Digital Commons Network^™

Examining School Facilities And Their Impact On Student Achievement, Andre’ Donnell Walker

All Dissertations

This quantitative study examined the impact of school facility conditions on student performance in a large urban school district in Texas. Drawing on Allen’s (2017) nine foundations of a healthy building, such as air quality, lighting, and ventilation, the study explored whether students in modern, rebuilt schools outperformed those in older or renovated facilities. Using data from the Texas Education Agency, the analysis focused on standardized test scores, attendance rates, and graduation rates. Results showed that rebuilt schools consistently outperformed renovated schools on STAAR assessments, particularly in mathematics (+8.2%) and science (+7.6%). Rebuilt schools also demonstrated higher attendance (+3.2%) and …

Roadmap To Success: Perspectives Of Black Females Overcoming Barriers In Doctoral Programs At Predominantly White Institutions (Pwis) And Historically Black Colleges And Universities (Hbcus) In Southeast Texas, Jenta’ Monique Young

All Dissertations

This study employed a qualitative research design to explore the experiences of 10 Black female doctoral students as they matriculated and successfully graduated from doctoral programs at Predominantly White Institutions (PWIs) and a Historically Black Colleges and Universities (HBCUs) in Southeast Texas. A descriptive phenomenological research methodology was employed in this study to illustrate the struggles and barriers Black females face during matriculation and their persistence in achieving success in a doctoral program. The participants were women who self-identified as Black or African American. Participants were previously enrolled full-time in a cohort-oriented doctoral program with face-to-face, online, or hybrid instruction …

Modeling And Analysis Of Electric Signal In Neurons, Kevin J. Roberts

All Graduate Reports and Creative Projects, Fall 2023 to Present

Neurons in humans and other species transmit information by sending electric signals via axons. This process relies on the generation and propagation of action potentials—rapid changes in the membrane potential of the axon. Understanding the mechanisms of action potentials, including how they are generated and influenced by the axon geometry and material parameters, is crucial for gaining insight into neurological diseases such as Alzheimer’s and Multiple Sclerosis (diseases highly correlated to demyelination). In this work, we review and summarize mathematical models for signal transmission–including the classical Hodgkin-Huxley model, the Single Cable (SC) model, and the Double Cable (DC) model. We …

Role Of Competition In Avoiding Social Collapse, Gabriel M. Tonks

All Graduate Reports and Creative Projects, Fall 2023 to Present

Historical examples suggest that isolated, resource-scarce societies are prone to increased hostility and social disasters. The research in this report explores the role of intrasocietal competition in avoiding resource collapse. Two resource-consumer models are proposed with competition which depends on the level of available resources. One of these models is selected for in-depth analysis, and the region in the parameter space where saddle-node bifurcations emerge is computed numerically. The effects of environmental noise on resource growth are simulated, showing that the increased noise usually has negative long-term effects which might be mitigated via increased consumer competition.

The Depositional Environment Of The Triassic Cow Branch Formation, Dan River Basin Of Virginia And North Carolina Through Petrographic Study And Geochemical Analysis, And In Relation To Taphonomic Processes And Vertebrate Morphology, Gina M. Workman

All Graduate Reports and Creative Projects, Fall 2023 to Present

The Upper Triassic Cow Branch Formation of the Dan River Basin, located in southern Virginia and northern North Carolina, has long captivated generations of geoscientists. Since the 1970s, researchers have sought to unravel the mystery surrounding the depositional environment of this ancient lake system. This world-class lagerstätte hosts a diverse assemblage of fossil fauna and flora, with a notable preservation bias toward fossil vertebrates, most prominently the archosauromorph, Tanytrachelos ahynis. The geology of the Cow Branch strata continues to evoke a persistent question: Are these sediments representative of a shallow or deep lake?

I undertook a petrographic and geochemical study …

Crime Statistics And Taxi Transportation In New York City: An Exploratory Data Analysis, Adelyn J. Fleming

All Graduate Reports and Creative Projects, Fall 2023 to Present

In a heavily populated city as busy and vibrant as New York City, people are constantly on the move. Some of that movement might be connected to the occurrence of certain crimes. This study explores how movement, especially from yellow taxicabs, relates to crime occurrences within different parts of the city. By looking at the 2018 taxi trip and crime data, alongside population data from the 2020 U.S. Census, this project aims to explore how individuals travel within the city and whether there is any relationship with the types of crime that occur within those areas. Visual tools and maps …

Error Reduction Methodology And Data Simulation For Interval Data, Ranik Christopher Jelinek

Undergraduate Honors Capstone Projects

Chronic kidney disease (CKD) is a progressive condition affecting hundreds of millions of individuals worldwide. However, clinical datasets often record continuous laboratory measurements as categorical intervals rather than precise numerical values. This interval-censored structure presents methodological challenges for standard regression-based classifiers. This study compares three strategies for handling interval-valued predictors prior to fitting a logistic LASSO model: (1) midpoint imputation, which replaces each interval with its arithmetic center; (2) ordinal encoding, which maps intervals to integer ranks; and (3) a Monte Carlo simulation approach, which repeatedly samples uniformly from each observed interval and averages predictions across replications. Using a 10-fold …

Copula-Based Tests For Assessing The Association Between Genetic Variants And Mixed Phenotypes, Martin Amoah

Open Access Theses & Dissertations

High-dimensional omics studies increasingly involve heterogeneous data types and phenotypes, which traditional association methods struggle to model jointly due to incompatible marginal distributions and complex dependence structures. This thesis develops a unified copula-based framework for assessing associations between genetic variants and mixed phenotypes by decoupling flexible marginal models from their joint dependence structure. While previous copula-based approaches in this setting have focused largely on continuous and binary traits, we extend these methods to a broader class of phenotype pairs. Specifically, we introduce new association tests for bivariate outcomes involving ordinal–continuous, nominal–continuous, and survival–continuous combinations. The proposed methodology derives joint density …

Systematic Review Of Instruments Measuring Teachers' Tpack, Jose Ruben Avalos

Open Access Theses & Dissertations

The study examines the assessment of Technological Pedagogical Content Knowledge (TPACK), a framework that integrates technology, pedagogy, and content knowledge for effective teaching. Given the increasing integration of technology in education, it is crucial to understand how TPACK is assessed and the tools used to measure teachers' proficiency in these areas. This study aims to review and analyze tools used to assess TPACK, evaluate their validity and reliability, and provide a synthesis of existing research to inform future developments in TPACK assessment. A systematic review of literature was conducted, focusing on studies related to the evaluation of TPACK. Four research …

Simulation, Modeling, And Economical Optimization Of Small Modular Reactors For Flexible Power System Operations, Javier Bejarano

Open Access Theses & Dissertations

The transition toward a low-carbon and increasingly renewable electric grid has heightened the need for generation technologies that can deliver both stability and operational flexibility. Small Modular Reactors (SMRs), with their modularity, reduced geographical footprint, and capacity for flexible operation, have emerged as promising resources for supporting modern power systems. However, a comprehensive evaluation of their technical performance across steady-state conditions, fault-induced disturbances, and economically optimized dispatch is necessary to understand their role in future grid architectures. This thesis provides an assessment of SMR capabilities using benchmark test systems, data-driven forecasting, dynamic simulation, and unit commitment modeling to evaluate how …

Modeling Aerosol Transport During High Particulate Matter Episodes In El Paso-Juarez Region And Mitigating Mining-Related Emissions Of Rare Earth Elements (Rees) To The Air, Suzan Aranda Luna

Open Access Theses & Dissertations

This dissertation examines the use of the HYSPLIT model to develop a methodology for the transport and dispersion of air masses affecting particulate matter (PM) concentrations in the El Paso Region, and bioleaching experiments as an alternative to mitigating rare-earth concentrations in the air. Chapter 2 describes the study methodology, 3 and 4 cover the modeling methodology using two-representative high PM2.5 episodes, occurring on February 28, 2024, and June 19, 2024, respectively. These sections encompass the analysis of backward trajectories using four different meteorological datasets to build trajectory frequency maps, the exploratory model analysis of modeled outputs from lower to …

Computational Methods For Complex Electromagnetic Geometries And Media, Edgar Bustamante

Open Access Theses & Dissertations

Additive manufacturing has enabled electromagnetic devices with increasingly complex geometries, but existing numerical tools remain limited in their ability to model and design such structures. This dissertation presents two major advancements that address these restrictions in the finite-difference frequency-domain method (FDFD) and the spatially-variant lattice algorithm (SVLA). These two numerical methods provide a foundation for future exploration in the simulation, optimization, and realization of next-generation electromagnetic devices. First, a general bianisotropic FDFD formulation based on the vector wave equation is presented that enables practical modeling of metamaterials using effective medium homogenized parameters rather than explicitly resolving subwavelength metamaterial features. The …

Mbse For Process Analytical Technology- Bwon Analysis Case Study, Arnaldo Garcia Cervantes

Open Access Theses & Dissertations

Volatile Organic Compound (VOC) emissions from industrial sources, particularly Benzene, present significant environmental and public health challenges. Regulatory frameworks, such as the U.S. Environmental Protection Agency’s Benzene Waste Operations NESHAP (BWON), mandate strict monitoring of control devices, specifically carbon adsorption canisters, to prevent emission breakthrough. However, current industry practices rely heavily on manual Method 21 testing, a labor-intensive process that creates lagging indicators and increases the risk of non-compliance events. This thesis proposes the design and development of an on-line, automated fugitive emissions monitoring system tailored for carbon canisters using Model-Based Systems Engineering (MBSE). Utilizing the Object-Oriented System Engineering Method …

¡Maestra, Ya Le Entiendo! Teachers And Students Creating A Language-Rich Learning Environment With Available Language Resources And Students’ Funds Of Knowledge, Yolanda D. Castro

Open Access Theses & Dissertations

This qualitative study investigates how dual language educators in elementary schools along the U.S.–Mexico border create language-rich learning environments with the Spanish resources available to them. Motivated by longstanding shortages of adequate Spanish instructional materials in bilingual classrooms, this study examines the extent to which this challenge persists in contemporary educational contexts. Grounded in translanguaging theory (de la Piedra, Araujo, & Esquinca, 2018; Flores & Chaparro, 2018; Otheguy, García, & Reid, 2015) and the funds of knowledge framework (González, Moll, & Amanti, 2005), the study explored: (1) the materials provided by districts and schools, (2) the challenges teachers face with …

Development Of Oxide And Oxynitride Thin Films For Advanced Optical Applications, Nathan Christopher Episcopo

Open Access Theses & Dissertations

To develop Ga2O3 and TiOₓNᵧ thin films for optical applications, the process–structure–properties relationship was investigated using a comprehensive set of characterization techniques to establish the atomic structure and composition of the films in relation to the deposition conditions. The results provide critical insights into how deposition parameters influence the atomic structure and composition during magnetron sputtering. Furthermore, the correlation between atomic structure and composition with the optical and electrical properties of the films was examined to determine how variations in these factors affect functional performance. Collectively, these findings offer the necessary information to target desirable optical properties for Ga2O3 and …

Intelligent Predictive Frameworks Under Data Scarcity And Uncertainty, Solayman Hossain Emon

Open Access Theses & Dissertations

Modern predictive systems frequently operate under conditions of limited annotated data, high uncertainty, and the need for reliable decision-making. When the predictive models expand across heterogeneous data types (e.g., spatial, temporal streams), the challenge lies not only in accurate prediction but also in adapting in data distributions shifts or label scarcity. To address these issues, this thesis explores an Intelligent Predictive Framework that operates robustly under data scarcity and uncertainty across two distinct domains: medical imaging (spatial) and time-series forecasting (temporal). In the first part of this work, a semi-supervised mean teacher (MT) paradigm is tailored for medical image segmentation …

Unmixing In Very High Spatial Resolution Hyperspectral Images, Ana C. Chavez Lopez

Open Access Theses & Dissertations

Hyperspectral Imaging (HSI) captures hundreds of contiguous narrow wavelength bands across the optical region of the electromagnetic spectrum collecting the spectral signature of materials in the field of view of the sensor enabling detailed analysis of each pixel's spectral signature. Satellite or airborne remote sensing systems often capture imagery with low to moderate spatial resolution (LMSR). At these resolutions, the measured spectral signature is a mixture of the signatures of the materials within a single pixel. This mixing of spectral information makes analysis and material identification difficult. Hyperspectral unmixing is an analysis technique that decomposes a pixel's spectrum into constituent …

From Morphology To Machine Learning And Genomics: Understanding Phenotypic Variation In Wild Ducks, Sara Gonzalez

Open Access Theses & Dissertations

Understanding the genetic underpinning and distribution of phenotypic variation within and between divergent groups is core towards shedding light into how populations diverge and adapt, as well as how hybridization breaks or builds on these scenarios; and thus, central to evolutionary biology. In wild organisms, however, quantifying and linking phenotypic traits to underlying genetic processes, like mutation, gene expression, epigenetics and allele interactions, remains challenging. This difficulty arises from the complex interplay between morphology, environment, and gene regulation, as well as the logistical barriers of collecting and standardizing large-scale data across individuals and populations. As a result, researchers are increasingly …

A Half Century Of Biophysical Change In Polygonized Tundra On The Coastal Plain Of Northern Alaska, Mariana Mora

Open Access Theses & Dissertations

Climate change is amplified in the Arctic. As a result, Arctic tundra landscapes are undergoing physical changes through accelerated thaw and ice-wedge degradation. Understanding the magnitude and direction of these changes in the Arctic is a necessary step toward understanding the response of the Arctic to climate change and feedbacks to the Climate System. Through repeat measurements collected from 1973 through 2018, we were able to assess decadal time scale changes in polygon geomorphology, thaw depth, land surface compression and expansion, and vertical elevation within a highly polygonized tundra system, and their implications when scaled to a regional level. This …

Evaluating Large Language Models For Requirements Engineering And Verification: A Comparative Analysis Of Gpt-5 And Gemini 3 Pro, Guadalupe Nevarez

Open Access Theses & Dissertations

Large Language Models (LLMs) are increasingly viewed as viable tools for Systems Engineering, yet empirical data regarding their effectiveness in generating engineering-quality requirements remains limited. This thesis compares the performance of GPT-5 and Gemini 3 Pro in generating system functional requirements for the Miner Guardian Drone, a prototype UAV designed for minefield remediation. Both models were provided with identical prompts and tasked with producing 15 functional requirements. Two independent raters evaluated the outputs using a nine-dimensional quality rubric aligned with IEEE 29148 and INCOSE guidelines to ensure rigorous assessment. The difference between the models was analyzed using descriptive statistics and …

One Step Fabrication: Software-Automated Printed Circuits Via Multi-Material Additive Manufacturing, Gabriel Sanchez

Open Access Theses & Dissertations

As of now, the creation of 3D printed components faces many issues regarding stability, repeatability, and manual labor. Existing methods lack an integrated software framework that automates circuit generation while ensuring predictable behavior in printed geometries. In this work, circuits are modeled by leveraging distributed equations that reduce to lumped approximations when the printed geometry remains uniform. The system is implemented through a parametric, domain-specific programming workflow and evaluated across 100 Hz to 100 kHz to assess the accuracy of the predicted electrical values. Printed results were validated by empirical studies involving an RLC meter and by comparing both theoretical …

Development And Optimization Of A Deep Level Transient Spectroscopy System, Samuel Ruiz

Open Access Theses & Dissertations

Deep-level transient spectroscopy (DLTS) remains one of the most widely used techniques for identifying electrically active defects that affect leakage current, carrier lifetime, and overall reliability in semiconductor devices. Legacy boxcar or capacitance meter implementations, however, often struggle with limited signal-to-noise ratio, labor-intensive data collection, and poor adaptability across diverse material systems. This thesis presents the design and optimization of a semi-automated, lock-in-amplifier-based DLTS platform. By pairing a Zurich HF2LI with PID-controlled cryogenic sweeps, precision signal generation, and MATLAB driven acquisition and processing scripts, the system will (i) enhance SNR through phase-sensitive detection, programmable low pass filtering, and parasitics calibration; …

Image And Signal Processing Methods For Clinical Decision Support: Reference-Based Lung Segmentation On Chest X-Rays And Ecg-Based Study Of Acute Hyperkalemia Using Machine Learning, Basavarajaiah Shanmukhayya Totada

Open Access Theses & Dissertations

ABSTRACT

Study-I: An Image Processing Pipeline for Reference Guided Lung Region Detection in Chest Radiographs with Shape Similarity Matching Accurate and reliable segmentation of the lung region in chest X-ray (CXR) images is essential for computer-aided diagnosis (CAD) systems, particularly in the early detection and monitoring of lung disorders. Traditional segmentation techniques often rely on manual annotations, limiting scalability and adaptability. The proposed reference-guided approach selects the most similar healthy CXRs dynamically, ensuring flexibility while benefiting from dataset-specific reference images. Building upon prior approaches that utilize shape similarity-based selection and SIFT-flow, this study introduces a fully automated segmentation pipeline that …

What Limits Dryland Ecosystems? Patterns Of Soil Fertility And Resource Limitation In The Chihuahuan Desert, Dylan Stover

Open Access Theses & Dissertations

Human activities are substantially altering global resource cycles with widespread implications for biogeochemistry and ecosystem functioning globally. Drylands, regions where precipitation is outweighed by water losses, are especially sensitive to these large shifts in resource cycles due to their inherently low and variable resource availability. In these regions, resource availability and biological activity are often concentrated around plants – or fertile islands – and predominantly driven by pulses of water. However, our knowledge of the processes influencing biological productivity in drylands – patterns of soil fertility and resource limitation – remains lacking, and their unique biogeochemical and biological processes create …

A Unified Framework For Embedding-Based Synthetic Data Generation With High Cardinality Categorical Features, Cesar Iram Vazquez

Open Access Theses & Dissertations

High-cardinality categorical variables remain difficult to model in tabular data, where classical encoders encounter sparsity, susceptibility to leakage, and the loss of meaningful relational structure. This dissertation develops a unified framework for learning, evaluating, and synthesizing representations of such variables using both traditional encoders and modern embedding methods, including Word2Vec, FastText, Node2Vec, TF–IDF/SVD, and supervised entity embeddings. The framework is applied across three benchmark datasets (Adult, PetFinder, Breast Cancer) and a hierarchical educational case study (IPEDS/CIP). Embedding quality is examined through both downstream predictive performance and structure-focused diagnostics that quantify neighborhood behavior and geometric coherence. To assess whether synthetic data …

Metal Zonation And Evolution Of The Bronson Slope Porphyry Cu-Au-Mo Deposit In The Iskut Region Of British Columbia, Canada, Luis Jacobo Yagual

Open Access Theses & Dissertations

Bronson Slope is a Cu-Au-Mo porphyry deposit located within the Stikine Terrane in the Golden Triangle District of northwestern British Columbia, Canada. This deposit represents a complex, multistage magmatic-hydrothermal system emplaced into sedimentary and volcanoclastic rocks of the Triassic Stuhini Group. Bronson has an inferred resource of 517.3 Mt at 0.33 g/t Au, and 0.09% Cu. This study integrates detailed and quick logging from 20 drill holes, totaling 20,296m, SWIR spectral analysis, ICP-MS geochemistry, XRF analysis, magnetic susceptibility measurements, geochronology, and 3D models developed in Leapfrog Geo which define the stratigraphy, intrusive geometry, extension, alteration footprint assemblage, metal zonation, and …

Algebraic Approach To Data Processing: Techniques And Applications, Julio Urenda

Open Access Theses & Dissertations

In many areas of human knowledge, symmetries and invariances play an important role. In fundamental physics, starting with Relativity Theory, new physical theories have been formulated in terms of invariances and of the corresponding transformation groups – i.e., in terms what a mathematician would call an algebraic approach. In engineering, devices like wind tunnels, which are based on scale-invariance, enable us to test smaller-scale models of the actual designs. In biological sciences, symmetries and invariances are extremely important in analyzing the shape and functioning of living beings, from mammals to viruses. Invariance and symmetry – in the form of fairness …

Self-Assessment In Calculus I, Bertha Naa Dei Neequaye

All Graduate Theses and Dissertations, Fall 2023 to Present

The purpose of this research investigate how undergraduate students in Calculus I at Utah State University learn and reflect on their level of understanding of Calculus I. In the study, self-assessment practices refer to students reflecting on what they have learned, rating their level of understanding and providing examples that illustrate their level of understanding. The structured and unstructured self-assessment rubrics were the two types of self-assessment rubrics used in the study. The structured self-assessment rubric provides a clear list of objectives of Calculus I topics for students to rate themselves on, while the unstructured self-assessment rubric is an open …

Fast Computation Of The Friction Stir Welding Process With Model Order Reduction, Joshua Kay

All Graduate Theses and Dissertations, Fall 2023 to Present

Friction stir welding (FSW) is a manufacturing process used to join materials through intense heat and pressure. To better understand and optimize this FSW process, mathematical models incorporating non-Newtonian Navier-stokes equations for large plastic deformation and heat equation for the heat transfer are used to simulate the FSW process. However, solving these coupled and nonlinear equations with high accuracy requires significant computational power and time. This thesis has applied model order reduction, more precisely the Proper Orthogonal Decomposition (POD) and Discrete Empirical Interpolation Method (DEIM), to efficiently solve the FSW system in low-dimensional space. Slight modifications are made regarding the …

The Effects Of Secondary Students Using Metacognitive Strategies On Reading Comprehension Scores, Georgia Miller

All Graduate Theses and Dissertations, Fall 2023 to Present

This study focuses on researching the use of metacognitive strategies on secondary students reading comprehension scores. Metacognitive strategies are strategies that help students become more aware of their own thought process and learning. The metacognitive strategies used for this study were self-monitoring, self-regulation, self-questioning as well as the use of vocabulary knowledge. The study takes place in an intermountain west charter high school Reading for Pleasure course for students ninth through twelfth grade. All students within the Reading for Pleasure course received specialized reading instruction over a six-week term from the researcher. All students received approximately 360 minuets of specialized …