On Large-Scale Knowledge Graph Completion: Dataset Creation, Embedding Model Evaluation, And Prediction Rule Explanation In Natural Language, Nasim Shirvani Mahdavi

Computer Science and Engineering Dissertations - Archive

Knowledge graph embedding models for completion tasks, especially link prediction, have been extensively evaluated using established benchmark datasets. These benchmarks suffer from significant limitations that fundamentally compromise evaluation reliability: they are often too small for comprehensive evaluation, and are problematic because they include redundant triples that artificially inflate performance metrics and administrative information that is not subject-matter knowledge. Furthermore, these datasets often fail to capture the multiary relationships crucial for representing real-world information. These limitations have led to unreliable model comparisons, overly optimistic performance estimates, and a disconnect between benchmark results and real-world knowledge graph completion capabilities, necessitating a fundamental …

Multi-Modal Model-Based Optical Flow Estimation For Event-Based Vision, Pritam Karmokar

Computer Science and Engineering Dissertations - Archive

Event cameras offer a fundamentally different sensing paradigm by asynchronously capturing brightness changes at high temporal resolution, directly encoding motion in the scene. However, their sparse and non-traditional data format poses significant challenges for dense motion estimation, particularly in the context of optical flow. Contrast Maximization (CM) has emerged as a powerful model-based framework for estimating optical flow from event data by optimizing the sharpness of motion-compensated event representations. This dissertation builds upon and significantly advances the CM framework through two complementary contributions.

First, we propose Edge-Informed Contrast Maximization (EINCM), a hybrid approach that augments the traditional events-only CM framework …

An Slo-Aware, Multi-Pronged Approach To Enhancing Resource And Energy Efficiency In Server Applications, Ning Li

Computer Science and Engineering Dissertations - Archive

Server applications operating in oversubscribed cloud environments face the dual challenges of meeting strict Quality-of-Service (QoS) requirements and improving resource and energy efficiency. As the number of user connections and workload diversity continue to grow, existing scheduling mechanisms struggle to balance QoS guarantees, fairness, resource efficiency, and power consumption. This dissertation presents a unified, cross-layer framework to address these challenges through three key contributions: AppleS, UTSLO, and REEF.

First, we propose AppleS, a user-space QoS-aware fine-grained I/O scheduling framework that delivers fair and efficient service to concurrent client connections. AppleS introduces a QoS-centric metric that guides admission control and scheduling …

Synthesis And Application Of Cu-Based Ultrasmall Nanoparticles For Targeted Glioblastoma Treatment, Ryan T. Hart

Material Science and Engineering Dissertations - Archive

Glioblastoma (GBM) is a highly malignant form of brain cancer with a bleak prognosis. Current maximal treatment involves surgical resection followed by chemo-or radiotherapy. Two critical barriers make treating GBM a formidable challenge. First, the tumor's tendril-like proliferation throughout healthy brain tissue often makes complete surgical removal and conventional radiation insufficient. Second, the blood-brain barrier (BBB), which protects the brain, unfortunately also shields GBM from life-saving anti-cancer drugs. Here, we develop a radioactive nanoparticle-based therapy that directly confronts these limitations, offering a new strategy for GBM treatment.

Prostate-specific membrane antigen (PSMA) is a promising target for glioblastoma (GBM) treatment because …

Phase-Field Modeling Of A Protective Layer For The Suppression Of Dendrites In Metallic Anode-Based Rechargeable Batteries, Bharat R. Pant

Material Science and Engineering Dissertations - Archive

Metallic anodes, such as Lithium (Li) and Zinc (Zn), offer promise for the development of high-capacity rechargeable batteries. However, metallic anode-based batteries suffer from severe dendrite growth during the plating process, which poses safety hazards and accelerates capacity degradation. Experimental studies suggest that using a protective coating on the anode surface could potentially mitigate dendrite growth and prolong the battery’s life. However, there are limited theoretical studies on the inhibition effect of a protective layer on dendrite growth. Herein, we developed a phase-field model to simulate the impact of a protective layer on the plating and stripping cycle for Li …

Fabrication Of Microscale Oxide Architectures On Silicon Via A Cmos-Compatible, Deposition-Last Process, Jamal A. Brown

Material Science and Engineering Theses - Archive

This work explores the feasibility of integrating complex oxide devices on silicon using a CMOS-compatible, deposition-last approach. While previous demonstrations of this method have succeeded at larger scales, this study focuses on extending the process to microscale features, with lateral dimensions as small as two microns. The fabrication sequence begins with photolithographic patterning and reactive ion etching of the silicon substrate, followed by the deposition of a silicon nitride mask to delineate device regions. We then epitaxially grew SrTiO3 and La-doped SrTiO3 layers on top of the nitride mask via molecular beam epitaxy. Electrical transport measurements of the La:STO layer …

Improving The Reliability Of Parts Produced Via Laser Powder Bed Fusion Through A Data-Driven Geometry Optimization Methodology, Federico Venturi

Mechanical and Aerospace Engineering Dissertations - Archive

This research aims to qualify the effect of design geometry on quality metrics of additively manufactured (AM) components that define reliability. Through the use of a novel methodology to characterize these quality metrics, AM components are inspected for the presence of defects such as surface roughness notches and porosity. These directly hinder the high-cycle fatigue characteristics demonstrated through the Kitagawa-Takahashi diagram and the El-Haddad model. By demonstrating the effect of geometry through a designed experiment and the adoption of the Murakami square root area parameter and Arola-Ramulu model, the improvement to fatigue life can be quantified. Incorporating this data into …

Stress Analysis Of Anisotropic Inclusion Problems Using Complex Variables, Liming Chen

Mechanical and Aerospace Engineering Dissertations - Archive

This research presents an analytical framework for determining stress fields in an elastic medium containing a circular anisotropic inclusion embedded in an infinitely extended isotropic matrix subjected to far-field uniform stresses. Stress distributions within both the inclusion and the matrix are described using classical stress functions, widely employed in two-dimensional elasticity theory.

To manage the complexity of the mathematical derivations, symbolic computation software (Mathematica) is used to streamline the analysis and obtain closed-form solutions. This approach overcomes traditional computational barriers that have limited the practical application of complex variable methods (CVM) in elasticity.

The methodology builds upon the foundational work …

Design Strategy For Hybrid Thrust Air Bearings: Comparative Analysis Of Rigid Vs. Foil Bearings Considering Optimum Taper Angle And Orifice Location With Experimental Validation, Ehiremen Ebewele

Mechanical and Aerospace Engineering Dissertations - Archive

Gas foil thrust bearings (GFTBs) are contactless bearings that offer advantages such as lightweight construction and the ability to accommodate misalignments and geometric irregularities. However, their load capacity is lower than rigid or magnetic bearings. The structure and geometry of the foil significantly influence GFTB performance. The taper-flat design is the most used configuration due to its effectiveness and ease of implementation. Key parameters in designing this geometry include taper ratio, taper height, orifice size, and orifice location. These parameters must be optimized alongside manufacturing constraints to produce an effective GFTB. This study presents a design optimization investigation of various …

Experimental And Numerical Modelling-Based Optimization Of Additive Manufacturing Processes, Vishnu V. Ganesan

Mechanical and Aerospace Engineering Dissertations - Archive

ABSTRACT

Experimental and Numerical Modeling-Based Optimization of Additive Manufacturing Processes

Vishnu V Ganesan, Ph.D.

The University of Texas at Arlington, 2025

Supervising Professor: Dr. Ankur Jain

Experimental and numerical modeling play a pivotal role in advancing additive manufacturing technologies by enabling a deeper understanding of complex, multi-physics processes that govern part quality, performance, and reliability. These manufacturing techniques—ranging from Powder Bed Fusion (PBF) and Material Extrusion (MEX) to Automated Fiber Placement (AFP)—involve tightly coupled thermal, mechanical, and material phenomena that are challenging to capture through empirical observation alone. Experimental methods offer critical validation and insights into real-world behavior, while numerical …

Intelligent Microfluidic Systems For Precision Manipulation And Real-Time Recognition Via Dielectrophoresis And Deep Learning, Negar Danesh

Mechanical and Aerospace Engineering Dissertations - Archive

This dissertation introduces intelligent microfluidic platforms by combining advanced DEP-based manipulation with real-time visual feedback. A DEP device featuring circular corral traps and dual-plane electrodes enables precise submicron particle trapping, high-resolution particle separation, and cell-particle co-assembly. Simulations and experiments confirm enhanced electric field control and stable confinement. To enable adaptive operation in EWOD systems, a deep learning model (U-Net) was developed for real-time droplet meniscus segmentation. The model achieved 98% accuracy and remained robust under noisy, low-contrast conditions. A live video pipeline was implemented, enabling consistent frame-by-frame feedback for closed-loop control. Together, these innovations establish a foundation for autonomous, high-performance …

Nonlinear Bump Stiffness Model And Its Effect On Structural Stiffness And Nonlinear Rotordynamic Characteristic Of Foil Bearing, Woongeon Lee

Mechanical and Aerospace Engineering Dissertations - Archive

Bump foils are the most widely used in foil bearings, but the behaviors of bump foils are complicated, and their characteristics have been a focus of research for decades. Bump foils are usually modeled as stiffness and damping are accounted for through interactions with shaft eccentricity, loading, shaft speed and excitation frequency. These nonlinear characteristics of the bump foil of radial foil bearings can be observed during both manufacturing and operational processes because of their inherent structural properties such as bump geometry, forming process, age-hardening process and complicated contact behavior with bearing housing. These nonlinear characteristics are one of the …

Multi-Objective Design Optimization Of Hypoid Geared Rotor Systems, Xinqi Wei

Mechanical and Aerospace Engineering Dissertations - Archive

Hypoid gears represent one of the most generalized and complex forms of gearing, widely used for power transmission of skew shafts in vehicles, aviation, and marine transmission applications. Optimizing their performance remains challenging due to the complex tooth surface and contact behavior. Specifically, the design parameters of the tooth surface are multi-scale, interdependent, and subject to strong constraints, leading to strong nonlinearity and an ill-conditioned Jacobian matrix in the parameter identification model. Moreover, feasible and insensitive contact conditions are difficult to constrain due to the inherent complexity of local conjugate contact between the meshing surfaces. These challenges significantly increase optimization …

Computational Study Of Detonation Wave Propagation And Propellant Injection In Detonation Engines, Jayson C. Small

Mechanical and Aerospace Engineering Dissertations - Archive

This research investigates the physics of detonation waves and their application to detonation engines, with two primary objectives: (1) to characterize detonation wave propagation, specifically detonation speed and wavefront thickness, in stoichiometric propane-oxygen mixtures near quenching conditions, and (2) to examine the physiochemical processes during propellant injection under detonation engine conditions, focusing on flush-wall-mounted, fluidic-valve injectors.

A multi-fidelity computational approach was employed. Reduced-order modeling based on the Chapman–Jouguet and Zeldovich–von Neumann–Doring models were used to evaluate detonation parameters and select an appropriate chemical mechanism. High-fidelity, multi-dimensional simulations solved the unsteady, compressible, reacting flows with finite-rate chemistry, using Reynolds-Averaged Navier–Stokes equations …

Topology-Driven Performance Analyses In Consensus Algorithms For Multi-Agent Systems, Brandon Ayala

Mechanical and Aerospace Engineering Theses - Archive

This thesis presents a simulation-based analysis of consensus algorithms in multi-agent systems, focusing on how network topology influences convergence performance. Both first-order and second-order linear consensus dynamics were examined across a variety of network configurations, including undirected and directed versions of cycle graphs, star graphs, minimum spanning trees, and fully connected graphs. In addition to standard consensus problems, leader-follower network structures were introduced to explore the impact of leader placement on convergence behavior, and extensions to multi-leader systems were analyzed to study robustness and convergence under multiple reference inputs. Graph-theoretic properties such as connectivity, degree distribution, and Laplacian eigenvalues were …

Multi-Agent Differential Games Under An Altruistic Equilibrium, Craig Alan Lovell

Mechanical and Aerospace Engineering Theses - Archive

This work studies a multi-agent differential game with linear dynamics under the Berge equilibrium. The governing coupled differential equations for a two-agent and a three-agent game under the Berge equilibrium are derived. These games are simulated and compared to the Nash equilibrium. A sensitivity study is performed which validates that, under some criteria, the Nash equilibrium can be recovered from the Berge equilibrium. Policy fusion between the Berge and Nash equilibrium is explored in a two-agent game. A five-agent game under the Berge equilibrium is simulated and multiple teams of agents in this game are evaluated. Finally, a mixed game, …

Deep Neural Network Models For Heatsink Performance Prediction And Optimization In Single Phase Immersion Cooling: Framework For Future Design Tools And Digital Twin Integration, Braxton J. Smith

Mechanical and Aerospace Engineering Theses - Archive

The rapidly rising computational power of modern computing components combined with the advanced packaging techniques being implemented has resulted in exponentially increasing thermal design powers (TDP) from CPUs and GPUs. Traditional air-cooling methods are approaching their effective cooling limits for many of these components, requiring lower supply air temperatures, higher supply air flowrates, and much larger heatsinks to remain feasible. Transitioning from air-cooling to single-phase immersion cooling offers numerous benefits in thermal performance, data-center size reduction, and energy efficiency. To leverage the merits of immersion cooling, the performance of a given heatsink must be predicted and optimized for best performance …

Animal Triangulation – Expanding The Oppressed/Oppressor Binary To A Triadic Constituency: The Oppressor, The Proxy, And The Oppressed, Katherine A. Abelanet

English Dissertations - Archive

Drawing on three fields of study, Animal Studies, Black Studies, and Shakespeare Studies, this dissertation examines animal triangulation as a system of oppression in which three constituents are triangulated for the benefit of the oppressor. Through triangulation, the oppressed/oppressor duality expands, creating a triad: the oppressor, the proxy, and the oppressed. This reimagining of the traditional binary of oppression opens new areas of conversation by adding an additional component. In animal triangulation, a proxy is created when an oppressor trains an animal or an animalized human to produce an abusive outcome on an oppressed group. By using a proxy, the …

Finding Our Way: Three Studies On The Evolving Role Of Arts Nonprofits In Contemporary Society, Trevor Meagher

Public Affairs Dissertations - Archive

Arts nonprofits play vital roles in defining the character of a community. However, our collective relationship with these organizations is evolving. This article-based dissertation leverages mixed methods to explore arts nonprofits’ evolving relationship with society.

The first article conceptually analyzes historical trends in arts advocacy in the United States. It explores how the arguments organizational supporters make in the hopes of securing financial and public support have developed and shifted in popularity over the past half-century. These streams are thematically connected through an emphasis on utilitarianism and value-extraction, and they have historically been employed in almost completely static proportion to …

Institutional Pressures And Nonprofit Executive Burnout: A Mixed-Methods Examination Of Organizational Culture And Leadership Sustainability In Texas, Lenita R. Dunlap Phd

Public Affairs Dissertations - Archive

Abstract

Nonprofit leader burnout represents a critical challenge threatening organizational sustainability and mission effectiveness across the nonprofit sector. Rather than an individual failing or isolated organizational pathology, burnout emerges as a systemic phenomenon embedded within institutional forces that operate across the nonprofit field. This mixed-methods examination employs a statewide Texas sample to capture institutional field-level dynamics that operate across municipal and regional boundaries, recognizing that nonprofit organizational fields transcend local contexts through statewide funding networks, professional associations, and regulatory environments that create coherent institutional pressures (DiMaggio & Powell, 1983). While research demonstrates that high work demands and resource constraints exacerbate …

Governance Matters: Evaluating The Drivers Of County-Level Economic Resilience In Texas Using Panel Data From The Post-Covid Recovery (2013-2023), Omar Wesley Bailey

Public Affairs Dissertations - Archive

This quantitative study examines the impact of adaptive governance measures taken by county governments in Texas on their Gross Domestic Product (GDP). The measures were selected based on their fit to adaptive governance theory. The years from 2013 to 2023 are covered, as they encompass the economic shock caused by the COVID-19 pandemic. The measures included the number of special-purpose districts, publicly available budgets, the urban-rural continuum association, the presence of performance dashboards, audits, FEMA-approved hazard mitigation plans, and the number of county revenue sources. The year and county were utilized as a fixed effect to capture time trends such …

Rethinking Energy Affordability: Assessing Dual Energy-Mobility Cost Burden In High-Density Multifamily Neighborhoods, Indira Manandhar

Planning Dissertations - Archive

This dissertation examines dual energy-mobility affordability from an equity perspective in high-density multifamily neighborhoods across nine U.S. cities. Traditional energy cost burden metrics focus only on residential energy and overlook transportation-related costs, obscuring how housing-related energy consumption and mobility costs jointly affect affordability for low-income and rent-stressed renters. This approach reflects the ongoing cost of maintaining everyday access rather than housing-related energy consumption costs alone. This study develops and applies a transferable, multicity block-group dual-energy mobility cost Burden (DECB) framework that integrates housing-related energy consumption costs with mobility costs into a composite indicator based on cost-to-income ratios and low-income/high-cost (LIHC) …

Warring Identities: The Transition From Servicemember To Civilian Employee, Michael Beeson

Business Administration Dissertations - Archive

This dissertation explores the role that military service identity plays in the transition to civilian employment. While there is a large volume of research on both the servicemember transition out of the military and military service identity, this dissertation contributes to this literature by examining the intersection of military service identity and the transition to civilian employment. This dissertation is designed to examine the nature of the military identity as servicemembers separate from the military and transition to civilian employment using competing theoretical identity frameworks rooted in identity and social identity theories. First I conduct a survey study that examines …

Navigating Compliance: How Wage Theft Influences Warn Act Decisions, Roberto Gonzales

Accounting Dissertations - Archive

Economic theory suggests that firms comply with regulations when the expected costs of noncompliance outweigh the expected benefits (Becker 1968). Despite minimal enforcement, weak penalties, and strong incentives for noncompliance, some firms comply with the provisions of the Worker Adjustment and Retraining Notification (WARN) Act, which mandates advance notice of mass layoffs and plant closings. Using a sample of 7,084 firm-years necessitating WARN Act disclosures from 2000 to 2020, I reassess the cost-benefit calculus by first demonstrating that wage theft violations provide the incentives necessary to compel firms to comply with other minimally enforced laws like WARN. Next, I find …

An Exploration Of Teacher Exodus In Predominantly African American Secondary Public Schools Amid Covid-19, Keith Demond Ford

Educational Leadership & Policy Studies Dissertations - Archive

For some time, K-12 teachers across America have been resigning from classrooms in large numbers. Like many of the nation’s communities, schools in American neighborhoods of color have seen an overwhelming amount of teacher resignations amid the COVID-19 pandemic. According to existing literature, education’s traditional systemic norms and health protocols which were initiated during COVID-19 motivated classroom teachers to leave their jobs. This qualitative study uses a phenomenological methodology as it discovers that an interrelatedness of factors influences six participants to resign from their classroom teaching roles at predominantly African American middle and high schools during and immediately following …

Case Study Exploring How Data-Driven Decision-Making Influences Culture At A Title I Elementary School, Cameron K. Ramirez

Educational Leadership & Policy Studies Dissertations - Archive

This qualitative case study explores how data-driven decision-making influences school culture at a Title I elementary school in Texas. Grounded in the conceptual frameworks of data-driven decision-making (Gill et al., 2014) and transformational leadership (Leithwood & Jantzi, 2005), this study investigated how school leaders and staff implement, interpret, and sustain data practices within a high-accountability context. Using a phenomenological approach, interviews were conducted with the principal, assistant principal, two instructional specialists, and three teachers, and artifacts were collected for data triangulation. The findings revealed that effective data use is cultivated through immersive, contextualized professional learning, collaborative systems, leadership modeling, and …

High Frequency Oscillations As Biomarkers Of The Epileptogenic Zone In Children With Drug Resistant Epilepsy, Lorenzo Fabbri

Bioengineering Dissertations - Archive

Epilepsy surgery stands out as the most effective treatment for patients dealing with focal drug-resistant epilepsy (DRE). Its effectiveness depends on successfully removing or disconnecting the epileptogenic zone (EZ), which is the brain area crucial for seizure generation. The seizure onset zone (SOZ) serves as the best approximation of the EZ; this is the region where most seizures begin, identified through invasive electroencephalographic (iEEG) recordings. However, the unpredictable nature of seizures means they can take hours or even days to occur, consuming valuable human and financial resources. As a result, there is a pressing need for an interictal biomarker that …

Strategies For Enhanced Meg Data Analysis In Clinical Practice And Emerging Frontiers, Pegah Askari

Bioengineering Dissertations - Archive

Epilepsy and dementia are debilitating neurological disorders that pose substantial challenges for patients, caregivers, and healthcare systems. Advances in magnetoencephalography (MEG) and signal processing offer new opportunities to improve diagnostic accuracy, surgical planning, and treatment monitoring. This dissertation presents a unified body of work comprising artifact removal, automated event detection, and deep learning-based biomarker discovery. These approaches collectively enhance the clinical utility of MEG for diverse patient populations.

The first study addresses a significant technical obstacle in the management of drug-resistant epilepsy. Patients receiving responsive neurostimulation (RNS) have historically been excluded from MEG as the data is contaminated by device-related …

Functional Enhancement Of Pancreatic Islets Through Photobiomodulation For Potential Diabetes Therapeutics, Kelli Fowlds

Bioengineering Dissertations - Archive

Islet transplantation is a potential therapeutic route for type 1 diabetic patients facing chronic ketoacidosis and/or hypoglycemia unable to be properly regulated with standard insulin administration. However, successful engraftment is hampered by a multitude of factors. Harvested islets face rapid, substantial degradation due to hypoxia and nutrient depletion once isolated. Transplanted islets are additionally susceptible to the instant blood-mediated inflammatory reaction (IBMIR). This combination of factors leads to more than half of transplanted islets failing to engraft post-surgery. Many areas of research are dedicated to investigating alternative approaches or supplemental treatments to improve the success rate of engraftment and insulin …

Novel Electrophysiological Biomarkers In Pediatric Drug Resistant Epilepsy And Genetic Epilepsy Syndromes, Sakar Rijal

Bioengineering Dissertations - Archive

Pediatric epilepsies, particularly those that are drug-resistant or genetically driven, represent some of the most complex neurological disorders encountered in childhood. Central to their pathophysiology is a disruption in the delicate balance between cortical excitation and inhibition (E/I), often resulting from impaired GABAergic interneuron function. This imbalance manifests as aberrant network dynamics and altered neural oscillations, giving rise to seizures and long-term cognitive impairments. In this thesis, we developed a translational framework to identify electrophysiological biomarkers that (i) assess cortical E/I imbalance and (ii) map epileptogenic zones, with the aim of enhancing diagnosis, guiding surgical planning, and informing therapeutic monitoring …