Digital Commons Network^™

Data-Driven Streamflow Forecasting In The Upper Colorado River Basin Using Spatio-Temporal Graph Networks, Akhila Akkala

All Graduate Theses and Dissertations, Fall 2023 to Present

Forecasting river flow is essential for managing water supplies, reducing flood risk, and supporting healthy ecosystems. In the Upper Colorado River Basin, much of the yearly water comes from melting snow. However, many traditional models struggle to capture how snowpack and river flow interact, especially across such a large and complex region.

This study uses a modern machine learning approach called a Spatio-Temporal Graph Neural Network (STGNN) to improve streamflow prediction. The model uses Snow Water Equivalent (SWE)—a measure of how much water is stored in the snowpack—along with river flow data. By treating each river gauge as part of …

Summary Of Pine Valley Area Groundwater Studies, Melissa Stamp, Bethany Neilson, Anna Mcentire, Burdette Barker, Lisa Welsh, Joanna Endter-Wada, Brian Steed

Reports

The Utah Division of Water Resources contracted with Utah State University to document key scientific and policy information related to the current water conflict between Iron and Beaver Counties over the development of the Pine Valley Water Supply Project (PVWSP). The proposed PVWSP would pump groundwater from Pine Valley in Beaver County and pipe it southeast to the Cedar City region of Iron County served by the Central Iron County Water Conservancy District (CICWCD). Numerous concerns about the project have been raised by Beaver County and other interested parties. A number of these concerns are related to different understandings or …

The Effects Of Lactoferrin And Iron-Enriched Whey On Iron Status Of Collegiate Females, Connor Kemp

All Graduate Theses and Dissertations, Fall 2023 to Present

Iron deficiency has remained a global issue even in developed countries despite food fortification and increased nutritional literacy, biological women of child baring age are at particular risk due to menstruation and reduced dietary intake of iron containing foods compared to men. This issue is of particular concern in athletics due to the critical role of iron in oxygen transport and energy metabolism. With nearly half of female athletes presenting low iron status iron supplementation is often necessary. With iron supplementation often resulting in gastrointestinal symptoms that could negatively impact sport performance itself there is a need to explore other …

Lace Network Firmware: A Polarfire Fpga Network For Data Routing And Command Interfacing In Space Applications, Kade C. Howes

All Graduate Theses and Dissertations, Fall 2023 to Present

Modern small spacecraft rely on powerful yet efficient onboard compute devices to process data from sensors in real-time due to tight power and volume constraints. This work explores a new compute device system built from PolarFire Field-Programmable Gate Arrays (FPGAs), which are power-efficient, reprogrammable chips well-suited for space applications. The system connects via a central controller FPGA with one or multiple companion processing FPGAs, allowing sensor data to be quickly received and shared across the network. Standardized data formats and interfaces increase compatibility with spacecraft computers. By simplifying data handling and using high-speed communication links, this architecture makes it easier …

Artificial Intelligence For Reliability: Predictive Health Maintenance And Geolocation In Gps-Denied Environments, Rafael Toche Pizano

Graduate Theses and Dissertations

In this dissertation, we explore the potential of machine learning and deep learning techniques to enhance the performance and robustness of applications across two major domains. By addressing the challenges within these fields, we demonstrate that we can leverage learning algorithms to obtain substantial improvements in accuracy and robustness. First, we tackle a problem in the field of predictive health maintenance. We propose a novel auto encoder and neural network based methodology to predict failure times in complex aviation systems to learn to distinguish between normal and abnormal operational behavior, and use this information to inform the neural network to …

Hyperspectral Indicators And Characterization Of Glyphosate-Induced Stress In Common Lambsquarters (Chenopodium Album L.), Mario Andrés Soto Valencia

Graduate Theses and Dissertations

Hyperspectral sensing enables detection of herbicide stress in weeds, but practical use requires strategies for redundancy control, rating variability management, and evaluator bias mitigation. This thesis evaluates common lambsquarters (Chenopodium album) under glyphosate exposure, aiming to identify key wavelengths, construct vegetation indices, and improve injury modeling. Greenhouse experiments used dimensionality reduction methods (principal component analysis, Relief F, Bayesian discriminant analysis) to isolate 34 unique wavelengths from about 3,200 bands. Calibration data were collected 14 days after treatment (DAT) to support wavelength selection and model development, while data from 27 DAT were used for independent validation. Class comparisons across six statistically …

Beam Steering Control For A Small-Scale 5g Antenna Array, Omar Wagih Elkalesh

Graduate Theses and Dissertations

This thesis demonstrates the design, development, and validation of a full-scale adaptive beam steering control system of a small-scale 5G antenna array, designed and thoroughly evaluated with MATLAB Simulink. Overcoming the significant challenge of establishing strong wireless links in dynamic environments, the new system uses a new closed-loop control framework that can automatically detect the signal sources and automatically change the beam direction in real-time. The use of the adaptation is necessary to combat tracking errors that are caused by the mobility of the mobile users, environmental variations, as well as channel estimation errors, widespread in future wireless communication systems. …

Transcriptomic And Contractile Adaptations In Skeletal Muscle In A Rodent Model Of Anorexia Nervosa, Oscar Armando Vicen

Graduate Theses and Dissertations

BACKGROUND: Anorexia Nervosa (AN) is a psychiatric disorder marked by severe chronic caloric restriction and is primarily diagnosed through psychological and behavioral symptoms. AN has the highest mortality of any psychiatric disorder with an increased risk of all-cause mortality. Many individuals with a history of AN experience incomplete recovery despite intervention treatment. Skeletal muscle molecular mechanisms under chronic energy deprivation remain poorly understood. PURPOSE: To investigate transcriptomic profiles of the gastrocnemius muscle following one month of a rodent model of AN. This study analyzed whether the molecular changes correlate with collected muscular force data to provide a comprehensive understanding of …

Privacy Protection In Cloud-Based Biometric Systems, Yatish Reddy Dubasi

Graduate Theses and Dissertations

The widespread adoption of server-based biometric authentication systems, often hosted in the cloud, has introduced significant privacy risks. While these systems offer convenience, they require storing sensitive biometric templates on remote servers, creating a high-value target for adversaries. Unlike passwords, compromised biometric data is immutable and cannot be reissued, leading to an irreversible loss of privacy. This threat is exacerbated by template inversion attacks, which can reconstruct a user's original biometric trait (e.g., a face image) from its stored feature vector. This dissertation addresses these critical privacy challenges by designing, implementing, and evaluating a suite of novel frameworks for privacy-preserving …

Towards Vision-Brain Understanding At Scales: From Classical To Quantum Machine Learning Approaches, Xuan-Bac Nguyen

Graduate Theses and Dissertations

In recent years, large-scale learning approaches such as unsupervised and self-supervised learning have revolutionized artificial intelligence. These methods enable machines to learn high-level representations without explicit human supervision, achieving remarkable success across vision, language, and multimodal tasks. However, such advances come at a cost—they rely on massive datasets, billions of parameters, and extensive computational resources. Despite these achievements, artificial systems still fall short of the remarkable learning efficiency of the human brain, which can infer, adapt, and generalize from limited experiences. This gap motivates a deeper exploration of how biological intelligence acquires knowledge and how these principles can inspire the …

Ecological Elemental Homeostasis And Stoichiometric Shifts: Biotic Responses To Ionic And Viral Stress, Samuel Anthony Tooru Dias

Graduate Theses and Dissertations

Anthropogenic activities are reshaping the elemental composition of freshwater ecosystems, often creating stoichiometric imbalances that influence the growth, physiology and interactions of aquatic organisms. Ecological stoichiometric theory (EST) provides a framework for examining these changes by linking organismal elemental regulation to broader ecosystem processes. While traditionally focused on elements, such as carbon (C), nitrogen (N), and phosphorus (P), emerging stressors highlight the need to expand this framework to be more elementally inclusive for the examination of novel interactions. My dissertation integrates abiotic (salinization) and biotic stressors (viral infection) into an EST framework to evaluate how these factors alter elemental regulation …

Updating The Surface Geological Maps In The Boston Mountains Region Of Arkansas Using Subsurface Well Log Correlation And Lidar Mapping, Olivia Smith

Graduate Theses and Dissertations

The Pennsylvanian Atoka Formation are the primary surface outcrops of the Boston Mountains in northwest Arkansas. Where fully preserved in the Arkoma Basin to the south, the Atoka Formation exceeds 18,000 feet of sandstone and shale. It is mapped as a single “undifferentiated” unit on the surface geological map of Arkansas. This project correlates ten subsurface subdivisions of the Atoka Formation plus the Desmoinesian to the surface outcrops of the southern Boston Mountains. This produced a higher resolution surface map beyond the current Atoka Undifferentiated scheme. Recognition of the Atoka Formation subdivisions in surface outcrops using standard lithostratigraphic and biostratigraphic …

Contextual Embedding Using Machine Learning For Cybersecurity: Access Control And Application, Thanh Bui

Graduate Theses and Dissertations

Access control is a well-established challenge in cybersecurity, with significant research focused on enhancing system autonomy and accuracy across various scenarios. Access control rules can be designed based on users’ roles, attributes, or relationships requesting access to specific resources. However, despite their benefits, these models still require human oversight. As systems expand and grow, it becomes increasingly complex for administrators to maintain precise access control rules, often necessitating extensive system updates or even a complete overhaul. This dissertation introduces a novel approach that leverages contextual embedding for user information to enable the system to autonomously authorize user requests for resources. …

Broiler Responsiveness To Dietary Amino Acid Density In A Commercial Setting, Virginia Slick

Graduate Theses and Dissertations

The majority of research assessing the amino acid responsiveness in broilers has been conducted in experimental designs utilizing pens that contain 12 to 25 birds with high replication. While this trial design is beneficial as a way to perform high replications with multiple treatments in a way that is both economically and spatially feasible, it may not accurately translate to a rearing environment more similar to that of commercial open floor housing. This research was conducted to determine if the effects of lysine driven amino acid density diets that have been found in the traditional floor pen setting correlate to …

When The Grid Goes Dark: A Digital Forensics Study Of Industrial Control System Cyberattacks, Katie Kettler

Graduate Theses and Dissertations

Industrial Control Systems (ICS) and Operational Technology (OT) maintain the grid, ensure water safety, and keep transportation running. Because they influence nearly every aspect of daily life, these systems have become prime targets for cyberattacks. The need for this research arises from the fact that when ICS and OT systems are compromised, the consequences go beyond data loss, and they can directly disrupt communities and endanger public safety. This thesis introduces digital forensics fundamentals and explains how investigations in ICS environments differ from those in traditional IT environments. This work then examines major attacks, including Stuxnet, the Ukrainian Grid Attacks …

Two Topics In Survival Analysis: Restricted Distance Covariance Test For Non-Proportional Hazard And A New Estimation For Dropout Rate, Ruizhe Yin

Graduate Theses and Dissertations

When treatment effects change over time, standard statistical methods, such as the log-rank test and the Cox proportional hazards model, may give misleading results. This dissertation presents the restricted distance covariance (rdcov) test, a nonparametric method that compares survival curves between groups within a chosen study period [0, τ] using right censored data. The statistic measures the dependence between pre-specified group labels and survival times using pairwise distances from Kaplan-Meier estimates. Our method does not rely on the proportional hazards assumption, and it equals zero only when survival functions are identical across groups. Thus, this test can be applied to …

Design Of Phase Shifter And True Time Delay Gan Mmics For High-Temperature Ku-Band Applications, Michael Lee Thompson

Graduate Theses and Dissertations

This thesis presents the design, implementation, and high-temperature characterization of Gallium Nitride (GaN) monolithic microwave integrated circuits (MMICs) developed for beamforming and phased-array systems operating in the Ku-band (12-14 GHz). Two integrated circuits were designed: a 3-bit digital phase shifter and a 3-bit true time delay (TTD), both optimized for high linearity, low insertion loss, low phase error, and stable operation at elevated temperatures up to 300°C. Developing both a phase shifter and a TTD enabled a direct comparison of their beamforming performance and the evaluation of beam squint effects over frequency, a critical factor in wideband array design. The …

Instance-Adaptive Gated Fusion Of Multi-Transform Image Representations, Prince Appiah

Open Access Theses & Dissertations

This dissertation proposes the Instance-Adaptive Gated Fusion (IAGF) framework, a novel deep learning architecture for adaptive and interpretable fusion of multiple time–series image transformations. While existing methods rely on static concatenation or dataset-level optimization, IAGF introduces a learnable gating mechanism that dynamically assigns per-instance weights to Recurrence Plots (RP), Gramian Angular Summation Fields (GASF), and Gramian Angular Difference Fields (GADF). The gating layer performs a convex fusion of transformation-specific embeddings under a softmax constraint, ensuring mathematical stability and interpretability. An entropy-regularized objective prevents dominance collapse and promotes balanced exploration of transformations during training. Comprehensive experiments across eighteen benchmark datasets, spanning …

Multi-Hop Hybrid Graph Neural Network, James Arthur

Open Access Theses & Dissertations

Graph-structured data appear across diverse domains, such as social networks, citation graphs, biological systems, and knowledge bases. Graph Neural Networks (GNNs) have emerged as a powerful framework for learning on such data, yet existing architectures face significant challenges. Graph Convolutional Networks (GCNs) suffer from over-smoothing as depth increases, Graph Attention Networks (GATs) introduce computational and statistical instabilities, and naïve multi-hop propagation inflates memory and computation while failing to adapt to topology. These limitations motivate the development of a new framework that is both expressive and scalable. This dissertation proposes the Multi-Hop Hybrid Graph Neural Network (MHHGNN), a novel architecture that …

Under Pressure: The Effects Of Stress And Cognitive Load On Interrogative Suggestibility, Claudia Cota

Open Access Theses & Dissertations

High-stakes situations, like police interrogations, can impair critical thinking due to stress and cognitive demands, making individuals more susceptible to suggestion. While much research focuses on children, young adults are also at risk for interrogative suggestibility, which can have serious legal consequences. This study experimentally manipulated stress and cognitive load to test whether both factors increase suggestibility in young adults, both independently and interactively, with the highest suggestibility among those experiencing both greater stress and cognitive demands. This was evaluated by examining both condition effects and self-reports of stress and cognitive load. College students (N = 230), aged 18 to …

¡Más Fuertes Y Resilientes! Strengthening Latino Occupational Resilience Through Career-Focused Support Services At Texas Hispanic Serving Institutions, Claudia Cochran-Miller

Open Access Theses & Dissertations

Latinos face many threats to their occupational resilience. Occupational displacement is looming due to technological advances that threaten jobs where Latinos are overrepresented such as in manufacturing, retail, construction, agriculture, and food services. As technological advances, labor practices, and other factors disproportionately affect the Latino population, more will be seeking better employment opportunities and will turn to higher education. Hispanic Serving Institutions (HSIs) are in position to significantly impact Latino occupational resilience. This correlational study examines the various career-focused support services offered by HSIs and how they relate to post-graduation outcomes for Latino graduates. Career-focused support services include alignment-driven career …

3d Face Modeling From 2d Images Using Deep Neural Networks, Mario Alberto De La Cruz Armendariz

Open Access Theses & Dissertations

Applications of 3D face reconstruction include biometric authentication, personalized avatars and digital identity, medical visualization, forensic analysis, and broader human-computer interaction. We propose an approach to 3D face reconstruction that can generate a fully textured 3D facial model using only two grayscale images: a front view and a profile view of the subject. Once trained, the system can perform the reconstruction autonomously without manual intervention. Unlike traditional methods requiring multi-camera setups, depth sensors, or cloud-based processing, the proposed approach runs fully offline on a standard CPU, supporting dynamic execution across CPU cores and eliminating the need for a dedicated GPU. …

Design And Validation Of Model Predictive Controllers For Lateral Vehicle Control, Keren Flores

Open Access Theses & Dissertations

This thesis develops, implements, and evaluates a Model Predictive Control (MPC) framework for lateral vehicle guidance using a linearized bicycle model. The complete control architecture is formulated from first principles, beginning with the derivation of the continuous-time planar dynamics and their conversion into a discrete-time state-space representation suitable for real-time control. The MPC problem is constructed explicitly through the development of prediction models, output selection matrices, and quadratic cost formulations. The controller is evaluated through a Python simulation environment that includes reference trajectory generation, nonlinear vehicle propagation, and constraint handling. Robustness is examined using systematic perturbations to vehicle mass, tire …

Microgrid Assessment And Ml-Based Power System Faults Detection Leveraging Real-Time Co-Simulation, Diego Normando Gandara Mendez

Open Access Theses & Dissertations

The rapid growth of distributed energy resources (DERs) and the increasing reliance on data-driven decision making have reshaped the operational challenges of modern electric power systems. As microgrids become more prominent in distribution networks, utilities require methods that unify planning, control, and real-time situational awareness to ensure resilient operation under faulted or uncertain conditions. The goal of this MSEE thesis is to design and validate a latency-aware ML framework for rapid, reliable fault detection in distribution grids. To achieve the goal of the thesis, there are three specific objectives. Objective 1 evaluates optimized microgrid configurations under varying DER levels and …

Advancing Trypanosoma Cruzi N-Myristoyltransferase As A Drug Target For Chagas Disease Through In Silico Discovery And Biochemical Evaluation, Diana Citlali González García

Open Access Theses & Dissertations

Chagas disease remains one of the most persistent and neglected parasitic infections in the Americas, advancing silently through the intracellular replication of Trypanosoma cruzi amastigotes and the invasive spread of trypomastigotes. The survival of the parasite is critically reliant on protein N-myristoylation, a lipid modification catalyzed by N-myristoyltransferase (NMT). This dissertation aims to advance beyond prior studies by systematically investigating NMT inhibition across multiple biological levels, spanning from the characterization of the purified enzyme, through cellular infection models, to the global proteomic remodeling induced within the parasite, thereby evaluating TcNMT as a potential therapeutic vulnerability in T.cruzi.Recombinant TcNMT was expressed, …

Encoding Of Inferences Into Long-Term Memory In Bilinguals, Bianca Valentina Gurrola

Open Access Theses & Dissertations

When reading and listening to information, people often make inferences to facilitate their comprehension and the creation of a discourse representation. However, because such inferences are not explicitly stated, they can lead to distortions in the memory representation known as inference-based memory errors. The present study investigated the encoding of inferences in bilinguals while considering the effects of language proficiency, presentation modality, and working memory load. In Experiment 1, Spanish-English bilingual participants read and listened to narratives composed from common schemas (e.g., going to eat at a restaurant) before completing a recognition test on the details from narratives. In Experiment …

Lamda: A Longitudinal Android Malware Dataset For Benchmarking Concept Drift Detection And Adaptation, Md Ahsanul Haque

Open Access Theses & Dissertations

Machine learning (ML)-based malware detection systems often fail to account for the dynamic nature of real-world training and test data distributions. In practice, these distributions evolve due to frequent changes in the Android ecosystem, adversarial development of new malware families, and the continuous emergence of both benign and malicious applications. Prior studies have shown that such concept drift—distributional shifts in benign and malicious samples—leads to significant degradation in detection performance over time. Despite the practical importance of this issue, existing datasets are often outdated and limited in temporal scope, diversity of malware families, and sample scale, making them insufficient for …

Comparison Of Ti-6al-4v Powder And Bulk Specimen Properties Across Manufacturers In Laser Powder-Blown Ded, Alejandro Javier Hernandez

Open Access Theses & Dissertations

The investigation and comparison of 4 different Ti64 powder feedstocks from 3 different manufacturers was done to determine if the quality of the powder had a profound effect on the properties of the bulk specimens despite using the same processing parameters. The characteristics of the powder observed are the atomization process used, particle size distribution, flowability, and its density. The Ti64 printing parameters for directed energy deposition that were kept consistent were the feed rate, scanning speed, and laser power. Coupons with varying build angles (0-30°) were printed to measure the impact of overhangs on bulk specimen properties (ultimate tensile …

Phishibl: A Systematic Evaluation Of Instance-Based Learning Model For Predicting Phishing Susceptibility, Shova Kuikel

Open Access Theses & Dissertations

Despite enormous efforts to develop defenses against phishing attacks, humans still struggle to detect phishing emails given the constantly evolving attacker strategies. This thesis aims to test the predictive capabilities of a cognitive model that represents the individual susceptibility to phishing emails. While training programs aim to raise awareness, most remain outdated and ineffective against evolving attack strategies. Recent advances in Machine Learning, Artificial Intelligence, and Large Language Models (LLMs) offer new defenses, yet understanding human decision processes remains crucial, as effective systems must emulate how people evaluate unfamiliar emails based on prior experience. This research introduces a cognitive model …

Investigation Of Hot Mix Asphalt Aging Effect On Binder Performance, Zahra Mohajeri

Open Access Theses & Dissertations

Asphalt roads continuously experience physicochemical changes under the combined influence of oxygen, heat, ultraviolet (UV) radiation, and water. Oxidation increases molecular polarity and association, causes maltenes loss, and continues hardening the asphalt binder, reducing ductility, stress-relaxation capacity, and resistance to cracking (Petersen 1982; Colbert and You 2012). Because aging is a cumulative process beginning at plant production, accelerating during construction/compacting, and continuing in service, the laboratory tests and indices must capture the extent of short-and long-term aging to support performance-related specification and Balanced Mix Design (BMD) (AASHTO R30 2022; Kim et al. 2017). This chapter reviews: (i) laboratory and field-representative …