Digital Commons Network^™

A Multi-Label Computer Vision-Based Approach For Condition Assessment Of Traffic Signs: Database Compilation, Model Training, And Evaluation, Shailaja Ratna Pandey

All Graduate Theses and Dissertations, Fall 2023 to Present

Traffic signs help drivers and pedestrians to understand roadway rules, warnings, and directions, which determine how road users should behave. When signs fade or delaminate, they become harder to read and interpret, which creates increased safety hazards. Transportation agencies usually deploy engineers to the field to inspect signs because they need to evaluate and document the sign’s condition based on established standards and engineering judgment. This process requires substantial time and cost and becomes challenging to apply across large highway networks.

This study evaluated two computer vision (CV) models for automated traffic sign condition assessment using highway images collected across …

A Laboratory Investigation Of Energy Dissipators At Embankment Dams, Nathan L. Young

All Graduate Theses and Dissertations, Fall 2023 to Present

Dams play a critical role in protecting communities from flooding and providing reliable water supplies. When large amounts of water pass through a dam’s spillway during floods, the discharge can travel at high speeds and carry potentially destructive kinetic energy that can damage the dam or erode downstream channels if that energy is not properly controlled. To reduce this risk, engineers commonly use hydraulic structures called energy dissipators that slow spillway discharge and safely release it downstream.

Commonly used energy dissipators at embankment dams include stilling basins that rely on a hydraulic jump – a sudden rise in water depth …

Experimental And Numerical Investigation Of Flow Coefficients In Three-Way, T-Port, Ball Valve, Tyler A. Mindrum

All Graduate Theses and Dissertations, Fall 2023 to Present

Many systems that move fluids, like water distribution networks and heating, ventilation, and air conditioning (HVAC) systems, rely on valves to control flow. This study evaluates a three-way valve, which can direct flow in multiple directions, but has not been extensively researched. Testing included physical data collection and computer simulations to compare how the valves behaved under different valve openings and flow conditions. The results showed that computer simulations can predict the general flow behavior of three-way valves, but that physical testing is still important, especially for valves with complex internal geometries.

Cadmium Biosorption By Fusarium Venenatum And Its Application In Functional Permeable Materials For Metal Removal, Bradley Lawson

All Graduate Theses and Dissertations, Fall 2023 to Present

Heavy metals are pollutants of increasing concern as continued industrialization and urbanization have escalated the discharge of these toxins into aquatic environments. Cadmium (Cd) is a metal of particular concern due to its acute toxicity and high mobility in aquatic ecosystems. Given these characteristics Cd poses significant health risks to both humans and aquatic ecosystems. The continued development of sustainable, low-cost remediation technology is imperative to manage metal pollution.

This research explores the use of fungal-based remediation systems to remove Cd from contaminated water. Living biomass of the filamentous fungus Fusarium venenatum was evaluated as a biosorbent material for Cd …

Ai-Assisted Import Of Static Requirements Documents Into Sysml Models Using A Vibe-Coded Plugin Approach, Joshua Larson

Open Access Theses & Dissertations

Model-based systems engineering (MBSE) promises a single authoritative model in place of static documents, but the translation of requirements documents into that model remains manual, slow, and dependent on scarce modeling expertise. This thesis asks whether an AI-assisted workflow can automate that translation, and whether the tooling itself can be built by vibe coding, in which a practitioner directs an AI in natural language rather than writing code directly. The result is a plugin for Magic Systems of Systems Architect (MSoSA) 2022x that reads a PDF requirements document, extracts requirements through the Anthropic Claude API, and generates a SysML model …

Prevention Vs Detection: A Discrete-Event Simulation Assessment Of Inspection Staffing, Pick-To-Light, And Ai-Based Inspection In Aerospace Wire Harness Kitting, Jorge Mares

Open Access Theses & Dissertations

Aerospace wire harness manufacturing operates under conditions that standard industrial engineering methods were not designed to address. Volumes are low, configurations change between orders, assembly is performed manually by certified labor that cannot be expanded quickly, and IPC/WHMA-A-620 Class 3 acceptance requires that every unit be verified rather than sampled. Kit assembly concentrates the resulting risk, because each item retrieved from the rack is an independent selection decision, and the attributes distinguishing a correct item from an incorrect one are frequently not visible to the operator. Errors introduced there are discovered downstream, after substantial certified labor has been invested. A …

Unsupervised Learning For Minimum Error Adaptive Sampling Of Atmospheric Vertical Temperature Profiles, Alejandro Medina

Open Access Theses & Dissertations

Uncrewed aerial systems (UAS) collect atmospheric data on fixed schedules, and endurance limits make blind searching costly. This thesis develops an unsupervised representation that summarizes a multi-decade radiosonde archive into a compact library of atmospheric states, giving a UAS an expectation of the column before it flies. The method standardizes both axes of a profile against the sounding's own surface conditions, which makes the representation independent of season and of station elevation. Applied to 27,270 soundings from Norman, Oklahoma, over the lowest 1.5 km of the atmosphere, 12 representative profiles reconstruct the record to within 1.0 °C of mean absolute …

From Screening To Risk: Assessment Of Potentially Toxic Elements In Children's Toys Along The El Paso, Tx, U.S.A.-Ciudad Juarez, Chih, Mex Border Region, Jesus Rodriguez-Loya

Open Access Theses & Dissertations

Children are uniquely vulnerable to potentially toxic elements (PTEs), absorbing them more readily than adults and encountering them through the hand-to-mouth behaviors of early childhood. Exposure carries element-specific consequences: lead (Pb) impairs cognitive development with no established safe threshold; cadmium (Cd) damages the kidneys and reduces bone mineralization; arsenic (As) is a recognized carcinogen and developmental neurotoxicant; hexavalent chromium (Cr) is carcinogenic and induces allergic dermatitis; nickel (Ni) is the leading cause of allergic contact dermatitis in children; and excess zinc (Zn) disrupts copper absorption and causes gastrointestinal distress. Toys are a distinctive source of such exposure, yet none had …

Integrated Framework For Tsn-Enabled Ot Networks And Scalable Edge Computing To Enable Real-Time Feedback Loop, Taposh Kumer Sarker

Open Access Theses & Dissertations

The advent of Industry 5.0 envisions smart manufacturing characterized by human centricity, sustainability, and systemic resilience. Realizing this vision requires the seamless convergence of Information Technology (IT) and Operational Technology (OT) networks. However, integrating massive, stochastic IT edge computing workloads with deterministic physical control loops introduces severe architectural friction, inherently threatening the safety guarantees required by industrial machinery. To resolve this fundamental incompatibility, this dissertation proposes the Edge-Augmented Real-Time Industrial Control System (EA-RICS).

EA-RICS is a comprehensive, multi-layered architecture designed to dismantle systemic bottlenecks across the physical data plane, the centralized control plane, and the edge operating system. First, the …

Secure And Compassionate Dementia Care: Non-Intrusive Remote Monitoring Of Falls, Wandering, And Agitation, Awan-Ur- Rahman

Master's Theses

Alzheimer’s disease and related dementias (ADRD) present significant safety challenges, as affected individuals may experience falls, wandering, agitation, and a progressive decline in independence. Although continuous monitoring can enable timely intervention, many existing systems rely on cameras or wearable devices, which may introduce concerns related to privacy, comfort, and sustained use. This thesis explores privacy-preserving and non-intrusive remote monitoring through two complementary studies. The first study presents an ambient Wi-Fi channel state information framework for recognizing agitation and eight daily activities. The proposed approach translates behavioral and physiological markers commonly captured by wearable sensors into the Wi-Fi sensing domain. The …

Constructing Female High School Students’ Stem Self-Efficacy: The Role Of High School Stem Research Experiences, Hyunjin Son

Dissertations

In the U.S., nearly a quarter of the workforce is employed in Science, Technology, Engineering, and Mathematics (STEM) occupations. However, the STEM workforce lacks diversity, limiting perspectives to address real-world problems facing society. While many factors influence decisions to pursue STEM majors in college and enter the STEM workforce, one factor commonly associated with performance and persistence in STEM is STEM self-efficacy. Independent research experiences have been shown to increase conceptual understanding and confidence in STEM, leading to STEM degrees and careers. As high school co-curricular STEM research opportunities become more common, the effects of such experiences on students’ STEM …

Machine Learning For Predictive Energy And Emissions Modeling Of Vehicles And Power Grids In The United States, S M Tanvir Faysal Alam Chowdhoury

Dissertations

The environmental benefits of electric vehicle (EV) adoption depend on more than replacing internal combustion engine vehicles with electric powertrains. EV adoption reshapes electricity demand, interacts with regional generation mixes, and influences travel behavior and congestion, creating a coupled transportation-energy system in which vehicle and power-plant emissions must be evaluated together. This dissertation develops machine-learning frameworks for predicting energy consumption and emissions from vehicles and power grids under rising EV adoption. The first component forecasts grid emissions from EV charging. Using simulation data from NREL's Cambium database, a Prophet-based time-series framework predicts carbon dioxide, nitrous oxide, and methane emission rates …

Evaluating Echo2 Biochar As Sustainable Bitumen Binder Modifier In Road Pavements: High-Temperature Performance Characterisation, Adeel Iqbal, Nuha S. Mashaan, Themelina Paraskeva, Mohamed A. Shahin

Research outputs 2022 to 2026

The incorporation of bio-derived modifiers in bitumen binders presents a practical pathway toward sustainable, carbon-sequestering road pavement infrastructure. This study evaluates commercially produced ECHO2 softwood biochar as a modifier for Australian viscosity-graded C170 bitumen, combining microstructural, thermal, physical, and rheological characterization to assess its suitability as a high-temperature reinforcing modifier. In this study, biochar was incorporated at 3%, 6%, 9%, and 12% by weight, utilizing particles smaller than 75 µm to maximize interfacial interaction. Characterization via SEM-EDS, XRD, and TGA revealed a highly stable, carbon-rich, amorphous material with a rough, porous morphology, favourable for physical interlocking with the bitumen matrix. …

Optimizing Few-Shot Learning In Pruned Large Language Models With Task-Specific Prompts, Danyal Aftab

Dissertations

Few-shot learning enables large language models to efficiently perform tasks given only a limited number of labeled examples. However, training these models entirely from scratch requires substantial computational resources, making it challenging for many organizations to fully leverage their potential. This thesis explores how structured pruning, task-specific prompting, and parameter-efficient fine-tuning can be combined to preserve few-shot learning capabilities in compressed LLMs, while also extending their utility to real-world recommendation systems.

In this research, we propose the Tailored LLM framework, which first reduces model size through structured pruning and then enhances few-shot learning performance using carefully designed prompts. We experiment …

Policy And Regulation In Virtual Power Plants Development, Hemlal Bhattarai, Aziz, Stefan Lachowicz

Research outputs 2022 to 2026

Electricity systems are changing due to the rapid deployment of distributed energy resources (DER), which also presents significant regulatory obstacles to their coordinated integration into energy markets and power grids. However, the majority of current material in publications concentrate on operational optimization and technical architectures, with little systematic synthesis of the legal and policy frameworks governing the deployment of VPP on a broad scale. To provide grid services, improve flexibility and support decarbonization objectives, virtual power plants (VPP) have become a crucial aggregation method. To close this gap, this research critically looks at the institutional roles, market structures, global policy …

Automated Battery Management Systems For Electric Vehicles, Woonki Na, Yuanyuan Xie

Mineta Transportation Institute

Electric vehicle (EV) safety, efficiency, and lifetime are strongly influenced by how well battery cells are managed, and as EV adoption accelerates, improving battery performance has become critical to vehicle reliability, cost, and public trust. This report conducts a field study on the core technologies and challenges in Battery Management Systems (BMS), focusing on the classification of BMS circuit topologies (design/structures) and systematically reviewing different topologies of active cell balancing circuits (systems that move energy from stronger battery cells to weaker ones). The study provides a detailed analysis of the working principles, advantages, and disadvantages of various active balancing circuit …

Extended Adaptive Oscillator Framework For Gait Phase Estimation With Adaptive Coupling And Transition Detection Across Locomotion Tasks, Nikhila Radha Krishnan

All Theses

Gait phase is a human-inspired physical variable that describes the instantaneous position of a person within a gait cycle. Adaptive oscillators have been widely used for gait phase estimation due to their ability to synchronize with periodic and pseudo-periodic biomechanical signals and generate monotonically increasing cyclic phase values. Typically, the performance of adaptive oscillators is strongly influenced by coupling strength, a parameter that bridges a trade-off between convergence speed and steady-state variability of the estimated stride frequency. In gait assistive applications, stride frequency estimation must be sufficiently fast to enable phase-based assistance while achieving a stable stride frequency estimate. The …

Drones In Wildfire Airspace Management: Developing A Scalable Framework For Mid-Sized Cities, Victoria Denise Tanner Williamson

Engineering Management & Systems Engineering Theses & Dissertations

Wildfires are becoming increasingly frequent and severe, creating growing risks for mid-sized communities with limited emergency response resources. The January 2025 Los Angeles wildfires—which burned more than 57,000 acres and destroyed over 18,000 structures—underscore the urgent need to strengthen wildfire response strategies through the integration of unmanned aerial systems (UAS) (Hardy, 2025).

This study develops a scalable framework for drone-assisted wildfire response in resource-constrained environments. Using the city of Waynesboro, Virginia, as a case study, the research examines how mid-sized jurisdictions can integrate unmanned aerial vehicles (UAVs) to improve preparedness, response, and recovery. A three-round, mixed-methods Delphi study engages emergency …

Enhancing Stem Education With Modeling, Simulation, And Ai Technologies: From Virtual Laboratories To Intelligent Teaching Assistants, Yiyang Li

Electrical & Computer Engineering Theses & Dissertations

Rapid advancements in modeling and simulation (M&S) and artificial intelligence (AI) present new opportunities to enhance various aspects of STEM education, from virtual laboratories that simulate physical lab environments in software to intelligent teaching assistants that provide on-demand, curriculum-aligned instructional support. Virtual laboratories offer a potential solution to the access and scalability challenges of laboratory courses by allowing students to conduct experiments without physical equipment or geographical constraints. AI-powered teaching assistants, particularly those grounded in course-specific materials, can help mitigate the instructional support gap that arises when students work independently in digital learning environments. This dissertation presents three-phase research into …

Modeling And Generating Crash Avoidance Behaviors In Safety-Critical Vehicle–Pedestrian Interactions Using Deep Reinforcement Learning, Qingwen Pu

Civil & Environmental Engineering Theses & Dissertations

Traffic crashes between vehicles and pedestrians arise from complex, split-second interactions in which both parties make rapid evasive decisions. Four fundamental gaps persist in existing research. Surrogate safety measures assume linear trajectories, failing to capture the curved movements of turning vehicles and crossing pedestrians at intersections. Single-agent modeling treats one party as a fixed obstacle, ignoring the joint decision-making that governs near-miss outcomes. The effect of vehicle type on pedestrian avoidance behavior—whether pedestrians respond differently to automated vehicles (AVs) than to human-driven vehicles (HDVs)—remains poorly understood. Finally, automated driving system development is hampered by a severe scarcity of large-scale, behaviorally …

Experimental Investigation Of The Discharge Modes Of Nanosecond Pulsed Plasmas At Atmospheric Pressure, Md Ziaur Rahman

Electrical & Computer Engineering Theses & Dissertations

The generation of repeatable and stable nanosecond pulsed atmospheric pressure plasmas is important to non-thermal plasma applications in various fields including medicine, material processing, food processing, and plasma ignition for combustion. This dissertation investigates the atmospheric pressure plasma initiation and formation under 10 – 200 ns pulsed power for electrode configurations applicable for transient plasma ignition (TPI) for combustion. The impacts of pulsed power parameters, gas condition, and electrode geometry on the discharge initiation and modes (i.e., streamer, transient spark and spark) are systematically evaluated for applying TPI for combustion. We evaluated the discharge modes driven by both longer and …

Structure Meets Context: A Simulation Study Of Centralized And Decentralized Decision-Making In Complex Environments, Murat Balci

Engineering Management & Systems Engineering Theses & Dissertations

The question of when to centralize or decentralize decision-making authority is a foundational problem in organizational theory and management science. Yet existing research often favors decentralized structures, frequently treating them as universally superior, and provides limited guidance on when centralization may be more effective. Leaning toward decentralization without thoroughly exploring options leaves organizational designers without clear direction under varying environmental conditions. This study addresses that gap by developing and applying a simulation-based framework to evaluate the context-dependent effectiveness of centralized and decentralized decision-making structures.

Drawing on contingency theory and decision science, the study conceptualizes environmental complexity along two dimensions: dynamism …

Reinforcement Learning For Cathode Material Design Through Sequential Decision-Making Frameworks, Taimoor Muzaffar Gondal, Muhammad Qasim, Yasir Arafat

Research outputs 2022 to 2026

The cathode material design is a persistent challenge in the development of next-generation rechargeable batteries. The cathode performance is critically influenced by certain key parameters, i.e., composition, crystal structures, ion transport, and degradation behaviour. Moreover, techno-economic and sustainable considerations also play a pivotal role in the viable cathode material design. In recent years, the integration of static machine learning models with conventional experimental techniques has significantly enhanced the cathode material design. However, the sequential nature of cathode discovery has not been fully captured by these techniques as they do not update their decision strategy based on prior outcomes. In this …

Human-Centered Electric Vehicle Adoption Framework For Smart Mobility: Modeling Perceived Range And Charging Anxiety As A Psychological Barrier, Fatemeh Nazari, Abolfazl (Kouros) Mohammadian, Thomas Stephens

Civil Engineering Faculty Publications

Electric vehicles (EVs) offer a transformative pathway toward reducing the environmental, economic, and health-related externalities of internal combustion engine vehicles in urban settings. Despite substantial advances in battery technology, charging infrastructure expansion, and supportive policy incentives, EV penetration remains limited which poses challenges for smart and sustainable mobility planning. A critical yet insufficiently modeled barrier to adoption lies in the psychological perceptions surrounding electric driving range and charging reliability, which is commonly framed as “range anxiety,” but more broadly reflecting perceived range and charging anxiety. To address this gap, this study introduces a latent psychological construct capturing individuals’ perceived range …

Genwriter 2.0: A Hybrid Case-Based And Llm Rewriting Approach For Mitigating Implicit Gender Cues In Text, Shweta Soundararajan, Sarah Jane Delany

Conference papers

Gendered language is the use of words or phrases that indicate an individual's gender. Although useful in some contexts, gendered language can reinforce gender stereotypes and introduce bias, particularly in machine learning models for tasks involving people such as recruitment or occupation classification. When textual content about individuals, such as biographies, contain gender cues, models can learn spurious associations between gender and other characteristics of individuals, such as profession, potentially resulting in unfair outcomes such as reduced hiring opportunities for women.

To address this challenge, we propose GenWriter 2.0, a hybrid approach that integrates Case-Based Reasoning (CBR) with Large …

Experimental And Molecular Dynamic Simulation Assessment Of H2/Brine/Cement Interfacial Interactions During Underground Hydrogen Storage, Nurudeen Yekeen, Sikiru, Ahmed Al-Yaseri, Berihun Mamo Negash

Research outputs 2022 to 2026

Cement is widely used as a structural and sealing material to ensure hydrogen containment in geological formations. However, the influence of H2–brine–cement wettability and H2–brine interfacial tension (IFT) on the integrity and sealing efficiency of cemented caprocks remains poorly understood. Furthermore, previous studies provide limited insights into hydrogen adsorption and sorption behavior under subsurface storage conditions. In this study, wettability and IFT of H2–brine–cement systems were experimentally measured at pressures of 500–1000 psi and temperatures of 25–50 °C to evaluate hydrogen migration, trapping, and the performance of cemented seals. Molecular dynamics simulations were conducted at pressures of 500–3000 psi and …

Storm Surge And Tides In Convergent Estuaries: The Case Of Extratropical Storm Merbok In Alaska, Steven Dykstra, Stefan Talke, David A. Jay, Matthew Lobo, Silvia Innocenti, Pascal Matte

Civil and Environmental Engineering Faculty Publications and Presentations

Coastal floods are composed of multiple drivers that interact with coastline geometries and are difficult to differentiate. To investigate the effects of basin shapes on storm surge and tides, we study the landfall of ex-Typhoon Merbok in the east Bering Sea, Alaska. Water levels at 34 stations are detided with a new tide wavelet tool, CWT_Multi (Lobo et al., 2024), and the spatial and temporal shifts in tides and surge are interpreted via long-wave theory. Results show nonstationary semiannual trends in tidal constituents due to ice effects and large interannual variability in mean-sea level (20-40 cm). After removing non-stationary tidal …

What Drives Blockchain Technology Adoption? A Meta-Analysis Across Tam, Tpb, And Utaut Frameworks, Amir Rahmani, Roohollah Ahmadi, Tugrul Unsal Daim, Mehdi Zamani, Dilek Ozdemir

Engineering and Technology Management Faculty Publications and Presentations

Research on blockchain adoption has expanded rapidly, with most studies conceptualizing adoption as behavioural intention. Technology adoption models, such as the Technology Acceptance Model (TAM), the Theory of Planned Behavior (TPB), and the Unified Theory of Acceptance and Use of Technology (UTAUT), are commonly applied to explore blockchain technology adoption (BTA). However, empirical results from the 12 hypotheses associated with these models remain fragmented and, at times, inconsistent, with limited comprehensive quantitative integration. To address this gap, the present study performs a meta-analysis to evaluate the degree and direction of these hypotheses systematically. In accordance with PRISMA guidelines, 149 quantitative …

Morphological Determinants Of Multiple Courtyard Configurations In Contemporary Urban Housing: A Quantitative Analysis Of Plot Area And Frontage Width, Maha Khalaf Hammad, Hasan Abdulrazzaq Hasan

AUIQ Technical Engineering Science

In modern cities with small plots and narrow frontages, courtyard-based housing has come back as a flexible way to use space. This study seeks to quantitatively examine the impact of residential plot area and frontage width on the diversity and functional distribution of courtyards in modern urban housing. A quantitative morphological approach was used by looking at the shapes of 121 modern residential plans that included internal courtyards. Using AutoCAD, we got spatial data, and then we used Microsoft Excel to look at the relationships between plot morphology, courtyard number, area, and functional role. The results show that the courtyard …

Systematic Review Of The Institutionalization Of Service Learning In Higher Education, Wilmer Hernan Cruz Gutierrez

ASEAN Journal of Community Engagement

An increasing number of universities are integrating service-learning (SL) to fulfill their social mission. However, sustainable institutionalization of SL remains a persistent challenge. This study identifies and analyzes the factors, actors, and strategies that drive and inhibit SL institutionalization in higher education. Using the PRISMA 2020 guidelines, a systematic literature review analyzed 52 documents from seven academic databases (including WoS, Scopus, and ERIC). The findings were grouped into three sections: cultural (integration into institutional values/missions), process (articulation within teaching, research, and outreach), and structural dimensions (dedicated support entities). The results obtained reveal a reciprocal relationship where cultural alignment enables processual …