Digital Commons Network^™

Evaluating Bias In Facial Recognition Datasets : A Study On Representation And Classification Fairness, Milyonta Williams

Theses

Facial recognition technology is widely used in security and identity verification but exhibits biases that disproportionately impact certain demographic groups. This thesis examines racial and skin tone biases in commonly used facial recognition datasets, assessing their influence on classification models. Using manual classification via the Fitzpatrick scale and numerical skin tone representations from LAB color values, we identified significant dataset imbalances, with lighter skin tones (Fitzpatrick Types 1 and 2) overrepresented and darker tones (Types 4-6) underrepresented. Model evaluation using Random Forest, SVM, and XGBoost showed an overall accuracy of 72\%, but classification for Asian individuals was notably weaker (0.45 …

Modifying The L-Tryptophan Affinity Of The Ribosomal Arrest Peptide Tnac, Alexis Orlando Delgado Castillo

Theses

Since creating biosensors from zero has proven a more challenging enterprise than expected, resorting into naturally occurring regulatory systems already characterized represents a more accurate, rapid, and attractive option. Various previous strategies have sought to exploit and modify regulatory elements that sense for different molecules, including monosaccharides (Tang et al., 2008), secondary metabolites (Flachbart et al., 2021), and other amino acids (Della Corte et al., 2020). This study aims to leverage current scientific knowledge and advances concerning the structure and function of the ribosomal arrest peptide TnaC. With this research I integrated the TnaC ribosome-arresting peptide into a new biosensor …

Aviation Weather Forecasting Utilizing An Artificial Neural Network, Joshua Mote

Theses

Weather forecasting is critical to minimize risk and maximize efficiency for flying operations and is challenging due to the uncertainty involved in atmospheric changes. Operational area weather is becoming more critical with the growing reliance on air domain for transportation. This study investigates whether the forecasting accuracy using a Hybrid Long-Short Term Memory (LSTM) Artificial Neural Network (ANN) outperforms the San Antonio International Airport (KSAT) Terminal Aerodrome Forecast (TAF) by integrating diverse data sources – regional Meteorological Aerodrome Report (METAR), TAF, Avian Advisory System (AHAS) Data and geomagnetic activity K Index Data. When tested on one year of historical data, …

Improving Satellite Needs Working Group Assessment Process Through Automation And Process Consolidation, Raj Dangol

Theses

The increasing complexity of modern software ecosystems, presents significant challenges to system resilience, maintainability and automation. This work presents a proof-of-concept implementation of an automation system to address these challenges for a large scale fragmented software systems. Succinctly we address these challenges in the context of Satellite Needs Working Group (SNWG), which is responsible for collecting and communicating federal agencies' Earth observation needs to National Aeronautics and Space Administration (NASA). Multiple automation scripts and applications exist to support the SNWG's assessment cycle, encompassing the areas of data validation, visualization, report generation, and user management. However, the dispersion of these tools …

Surveying Subterranean Biodiversity Of The Tongass National Forest Using Traditional Survey Approaches And Environmental Dna (Edna) Metabarcoding, Jared P. Higgs

Theses

The Tongass National Forest (TNF) is a large temperate rainforest in southeastern Alaska, much of which is underlain by karst. Timber harvest, among other threats, can have detrimental effects on karst habitats; however, the subterranean fauna of this region is understudied and lacks a baseline for monitoring. I spent three field seasons conducting biological assessments of caves in the TNF using two approaches: traditional specimen-based sampling and eDNA metabarcoding. To improve the reference sequence database, I generated 213 novel sequences from invertebrate specimens collected from 35 caves. I also collected 125 water samples from 39 sites for environmental DNA (eDNA) …

Utilization Of Artificial Intelligence To Predict Surface Energy Budget, Joseph Bonucchi

Theses

Estimating heat and moisture exchange between the land and atmosphere has several important practical applications, including water resource management, air pollution forecasting, and atmospheric propagation modeling. Turnkey systems for measuring the surface energy budget typically cost between $5,000 and over $50,000. This study explores the use of artificial intelligence (AI) to predict sensible heat flux (SHF) and latent heat flux (LHF) using inexpensive surface meteorology data and downwelling solar radiation measurements as inputs. Observations from Amer- iFlux sites were used to train several AI models—Convolutional Neural Networks (CNNs), One Dimensional Transformers (1D Transformers), Artificial Neural Net- works (ANNs), and Long …

Information Capacity For Time-Varying Adversarial Networks, Raphael Thorp

Theses

This thesis investigates the capacity of time-varying adversarial networks where intelligent adversaries can corrupt transmissions on restricted subsets of network edges that change availability over time. Building upon the work of Beemer et al. on adversarial network coding with restricted adversaries, we analyze networks whose topology evolves temporally, motivated by applications in space networking and delay-tolerant systems. We introduce different adversarial modes that capture different temporal aspects of corruption behavior and establish their hierarchical relationship with respect to network capacity. The analysis employs time-expanded graph representations and develops recursive counting methods for computing expected network capacity under random time assignments, …

Evaluating Sequential Inference Via Poisson And Change-Point Frameworks, Samuel Johnson

Theses

Sequential testing reduces sample size and costs compared to fixed-sample approaches by allowing decision making during data collection. This thesis investigates sequential methods for Poisson processes and change-point detection. Wald’s sequential probability ratio test (SPRT) and efficiency measures are developed. Practical applications of the SPRT are studied, from detecting noisy sources to classification algorithms. The MaxSPRT is derived, and its critical value algorithm is optimized. The MaxSPRT, a Bayesian SPRT, Wilk’s generalized likelihood ratio test, and the Cash statistic are examined. Various change-point algorithms are surveyed, including Shewhart control charts, cumulative sum methods, homogeneity tests, and multiple change-point approaches. These …

Blockchain Poisoning Attacks In Federated Learning, Mohammad Raihan Uddin

Theses

Federated Learning (FL) enables collaborative model training across distributed clients without sharing raw data, thereby preserving privacy. However, conventional FL depends on a centralized aggregator, exposing it to poisoning and backdoor attacks that threaten model integrity. This thesis introduces B-ZkFed, a blockchain-based and zero-knowledge proof (ZKP)-enhanced FL framework designed to ensure verifiable trust, transparency, and robustness. The blockchain layer decentralizes aggregation through smart contracts, while the ZKP module allows clients to cryptographically prove the correctness of updates without revealing private data. A multi-layer adaptive defense combining gradient-norm filtering, model-similarity analysis, and robust aggregation mitigates poisoning threats under both IID and …

Understanding The Determinants Of Blockchain Adoption: An Empirical Study, Amarpreet Kohli, Nihar Kumthekar, Piyush Shah, Rebecca Jauch

Journal of International Technology and Information Management

Blockchain technology (BT) has the potential to enhance security and robustness of transactions through a distributed ledger bookkeeping process. This study employs technology-organization-environment (TOE) framework and threat-rigidity theory (TRT) to examine whether perceived disruption caused by COVID-19 pandemic significantly impacted the adoption of BT, and inclination to adopt BT in the US. The COVID-19 pandemic provided a unique backdrop, as it affected businesses across all industries, sizes, and geographies. Results show a non-significant effect of perceived pandemic disruption on the current stage of BT adoption and intention to adopt BT. However, disruption readiness positively influences the current stage of BT …

The University Of Texas Permian Basin 2025-2026 Undergraduate Catalog 2025-2026, The University Of Texas Permian Basin

Course Catalogs

No abstract provided.

The University Of Texas Permian Basin 2025-2026 Graduate Studies Catalog, The University Of Texas Permian Basin

Course Catalogs

No abstract provided.

Judicial Economy In The Age Of Ai, Yonathan A. Arbel

Articles

Individuals do not vindicate the majority of their legal claims because of access to justice barriers. This entrenched state of affairs is now facing a disruption. Lawyers and non-lawyers alike are adopting artificial intelligence (AI) tools to perform legal tasks tools that sharply reduce the costs of generating legal materials. There is finally hope that AI might allow many more to access justice.

Paradoxically, what we gain in access to justice we might lose in the delivery of justice. The problem is not that AI tools are ineffective. Indeed, they are even more effective than most realize affecting every stage …

Simplified Soil-Based Approach For Maximum Pressure Prediction In Horizontal Directional Drilling Operations, India Clark

Theses

Horizontal Directional Drilling (HDD) is a trenchless pipeline installation method used in areas where traditional trenching is not feasible due to environmental concerns, existing infrastructure, or other constraints. However, HDD presents significant engineering challenges, with design failures often resulting from excessive installation stresses and Hydro Fracture. Hydro Fracture occurs when the pressure of drilling fluid exceeds the soil’s bearing capacity, leading to unintended subsurface fractures. To mitigate this risk, researchers have relied on the Delft Equation to estimate the maximum allowable mud pressure for borehole stability. However, this equation does have notable limitations and assumptions, which may not accurately reflect …

Sensor Fusion For Enhancing Motion Capture : Integrating Optical And Inertial Motion Capture Systems, Hailey Hicks

Theses

This study aimed to create and evaluate a custom sensor fusion algorithm based on Gauss-Newton optimization that combines Optical Motion Capture (OMC) and Inertial Motion Capture (IMC) measurements to combat the limitations of solely using each system. The goal was to demonstrate how inertial measurement unit (IMU) data can be seamlessly integrated into motion capture data to provide a more efficient and reliable gap filling process for future research. The algorithm takes the first and last frame of OMC data, as quaternions, and fills the rest with IMU gyroscope orientation data to simulate gaps of up to ten minutes. The …

A Deep Learning Multi-Channel Framework For Indoor Image Retrieval, Vidhi M. Bhatia

Theses

Processing and analyzing multi-source image data is vital across a wide range of fields, including artificial intelligence (AI), deep learning, computer vision, geolocation, autonomous navigation, remote sensing, and forensic investigations. Although conventional image matching methods such as Scale-Invariant Feature Transform (SIFT) and Speeded-Up Robust Features (SURF) have proven effective in controlled setting, they often face challenges when applied to diverse datasets that exhibit substantial variations in viewpoint, scale, lighting conditions, and modality. Recent developments in deep learning, including convolutional neural networks (CNNs), transformers, generative adversarial networks (GANs), and self-supervised learning, have led to the creation of more efficient and precise …

Comparing Role Differences Among Systems Architects, Systems Designers, And Systems Engineers, Kelly X. Campo

Theses

The roles of a systems architect (SA), systems designer (SD), and systems engineer (SE) often work together to develop systems, especially as the scale and complexity of engineered systems increase. However, management of these roles can result in ambiguity of task assignments and may reduce accountability for deliverables. Furthermore, there are few published works examining the roles of SAs, SDs, and SEs collectively. This research explores perceptions of the similarities and differences between the roles of SAs, SDs, and SEs by conducting a systematic literature review of 57 sources containing 1064 quotes in addition to a thematic content analysis, analyzed …

Average Heat Flux Measurements In An Additively Manufactured Rotating Detonation Rocket Engine Calorimeter, Matthew Aaron Maybee

Theses

Rotating detonation rocket engines (RDREs) offer benefits over traditional deflagrative engines, including increased engine performance, compact combustion and negligible detrimental thermoacoustic instabilities due to mode-locking. Realizing the benefits of a detonation-based propulsion system will be accompanied by increased thermal loads due to a combination of heat release at elevated pressure and temperature, as well as compact heat release due to detonation. Managing these heat loads necessitates the development of thermal management strategies. As a first step towards establishing the requirements for detonation-based engine thermal management strategies, this work develops an additively manufactured (AM) water-based, axially resolved calorimeter for integration in …

Ammonium Perchlorate Manufacturing Effects On Propellant Burning Rate, Erin Faith Wallace

Theses

This thesis investigates the effect of ingredient variations on the burning rate of reduced smoke, low burning rate composite solid propellant. The effort focused on identical propellant formulations which presented significant burning rate differences correlated with the ammonium perchlorate (AP) source. A series of 1-gallon propellant mixes were prepared and tested utilizing both Manufacturer A and Manufacturer B ammonium perchlorate to investigate the propellant burning rate and pressure exponent shift anomaly and correlate those findings to the differing ingredient properties between the two AP lots. Each propellant mix was evaluated for burning rate utilizing subscale test motors and a scanning …

Near-Field Analysis Of Horn Antennas For Electromagnetic Compatibility Testing, Landon Riley Carroll

Theses

Standard gain horn antennas are widely used in electromagnetic compatibility (EMC) testing and antenna measurements. In EMC testing, it is often required to generate high electric field intensities across a wide frequency range within the near-field region. However, the focusing properties of antennas are deteriorated in the radiating near-field region. In order to increase engineering confidence in EMC testing, it is desirable to understand the root causes of the aforementioned radiation degradation. In this thesis, the near-field characteristics of three different pyramidal standard gain horns are investigated using full-wave analysis, analytical methods, and measurement. The causes of near-field gain reduction …

Factors Affecting Freshwater Fish Communities In Two North Alabama Counties, Joshua Fitts

Theses

This study examined how physical habitat characteristics influence freshwater fish diversity in streams of Madison and Limestone Counties, Alabama. Ten 150-meter stream reaches were sampled using backpack electrofishing and seining, with habitat variables measured at fixed transects. Principal component analysis identified four main habitat gradients representing flow and substrate, channel size, gravel dominance, and canopy–bedrock conditions. Although overall species richness and Shannon diversity were not significantly related to these gradients, species-specific correlations revealed clear ecological preferences. Regression models showed that root wads, herbaceous vegetation, and riprap modestly increased richness, emphasizing the role of structural diversity. These findings highlight the importance …

Legal Writing Manual (4th Ed.), Jean Mangan, Dylan Cohen, Frank Easterlin, Brittany Goad, Gabrielle Gravel, Chase Lyndale, George "Max" Miseyko, Emily Whitest

Books

This manual provides you with an overview of first-year legal writing topics and provides checkpoints during your writing process. On the other hand, this manual does not answer every question you have ever had on any legal writing concept and it is certainly not a spellbook that will make you instantly awesome at legal writing. Writing as a skill is a lifelong development process. Everyone can be an effective legal writer. Put in the time to study the concepts and then to practice using those concepts in your writing. Seek feedback on your writing and implement the feedback you receive. …

Serious Bacterial Infections And Hepatitis C Virus Among People Who Inject Drugs, Thomas J. Stopka, Robin M. Nance, L. Sarah Mixson, Hunter Spencer, Judith I. Tsui, Judith M. Leahy, Mai T. Pho, Jean Dejace, Judith Feinberg, April M. Young, Wei Teng Yang, Amelia Baltes, Eric Romo, Randall T. Brown, Kerry Nolte, William C. Miller, William A. Zule, Wiley D. Jenkins, Joseph A. Delaney, Peter D. Friedmann

Epidemiology and Environmental Health Faculty Publications

Limited research has examined the possible synergistic interrelationships between serious bacterial infections (SBIs) of the heart (i.e., endocarditis), bone, spine, brain, or joints (e.g., osteomylelitis) and hepatitis C virus (HCV) infections. We examined whether syndemic interactions existed between SBI, HCV, and substance-use-related factors in rural communities, hypothesizing that injection-mediated risks elevated the likelihood for both SBIs and HCV infections, which could be exacerbated by synergistic biological–biological or biological and social interactions. We calculated the prevalence ratios (PRs) of past-year SBI associated with each risk factor in separate models. Effect modification among significant risk factors was assessed using multiplicative interaction. Among …

Viral Transcript And Tumor Immune Microenvironment-Based Transcriptomic Profiling Of Hpv-Associated Head And Neck Squamous Cell Carcinoma Identifies Subtypes Associated With Prognosis, Anastasiia Nikitina, Daria Kiriy, Andrey Tyshevich, Dmitry Tychinin, Zoya Antysheva, Anastasya Sobol, Vladimir Kushnarev, Nara Shin, Jessica H. Brown, James Lewis, Krystle A. Lang Kuhs, Robert Ferris, Lori Wirth, Nikita Kotlov, Daniel L. Faden

Epidemiology and Environmental Health Faculty Publications

Human papillomavirus (HPV)-associated head and neck squamous cell carcinoma (HPV-positive HNSCC) has distinct biological characteristics from HPV-negative HNSCC. Using an AI-based analytical platform on meta cohorts, we profiled expression patterns of viral transcripts and HPV viral genome integration, and classified the tumor microenvironment (TME). Unsupervised clustering analysis revealed five distinct and novel TME subtypes across patients (immune-enriched, highly immune and B-cell enriched, fibrotic, immune-desert, and immune-enriched luminal). These TME subtypes were highly correlated with patient prognosis. In order to understand specific factors associated with prognosis, we used the unsupervised clustering of an HPV-positive HNSCC cohort from The Cancer Genome Atlas …

Document Encoding Effects On Large Language Model Response Time And Consistency, Dianeliz Ortiz Martes, Nezamoddin N. Kachouie

Mathematics and System Engineering Faculty Publications

Large language models (LLMs) such as GPT-4 are increasingly integrated into research, industry, and enterprise workflows, yet little is known about how input file formats shape their outputs. While prior work has shown that formats can influence response time, the effects on readability, complexity, and semantic stability remain underexplored. This study systematically evaluates GPT-4’s responses to 100 queries drawn from 50 academic papers, each tested across four formats, TXT, DOCX, PDF, and XML, yielding 400 question–answer pairs. We have assessed two aspects of the responses to the queries: first, efficiency quantified by response time and answer length, and second, linguistic …

Monte Carlo Gradient Boosted Trees For Cancer Staging: A Machine Learning Approach, Audrey Eley, Thu Thu Hlaing, Daniel Breininger, Zarindokht Helforoush, Nezamoddin N. Kachouie

Mathematics and System Engineering Faculty Publications

Machine learning algorithms are commonly employed for classification and interpretation of high-dimensional data. The classification task is often broken down into two separate procedures, and different methods are applied to achieve accurate results and produce interpretable outcomes. First, an effective subset of high-dimensional features must be extracted and then the selected subset will be used to train a classifier. Gradient Boosted Trees (GBT) is an ensemble model and, particularly due to their robustness, ability to model complex nonlinear interactions, and feature interpretability, they are well suited for complex applications. XGBoost (eXtreme Gradient Boosting) is a high-performance implementation of GBT that …

Education About, In, And For Wetlands: Practices, Premises, Possibilities, And Challenges, Tom Marcinkowski

Mathematics and System Engineering Faculty Publications

The purpose of this paper is to review areas of educational theory, research, and practice relevant to wetlands education, notably education about, in, and for wetlands. Five key areas are reviewed: (a) from the Report of the Intergovernmental Conference on Environmental Education, goals and objectives for wetlands education; (b) from the literature, major curricular and instructional approaches in and elements of wetlands education; (c) from the literature, broad instructional strategies available to and commonly used in wetlands education; (d) from websites of federal agencies in the U.S., education, outreach, and training programs that focus on education about, in, and for …

Ground-Based Cloud Type Classification For Aviation Weather Hazard Detection Using Deep Learning, Marcus P. Cote, Michael E. Splitt, Steven M. Lazarus, Ryan T. White, Cecilia G. Baker

Mathematics and System Engineering Faculty Publications

General aviation pilots who encounter hazardous weather face a heightened risk of fatal accidents compared to those in other sectors of aviation. To help avoid unplanned weather encounters, accurate information on cloud type and sky conditions can enhance situational awareness and hazard recognition. Among available weather information resources, ground-based webcam networks are growing for aviation meteorology and other interests such as wildfire monitoring. These webcams can provide near-real-time visual weather information to pilots, especially in regions of complex terrain where traditional weather observation methods may lack adequate spatial and temporal coverage. To harness the benefits from webcams while reducing the …

Potentiation Of Gelonin Cytotoxicity By Pulsed Electric Fields, Olga N. Pakhomova, Eleni Zivla, Giedre Silkuniene, Mantas Silkunas, Andrei G. Pakhomov

Bioelectrics Publications

Gelonin is a ribosome-inactivating protein with extreme intracellular toxicity but poor permeation into cells. Targeted disruption of cell membranes to facilitate gelonin entry is explored for cancer and tissue ablation. We demonstrate a hundreds- to thousands-fold enhancement of gelonin cytotoxicity by pulsed electric fields in the T24, U-87, and CT26 cell lines. The effective gelonin concentration to kill 50% of cells (EC₅₀) after electroporation ranged from <1 nM to about 100 nM. For intact cells, the EC₅₀ was unattainable even at the highest gelonin concentration of 1000 nM, which reduced cell survival by only 5–15%. For isoeffective electroporation treatments using 300 ns, 9 µs, and 100 µs pulses, longer pulses were more efficient at lowering gelonin EC₅₀. Increasing the electric field strength of 8, 100 µs pulses from 0.65 to 1.25 kV/cm reduced gelonin EC₅₀ from 128 nM to 0.72 nM. Conversely, the presence of 100 nM gelonin enabled a more than 20-fold reduction in the number of pulses required for equivalent cell killing. Pulsed electric field-mediated delivery of gelonin shows promise for hyperplasia ablation at concentrations sufficiently low to minimize or avoid systemic toxicity.

Anabolic Properties Of The Progestin Altrenogest And Its Regulation As An Environmental Substance In Horse Racing – Review And Analysis, Andreas F. Lehner, Levent Dirikolu, Sarah Jacob, Kimberly Brewer, Abelardo Morales Briceñoe, Robert Holland, George Maylin, Clara Fenger, Thomas Tobin

Maxwell H. Gluck Equine Research Center Faculty Publications

Altrenogest is a progestogen substance used in equine medicine for the synchronization of ovulation during the spring breeding season and the control of estrus in mares. It accomplishes its actions by down-regulation of endometrial progesterone receptors and repression of estrogen receptor transcriptional activation. However, various groups have also measured androgen receptor binding activity for altrenogest in vitro; these findings combined with androgenic and anabolic properties roughly 1/20 in potency of testosterone and its structural similarity to the anabolic steroid trenbolone have created concerns among racing authorities of altrenogest’s potential abilities to alter the outcome of equine athletic performance, even though …