Digital Commons Network^™

Effects Of Tourist Feeding On The Gut Microbiome And Ecophysiology Of Endangered Northern Bahamian Rock Iguana (Cyclura Cychlura), Erin Lucy Lewis

All Graduate Theses and Dissertations, Fall 2023 to Present

The lifespan and reproduction of an animal depends on maintaining a healthy physiology. The proportion of individuals that survive to an age at which procreation can occur is important to long-term stability of populations and contributes to species survival. Health in an animal is measured in a variety of ways, including through monitoring of the body’s physiological systems, as well as its ability to respond to invading pathogens, and through the different types of bacteria present in the gut. Relationships among those different health metrics have been discovered in recent years and have been found to play important roles in …

A Low Power Fpga Compute Array For Machine Learning And Artificial Intelligence Applications, Todd Wilson

All Graduate Theses and Dissertations, Fall 2023 to Present

Modern small satellites often lack the ability to analyze their data in real time, relying instead on downlinking raw measurements to Earth before any scientific interpretation can occur. This delay restricts missions that require rapid awareness of environmental or space-weather events. This thesis presents the Low-power Array for Cubesat Edge Computing Architecture, Algorithms, and Applications (LACE-C3A), a hardware platform designed to enable in-orbit data processing within the power and volume limits of CubeSat-class spacecraft. 

LACE-C3A uses a modular cluster of flash-based FPGAs, which offer low power consumption, radiation resilience, and in-flight reconfigurability. The system consists of a Controller board responsible …

Exploring Cognitive Load Theory In The Post-Secondary Engineering Classroom, Gabriel Q. Van Dyke

All Graduate Theses and Dissertations, Fall 2023 to Present

Engineering programs often emphasize subject-matter expertise over pedagogical training, which can leave students struggling with course demands and contribute to retention challenges. This study applied Cognitive Load Theory (CLT) to examine how undergraduate engineering students experience the cognitive demands of their coursework compared to non-engineering classes. Using a sequential explanatory mixed methods design, cognitive load surveys were followed by interviews to address two research questions: (1) What are the differences in intrinsic and extraneous cognitive load levels between engineering courses and non-engineering courses taken concurrently by undergraduate engineering students? (2) How do engineering students perceive the unique challenges or benefits …

Aerodynamic Parameter Estimation For A Scaled F-16: A Simulation-Based Sensitivity Analysis, Kathle C. Tischner

All Graduate Theses and Dissertations, Fall 2023 to Present

The physical motion of an aircraft is determined by the resulting forces and moments acting on the aircraft. These forces and moments can be defined as a mathematical equation where the control deflections, rotation rates, and orientation of the aircraft are multiplied by individual constants and summed together to define the entire force or moment. This method results in a highly accurate model that defines the motion of the aircraft at low angles of attack and sideslip. Initial calculations of the aerodynamic model are created based on analytical estimations based on the physical properties of the aircraft. Additional refinement of …

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 …

Freshwater Mussel Reintroduction And Recolonization Habitat Modeling Using Hydraulic, Sediment And Geomorphic Parameters, Megan Elizabeth Dinicola

All Graduate Theses and Dissertations, Fall 2023 to Present

Freshwater mussels are an important group of aquatic animals that live within the riverbed, but their populations have been drastically reduced by habitat alteration and other anthropogenic activities. In an effort to bolster populations, river managers and biologists are using mussel reintroductions as part of their restoration efforts but there are gaps in our understanding of where to reintroduce mussels within a river to see them create self-sustaining populations. This research helps shrink this gap by better understanding the physical habitat needs and population expansion potential of subadult freshwater mussels, or the size of mussel that hatcheries grow for reintroduction, …

Continuous Symmetry Discovery And Enforcement Using Vector Fields With Application To Time Series And Image Data, Benjamin D. Shaw

All Graduate Theses and Dissertations, Fall 2023 to Present

Machine learning powers many technologies we use every day, from image classification in computer vision to analyzing time series data such as sensor readings or financial trends. One way to make these systems smarter and more reliable is by using symmetry, meaning patterns that remain unchanged under certain transformations, such as rotations for images or uniform changes in signal amplitude for time series. Discovering these patterns can improve understanding of data and help build models that perform well in new situations. 

Current methods for finding symmetry often rely on large neural networks and are limited to simple transformations like stretching …

Social And Institutional Factors Influencing Restoration Decisions In Sagebrush Plant Communities In The Great Basin, Carmen Calzado-Martínez

All Graduate Theses and Dissertations, Fall 2023 to Present

Sagebrush landscapes of the Great Basin in the western United States have changed dramatically over the past century. Invasive grasses, repeated wildfires, and past land-use practices have made it increasingly difficult for native plant communities to recover once they are damaged. Most restoration efforts occur after disturbances such as wildfire, when ecosystems may already be severely degraded. An alternative approach is proactive restoration, which aims to strengthen ecosystems before major damage occurs. 

This dissertation examines whether proactive restoration strategies could realistically be used in sagebrush rangelands and what factors influence their adoption. The research combines three complementary approaches. First, interviews …

Does Psychosocial Stress Moderate The Association Between Indicators Of Vascular Health And Cognitive Performance: An Examination In Native Hawaiian - Pacific Islander And Non-Nhpi Older Adults, Maddy Mills

All Graduate Theses and Dissertations, Fall 2023 to Present

Late-life cognitive decline and dementia that are unrelated to normal aging are a source of major global health concerns. Vascular risk factors, including high blood pressure, high cholesterol, and diabetes, along with psychosocial stress, are well-established risk factors for cognitive decline. However, no research has explored how these variables interact to influence cognitive performance in older adults. Native Hawaiian-Pacific Islanders (NHPI) face disproportionate rates of vascular risk factors linked to cognitive decline, yet this population has been historically underrepresented in health research. As a result, limited evidence exists regarding how these factors collectively impact cognitive performance in this population. This …

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 …

Enhancing Evidence-Based Practice Decision-Making Among Practitioners In Adult Disability Service Settings, Aubrey Vance

All Graduate Theses and Dissertations, Fall 2023 to Present

Board Certified Behavior Analysts (BCBA®s) working in adult disability services often face challenges such as high caseloads, limited oversight, and restricted resources, which can make it difficult to use individualized, research-supported interventions. Although evidence-based practice (EBP) is central to applied behavior analysis, many practitioners receive little training on how to integrate research evidence, client values, and clinical judgment into their decision-making. This study examined whether BCBAs could be effectively trained to use a structured decision-making framework based on the EBP model by Slocum et al. (2014). Using a multiple baseline design, we evaluated the effects of Behavioral Skills Training (BST) …

Developing And Improving Digital Image Correlation (Dic) Techniques For Challenging Environments, Prasenjit Dewanjee

All Graduate Theses and Dissertations, Fall 2023 to Present

Understanding how materials and parts deform during testing is crucial for creating safer and more reliable engineering systems. Engineers need to measure not only how much a part deforms, but also where deformation concentrates before any damage or failure happens. Digital image correlation (DIC) is a camera-based, non-contact measurement method that tracks surface motion and deformation across a whole area. It is particularly useful when traditional contact-based measurement techniques cannot withstand harsh conditions or capture enough detail. This dissertation develops optical methods to improve DIC in three challenging measurement situations. First, a shortwave ultraviolet lighting technique is developed to reduce …

Out Of Sight, Out Of Mind? Psychological Distance And Public Perceptions Of The Great Salt Lake, Nathan Thompson

All Graduate Theses and Dissertations, Fall 2023 to Present

Over the past several years, Great Salt Lake has received a lot of media attention, both locally in Utah as well as nationally and even internationally. Within Utah, public perception surveys have indicated that concern about the lake varies depending on how low the lake levels are. This suggests that a concept called psychological distance might be influencing concern about the lake as well as support for strategies to help the lake. Psychological distance is the perceived distance a person has from an object, event, or person and is manifested in four ways: across physical distance (spatially), across time (temporal), …

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 …

Production Of Hydrolyzed Lactose Syrup From The Acid Whey, Aubrey Jean Arbon

All Graduate Theses and Dissertations, Fall 2023 to Present

Acid whey has gained significant attention within the dairy industry due to its complex matrix and the processing challenges. This by-product contains lactose that can be isolated, hydrolyzed, and further processed to produce hydrolyzed syrup. To optimize lactose utilization, it is essential to fine-tune the kinetics of the β-galactosidase enzymes used for lactose hydrolysis. To analyze sugars in acid whey, and LC-MS-based chromatographic method was developed. Once the method was developed, the kinetics of β-galactosidase were optimized with respect to enzyme concentration, pH, and temperature. The goal was to achieve the highest possible lactose hydrolysis. The hydrolyzed acid whey was …

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 …

The Practice Of Inclusion: Indigenous Knowledge And Ethical Design, Kate E. Van Der Zalm

All Graduate Theses and Dissertations, Fall 2023 to Present

Indigenous Knowledge is a cumulative body of practices and beliefs developed by Indigenous communities through generations of interaction with the natural environment. This knowledge offers valuable insights for caring for the land in sustainable and respectful ways but is not fully considered in modern planning and design practices. This research examines how Indigenous Knowledge is currently understood and used within landscape planning and design firms in British Columbia, Canada. Using a combination of existing research and interviews with design professionals and Indigenous participants, the study explores where Indigenous Knowledge is being applied, where challenges exist, and what opportunities remain for …

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 …

Faith And Doubt: Exploring How We Interpret The World, Amber Mccuen

All Graduate Theses and Dissertations, Fall 2023 to Present

This collection of four fictional short stories explores questions of belief—and practice of belief—in four separate contexts. The first story, “Little Marie,” follows a young girl who’s made her own system of belief created by correlation. The second story, “Last Days,” sees a woman return to her childhood home which has been overcome by the hoarding habits of her paranoid, fundamentalist Christian mother. The third story, “Graduation,” takes place at a divinity school graduation and explores the strength of both social influence and unspoken rules within closed groups. The final story, “Away From the Ninety and Nine,” follows a cult …

Developing Fragility Curves For Steel Special Moment-Resisting Frames In Utah, Olivia P. Murphy

All Graduate Theses and Dissertations, Fall 2023 to Present

Major seismic events along the Wasatch Fault represent a serious threat to Utah's residents and built environment. Engineers currently rely on a statistical approach that calculates earthquake ground shaking based on probabilities of various events occurring over extended time periods. This method informs how strong new buildings must be constructed. However, many structural engineering professionals in Utah worry that this probability-based approach may significantly underestimate the actual ground shaking compared to an alternative method that examines the largest possible earthquake a fault can generate. The substantial differences between the two analytical approaches raise fundamental concerns about whether existing construction standards …

Mease: Multi-Agent Episodic Action Sequence Explanation, Phyo Wai Khaing, Minghong Geng, Shubham Pateria, Budhitama Subagdja, Ah-Hwee Tan

Research Collection School Of Computing and Information Systems

Multi-agent reinforcement learning (MARL) achieves remarkable performance in complex coordination tasks, yet interpreting the emergent behaviors of trained agents remains a fundamental challenge. Most current explainability methods focus on individual agent decisions, overlooking the critical interplay of joint strategiesand temporal coordination patterns that define successful multi-agent policies. We present MEASE (Multi-agent Episodic Action Sequence Explanation), a novel explainable MARL (XMARL) framework that explains trained MARL policies as human-interpretable emergent cooperative joint behaviors. MEASE employs a cognition-inspired episodic memory model to learn spatio-temporal multi-agent interaction patterns, coupled with abstraction algorithms that identify significant cooperative agent behaviors. We evaluate MEASE on diverse …

Quantitative Bounds On Resource Usage Of Probabilistic Programs, Krishnendu Chatterjee, Amir Kafshdar Goharshady, Tobias Meggendorfer, Dorde Zikelic

Research Collection School Of Computing and Information Systems

Cost analysis, also known as resource usage analysis, is the task of finding bounds on the total cost of a program and is a well-studied problem in static analysis. In this work, we consider two classical quantitative problems in cost analysis for probabilistic programs. The first problem is to find a bound on the expected total cost of the program. This is a natural measure for the resource usage of the program and can also be directly applied to average-case runtime analysis. The second problem asks for a tail bound, i.e. ‍given a threshold t the goal is to find …

Market Reactions To Deceptive Language In Fake News: Implications From Language Expectancy Theory And Transfer Learning, Ka Chung Ng, Ping Fan Ke, Ping Fan, Mike So, Tam, Kar Yan

Research Collection School Of Computing and Information Systems

The advent of generative artificial intelligence (AI) has heightened the proliferation of fake news. A key challenge is the limited real-world data to investigate the societal impact of fake news produced by generative AI. In this paper, we examine stock market reactions to financial news articles that exhibit stylometric similarity to human-crafted and AI-crafted fake financial news. Grounded in language expectancy theory, we employ a style-based transfer learning model, pre-trained to recognizing deceptive language employed in various types of fake news intricacies. We then apply this model to a comprehensive dataset of financial news, assigning a “veracity style score” to …

Open Source Software Development Tool Installation: Challenges And Strategies For Novice Developers, Larissa Salerno, Christoph Treude, Patanamon Thongtanunam

Research Collection School Of Computing and Information Systems

As the world of technology advances, so do the tools that software developers use to create new programs. In recent years, software development tools have become more popular, allowing developers to work more efficiently and produce higher-quality software. Still, installing such tools can be challenging for novice developers at the early stage of their careers, as they may face issues such as compatibility problems (e.g., with operating systems) and unclear instructions. Therefore, this work aims to investigate the challenges novice developers face when installing software development tools and the strategies they employ to overcome them. To investigate these, we conducted …

Natural Adversaries: Fuzzing Autonomous Vehicles With Realistic Roadside Object Placements, Yang Sun, Haoyu Wang, Christopher M. Poskitt, Jun Sun

Research Collection School Of Computing and Information Systems

The emergence of Autonomous Vehicles (AVs) has spurred research into testing the resilience of their perception systems, i.e., ensuring that they are not susceptible to critical misjudgements. It is important that these systems are tested not only with respect to other vehicles on the road, but also with respect to objects placed on the roadside. Trash bins, billboards, and greenery are examples of such objects, typically positioned according to guidelines developed for the human visual system, which may not align perfectly with the needs of AVs. Existing tests, however, usually focus on adversarial objects with conspicuous shapes or patches, which …

Fighting Against Recruitment Scams: Theory-Driven Supervised Learning And Empirical Analysis For Digital Fraudulent Recruitment Posting Behavior, Tom (Tianteng) Wang, David (Jingjun) Xu, Keng Siau, Zhongju (John) Zhang

Research Collection School Of Computing and Information Systems

The number of recruitment postings on digital recruitment hiring platforms has increased since the COVID-19 pandemic. However, the weak surveillance and operations of these platforms, combined with the fact that most job seekers have relatively low vigilance and a strong desire for recruitment offers, enable scammers to easily deceive job seekers for their money and confidential information. In this work, we combine prevailing text mining techniques (i.e., ChatGPT with prompting engineering and supervised machine learning) with interpersonal deception theory (IDT) from social science to design an interpretable IT system to predict fraudulent recruitment postings on digital recruitment-hiring platforms. We compare …

Enhancing Action And Ingredient Modeling For Semantically Grounded Recipe Generation, Guoshan Liu, Bin Zhu, Yian Li, Jingjing Chen, Chong-Wah Ngo, Yu-Gang Jiang

Research Collection School Of Computing and Information Systems

Recent advances in Multimodal Large Language Models (MLMMs) have enabled recipe generation from food images, yet outputs often contain semantically incorrect actions or ingredients despite high lexical scores (e.g., BLEU, ROUGE). To address this gap, we propose a semantically grounded framework that predicts and validates actions and ingredients as internal context for instruction generation. Our two-stage pipeline combines supervised fine-tuning (SFT) with reinforcement fine-tuning (RFT): SFT builds foundational accuracy using an Action-Reasoning dataset and ingredient corpus, while RFT employs frequency-aware rewards to improve long-tail action prediction and ingredient generalization. A Semantic Confidence Scoring and Rectification (SCSR) module further filters and …

Optimization Of The Baffle Geometry Of A Circular Culvert Outlet Structure To Maximize Energy Dissipation, Kiarash Shirmahi

Department of Civil and Environmental Engineering: Dissertations, Theses, and Student Research

High-velocity flow at culvert outlets can lead to significant soil erosion and damage to downstream infrastructure, particularly in agricultural regions where land protection is critical. Circular culverts, commonly used in transportation systems, are especially susceptible to this issue due to flow acceleration caused by geometric constraints and installation angles. Despite extensive research on energy dissipation in rectangular culverts, limited attention has been given to circular configurations. This study addresses this gap by evaluating the hydraulic performance of baffle systems designed to reduce outlet energy in circular culverts.

A series of laboratory experiments was conducted using a scaled physical model of …

Leveraging Code Embeddings To Identify And Address Blind Spots In Benchmark Creation, Charles Moloney

School of Computing: Dissertations, Theses, and Student Research

Formal software verification remains critical for early vulnerability detection, yet benchmarking these tools is costly and often reliant on centralized datasets such as SV-COMP. While such repositories enable standardized evaluation, they introduce risks of overfitting and bias, particularly due to first-party benchmark contributions. To address these limitations, we extend ARG-V, our tool for generating SV-COMP-compatible benchmarks from real-world Java code, with a novel approach of using code embedding techniques to selectively sample from mined code. By leveraging Nomic Embed Code and a cosine-based Minimum Hyperspherical Energy (MHE) objective, we systematically select and transform benchmarks from scraped GitHub code that …

Application Of Maritime Non-Line-Of-Sight Relay Attack On Wireless Digital Communication, Nathan Meyer

School of Computing: Dissertations, Theses, and Student Research

As wireless communication becomes increasingly prevalent, securing information over wireless channels is an ongoing challenge, especially in maritime environments where communication depends on radio links. While higher layer wireless attacks have been widely studied, lower level physical-layer relay attacks in maritime settings have received less attention. This thesis presents a simulation of a maritime relay attack in a beyond line-of-sight wireless environment for study. A three antenna communication model is developed where a legitimate transmitter sends a digital wireless signal, an attacking antenna intercepts, modifies, and retransmits the signal, and a final receiver observes both the direct and relay transmission. …