Digital Commons Network^™

A Comparative Machine Learning Framework For Identifying Ai-Generated Versus Real Celebrity Faces, Sidney Gehring

Data Science Undergraduate Honors Theses

The rapid advancements in the world of generative artificial intelligence has enabled the creation of highly realistic fictitious facial images, raising concerns about authenticity and bias in computer vision systems. This study investigates the capabilities of machine learning models to distinguish between real and artificially generated facial images across gender and race focusing on celebrity imagery. Four datasets were used against the classification model, each trained on images of a single celebrity within distinct demographic groups: White women, White men, Black women, and Black men. For each group, real images are paired with AI-generated counterparts designed to closely replicate the …

A Forecasting Framework For Distribution Center Capacity Utilization: An Applied Industry Study, Jordan J. Shortt

Data Science Undergraduate Honors Theses

This project develops and evaluates a predictive modeling framework for forecasting distribution center capacity utilization at Company Y, with monthly forecast horizons up to one year. Motivated by the operational challenges of seasonal demand volatility, promotional cycles, and the absence of a formally defined capacity metric, the study first constructs a historical capacity utilization measure from raw warehouse management system data — reconciling item volumes, location dimensions, and utilization factors across all DCs — which serves as the target variable for all modeling work. Four models are developed and evaluated against a naïve seasonal baseline: SARIMA, LightGBM, LSTM, and a …

Developing Tracking Compliance Standards For Inbound Freight: A Data-Driven Industry Application At O’Reilly Automotive, Jackson Endacott

Data Science Undergraduate Honors Theses

Visibility of inbound freight is critical for managing operational efficiency, yet many organizations lack standardized compliance metrics for third-party carriers to uphold, preventing them from utilizing tracking data to make data-driven decisions. During a summer internship with the Transportation Department at O’Reilly Automotive, data inconsistencies were addressed in the Transportation Management System (TMS), and that data was utilized to create tracking compliance standards for third-party carriers. Data populated from various sources within O’Reilly’s TMS was cleaned, validated, and utilized to create a Tracking Scorecard that evaluates message transmission rates, timeliness, and errors. This tool provides actionable insights to improve tracking …

Pyspqr: A Python Package For Density Estimation Using Deep Learning, Cameron Eddy, Reetam Majumder

Electrical Engineering and Computer Science Undergraduate Honors Theses

Splines are used for representing complex functions. In statistics, splines can be used for distributional shapes that are difficult to model by traditional parametric approaches. Ramsay (1) uses M-Spline bases to estimate continuous distributions. Semi-Parametric Quantile Regression (SPQR), developed by Xu and Reich (2), models conditional distributions where a neural network is used to estimate the basis function weights that depend on covariates. (3) implements a package for SPQR in R. We build on this by implementing a version of SPQR in Python with PyTorch. By using PyTorch, we can use more sophisticated deep learning architectures than those available in …

Towards Multi-Hop Retrieval Using Bipartite Question-Oriented Graphs, Micah Mccollum

Electrical Engineering and Computer Science Undergraduate Honors Theses

Accurately answering multi-hop questions requires full retrieval of multiple, interdependent passages and is a long-standing problem in the area of natural language question answering (QA). While retrieval-augmented generation (RAG) helps address single-hop questions, many retrievers presently focus on semantic similarity in a dense vector space, which is insufficient for handling multi-hop questions specifically. To ameliorate this, we propose constructing a bipartite question- oriented graph composed of hypothetically generated questions connected to passages at index time. The construction of the graph is guided by a large language model (LLM) to prioritize the formation of edges that signal whether a question can …

Evaluating The Use Of Extended Reality Technology To Improve Marching Band Conducting Patterns, Nathan R. Fuhrman

Electrical Engineering and Computer Science Undergraduate Honors Theses

Conducting pattern consistency is an essential skill for marching band drum

majors, yet developing this consistency through individual practice remains diffi-

cult without real-time feedback. This thesis investigates if the use of extended

reality technologies can be used to enhance the conducting skills of novice drum

majors. Using the Meta Quest 3’s passthrough capability, the system overlays vi-

sual feedback elements — including a 3D pattern guide, path visualization, tempo

cues, and a real-time score — onto the user’s physical environment. A within-

subjects study with seven participants evaluated eight combinations of three binary

feedback variables: pattern guide visibility, tempo …

​Autonomous Agentic Orchestration For Physics-Aware Scientific Discovery: An Integrative Multimodal Framework For 2d Material Characterization​, Sankalp Pandey

Electrical Engineering and Computer Science Undergraduate Honors Theses

The advancement of next-generation semiconductor and quantum technologies relies on the scalability of the fabrication of two-dimensional (2D) van der Waals heterostructures. However, this process is severely bottlenecked by characterization workflows. Optical microscopy provides high-throughput imaging of 2D material flakes, but lacks the explicit physical priors required for the discernment of sub-nanometer thickness variations, such as distinguishing monolayers from bilayers. The use of computer vision models to automate the localization and characterization process of the flakes was proposed. As a part of this effort, we develop QuantumFlake, an open-source framework to streamline the integration and deployment of computer vision models …

Shooting For The Stars: Stem Outreach Strategies Between 2nd And 7th Grade, Paige Miller

Chemical Engineering Undergraduate Honors Theses

Engineering and planetary science outreach programs are increasingly important as industries and research organizations face growing demand for STEM professionals. Despite the importance of these fields, many students receive little exposure to engineering careers during their early educational experiences. This honors thesis examines the effectiveness of interactive STEM outreach presentations designed for elementary and middle school students. Specifically, this study evaluates outreach activities centered on chemical engineering applications and the NASA M2M CO₂ regeneration project for Martian environments.

Two student age groups participated in this study: 2nd grade students at Butterfield Elementary School and 7th grade students at Woodland Junior …

Modeling Hot Jupiter Atmospheres For The Classification Of Low Abundance Molecules, Mika Brown

Physics Undergraduate Honors Theses

Transmission spectroscopy is a powerful method for studying exoplanet atmospheres. With the recent launch of the James Webb Space Telescope (JWST), several molecules have been successfully detected in hot Jupiter atmospheres at an unprecedented level of precision with transmission spectroscopy. To better understand current detection capabilities and limitations, this project used machine learning techniques to determine which molecules are currently identifiable at the spectral resolution and wavelength range of JWST’s NIRSpec instrument in PRISM mode. A large synthetic dataset of transmission spectra was first generated using the petitRADTRANS radiative transfer Python package. The resulting spectra were then used to train …

Real-Wastewater-Derived-Struvite Effects On Micronutrients In Runoff Water, Lauren E. Pruitt

Crop, Soil and Environmental Sciences Undergraduate Honors Theses

Phosphorus (P) is an essential nutrient needed in agriculture for proper plant growth and development and is often introduced into agricultural systems in the form of synthetic P fertilizers. Mined rock phosphate is the primary P source for the production of synthetic P fertilizers and is a finite resource. Struvite (MgNH₄PO₄·6H₂O) is a compound that can be precipitated from municipal wastewater, recovering P, and is currently being evaluated for its potential use as an alternative fertilizer-P source. The objective of this study was to evaluate the effects of fertilizer-P source [i.e., synthetic electrochemically precipitated …

Construction Impacts On Nutrient Loads In An Urban Stream In The Ozark Highlands, Matthew B. Wilson

Crop, Soil and Environmental Sciences Undergraduate Honors Theses

Degradation of water quality is primarily caused by human activity, including urbanization. Urban stream syndrome can be characterized as a stream that has undergone physical, chemical, and biological changes as a result of urbanization, which can include an influx of nutrients that can drive unwanted plant and algae growth. It is known that construction can result in untreated nutrients entering a stream; however, it is not understood how construction affects downstream nutrient transport. The objective of this study was to understand the impacts of construction on urban water quality in Tanglewood Branch in Fayetteville, Arkansas, in the Ozark Highlands, which …

Clawing Our Way To Inclusion: Identifying Minority Students’ Barriers To Entering The Veterinary Medicine Profession, Danielle Reeves

Animal Science Undergraduate Honors Theses

Veterinary services are being utilized more each year as pet owners are increasingly viewing and treating their pets like family members. Due to this changing perspective, the veterinary profession has grown significantly. Yet, despite this change, there is a lack of ethnic/racial diversity within the veterinary field. The purpose of this study was to determine the factors and/or barriers associated with minority students' desire or lack of desire to pursue a career in veterinary medicine. This study used an online survey tool to collect qualitative and quantitative data from 423 undergraduate students at the University of Arkansas during the spring …

An Explanation Of Alternatives Within A Portfolio, Isaac J. Reitman

Finance Undergraduate Honors Theses

This thesis attempts to provide insight into the role of alternative investments within modern portfolio construction for accredited and institutional investors.

The asset classes discussed are as follows: private credit, private equity, venture capital, hedge funds, collectibles, and real estate.

Modular Category Optimization For Substitutability: An Item-Level Approach, Medhansh A. Sankaran

Data Science Undergraduate Honors Theses

This thesis examines substitutability within Walmart apparel as a foundation for modular category optimization. Using large-scale item-level data, I develop an attribute-based framework that aggregates products to the fineline level, constructs a structured feature space, and identifies candidate substitute relationships through similarity-based matching within relevant merchandise groupings. The results show that Walmart item master data contains sufficient structure to support scalable substitute generation across a high-variety assortment. However, substitutability is not uniform: many item pairs exhibit high similarity but low observed demand transfer, indicating that structural similarity alone does not guarantee substitution. To address this, the framework is positioned within …

Recursion, Regurgitation, And Regeneration: Testing Limits And Revealing Biases Of Generative Ai Models Through Multimodal Feedback Loops, William Donnell-Lonon

Data Science Undergraduate Honors Theses

Contemporary generative AI systems such as OpenAI's GPT-4o and DALL-E models embed complex priors about society, reality, and history shaped by training data distributions, social alignment procedures, legal constraints, and safety regulations. This study uses a "telephone game" methodology to investigate how embedded social, political, and visual biases propagate and reveal themselves through iterative multimodal generation loops, where image captioning and text-to-image models are chained in successive feedback cycles.

Using CLIP similarity metrics, facial recognition algorithms, semantic drift analysis, and qualitative content observations, I tested how image subject matter affects the rate and quality of semantic and visual shift, identity …

Escaping The Promotion Trap: A Machine Learning Framework For Brand Equity Preservation In Beverage Cpg, Lucas P. Jones

Data Science Undergraduate Honors Theses

When companies acquire beverage brands, they typically value them based on total sales revenue. This traditional approach treats all sales equally over time, whether they are driven by genuine consumer demand or temporary discounts. This is important because while promotions can boost short-term sales, they tend to erode brand value over long periods of time. The measurement problem extends to acquisitions, where buyers lack the tools to distinguish real consumer demand from artificial promotional inflation.

This thesis develops a framework to separate genuine baseline demand from promotional dependence using Nielsen scanner data covering 189 beverage brands across 188,304 weekly observations …

A Spatial Analysis Of Streetlights In The City Of Sugar Land, Samuel J. Trout

Data Science Undergraduate Honors Theses

The purpose of this paper is to analyze patterns between public safety and streetlighting for the City of Sugar Land, TX so that they may better protect their citizens.  The data involved come from the City of Sugar Land’s public works division and include type and location for all the attributes. The method of doing so involved visualizing the patterns of streetlights and their closest light readings to visualize which streetlights are underperforming using the Shiny package in R. Statistical tests were also used to quantify the association between lighting, crime occurrence, and crosswalks. From this, and the literature review, …

Harness: Hybrid Architecture For Resilience In Networked Engineering System Simulations, Daniel Scott

Graduate Theses and Dissertations

This dissertation presents the development of HARNESS, a unified, domain-agnostic framework for the modeling, optimization, and evaluation of complex systems under conditions of degradation and uncertainty. The research addresses a persistent challenge in systems engineering: the lack of a generalizable, behaviorally grounded approach for quantifying resilience and robustness across diverse domains. HARNESS integrates graph-theoretic dependency modeling, GPU-accelerated evolutionary optimization, and agent-based simulation into a modular architecture that enables both system design and diagnostic analysis. The framework models system interdependencies through user-defined components, parameters, and constraints, allowing architectures to evolve dynamically while maintaining structural validity. A mutation-only genetic algorithm with a …

Soil Moisture Regime Effects On Near-Surface Soil Chemical Properties In Alfisols Under Native Tallgrass Prairie In Arkansas, Sydney M. Talley

Crop, Soil and Environmental Sciences Undergraduate Honors Theses

Tallgrass prairie ecosystems provide many crucial ecosystem services, including nutrient cycling and storage, organism habitat, and soil and water conservation. However, tallgrass prairies are considered an endangered ecosystem, particularly in the Ozark Highlands and Grand Prairie regions of Arkansas, where less than 0.05% of Arkansas’ original prairie land area remains. Understanding soil nutrient supplies over time in native tallgrass prairie ecosystems is critical for quantifying the success of restoration and rehabilitation activities. The objective of this study was to evaluate the effects of soil moisture regime (SMR) (i.e., aquic and udic), region (i.e., Ozark Highlands and Grand Prairie), and their …

Bounded Multiplication And Composition Operators On Sequence Besov Spaces, Robert Anderson

Mathematical Sciences Undergraduate Honors Theses

The sequence Besov space $b_p$, $p>1$, is the space of analytic functions $f(z)=\sum_{n=0}^{\infty} a_n\, z^n$ on the open unit disk

$\mathbb D$ with $$\sum_{n=0}^{\infty} n^{p-1}\, |a_n|^p< \infty\, .$$

We will give a brief introduction to the space $b_p$, as well as explore how certain operators behave on the space. For example, let $\varphi$ be an analytic self-map of $\mathbb D$. We study the multiplication operator $M_\varphi$ on $b_p$ and look at examples including when $\varphi$ is a polynomial. We also study the composition operator $C_\varphi$ on $b_p$, and in more depth on $b_2$ the Dirichlet space. The culmination will be an …

Enhancing Food Security In Stann Creek. Belize Using Meat Rabbits, Lindsey Garretson

Crop, Soil and Environmental Sciences Undergraduate Honors Theses

In recent years, food insecurity and the prevalence of hunger have rapidly grown throughout the world, but especially within Latin America and the Caribbean. Along with growing rates of food insecurity and hunger there are increases in medical conditions including negative impacts the functioning of every major organ system, increased rates of mental illness, both overweight and underweight children, wasting in both children and adults, and anemia. Availability and access to healthy, nutritional food options can help lower the risk of these conditions. With these considerations, the goal of this project was to create an all-encompassing manual and construction guide …

From Data Digitization To Personalized Care: Deep Learning And Decision Analytics In Healthcare Systems, Ahla Ko

Graduate Theses and Dissertations

This dissertation traces a progression from foundational data infrastructure to individualized clinical decision-making, developing and evaluating three computational frameworks that advance healthcare efficiency and personalization through deep learning and decision analytics. The first study presents an end-to-end pipeline for automated recognition of handwritten medical forms, addressing persistent challenges in health data digitization. Integrating a YOLO-based field detection model, a Convolutional Recurrent Neural Network (CRNN) for text transcription, and a confidence-based human-in-the-loop quality assurance framework, the system achieved 99.75\% Exact Match Accuracy and a 0.13\% Character Error Rate on medical forms collected from a tuberculosis research project in Moldova. A GPU-accelerated …

A Spatial Analysis Of Socioeconomic Characteristics And Community Vulnerability To Natural Hazards In Arkansas, Emma Steuber, Brad Peter

Geosciences Undergraduate Honors Theses

Natural hazards have become more frequent in recent years, and because of their destructive impacts, it is crucial to locate regions that are most affected historically by hazardous events and identify what socioeconomic characteristics co-occur spatially. While many studies have analyzed this relationship at national and state scales, few have focused specifically on Arkansas, and even fewer have incorporated multiple socioeconomic characteristics. Comparing the spatial distribution of community characteristics in Arkansas with zones of common natural hazards is essential for identifying who is most at risk. This study utilizes Geographic Information Science (GISci) to examine and map the spatial relationship …

Survival Patterns Among Adult And Pediatric Bone Cancer Patients, Ethan Estes

Mathematical Sciences Undergraduate Honors Theses

Recently noted, Huang et al. (2023), machine learning (ML) models, while offering great advantages over traditional statistical predictive modeling methods, are less explored in the analysis of survival and other similar time-to-event predictive data modeling. ML methods such as neural networks offer a great deal of promise but need to be further explored to investigate their comparative power in predicting survival outcomes. Focusing specifically on survival analysis in adult and pediatric bone cancer patients, traditional methods, like shown in Emmert-Streib and Dehmer (2019), will be shown with machine learning models using methods in Hothorn, Hornik, and Zeileis (2006). In this …

Geospatial Science And The Changing Environment: Applied Methods For Sustainable Agriculture And Landscape Management, Harrison Wakefield Smith

Graduate Theses and Dissertations

Rapid environmental change is disrupting agricultural productivity, ecological function, and the long-term resilience of managed landscapes. At the same time, the rapid growth of geospatial data science has improved our understanding of environmental change and increasingly is being used to improve sustainability in agricultural and environmental management. However, critical gaps remain that limit the applicability of data-driven insights in landscape management. This dissertation investigates the potential of geospatial analytics for sustainable agriculture and landscape management, with a focus on applied methods that operate across spatial and temporal scales. Using field, landscape, regional, and national datasets, it explores the capabilities and …

Can Methanogens Grow On Asteroids?, Isabella N. Reimer

Biological Sciences Undergraduate Honors Theses

Because of asteroids’ chemical features, they may serve as potential environments for life and are of interest in astrobiology. Dr. Kral’s laboratory studies methanogens, microorganisms in the domain Archaea, as possible life forms on extraterrestrial bodies. Since some methanogens can withstand harsh environmental conditions and produce methane as a waste product, methane production can be used as an indicator of potential microbial activity.  In this study, three methanogen species, Methanothermobacter wolfeii, Methanobacterium formicicum, and Methanosarcina barkeri were tested for growth on asteroid simulants based on the Orgueil (CIE-1) and Murchison (CME-1) meteorites. First, methanogen growth was assessed in the …

The Environment, Health, And Vector Nexus: Evaluating The Spatiotemporal Variability And Societal Impact Of Ticks In Arkansas, Dalton Williams

Graduate Theses and Dissertations

Tick-borne diseases (TBDs) are a surging public health and veterinary concern in the United States. In states like Arkansas, climate change and shifting land use have recalibrated the ecological niches of vector species. This research utilizes species distribution and ecological niche modeling to assess the spatiotemporal suitability of ixodid tick habitats, specifically where environmental and socioeconomic factors intersect. By integrating spatial science with public health frameworks, this study identifies priority intervention areas in underserved rural regions where healthcare resources are often constrained. This study provides a comprehensive methodological framework, leveraging remote sensing datasets and historic disease data to delineate exposure …

Cross-Facility Reliable Deep Learning Based Beef Marbling Assessment Via Unsupervised Domain Adaptation Regression, Samuel Vinson

Biological and Agricultural Engineering Undergraduate Honors Theses

Inconsistent quality grading in beef production leads to inefficiencies, economic disparity, and consumer mistrust. While USDA meat grading traditionally relies on skilled visual inspectors, these human evaluations suffer from cross-facility variability and subjectivity. This paper introduces the first known application of unsupervised domain adaptation regression for cross-facility beef marbling score prediction—an innovation that improves generalization across diverse environments in the beef supply chain. Utilizing numerical scores ranging from 100-900, the research employed convolutional neural networks (CNNs), including ResNet, VGG, and AlexNet architectures. The study specifically introduced and validated a unified unsupervised domain adaptation regression method using the ResNet-50 architecture to …

A Systems Approach To Nitrogen Fertilizer Management: Modeling Emissions And Runoff Pathways In Arkansas Agriculture, Avonelle Lindon

Biological and Agricultural Engineering Undergraduate Honors Theses

Nitrogen fertilizer management is a critical challenge in modern agriculture. This thesis develops a system dynamics model of nitrogen in Arkansas rice and corn systems to explore barriers to translating agricultural research into practical farmer guidance.  The modeling process revealed key challenges: (1) scarcity of Arkansas-specific factors and best management practice (BMP) effectiveness data; (2) tension between model comprehensiveness and accessibility; (3) misalignments in conservation incentive structures; and (4) difficulty in validating models without field measurements. The resulting model demonstrates basic nitrogen cycle processes and BMP integration, but validation against published literature revealed significant issues with predictive accuracy. These findings …

Understanding Grain Market Behavior: A Distributional Analysis Of Soybean And Corn Futures During Political And Global Disruptions, Caroline Brickey

Agricultural Economics and Agribusiness Undergraduate Honors Theses

This thesis analyzes soybean and corn futures over six years to evaluate how major global events influence volatility, price movement, and trader positioning. Using quantitative market data, the study identifies patterns of market sensitivity and event driven shocks, showing how uncertainty shapes commodity futures behavior and short term price dynamics during political and global disruptions.