Digital Commons Network^™

Cultural Perceptions And Willingness Or Reluctance To Use Ai Chatbots For Emotional Support By International African Students In Higher Educational Institutions In The United States, Zakariah Issah

Graduate Theses, Dissertations, and Problem Reports (ETD)

The increasing use of artificial intelligence (AI) chatbots for emotional support underscores the need to understand how cultural perceptions shape their adoption among international African students in higher education institutions in the United States. Guided by the Technology Acceptance Model (TAM) and Social Stigma Theory, this qualitative study explored the perceptions, motivations, and barriers influencing the use of AI chatbots for emotional support. Semi-structured interviews were conducted with 20 undergraduate and graduate students from 10 African countries. The findings reveal that participants viewed AI chatbots as conditional and situational sources of emotional support rather than replacements for human relationships. Convenience, …

Innovative Strategies For Stabilizing Zinc Anodes: From Molecular Design To Practical Zinc-Ion Batteries, Nhat Anh Thi Thieu

Graduate Theses, Dissertations, and Problem Reports (ETD)

Aqueous zinc-ion batteries (AZIBs) have become increasingly attractive as grid-scale energy storage solutions due to their safety, low cost, and environmental friendliness. However, the anode-electrolyte interface in AZIBs is prone to instability due to severe dendrite growth, self-corrosion, parasitic water-induced side reactions, and hydrogen evolution reactions (HER), which collectively lead to poor cyclability. To date, various interfacial engineering strategies have been investigated to address these challenges and improve the stability of Zn metal anodes. This dissertation presents a unified strategy for regulating Zn deposition through synergistic electrode and electrolyte design in laboratory-scale coin cells and then applies these concepts to …

Dielectrophoretic Biomarkers For Cancer Detection And Cell Analysis: Integrating Microfluidics And Ai, Raphael Olumide Oladokun

Graduate Theses, Dissertations, and Problem Reports (ETD)

Pancreatic ductal adenocarcinoma (PDAC) carries a five-year survival rate of 13%, driven largely by late-stage diagnosis and the absence of sensitive noninvasive screening tools. Current diagnostic methods lack the sensitivity to detect disease-associated systemic changes at early and precancerous stages, representing a critical clinical gap. This dissertation addresses the central hypothesis that PDAC and its pathological subtypes induce measurable, disease-associated electrophysiological changes in circulating PBMCs that can serve as correlative liquid-biopsy biomarkers. To test this hypothesis, this work asks: can dielectrophoresis (DEP), impedance and zeta potential analysis with AI-assisted classification distinguish benign pancreatic conditions (non-malignant control), precancerous lesions (primarily IPMNs), …

Development And Validation Of A Multi-Output Neural Network-Based Virtual Temperature Sensor For Electric Vehicle Thermal Management, Dalton Michael Wiggins

Graduate Theses, Dissertations, and Problem Reports (ETD)

Battery electric vehicles (BEVs) rely on accurate thermal management to ensure component performance, efficiency, safety, and long-term durability. Critical propulsion system components, including electric motors and high-voltage battery packs, are commonly monitored using physical temperature sensors. However, these sensors increase system cost, introduce additional hardware complexity, and may be impractical for directly measuring temperatures at critical internal locations. Virtual temperature sensors (VTSs) provide a software-based alternative by estimating component temperatures using readily available vehicle operating data.

This research presents the development and validation of a long short-term memory (LSTM) neural network-based virtual temperature sensor capable of simultaneously estimating the motor …

Evaluation Of Engineering Controls In Mitigation Of Fecal And Chloride Contamination To An Urban Stream, Gabriel J. Zenny

Graduate Theses, Dissertations, and Problem Reports (ETD)

Fecal coliform contamination is a major contributor to surface water pollution in the United States’ (U.S.) waterways, whether from combined sewer overflows (CSOs) (point source pollution), runoff from precipitation and snowmelt (nonpoint source pollution), or exfiltration from aging and failing infrastructure. In addition to fecal bacteria, chloride contamination is also a major, prevalent surface water contaminant impacting U.S. waterways. Chloride contamination is predominantly released into U.S. waterways as nonpoint source pollution, endemic to northern areas that use industrial brine and salt as a form of mitigation for ice accumulation on roadways. The purpose of this research was to investigate impairment …

Semantic-Weighted Lidar–Camera Slam For Robust Mapping In Vegetation-Rich Environments, David Aigbovboise Akhihiero

Graduate Theses, Dissertations, and Problem Reports (ETD)

Many LiDAR odometry and SLAM methods are lightweight and effective, but they assume that all LiDAR point returns are equally reliable. In practice, this assumption is often violated in vegetation rich or semi transparent environments, where in a single beam footprint, LiDAR beams may intersect multiple scattering surfaces like leaves, branches or glass. These ambiguities in returns produces probabilistic or biased range measurements that violate the assumptions of most geometric registration frameworks and can lead to drift and inconsistency.

To address this challenge, this dissertation proposes a semantic-weighted LiDAR-camera SLAM framework that integrates class dependent weights into a front-end LiDAR …

Elucidating Structure–Reactivity Relationships In Ni-Catalyzed Co2 Methanation, Majed Alam Abir

Graduate Theses, Dissertations, and Problem Reports (ETD)

The catalytic hydrogenation of carbon dioxide (CO₂) to methane represents a promising strategy for carbon utilization and renewable energy storage within power-to-gas systems. When coupled with hydrogen derived from renewable electricity, CO₂ methanation enables the conversion of intermittent energy sources into storable and transportable chemical fuels compatible with existing natural gas infrastructure. Nickel-based catalysts have emerged as leading candidates for this reaction due to their high activity towards CO₂ methanation, abundance, and cost. However, the performance and long-term stability of Ni catalysts are strongly influenced by catalyst support properties, Ni nanoparticle size, and promoter effect, and …

Multimodal Representation Learning For Face Understanding: From Caption Supervision To Foundation Model Adaptation, Md Mahedi Hasan

Graduate Theses, Dissertations, and Problem Reports (ETD)

The rapid advancement of intelligent surveillance systems and the increasing demand for reliable biometric identification in border security, public safety, and digital forensics require robust face understanding under unconstrained conditions, including low resolution, pose variation, and occlusion. While Vision Transformer (ViT)-based foundation models have greatly improved visual representation learning, their patch-based tokenization and lack of spatial inductive bias limit their ability to capture fine-grained details in low-resolution inputs. This dissertation investigates multimodal representation learning for face understanding through natural language supervision, large-scale face-caption pre-training, and parameter-efficient foundation model adaptation. It hypothesizes that textual supervision provides complementary semantic cues that improve …

Multi-Timescale Monitoring And Modeling For Resilient Smart Grids: Pmu Anomaly Detection And Battery Digital Twins, Muhammad Imran Hossain

Graduate Theses, Dissertations, and Problem Reports (ETD)

Modern power systems face failures at very different timescales. Cyber-physical disturbances may emerge within seconds, while battery degradation develops over hundreds of operating cycles. Both monitoring problems share the same underlying difficulty: power systems produce measurement data in abundance, but reliably labeled examples of abnormal or degraded operation are scarce. Rare grid events are difficult to label, and battery degradation data are heterogeneous across cells, cycling protocols, and chemistries. This thesis addresses these challenges through two complementary domain-informed learning frameworks that constrain representation learning using information specific to each physical problem.

First, at the system level, T-BiGAN, a Transformer-augmented bidirectional …

Development Of Novel Methods For Investigative Leads In Firearm And Explosive Related Incidents, Addio Joseph Fiordigigli Jr.

Graduate Theses, Dissertations, and Problem Reports (ETD)

Criminal outbreaks and gun violence persist as a multifaceted global crisis, marked by escalating rates of homicide, suicide, and terrorism that destabilize communities and strain public resources. The proliferation of illicit firearms and homemade explosive devices, along with the complexity of modern criminal networks, necessitates innovative scientific tools to strengthen preventive intelligence operations and ensure that the legal process is grounded in physical evidence. More efficient detection of traces left behind at a crime scene can help prevent further harm or injury from follow-up attacks. This study aims to develop and evaluate new triage methods for characterizing gunshot residues (GSR) …

Optimization Of The Cmc Algorithm, Christopher Joseph Moner

Graduate Theses, Dissertations, and Problem Reports (ETD)

Cartridge cases recovered from discharged firearms contain tool marks produced by the internal mechanisms of said firearm. Firearm and tool mark examiners com pare these marks to determine whether two cartridge cases originated from the same firearm. Traditional comparison methods have been criticized for their subjective nature and reliance on examiner interpretation rather than objective decision thresholds. The Congruent Matching Cells (CMC) algorithm was developed as a quantitative, objective method for tool mark comparison. CMC is a surface topography correlation algorithm that partitions a tool mark into small regions, or cells, and evaluates their similarity using the areal cross-correlation function …

Student Support In Civil And Environmental Engineering, Heather Marie Rice

Graduate Theses, Dissertations, and Problem Reports (ETD)

Many student support services target first-year engineering students to help improve their transition from high school to college and to reach first-year retention goals. These opportunities are communicated to students through a variety of ways. The objectives of this work are to evaluate student perspectives of student services support factors in a civil and environmental engineering program and investigate how student support services and opportunities are communicated to students in a civil and environmental engineering program. The media identified for student support service outreach were the fundamentals of engineering program newsletters, academic advising newsletters, Statler eNews newsletters, and the bulletin …

Global Weak Solutions Of Optical Variational Wave System, Shahrazad Hamed Alnafie

Graduate Theses, Dissertations, and Problem Reports (ETD)

The coupling of a variational wave equation with Maxwell’s equations gives rise to the optical variational wave system, a hyperbolic PDE system that models the director field of the nematic liquid crystals. This system presents unique analytical challenges that have not been addressed in the existing literature. In this dissertation, we study the one-dimensional case of this system.

We establish the global existence of conservative weak solutions to the associated Cauchy problem. The hyperbolic system is derived using the energy variational method. Through a sequence of suitable coordinate transformations, we reformulate the system while preserving its hyperbolicity. Due to degeneracy …

Exploring Chinese Students’ Lived Experiences And Perceived Development In A Structured Cross-Cultural International Collaborative Degree Program: A Qualitative Case Study In The Context Of The Wvu–Tufe 3+1 Collaborative Program, Zhongmin Zhao

Graduate Theses, Dissertations, and Problem Reports (ETD)

The purpose of this qualitative case study is to examine the lived experiences and perceived development of Chinese students within the structured 3+1 cross-cultural international collaborative program. Grounded in Schlossberg’s Transition Theory and Chickering’s Seven Vectors of Identity Development Framework and guided by the four theoretical propositions, this study explores how the Chinese students experience the challenging transition from their home institution to the host institution, how the students participating in the program perceive their developmental growth across multiple developmental dimensions, and how the students perceive the program structures and institutional practices as supporting or hindering their development.

Data were …

Resilience And Reactivity: The Relation Between John Henryism And Cardiovascular Responses To Laboratory Stressors In An Appalachian Sample, Emma Raycher Thompson

Graduate Theses, Dissertations, and Problem Reports (ETD)

John Henryism active coping (JHAC), named for folk hero John Henry, is defined as the perception that one can overcome stressors through hard work (James et al., 1983). This construct has been tied to numerous health outcomes, showing a negative influence on cardiovascular health (Bennett et al., 2004). Many researchers have examined the relation between JHAC and cardiovascular reactivity to stress, though findings are mixed. Further, despite the legend of John Henry occurring in Appalachia, and traits associated with John Henryism, such as resilience, being prominent within this region, no study has examined the relation between JHAC and reactivity in …

Conservative Discourse: How It Shapes And Is Shaped By Social Studies Education In West Virginia, Elizabeth Christine Rexroad

Graduate Theses, Dissertations, and Problem Reports (ETD)

This narrative inquiry dissertation investigates how conservative Discourse both shapes and is shaped by social studies teacher identity, agency, and the figured world of social studies education in West Virginia. Drawing on the storied lives of three early-career secondary social studies teachers, this study examines how conservative Discourse operates as a structuring force in the daily lives and practices of teachers working in an exceptionally conservative political and social landscape. Using Critical Narrative Analysis (Souto-Manning, 2014) and discourse analysis (Gee, 2014) as analytical frameworks, and figured worlds theory (Holland et al., 1998) as theoretical lens, this study reveals how conservative …

Ai-Based Smart Proxy Models For Flow Assurance, Integrating Oil Rate Prediction, Pipeline Monitoring, And Leak Detection, Ali Sajedian

Graduate Theses, Dissertations, and Problem Reports (ETD)

Oil and gas pipeline networks operate under complex multiphase flow conditions and dynamic transient regimes that present significant challenges for traditional monitoring, anomaly detection, and operational decision-making methodologies. Many existing monitoring approaches rely on high-fidelity physics-based transient flow simulations to accurately represent system behavior. However, these models are computationally intensive and therefore difficult to implement in real-time operational environments.

This dissertation presents a physics-guided artificial intelligence framework for intelligent pipeline monitoring and integrity management based on the concept of Smart Proxy Modeling. By integrating first principles engineering knowledge with machine learning techniques, the proposed framework develops computationally efficient surrogate models …

Revival Through Resilience In The Post-Mined Landscape: Demonstrating The Socio-Economic Context Of Appalachia And Exploring How Community Infrastructure And Cultural Tourism Can Be Catalysts For Economic Regeneration In Appalachian Communities, Azita Tasnim Ritu

Graduate Theses, Dissertations, and Problem Reports (ETD)

Post-industrial communities across Appalachia continue to experience economic and environmental challenges following the decline of coal mining and related industries. Towns such as Smithers and Montgomery, West Virginia, reflect these conditions through economic stagnation, population loss, aging infrastructure, and degraded landscapes, creating an urgent need for sustainable redevelopment strategies.

The Appalachian Regional Commission emphasizes economic diversification, infrastructure investment, and community revitalization as critical components for improving regional quality of life. However, many former mining communities continue to struggle with underutilized heritage assets, degraded landscapes, and limited economic alternatives. Cultural landscapes and local identity remain significant but often overlooked resources that …

Studying The Mechanism For Ricin-Induced Growth Suppression, Daniel Judge

Graduate Theses, Dissertations, and Problem Reports (ETD)

This study focuses on ribosome-inactivating proteins (RIPs), a class of potent toxins that includes ricin, α-sarcin, and shiga toxin, which irreversibly damage large subunit rRNA. Although the catalytic activity of ricin toxin A chain (RTA) is well characterized, the precise mechanisms linking ribosome damage to altered cellular morphology remain poorly understood. In this study, we engineered a tetracycline-regulatable expression system to express RTA in Saccharomyces cerevisiae. We characterized the effects of RTA expression on yeast growth, viability, and reproductive potential. We demonstrated that our expression system produced rapid and robust RTA expression and ribosome depurination within less than one …

Evaluation Of Acid Mine Drainage Treatment In The Upper Deckers Creek Watershed, Sarah E. Nelson

Graduate Theses, Dissertations, and Problem Reports (ETD)

Acid mine drainage (AMD) is a legacy contaminant, impairing Appalachian watersheds despite decades of regulatory work and investment in remediation. This study analyzes and evaluates the performance of seven AMD treatment systems (5 passive and 2 active) as well as thirteen untreated sources in the headwaters of Deckers Creek. Monthly influent and effluent samples measuring pH, major metals, and acidity were collected from January 2024 through 2026 to assess variability in treatment performance, and engineering site visits were conducted for each treatment system. Based on these two components, recommendations customized for each individual treatment system were made, and the implementation …

Plant-Wide Process Modeling, Techno-Economic Optimization, And Bayesian Uncertainty Quantification For Manufacturing Value-Added Products From Lignocellulosic Biomass, Poulomi Das

Graduate Theses, Dissertations, and Problem Reports (ETD)

For decades, many chemicals have been produced from fossil resources, contributing to resource depletion, pollution from extraction and refining, and hazardous byproducts. Growing environmental concerns and declining fossil reserves have intensified the search for sustainable sources of fuels, energy, and chemicals. Lignocellulosic biomass, the only abundant renewable carbon source, is therefore being explored as a feedstock for second-generation biofuels and high-value chemicals.

Currently, global wood-panel industry heavily depends on petroleum-derived commercial adhesives like phenol-formaldehyde, urea-formaldehyde, etc. These formaldehyde-based chemicals cause hazards to both human health and environment through emission of toxic volatile organic compounds. Typically, lignin is considered as one …

Landscape As Expo: Reimagining Desert Landscapes As Climate-Adaptive Cultural Infrastructure In Las Vegas, Parinaz Baradaran Anaraki

Graduate Theses, Dissertations, and Problem Reports (ETD)

Contemporary desert cities face increasing environmental and social challenges driven by climate change, including extreme heat, water scarcity, fragmented ecological systems, and limited access to high-quality public open space. In many rapidly urbanizing regions, conventional urban development has marginalized desert landscapes, treating them as vacant land rather than valuable ecological and cultural assets. This thesis proposes Landscape as Expo as a new framework for transforming desert landscapes into climate-adaptive cultural infrastructure, where ecological processes become both functional systems and public experiences.

The project focuses on a 140-acre site within the Tule Springs Planning District in North Las Vegas, Nevada, identified …

Hyperglycemia Detection From Single-Lead Ecg Using A Hybrid Cnn & Transformer Model, Adam Ayomikun Ogunjembola

Graduate Theses, Dissertations, and Problem Reports (ETD)

Diabetes Mellitus is known as high blood glucose. This high blood glucose level happens when the body has a problem with producing or using insulin. Insulin is a very important hormone that the pancreas makes to control how much glucose gets into the bloodstream and cells. Diabetes Mellitus has an effect on the body if it is not treated, such as damaging the blood vessels and nerves which can lead to stroke, kidney failure, heart attack and permanent loss of vision. Since people with diabetes need to measure their glucose levels in order to determine how much insulin or medicine …

Computer Vision Methods For Rfi Segmentation In Radio Astronomy, Yechan Kweon

Graduate Theses, Dissertations, and Problem Reports (ETD)

Radio Frequency Interference (RFI) increasingly contaminates the radio astronomy spectrum, often exceeding astronomical signal amplitudes by 50–70 dB. Reliable detection and mitigation are therefore essential for studies of faint transient phenomena such as pulsars and fast radio bursts (FRBs). Existing practical methods including Spectral Kurtosis (SK), Median Absolute Deviation (MAD), and SumThreshold perform well in many settings but depend on assumptions about the RFI environment and data statistics, limiting their effectiveness for weak, broadband, or nonstationary interference.

We develop a transform based RFI detection method that requires no prior knowledge of the RFI origin or type. The method operates on …

Architecture And Mechanistic Engineering Of Nanocomposite Steam Electrodes For High-Performance Metal-Supported Protonic Ceramic Cells, Xuemei Li

Graduate Theses, Dissertations, and Problem Reports (ETD)

The advancement of proton-conducting ceramic cells (PCCs) is crucial for efficient energy conversion in hydrogen- and/or ammonia-based energy carrier systems. However, a bigger success requires significant progress in cell fabrication, interfacial stability, fast electrode kinetics, and high Faradaic efficiency. This study investigates the rational design, fabrication, and performance breakthroughs of PCCs, with a focus on electrode architecture engineering, material interfacial coupling, and mechanistic understanding of electrochemical processes.

The metal-supported fuel electrode structure of PCFCs was systematically optimized, revealing the significant influence of Ni diffusion on cell performance and durability. High power density and stable ammonia-fueled operation were achieved. A heterointerface-rich …

Dataless Neural Networks For Boolean Satisfiability And Network Optimization, Andrew Evan Gautier

Graduate Theses, Dissertations, and Problem Reports (ETD)

Combinatorial optimization problems (COPs) require searching over a finite solution space subject to constraints, with the goal of satisfying an objective function. They arise in operations research, scheduling, resource allocation, circuit design, and many other fields. Many problems in combinatorial optimization (including satisfiability and network design) are NP-hard. Traditionally, researchers have built approximate solvers that return near- optimal solutions efficiently by developing increasingly sophisticated heuristics and meta- heuristics. Deep learning has provided new opportunities for improving combinatorial solvers by leveraging neural guidance to prune the search space. Traditional neural networks have distinct drawbacks in this context: separate training and …

Comparing Unet And Hrnet For Geomorphic Feature Extraction From Digital Terrain Model-Derived Land Surface Parameters, Behnam Solouki

Graduate Theses, Dissertations, and Problem Reports (ETD)

Automated extraction of geomorphic features from high spatial resolution terrain data is important for environmental monitoring, geohazard assessment, and landscape change analysis. This study compares two convolutional neural network architectures, UNet and High-Resolution Network (HRNet), for semantic segmentation of mine benches and sinkholes from lidar-derived digital terrain models and land surface parameters. Mine benches represent anthropogenic, elongated, stepped landforms associated with historic surface mining, whereas sinkholes are natural, compact depressions common in karst terrain. Three terrain-derived input layers were used: square-root-transformed slope, broad-scale topographic position index, and fine-scale annulus topographic position index. Models were trained using five training sample sizes, …

Physics-Informed Machine Learning Methods To Predict Heavy-Duty Diesel Engine Performance And Emissions, Sandeep Guguloth

Graduate Theses, Dissertations, and Problem Reports (ETD)

The development of internal combustion engines for increased efficiency and reduced emissions demands improved design tools that are cost-effective, fast, and easy to integrate into existing engineering workflows. Low-dimensional physically based engine models serve this role by reducing the need for iterative experimental prototyping but historically rely on empirical correlations that sacrifice fidelity compared to CFD. Machine learning (ML) approaches, conversely, achieve high predictive accuracy but lack interpretability and generalize poorly beyond their training data. Physics-informed machine learning (PIML) bridges this gap by constraining the solution space to physically feasible predictions, offering a more reliable way to model in-cylinder phenomena. …

Smartbot V3: A Scalable Educational And Research Robotics Platform And Decentralized Construction Framework, Robert Tyler Cook

Graduate Theses, Dissertations, and Problem Reports (ETD)

Autonomous robotic systems are increasingly used in both engineering education and robotics research, creating a need for systems capable of supporting both within a common platform. This thesis presents SMARTbot V3, a scalable robotics platform developed to support undergraduate robotics education and multi-robot research.

SMARTbot V3 is a differential-drive mobile manipulator incorporating a 3-degree-of-freedom manipulator, LiDAR, RGB cameras, onboard computation, and Robot Operating System 2 (ROS2) software. The platform was designed to support scalable deployment through standardized hardware, modular construction, and common software. A fleet of twenty robots was manufactured and deployed for both educational and research activities. Educational validation …

Data Augmentation And The Reliability Of Conformal Prediction For Uncertainty Quantification In Medical Imaging, Rizwan Ahamed

Graduate Theses, Dissertations, and Problem Reports (ETD)

The safe clinical deployment of deep learning models for high-stakes medical imaging tasks requires more than high average accuracy; it requires demonstrable, per-case reliability. Uncertainty quantification (UQ) provides the missing signal that tells a clinician when a model prediction can be trusted and when a case should be escalated for expert review. Among UQ approaches, conformal prediction (CP) is especially attractive because it produces prediction sets that are guaranteed, under the assumption of exchangeability, to contain the true label with a user chosen probability, and it does so without assumptions about the model or the data distribution. This report first …