Digital Commons Network^™

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 …

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 …

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 …

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 …

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 …

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 …

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 …

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 …

Post-Quantum Cryptography Encryption Implementation For Messaging App, Callum S. Ward

Theses/Capstones/Creative Projects

This paper and complementary capstone project aim to explore the state of post-quantum cryptography today by defining the algorithms with which quantum computers can decipher modern asymmetric cryptographic algorithms in exponentially accelerated time, exploring national standards body NIST’s recommendations to circumvent these weaknesses with post-quantum solutions, and implementing recommended algorithms in my group’s project for the UNO Computer Science Capstone course, LockTalk. After having decided on ML-KEM for quantum-resistant asymmetric key transfer and AES-256 for symmetric message encryption and decryption, I was able to cryptographically encode messages to obscure their plaintext values from communication interceptions without any discernible increase in …

Blockchain Message Integrity For Messaging App: Python-Based Implementation Of Blockchain-Backed Verification And Tamper Detection, Brendan J. Farrell

Theses/Capstones/Creative Projects

With the rapid development and use of digital communication, the need for maintaining the integrity and authenticity of transmitted information becomes more pressing than ever.  However, existing methods of data exchange have several flaws and drawbacks such as reliance on centralized networks which are subject to manipulation, modifications, and potential failures.  Thus, the current project offers an innovative approach to improving the integrity and detection capabilities of messages in real-time communication platforms using the power of blockchain technology.  The proposed solution uses the inherent features of blockchain-based systems to ensure secure and safe message transmission.

Message Malware: File Vulnerability Scanning In Messaging Apps, Miah Mason

Theses/Capstones/Creative Projects

As messaging platforms become primary communication hubs within highly secure environments, they introduce significant vulnerabilities regarding file sharing with potential malicious content. This research, an honors extension of the Northrop Grumman sponsored Capstone project ‘LockTalk’, evaluates the technical abilities of automated file scanning methods within messaging platforms like Slack, Microsoft Teams, or our own developed platform LockTalk. This paper investigates a variety of scanning methods and their applications, with particular emphasis on comparing the qualities of static scanning, used in signature-based detection, and dynamic scanning with heuristics. Furthermore, this paper investigates the differences and advantages of both End-to-End Encryption (E2EE), …

Using Ai For Data Loss Prevention, Camden A. Wright

Theses/Capstones/Creative Projects

Data Loss Prevention (DLP) systems play a critical role in protecting modern systems that handle sensitive information from both accidental and malicious exposure. Traditional DLP approaches often rely on static rules and methods that can struggle to adapt to complex and evolving data patterns. This paper presents a hybrid DPL system that integrates machine learning-based message classification, rule based policy enforcement, and context-aware access control to improve both detection accuracy and decision reliability. In addition, the system introduces a second stage access control model that evaluates user context, including role of clearance level and job title to determine whether access …

Safepass: Efficient Emergency Vehicle Passage With Minimal Disruption To Traffic Flow, Osho Osho, Suchetana Chakraborty, Sajal K. Das

Computer Science Faculty Research & Creative Works

Emergency vehicle passage in congested urban networks poses a dual challenge: ensuring rapid response while minimizing disruption to surrounding traffic. This study addresses this challenge in the context of Connected Autonomous Emergency Vehicles (CA-EVs), proposing SafePass , a lightweight distributed framework for seamless CA-EV passage through decentralized, cooperative maneuvering of surrounding Connected Autonomous Non-Emergency Vehicles (CA-NEVs). At its core, SafePass employs the Target Lane Potential (TLP), a novel utility-based metric combining lane-choice utility with probabilistic gap acceptance, augmented by a cascade-aware penalty that suppresses upstream shockwaves triggered by gap-creation maneuvers. Evaluated in Simulation of Urban Mobility (SUMO) using synthetic traffic …

Utilizing Brain Computer Interfaces That Interact With A Virtual Keyboard, Skye Lilienthal

Honors Theses

A brain-computer interface (BCI) can allow someone to utilize electrical signals in their brain to complete tasks using a computer. BCIs can help people take advantage of technology to type without the need for a traditional keyboard setup. This paper used the OpenBCI Mark IV to test the effectiveness of non-invasive BCIs with dry electrodes within the OpenViBE P300 Speller. This paper shows how to use the P300 speller through a setup pipeline. Results indicate that electrode placement affects P300 accuracy and that areas related to visual processing improve accuracy, suggesting that P300 signals can be detected within OpenBCI Mark …

Towards Generalizable Representation Learning Across Domains, Hossein Kashiani

All Dissertations

Despite remarkable progress in deep learning, a major challenge remains: machine learning models often struggle to generalize to unseen domains under distribution shift. In real-world settings, data often differ from training conditions due to changes in lighting, sensor type, image resolution, and style. These differences can significantly degrade performance, highlighting the need for representations that are both robust and generalizable. This thesis addresses this challenge by developing a set of frameworks for generalization across domains in anomaly detection, deepfake detection, and vision-language image recognition. For anomaly detection, this thesis introduces ROADS, a robust prompt-driven framework for multi-class unified anomaly detection. …

Open Space Management Planning: A Framework And Case Study From Eagle Mountain City, Utah, Nathan K. Shumway

All Graduate Reports and Creative Projects, Fall 2023 to Present

Open Space Management Plans (OSMPs) are increasingly used by municipalities to guide the long-term stewardship of natural lands; however, little formal guidance exists regarding how these plans are structured, developed, or organized in practice. While numerous OSMPs are publicly available, their compositional logic, procedural workflows, and thematic priorities remain largely undocumented within academic literature. This study addresses that gap through a qualitative document analysis of fifteen publicly accessible OSMPs from the western United States, published between 2015 and 2024.

Using manual matrix-based coding in Microsoft Excel, each plan was analyzed through three lenses: structural composition, procedural development, and thematic content. …

Design And Verification Of The Multi-Slit Solar Explorer Camera Field Programmable Gate Arrays, Jordan M. Johnson

All Graduate Reports and Creative Projects, Fall 2023 to Present

The Multi-Slit Solar Explorer, or MUSE, is a NASA mission that will take images of the Sun to study solar flares and the solar corona. The mission will provide insight into the mechanisms behind space weather. The mission consists of two cameras: the Spectrograph (SG), and the Context Imager (CI). The Utah State University Space Dynamics Laboratory is providing both cameras for the mission.

This report describes a part of the design and verification process for a central component on these cameras known as the Field Programmable Gate Arrays (FPGAs). These FPGAs are programmed to acquire, handle, and send images …

Urea-Based Boronium Salts As Antimicrobial Agents, Gabriel Allen Merchant

Honors Theses

Quaternary ammonium compounds (QACs) are widely used in disinfectants due to their ability to inhibit the growth of and eliminate microbes. The potency, broad-spectrum activity, and low cost of QACs have made them a cornerstone of modem hygiene. In recent years, QACs have garnered many health and safety concerns due to their overuse and subsequent accumulation in the environment. The increased use of QACs has further led to an increase in antimicrobial-resistant bacteria, making the synthesis of novel antibacterial compounds vital to combat this growing threat. Recent advances in boronium salts offer a unique alternative to address these adverse effects. …

Structure-Property Relationships In Epoxy/Amine-Derived Polyester Thermosets, Jeffrey Aguinaga

Dissertations

This dissertation relates to ester-containing aromatic epoxy monomers and thermosets formed via reaction of those monomers with either ester-containing or non-ester-containing amine comonomers.  Due to the wide array of potential reactants (many bioderivable) to form ester-containing epoxy monomers that are closely related in structure, fundamental study of structure-property relationships was highly practical for this platform of materials.

Though properties of aromatic epoxy thermosets of relatively high-crosslink density and network strand rigidity vary widely with chemical composition and architecture, relatively low fracture toughness and impact resistance due to lack of ductility are typical. Integration of ester functionality and aliphatic spacers/connectors for …

Exploring The Effects Of Polymer-Graphene Interactions On Bulk Composite Properties Using Finite Element Analysis, Bryant Grove

Dissertations

As a filler in high performance materials, graphene significantly enhances the mechanical properties of polymer composites. Experimental characterization of graphene composite enhancements is limited by labor-intensive processes in both synthesizing composites for different purposes and in characterizing the interactions between graphene and polymer composites that lead to these enhancements. Computational approaches such as finite element analysis (FEA) are suitable alternatives that go beyond experimental analysis. This dissertation demonstrates the utility of FEA in analyzing polymer graphene composites with an emphasis on modeling the interaction between graphene fillers and the matrix within the interphase formed between them. The accessible design framework …

Enhancing Traffic Safety Through Ai-Driven, Privacy-Preserving, And Secure Impaired Driving Detection Systems, Razan Alsulieman

Dissertations

Drunk driving remains a major threat to road safety worldwide, contributing significantly to traffic injuries and fatalities each year. Traditional detection approaches are largely reactive and vehicle-centric, relying on in-vehicle sensors, breathalyzers, or post-incident enforcement. These methods often depend on driver cooperation, intrusive hardware installations, or limited monitoring environments, restricting their scalability and effectiveness in large transportation systems. At the same time, modern cities increasingly deploy roadside cameras, surveillance networks, and drone- based monitoring systems, creating new opportunities for proactive intoxication detection at the infrastructure level. However, leveraging such external monitoring introduces challenges related to secure data collection, reliable AI-based …

Sustainability Savvy: The Role Of Competence And Efficacy In Promoting Pro-Environmental Behavior, Lorenna Graham

Environmental Studies Honors Projects

Combatting environmental issues requires both large-scale and individual change. While many understand that personal pro-environmental behavior (PEB) is necessary, individuals do not always engage in this behavior (Hines, 1986, Goh, 2022). Thus, there is a need to investigate psychological factors which encourage PEB. Prior research suggests competence and outcome efficacy as likely PEB predictors (Bentler, 2023, Lavergne & Pelletier, 2015, Priolo, 2016), while cognitive dissonance has been shown to both encourage and discourage PEB (Bouwman, 2022, Dickerson, 1992, Ehrich & Irwin, 2005). Study 1 investigates the relationship between cognitive dissonance and PEB with competence and outcome efficacy as potential moderators. …

Sustainability Concepts In "Lab" Projects For Calculus I, Ii, And Iii (Poster), Joshua Holden

Faculty Publications - Mathematics

No abstract provided.

Integrating Ai Into Collection Development Workflows: Prompts, Rubrics, And Responsible Use, Ivan Portillo, David Carson, Margaret Puentes

Library Presentations, Posters, and Audiovisual Materials

AI technologies are advancing at a rapid pace and offer new opportunities for library advancement. This session highlights practical ways AI can support collection development and discusses opportunities to improve library workflows.  Attendees will also learn how AI can strengthen library resource management by optimizing decision making and use of resources.

Learning Outcomes: 

• Attendees will learn about approaches to integrating artificial intelligence into collection development
• Attendees will learn about artificial intelligence tools and their applicability to collections 
• Attendees will learn about the ethical use of artificial intelligence tools 

The Impact Of Community On Professional Identity In Computer Science Education, Ian A. Kollipara

School of Computing: Dissertations, Theses, and Student Research

This thesis explores the application of Communities of Practice (CoPs) in Computer Science Education. The work consists of two qualitative studies examining related but distinct populations: (1) K–12 CS teachers and (2) undergraduate CS students. The first study presents a retrospective analysis of conneCTION, an online CoP for K–12 CS educators, identifying strengths, weaknesses, and design considerations that inform future platform development. The second study investigates how participation in a CoP can mitigate negative and exclusionary stereotypes in CS. This study was conducted in an under-explored context: a small, private, religious, Midwestern university, and examines an existing community, the Programming …

College Of Natural Sciences Spring Newsletter, College Of Natural Sciences

College of Natural Sciences Newsletters and Reports

[Page 1] Dean's Message
[Page] 2 Awards & Recognitions // Student Spotlights
[Page] 3 Zhang Named to Landsat Science Team // The Power of Teaching
[Page] 4 “Science as Art” Competition Welcomes High School Artists
[Page] 5 Testing for “Forever Chemicals” in Surface Water // New Faculty Spotlight
[Page] 6 Ambassador Initiated Outreach
[Page] 7 57th Annual Geography Convention
[Page] 8 Twice the Impact on On Call with the Prairie Doc
[Page] 9 Making Staple Foods Healthier // Halaweish & Cole-Dai Retire
[Page] 10 Drone Day 2026
[Page] 11 Student Research, Scholarship, and Creative Activity Day (SRSCAD)
[Page] 12 Ceremony …

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 …

Model Stormwater Standards 2026, Unh Stormwater Center

UNH Stormwater Center

The purpose of post-construction stormwater management standards is to provide reasonable guidance for the regulation of stormwater runoff to protect local natural resources from degradation and prevent adverse impacts to adjacent and downstream land, property, facilities, and infrastructure. These standards regulate discharges from stormwater and runoff from land development projects and other construction activities to control and minimize increases in stormwater runoff rates and volumes, soil erosion, stream channel erosion, and nonpoint source pollution associated with stormwater runoff.