Digital Commons Network^™

The Application Of Natural Language Processing Towards Auditing Of Unstructured Data: A Design Science Approach, Dennis K. Amoatey

Electronic Theses and Dissertations

Financial auditors must manually review large volumes of unstructured text that may include contracts, internal policies, footnotes, and journal entry descriptions. This time-intensive process introduces risk of human error and inconsistency. Despite advances in automation, no systematic approach exists for applying Natural Language Processing (NLP) to this problem at scale. Using a design science approach, this study develops a framework that demonstrates how NLP techniques can be incorporated across key phases in the audit process, including planning, internal controls evaluation, evidence gathering, and reporting. Initial evaluation through expert feedback had a mix of responses. While some argued difficulty with data …

Journal Of Roleplaying Studies And Steam (Jrpssteam) Vol. 5 [2026], Número 1 (Issue 1), Romano Ponce-Díaz Phd, Cristo Leon, Ivan Avila, Sarah Lynne Bowman, Kjell Hedgard Hugaas, Alexandra Schreiber Ma, Jaime Eduardo García Maya, Víctor Emmanuel Quintana Villarreal Vic Emma, Francisco Gonzalez Ing., Daniel Romero Benguigui, Antonio Roda-Martínez

Journal of Roleplaying Studies and STEAM

El presente número del Journal of Roleplaying Studies and STEAM examina la convergencia entre las prácticas lúdicas, el diseño narrativo y los procesos de mediación sociocultural en la investigación contemporánea. Las contribuciones reunidas en este número abordan el juego de rol como un dispositivo de producción de conocimiento, intervención psicoeducativa y reelaboración de representaciones culturales. Nos podemos atrever a señalar que la educación es la convergencia entre la ludología, las ciencias sociales, los estudios visuales y el análisis cultural; entendiendo a la educación como la actividad consciente e intencionada de transmitir información y conocimientos a las siguientes generaciones.

Martin Heidegger …

A Novel Approach To Creativity Assessment: Forced Pairwise Ranking With Large Language Models, Phillip R. Gregory Jr

Master's Theses

Assessing creativity at scale remains a persistent challenge in cognitive science, as human raters are costly, slow, and often inconsistent in their judgments. This thesis introduced a novel framework for automated scientific creativity assessment using forced pairwise ranking, in which fine-tuned large language models compared response pairs and determined which was more creative. Five empirical studies were conducted using Llama-2-7B and Llama-2-13B models adapted via LoRA fine-tuning and benchmarked against human scored responses from the Scientific Creative Thinking Test. A regression baseline achieved Pearson �� = .74 on the test set, matching the human inter-rater ceiling reported in the literature. …

On The Paleontology Of Belize, Alson Ovando

Electronic Theses and Dissertations

Paleontology can be considered an underrepresented and emerging area of science in Belize. A primary aim of this thesis is to provide a background of paleontology in Belize and present the first comprehensive study of Quaternary vertebrate fossils known from the country. Quaternary fossil sites across Belize include caves, rivers, and sinkholes. In addition to reviewing and assessing material from known sites, this thesis presents new information and discoveries that were made while investigating Belize’s Quaternary fossil record. This thesis also includes a geospatial model depicting ecoregions in Belize during the last glacial maximum. Overall, the results presented here demonstrate …

Stochastic Universal Differential Equations For Epidemiological Modeling: Uncertainty Quantification In Disease Transmission Dynamics, Alice Menaya Armah-Bonney

Electronic Theses and Dissertations

Epidemic forecasting requires not only predictions of expected case counts, but also quantification of uncertainty, although existing surrogate modeling frameworks for agent-based models remain fundamentally deterministic. In this thesis a Stochastic Universal Differential Equation framework is presented that extends the deterministic Universal Differential Equation approach by incorporating a learnable stochastic diffusion term, enabling calibrated probabilistic forecasts while preserving the mechanistic interpretability and computational efficiency of the deterministic baseline. In doing so, a two-phase training algorithm is introduced to ensure stable convergence and the framework is validated against the ensemble output from ExaEpi, an exascale agent-based model of a COVID-19 outbreak …

Extreme Precipitation Events And Population Exposure: Site Recommendations For The Future Tennessee Mesonet, Victoria G. Redlund

Electronic Theses and Dissertations

This study examines frequency of and population exposure to extreme rainfall events in Tennessee to guide the placement of future mesonet weather stations. Using 1991-2021 daily nClimGrid precipitation records, extreme events were defined as events of rainfall ≥50 mm. These events were collated on an annual scale and normalized alongside square-root-scaled population densities derived from Landscan to develop extreme rainfall vulnerability maps. Results highlight where extreme rainfall is most frequent relative to population densities in each county. The findings were compared with models of mesonet suitability and feasibility to determine how meteorological needs correlate with siting needs such as land …

Quantifying Discard Mortality Of Undersized And Ovigerous Crabs In The Gulf Of Mexico Blue Crab Fishery, Micayla Cochran

Master's Theses

Blue crabs support a valuable commercial fishery in the Gulf of Mexico. Most states require the release of undersized and ovigerous blue crabs, yet mortality of these discarded crabs is an understudied component of total mortality. The first objective of this project was to quantify discard mortality of non-target crabs using bycatch surveys across the Lake Pontchartrain–Mississippi Sound coastal system. Ovigerous crabs were most common at high salinities and temperatures, whereas undersized crab presence was inversely correlated with soak time, temperature, and the number of crabs per trap, and also varied among geographic locations. A reflex action mortality prediction assessment …

Sevoauth: Secure Voiceprint Authentication With Hash-Based Feature Transformation, Rui Zhang, Zheng Yan, Robert H. Deng

Research Collection School Of Computing and Information Systems

While voiceprint authentication offers convenient user authentication and access control through voice feature recognition, a critical research gap remains: existing voiceprint authentication systems fail to simultaneously achieve sound security against replay, spoofing, and adversarial attacks, preserve voice privacy leakage, and satisfy usability demand. Previous efforts have struggled to balance these issues comprehensively. To bridge this gap, we present SeVoAuth, a cloud-based Voiceprint Authentication as a Service (VAaaS) system designed to provide privacy preservation, robust security, and enhanced usability. SeVoAuth stores a synthesized voiceprint of a user in the cloud during user registration, thereby safeguarding the privacy of the real voiceprint …

Synthesis And Evaluation Of Long-Term History-Aware Medical Dialogue, Hebin Hu, Renke Dai, Ah-Hwee Tan, Yilin Kang

Research Collection School Of Computing and Information Systems

An effective healthcare agent must be able to recall and reason over a patient’s longitudinal medical history. However, the absence of datasets with realistic long-term dialogue timelines limits systematic evaluation. Real clinical text is constrained by privacy and ethics, while existing benchmarks focus on isolated interactions, failing to capture cross-session reasoning. We introduce a framework for synthesizing high-quality, long-term medical dialogues with LLMs. Our approach entails a knowledge-guided decomposition into three stages: constructing synthetic patient profiles with diverse disease and complication trajectories, generating multiturn dialogues per encounter, and integrating them into a coherent longitudinal history dataset, MediLongChat. We establish three …

Fighting Against Recruitment Scams: Theory-Driven Supervised Learning And Empirical Analysis For Digital Fraudulent Recruitment Posting Behavior, Tom (Tianteng) Wang, David (Jingjun) Xu, Keng Siau, Zhongju (John) Zhang

Research Collection School Of Computing and Information Systems

The number of recruitment postings on digital recruitment hiring platforms has increased since the COVID-19 pandemic. However, the weak surveillance and operations of these platforms, combined with the fact that most job seekers have relatively low vigilance and a strong desire for recruitment offers, enable scammers to easily deceive job seekers for their money and confidential information. In this work, we combine prevailing text mining techniques (i.e., ChatGPT with prompting engineering and supervised machine learning) with interpersonal deception theory (IDT) from social science to design an interpretable IT system to predict fraudulent recruitment postings on digital recruitment-hiring platforms. We compare …

Securing Cloud-Native Systems: From Vulnerability Analysis To External And Insider Threat Detection, Jiongchi Yu

Dissertations and Theses Collection (Open Access)

Cloud-native systems have become the backbone of modern software infrastructure. However, their dynamic resource orchestration and complex configurability introduce a large attack surface and intricate security challenges. Adversaries can externally exploit vulnerabilities in cloud components or perform insider movement within cloud environments to launch attacks. As these systems increasingly support critical services, security breaches can lead to severe operational and economic consequences.

Despite extensive efforts in vulnerability detection and attack monitoring, existing approaches struggle to remain effective in cloud-native environments characterized by rapid evolution and inherent heterogeneity. In particular, they exhibit three fundamental limitations: (1) Insufficient understanding of defect patterns …

Safe Control Design For Quadruped Locomotion In Unstructured Environments Using Linear Transfer Operators, Sriram Sundar Krishnamoorthy Shankara Narayanan

All Dissertations

Deploying quadruped robots in unstructured, obstacle-rich environments requires control and planning methods that remain safe and reliable despite complex terrain geometry, limited sensing, and inevitable modeling errors. This thesis develops operator-theoretic tools for safe control design of robotic systems using linear transfer operators, with a focus on quadruped locomotion in unstructured environments. The central goal is to develop a unified operator-theoretic framework for safe control design based on the Perron–Frobenius (P–F) and Koopman operators. In particular, the thesis leverages \emph{density functions} to develop safe navigation frameworks in the dual space of densities. In the operator-theoretic perspective, the P–F operator governs …

The Impact Of Label Material On Perceived Value And Environmental-Friendliness Of Beverages In Returnable Glass Bottles Versus Actual Environmental Impact Via Life Cycle Assessment, Toni Sharp

All Dissertations

With guidance from the EPA to reduce virgin packaging use and alternatively increase reuse, the concept of reusable packaging has re-emerged as a potential sustainable alternative to single-use and recyclable packaging. For businesses, an understanding of the potential environmental benefits of switching from single-use packaging to reusable packaging, along with consumer willingness to pay for sustainable packaging are paramount. Existing literature on willingness to pay (WTP) for ethical or sustainable products typically relies on consumers’ stated preferences found through surveys using hypothetical products and prices. It has been revealed that sustainability claims printed on the label or products in glass …

Intersectionality And Belonging: Higher Education Mathematics, Ashley Natalie

Mathematics and Statistics

Students with intersecting marginalized identities (such as race, gender, socioeconomic status, disability, or first-generation background) often face unique challenges in advanced mathematics that affect confidence, participation, amounting to a sense of belonging. These experiences remain underrepresented in mathematics education research. This qualitative, narrative-based study examines how these students experience classroom dynamics and belonging in upper-level mathematics courses. Semi-structured interviews will be analyzed thematically to identify patterns related to identity, classroom culture, instructor behavior, and peer interactions. Findings aim to highlight barriers and supportive practices, informing more inclusive teaching strategies and equitable learning environments in advanced mathematics.

Intersectionality And Belonging: Higher Education Mathematics, Ashley Williams

Mathematics and Statistics

Students with intersecting marginalized identities (such as race, gender, socioeconomic status, disability, or first-generation background) often face unique challenges in advanced mathematics that affect confidence, participation, amounting to a sense of belonging. These experiences remain underrepresented in mathematics education research. This qualitative, narrative-based study examines how these students experience classroom dynamics and belonging in upper-level mathematics courses. Semi-structured interviews will be analyzed thematically to identify patterns related to identity, classroom culture, instructor behavior, and peer interactions. Findings aim to highlight barriers and supportive practices, informing more inclusive teaching strategies and equitable learning environments in advanced mathematics.

Polyglot File Detection For Forensic Investigations, Chase Stevens

Graduate Theses and Dissertations (2019 - present)

As technology has become far more ubiquitous over the years, so too has the amount of digital evidence that can and needs to be collected and processed. Forensic tools are developed in response to the growing need, but are limited to what they are programmed to do. One such forensic tool is Autopsy, one of the most widely used open-source tools. Autopsy uses known file-type signatures (e.g., headers, trailers) to identify and recover files from forensic images. Polyglot files introduce a unique problem to both these forensic tools and investigators alike. In the context of the research conducted, polyglot files …

Detecting Sophisticated Cyberattacks On Public Water Infrastructure, Ayrton Purdy

Graduate Theses and Dissertations (2019 - present)

In recent years there has been an increasing number of cyberattacks on public water generation and distribution systems. Advanced persistent attackers could usurp sensors and control systems to contaminate public drinking water. In order to conceal their malicious activity, they can manipulate sensor data flows to give the appearance of normal activity. The compromised sensors would report normal chemical levels even though unsafe water is entering the distribution system. In response, this research proposes a multi-sensor, cross-comparison approach to anomaly detection. The proposed approach is designed to detect sophisticated cyberattacks which are not easily detectable using traditional cyber tools. The …

Developing A Framework For Microchip Design Recovery, Eric Diep

Graduate Theses and Dissertations (2019 - present)

Due to the increase in diverse chip production over the past decade, reverse engineering has become a difficult and daunting task. This research develops a methodology for microchip design recovery, seeking to validate and reproduce prior approaches to physical reverse engineering using low-cost tools and techniques. We used mechanical hardware abrasion tools and techniques to delayer and capture silicon integrated chip (IC) layout. We focused on the Mifare Classic EVl microchip, commonly implemented in public transit/transportation cards, to extract information for design recovery. The research explores limitations and advantages of mechanical abrasion and optical microscopy in context to modem chip …

A Generative Ai Method For Minority Class Handling In Anomaly Detection With Drift And Explainability Analysis, Kelvin J. Mwiga, Mussa A. Dida, Ahmad Mohsin, Iqbal H. Sarker

Research outputs 2022 to 2026

Artificial Intelligence, particularly machine learning (ML) algorithms, plays a crucial role in detecting cyberattacks, including anomalies and intrusions. However, machine learning models trained on imbalanced cybersecurity datasets often struggle to accurately detect minority data instances and potential threats, thereby weakening overall system security. Despite extensive research, a persistent challenge is the inadequate explanation for model predictions concerning minority data classes. This study aims to address these limitations by developing a generative AI-based approach to manage minority classes in anomaly detection, incorporating concept drift handling and explainability analysis. We introduce an over-sampling technique, CGGReaT, designed to enhance the presence of minority …

A Survey Of Privacy-Preserving Federated Learning For Intrusion Detection Systems, Thomas Bunko, Michael N. Johnstone, Wencheng Yang, Ben A. Scott

Research outputs 2022 to 2026

Intrusion detection systems (IDS) monitor and detect malicious activity and unauthorized access that may compromise systems. Traditional IDS approaches send data to a central server for analysis, raising privacy concerns as data owners lose control over security. Federated Learning (FL) offers a privacy-preserving alternative by allowing local devices to process their data and generate models without sharing raw data. These local models are aggregated centrally to form a comprehensive model with performance comparable to centralized systems. This paper reviews FL-based IDS research, and is the first review paper to focus on privacy-preserving techniques collectively known as privacy-preserving Federated Learning (PPFL) …

Assessment Of Mississippi Landfill Capacity In Relation To Waste Generation And Land-Use Constraints, Jason C. Anderson

Master's Theses

Municipal solid waste (MSW) management presents a growing challenge in Mississippi as population trends, socioeconomic change and regional development continue to place pressure on existing landfill capacity. This thesis examines waste generation and disposal patterns from 2000 through 2022 across Mississippi counties, with projections extending to 2050. Historical landfill tonnage data was gathered and compiled from the Mississippi Department of Environmental Quality (MDEQ) and analyzed using regression models in Excel and RStudio, with forecasts generated for both in-state and out-of-state waste flow. Results highlight significant variations among landfills, including differing closure timelines, changing county service areas and notable shifts in …

Discovering Strategic Behaviors In The Floor Using Reinforcement Learning, Kevin Parks

All Graduate Reports and Creative Projects, Fall 2023 to Present

This project investigates how a reinforcement learning (RL) agent can develop territorial strategies in a highly stochastic, grid-based approximation of the television game show The Floor. I design a custom Gymnasium-compatible environment that models the show’s core mechanics on a 10×10 board, including probabilistic duels governed by player skill, adjacency-constrained attacks, chain-attack rules, and a Randomizer mechanism for selecting new initiating players. A Maskable Proximal Policy Optimization (Maskable PPO) agent is trained under several reward configurations and evaluated against stochastic non learning opponents as well as random and “always pass” baselines.

Across experiments, the best-performing configuration achieves a win …

Open Space Management Planning: A Framework And Case Study From Eagle Mountain City, Utah, Nathan K. Shumway

All Graduate Reports and Creative Projects, Fall 2023 to Present

Open Space Management Plans (OSMPs) are increasingly used by municipalities to guide the long-term stewardship of natural lands; however, little formal guidance exists regarding how these plans are structured, developed, or organized in practice. While numerous OSMPs are publicly available, their compositional logic, procedural workflows, and thematic priorities remain largely undocumented within academic literature. This study addresses that gap through a qualitative document analysis of fifteen publicly accessible OSMPs from the western United States, published between 2015 and 2024.

Using manual matrix-based coding in Microsoft Excel, each plan was analyzed through three lenses: structural composition, procedural development, and thematic content. …

Sql Query Optimization - Human Vs. Chatgpt, Hailey Dennis

All Graduate Reports and Creative Projects, Fall 2023 to Present

Large Language Models (LLMs) such as ChatGPT have become ubiquitous tools for working professionals in the software industry. Many engineers are finding new ways to increase productivity by offloading tasks onto LLMs, while others are finding it difficult to trust code produced artificially, even after review. Taking a look at both perspectives, this study aims to compare a human’s ability to optimize SQL queries to that of an LLM and assess the experience using both methods.

Manual query optimization is a tedious task that relies heavily on statistics, heuristics, and good intuition. The SQL developer must search for the optimal …

From The Hopf Fibration To Instantons: Geometry In Gauge Theory, Emily D. Wessman

Undergraduate Honors Capstone Projects

This paper explores the relationship between topology, differential geometry, and gauge theory through the study of Yang-Mills theory and its solutions, known as instantons. Beginning with the Hopf fibration, we show how principal fiber bundles encode topological information and appear in physical contexts such as electromagnetism. In particular, we consider how the fibration of S³ over CP¹ ≅ S² represents the Dirac magnetic monopole, and how the Chern number associated with the bundle is exactly the winding number for the monopole.

We then develop the framework of gauge theory, focusing on connections on principal SU(2) bundles …

Utilizing Pine Needles To Compare Spatial Profiles Of Polycyclic Aromatic Hydrocarbons (Pahs) In Two Urban Areas, Autumn Jensen

Undergraduate Honors Capstone Projects

Polycyclic aromatic hydrocarbons (PAHs) are an important class of semivolatile air pollutants known for their adverse health impacts. This research used conifer needles as passive air samplers to create spatial maps of two Utah cities (Rose Park and Spanish Fork) to compare overall PAH exposure and identify any differences in their congener profiles or PAH “fingerprints”. Conifer needles were chosen due to their prevalence as a passive air sampler in previous research and their ubiquity in urban and suburban environments. Second year needles were collected and the concentrations are considered to be an annually averaged view of the PAH concentrations …

Prediabetes Prediction Before Disease Onset Using Multimodal Health Data: A Machine Learning Approach, Luisa Veronica Gracia Mazuca

Open Access Theses & Dissertations

Prediabetes is a critical health condition that increases the risk of developing type 2 diabetes. The hemoglobin A1c (HbA1c) test diagnoses patients with prediabetes, but the disease has already caused metabolic alterations. Early detection is essential for timely interventions, and machine learning models offer a promising approach to identify prediabetic individuals through the analysis of biomarkers such as cytokines. We compared four classifiers-logistic regression, decision tree, random forest, and k-nearest neighbors - using cytokines (TNF-α, MCP-1, IL-1β, IL-6, IFN-γ), age, BMI, and waist-to-hip ratio (WHR). Models were evaluated using stratified 5-fold cross-validation and ROC-AUC. K-Nearest Neighbors (k-NN) achieved the highest …

Provenance Analysis Of Advanced Persistent Threats In Operational Technology Environments, Laura Aminta Guevara

Open Access Theses & Dissertations

Live vulnerability testing and penetration assessments of critical infrastructure are costly, complex operationally and, in many cases, unsafe to conduct directly against live systems, whether these are commissioned in-house and through third-party providers. For Operational Technology environments specifically, these constraints are further aggravated by the limited vendor support and inconsistent security patching available that characterize many industrial communication protocols. This significantly restricts the scope and feasibility of conventional penetration testing. At the same time, the increasing overlapping of OT systems with enterprise networks and the internet has expanded the attack surface of ICS infrastructure, making more pressing the need for …

Exploratory Proxy Occupational Health Risk Assessment On Pm2.5 Exposure Among Outdoor Personnel At International Ports Of Entry, Josdell Maria Guerra Ruiz

Open Access Theses & Dissertations

Despite growing public health concerns on PM2.5 exposure and its respiratory health effects, no documented evidence has been found on the application of proxy methods to perform occupational health risk assessments for PM2.5 exposure among outdoor personnel. The purpose of this research study was to conduct a descriptive and predictive occupational health risk assessment for cancer and non-cancer respiratory health outcomes related to PM2.5 exposure among outdoor personnel at targeted international ports of entry (IPOE). A total of 61 samples were collected, for 24 hours, at two targeted IPOEs (every sixth day) over 12-month period. Samples included measurements on PM2.5 …

Zero-Knowledge Proofs For Verifiable Machine Unlearning, Bidur Niroula

Open Access Theses & Dissertations

Machine unlearning aims to remove the influence of deleted data from a trained machine learning model. This is important because privacy regulations such as GDPR, CCPA, and PIPEDA give individuals the right to request the deletion of their personal data. Since unlearning can be expensive, a dishonest server may skip it or return an incorrect model and this motivates verifiable machine unlearning. Existing cryptographic approaches prove that the server executed a specific training or unlearning algorithm on the committed dataset, so the proof is tied to the algorithm's trajectory. Empirical verifiers avoid this cost but are known to be circumventable …