Digital Commons Network^™

Inferring Microstructure In Quaternary Sands Near Charleston, South Carolina Using Measured-To-Estimated Shear-Wave Velocity Ratio, Bikram Paudel

All Theses

The 1886 Charleston earthquake is one of the most destructive earthquakes in the history of the southeastern United States. It caused widespread damage and liquefaction, which is a phenomenon in which loose saturated granular soils lose their strength and behave like liquids during earthquakes. The main purpose of this research is to investigate how the earthquake changed the internal structure (termed as “microstructure”) of the sandy soil in the Charleston area. In general, when soil is deposited on a site and sits there for a long period of time, it develops a stronger structure through aging and cementation. To infer …

A Qualitative Analysis Of Ramp Metering Implementation: Lessons Learned From The West Coast Of The United States, Sydney Ford

All Theses

This study evaluates how ramp meters, traffic lights installed on highway on-ramps, are used to reduce traffic on the West Coast of the United States, specifically in California, Oregon, and Washington. This research was conducted to better understand how ramp meters are planned and implemented, and to help government agencies manage traffic effectively without adding new highway lanes.

This study reviewed 129 public documents from federal, state, and local agencies to evaluate public involvement in ramp metering planning, concerns about the meters, costs and funding for the meters, and the meters’ design and implementation.

Robustness Of Vision Language Models For Pedestrian Detection Tasks, Ostonya K. Thomas

All Theses

Autonomous vehicle (AV) systems typically employ modular systems in which discrete components handle separate tasks such as perception, computation, and path planning. While flexible, this approach allows errors to propagate and compound across the pipeline, and many AI systems offer little transparency into their internal decision-making. Such limitations are particularly concerning in safety-critical domains where failures can carry lethal consequences. Vision Language Models (VLMs) have emerged as a promising alternative because they support end-to-end implementations that bypass compounding error risks and provide natural language explanations of their outputs. Despite these advantages, prior research has demonstrated that both computer vision systems …

Neural-Network-Based Modeling Of Grid-Forming Inverters, Jacob D. Levesque

All Theses

Renewable energy production has grown significantly in recent years and continues to expand, resulting in an increasing number of inverter-based resources (IBRs) in the grid. As the number of IBRs in the grid continues to grow, grid-forming (GFM) inverters are becoming increasingly popular due to their ability to regulate voltage and frequency, providing increased grid stability and enabling islanding. As GFM inverters become more widely used in power systems, accurate and efficient models of their behavior are needed for system design purposes.

Emerging advances in neural networks have led to research on computationally efficient neural-network-based (NN-based) modeling approaches for inverters. …

Between Chronicle And Legend: A Two-Scene Environment And Visual Effects Examination Of Physical Accuracy And Emotional Exaggeration On The Honey Creek Bridge Collapse, Alison R. Gaddy

All Theses

This thesis explores how truth and dramatization intersect in digital storytelling by comparing realistic and stylized simulations of the Honey Creek bridge collapse within the context of the Kate Shelley animated short. At the core of storytelling lies a tension between factual accuracy and dramatic stylization. We investigate that tension by examining how narrative truth is conveyed, distorted, or enhanced through visual dramatization by focusing on the psychology of audience perception and the motivations behind creative embellishment. The practical contribution of this research is the development of two distinct digital scene setups depicting the same Honey Creek bridge collapse event. …

The Impact Of The Video Assistant Referee On Aggregate Match Outcomes And Measured Home-Field Advantage In European Soccer, Christopher P. Vetter

All Theses

The introduction of Video Assistant Referee (VAR) in European soccer aimed to improve referee decision accuracy in high-impact situations. This study examines the association between VAR implementation and match outcomes across Europe’s five major leagues. Exploiting the staggered adoption of VAR in Europe’s leagues between 2017 and 2019, the analysis utilizes both OLS and event study frameworks to evaluate average and dynamic patterns in match outcomes.

The results do not provide clear or consistent evidence of systematic changes in aggregate match outcomes following VAR implementation. While some event-time estimates suggest possible delayed movements in outcomes such as goals and yellow …

Romanticizing 'Monsters': Sexualized Digital Fandom Of The Menendez Brothers, Kimberly M. Brooks

All Theses

This study was conducted to explore the expressions of sexualized fandom and parasocial relationships within the context of true crime. The Menendez Brothers were chosen as the case to focus on due to the Netflix dramatization ‘Monsters: The Lyle and Erik Menendez Story’ release and online popularity. Reddit was the platform chosen for data collection because of the longstanding presence of true crime followers participating in dialogue on the platform. The r/MenendezBrothers thread was chosen to collect data from because of its large following and large number of weekly contributions. Sprinklr, the social media analytics platform, was employed to gather …

Multimodal Aerial Image-Based Ground Object Detection And Classification Using Yolo, Erik Nielsen

All Theses

Object detection in unmanned aerial vehicles (UAVs) present a unique challenge due to small object sizes, varying viewpoints, and changing environmental conditions. These challenges are exacerbated when operating during daytime and nighttime scenarios where illumination differences can heavily impact detection performance. This work is motivated by military object detection applications where the ability to reliably identify small objects such as landmines or unexploded ordnance from aerial imagery presents a critical safety need and a significant technical challenge. In this paper, we investigate object detection using both visible (RGB) and infrared (IR) imagery to improve robustness and reliability across diverse operating …

The Impact Of Dipeptides On Product Quality In Chinese Hamster Ovary Cells, Louise C. Herman

All Theses

Biopharmaceuticals are medicines produced in cells which are used to treat diseases such as cancer. Monoclonal antibodies (mAbs) represent the majority of approved biotherapeutics. MAbs are mostly produce using Chinese hamster ovary (CHO) cells. CHO cells are favored for resiliency, scalability, and established safety, and are considered the “workhorse” organism for biopharmaceuticals.  Amino acids are a key component of cell culture media, however several amino acids have solubility limits, such as cysteine, cystine, and tyrosine.  At neutral pH, these amino acids are poorly soluble.  However, dipeptides, such as N,N'-di-L-Alanyl-L-Cystine (ACCA) have been reported to increase cysteine and cystine availability. Further, …

The Dam Plan Matters: Proactive Policy And Nature-Based Solutions For Deliberate Dam Removal, Leah Kaisner

All Theses

Throughout the United States, the dam infrastructure is aging out of their lifespan. This increases risk of loss of life and property, particularly with dam failure. Dam aging necessitates proactive planning methods is needed to prepare communities for dam removal effects rather than responding to failure disasters. This thesis studies how city planners and local officials can use nature-based solutions, river restoration, and resilient policy tools to prepare for upstream dam removal. I created a Dam Removal Preparedness (DRP) Framework for integrating nature-based solutions, resilient policy, and restoration methods and used it as a scoring system to assess community plans’ …

Fluorescence-Based Quantification Of Hepatic Ldl Uptake And Donor Hepatocyte Engraftment Using Atto 700–Labeled Ldl, Victor Agustin Cortes Flores

All Theses

Familial hypercholesterolemia (FH) is an inherited disorder characterized by elevated low-density lipoprotein cholesterol (LDL-C) that increases the risk of premature atherosclerotic cardiovascular disease. In severe FH, including low-density lipoprotein receptor (LDLR), hepatic LDL clearance is profoundly impaired and many lipid lowering treatment strategies have limited effectiveness. Current advances in ex vivo CRISPR–Cas9 hepatocyte gene editing in vivo and ex vivo approaches for treatment of FH are under development.

However, a central barrier to translation is the ability to quantitatively measure the percentage of healthy gen edited hepatocytes in the liver while simultaneously assessing functional hepatic LDL handling. This thesis establishes …

Increasing The Number Of Injections Per Cycle In A Gasoline Compression Ignition Strategy: An Experimental Study, Joshua Murray

All Theses

Gasoline Compression Ignition (GCI) is an advanced compression ignition strategy which utilizes the high octane number of gasoline to improve diesel soot and NOx emissions by enabling partially premixed injections of fuel. GCI work in the literature typically uses single, double, or triple injection strategies, with higher numbers of injections noted for their ability to achieve low MPRRs, improved soot and NOx emissions, and higher efficiency. Thus, this study extends the literature by evaluating quadruple and quintuple injection strategies for continued improvement in engine efficiency and emissions.

The experiments in this work are conducted on a heavy-duty Detroit Diesel DD13 …

Exercise-Induced Muscle Damage As A Model For Exploring The Effects Of Pain On Gait, Sydney Savage

All Theses

Persistent gait asymmetry following anterior cruciate ligament reconstruction (ACLR) is a recognized contributor to post-traumatic knee osteoarthritis, yet the independent role of pain in driving altered movement patterns remains poorly understood due to confounding factors inherent to clinical populations. This study used exercise-induced muscle damage (EIMD) as a controlled experimental model to isolate the effects of musculoskeletal pain on gait, independent of kinesiophobia, structural damage, and proprioceptive disruption. Eighteen healthy adults underwent unilateral eccentric calf-raise protocols to induce delayed onset muscle soreness (DOMS), with gait assessed at baseline, 48 hours, and 168 hours post-exercise using bilateral inertial measurement units. Outcomes …

Beyond The Interface: Human Perceptions Of Generative-Ai Chatbots As Conversational Partners, Browning W.E. Blair

All Theses

Generative AI (gen-AI) chatbots are becoming embedded in everyday communicative life, yet it remains unclear whether users perceive these systems as socially reciprocative conversational partners. Therefore, this study examines how young adults understand and interact with gen-AI chatbots, focusing on perceptions of conversational partnership, anthropomorphism, politeness, discomfort, and technical understanding. Guided by the CASA framework, Media Equation Theory, and the uncanny valley hypothesis, this study employed four semi-structured, online focus groups with 15 undergraduate students and recent college graduates in the United States. Findings indicate that participants did not broadly perceive gen-AI chatbots as conversational partners in the interpersonal sense. …

The Invisible Toll: Black College Women And The Intersection Of Academic Stress, Rest Deficiency And Exhaustion At Clemson University, Jomya Ford

All Theses

Leisure has been an under-explored aspect of Black women’s lives in higher education, particularly within predominantly white institutions (PWIs), where limited culturally relevant opportunities and racialized isolation shape daily experiences. Constraints around rest, rooted in racism and gendered expectations, continue to influence how Black college women navigate academic pressure, deficiency narratives, and exhaustion. Guided by intersectionality, this qualitative study draws on semi‑structured interviews with Black undergraduate and graduate women at a PWI to explore how cultural upbringing, institutional climates, and internalized expectations shape their definitions and practices of rest. Findings show that while participants recognize rest as necessary, they rarely …

Design And Development Of A Perfusable Hydrogel Platform With Bioprinted Human-Endothelialized Microvascular Channels, Calvin A. Chernyatinskiy

All Theses

We developed an integrated bioprinting and perfusion platform to generate vascularized hydrogel constructs that support perfusable microchannel networks. Multiple hydrogel formulations, sacrificial ink systems, device geometries, and perfusion conditions were systematically evaluated to optimize print fidelity, mechanical stability, and cellular compatibility. Internally gelling alginate–calcium carbonate hydrogels were identified as a robust matrix, providing tunable gelation kinetics and structural stability during embedded printing. In parallel, Pluronic F-127 fugitive ink enabled reliable fabrication of continuous hollow channels due to its shear-thinning behavior and efficient post-print removal.

The finalized platform integrates stereolithographically fabricated perfusion chambers with extrusion-based bioprinting to produce three-dimensional, perfusable vascular …

Micro-Solar Kiln Design: A Cost-Effective Approach For Small Landowners To Produce Higher Quality Lumber, Bart Swecker

All Theses

Small-scale and hobby sawmill operators increasingly seek low-cost methods for drying lumber to moisture contents suitable for interior use, yet conventional kiln systems are often impractical due to capital cost, power requirements, and operational complexity. While air drying remains common at small scales, many operators require a controlled finishing step to improve dimensional stability and product value. Solar kilns offer an intermediate solution between air drying and conventional kilns; however, most published designs and performance data focus on systems with capacities far larger than those typically used by small-scale operators. Consequently, limited guidance exists for micro-scale solar kilns, particularly under …

Characterizing The Molecular Response Of Embryonic Zebra Finch To Acute Sound Playback, Saidat O. Adeniran-Obey Miss

All Theses

Auditory stimuli are important cues that influence developmental plasticity in animals and are important for development and adaptation to an ever-changing environment. In the zebra finch (Taeniopygia guttata), there is evidence of adaptive developmental reprogramming in response to a prenatal ‘heat call’. Embryos exposed to this heat call exhibit changes in growth rate post-hatch, increased heat resistance, and enhanced reproductive success at maturity. However, it has long been assumed that embryonic zebra finches cannot respond to sound due to the immaturity of their auditory system. These findings raise the critical question of whether late-stage zebra finch embryos can, …

Bayesian Assembly Tool For Intelligent Digital Twin Selection, Shishir Sharma

All Theses

Digital twins can be used for system performance optimization, health monitoring, predictive maintenance, and investigating system anomalies. A ground vehicle digital twin may be assembled using representations of the subsystem models (tires, suspension system, powertrain, etc.) of different fidelity. Lower fidelity Digital Twins have relatively simpler design and physics, hence are generally computationally less expensive, but may not represent the physical system accurately. On the contrary, higher fidelity Digital Twins are generally more precise in their ability to represent the physical system, but due to complexity, are usually computationally more demanding. This thesis describes the application of Bayesian Classification within …

Depicting Cultural Nuance Through Level Design, Sydney A V Fleming

All Theses

As the audience for gaming grows and expands, gamers consistently crave new stories that are interesting and that immerse them. The ability of gamers to relate to the characters is solely dependent on conscious choices made by developers. For the story to be enjoyable and immersive, It helps to understand the character’s motivation. Why would they act this way? Would they make this choice? Understanding a character culturally is a step in the right direction to gaining this needed understanding. Conveying culture respectfully in games is always a challenge. The goal of this project is to use the Unreal Engine …

Development Of Low-Cost Triaxial Force Sensor For Measurement Of Human-Exoskeleton Interaction Forces, Hamdan Khan Sarvathullah

All Theses

Contemporary research suggests that shear force is a major contributor to discomfort and pressure injury. However, the variation of shear forces during human-exoskeleton interaction dynamics is a highly unexplored field. The high cost of commercial triaxial force sensors may be a major factor in the notable lack of research in this field. Therefore, in this paper, we present a low-cost, 3D-printed triaxial force sensor designed specifically to measure the triaxial interaction forces between an exoskeleton and its user. The triaxial force sensor uses Carbon-Black/Silicone Rubber (CB/SR) strings to measure shear forces, whereas the normal force is measured with a Force …

Exploration Of Real-Time Power Electronic Simulation On Amd Npu, Shouyu Du

All Theses

The rapid electrification of the automotive and data center sectors has created a critical demand for high-fidelity, real-time simulation of complex power electronic systems. While Hardware- in-the-Loop (HIL) simulation on Field-Programmable Gate Arrays (FPGAs) is the current industry standard, it presents significant challenges regarding development complexity and memory limita- tions. This dissertation investigates the feasibility of utilizing Neural Processing Units (NPUs)— specifically the AMD AI Engine (AIE) XDNA2 architecture—as a novel platform for real-time, deterministic circuit simulation. This study establishes a comprehensive automated modeling framework based on graph theory and Massarini’s method to derive linear state-space representations for arbitrary circuit …

Identification, Pathogenicity, And Fungicide Sensitivity Of Itersonilia Perplexans Associated With Petal Spot Of Gerbera Cut Flowers In Colombia, Matheus Beger

All Theses

Petal diseases significantly affect gerbera cut flower production, as minor visual damage renders flowers unmarketable. Among those pathogens causing petal spots, Itersonilia perplexans affects some Asteraceae plants. However, this pathogen's impact on Colombian gerbera remains poorly studied. This study was designed to fill four gaps: molecular identification of Colombian isolates, confirmation of pathogenicity, standardized culture media, and fungicide sensitivity data. Four objectives were pursued: (i) isolate and identify the causal agent through sequencing the Internal Transcribed Spacer, Small Subunit and Large Subunit from the rDNA; (ii) evaluate pathogenicity on detached gerbera petals; (iii) identify optimal culture media for I. perplexans …

Implementation Of A Local Llm Serving System For Agentic Ai, Zhiheng Ni

All Theses

This thesis presents a system that allows large AI models to run directly on personal devices instead of relying on cloud servers. Recent advances in artificial intelligence, especially large language models (LLMs), have made it possible to build powerful applications such as chatbots, coding assistants, and intelligent agents. However, most of these systems run in the cloud, which raises concerns about privacy, latency, and cost.

To address these issues, this work develops a local AI serving system that runs efficiently on a specialized hardware component called a Neural Processing Unit (NPU). The system provides a unified interface that supports multiple …

Developing Aero-Floating Treatment Wetland (Aeroftw) Scaffolds: A Non-Plastic Alternative To Conventional Plastic-Based Ftws, Ada C. Montoya Gomez

All Theses

This research was conducted to explore the possibility of constructing floating treatment wetlands (FTWs) without using plastic materials. FTWs are floating platforms that hold plants on the water’s surface, letting roots dangle within the water column, to help remove contaminants from contaminated water, especially in stormwater ponds. Many conventional FTWs are made with plastic components, such as mats and plastic cup containers, which can release microplastics into the environment over time. The goal of this project was to design and test a new type of FTW that does not depend on plastics to support FTW flotation. The study took place …

Energetic Eutectics: An Experimental And Computational Investigation On Explosive Deep Eutectic Solvents, Connor J. Parker

All Theses

This study reports on the incorporation an extreme gradient boosting (XGBoost) machine learning strategy tailored to identifying potential high-energy, insensitive explosive deep eutectic solvents. 1,1-diamino-2,2-dinitroethylene (FOX-7) was investigated as the explosive of interest in our eutectic modeling. The resulting predictions highlighted a wide range of binary compositions demonstrating significant depression from the FOX-7 melting temperature with >70% probabilities of formation. Subsequent computational investigation into select mixtures provided underlying stabilization energies and optimized mixture geometries, which were then assessed experimentally with near simulant compounds oxalyldihydrazide and 1-methyl-3- nitroguanidine replacing FOX-7.

Experimental results with these chosen simulants did not demonstrate classical eutectic …

Ai-Powered Insights In Pediatric Nephrology: Current Applications And Future Opportunities., Arwa Nada, Yamen Ahmed, Jieji Hu, Darcy K. Weidemann, Gregory H. Gorman, Eva Glenn Lecea, Ibrahim A. Sandokji, Stephen Cha, Stella Shin, Salar Bani-Hani, Sai Sudha Mannemuddhu, Rebecca L. Ruebner, Aadil Kakajiwala, Rupesh Raina, Roshan George, Rim Elchaki, Michael L. Moritz, The American Society Of Pediatric Nephrology Quality Improvement And Artificial Intelligence (Aspn Qi/Ai) Interest Group

Manuscripts, Articles, Book Chapters and Other Papers

Artificial intelligence (AI) is rapidly emerging as a transformative force in pediatric nephrology, enabling improvements in diagnostic accuracy, therapeutic precision, and operational workflows. By integrating diverse datasets-including patient histories, genomics, imaging, and longitudinal clinical records-AI-driven tools can detect subtle kidney anomalies, predict acute kidney injury, and forecast disease progression. Deep learning models, for instance, have demonstrated the potential to enhance ultrasound interpretations, refine kidney biopsy assessments, and streamline pathology evaluations. Coupled with robust decision support systems, these innovations also optimize medication dosing and dialysis regimens, ultimately improving patient outcomes. AI-powered chatbots hold promise for improving patient engagement and adherence, while …

Mechanistic Investigation Of Arsenic Removal From Drinking Water Using Metal–Organic Frameworks And Granular Activated Carbon, Mousa Almousa

Theses and Dissertations

Arsenic contamination in groundwater represents a critical environmental and public health challenge due to its high toxicity and widespread occurrence in natural aquifers. Chronic exposure to arsenic, even at trace levels, is associated with severe health effects, including skin lesions and increased cancer risk. Conventional treatment technologies, such as adsorption using activated carbon or metal oxides, often suffer from limited selectivity, regeneration difficulty, and reduced efficiency under varying pH conditions. Therefore, developing advanced sorbent materials with high capacity, selectivity, and structural stability is essential for addressing arsenic pollution in decentralized water systems.Metal–organic frameworks (MOFs) have recently emerged as promising materials …

Variable Selection Via Penalized Logistic Regression For Binary Classification, Gloria Antwi-Boasiako

Theses and Dissertations

In this study, we developed some hybrid estimators for variable selection in logistic regression by integrating the sparse local gradients (SLG) with some existing variable selection methods such as LASSO, Elastic net, SCAD, and MCP. The goal is to retain the flexibility of penalized likelihood estimation while improving the stability and interpretability of the selected model.

The finite-sample performance of the proposed methods is examined through a Monte Carlo simulation study covering low-, moderate-, and high-dimensional settings under different levels of predictor correlation. The simulation results show that incorporating SLG screening generally leads to more controlled model sizes and fewer …

Geochemical Modeling Of Co2 Sequestration In Saline Aquifer: Broom Creek Saline Aquifer, Lawrence Chima Asouzu

Theses and Dissertations

Geological carbon sequestration in deep saline aquifers is widely regarded as a critical technology for mitigating anthropogenic CO₂ emissions. This dissertation presents a formation-specific, kinetically constrained reactive transport modelling study of CO₂ storage performance in the Broom Creek Formation, a quartz- and feldspar-dominated saline aquifer in the Williston Basin, North Dakota.

A high-resolution geological model was constructed in Petrel using well logs, well tops, and Sorensen’s permeability correlation, then exported via RESCUE file into CMG GEM for dynamic reactive transport simulation. The base-case scenario involved injection of CO₂ at 15 MMScf/day for one year, followed by 199 years of post-injection …