Physical Sciences and Mathematics Commons^™

Watchdogs Or Lapdogs: How Audit Committees Influence Financial Reporting Quality And Cybersecurity, Yanru Yang

2025

With the increasing complexity of the business environment, the role of corporate governance and oversight is expanding continuously. Grounded in archival research, my dissertation consists of three studies that explore the features of audit committees in monitoring both financial reporting and broader areas, such as cybersecurity.

The first paper, co-authored with Gopal Krishnan and Wei Yu, examines the implications of audit committee (AC) director departure for financial reporting quality and audit risk. We find that the departures in the firms with most concerning AC departures are associated with a higher likelihood of a future “Big R” restatement announcement and auditor …

Digital Platform Transitions In The Finance Industry: Three Essays, Cheryll-Ann Wilson

2025

This three-paper dissertation is motivated by an emerging dichotomy in the financial sector: an increasing use of an open-source digital platform—the Python platform—in an industry that historically has been wedded to proprietary systems.

Chapter 1 is a qualitative pilot study to ascertain which factors are likely to motivate investment professionals to select Python versus other tools and/or technologies. I find that efficiency and access to industry-specific libraries—notably Pandas and NumPy—are significant motivators in their selection of Python over Excel. Chapters 2 and 3 examine the issues through a sequential, exploratory mixed methods approach.

Chapter 2—the qualitative field study—investigates how and …

Valorizing Municipal Solid Waste For Sustainable Aviation Fuel And Polyhydroxyalkanoate Bioplastics: Pyrolysis And Microbial Pathways, Emon Das

Theses and Dissertations--Biosystems and Agricultural Engineering

The escalating global burden of municipal solid waste (MSW), projected to reach 3.88 billion tons annually by 2050, calls for innovative valorization strategies to mitigate environmental impacts and promote a circular bioeconomy. This thesis investigates the conversion of MSW into two high-value products: sustainable aviation fuel (SAF) and polyhydroxyalkanoate (PHA) bioplastics. Chapter one presents comprehensive physicochemical characterization and pyrolysis-GC/MS analysis of MSW feedstocks. The physicochemical results reveal that densification enhances handling and storage properties, while pyrolysis-GC/MS analysis indicates that plastic-rich MSW streams produce bio-oils with favorable hydrocarbon profiles suitable for SAF production, potentially contributing to decarbonization efforts in the aviation …

The Impacts Of Land Use And Groundwater Inputs On Stream Health And Habitat Of Jennings Creek, Bowling Green, Kentucky, Allison Francis

Mahurin Honors College Capstone Experience/Thesis Projects

In Bowling Green, Kentucky, the Jennings Creek watershed encompasses the entire city and surrounding area; however, little work has been completed focused on assessing the Creek’s water quality, habitat, and biological indicators. Jennings Creek is fed by several karst groundwater springs, making it highly vulnerable to contamination due to the rapid connection between the surface and subsurface via sinkholes and underground rivers. An examination of Jennings Creek’s water quality, habitat, and biological indicators provides an assessment of the watershed’s health.

The methodology closely followed the methods for assessing habitat by Kentucky’s Energy and Environment Cabinet and was approved for the …

World As Other, World As Self: Beyond Dualism In Environmental Narratives, Tamara Wallace Ramirez

CGU Theses & Dissertations

Stories of place matter to the way we live with the Earth. A dualistic perspective that pits "culture" against "nature" enables environmental degradation on small and large scales. Conversely, understanding humans and nonhumans as entwined allows us to think and act differently with our planetary community. This view entails integrating the "self" and the "other." Instead of being antithetical to the other, the self arises through engagement with others, human and nonhuman. Understanding our mutuality with others while respecting their alterity and agency fosters caring and dedication. Our sense of connection with the more-than-human world inspires our compassion. However, such …

Enhancement Of Mechanical, Structural, And Electrical Properties In Advanced Composites And Vat Photopolymerized 3d Printing Nanocomposites, Poom Narongdej

CGU Theses & Dissertations

Advanced composites have gained significant attention across various industries, including aerospace, automotive, clean energy, and healthcare, owing to their exceptional mechanical properties and versatility. Fiber-reinforced polymer (FRP) composites, particularly those reinforced with carbon fibers, are extensively used as structural materials in spacecraft, aircraft, high-performance vehicles, and wind turbines due to their high strength-to-weight ratios, stiffness, durability, and tailorable mechanical characteristics. In healthcare, the advent of additive manufacturing (3D printing) has expanded the utility of advanced composites, enabling precise customization of components to meet patient-specific needs while offering design flexibility and ease of fabrication. Despite these advantages, several challenges hinder the …

Osa-Diff: An Origin Sampling Based Adversarial Attack Using Diffusion Models, Shayan Jalalipour, Banafsheh Rekabdar

Computer Science Faculty Publications and Presentations

Diffusion models are becoming an increasingly popular emerging technology, however their use in adversarial attacks remains a scarcely explored topic. We show that diffusion models can be used to create end-to-end hidden adversarial perturbations with high rate of success, and propose a novel diffusion based adversarial attack that allows for substantially faster training time (through improved convergence on high quality images) and with substantially less computational overhead than typical diffusion model training

The Stochastic Occupation Kernel (Sock) Method For Learning Stochastic Differential Equations, M. L. Wells, Kamel Lahouel, Bruno Jedynak

Mathematics and Statistics Faculty Publications and Presentations

We present a novel kernel-based method for learning multivariate stochastic differential equations (SDEs). The method follows a two-step procedure: we first estimate the drift term function, then the (matrix-valued) diffusion function given the drift. Occupation kernels are integral functionals on a reproducing kernel Hilbert space (RKHS) that aggregate information over a trajectory. Our approach leverages vector-valued occupation kernels for estimating the drift component of the stochastic process. For diffusion estimation, we extend this framework by introducing operator-valued occupation kernels, enabling the estimation of an auxiliary matrix-valued function as a positive semi-definite operator, from which we readily derive the diffusion estimate. …

Action This Day: The Mathematics And Machinations That Bested The German Enigma, Jonah Weinbaum

Dartmouth College Master’s Theses

This thesis presents a comprehensive and chronological overview of cryptographic techniques designed to break Enigma, beginning in 1932 and culminating in the creation of the Turing-Welchman Bombe. We discuss the mathematical theory and electromechanical implements used to decode one of history's greatest ciphers.

Reexamining the Bombe through the lens of modern group theory, we critique Alan Turing's estimation of the number of "stops" that the Bombe produces for various plaintext-ciphertext pairing structures. To address its limitations, we introduce a new framework for estimating the number of stops by extending John Dixon's theorem concerning the probability that uniformly distributed elements of …

Mangroves: A Lesson On Modeling Changing Shorelines, Willa Skye

ENGS 15.11: Design and Education

This lesson is an overview of storm barriers, specifically mangroves and how they maintain shorelines. It is meant to offer a visual experience of coastline protection and provide a background for deeper understanding about intertidal zones and their conservation. Students will spend time creating a solution to a flooding problem by making a mock coast and storm barrier. To wrap-up the lesson, students will pair up, then reflect on their model and then individually write or draw their takeaways.

Mathematics And Determinism: Chaos, Quantum Mechanics, And The Limits Of Predictive Structure, Jackson T. Salumbides

CMC Senior Theses

This thesis examines the relationship between mathematics and determinism by analyzing how chaos theory, quantum mechanics, and formal mathematical limits challenge traditional conceptions of predictability and causal structure. Chaos theory shows that deterministic systems can exhibit practical unpredictability due to sensitivity to initial conditions. Quantum mechanics introduces probabilistic outcomes that complicate deterministic interpretation, though alternative frameworks such as Bohmian mechanics and superdeterminism attempt to restore determinism at conceptual cost. Additionally, results from mathematical logic, including Gödel’s incompleteness theorems and Turing’s undecidability, demonstrate intrinsic limitations on what can be deduced or computed, even in fully deterministic systems. By synthesizing these areas, …

Tiered Coalition Formation Game Variants, Stability, And Simulation, Nathan Arnold

Theses and Dissertations--Computer Science

Tiered coalition formation games (TCFGs) have been proposed for modeling the ordering of power in intransitive structures. Furthering our understanding of the usefulness of this concept requires a close examination of this game and its variants, as well as the delineation between stability concepts and methods of finding stable outcomes. Derived from a simulation of the performance of characters in the games Pokémon Red and Blue Versions, we present an approximation of its power structure found via machine learning. We compare our findings to the community consensus ranking presented on a fan-run website, and further comment on the stability of …

Temporal Team Formation Games With Dynamic Preferences, Cameron Egbert

Theses and Dissertations--Computer Science

In the professional world, it is imperative for management entities to allocate their human resources to a work schedule, and such models of coalition formation games are well-studied. However, most existing literature only considers coalition formation in the context of a single moment in time, without accounting for changing preferences among individuals as they work together. The primary contribution of this thesis is a new team formation game that incorporates skill-based team formation and a dynamic variant of Additively Separable Hedonic Games. These Temporal Team Formation Games with Dynamic Preferences (TTFG-DPs) allow for two psychologically common preference dynamics: a preference …

Development Of Software For Genetic Distances, Genotyping, And Phylogenetics Using Rna-Seq Data, Andrew C. Tapia

Theses and Dissertations--Computer Science

This dissertation concerns a new application of RNA-seq data—computation of pairwise genetic distance matrices. RNA-seq captures sequences of RNA molecules in some cells or tissues of interest. RNA-seq provides data are well-suited to studies examining gene expression, and its use for this purpose is currently widespread. A pairwise genetic distance matrix, the main topic of this dissertation, quantifies differences in the genomes of every pair of samples (e.g., individuals) in a given set. Genetic distance matrices are versatile; they can be used for various kinds of downstream analyses, including genotyping, phylogenetics, and genetic diversity measurement. Although DNA sequence data are …

Information-Theoretic Methods For Efficient Training And Robust Evaluations In Self-Supervised Learning, Oscar Skean

Theses and Dissertations--Computer Science

Self-supervised learning (SSL) has become a cornerstone of modern machine learning, offering a scalable alternative to costly human annotation by constructing pretext tasks directly from raw data. While SSL has delivered strong results across vision, language, and multimodal domains, two major limitations persist: (1) SSL methods are often significantly slower to train than supervised counterparts, and (2) evaluation protocols remain narrow, with most studies relying on linear probing accuracy on the pretraining dataset. . These challenges are particularly acute for large language models (LLMs), where training costs and interpretability of intermediate representations are critical concerns.

In this work, we propose …

Machine Learning Methods For Intrusion Detection And Response In Network Security, Ayomide Oyemaja

College of Graduate Studies: Theses & Dissertations

Intrusion Detection Systems (IDS) play a crucial role in computer network security by identifying malicious activities and potential cyberattacks. This thesis combines machine learning and cybersecurity by applying Reinforcement Learning (RL) in intrusion detection and response using the NSL-KDD dataset.

We designed and implemented a Q-learning framework where an agent learns to classify network traffic over time by interacting with the environment and receiving rewards based on detection accuracy. We also look at the importance of feature selection and classification techniques and how effective they are in improving model performance, reducing the complexity of computation, and producing more desirable results. …

Dynamic Analysis Of Malware Detection Using Customized Payloads: Examining The Effectiveness Of Manual And Automated Approaches In Web Applications, Jiban Krisna Das

College of Graduate Studies: Theses & Dissertations

Web applications are becoming the prime targets for cyber-attacks, where SQL injection (SQLi) and Cross Site Scripting (XSS) are the most exploited vulnerabilities. The study explores a novel approach using customized payloads to examine the effectiveness of manual and automated techniques of malware detection. This dynamic approach can effectively generate attack payloads and identify the vulnerabilities in a website thereby strengthening website security measures. This research focuses on dynamic analysis in a controlled environment while testing and analyzing SQL and XSS payloads under varying security conditions. This quantitative analysis involves crafting targeted payloads to bypass Web Application Firewall (WAF) filters …

Seafloor Magnetic Alteration Through Time Across The Northern Mid Atlantic Ridge, Jelil Olamide Olaoye Mr

College of Graduate Studies: Theses & Dissertations

The magnetic properties of oceanic crust evolve with age due to chemical alteration, changes in magnetic mineralogy, and physical processes associated with seafloor spreading. This study investigates how magnetic properties change over time in basaltic rocks from the northern Mid Atlantic Ridge, with a focus on two V-shaped ridge sites (VSRs; U1562 and U1563), two V-shaped troughs (VSTs; U1554 and U1555) and a normal crust site formed during episodic mantle upwelling. Magnetic analyses including anisotropy of magnetic susceptibility (AMS), natural remanent magnetization (NRM), alternating field demagnetization (AF) and hysteresis loops, was performed with optical microscopy and scanning electron microscopy (SEM) …

A Mathematical Modeling Approach To Investigate The Impacts Of Post-Infection Mortality And Partial Immunity On Disease Endemicity, Brendan M. Shrader

Honors Undergraduate Theses

A number of infectious diseases cause post-infection conditions or complications, such as COVID- 19, Q fever, and Polio. These conditions result in recovered individuals having a higher mortality rate than susceptibles, and this can impact disease dynamics. An existing mass-action model in the literature that incorporated post-infection mortality was shown to have limit cycles, or persistent oscillations, in the infected population. To better understand what causes these limit cycles, we develop and analyze a new epidemiological model with standard incidence. We show standard results, including the existence, uniqueness, and stability of the disease-free and endemic equilibria, and we rule out …

A Time Series Analysis Of The Macroeconomic Indicators, Mia Houston

Honors Undergraduate Theses

Understanding inflation—particularly across regions and categories—is crucial for effective policymaking, strategic business decisions, and safeguarding vulnerable populations, as it highlights the diverse drivers and impacts of price changes within the economy. This has become increasingly crucial in recent years between the volatile inflation conditions introduced by the COVID-19 pandemic, energy price shocks, and renewed trade tensions and tariffs. This thesis analyzes 77 U.S. monthly inflation time series from 2003 to 2023 using two forecasting approaches: an elementwise Seasonal Autoregressive Integrated Moving Average (SARIMA) model and a Factor-Augmented Vector Autoregressive (FAVAR) model. The data obtained from the Bureau of Labor Statistics …

Theoretical Analysis Of Cnns For Automatic Seizure Detection In Eeg Signals, Jackson T. Small

Honors Undergraduate Theses

Epilepsy is a common brain disorder where neurons in the brain rapidly fire, causing recurring seizures. The brain activity during a seizure can be detected by electroencephalogram (EEG) signals; however, this process is not only labor-intensive and time-consuming but is also subject to inter-rater variability, with a study showing only moderate agreement when diagnosing patients, even among experts. Convolutional Neural Networks (CNNs) are often proposed to detect seizures automatically, achieving high performance. The focus on performance comes at a cost of losing interpretability, leaving the model as effective but seen as a ’black box’. This thesis confronts the interpretability knowledge …

Digital Evidence In Cybersecurity: Legal Constraints And Technical Hurdles, Steffany Butler

Master's Theses and Doctoral Dissertations

The increasing use of digital technologies such as Internet of Things devices, cloud computing, and networked information systems has made digital evidence essential to modern cybersecurity investigations. Digital evidence supports the reconstruction of cyber incidents, identification of responsible parties, and legal proceedings. However, its collection and preservation pose substantial technical and legal challenges. Rapid technological change, strong encryption, data volatility, cloud-based and distributed storage, and variations in jurisdictional privacy and evidentiary laws complicate the timely, reliable, and legally admissible acquisition of digital evidence. This study addresses how investigators can effectively collect and preserve digital evidence while maintaining data integrity, legal …

What Amino Acid Residue Is Responsible For The Interaction Of Atg11 With Its Autophagy Partner Atg9?, Patricia Omoyemwen Woghiren

Senior Honors Theses and Projects

Macroautophagy is a cellular function that involves the formation of a double membrane vesicle that isolates and transports cellular materials to the vacuole or lysosome for degradation and recycling. It is divided into selective and non-selective macroautophagy. Atg11 and Atg9 are two key proteins involved in selective macroautophagy, and their interaction is critical for selective macroautophagy. Specific residues on Atg9 critical for Atg11 binding have been identified, but similar residues on Atg11 have not been identified. The aim of my research was to identify a specific residue critical for Atg11’s interaction with Atg9. To this end, we carried out Yeast-twohybrid …

Analyzing Patterns In Chicago Motor Vehicle Crashes Using Time-Series Techniques, Christina Trotta

Senior Honors Theses and Projects

This project explores time series forecasting of daily traffic crash rates in Chicago from 2018 to 2024, with a focus on understanding how past crash patterns and external conditions influence future risk. The primary research question asks: To what extent does yesterday’s crash rate help predict today’s? Using a combination of Holt-Winters exponential smoothing, Prophet forecasting, and SARIMAX models, we assess the role of autoregression, seasonality, and exogenous variables such as weather and roadway conditions. Daily crash data was cleaned, aggregated, and enriched with engineered features including holiday indicators, weather metrics from O’Hare and Midway airports, and binary flags for …

Pointer Land Game App With Unity, Isaac S. Mullison

Senior Honors Theses and Projects

In this project, I implemented my game concept, Pointer Land, using the Unity game engine. I have implemented the game in the past using other frameworks (such as Flutter), but I thought that doing this using Unity would help me gain two major types of experience: using cross-platform software frameworks in general and using Unity. I found this project to be helpful in doing that. I have found that, with every software framework that I learn, there are new concepts associated with the framework. For Unity, I quickly figured out that a lot of the scripting I was doing involved …

Digital Forensics & Artificial Intelligence: Senior Honors Project Research Report, Noah Shelton Kasir

Senior Honors Theses and Projects

This project studied how current artificial intelligence large language models could be used to learn digital forensics and anti-forensics techniques compared to traditional search engines such as Google Search. This project aimed to answer the question “Can an ordinary person use AI to learn both anti-forensics and traditional digital forensics skills effectively and efficiently?”. The project research was divided into two distinct phases. Phase one consisted of the creation of a fictional case by acting as a layperson using the help of the Microsoft Copilot AI tool. This case consisted of a layperson “suspect” attempting to learn multiple anti-forensics techniques …

The Role Of Leptin In The Regulation Of The Soluble Amyloid Precursor Protein Alpha (Sappa) Levels In Non-Small Cell Lunch Cancer (Nsclc) Cell Media, Benjamin Haddad

Senior Honors Theses and Projects

We previously found that the levels of soluble amyloid precursor protein α (sAPPα) are partly regulated by acetylcholinesterase (AChE) in human non-small cell lung cancer cell lines A549 (p53 wild-type) and H1299 (p53-null). In this study, we hypothesize that sAPPα is partly regulated by leptin, a hormone classically recognized for its anorexigenic role in appetite regulation— yet recently shown to play a role in cancer cell signaling. It was observed that cells treated with leptin exhibited greater concentrations of sAPPα and lower concentrations of Aβ40/42 in the media compared to those of cells left untreated. An opposite effect was observed …

Sickle-Cell Genotyping Cost Analysis In Amua And R, Nicholas P. Haley

Senior Honors Theses and Projects

Sickle cell disease (SCD) is a prevalent genetic disorder in the United States, with a significant economic burden due to the high costs of care, especially from chronic red blood cell (RBC) transfusions. These transfusions carry risks such as alloimmunization, which can lead to complications like delayed hemolytic transfusion reactions (DHTRs), further increasing healthcare costs in addition to increasing suGering. This study aims to aid in the evaluation of cost-eGective strategies for SCD management using Markov models, currently within TreeAge Pro software, which is proprietary. A decision model was adapted from the Kacker et al. (2013) study, which analyzed the …

Codecontext: Integrating External Context For Enhanced Source-Code Model Performance In Software Development, Mohammad Arjamand Ali

Senior Honors Theses and Projects

In the ever evolving field of software development, understanding and maintaining complex codebases is crucial. There exist machine learning models and algorithms that aid in this by specifically learning to ‘understand code’, allowing engineers to build applications that help develop and maintain these large codebases. Although existing source-code machine learning models often overlook an important factor: the code's context. Our research focuses on leveraging external contextual information to enhance source-code model performance. We’ve developed a data pipeline that utilizes CodeQL to extract contextual information from the CodeSearchNet benchmark dataset to extend and create an augmented version of the dataset. We …

Fairness-Aware And Culturally Adaptive Machine Learning For Predicting Adolescent Substance Use, Stephanie Nworgu

Senior Honors Theses and Projects

Early initiation of substance use during adolescence poses significant risks to long-term health, educational attainment, and social outcomes, making early identification a critical public health priority. Machine learning models have increasingly been used to predict substance use risk; however, many such models do not explicitly examine whether predictive performance differs across demographic groups. This senior project examines the fairness of logistic regression models used to predict first-time alcohol use among adolescents. Using nationally representative survey data from the Youth Risk Behavior Surveillance System (YRBSS), pooled across the 2017, 2019, 2021, and 2023 survey cycles, this study develops logistic regression–based predictive …