Digital Commons Network^™

Modulating Linear Frequency Modulated Pulses To Send Communications Data In A Bistatic Sar Scenario, Jarren T. Worthen

All Graduate Theses and Dissertations, Fall 2023 to Present

Synthetic aperture radar (SAR) is the technology that enables the creation of images using radar waves, allowing images to be formed regardless of weather. In bistatic SAR a radar platform uses a radar pulse from a separate platform to form an image. It is important that these radar systems are able to communicate with each other. Rather than wasting energy and space flying with a separate communication system, the radar systems could use the already existing SAR system to send data between each other while still forming SAR images. The work of this thesis is to show how very simple …

Modular Verification For Network-On-Chip Designs Using Probabilistic Verification And Assume-Guarantee Reasoning, Nicholas Waddoups

All Graduate Theses and Dissertations, Fall 2023 to Present

To satisfy increasing demands for computer chip performance in personal computing, mobile devices, and commercial server computing, a modern computer chip is constructed with tens (or hundreds) of small individual computing modules. Each of these modules must communicate with one other to share information about the running state of a computer. Historically, when chips were a few modules a simple communication method sufficied. However, as the number of modules in a chip grew, a more effecient method was needed in order to maintain performance across the system as a whole. A Network-on-Chip (NoC) design is the de-facto communication method for …

Magnetic Properties And Ultrafast Spin Dynamics In Quantum Materials, Trung Kien Mac

All Graduate Theses and Dissertations, Fall 2023 to Present

Modern electronics mostly work by moving electric charge, which generates heat and hence wastes energy, especially as devices become smaller and faster. An alternative is to use the spin of electrons (a tiny magnetic property) and related “valley” states in certain atomically thin materials to store and process information more efficiently. This thesis explores how magnetism and spin behavior can be created and measured in a family of ultra-thin materials known as van der Waals quantum materials. Three kinds of materials are studied. First, atomically thin semiconductors are shaped into narrow nanoribbons. Because of their narrow size, their edges can …

Theory, Implementation, And Practical Applications Of A Modern Parabolized Navier-Stokes Code, Logan B. Freeman

All Graduate Theses and Dissertations, Fall 2023 to Present

The Parabolized Navier-Stokes (PNS) method is a specialized computational approach for solving the equations that govern fluid flowing faster than the speed of sound, known as supersonic flow. By leveraging unique physical properties of supersonic environments—specifically that information cannot travel upstream—this method allows for significantly more efficient calculations than traditional approaches. Supersonic flows are important for many military and civilian applications including hypersonic weapons, high-speed passenger aircraft, and reentry. This thesis provides a comprehensive review of the two-dimensional PNS formulation, detailing the mathematical derivation and its practical implementation for solving flow problems. Through performance analysis and error assessment, this research …

Simulation Of Hypersonic Conditions In A Lab-Scale Environment Using A Hybrid Rocket With Nitrogen Cooling, Joshua R. Sorenson

All Graduate Theses and Dissertations, Fall 2023 to Present

Developing hypersonic vehicles requires testing under extreme heat, airflow, and pressure. Traditional facilities like shock tunnels and arc-heated wind tunnels are costly and slow to set up. This thesis proposes a simpler, low-cost method using a small-scale hybrid rocket motor as a gas generator. The rocket’s hot exhaust is directed onto the front edge of a scaled-down model that represents the nose of a hypersonic vehicle. This creates a realistic flow that matches both the intense heat energy and the pushing force experienced in high-altitude hypersonic flight. The setup allows easy measurement of motor performance, surface pressures, leading-edge temperatures, and …

The Augmented Matching Law, Matias A. Avellaneda

All Graduate Theses and Dissertations, Fall 2023 to Present

Every living organism, including humans, has a finite amount of time available: 24 hours in a day, 365 days in a year, and a certain number of years in its life. At every moment, such an organism will be engaging in one of a multitude of possible activities, such as eating, sleeping, or reading this dissertation. We use the term choice to denote the way in which the organism distributes its time among all these activities, and some of these choice patterns are more beneficial to the organism than others, showcasing the importance of understanding the mechanisms underlying choice. A …

Mining Time Series Shapelets And Association Rules For Solar Flare Prediction, Drew Watson

All Graduate Theses and Dissertations, Fall 2023 to Present

Solar flares are the largest explosions in the solar system; they are caused by changes in the Sun’s magnetic field. Strong solar flares can disrupt power systems, damage satellites, and interfere with radio communication, so improving flare prediction is important. This thesis develops a way to predict severe solar flares while also helping researchers understand why those predictions are made. The approach looks for short patterns in solar magnetic field data that are linked to future flare activity. It then studies how these patterns appear together and in what order they happen over time. By doing this, the research not …

Dbssnet: Dual-Branch Spectral-Spatial Network With Data-Driven And Knowledge-Guided Band Selection For Uav Hyperspectral Wheat Rust Detection, Subin Kim

All Graduate Theses and Dissertations, Fall 2023 to Present

Wheat rust is a serious plant disease that can reduce crop yield and quality. In practice, the disease is often noticed only after visible symptoms appear, when some damage may already be difficult to reverse. This thesis studies whether drone-based imaging can help detect wheat rust earlier and more reliably in field environments. 

Unlike an ordinary color photograph, a hyperspectral image records reflected light at many narrow wavelengths. These measurements can reveal useful information about plant condition, but they are also high dimensional, noisy, and difficult to analyze when only a limited number of labeled field samples are available. To …

Viability Assessment Of Bovine Embryos: A Public Dataset And Deep Learning Baselines, Erfan Khayyati

All Graduate Theses and Dissertations, Fall 2023 to Present

Improving the success rates of cattle breeding is essential for sustainable agriculture, global food security, and high-quality livestock production. Currently, determining whether a lab-grown bovine embryo is healthy enough for a successful pregnancy requires highly trained experts to manually evaluate days of continuous time-lapse video footage. This process is not only incredibly time-consuming but also highly subjective; human reviewers often suffer from visual fatigue when tracking subtle, microscopic cellular changes over a seven-day period, leading to significant disagreement among even top experts on an embryo’s true potential. Furthermore, assessing bovine embryos is notoriously difficult due to their dark, lipid-dense cellular …

Divergent Belowground Strategies Of Savanna Grasses Under Varying Fire Regimes, Abigail C. Schmidt

All Graduate Theses and Dissertations, Fall 2023 to Present

Savannas are unique ecosystems, where trees and grasses live together across the landscape, not quite forming full forests or open grasslands. The ability for trees and grass to coexist is largely the result of widespread disturbances, such as fire. Fire in savannas is largely thought of in how it maintains plants above ground, however, fire also plays a key role in ecosystem and plant processes belowground. First, fire can change how soil nutrients, namely phosphorus, are cycled. Phosphorus is a key nutrient that plants need to function, and plants acquire phosphorus through their roots. Frequent fire can enhance phosphorus availability, …

Multispecies Weed Detection Using Unmanned Aerial Vehicles And Deep Learning Object Detection Models In Utah Forage Crop Corn Field, Utsav Bhandari

All Graduate Theses and Dissertations, Fall 2023 to Present

Weeds cost global agriculture over $32 billion annually and reduce crop yields by nearly one-third. Current weed control relies heavily on spraying herbicides uniformly across entire fields, leading to herbicide-resistant weeds, environmental harm, and increasing costs for farmers. A smarter approach is detecting weeds from the air and spraying only where they are present. This could dramatically reduce herbicide use while protecting crop yields. This thesis developed a complete system for identifying weeds in corn fields using drone-captured images and artificial intelligence. Working in commercial forage corn fields in Cache Valley, Utah, high-resolution aerial images were collected and used to …

Spatial Prediction Under Uncertainty: Methodological And Computational Advances In Bayesian Maximum Entropy, Kinspride K. Duah

All Graduate Theses and Dissertations, Fall 2023 to Present

Environmental decisions such as infrastructure design, water management, and snow load estimation depend on spatial data that are often incomplete or uncertain. In many cases, measurements are not exact values but ranges, reflecting limitations in data collection methods. Traditional mapping techniques typically simplify these uncertain measurements, which can lead to less accurate predictions. This dissertation introduces improved statistical tools for making spatial predictions when data are uncertain or partially known. By utilizing a framework called Bayesian Maximum Entropy (BME), this research demonstrates how exact measurements and range-based data can be combined in a mathematically consistent way. The work demonstrates that …

Unifying And Expanding Global And Local Variable Importance Methods For Explainable Machine Learning, Kelvyn K. Bladen

All Graduate Theses and Dissertations, Fall 2023 to Present

Machine learning methods are powerful analytical tools used across all scientific disciplines and many other fields of investigation for prediction and inference from diverse data sources. Despite their broad applicability, machine learning methods are often highly complex and difficult to interpret. Developing a greater understanding of which variables most influence a response is essential for increasing the interpretability of these models and supporting informed decision-making. This research focuses on improving how we evaluate the importance of these variables.

One common approach is to shuffle the values of a variable and see how much the model accuracy gets worse. Another approach …

Learning Latent Structure In High-Dimensional Data Via Geometry And Graphs, Haozhe Chen

All Graduate Theses and Dissertations, Fall 2023 to Present

Modern datasets often contain many measured variables for each observation, such as gene-expression levels, brain activity signals, or features in tabular data. These data are also often noisy, meaning that useful patterns are mixed with measurement error or irrelevant variation. Although such datasets can appear complex, they are frequently represented by simpler hidden structures, such as trajectories, clusters, or relationships between observations. This dissertation develops methods for uncovering these hidden structures by learning geometric and graph-based representations directly from data. The first part introduces Functional Information Geometry, which represents local patterns in high-dimensional data using functional features and constructs a …

The Impact Of Early Exposure To Engineering Concepts In The Form Of Family, School Classes, And Stem Extracurriculars On The Long-Term Sense Of Belonging In Undergraduate Women In Engineering, Hannah Lloyd

All Graduate Theses and Dissertations, Fall 2023 to Present

Engineering continues to struggle with the underrepresentation of women, and many women who begin engineering programs report feeling isolated or uncertain about whether they belong. A strong sense of belonging has been linked to greater confidence, persistence, and success in engineering. This study examined how early experiences with engineering before college may influence students' sense of belonging later in their undergraduate engineering programs.

Using survey responses from undergraduate engineering students across the United States, this study explored several types of early exposure to engineering, including family influence, school-based engineering and STEM courses, extracurricular programs such as robotics clubs and engineering …

Visualizing The Phase Space Of Two Interacting Spherical Magnets Via Lagrangian Descriptors, Matthew Pontius

All Graduate Theses and Dissertations, Fall 2023 to Present

This thesis studies the motion of one spherical magnet sliding on another fixed spherical magnet. Although the setup is simple, the resulting motion can range from regular and predictable to chaotic as the energy increases. To understand this behavior, mathematical tools are used to visualize how all possible motions are organized in phase space. These methods reveal patterns such as stable regions, repeating motions, and chaotic trajectories. The results show how order and chaos coexist in this system and provide insight into how small changes in the initial conditions can lead to very different outcomes.

Hidden Symmetries And Higher Dimensional Rotating Black Holes, Luis Fernando Temoche Hurtado

All Graduate Theses and Dissertations, Fall 2023 to Present

A standard approach to probing the dynamics of a physical system is to expose it to an external perturbation—such as an incident wave—and analyze its response after the interaction. Mathematically, this procedure is formulated in terms of differential equations governing the evolution of the perturbation.

In the context of black hole physics, an analogous strategy can be employed by studying the response of the event horizon to external perturbations. The differential equations describing these interactions are often invariant under nontrivial transformations, revealing hidden symmetries that help explain distinctive features of higher-dimensional black holes.

By exploiting these hidden symmetries in the …

Pesticide Dissipation In Agroecosystems – Exploring Pesticide Fate And Transport Mechanisms To Protect Alternative Pollinators, Calvin Luu

All Graduate Theses and Dissertations, Fall 2023 to Present

Honey bees are the most well-known pollinators, but there exists thousands of other bee species that contribute to pollination; one such group of bees are the solitary bees. True to their namesake, solitary bees do not live in hives like honey bees. Some solitary bees, like alfalfa leafcutting bees (ALCB) and blue orchard bees, can pollinate crops more efficiently than honey bees. However, since they live solitary lives, pesticide exposure is much more harmful to their overall population. If one honey bee dies from pesticide exposure, the hive can still survive, and the queen bee will continue producing offspring. If …

Modeling Power Distribution Architectures And Maintaining Constant Power With Misalignment In Dynamic Wireless Charging Systems For Electric Vehicles, Mayank Chawla

All Graduate Theses and Dissertations, Fall 2023 to Present

With increasing demand for wireless power transfer systems from phone charging and medical devices, in-motion wireless charging of electric vehicles offers a unique advantage of charging the vehicle while in motion on an electrified roadway. Compared to the stationary or wired charging, electric vehicle users can significantly save time and cost with a reduction in the battery size. However, with large-scale infrastructure required for a wireless charging roadway and the driver’s ability to align with the electrified roadway, come significant challenges for the practical implementation of in-motion wireless charging systems.This dissertation aims to solve some of the problems associated with …

The Impact Of Ai On The Landscape Design Process, Jacob Owen Huff

All Graduate Theses and Dissertations, Fall 2023 to Present

Artificial intelligence (AI) is becoming more common in design fields, including landscape architecture. For example, AI has been used to visually analyze park aesthetics and generate landscape design concepts (Jahani et al., 2022; Senem et al., 2023; Ploennigs & Berger, 2023). This study explores how AI, specifically an image-generation tool called Midjourney, affects the design process for landscape architecture students.

Students completed two design projects—one using AI-generated images and one using traditional, non-AI precedent images. Their final designs were evaluated by professional landscape architects who did not know which designs had been influenced by AI. Students also completed surveys about …

Applications Of Machine Learning To Gas Plume Analysis In Longwave Infrared Hyperspectral Images, Scout C. Jarman

All Graduate Theses and Dissertations, Fall 2023 to Present

Each pixel from a hyperspectral camera measures the intensity of light over a continuous range of wavelengths, which is in contrast to traditional color cameras, which just measure the intensity of red, green, and blue wavelengths of light. Longwave infrared hyperspectral images can be used to detect gases from a distance by measuring how different materials emit and absorb heat. This makes them useful for applications such as monitoring industrial emissions or locating hazardous gas leaks. In practice, however, gas signatures in these hyperspectral images are often weak and easily obscured by variations in the background scene, making reliable identification …

From Evidence To Impact: Supporting Sensemaking And Instructional Revision In Stem Classrooms, Bonni Jones

All Graduate Theses and Dissertations, Fall 2023 to Present

Science and math literacy is crucial for informed citizenship and economic competitiveness, yet many students leave school without developing the critical thinking skills needed to understand and solve complex issues or pursue STEM careers. This disconnect often stems from traditional teaching methods that emphasize memorization and following steps over authentic reasoning and problem solving. This dissertation addresses this challenge by identifying how teachers in research studies have taught STEM in ways that develop students' ability to think, reason, and problem-solve like real scientists.

By analyzing research on instruction that incorporates modeling, inquiry, and sensemaking, and working directly with teachers, this …

Method Validation Of The Cdc Bottle Bioassay And A Historical Record Of Polycyclic Aromatic Hydrocarbons In Glacier National Park, Evah F. Peard

All Graduate Theses and Dissertations, Fall 2023 to Present

Certain contaminants can persist in the environment for long periods of time, build up within living tissues, travel far from their origin, and harm both ecosystems and organisms. This thesis focuses on two types of contaminants: insecticides and polycyclic aromatic hydrocarbons (PAHs). Insecticides are manufactured to control pests while PAHs are found in oil and gas products and can be produced by industry, vehicle engines, and wildfires. Understanding how harmful these contaminants are and where they end up in the environment is critical for protecting environmental health.

First, I evaluated a widely used test developed by the Centers for Disease …

Impact Of Chronic Stress And Nutrition On Functional Connectivity And Neural Networks In Young Kichwa Children From The Ecuadorian Amazon Rainforest, Matthew L. Cook

All Graduate Theses and Dissertations, Fall 2023 to Present

Early childhood is a critical period for brain development. Positive and negative experiences during this time can have lasting effects on learning, health, and well-being. However, most research on children’s brain development has been conducted in wealthy, industrialized nations, leaving important gaps in our understanding of how children develop in other cultural and environmental contexts.

This study examined brain development in Indigenous Kichwa children living in two rural communities in the Ecuadorian Amazon Rainforest. The goal was to better understand how chronic stress and nutrition may influence a child’s developing brain during early childhood. Children participated in noninvasive brain assessments …

Assessing Ecological Integrity Of Streams Across The Western U.S., Jennifer L. Courtwright

All Graduate Theses and Dissertations, Fall 2023 to Present

Large-scale assessments of stream health (ecological integrity) are required by policies such as the U.S. Clean Water Act and provide critical information needed to properly manage public lands. Our ability to quantify the ecological condition of streams in the western U.S. and identify the causes of degraded conditions has previously been impeded by a lack of standardized large-scale datasets, high natural temporal and spatial variability of ecological attributes, and poor-quality land use data. I compiled large-scale monitoring datasets and built models to predict the values of ecological attributes (metrics) at a given site in the absence of human impacts. In …

Understanding And Predicting Precipitation Characteristics In The United States Through Machine Learning, Numerical Modeling And Measurements, Cody Luther Ratterman

All Graduate Theses and Dissertations, Fall 2023 to Present

Precipitation is one of the most important yet uncertain variables in the climate system. It varies dramatically in terms of timing, accumulation, rate, and phase, depending on location, season, circulation patterns, and atmospheric conditions. Precipitation forecasts, especially snowfall, are essential to supporting drought mitigation and water management in the Intermountain West. Because rainfall and snowfall lead to opposite effects on snowpack, accurately partitioning rain and snow is important to estimate snowpack levels, winter recreation, mountain ecosystems and runoff. The research findings in this dissertation have advanced the understanding and prediction of precipitation and snowpack in the U.S. by addressing the …

Bridging The Gap: Exploring The Development Of Science Self-Efficacy Among Students With Learning Disabilities, Aria Hadley-Hulet

All Graduate Theses and Dissertations, Fall 2023 to Present

Students with learning disabilities are often overlooked in efforts to broaden participation in STEM. This multi-paper dissertation investigates science self-efficacy among this population through the lenses of the social model of disability and self-efficacy theory. An integrative review reveals consistently lower academic self-efficacy among students with learning disabilities and a lack of research examining their science self-efficacy specifically. Quantitative analysis of national data shows lower science self-efficacy overall, yet no differences among students enrolled in advanced science courses. A mixed-methods study further demonstrates that in inclusive school environments characterized by asset-based teacher beliefs and normalized accommodations, science self-efficacy differences disappear. …

The Role Of Heterogeneity In Earthquake Rupture Dynamics: Insights From Friction Experiments On A 1-Meter Laboratory Fault, Alejandro Aguilar

All Graduate Theses and Dissertations, Fall 2023 to Present

Tectonic faults are made of many kinds of rocks and minerals, creating natural weak and strong zones along faults where earthquakes occur. These differences can affect how faults move, including whether slip occurs slowly and quietly or suddenly and destructively during an earthquake. However, it is not fully understood how these variations influence when earthquakes start, how fast they spread, and whether they stop or grow into large ruptures. This research studies how different fault materials interact during earthquake slip. Using a large laboratory machine that simulates fault movement under realistic conditions, we recreate earthquake processes and closely measure how …

Investigation Of Yy Production Methods For Invasive Channel Catfish Ictalurus Punctatus Population Management, Andrew M. Wisniewski

All Graduate Theses and Dissertations, Fall 2023 to Present

Aquatic invasive species are one of the leading causes of native fish declines in the Southwestern United States. Channel Catfish Ictalurus punctatus were introduced into the Colorado River Basin, including the San Juan River, New Mexico, Colorado, and Utah for fishery enhancement during the 20th century. This introduction has contributed to the decline of native species and despite intensive mechanical removal efforts, the Channel Catfish population has persisted in the San Juan River. The Trojan Sex Chromosome approach is a promising eradication strategy that proposes the production and release of Trojan sex chromosome carriers (YY) to skew a targeted population’s …

Mapler: An R Package For Estimating The Impact Of Climate Change On Maple Syrup Production, Matthew T. White

All Graduate Theses and Dissertations, Fall 2023 to Present

Successful maple sap tapping depends on the freeze/thaw cycle (i.e., temperatures fluctuating above/below freezing) during the winter and spring. Climate change threatens to alter the timing and duration of the tapping season. This necessitates research into how maple sap tapping will be impacted by climate change in order to help maple syrup producers prepare for the future. We define a sap day as a day where the freeze/thaw cycle occurred. Using information climate scientists use to predict future temperatures, we calculate how many sap days could occur each year. We develop software to analyze these sap day calculations to determine …