Digital Commons Network^™

Layer-Wise Prediction Of Overhang-Related Geometric Deviation In Metal Additive Manufacturing With Conditional Generative Adversarial Networks, Himal Sapkota

Theses

Ensuring dimensional precision in parts with complex overhangs is a significant concern in Metal Additive Manufacturing (MAM), as undetected geometric deviations can compromise functionality and reliability. This research introduces a Conditional Generative Adversarial Network (cGAN), specifically the Pix2Pix framework, to predict layer-wise geometric deviations in Laser Powder Bed Fusion (LPBF) printed parts with overhang geometries using paired 2D CAD slices and corresponding X-ray Computed Tomography (XCT) based ground truth images. A key innovation is using RGB color-coded CAD slices to encode overhang angle information, enhancing feature distinction and prediction accuracy compared to non-color-coded inputs. Eighteen Pix2Pix models were trained across …

College Leaders’ Perspectives Of Diversity At A Community College System In Texas: A Phenomenological Study Of Validation, Xandelyn Wright Washington

All Dissertations

The United States has undergone dramatic changes in student demographics over the last 40 years. Nowhere is this reflected more than in the field of education (Center for Public Education, 2012; Fabina et al., 2023). Disaggregation of student demographics is a useful and common method for measuring student outcomes, and in the United States, non-majority students consistently have lower student outcomes (Gay, 2013; Howard, 2010; Ocay et al., 2023).

Ma and Baum (2016) and McNair et al. (2015) stated that the role of community colleges is pivotal in postsecondary education. As such, college leaders and administrators have focused attention on …

Vision To Reality: Groundbreaking Impacts Of Artificial Intelligence On Key Performance Indicators In The Built Environment, Christopher Hamilton Sr

All Dissertations

As construction transitions into an era shaped by Industry 4.0 and data-driven decision-making, Artificial Intelligence (AI) emerges as a transformative tool with the potential to enhance key performance indicators (KPIs) such as schedule adherence, cost management, quality assurance, safety, resource allocation, and customer satisfaction. However, few studies have empirically assessed the direct influence of AI adoption on operational performance or examined the innovation diffusion factors that facilitate its integration. This gap underscores the need to align AI initiatives with broader organizational strategies, ensuring that technological adoption translates into measurable improvements in construction performance.

This quantitative study investigated two core research …

Vlsi Chip Design And Fabrication For Solar Panel Diagnosis System, Abhitej Divi

All Dissertations

Solar photovoltaic panels (PV) are a key clean energy solution to combat global warming, with global capacity now exceeding 714 GW due to rapid technological and policy advancements in solar panels (SP). However, the efficiency and service life of SPs remain limited due to the lack of advanced fault detection systems, as SPs are prone to short circuits, open circuits, and power degradation.

This work presents a novel design of a fault-detecting very large-scale integrated circuit (VLSI), simulation results, and the complete chip layout prepared for fabrication using TSMC 180 nm CMOS technology with λ = 90 nm. SP’s diagnosis …

Seismic Performance Assessment Of Fatigue-Damaged Cantilever Overhead Sign Structures Using Near-Field Ground Motions, Yeasin Ahmed

Open Access Theses & Dissertations

Cantilever overhead sign support (COSS) structures are one of the most common features of transportation systems, providing navigational information to motorists. The slender geometry, lightweight design, and welded connection at the base make COSS structure susceptible to fatigue cracking under long term cyclic loading from wind-induced galloping, truck-induced gust pressure and so on. COSS structures are traditionally designed considering nominal wind conditions. However, rising incidents of seismic activity in regions like Dallas-Fort Worth related to industrial injection wells in the Permian Basin have created a serious concern regarding the seismic performance of potentially fatigued-damaged COSS structure. The interaction between already …

The Relationship Between Inclusive Classroom Practices, Stem Identity And Stem Interest In Latinx Secondary Students, Laura Corral Carrillo

Open Access Theses & Dissertations

Latinx students remain underrepresented in science, technology, engineering, and mathematics (STEM) fields despite representing a growing portion of the U.S. school population. Research suggests that inclusive classroom practices (ICPs) that affirm students' cultural and linguistic identities can play a critical role in shaping STEM identity and fostering interest in STEM pathways. This mixed-methods study investigated the relationship between ICPs, Latinx high school students' STEM identity development, and their interest in pursuing STEM careers in the Texas borderlands. The study employed a convergent design, integrating quantitative survey data from 52 students and qualitative interview data from four secondary science teachers. Quantitative …

Mechanical Characterization Of M Plane (10-10) And C Plane (0001) Gallium Nitride Semiconductors Via Spherical Nanoindentation, Daniela Alejandra Duarte

Open Access Theses & Dissertations

Gallium nitride's (GaN) mechanical characterization is essential for evaluating its performance and long-term dependability, especially when subjected to mechanical stress and irradiation. The design and optimization of GaN-based devices, which are extensively employed in high-power electronics and optoelectronics, depend on an understanding of these characteristics. Mechanical characterization allows for the evaluation of key characteristics, including stress distributions, representing the spatial variation of internal stresses under applied loading, and pop-in events, which correspond to abrupt displacements associated with the onset of dislocation nucleation and slip. These features are essential for understanding the anisotropic (direction-dependent) response of the material to external forces …

Investigating The E74-Mediated Regulation Of A Gata Factor In Aedes Aegypti Mosquitoes, Jacklyn Marie Estrada

Open Access Theses & Dissertations

The mosquito species Aedes aegypti has a significant impact on public health as a vector for multiple pathogens. Its ability to transmit deadly diseases, including Yellow Fever, Dengue Fever, and Zika, emphasizes the urgency of understanding its reproductive biology. In female mosquitoes, reproductive success hinges on obtaining a vertebrate blood meal, which triggers vitellogenesis - the synthesis of yolk protein precursors (YPPs) necessary for egg development. Without a blood meal, female Ae. aegypti remain in a state of previtellogenic arrest, where the YPP gene vitellogenin (Vg) is repressed by a type of transcriptional factor, GATAr (AaGATAr) (Attardo et al., 2003). …

The Origin And Geologic History Of Dolostones Associated With The Moab Valley Salt Wall, Paradox Basin, Utah, Charles Ojodale Igomu, Charles Ojodale Igomu

Open Access Theses & Dissertations

This thesis investigates the origin and geologic context of dolostones associated with the Moab Valley salt wall in southeastern Utah, a feature within the broader Paradox Basin that offers an exceptional opportunity to study the interplay between carbonate sedimentation, diagenesis, and salt diapirism. The fundamental research question focuses on evaluating whether dolostones observed in the Moab Valley are all depositional, diagenetic or structurally reworked components of deeper stratigraphy, and how their presence and geometry relate to the halokinetic processes that shaped sedimentation across the Moab Valley. This study tested the hypothesis that dolostones within Moab Valley represent a mixed assemblage …

Cellular And Noncellular Influences On Lipid Nanoparticle Tropism In The Liver, Mario Yomir Mata Corral

Open Access Theses & Dissertations

Hepatocellular carcinoma (HCC) is currently ranked as the second leading cause of cancer-related mortality worldwide, causing more than 700,000 deaths a year. The liver is important in blood filtration and metabolism, and for this reason is a prime target for drug delivery, with lipid nanoparticles (LNPs) showing promise as carriers due to their natural hepatic tropism. However, LNP efficacy is decreased in HCC due to the limited understanding of liver physiology in cancerous environments. This project proposes to address this gap by using a tissue-clearing technique known as CLARITY along with a chemically tagged LNP for comprehensive visualization of LNPs …

Evaluation Of Salt-Free Electrodialysis Metathesis For High Recovery Inland Desalination Brine Management, Tayia Oddonetto

Open Access Theses & Dissertations

Salt-Free Electrodialysis Metathesis (SF-EDM) is an emerging electro-driven membrane technology designed to minimize brine discharge while enabling selective ion separation and resource recovery. This dissertation presents an evaluation of SF-EDM, spanning bench-scale studies with synthetic brine from the Brackish Groundwater National Desalination Research Facility in Alamogordo, NM, real reverse osmosis (RO) brines from the Kay Bailey Hutchinson Desalination Plant in El Paso, TX, and finally a weeklong pilot demonstration at the Yuma Desalting Plant in Yuma, AZ. Bench-scale experiments established process feasibility and performance trends, while pilot results revealed the value of pre-treatment and system configuration. SF-EDM demonstrated high hydraulic …

Aluminum Doped Tin Sulfide Thin Films For Solar Cell Applications, Gabriel Rodriguez Guijarro

Open Access Theses & Dissertations

Tin sulfide (SnS) is theorized to be a suitable material for solar cells, but there are some difficulties that have not been overcome when making thin films that have the properties needed to compete with other materials. This work investigates the structural and optoelectronic properties of aluminum-doped SnS thin films, deposited via magnetron cosputtering physical vapor deposition at different temperatures. To characterize the films a variety of techniques were used: Raman spectroscopy, SEM, TEM, X-Ray Reflectivity, and UV-Vis spectroscopy. The results show that the target stoichiometry is a relevant parameter to take into account when growing SnS thin films, the …

A Digital Engineering Framework For Ai-Driven Trade-Off Evaluation And Predictive Component Classification, Alejandro Silva Au

Open Access Theses & Dissertations

This thesis introduces a digital engineering tool designed to help engineers make smarter decisions when choosing actuators. At its core, the system brings together machine learning (specifically XGBoost) and a decision-making method called Multi-Utility Attribute Theory (MUAT). The goal is to support engineers in picking components based on what really matters for their designs, whether that's speed, cost, durability, or any other performance factor. What makes this tool stand out is its user-friendly interface that lets people interact with the system directly. It takes a set of actuator performance data, classifies each one into a relevant use category, and then …

Model-Based Systems Engineering For Aerospace Applications: Strategic Requirements Prioritization In Complex Adaptive Systems And Digital Integration, Iqtiar Md Siddique

Open Access Theses & Dissertations

Ineffective systems engineering practices continue to jeopardize aerospace missions, resulting in multi-billion-dollar losses, delays, and fragmented development outcomes. As complexity intensifies and timelines shrink, conventional document-based methods increasingly fail to support early validation, cross-domain traceability, and synchronized tool usage. This research presents an integrated approach that addresses three critical gaps: synchronizing executable and traceable MBSE models across structural, behavioral, and requirements domains; applying scalable requirements prioritization techniques tailored for Complex Adaptive Systems; and establishing automated simulation feedback loops through digital toolchain integration. Central to this strategy is the Digital Trinity, which connects system models, simulations, and lifecycle data through a …

Laser Scan Path Design For Controlled Microstructure In Additive Manufacturing With Integrated Reduced-Order Phase-Field Modeling And Deep Reinforcement Learning, Augustine Twumasi

Open Access Theses & Dissertations

Laser Powder Bed Fusion (L-PBF) is a well-established additive manufacturing technique for fabricating intricate metal components with exceptional precision. A significant challenge in L-PBF is the formation of complex microstructures that influence final material properties. We propose a physics-guided, machine learning-aided approach to optimize scan paths for desired microstructure outcomes, such as equiaxed grains. We employed a phase-field method (PFM) to model the evolution of the crystalline grain structure. To reduce computational costs, we trained a surrogate machine learning model, a 3D U-Net convolutional neural network, using single-track phase-field simulations with varying laser powers to predict crystalline grain orientations based …

Multi-Material Cell Clipping On The Gpu, Melanie Cassidy Walsmith

Open Access Theses & Dissertations

The process of clipping a multi-material cell finds diverse applications across fields such as numerical simulations and computer graphics visualization. Computational fluid dynamics problem often combines multiple materials with different physical properties. The interfaces between those materials may be a part of the solution and evolve in time and can be non-aligned with the mesh. When volume conservation is crucial, interface reconstruction methods are used to approximate such material interfaces. They involve multiple steps, one of which is the process known as clipping. Clipping consists of intersecting and cutting a given cell with a material interface (represented by a line …

Fixing A 100-Year-Old Mistake, Michael J. Graetz

Faculty Scholarship

Posing the question of international tax cooperation versus competition reminds me of multiple-choice exams in which the right answer is “all of the above.” National interests determine which dominates at any given time. And in tax competition among nations, zero is not a lower bound.

In 1918, to encourage U.S. investments abroad, the United States enacted a credit for foreign taxes paid by U.S. companies and relinquished taxing rights to most foreign-source income. With the foreign tax credit, the United States assumed sole responsibility for reducing the double taxation of its residents and citizens. As the influential economist Edwin Seligman …

Preschool Teachers’ Perspectives On Conceptual Movement In Academic Instruction: A Mixed- Methods Study With Implications For Early Math, Kehinde H. Orimaye

Electronic Theses and Dissertations

This convergent mixed-methods study investigated Missouri preschool teachers’ familiarity, implementation, and perceptions of conceptual movement (CM), the purposeful integration of bodily actions to support young children’s understanding of abstract academic concepts, particularly in early mathematics instruction. Grounded in embodied cognition and informed by enactivism and the theory of event coding (TEC), the study explored: (a) preschool teachers’ awareness and frequency of CM use; (b) how teacher characteristics such as experience, age group taught, and math anxiety relate to CM implementation; and (c) teachers’ perceptions of CM’s instructional value, implementation challenges, and professional development needs.

Quantitative data were collected through a …

Advancing Real-World Implementation Of The Well Optimized Linear Finder (Wolf) High-Speed Atmospheric Turbulence Compensation Method, Timothy Evan Coon

Theses and Dissertations

This dissertation advances the real-world implementation of the Well Optimized Linear Finder (WOLF) method for high-speed Atmospheric Turbulence Compensation (ATC). Atmospheric turbulence introduces phase aberrations into optical wavefronts and degrades image quality in terrestrial imaging systems. Traditional phase diversity methods are computationally intensive and poorly suited to real-time operation. The WOLF method addresses these limitations through a novel, point-wise formulation of the optical transfer function (OTF) as a structured autocorrelation of the generalized pupil function (GPF). This formulation enables the estimation of phase aberrations at individual spatial coordinates with distributed computational complexity.

The research begins by developing a MATLAB-based simulation …

Investigating Global Lightning Observed From Ground And Space, And Its Relationship To Solar Activity, Megan Diane Mark

Theses and Dissertations

The extremes of lightning, specifically lightning with long-lasting continuing currents and lightning with extremely high peak currents, are investigated from both ground- and space-based observations. Additionally, the potential solar influence on lightning is investigated on large spatial scales.

Continuing currents may occur following the impulsive flow of current during a cloud-to-ground (CG) return stroke and are usually low amplitude (from a few amperes to a few kiloamperes) and long duration (several to hundreds of milliseconds). Remotely estimating their duration from the electromagnetic fields measured by existing ground-based lightning locating systems (LLSs) is not possible, but some space-based lightning detection systems …

Characterization Of Search Spaces And Effects On Machine Learning, Leo Ghelarducci

Doctoral Dissertations and Master's Theses

The present status of the field of Machine Learning (ML) focuses on optimization of popular models. Rarely are the effects of the problem characteristics upon the solution algorithm studied. There exists no standard for knowing when to apply ML algorithms to a given problem or how to estimate the effectiveness of results. Focusing on the search space of problems, a rigorous study was conducted to generate an in-depth understanding of the impact of search space characteristics to the performance of a ML algorithm, specifically a Genetic Algorithm (GA). The effects of specific problem characteristics, represented via solution space characteristics, on …

Is R&D Rivalry Slowing The Growth Of Productive Firms?, Yoshiki Ando, James Bessen, Xiupeng Wang

Faculty Scholarship

The reallocation of jobs to more productive firms is a substantial component of aggregate productivity growth, yet job reallocation rates have declined substantially in the United States. This paper explores the hypothesis that greater technological rivalry has exacerbated adjustment costs, slowing reallocation. Using microdata at the US Census and estimates of technological rivalry in firm growth regressions, we find that technological rivalry slows firm responses to productivity shocks. Firms do not expand as rapidly in the face of higher obsolescence risk. Estimating counterfactual firm growth from 1997-2018, we find that growing technological rivalry accounts for most of the decline in …

Formation Control Between Leader And Migratory Follower Tissues Allows Coordinated Growth, Toru Kawanishi, Takamichi Sushida, Tony Y-C Tsai, Hiroyuki Takeda, Sean G Megason

2020-Current year OA Pubs

Coordinated growth of multiple tissues is fundamental to shaping our body, but the underlying mechanisms remain underexplored. In zebrafish embryos, midline tissues composed of the notochord, floorplate, and hypochord elongate synchronously with their lengths aligned. We show that floorplate and hypochord cells collectively migrate posteriorly along the nascent notochord extracellular matrix as it extends posteriorly, maintaining the tripartite configuration. Fibroblast growth factor-mediated migration in a spatially graded manner causes cell stretching, which triggers Yap-dependent proliferation and controls floorplate and hypochord growth. Supported by mathematical modeling, we further suggest that their growth is fine-tuned by mechanical tethering to the notochord via …

Applying Large Language Models For Surgical Case Length Prediction, Adhitya Ramamurthi, Bhabishya Neupane, Priya Deshpande, Ryan Hanson, Srujan Vegesna, Deborah Cray, Bradley H. Crotty, Melek Somai, Kellie R. Brown, Sachin S. Pawar, Bradley Taylor, Anai N. Kothari

Electrical and Computer Engineering Faculty Research and Publications

Importance Accurate prediction of surgical case duration is critical for operating room (OR) management, as inefficient scheduling can lead to reduced patient and surgeon satisfaction while incurring considerable financial costs.

Objective To evaluate the feasibility and accuracy of large language models (LLMs) in predicting surgical case length using unstructured clinical data compared to existing estimation methods.

Design, Setting, and Participants This was a retrospective study analyzing elective surgical cases performed between January 2017 and December 2023 at a single academic medical center and affiliated community hospital ORs. Analysis included 125493 eligible surgical cases, with 1950 used for LLM fine-tuning and …

The Importance Of Imperfect Pre-Clinical Models In Adolescent Idiopathic Scoliosis, Diane S Sepich, Ryan S Gray, Nadav Ahituv, Christina A Gurnett, Jonathan J Rios, Lila Solnica-Krezel, Carol A Wise

2020-Current year OA Pubs

Adolescent idiopathic scoliosis (AIS) is a twisting spinal deformity that occurs in otherwise healthy children at the time of rapid pre-pubescent growth. AIS affects ∼3% of children worldwide and is the most common musculoskeletal diagnosis in pediatric populations, posing a significant physiological, psychosocial and financial burden to patients. Genetic predisposition is a clear and major contributor to AIS, and insights from genomic discoveries are inspiring translational studies ultimately aimed at developing novel diagnostics and therapies. Pre-clinical animal models of AIS are now essential to validate human genetic findings, understand gene-by-environment interactions, and speed etiologic and therapeutic discovery. In this Perspective, …

Investigation Of Wireless Communication Sub-Optimizing Factors And Ai-Based Optimization For Ber Reduction, Lalan Jee Mishra

Theses and Dissertations

The increasing demand for high-throughput, low-latency, and reliable wireless communication has led to significant advancements of cellular wireless technologies since the early ‘80s. However, in dynamic and interference-prone environments—particularly those involving Unmanned Aerial Vehicles (UAVs)—signal degradation due to pathloss, multipath propagation, co-channel interference, and weather-induced attenuation continues to undermine performance. These factors contribute to elevated bit error rates (BER), inefficient spectrum usage, and unreliable communication links, thereby limiting the practical utility of wireless systems in aerial applications. Traditional mitigation techniques, while effective under certain conditions, often fail to adapt to rapidly changing wireless environments. This shortcoming underscores the need for …

Characteristics Of Responders To Interventions For Parkinson Disease: A Scoping Systematic Review, Sidney T. Baudendistel, Gammon M Earhart

2020-Current year OA Pubs

AIMS: The purpose of this review is to identify the characteristics of responders in interventions targeting motor function for individuals with Parkinson disease.

MATERIALS & METHODS: The primary search included, 'Parkinson' + 'responder.' A second, broader, search further included 'response' + 'responsiveness' + 'responsive.' Records were sorted by intervention: neuromodulation, pharmaceutical, physical, and placebo.

RESULTS: Thirteen studies were identified in the primary and 19 studies in the secondary search, culminating in 120 characteristics. For neuromodulation interventions, responders were younger at onset, more responsive to levodopa, and had more difficulties with activities of daily living. Responders to pharmaceuticals were younger at …

Night-Time Warming And Prey Availability Interact To Influence Physiology In Prairie Lizards (Sceloporus Consobrinus), Allison R. Litmer, Morgan K. Pelley, Steven J. Beaupre

Biological Sciences Faculty Publications and Presentations

Among ectotherms, temperature and food availability are drivers of individual and population characteristics. Increasing night-time temperatures due to climate change can increase energetic demands, potentially amplified or mitigated by prey consumption. Few studies examine night-time temperatures specifically, and consequences of co-occurring changes in the abiotic and biotic environment. Thus, we examined interactions between warming night-time temperatures and prey availability (as a proxy of foraging time and effectiveness), and how they affect food consumption, digestive passage time, metabolizable energy intake (MEI), assimilated energy, and fecal and urate production in a model organism, prairie lizards (Sceloporus consobrinus). Three temperature treatments (current conditions, …

Training Robot Swarms For Adaptive Foraging In Environments With Obstacles, Pigar Biteng, Tameem Uz Zaman, Qi Lu

Computer Science Faculty Publications

In this work, we train adaptive and efficient foraging strategies for robot swarms in a large, unmapped search space with multiple randomly distributed box obstacles using the penalty-reward based NeuroEvolution of Augmented Topologies (NEAT), P-NeatFA. This model enables efficient multi-robot foraging behavior and obstacle avoidance by rewarding effective actions and penalizing inefficient ones, thereby minimizing redundant exploration and outperforming traditional stochastic foraging algorithms. We optimize foraging strategies and search patterns in robot swarms by training models that maximize cumulative rewards in three types of resource distribution environments. The evaluation focuses on the number of resources collected within a fixed time …

Evolving Adaptive Foraging Robot Swarms With Neat In Environments With Obstacles, Tameem Uz Zaman, Pigar Biteng, Qi Lu

Computer Science Faculty Publications

We apply NeuroEvolution of Augmented Topologies (NEAT) to evolve adaptive and efficient swarm foraging behaviors in unknown environments with randomly placed obstacles. By rewarding effective actions and penalizing inefficient ones using the proposed strategy P-NeatFA, the training generates efficient foraging and obstacle avoidance strategies, reducing redundancy and outperforming traditional stochastic foraging algorithms. Optimization is guided by cumulative reward-based fitness, evaluated through simulations involving three types of distributed resources. Foraging performance is assessed in terms of resource retrieval rates. We compare the performance of our proposed P-NeatFA with that of CPFA and NeatFA. Experimental results show that P-NeatFA significantly outperforms the …