Digital Commons Network^™

Vision-Language Guided Quadruped Navigation With Reinforcement Learning Control, Chen Yuan Wang

Theses and Dissertations

Large Language Models and their multimodal variants, Vision-Language Models (VLMs), can interpret natural language instructions and visual context. Reinforcement Learning (RL) methods such as Proximal Policy Optimization (PPO) have been shown to successfully learn stable quadruped locomotion. This work investigates whether a VLM integrated with an RL controller can control a quadruped robot to perform instruction-following navigation to a predefined target using text instructions, egocentric vision, and proprioceptive state.

Most VLM-based robotics work directly target prediction of robot actions from multimodal inputs. This approach often depends on large amounts of expert demonstration data, generated by controllers such as trained RL …

Using Siamese Neural Networks To Effectively Detect Trojans In Fpgas When Trojans Manipulate Encryption Operations At The Bitstream Level, Kylie Arnett

Graduate Theses and Dissertations (2019 - present)

This research investigates security vulnerabilities in Field-Programmable Gate Arrays (FPGAs) at the bitstream level, focusing on hardware trojans (HTs) that manipulate encryption operations. This study addresses two critical questions: (1) The feasibility of exploiting FPGA bitstreams to selectively bypass encryption operations when a predefined input pattern is observed (all ones), thereby exposing sensitive data, and (2) the efficacy of Siamese Neural Networks (SNNs) in detecting such trojans with high accuracy. FPGAs are vulnerable to malicious modifications during manufacturing or deployment, posing risks to data integrity and system functionality. In this work, a trojan is inserted into a Xilinx series-7 FPGA …

Polyglot File Detection For Forensic Investigations, Chase Stevens

Graduate Theses and Dissertations (2019 - present)

As technology has become far more ubiquitous over the years, so too has the amount of digital evidence that can and needs to be collected and processed. Forensic tools are developed in response to the growing need, but are limited to what they are programmed to do. One such forensic tool is Autopsy, one of the most widely used open-source tools. Autopsy uses known file-type signatures (e.g., headers, trailers) to identify and recover files from forensic images. Polyglot files introduce a unique problem to both these forensic tools and investigators alike. In the context of the research conducted, polyglot files …

Detecting Sophisticated Cyberattacks On Public Water Infrastructure, Ayrton Purdy

Graduate Theses and Dissertations (2019 - present)

In recent years there has been an increasing number of cyberattacks on public water generation and distribution systems. Advanced persistent attackers could usurp sensors and control systems to contaminate public drinking water. In order to conceal their malicious activity, they can manipulate sensor data flows to give the appearance of normal activity. The compromised sensors would report normal chemical levels even though unsafe water is entering the distribution system. In response, this research proposes a multi-sensor, cross-comparison approach to anomaly detection. The proposed approach is designed to detect sophisticated cyberattacks which are not easily detectable using traditional cyber tools. The …

Examining Student Practices In A Technology-Mediated Math Classroom, Bradley T. Dodd

Electronic Theses, Projects, and Dissertations

It is important for math educators to make sense of student thinking in the classroom. Without opportunities to practice this skill math educators struggle to improve, particularly when students are engaging in mathematics using technology. As such, there is a need for video artifacts of students engaging with mathematics using technology for use in professional development activities (Lovett 2020). In accordance with Lovett et al.'s (2020) design principles for examining student practices in a technology-mediated environment, I carried out a study to determine whether these artifacts of student work could be created working with college undergraduates as participants. Students engaged …

Comparing Awssi And Traditional Winter Metrics For Predicting Overwinter Survival Of Juvenile Walleye (Sander Vitreus), Camille N. Shifrin

Honors Program: Senior Projects (Public)

Winter conditions are an important driver of recruitment variability in freshwater fishes, yet winter severity is often characterized using single climate metrics. These simplified approaches may not capture the cumulative stress experienced by fishes during winter. The Accumulated Winter Season Severity Index (AWSSI) integrates multiple components of winter climate and may therefore provide a more biologically relevant indicator of overwinter survival. In this study, we compared AWSSI with traditional winter severity metrics to explain interannual variation in overwinter survival of juvenile Walleye (Sander vitreus) in Harlan County Reservoir, Nebraska. Model comparisons using Akaike’s Information Criterion (AIC) indicated that …

Real-Wastewater-Derived-Struvite Effects On Micronutrients In Runoff Water, Lauren E. Pruitt

Crop, Soil and Environmental Sciences Undergraduate Honors Theses

Phosphorus (P) is an essential nutrient needed in agriculture for proper plant growth and development and is often introduced into agricultural systems in the form of synthetic P fertilizers. Mined rock phosphate is the primary P source for the production of synthetic P fertilizers and is a finite resource. Struvite (MgNH₄PO₄·6H₂O) is a compound that can be precipitated from municipal wastewater, recovering P, and is currently being evaluated for its potential use as an alternative fertilizer-P source. The objective of this study was to evaluate the effects of fertilizer-P source [i.e., synthetic electrochemically precipitated …

Construction Impacts On Nutrient Loads In An Urban Stream In The Ozark Highlands, Matthew B. Wilson

Crop, Soil and Environmental Sciences Undergraduate Honors Theses

Degradation of water quality is primarily caused by human activity, including urbanization. Urban stream syndrome can be characterized as a stream that has undergone physical, chemical, and biological changes as a result of urbanization, which can include an influx of nutrients that can drive unwanted plant and algae growth. It is known that construction can result in untreated nutrients entering a stream; however, it is not understood how construction affects downstream nutrient transport. The objective of this study was to understand the impacts of construction on urban water quality in Tanglewood Branch in Fayetteville, Arkansas, in the Ozark Highlands, which …

Datapeer: A Hybrid Interaction Model Web Application Integrating Llms For Human–Llm Collaboration In Data Analysis And Exploration, William I. Bumcum

Honors Theses

DataPeer is a web application that combines open-ended high agency (OHA) and structured low-agency (SLA) interaction paradigms to support human-LLM collaboration in exploratory data analysis. DataPeer integrates a large language model (LLM) with a React frontend and FastAPI backend, allowing both qualitative and quantitative analysis of user-uploaded CSV datasets through a chat-based interface. Users can attach datasets and provide natural language queries, while the LLM provides data analysis to the user. This thesis investigates the integration of LLMs into data analysis workflows and addresses gaps in interaction design and user agency in LLM-driven data tools by offering a responsive interface …

Sql Query Optimization - Human Vs. Chatgpt, Hailey Dennis

All Graduate Reports and Creative Projects, Fall 2023 to Present

Large Language Models (LLMs) such as ChatGPT have become ubiquitous tools for working professionals in the software industry. Many engineers are finding new ways to increase productivity by offloading tasks onto LLMs, while others are finding it difficult to trust code produced artificially, even after review. Taking a look at both perspectives, this study aims to compare a human’s ability to optimize SQL queries to that of an LLM and assess the experience using both methods.

Manual query optimization is a tedious task that relies heavily on statistics, heuristics, and good intuition. The SQL developer must search for the optimal …

Utilizing Pine Needles To Compare Spatial Profiles Of Polycyclic Aromatic Hydrocarbons (Pahs) In Two Urban Areas, Autumn Jensen

Undergraduate Honors Capstone Projects

Polycyclic aromatic hydrocarbons (PAHs) are an important class of semivolatile air pollutants known for their adverse health impacts. This research used conifer needles as passive air samplers to create spatial maps of two Utah cities (Rose Park and Spanish Fork) to compare overall PAH exposure and identify any differences in their congener profiles or PAH “fingerprints”. Conifer needles were chosen due to their prevalence as a passive air sampler in previous research and their ubiquity in urban and suburban environments. Second year needles were collected and the concentrations are considered to be an annually averaged view of the PAH concentrations …

Provenance Analysis Of Advanced Persistent Threats In Operational Technology Environments, Laura Aminta Guevara

Open Access Theses & Dissertations

Live vulnerability testing and penetration assessments of critical infrastructure are costly, complex operationally and, in many cases, unsafe to conduct directly against live systems, whether these are commissioned in-house and through third-party providers. For Operational Technology environments specifically, these constraints are further aggravated by the limited vendor support and inconsistent security patching available that characterize many industrial communication protocols. This significantly restricts the scope and feasibility of conventional penetration testing. At the same time, the increasing overlapping of OT systems with enterprise networks and the internet has expanded the attack surface of ICS infrastructure, making more pressing the need for …

Numerical Methods For Modeling Darcy-Forchheimer Flow In Heterogeneous Porous Media, Nate Mcnair

Open Access Theses & Dissertations

Classic approaches to modeling fluid flow in porous media rely on Darcy's Law, which assumes a linear relationship between volumetric flow rate and the pressure gradient. However, in recent years, applications such as enhanced geothermal systems have highlighted the need to model nonlinear flow behavior, since experimental and observational data show that, once flow velocity exceeds a certain threshold, the relationship between velocity and macroscopic pressure gradient becomes nonlinear. This requires alternative models that more accurately capture the physical behavior of these systems.The Darcy-Forchheimer model provides one such alternative by introducing a nonlinear velocity-pressure relationship. However, this nonlinearity creates additional …

Zero-Knowledge Proofs For Verifiable Machine Unlearning, Bidur Niroula

Open Access Theses & Dissertations

Machine unlearning aims to remove the influence of deleted data from a trained machine learning model. This is important because privacy regulations such as GDPR, CCPA, and PIPEDA give individuals the right to request the deletion of their personal data. Since unlearning can be expensive, a dishonest server may skip it or return an incorrect model and this motivates verifiable machine unlearning. Existing cryptographic approaches prove that the server executed a specific training or unlearning algorithm on the committed dataset, so the proof is tied to the algorithm's trajectory. Empirical verifiers avoid this cost but are known to be circumventable …

Log Anomaly Detection With Parameter-Efficient Tiny Language Models: From Centralized Fine-Tuning To Privacy-Preserving Federated Learning, Isaiah Thompson Thompson Ocansey

Open Access Theses & Dissertations

System logs are a primary source of information for identifying faults, misconfigurations, and security incidents in computing infrastructure. As these logs grow in volume and complexity, manual inspection becomes impractical, and automated detection methods are needed. This thesis investigates how compact language models can be applied to the task of log anomaly detection under two operational conditions: when log data is centralized and when it is located at different data sites.

In the first part, we propose LogTinyLLM, which applies parameter-efficient fine-tuning through Low-Rank Adaptation and adapter-based techniques to adapt tiny language models for identifying contextual anomalies in log sequences. …

Contamination-Aware Boosting For Cancer Prediction, Francis Opoku

Open Access Theses & Dissertations

Modern cancer research increasingly relies on machine learning methods to model complex relationships between high-dimensional genomic predictors and clinically relevant outcomes. Gradient boosting methods, particularly XGBoost, have become widely used due to their strong predictive performance and ability to capture nonlinear effects and interactions. However, these methods are sensitive to contamination in the data, especially in the response variable, where even a small fraction of aberrant observations can disproportionately influence model fitting and degrade generalization.

In this thesis, we propose a contamination-aware extension of XGBoost, termed CA-XGBoost, which improves robustness by explicitly modeling residuals through a latent mixture framework. This …

Penalty Approach To Constrained Optimization Problems In Water Reservoir And Energy Generation Management, Edwin Horacio Trejo

Open Access Theses & Dissertations

The growing demand for resilient and sustainable energy generation has driven interest in Hybrid Floating Photovoltaic-Hydropower (HFPVH) systems. Operating these systems effectively requires making water release decisions that satisfy physical and regulatory constraints while maximizing energy production. Prior work by Vega (2024) developed a Dynamic Outlier Filter Long Short-Term Memory (DOF-LSTM) architecture for forecasting reservoir release patterns. That predictive work is valid and addresses an important component of the HFPVH decision pipeline. However, the constraint system in that work operates externally to the learning process, and the behavior of penalty-based constraint enforcement had not been studied independently in this context. …

Molecular Mechanisms Of Pfas Induced Protein Dysfunction: Implications For Neurodegenerative Risk, Daisy Lee Wilson

Open Access Theses & Dissertations

Per- and polyfluoroalkyl substances (PFAS) are persistent environmental contaminants with widespread human exposure and well-established links to adverse health outcomes. However, despite increasing epidemiological and experimental evidence, the molecular mechanisms underlying PFAS-induced neurotoxicity remain incompletely defined. This dissertation investigates PFAS toxicity across biological scales, integrating protein biophysics with neuronal cell models to elucidate pathways relevant to neurodegeneration. At the molecular level, we demonstrate that PFAS disrupts the structure and function of globular proteins, including the impairment of α-lactalbumin's calcium-binding capacity and of β-lactoglobulin's retinol binding, through concentration-dependent conformational destabilization. By applying these findings to a neuronal model, we show that …

Comparative Case Studies Of How General Chemistry Ii Students Explain Entropically-Driven Phenomena, Raymundo Aragonez

Open Access Theses & Dissertations

Understanding how students conceptualize entropy remains a central challenge in chemistry education. Often referred to as a "driving force" of chemical reactions, the dispersal of energy as a process proceeds is indicative of a process's spontaneity or thermodynamic favorability. Students frequently default to discussing phenomena in deterministic terms, potentially reflecting the language choice and heuristics selected by the instructor such as "disorder". In this study, assessment prompts about entropy from a convenience sample of general chemistry textbooks were characterized as to their potential to elicit three-dimensional learning, and students' responses to assessment prompts from a curriculum aligned with three-dimensional learning …

Automated Arctic Coastal Boundary Extraction From Multispectral Satellite Imagery, Harshavardhini Bagavathyraj

Open Access Theses & Dissertations

Arctic coastlines are changing rapidly as permafrost thaw and coastal erosion accelerate under a warming climate, creating a need for accurate and scalable methods to monitor landscape change. Two geomorphically important indicators of this change are the shoreline, which represents the land--water boundary, and the bluff edge, which marks the transition from vegetated tundra to the coastal slope or cliff. However, delineating these features from high-resolution imagery remains challenging because Arctic scenes are spatially extensive and visually complex. In this study, we address these challenges by developing deep learning methods for automated shoreline and bluff-edge extraction from high-resolution satellite imagery …

Computational Studies Of Dna-Wrapped Carbon Nanotubes: From Enantioselective Dna Binding To Molecular Recognition Of Small-Molecule Analytes, Sayantani Chakraborty

Open Access Theses & Dissertations

Single-walled carbon nanotubes (SWCNTs) exhibit chirality-dependent optoelectronic properties and near-infrared fluorescence that make them promising platforms for biosensing. When functionalized with single-stranded DNA (ssDNA), SWCNTs form conjugates capable of selective molecular recognition. However, the molecular mechanisms governing chirality recognition and analyte-induced optical modulation remain incompletely understood. This dissertation investigates these mechanisms through an integrated computational approach combining molecular dynamics simulations, enhanced sampling techniques, and machine learning. First, atomistic molecular dynamics (MD) and replica exchange MD simulations were used to investigate how short ssDNA sequences interact with enantiomers of (7,5) SWCNTs. Analyses of base stacking, nucleotide orientation, sugar-phosphate positioning, and contact …

Hvsr-Based Resonance Analysis And Fault Zone Characterization In The El Paso Region, Alexandro Dominguez

Open Access Theses & Dissertations

Horizontal to Vertical Spectral Ratio (HVSR) analysis offers an efficient method for characterizing near-surface structure, resolving sediment thickness, and identifying fault-controlled basin geometry in regions with strong impedance contrasts. This study applies HVSR techniques to continuous ambient-noise recordings collected across the El Paso region, a tectonically active segment of the southern Rio Grande Rift where accurate subsurface mapping is essential for seismic hazard assessment. Ambient-noise windows were processed, spectrally smoothed, and stacked to obtain stable HVSR curves, from which fundamental resonance frequencies and corresponding sediment-thickness estimates were derived. Spatial patterns in these resonance frequencies reveal pronounced basin asymmetry, abrupt lateral …

From Covid-19 To Influenza: Transforming Public Health Surveillance Through Freeze-Drying Innovations, Rui Dong

Open Access Theses & Dissertations

Public health surveillance increasingly relies on wastewater-based epidemiology (WBE) as a non-invasive, community-level early warning system for infectious diseases like COVID-19 and influenza. However, detecting minute viral concentrations in complex wastewater matrices remains a significant analytical challenge. Traditional concentrating methods, such as ultrafiltration, are limited by high performance variability and significant viral signal loss due to necessary pretreatment steps, such as pre-clarification, which inadvertently discard solid-associated viral fractions. To address these limitations, this dissertation introduces and evaluates freeze-drying as a novel, pretreatment-free concentrating method for wastewater viral surveillance. By sublimating water, freeze-drying uniquely retains both liquid and solid-phase viruses within …

A Diagnostic Test For Confounding Under Collapsibility In Generalized Linear Models (Glms), Samuel Dela Gadah

Open Access Theses & Dissertations

This thesis develops and validates a diagnostic framework for assessing potential confounding in generalized linear models (GLMs) with collapsible link functions. Under collapsibility and effect homogeneity, the absence of confounding implies equality between marginal and covariate-adjusted treatment effects on the link scale, which motivates the change-in-estimate parameter δ = γ − γ(c) as the target of a formal hypothesis test. Two complementary inferential routes are developed: a nonparametric bootstrap and an independent estimating equation (IEE) procedure based on a stacked-data construction that yields a closed-form sandwich variance and is implementable in standard generalized estimating equation software. A backward elimination procedure …

Age And Characteristics Of Quaternary Fluvial And Dune Deposits Along The Arkansas And Cimarron Rivers In Osage And Pawnee Counties, Oklahoma, Barry A. Duncan

Graduate Theses and Dissertations

Quaternary aeolian and fluvial deposits along the Arkansas and Cimarron Rivers in Osage and Pawnee counties of central Oklahoma, record Late Pleistocene and Holocene fluvial landscape history in the eastern Osage Plains. Sediment supply, climate variability, channel incision, and channel migration control this landscape evolution. Sediment supply of both streams is dominantly sand. Late Pleistocene and Holocene precipitation have varied with periods of drought alternating with increased precipitation and warming. The study area is near the eastern boundary of substantial aeolian activity with drought and aeolian reworking of fluvial sand more severe to the west. This study examines the sediment, …

First-Principles Study Of Uranium Mononitride, Roy Noe Herrera Navarro

Open Access Theses & Dissertations

This thesis presents a first-principles investigation of uranium mononitride (UN), withemphasis on the connection between uranium 5f electron correlation and defect stability. Electronic-structure calculations were performed within density functional theory using the Vienna Ab initio Simulation Package. Exchange-correlation effects were treated within the generalized gradient approximation, and a Hubbard correction was applied to the uranium 5f manifold. The adopted Hubbard parameter was motivated by first-principles linear-response analysis and considered in the broader context of DFT+DMFT descriptions of correlated uranium systems, including recent interpretations of UN as a Hund-metal system. Bulk UN was studied in unit-cell and 2 x 2 x …

Singularity-Enriched Neural Networks For Elliptic Problems In Polygonal Domains, Harshini Reddy Kodiganti

Open Access Theses & Dissertations

This thesis develops and analyzes neural-network-based solvers for the Poisson equation on polygonal domains, where re-entrant corners induce reduced solution regularity and challenge standard numerical methods.

Three neural formulations are investigated: Physics-Informed Neural Networks (PINNs), Physics-Informed Extreme Learning Machines (PIELMs), and Rank-Inspired Neural Networks (RINNs). PINNs rely on gradient-based optimization with automatic differentiation, while PIELMs employ randomly initialized hidden features with least-squares training, achieving significantly lower computational cost. RINNs extend this framework through covariance-driven orthogonalization to improve numerical conditioning and stability.

On convex polygonal domains, all three methods are benchmarked against analytical solutions. Both PIELM and RINN consistently achieve higher …

Three Essays On Workplace Ethics And Ai: Conceptualizing, Scale Development, And Validation Of Self-Value Actualization, And Ai-Enabled High-Performance Work Systems, Mansura Nusrat

Open Access Theses & Dissertations

This dissertation advances understanding of workplace ethics and responsible AI integration across three interconnected essays unified by social cognitive theory. My first essay introduces self-value actualization (SVA), a novel construct defined as the dynamic, integrated psychological process through which individuals continually strive to align and fulfill their core moral values through observable professional behavior. Drawing on social cognitive theory and emotional intelligence theory, I conceptualize SVA as a higher-order self-regulatory orientation comprising three mutually reinforcing processes: value congruence, moral reflection, and adaptive morality. I developed and validated a 9-item SVA scale across four studies using expert panels, exploratory factor analysis, …

Deep Neural Network-Gaussian Process For Housing Price Analysis, Bismark Nyarko

Open Access Theses & Dissertations

Neural networks have demonstrated remarkable predictive performance in complex, high-dimensional settings. However, their highly parameterized structure and nonlinear architecture often make them difficult to interpret, limiting formal statistical inference and principled uncertainty quantification. In contrast, Gaussian processes (GPs) provide a fully probabilistic framework with a relatively small number of hyperparameters, enabling coherent uncertainty quantification and seamless integration into hierarchical and structured statistical models. Despite their theoretical flexibility as nonparametric function approximators, standard GP formulations frequently exhibit weaker predictive performance than modern neural networks in large-scale applications.

In this work, we employ a Gaussian process covariance function designed to approximate the …

Efficient Solvers For Phase Field Models, Raymond Obeng

Open Access Theses & Dissertations

Phase field models provide a versatile framework for describing phase transitions and pattern formation in materials, enabling the study of complex phenomena such as crystallization, grain growth, and defect dynamics. Among these models, the Phase Field Crystal (PFC) equation has gained significant attention due to its ability to capture atomic-scale structures while evolving on diffusive time scales. However, the numerical solution of the PFC equation presents substantial challenges arising from its high-order nature and the large-scale, coupled linear systems generated by discretization.

In particular, standard formulations of the discretized PFC system lead to non-symmetric and often ill-conditioned linear systems, which …