Rony Kumer Saha, Bohong Zhang, S. Narasimman, Farhan Mumtaz, Jeffrey D. Smith, Rex E. Gerald, Ronald J. O'Malley, Jie Huang

Electrical and Computer Engineering Faculty Research & Creative Works

Metal-coated optical fibers are widely employed in sensing applications owing to their superior mechanical strength and corrosion resistance. However, their calibration at elevated temperatures is hindered by hysteresis, manifested as discrepancies between heating and cooling cycles, primarily caused by residual strain from mismatched thermal expansion coefficients (TECs) between the metal coating and silica cladding. This research introduces an optimal heat treatment procedure aimed at minimizing the impact of the mismatch in TECs between the cladding and the coating materials that causes the residual strain in gold (Au) and copper (Cu) coated fibers for achieving reliable distributed high temperature sensing up …

Large Language Models For Neurology: A Mini Review, Donald C. Wunsch, Daniel B. Hier

Electrical and Computer Engineering Faculty Research & Creative Works

Large language models have the potential to transform neurology by augmenting diagnostic reasoning, streamlining documentation, and improving workflow efficiency. This Mini Review surveys emerging applications of large language models in Alzheimer's disease, Parkinson's disease, multiple sclerosis, and epilepsy, with emphasis on ambient documentation, multimodal data integration, and clinical decision support. Key barriers to adoption include bias, privacy, reliability, and regulatory alignment. Looking ahead, neurology-focused language models may develop greater fluency in biomedical ontologies and FHIR standards, improving data interoperability and supporting more seamless collaboration between clinicians and AI systems. Two future developments have the potential to be particularly impactful: (1) …

Evaluation Of Multiple Generative Large Language Models On Neurology Board-Style Questions, Mohammad Almomani, Vijaya Valaparla, James Weatherhead, Xiang Fang, Alok Dabi, Chih Ying Li, Peter Mccaffrey, Dan Hier, Jorge Mario Rodríguez-Fernández

Electrical and Computer Engineering Faculty Research & Creative Works

Objective: To compare the performance of eight large language models (LLMs) with neurology residents on board-style multiple-choice questions across seven subspecialties and two cognitive levels. Methods: In a cross-sectional benchmarking study, we evaluated Bard, Claude, Gemini v1, Gemini 2.5, ChatGPT-3.5, ChatGPT-4, ChatGPT-4o, and ChatGPT-5 using 107 text-only items spanning movement disorders, vascular neurology, neuroanatomy, neuroimmunology, epilepsy, neuromuscular disease, and neuro-infectious disease. Items were labeled as lower- or higher-order per Bloom's taxonomy by two neurologists. Models answered each item in a fresh session and reported confidence and Bloom classification. Residents completed the same set under exam-like conditions. Outcomes included overall and …

Safety Aware Continual Reinforcement Learning-Based Output Tracking Control Of Nonlinear Continuous-Time Systems, Irfan Ganie, Sarangapani Jagannathan

Electrical and Computer Engineering Faculty Research & Creative Works

An output feedback (OF)-based control scheme utilizing both a scalable multilayer neural network (MNN) observer and actor–critic MNN via integral reinforcement learning (IRL)/adaptive dynamics programming (ADP) approach for a class of nonlinear systems with output constraints is introduced. The proposed observer, critic, and actor MNN weight updates are derived using a singular value decomposition (SVD) of MNN activation function gradient along with output error, Bellman and control input errors, respectively. Next, the approach incorporates continual learning (CL), utilizing a penalty function in the weight update laws for both actor–critic MNNs to consolidate knowledge from previous tasks and enhance learning in …

Multi-Parameter Optimization And Adaptive Temperature Compensation For Fbg Strain Sensors In Wide-Temperature-Range Aerospace Applications, Ruling Zhou, Jiacheng Yu, Yutang Dai, Jianguan Tang, Minghong Yang, Farhan Mumtaz

Electrical and Computer Engineering Faculty Research & Creative Works

Accurate strain measurement in cryogenic fuel pipelines is crucial for ensuring the structural integrity and reliability of rocket engine systems operating under extreme thermal conditions. Fiber Bragg grating (FBG) sensors show significant potential for such applications; however, their inherent temperature-strain cross-sensitivity limits performance over wide temperature ranges. This research presents an enhanced compensation strategy combining multi-parameter optimization with temperature-zone-specific adaptation to improve the accuracy and stability of FBG-based strain sensing in harsh aerospace environments. Four special steel substrate materials including S03, S06, S07, and 1Cr18Ni9Ti, were evaluated using strain transfer theory and thermo-mechanical coupling simulations. Genetic algorithms optimized key design …

Safe Optimal Control Framework For Cooperative Manipulation Of Objects In Human–Robot Teams, Irfan Ganie, Sarangapani Jagannathan

Electrical and Computer Engineering Faculty Research & Creative Works

This article introduces a distributed deep neural network (NN)-based adaptive control framework for cooperative object manipulation in human–robot teams with unknown agent dynamics by using three distinct multilayer NN observers (MNNOs). The first observer, termed the reference point estimator, enables each robotic agent to estimate the object's reference center using consensus-based learning, even without direct access to global reference trajectories. The second observer, referred to as the human force-to-trajectory estimator, uses human-applied forces to infer the intended position, velocity, and acceleration of the object, enabling real-time estimation of human intent. Together, these two observers allow distributed estimation of human-intended motion. …