Digital Commons Network^™

Universal Systems Simulation Via Constraint Hypergraphs With Applications To Digital Twins, John Morris

All Dissertations

The characterization of systems encompasses a variety of modeling frameworks designed to capture specific behaviors and components of various system domains. Whatever the framework, the core elements of a system representation are the information of the system and a description of how that information is related. The relations in deterministic systems are functions, which, when composed to form executable processes, can be used to simulate system data. A declarative modeling framework is one that encodes mechanisms for preparing these simulations within the model structure, allowing an external agent to form the execution processes required for a given context. To date, …

Enhancing Teacher Planning Practices To Improve Teacher Self-Efficacy Through Professional Learning Communities, Philip L. Price

All Dissertations

This improvement science dissertation investigated the impact of implementing Professional Learning Communities (PLC) on teacher self-efficacy at Parkway Elementary, a Title I school serving a diverse student population with historically lower academic performance. The study addressed the problem of low teacher self-efficacy, a critical factor influencing Tier 1 instructional quality and student outcomes. Utilizing the Plan-Do-Study-Act cycle, this research tested the theory that adopting a four-question framework within weekly collaborative grade-level meetings would measurably increase teacher self-efficacy. Seven teachers participated in the research, with data collected through the Teacher Sense of Efficacy Scale, semi-structured interviews, and PLC observations. Quantitative findings …

Exploring Glycosomes As Therapeutic Targets For Trypanosoma Brucei, Sabrina Sutton Pizarro

All Dissertations

Trypanosoma brucei is a protozoan parasite which causes human African trypanosomiasis and the livestock wasting disease, nagana. These parasites have highly specialized peroxisomes, called glycosomes, which house a variety of essential metabolic pathways, including glycolysis. Glycolysis is the sole means of energy production in the infective life stage of T. brucei making glycosomes and the glycolytic pathway promising targets for therapeutic strategies. In this work, we have studied the glycosome as a therapeutic target from multiple perspectives. The first portion of this work addresses drug trafficking. The efficacy of small-molecule inhibitors of glycosomal enzymes is restricted by the rate of …

Flexible Spatial Priors In Bayesian Neuroimaging: Gmrf, Nngp, And Deep Gmrf, Boyoung Hur

All Dissertations

Structural neuroimaging is essential for understanding neurological disorders such as Alzheimer’s disease, enabling accurate delineation of brain regions through image segmentation. Among various segmentation methods, multi-atlas-based approaches like label fusion have become leading techniques. In statistics, Bayesian hierarchical models for label fusion are increasingly favored for their ability to incorporate uncertainty and prior knowledge. Also, a key challenge in modeling neuroimaging data is spatial dependence among image voxels, making the choice of spatial prior critical—particularly in high-resolution settings where segmentation accuracy and computational efficiency are both essential.

This dissertation proposes fully Bayesian spatial hierarchical models that explore two flex- ible …

Thermal Management Of Power Electronic Converters In Electric Motor Drives Using Active Thermal Control And Active Cooling, S M Imrat Rahman

All Dissertations

The application of power electronic converters (PEC) in electric vehicles (EVs) has significantly increased due to their enhanced controllability and flexibility. Additionally, Permanent Magnet Synchronous Machines (PMSMs) are favored in EVs for their higher torque, efficiency, performance, and heat dissipation capabilities compared to asynchronous machines. The reliable operation of power converters in PMSM drives is crucial for EV operation, and this is driving interest in developing innovative and sustainable technologies that ensure the safe and reliable functioning of PECs. One of the main challenges in achieving reliable PECs is designing effective thermal management systems to control junction temperature and reduce …

Contributions To Statistical Modeling And Estimation Of Rainfall Intensity–Duration–Frequency Curves, Jiyun Huang

All Dissertations

Extreme rainfall can cause flooding, damage infrastructure, and create serious risks for communities. Engineers use Intensity-Duration-Frequency (IDF) curves to estimate precipitation extremes over different lengths of time, such as one hour or one day, and the average time one would expect wait for one of these events to occur. Several approaches exist for estimating IDF curves, but no single approach is known to be best in all cases. In this dissertation, I study statistical methods that aim to improve IDF curve estimation. I use the Canadian Regional Climate Model (CanRCM4) Large Ensemble, which contains 35 independent climate simulations. These simulations …

Surface Reaction And Transportation Of Radium-226 In Marine Systems, Jiusi Wang

All Dissertations

Historical uses of radium (Ra)-containing self-luminous paint, such as on gauges and dials in naval ships, have led to the potential for such paint, and thus Ra, to be released into the marine environment. Radium-226 (²²⁶Ra) behavior in marine systems is not fully described in the literature, presenting a knowledge gap in the process of evaluating potential ecological impact of Ra in marine systems. This study explores various mechanisms contributing to Ra environmental transport in marine systems on a laboratory scale, including leaching, sorption, and diffusion. ²²⁶Ra leaching from watch hand dials containing radioactive luminous paint is …

Machine Learning-Enabled Safety-Critical Model Predictive Control For Uncertain Dynamical Systems, Hossein Nejatbakhsh Esfahani

All Dissertations

This dissertation explores the interactions between Model Predictive Control (MPC), Safety-critical Control, and Artificial Intelligence (AI)/Machine Learning (ML) methods, with a particular focus on Reinforcement Learning (RL) and Bayesian Optimization (BO). We then leverage AI/ML to address several challenges in the control design and safe operation of uncertain dynamical systems. In many applications, ranging from autonomous vehicles and robotics to energy systems and industrial processes, ensuring safety is as essential as satisfying control objectives. The use of Control Barrier Functions (CBFs) within the MPC framework recently has emerged as a powerful tool to guarantee safety by enforcing constraints in optimal …

Legitimacy, Learning, And Launch: Exploring Relationships, Community, And Connection In An Undergraduate Research Experience, Randi J. Sims

All Dissertations

Undergraduate research experiences (UREs) are critically important methods for integrating undergraduate students into legitimate scientific practices. While widely celebrated for producing positive outcomes such as increased self-efficacy, research skills, and STEM retention, less is known about the processes through which undergraduate mentees become integrated members of their research groups and the broader scientific community. This dissertation presents findings from both a systematic literature review and a quantitative ethnographic study of a biological sciences URE at a southeastern R1 predominantly white institution (PWI). Grounded in communities of practice and legitimate peripheral participation frameworks, this study explores how undergraduate researchers build relationships, …

Reverse (Bio)Engineering: A Machine Learning Approach To Optimize Baseball Pitcher Health And Performance, Robert C. Moore

All Dissertations

Ball tracking systems are becoming ubiquitous in sport, creating an unprecedented opportunity for big data applications to optimize human health and performance. These applications are especially common in baseball, a sport known for analyzing ball flight data to quantify performance. Analysts routinely use ball flight data to identify the attributes of top performing pitchers, finding that the best pitchers throw with optimal combinations of release speed and spin to precise locations. However, for certain pitchers, the throwing motion required to produce optimal ball flight places exceedingly high biomechanical load on the elbow, and consequently injury rates continue to rise. This …

Virtual Coaching: Ushering In A New Era In School Improvement, Tygere Alisha West Charles

All Dissertations

This research study examined virtual coaching as a vehicle for principal professional development. The study focused on coaching a principal in a rural, low-performing, high-poverty South Carolina school district to improve support for teachers and students. This study explored virtual coaching and is rooted in improvement science as measured by plan-do-study-act (PDSA) cycles (Bryk et al., 2017). It explored how virtual coaching supported a rural principal’s professional development needs.

Principals must be transformational leaders who balance their support needs and accountability while meeting the needs of the diverse stakeholders they serve. Ongoing professional development is an essential component in helping …

Hybrid Learning For Rough Terrain Navigation Of Actively Articulated Wheeled Vehicles, Dhruv Mehta

All Dissertations

Conventional wheeled ground vehicles have been used for rough terrain navigation in the recent years. They consist of a chassis connected to wheels through passive, semi-active, or active suspension systems. However, their fixed configurations limit mobility and maneuverability, constraining their ability to autonomously navigate diverse and rough terrains. Autonomous Ground Vehicles (AGVs) face significant challenges in this regard, including varying terrain roughness, soil hardness, and obstacle crossing.

To address these limitations, Actively Articulated Wheeled Vehicle (AAWV) architectures have recently emerged, offering real-time geometric adaptability. AAWVs have chassis and wheels connected via articulated serial or parallel linkages. However, increased articulation introduces …

Data-Driven Discovery Of Finite-Dimensional Koopman Operator For Modeling And Control Of Uncrewed Ground Vehicles, Ajinkya Joglekar

All Dissertations

This dissertation advances data-driven modeling and adaptive control techniques for Uncrewed Ground Vehicles (UGVs), with a focus on autonomy in mission-critical and safety sensitive environments. UGVs are deployed across a wide spectrum of domains, from structured manufacturing shop floors to unstructured off-road terrains, including planetary exploration, precision agriculture, and disaster response. These platforms, operating in dull, dirty, and dangerous conditions, demand autonomy that is both adaptable and robust. While traditional model-based control methods offer interpretability and robustness, they struggle with unmodeled dynamics, parameter variations, and integration of high-dimensional sensing. Conversely, modern machine learning approaches can directly exploit sensory data but …

Leveled Homomorphic Encryption Schemes: Noise And Precision Control, Kyle Yates

All Dissertations

Homomorphic encryption allows for computations on encrypted data without exposing the underlying plaintext, enabling secure and private data processing in various applications such as cloud computing and machine learning. In this thesis, we conduct a comprehensive worst-case noise analysis for three prominent leveled homomorphic encryption schemes: Brakerski-Gentry-Vaikuntanathan (BGV), Brakerski-Fan-Vercauteren (BFV), and Cheon-Kim-Kim-Song (CKKS). We propose modifications to these schemes and their residue number system (RNS) variants, ensuring fresh encryption noise falls under a constant bound. For BFV and BGV, we design and prove parameter conditions which guarantee certain homomorphic circuit evaluations return ciphertexts containing noise within a fixed bound. For …

An Experimental Evaluation Of A Gamified Learning Approach To Address Bullying Knowledge, Perceptions, And Self-Efficacy Among Elementary Students: Playing Yozgoo In Albania, Sashen Rexhepaj

All Dissertations

This study evaluated the effectiveness of Yozgoo's web-based gamified educational intervention in enhancing elementary school students’ knowledge, attitudes, and self-efficacy related to bullying prevention in Albania. Utilizing a true experimental pre-test and post-test control group design, the study involved 120 students (ages 10-12) equally divided by gender and randomly assigned to either an experimental group (n = 60) or a control group (n = 60). The experimental group participated in Yozgoo gameplay sessions over six to eight weeks, while the control group engaged in standard activities without exposure to the intervention.

Three validated measures were administered to assess outcomes: …

Integrating Dft And Machine Learning To Predict Structural Properties In High Entropy Alloys, Nathan Linton

All Dissertations

In the past decade, a paradigm shift in the design of metal alloys has been observed. These new alloys are commonly referred to as high entropy alloys (HEAs), multi-principal element alloys (MPEAs), or complex, concentrated alloys (CCAs). In contrast to conventional alloys, which consist of one main element (for example 80%) with other elements in small amounts, HEAs are made of four or more main elements ranging from 5 to 35% each element. Due to the large presence of multiple elements, HEAs have shown substantial material property improvements over conventional alloys such as steel. For example, they have high ductility …

Digital Reflections: Evaluating Body Dissatisfaction In Xr Through Eye- And Body-Tracked Virtual Humans, Deyrel Diaz

All Dissertations

In an era where digital and physical realities increasingly intertwine, the perception of body image is undergoing a significant transformation. Traditional understandings of body dissatisfaction, long studied in relation to psychological distress and eating disorders, are now being reshaped by technologies such as Virtual Reality (VR), Augmented Reality (AR), and Artificially Intelligent (AI)- generated media. These technologies have introduced novel ways of experiencing and interacting with the human form, raising critical questions about their impact on self-perception and internalization of beauty standards.

As virtual representations become more prevalent in entertainment, social media, and interactive platforms, it is becoming more crucial …

Atomic-Scale Engineering Of Dilute Pd–Cu Alloys For Selective Electrocatalytic Cox Reduction, Zehua Jin

All Dissertations

The excessive release of carbon dioxide (CO2) into the atmosphere has become a major cause of global warming and ocean acidification, threatening the sustainability of human life on Earth. To address this challenge, scientists are exploring ways to convert CO2 into useful fuels and chemicals instead of simply capturing and storing it. One promising approach is electrocatalysis, which uses electricity—potentially from renewable sources—to drive chemical reactions that transform CO2 under mild, environmentally friendly conditions.

This research aims to understand how the arrangement of atoms in metallic catalysts affects the conversion of CO2 and carbon monoxide (CO) into valuable products such …

Cosmic Duets: A Search For Binary Supermassive Black Holes In Merging Galaxies, Sagar Adhikari

All Dissertations

Galaxies are vast cosmic islands of stars, dust, and gas. They come in various shapes and sizes. They might look static for the timescales we are used to, but they are dynamic and collisional systems that can merge with other galaxies to make bigger galaxies. Most galaxies, including the Milky Way, host a central supermassive black hole (SMBH) with a mass greater than a million (sometimes a billion) times the mass of the Sun. When galaxies merge, their SMBHs form a binary system before ultimately merging. These cosmic duets are of great interest to astronomers and astrophysicists as they are …

Improvisation Of Mands Using Augmentative And Alternative Communication, Lauren Decker

All Graduate Theses and Dissertations, Fall 2023 to Present

Research shows that young children who use pictures to communicate can use colors, shapes, and functions of items to request when the specific picture of the item is not available. This problem-solving skill is called improvisation, which this study taught to a preschool aged participant with communication delays. A four-year-old preschool student was able to make these requests with basic colors, shapes, and three function pictures. They also were able to make these requests for items not taught to them in different settings. This suggests that improvisation training can be successfully implemented with preschool aged children with communication delays and …

An Evaluation Of Virtual Reality Modeling To Improve Accuracy Of Physical Education Skills In Teenage Students With Disabilities, Kristen Lee

All Graduate Theses and Dissertations, Fall 2023 to Present

Virtual Reality (VR) technology is becoming more common in schools, especially for teaching and training. In this study, researchers explored how VR can help teenagers with disabilities improve their physical education skills, specifically push-ups, lunges, and jumping jacks. The participants all showed an increase in their skills and reached a high level of accuracy on every skill. The results showed that adding feedback was also necessary for some participants. Additionally, participants enjoyed using the VR equipment and showed high levels of happiness throughout the study. These findings suggested that using VR technology can be an effective way to support teenagers …

Discourses Embedded In The Adams V. School Board Of St. Johns County Decision And The Rights Of Transgender Students In Schools, Douglas Larson

All Graduate Theses and Dissertations, Fall 2023 to Present

This study was critical analysis of the language of the court case Adams v. School Board of St. Johns County (2022). This case was brough by a student against the School District challenging a policy that prevented him, a transgender boy, from using the boys’ restroom. The analysis was not intended to determine the merits of the case or the correctness of the legal reasoning. Rather, the analysis was performed on the text of the case—the language used by the judges—to learn about the beliefs, attitudes, and values of the judges.

The reason this analysis is important is because judges …

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 …

Developing Standardized Testing Datasets For Benchmarking Automated Quality Control Algorithm Performance With Aquatic Sensor Data, Ehsan Kahrizi

All Graduate Theses and Dissertations, Fall 2023 to Present

Advances in water monitoring technologies have led to a large increase in the amount of data collected from rivers, lakes, and other water systems. However, ensuring that these data are accurate and reliable remains a major challenge. Traditional data quality checks are done manually by a technician, which can be slow, inconsistent, and not practical for real-time monitoring. This research addresses these challenges by developing standardized datasets for testing computer-based methods that automatically detect and correct errors in water data. Using information from the Logan River Observatory in northern Utah, we created a step-by-step process to identify, categorize, and label …

Predicting Major Solar Flares Using Convolutional Neural Networks And Multivariate Magnetic Field Time-Series Data, Arash Azizian Foumani

All Graduate Theses and Dissertations, Fall 2023 to Present

Major solar flares are sudden, intense bursts of X-ray energy from the Sun, capable of severely impacting critical technological infrastructure like satellites, communication networks, and power grids on Earth. Accurate prediction of these high-intensity events is crucial but presents a significant challenge. This is largely due to their infrequent occurrence and the complex, dynamic nature of the Sun's underlying magnetic activity which drives these events. This research focuses on improving the prediction of major solar flares by utilizing detailed historical data that tracks the evolution of magnetic properties within solar active regions over time. This time-based data, however, contains inherent …

Cognitive Dynamics In Undergraduate Engineering Education: Effects Of Need For Cognitive Closure And Achievement Goal Orientation On Cognitive Engagement, Zain Ul Abideen

All Graduate Theses and Dissertations, Fall 2023 to Present

Cognitive and motivational factors play an important role in students’ engagement during problem-solving, which can lead to academic and professional success. Among these factors, Need for cognitive closure (NFCC) and achievement goal orientation (AGO) have been studied extensively individually, but their interaction and impact on engineering students’ problem-solving is still not explored. NFCC refers to the person’s desire for quick answers, and AGO is the student’s approach to learning and success. This research investigated the impact of NFCC on gender and engineering major, and the relation between NFCC (five facets) and AGO (Mastery, Performance) at their different levels. Additionally, this …

Enabling Scalable Camera-Based Streamflow Monitoring With Serverless Cloud Computing, Sajan Neupane

All Graduate Theses and Dissertations, Fall 2023 to Present

This thesis introduces a modern and automated method for monitoring rivers and streams using cameras and cloud-based software tools. Traditional monitoring methods often rely on sensors placed directly in the water, which can be expensive, hard to install, and difficult to maintain, especially in remote or rough terrain. In contrast, this approach uses cameras to observe water flow from a distance, offering a safer and more cost-effective alternative. However, camera systems come with their own challenges, such as collecting large amounts of image data, transferring it reliably from the field, and analyzing it quickly enough to be useful. This research …

Using Luminescence Of Quartz Temper From Archaeological Pottery To Infer Wildfire Intensity In The Southwestern Us, Brooklyn D. Dib

All Graduate Theses and Dissertations, Fall 2023 to Present

The size and frequency of wildfires have increased recently, impacting ecosystems, communities, and human health. This research uses the heat-sensitive luminescence signals of quartz sand temper within archaeological pottery to record past wildfire conditions. Pottery sherds, which are fragments of archaeological pottery, from the forest floor in sites in New Mexico and Arizona were collected from different fire contexts (no fire exposure, historical fires, prescribed burns, and modern wildfires). These forests are primarily Ponderosa Pine with a grassy understory. The interior sand grains of each sherd sample were analyzed using optically stimulated luminescence, which dates when the mineral grains were …

Quicklime-Based Self-Healing Concrete For Bridge Deck Applications, Mehrnoosh Nazari

All Graduate Theses and Dissertations, Fall 2023 to Present

Concrete is one of the most widely used construction materials in the world. However, over time, it can crack and deteriorate, especially on roads and bridges exposed to harsh weather and deicing salts. Inspired by the long-lasting durability of ancient Roman concrete, this study explores the self-healing capabilities of concrete incorporating quicklime (calcium oxide) aggregates to extend the service life of bridge decks. For this purpose, three concrete mixtures were developed using local materials: one without quicklime (C-Q 0%) and two with 2% (C-Q 2%) and 4% quicklime (C-Q 4%). These mixtures were tested for fresh properties, strength, durability, and …

Biocontrol Of Canada Thistle (Cirsium Arvense) With The Rust Fungus, Puccinia Punctiformis In The Intermountain West: Integrated Weed Management Compatibility And Characterization Of Microbiome Associations, Caitlin Henderson

All Graduate Theses and Dissertations, Fall 2023 to Present

Canada thistle (Cirsium arvense) is an invasive weed of major concern in both agricultural and native areas. It competes against native plants, reduces crop production and quality, and causes significant costs in management and damages. Canada thistle can survive and spread through seeds, but primarily does so through its extensive root system, which causes the greatest management difficulties. There are several control methods for this invasive weed, herbicides are perhaps the most common and effective, however, they have limitations and negative consequences. Herbicide use near waterways is restricted and there are growing concerns of the development of herbicide …