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Integrated Geophysical, Geotechnical, And Mineralogical Characterization Of Expansive Weches Formation Soils In East Texas: Implications For Infrastructure Design, Samuel Annobil

Electronic Theses and Dissertations

This study investigates the geotechnical, geophysical, and mineralogical characteristics of soils derived from the Weches Formation in Nacogdoches County, East Texas, with emphasis on the relationships among electrical resistivity, moisture condition, compaction state, and mineralogical composition. The Weches Formation is well known for producing clay-rich, moisture-sensitive soils that pose challenges to subgrade performance because of their plasticity and swelling behavior. Representative soil samples were collected and subjected to laboratory testing, including particle size analysis, Atterberg limits, Standard Proctor compaction, free swell tests, electrical resistivity measurements, and X-ray diffraction (XRD) mineralogical analysis. The soils are predominantly fine-grained and clay-rich, with USCS …

Final Silver Bow Creek Conservation Area Materials Management Plan, Pioneer Technical Services, Inc.

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

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 …

Causality-Driven Test Case Minimisation For Cyber-Physical Systems, Michael Foster, Christopher M. Poskitt, Nicholas R. Latimer, Neil Walkinshaw, Richard Somers, Robert M. Hierons

Research Collection School Of Computing and Information Systems

Cyber-physical systems allow digital control systems to interact with the physical world using sensors and actuators. They are increasingly being used to automate critical infrastructure, where software faults can have dire consequences. Due to the complex nature and unpredictability of these systems, their resilience is often tested using a technique called fuzzing, which generates quasi-random sequences of sensor and actuator manipulations with the goal of forcing a system into unsafe states. However, there is currently no way of determining which manipulations of a test case cause a failure without systematically removing each one and re-running the test, which can be …

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 …

Green Synthesis And Characterization Of Carbon Dots From Date Seeds For Antimicrobial Applications, Mariam Rami Hamdan

Theses

This thesis focuses on the synthesis and functionalization of Carbon Dots (CDs) derived from date seeds, followed by their conjugation with different antibiotics for antimicrobial applications. Carbon dots have gained increasing popularity due to their unique optical characteristics, surface properties, and biocompatibility. On the other hand, the utilization of date seeds offers a sustainable route towards obtaining value-added nanomaterials from agricultural waste. The central aim of this project is to develop and characterize CDs from date seeds and investigate their possible use as antibiotic carriers to improve antibacterial efficacy. The CDs were prepared using a green, cost-effective method and characterized …

Regional Assessment Of South Texas Wells Produced Water, Hunter T. Barnett

Water Resources Science and Technology Theses and Graduate Research Reports (Archived)

This study presents a regional assessment of produced water (PW) quality from oil and gas wells in South Texas, with a focus on variability and its implications for treatment and reuse. As oil and gas production continues to expand, PW waste streams will continue to grow. With a focus on the Eagle Ford Shale, understanding the chemical composition is critical for effective PW management. A total of 28 PW samples were collected from wells located in Pleasanton, Jourdanton, and Tilden, Texas. Samples were analyzed for key parameters including total dissolved solids (TDS), chloride, total hardness, and calcium. The results showed …

Ai Institute Summer Camp Webinar Summary, Dora Nguyen

Paul English Applied Artificial Intelligence (AI) Institute Publications

This report summarizes the AI Institute Summer Camp informational webinar hosted by the Paul English Applied Artificial Intelligence Institute (PEAAII) at the University of Massachusetts Boston. The webinar introduced the structure, curriculum, learning objectives, and student outcomes associated with the 2026 AI Institute Summer Camp. In addition to summarizing the webinar content, this report analyzes participant questions, engagement trends, and areas of audience interest. Findings indicate strong interest in coding accessibility, mentorship opportunities, student outcomes, research experiences, and program flexibility. The report also identifies opportunities for improving future webinar delivery, including expanded eligibility guidance, pre-camp learning resources, enhanced presentation of …

Evaluating The Rural/Urban Divide In Conservation: Methods Of Improvement In Conservation Programming Across Kentucky, Lauren Tackett

Honors College Theses

Kentucky’s lands and waterways have always defined the state. Our unique karst landscape, combined with the Appalachian Mountains and Ohio River, help characterize the state and its identity. However, across Kentucky conservation efforts within recent years have been under attack. Through legislation changes and policy challenges, various bills have sought to repeal Kentucky’s conservation efforts regarding water, soil, and land use. Furthermore, there has been a rise in environmental disasters within the state that cause long term issues for both rural and urban communities to contend with. The responsibility of land stewardship falls on a variety of entities but weighs …

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

All Graduate Theses and Dissertations, Fall 2023 to Present

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

Effects Of Beaver Dams On Components Of Riverscape Health And Biodiversity In The Great Basin, Cashe C. Rasmussen

All Graduate Theses and Dissertations, Fall 2023 to Present

Networks of rivers and their floodplains (i.e., low-lying areas adjacent to rivers and streams that could plausibly flood) have been degraded, reducing the availability of freshwater and habitat for people and wildlife. Therefore, land managers are pursuing cost-effective restoration strategies, including partnering with beavers (Castor canadensis), to promote the health of these ecosystems and associated benefits. However, our understanding of beaver-mediated restoration benefits remains incomplete. Here, we compared locations along streams with and without beaver dams to measure the benefits of beavers in the Great Basin of the Western United States. We measured the effects of beaver dams …

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 …

Comparing Strategies For Wetland Revegetation In An Uncertain Water Future, Hailey M. Machnikowski

All Graduate Theses and Dissertations, Fall 2023 to Present

Wetlands worldwide are expected to experience more frequent and intense droughts and floods due to climate change. These shifting water conditions introduce challenges to restoring wetland plants, especially using direct seeding. Seeding is cost and labor-efficient compared to planting, but seeds and seedlings are highly vulnerable to water stress, so restoration efforts often fail when conditions are too wet or dry. Understanding how to improve seed-based revegetation under these conditions is increasingly important. Therefore, we sought to understand the response, measured by percent canopy cover or dry biomass weights, of native plants to different durations of drought in greenhouse experiments, …

Advancing Context-Aware Detection Of Socially Harmful Discourse Using Transformer-Based Models, Santosh Chapagain

All Graduate Theses and Dissertations, Fall 2023 to Present

Social media platforms are a central part of modern communication, shaping how people share ideas, build communities, and discuss social issues. While these spaces can support connection and self expression, they also enable the spread of harmful language such as hate speech. At the same time, social media is an important place where members of marginalized communities, including sexual and gender minorities, express stress, discrimination, and emotional challenges in ways that are often indirect and context dependent.

This research examines whether modern artificial intelligence systems can better identify harmful language and expressions of minority stress in online posts. The study …

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 …

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

All Graduate Theses and Dissertations, Fall 2023 to Present

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

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

How Novices Write Code: Discovering Best Practices, Matt Rau

All Graduate Theses and Dissertations, Fall 2023 to Present

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

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

Student Programming Behavior With And Without Phone Notification Suppression, Gavin T. Eddington

All Graduate Theses and Dissertations, Fall 2023 to Present

Many students work on programming assignments while receiving notifications from their phones, such as text messages or social media alerts. These notifications can interrupt focus and make it harder to stay engaged with a task. This study examines whether silencing phone notifications helps students stay more focused while programming. 

We collected data from students in an introductory computer science course while they worked on programming assignments. Students completed some assignments with notifications silenced and others without. We measured their activity using software that records typing behavior and identifies when students take long pauses, which can indicate interruptions or loss of …

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

All Graduate Theses and Dissertations, Fall 2023 to Present

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

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

An Assessment Of The Deep And Coastal Responses To Hurricane Passage In The Gulf Of Mexico, Using Complementary Observational Records And Model Simulations, Senam Kofi Tsei

Dissertations

In this dissertation, I examine and discuss different ocean features and ocean processes essential to the intensification of tropical cyclones in the Gulf of Mexico, drawing on observations, theory, and numerical model analyses across both the deep ocean and continental shelf-regimes. In the deep ocean, I integrate in situ measurements, theoretical framework, a 1D shear driven mixed layer model, and a high resolution model outputs to evaluate how salinity-driven stratification, Loop Current warm core eddies, pre-existing warm mixed layer temperatures, and the governing mechanisms mixed layer adjustment shape the upper ocean response before, during, and after storm passage. In the …

Crossing Boundaries: Brachinites And Their Diverse Asteroidal Origins, B. G. Rider-Stokes, F. A. Davies, T. H. Burbine, E. Maclennan, R. C. Greenwood, S. L. Jackson, M. Anand, Daniel Sheikh, M. M. Grady

Geology Faculty Publications and Presentations

Brachinite meteorites are typically linked to the olivine-rich A-type asteroids. In this study, however, they appear to exhibit unexpected spectral diversity. Spectroscopic analysis of seven meteorites from the brachinite clan reveals two distinct populations in band parameters, overlapping with both the A-type and S-complex asteroids. This dual association shows that a single meteorite group can originate from multiple asteroid taxonomies. Notably, one S-complex-like specimen, Northwest Africa (NWA) 14,635, displays band parameters similar to those of asteroid (65803) Didymos, the target of the European Space Agency's (ESA) ongoing Hera mission. These results underscore the value of spectroscopic characterization of poorly understood …

Drought-Tolerant Plants Of Great Salt Lake: Determining Dormancy Break, Germination, And Seeding Timing Requirements To Improve Restoration Under Hydrologically Extreme Conditions, Montana Horchler

All Graduate Theses and Dissertations, Fall 2023 to Present

Wetlands are declining worldwide, and those in arid regions are especially vulnerable to climate change, drought, water diversions, and other human pressures. As a result, land managers increasingly rely on active revegetation to re-establish native plant communities and their associated ecosystem functions. Restoration that utilizes seeds as the propagule source is often the most cost-effective way to revegetate large areas, but in highly variable environments such as exist at Great Salt Lake, Utah, drought and flooding regularly limit plant establishment. Restoration practitioners require science-informed strategies to reach their goal of establishing diverse native plant communities with high native species cover. …

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 …

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 …

Counterfactual Explanations For Time Series Through Local Pattern Mining And Generative Models, Omar Bahri

All Graduate Theses and Dissertations, Fall 2023 to Present

Machine learning systems increasingly make decisions that affect people’s lives, from medical diagnoses to loan approvals. When these systems analyze time series data—sequences of measurements collected over time, such as heart rhythms or sensor readings—users need to understand why a particular prediction was made. Counterfactual explanations address this need by answering “what-if” questions: what would need to change in the input for the system to make a different prediction? 

This dissertation develops methods for generating counterfactual explanations specifically designed for time series data. Time series often contain distinctive local patterns—short subsequences that distinguish one class from another. For example, a …

Rainbow Dominating Sets Of Graphs, Samuel L. Powell

All Graduate Theses and Dissertations, Fall 2023 to Present

The content of this thesis may be compared to a stack of plates with a common design that are broken, one at a time. If the plates are broken into large enough pieces you would be able to choose one fragment from each broken plate to discover the entire design that the plates share. For example, if you were still missing the center of the design after taking a piece from some plates, you could look for the piece of the next broken plate with the region in question.

We study the question of how many broken plates might guarantee …

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

All Graduate Theses and Dissertations, Fall 2023 to Present

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

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

All Graduate Theses and Dissertations, Fall 2023 to Present

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

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

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

Scalable Roof Polygon Extraction And Geometric Characterization From Remotely-Sensed Data For Snow Load Assessment, Jashon Newlun

All Graduate Theses and Dissertations, Fall 2023 to Present

Heavy snow accumulation on rooftops is a serious structural risk in cold climates, and understanding how much snow builds up on different types of roofs is essential for safe building design. Currently, most data on roof snow loads comes from small, labor-intensive field surveys that cover only a handful of buildings at a time. This results in far too few measurements of buildings to draw confident conclusions about how snow behaves across communities. This thesis develops and demonstrates a new automated approach for measuring roof snow accumulation and extracting key building characteristics across thousands of buildings at once using airborne …

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

All Graduate Theses and Dissertations, Fall 2023 to Present

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

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