Physical Sciences and Mathematics Commons^™

Vision-Based Vibration Monitoring Of Civil Structural Damage Detection Using A Low-Cost Autonomous Uav, Javier Antonio Becerril

Theses and Dissertations

This thesis presents the development and experimental validation of a low-cost autonomous unmanned aerial vehicle (UAV) for non-contact vibration-based structural damage detection. We extract structural vibration signals directly from video recordings captured by the onboard camera during flight. The extracted vibration signals are analyzed in the frequency domain to identify natural frequency shifts associated with structural degradation and damage.

To evaluate the effectiveness of the proposed approach, a laboratory-scale steel frame structure is tested under both healthy and simulated damage conditions. In contrast to advanced commercial UAV inspection systems, the developed UAV achieves comparable inspection capability at a significantly lower …

Pesticides And Poverty: How Socioeconomic Factors Relate To Pesticide Application In The Continental Us, Reed Smetter

Theses and Dissertations

Pesticides are often used to help reduce the populations of weeds, insects, and pathogens in agricultural and urban settings, reducing the risk of outbreaks and losses of agricultural yield. The communities that surround agricultural areas often bear the brunt of the negative community and environmental health effects of these chemicals, and are frequently rural, poor, and lack critical infrastructure resources. Pesticide application volumes are often linked closely with specific health effects. In this study, I apply social vulnerability theory to compare the potential connections between the application rates of pesticides and socioeconomic variables across the United States using a nationwide …

A Visit-Count-Based Complete Foraging Strategy For Robot Swarms, Arturo Yahir Gonzalez

Theses and Dissertations

Swarm robotics systems often rely on a balance between exploration and exploitation to perform tasks like Central Place Foraging. While exploitation methods such as pheromone trails and site fidelity are well-studied, the efficiency of the underlying random search exploration remains a challenge, frequently leading to redundant coverage and wasted time as multiple agents repeatedly search the same fruitless areas. This thesis introduces a memory-enhanced exploration strategy designed to improve the efficiency of random search in a swarm of simple robots.

In our proposed algorithm, each robot, constrained with limited memory, periodically logs its recent locations while exploring. This spatial data …

Spatiotemporal Evolution Of Flow Decline And Water Consumption In A Highly Regulated Transboundary River: The Lower Rio Grande/Bravo, Ana Yarely Casillas Rodriguez

Theses and Dissertations

Long-term flow variability in transboundary rivers reflects the combined influence of water availability, infrastructure development, and binational water use. Integrating historical discharge with evolving water-use data remains challenging due to fragmented records and nationally bounded assessments. This study reconstructs a 125-year discharge record (1900–2025) from historical Water Bulletins and modern observations at 12 gauging stations, providing a spatiotemporal assessment of flow evolution and water-budget components in the Lower Rio Grande/Bravo (LRG).

Discharge records were grouped into four hydrologic regimes—natural (1900–1913), pre-dam (1935–1950), post-dam (1974–1989), and modern (2010–2025)—and analyzed alongside binational water-use data across major sectors. A basin-scale water budget, using …

Probing The Dynamic Behavior Of The Androgen Receptor In The Presence Of Heptyl And Methyl Parabens, Edgardo De Leon

Theses and Dissertations

The androgen receptor (AR) mediates physiological signaling from endogenous androgens, a function that can be disrupted by endocrine disruptors with serious reproductive and developmental consequences. Parabens, widely used preservatives, inhibit AR signaling in cell-based assays, with inhibitory potency correlating with alkyl chain length: heptylparaben exhibits stronger antagonism than methylparaben, which shows no effect. We hypothesize this differential potency arises from allosteric modulation at the AR Binding Function 3 (BF-3) site, altering dihydrotestosterone (DHT) binding dynamics. Docking calculations using antagonist-bound AR crystal structures, followed by molecular dynamics simulations, show that methylparaben fails to remain bound at BF-3, whereas heptylparaben maintains stable …

Morphological Evolution And Sediment Budget Of A Flood-Tidal Delta On The Rio Grande Delta Plain: Bahia Grande, Texas, Usa, Aleen Pertuz Paz

Theses and Dissertations

The Isabel Delta is a recently formed flood-tidal delta within the restored Bahia Grande system on the Rio Grande Delta Plain, Texas, USA, where renewed tidal connectivity has created conditions for rapid sediment buildup and landform evolution. This study quantified morphological changes from 2008 to 2025 using satellite imagery. It assessed sediment retention by comparing the effective sediment discharge required to reproduce observed delta growth with field-based estimates of sediment supply derived from channel hydrodynamics, cross-sectional area, and suspended sediment concentration. The delta expanded steadily throughout the study period, with increases in bar, channel, and total surface area, and an …

On The Structure Of The Homotopy Lie Algebra Of Local Rings, Dawson M. Strong

Theses and Dissertations

This thesis investigates the construction and homological properties of the homotopy Lie algebra π(R) of a commutative local ring (R,m,k). Drawing upon the theoretical framework of differential graded (DG) algebras, we first establish the theory of minimal free resolutions and other standard topics in homological algebra. The core of this work details the iterative construction of the acyclic closure R⟨Y⟩ of k over R, which is achieved by the systematic adjunction of exterior and divided power variables to eliminate cycles in homology. We demonstrate that this acyclic closure serves as a minimal free resolution and provides the means to define …

Accurate Polyp Segmentation With Visual Mamba, Diego Adame

Theses and Dissertations

Medical image segmentation is a fundamental task in computer-aided diagnosis because it enables precise delineation of anatomical structures and pathological regions from clinical images. While convolutional neural networks and Transformer-based models have achieved strong performance on many medical segmentation benchmarks, CNNs struggle to model long-range dependencies and Transformers often incur high computational complexity for high-resolution medical images. Recently, state space models have emerged as an efficient alternative for dense prediction tasks due to their ability to capture long-range dependencies with linear complexity. However, existing Mamba-based segmentation models still rely on pixel-wise raster scanning that disrupts spatial locality and use simple …

Soil Water Content Beneath Agrivoltaic Installations In A Subtropical Semi-Arid Climate, John Justin Rodriguez

Theses and Dissertations

Agrivoltaics (AV) not only beneficially influences agricultural microclimates in the field, AV systems can generate on-site energy to offset operational costs, diversify income sources, and improve overall resilience, while providing environmental co-benefits such as reduced heat stress on plants and improved resource use efficiency. This thesis evaluated agrivoltaic shading effects on SWC and soil temperature using high-resolution in situ measurements collected over one year in an active vineyard, incorporating row type, soil depth, shading, and time of day. With precipitation as the primary water source, shaded soils exhibited up to 24.53% lower SWC relative to sun-exposed soils, likely due to …

Multivariate Time-Series Forecasting Of 24-Hour Ambulatory Blood Pressure Using Long Short-Term Memory And Temporal Fusion Transformers, Sebastian Alejos Torres

Theses and Dissertations

Time series play a central role in healthcare by enabling continuous patient monitoring and forecasting of physiological and clinical measurements. Traditional models, such as autoregressive integrated moving average (ARIMA), are limited in capturing nonlinear dynamics and irregular sampling. In this study, we develop and evaluate Long Short-Term Memory (LSTM) networks and Temporal Fusion Transformers (TFTs) to forecast 24-hour ambulatory systolic and diastolic blood pressure (SBP and DBP) time series enriched with demographic and clinical features. Mean absolute error (MAE), root mean squared error (RMSE), mean absolute percentage error (MAPE), and R² were used to evaluate predictive accuracy and temporal pattern …

Structure–Property Engineering Of Sn-Based Hybrid Perovskites Via Bulky Organic Cation Incorporation: From 3d To 2d Architectures, Kevin Alejandro

Theses and Dissertations

This thesis investigates tin-based hybrid organic/inorganic perovskites (HOIPs) as a lead-free alternative to silicon solar cells. To manipulate optoelectronic and efficiency of the semiconductors, methylammonium was substituted with bulky propylammonium and tetrabutylammonium cations to induce quasi-2D/3D Ruddlesden-Popper phases. X-Ray Diffraction confirmed 2D layered phases in propylammonium hybrids (5-15%), while tetrabutylammonium hybrids faced steric limits, triggering vacancy ordered perovskite phases at 1% concentration. Optical analysis showed a bandgap narrowing from 1.30 eV to 1.26 eV with increased substitution. Although photovoltaic performance generally declined, the 10% propylammonium hybrid achieved the highest fill factor of ~0.79, indicating superior internal charge transport. This work …

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 …

Impaired Tunability Of Brain State And Motor Dysfunction In A Mouse Model Of Rett Syndrome, Victoria Kindler Norman

Graduate Theses and Dissertations

Rett syndrome (RTT) is a rare neurological disorder, caused by disrupted function of the MECP2 gene, resulting in impaired cognitive and motor functions. Previous studies suggest that although MECP2 has important functions throughout the body, the etiological origins of RTT-related dysfunction should be sought within the brain. However, it remains a mystery how neural population dynamics are altered in the RTT brain and how these alterations relate to motor dysfunction. Previous studies using an RTT mouse model point to abnormal correlations among firing rates of neurons. Here we hypothesize that such disrupted neural activity correlation could be caused by abnormal …

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. …

A Survey On Digital Reading Materials And Personal Study Of Christian Religious Texts, Teancum Price

All Graduate Theses and Dissertations, Fall 2023 to Present

Religion, including reading from religious texts such as scriptures, are a part of the daily lives of many people. Modern technology has influenced the way that this religious reading takes place, but its effects have not yet been studied. Existing research of the effects of technology on reading focus on topics such as reading comprehension, but the study of religious texts is often focused on achieving a religious experience, so the existing research does not capture the whole scope of these changes. In our study, we surveyed two universities (Utah State University and Abilene Christian University) to ask individuals how …

Large Language Models For Introductory Computer Science Education: Content Generation, Intelligent Tutoring, And Learner Modeling, Muhammad Fawad Akbar Khan

All Graduate Theses and Dissertations, Fall 2023 to Present

This dissertation studies how artificial intelligence, especially large language models such as GPT, can help students learn introductory computer programming when the models are used inside a carefully designed learning system. Instead of focusing on AI as a standalone tool, the dissertation follows a connected story: generating learning resources, building a tutoring platform, running a user study, and then analyzing how students behave while they program.

The work first uses prompt engineering to create a large collection of 11,700 Python exercises aligned with introductory computer science topics. Students and instructors then evaluate these exercises to check whether they are clear, …

Assessing Geomorphic Change From Large Wood Additions In An Intensively Monitored Watershed, Alexander Walt

All Graduate Theses and Dissertations, Fall 2023 to Present

Rivers across the American West are under stress. Over time, human activities have decreased riparian vegetation and removed naturally occurring large wood from fallen trees and beaver dams. Overgrazing, wetland drainage, and artificial barriers like levees and berms have further changed these ecosystems, leaving behind simple channels that lack varied habitat for aquatic species.

Efforts to restore rivers have made some progress, but many projects are small in scale and focus more on reshaping the river rather than restoring the natural processes that keep it healthy. This study evaluates a different approach—Low-Tech Process-Based Restoration (LTPBR)—which works with nature to rebuild …

An Alternative Representation For Temporal Json, Bishal Sarkar

All Graduate Theses and Dissertations, Fall 2023 to Present

JavaScript Object Notation (JSON) is a common format for representing and exchanging data on the web. Most systems only keep the current version of a JSON document, even though, in many situations, it is also important to know how that document changed over time. For example, an application might need to answer questions such as “What did this record look like last week?” or “How has this list grown over the past year?” A simple way to keep this history is to store a full copy of the document every time it changes, but this quickly becomes wasteful, most of …

Influence Of Coterie On Utah Prairie Dog Translocation Success, Bonnie Stokes

All Graduate Theses and Dissertations, Fall 2023 to Present

The Utah prairie dog (Cynomys parvidens) is a threatened species found in southwestern Utah. Utah prairie dogs are small, burrowing squirrels that live in family groups called coteries. Translocation, the intentional capture, movement, and release of animals from one location to another, has been widely used to aid in their recovery; however, post-translocation survival remains low. The primary objective of this study was to evaluate the effect of translocating Utah prairie dogs as intact coteries on post-translocation survival.

This study was conducted within the West Desert Recovery Unit in Iron and Beaver Counties, Utah, during July–October 2023 and …

St-Fmformer: An Autoregressive Generation Framework For Scientific Ensemble Data Predictions, Md Robiul Islam

All Graduate Theses and Dissertations, Fall 2023 to Present

Understanding how physical systems change over time is important in areas such as weather prediction, fluid dynamics, and environmental science. However, accurately predicting future behavior is difficult because these systems are complex and constantly evolving. 

This research develops a deep learning approach to predict how such systems evolve over time. The model learns patterns from past observations and uses them to generate future states step by step. This provides a faster alternative to traditional simulation methods while maintaining strong predictive performance. 

The proposed method focuses on improving the consistency of predictions over time and is designed to work across different …

Visualizing Probabilistic Model Checking: An Interactive Framework For Exploring Ctmc Models, Ishara Mawelle Kankanamge

All Graduate Theses and Dissertations, Fall 2023 to Present

Probabilistic model checking is a critical method for analyzing systems characterized by uncertainty, such as communication protocols, randomized algorithms, and biochemical networks. While formal verification tools provide precise numerical data about these systems, interpreting these results is often limited by large state space, high-dimensional state space and time dependent evolution. Current tools typically output raw numerical data, offering limited support for intuitively understanding the time-dependent behavior of a model. This research presents an interactive visualization framework designed to bridge the gap between complex numerical analysis and human intuition. The framework integrates coordinated visual interfaces, including lower-dimensional state-space projections and synchronized …

How Novices Write Code: Discovering Best Practices, Matt Rau

All Graduate Theses and Dissertations, Fall 2023 to Present

Learning to program is a difficult endeavor, leading to chronically high failure rates in introductory programming courses. One thing that makes teaching programming difficult is that we don’t fully understand what problem solving habits and writing strategies separate successful programmers from struggling ones. Knowing how to teach these habits to a new programmer is an equally difficult challenge,

Studying the way people write code has proved difficult. Until recently, there was very little relevant publicly available data, and no good ways to analyze student programming behavior at a large scale. In this thesis, I address both issues. I publish a …

Post-Wildfire Erosion And Biogeochemistry: Integrating Aerial Imagery And Soil Testing To Assess Landscape Recovery, Justin A. Allred

All Graduate Theses and Dissertations, Fall 2023 to Present

After a wildfire, land managers are required to monitor large tracts of land with limited time and budgets. Traditionally, tracking landscape recovery is a time intensive process. This research explored the effectiveness of using drones (UAVs), strategic soil sampling, and computer modeling as additional tools for land managers in order to monitor the recovery more efficiently.

By using drones to collect aerial imagery and using machine learning, plant regrowth was monitored in back-to-back years. The machine learning model performed well at telling broad groups apart (trees vs grass) but it struggled to identify differences between plant species. Because many plants …

Gradient Based Optimization Methods For Robust Learning And Biomedical Signal Modeling, Jarrod Mau

All Graduate Theses and Dissertations, Fall 2023 to Present

This dissertation explores how modern artificial intelligence techniques can be used to better understand complex biological data. Specifically, it develops new machine learning based methods and applies them to two important biomedical problems: analyzing brain signals and studying protein behavior.

The first part of the work introduces a new machine learning approach designed to improve how computers classify structured data. Traditional neural networks are powerful but can sometimes generalize poorly. This research proposes a method that combines the flexibility of neural networks with the reliability of ensemble techniques, leading to more robust and accurate predictions across different types of datasets. …

When A Sum Of Cubes Equals The Square Of The Sum, Jessica M. Aguilar

Electronic Theses, Projects, and Dissertations

This thesis investigates extensions and structural generalizations of the classical identity \[ \sum_{k=1}^{n} k^3 = \left( \sum_{k=1}^{n} k \right)^2, \] traditionally attributed to Nicomachus of Gerasa. Despite its simple look, this cube - square identity reveals connections between combinatorics, multiplicative number theory, and Diophantine equations.

We begin by presenting an expanded combinatorial proof of the identity based on Stein’s rectangle - counting argument, clarifying the geometric structure underlying the formula. We then establish a multiplicative analogue using Euler’s divisor-counting function \( \tau(n) \), proving that \[ \sum_{d \mid n} \tau(d)^3 = \left( \sum_{d \mid n} \tau(d) \right)^2, \] thereby extending …

Examining Student Practices In A Technology-Mediated Math Classroom, Bradley T. Dodd

Electronic Theses, Projects, and Dissertations

It is important for math educators to make sense of student thinking in the classroom. Without opportunities to practice this skill math educators struggle to improve, particularly when students are engaging in mathematics using technology. As such, there is a need for video artifacts of students engaging with mathematics using technology for use in professional development activities (Lovett 2020). In accordance with Lovett et al.'s (2020) design principles for examining student practices in a technology-mediated environment, I carried out a study to determine whether these artifacts of student work could be created working with college undergraduates as participants. Students engaged …

Separating And Identifying Delta-8-Thc And Delta-9-Thc On Gc/Ms, Ann Schmidt

Honors Projects

Delta-8-THC and delta-9-THC are two psychoactive compounds found in marijuana products which are only distinguishable from each other by alternating the location of a single double bond.  This makes them a challenge to separate and identify as different compounds using the GC/MS.  These isomers are legally recognized as the different compounds, so being able to identify delta-8 and delta-9 THC separately is crucial to forensic analysis. The goal of this research project is to optimize an Intuvo 9000 GC connected to a standard MS to be able to separately and prominently identify delta-8-THC and delta-9-THC in a sample.  This was …

Constraint-Aware Metaheuristic Optimization For Experimental Design, Benjamin N. Fuller

All Graduate Theses and Dissertations, Fall 2023 to Present

Designing experiments becomes much more challenging when many variables and strict constraints are involved, as is common in modern science and engineering. This thesis introduces a new computational and mathematical framework that efficiently searches for optimal experiments in complex, high-dimensional spaces where traditional methods fail. By combining geometric techniques with flexible optimization algorithms like particle swarm optimization, our methods handle difficult constraints while scaling to real-world problems. Built in the high-performance Julia programming language and released as open-source software, this work bridges advanced theory with practical tools, offering researchers a powerful and accessible way to design better experiments under realistic …

Leveraging The Iron Oxide Archive Of Mineralization, Deformation, And Exhumation Across Geologic Time, Jordan L. Jensen

All Graduate Theses and Dissertations, Fall 2023 to Present

The iron oxide mineral hematite commonly forms from groundwater near Earth’s surface and can preserve a history of fluid flow, fault slip, and landscape evolution. This record can be decoded using (U-Th)/He thermochronology, a dating method based on the temperature-sensitive ingrowth of helium from uranium and thorium decay. Because later heating and natural variation in hematite crystals can produce ambiguous (U-Th)/He results, I integrate dating with tools that reveal differences in hematite chemistry and textures. I apply these techniques to two distinct settings: ancient granitic rocks in Colorado and an active fault zone in the southern San Andreas fault (SSAF) …

Adversarial Heterogeneous Agent Learning For Robotic Systems: A Framework For Coordinated Competitive Behaviors, Christopher T. Allred

All Graduate Theses and Dissertations, Fall 2023 to Present

Autonomous robot teams must move reliably, explain their actions, and work together—even in changing or adversarial settings. We present a structured, three-stage pathway that builds coordinated team behavior from strong single-robot skills. First, we develop robust legged-robot locomotion and interpretability using only internal actuator signals. From these proprioceptive cues, robots learn to classify terrain and predict short-term power use, enabling energy-aware movement without external sensors. We further analyze learned behaviors with motif discovery to reveal recurring sensor–action patterns, which clarify how agility emerges and guide reward design. Second, we compose these skills into heterogeneous teamwork using centralized training with decentralized …