Digital Commons Network^™

Facilitating Deep Learning Performance Analysis Through Automated Roofline Model Generation, Irvin Lopez-Audetat

Open Access Theses & Dissertations

This thesis presents a tool to profile deep learning (DL) and machine learning (ML) models by collecting FLOPs, memory movement, and timing data through cyPAPI to generate roofline performance models. The tool is containerized for portability and reproducibility, integrates directly with PyTorch workflows, and provides fine grained insights into computational bottlenecks across model components. Unlike prior system-level or benchmarking-centric tools, this project empowers developers and researchers with an accessible, modular framework for performance analysis and optimization.

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; …

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 …

Hubert-Based Models And Evaluation Strategies For Pragmatically-Faithful Speech To Speech Translation, Javier Vazquez

Open Access Theses & Dissertations

Pragmatic fidelity in speech-to-speech translation (S2ST) has largely been understudied, leading to communication tools inadequate to support non-superficial dialog. We aim to improve pragmatic faithfulness in English-Spanish translation through the development of machine learning models that are able to predict a corresponding pragmatic representation in the other language. To evaluate performance, we developed a pipeline that utilizes a recently-developed pragmatic similarity evaluation metric to compare models. Further, we developed models that exploit HuBERT features as these have been found suitable for various prosody and pragmatics related tasks. Our models outperformed human and state-of-the-art predictions, albeit the methodology being limited to …

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 …

Physics-Guided Strategies For Enhancing Neural Networks Trained With Limited Data, Jose Guadalupe Perez Zamora

Open Access Theses & Dissertations

Deep neural networks excel at a wide range of processing tasks across various disciplines. However, the quantity and quality of data significantly impact network performance. In specialized domains, high-quality datasets are often difficult to gather, interpret, and curate for effective learning. Few-shot learning techniques, including transfer learning, data augmentation, and meta-learning, have emerged to address these constraints.

We propose three physics-guided strategies for enhancing neural networks trained with limited data: (1) combining existing models like LSTMs with Physics-Informed Neural Networks through two-branch architectures that merge their outputs, (2) deriving custom physics-informed data augmentation algorithms to expand limited datasets, and (3) …

Smags-Lasso: A Novel Feature Selection Method For Sensitivity Maximization In Early Cancer Detection, Hamid Khoshfekr Rudsari, Sara Khorami-Sarvestani, Johannes F Fahrmann, James P Long, Samir Hanash, Kim-Anh Do, Ehsan Irajizad

Faculty, Staff and Student Publications

Background: Sensitivity and specificity are foundational metrics for cancer detection tools. However, most machine learning algorithms prioritize overall accuracy during optimization, which fails to align with clinical priorities of early detection. We aim to develop a feature selection machine learning algorithm while maximizing sensitivity at a given specificity.

Methods: We developed SMAGS-LASSO, a machine learning algorithm that combines our developed Sensitivity Maximization at a Given Specificity (SMAGS) framework with L1 regularization for feature selection. This approach simultaneously optimizes sensitivity at user-defined specificity thresholds while performing feature selection. SMAGS-LASSO utilizes a custom loss function with L1 regularization and multiple parallel optimization …

Normalization Of Temperature Effects For Quality Assurance Of Quantitative Prostate Apparent Diffusion Coefficient Imaging Across Multiple Sites, Ken-Pin Hwang, Joshua Yung, R Jason Stafford, Caroline Chung, Aradhana M Venkatesan

Faculty, Staff and Student Publications

Background: Apparent Diffusion Coefficient (ADC) as measured by diffusion weighted imaging is known to negatively correlate with prostate tumor aggressiveness. Heterogeneity in system and protocol performance causes potential variability in ADC acquired across a large scanner network, prompting a need to evaluate quantitative ADC from a prostate-specific MR diffusion protocol as part of quality assurance (QA). Due to the temperature dependence of ADC, repeatability and reproducibility assessments typically require phantoms to maintain a temperature of 0°C, imposing a considerable burden when assessing large numbers of scanners.

Purpose: To develop a QA procedure at room temperature for assessing the reproducibility of …

Benthic Infaunal Responses To Shoreline Restoration, Jessica Lauren Cline

Theses and Dissertations

In the age of increasing urban coastal sprawl, natural shorelines are being replaced by hard armoring structures, which result in the loss of valuable ecosystem services. Hybrid living shorelines, areas that include limited and less intensive armoring strategies paired with the integration of plants and other natural materials, present an opportunity to marry the need for more aggressive stabilization with the continued preservation of ecosystem functions and biological communities. This project uses benthic infauna to evaluate the success of a living shoreline installation in Palm Bay, Florida. The deployment features experimental treatments of breakwaters and red mangroves to explore how …

Qualitative Stereo Vision Using Distributed Extended Waltz Filtering, Ben Mathew

Theses and Dissertations

Stereo vision is a fundamental problem in computer vision, aimed at reconstructing three-dimensional scene structure from two or more two-dimensional images. Traditional stereo algorithms rely on quantitative disparity estimation, often constrained by calibration precision, lighting variations, and surface texture. In contrast, our proposed Qualitative Stereo Vision seeks to understand depth relationships and spatial configurations from multiple planar views through symbolic reasoning and constraint satisfaction, offering a more flexible and cognitively plausible approach to scene interpretation.

This dissertation presents a novel framework called Distributed Extended Waltz Filtering, designed to provide qualitative stereo vision, particularly in the presence of occlusions—a persistent challenge …

The Blackstone Ratio, Modified, Murat C. Mungan

Faculty Scholarship

In his discussion of evidentiary policies, Blackstone famously noted that ‘it is better that ten guilty persons escape than that one innocent suffer’ (Blackstone 1769). The conventional wisdom among lawyers, judges as well as academics holds that accepting this statement as a maxim necessitates the adoption of pro-defendant evidentiary rules. It is also commonly believed that costs associated with false convictions being greater than those associated with failures to punish offenders due to the presence of punishment costs provides a utilitarian rationale for Blackstonian principles. After formalizing Blackstone ratios (either as marginal rates of substitution or, alternatively, as the ratio …

Employers’ Perceptions Of Workplace Readiness Skills, Tabitha S. Young, Natalie K. Ferand

Journal of Research in Technical Careers

Employability skills are continually changing, and the workforce provides the transparency needed for the success of business employment. Workplace readiness skills and human capital theory form the backbone for organizational success and sustainability. This study examined employers’ perceptions of workplace readiness skills at the expected proficiency level of an entry-level employee, the average level of skill for an entry-level employee, and the level of importance of the skill to their industry. The Virginia Workplace Readiness Skills have impacted employers and prepared students for the workplace. The results indicated that the workplace readiness skills mentioned in the literature align with the …

Reported Value Of Culturally Responsive Teaching Practices Of Virginia Agricultural Education Teachers, Natalie K. Ferand, Kendrick Spencer, Bradley Bowen

Journal of Research in Technical Careers

To address the increasing diversity in schools and the monolithic culture of teachers, researchers have called for pedagogies that reflect the diverse and pluralistic identities of students. While core academic areas have long adopted culturally relevant pedagogy, school-based agricultural education (SBAE) has lagged behind. This study aimed to determine the views of agricultural education teachers in Virginia on culturally responsive pedagogy dispositions and identify areas of professional development need. Teachers valued the differences among students and the communities in which their schools are located. However, results revealed a need for professional development in using the local community as a resource …

Online Experiential Learning In Career And Technical Education, Matthew Bornak

Journal of Research in Technical Careers

This scoping review investigates the integration of OEL into Career and Technical Education (CTE) programs. Using Arksey and O’Malley’s five-step scoping review framework, articles were identified through ERIC and Google Scholar and managed in Zotero. MAXQDA was used for coding, revealing thematic clusters related to modalities (synchronous, asynchronous, hybrid), technologies (LMS, AR/VR, simulation tools), and learner characteristics (nontraditional students, CTE-specific learning styles). The review highlights the conceptual anchors of Kolb’s Experiential Learning Theory, Carver et al.’s Experiential E-Learning Model, and Baasanjav’s online experiential design. Findings reveal that while OEL in CTE remains underexplored, it offers potential to increase accessibility, inclusivity, …

Spotted Seal Coastal Haul Out Behavior In Arctic Alaska, Maeghan Connor

Biological Sciences

Hauling out - the act of exiting the water to rest, molt, breed, and pup on solid surfaces - is a key behavior of pinnipeds worldwide. Unlike other ice seals (i.e., ice-associated phocid species), spotted seals (Phoca largha) in Alaska frequently use terrestrial substrates to haul out during the summer and fall open-water period in the Chukchi and Beaufort Seas. Despite being a core aspect of spotted seal ecology, their terrestrial haul out behavior remains understudied. To address this, we analyzed data collected from 2020 - 2022 near two known haul out sites in Dease Inlet, Alaska, including time-lapse camera …

Exploring Phenological Mismatch And The Role Of Aquatic Insects For Olive-Sided Flycatchers (Contopus Cooperi) Breeding In Boreal Alaska, Ian Kwit

Biological Sciences

Migratory insectivorous birds are an increasingly threatened group worldwide. These birds rely on an ephemeral resource of insects during a short window in which they arrive at breeding territories to rear young. Climate change has the potential to create a phenological mismatch between the timing of bird breeding and the availability of key insect prey. This study investigates the potential for such a phenological mismatch in a population of olive-sided flycatchers (Contopus cooperi). We used data on breeding phenologies and the composition of insect communities around nests in three regions of Alaska, Anchorage, Fairbanks, and Tetlin National Wildlife Refuge, to …

Evaluating Dietary Protein Sources And Protein Balance In Herbivorous Mammals Using Stable Isotope Analysis Of Amino Acids, Garrett A. Savory

Biological Sciences

Knowing how large herbivorous mammals acquire nutrients is critical to understanding how they can survive and reproduce in seasonally nutrient-limited landscapes. Gut bacteria and other microorganisms in herbivores digest plant fiber, providing energy, and potentially protein. In my first data chapter, I evaluated the importance of dietary and gut microbial protein to herbivores with different digestive physiologies using carbon isotopes of essential amino acids as markers of protein source. Foregut fermenters, moose (Alces dices) and muskox (Ovibos moschatus), and a hindgut fermenter with coprophagy, snowshoe hares (Lepus americanus), derived half of their protein from gut bacteria, whereas horses (Equusferus caballus), …

M-Polar Diophantine Neutrosophic N-Soft Set For Digital Competencies And Traditional Skills: Toward Holistic Training For New Craftsmen, Kaixia Zhuo

Neutrosophic Sets and Systems

No abstract provided.

Earthquake Relocation, Fault Complexity, And Nucleation Patterns In Interior Alaska, Nealey Sims

Geosciences

Interior Alaska is one of the most seismically active intraplate regions in North America, yet its faults remain poorly defined due to diffuse seismicity and limited surface expression. Bounded by the Denali and Tintina fault systems, the region hosts the Minto Flats, Fairbanks, and Salcha fault zones, which produce large earthquakes, as evidenced from the 1937 Ms 7.3 Salcha and 1995 Mw 6.0 Minto Flats events. Despite their hazard potential, these structures have historically been represented as broad seismic zones rather than mapped faults. This dissertation applies mod­ern seismological approaches—network matched filtering, waveform cross-correlation, and rela­tive relocation—to build high-resolution earthquake …

Forecasting Chemoradiation Response Midtreatment For High-Grade Gliomas Through Patient-Specific Biology-Based Modeling, David A Hormuth, Maguy Farhat, Bikash Panthi, Holly Langshaw, Mihir D Shanker, Wasif Talpur, Sara Thrower, Jodi Goldman, Sophia Ty, Calliope Custer, Jeanne Kowalski, Thomas E Yankeelov, Caroline Chung

Faculty, Staff and Student Publications

Purpose: The entire course of radiation therapy (RT) for high-grade glioma (HGG) is currently derived from pre-RT magnetic resonance imaging (MRI). Although it is possible to adapt RT during the course of treatment, it is often guided only by anatomical changes to the tumor. This study seeks to determine if a biology-based mathematical model, parameterized by patient-specific, multiparametric MRI (mpMRI) data, can accurately forecast HGG response during RT.

Methods and materials: Twenty one patients with HGG planned for 6 weeks of concurrent RT and chemotherapy were imaged weekly with mpMRI during RT and at 1, 2, and 3 months post-RT. …

Development And Optimization Of Moxifloxacin Solid Lipid Nanoparticles Via Double Emulsion Organic Solvent Free Technique Applying Box–Behnken Experimental Design, Esraa M. Elshazly, Mona G. Arafa, Samia A. Nour

Pharmacy

The current research proposes the preparation of Moxifloxacin-loaded solid lipid nanoparticles through a solvent-free double emulsion technique, to overcome chronic wound healing limitation. The independent variables: stearic acid, Span 80, and Tween 80 were optimized via Box–Behnken design, based on entrapment efficiency (EE%), zeta potential (ZP), and particle size (PS). To statistically optimize the formulation variables, a three-factor, three-level (3³) design involving 15 runs was employed and optimization was carried out to attain maximum EE% and ZP and minimum PS yielding an overall desirability of 0.851. Results indicated that increasing stearic acid enhanced EE%, Span 80 increase PS, and Tween …

Personalized Risk Prediction For Cancer Survivors: A Generalized Bayesian Semi-Parametric Model Of Recurrent Events With Competing Outcomes, Nam Hoai Nguyen, Seung Jun Shin, Elissa Dodd-Eaton, Jing Ning, Wenyi Wang

Faculty, Staff and Student Publications

Multiple primary cancers are increasingly more frequent due to improved survival of cancer patients. Characteristics of the first primary cancer largely impact the risk of developing subsequent primary cancers. Hence, model-based risk characterization of cancer survivors that captures patient-specific variables is needed for healthcare policy making. We propose a Bayesian semi-parametric framework, where the occurrence processes of the competing cancer types follow independent non-homogeneous Poisson processes and adjust for covariates including the type and age at diagnosis of the first primary. Applying this framework to a historically collected cohort with families presenting a highly enriched history of multiple primary tumors …

Life Cycle Assessment Comparing Electric And Petrol-Powered Rigid Inflatable Boats For Recreational And Harbour-Master Applications, Amir Bordbar, Badr Moutik, Adam Kyte, Simon Ussher, Keri Collins, Marcin Roszkowski, Tony Wilson, Sarah Fear

School of Geography, Earth and Environmental Sciences

This study presents the first cradle-to-grave life cycle assessment (LCA), focusing exclusively on environmental impacts, comparing electric and petrol-powered rigid inflatable boats (RIBs) under low-usage recreational and high-usage harbour-master scenarios. The study follows ISO-compliant LCA methodology and emphasizes transparency in data and assumptions. Ten environmental impact categories were analysed, including global warming potential (GWP), particulate matter formation, acidification, eutrophication, ecotoxicity, and resource scarcity. Results show that switching to electric RIBs reduces GWP by 34 % for recreational and 52 % for harbour-master scenarios, despite higher production-phase impacts across all categories. The electric RIB delivers notable operational benefits in GWP and …

Review Of Resonance: A Sociology Of Our Relationship To The World By Hartmut Rosa, Ryan Derby-Talbot

Turning Toward Being: The Journal of Ontological Inquiry in Education

No abstract provided.

Disclosing That Which Has Been Made Invisible: Collective Ontological Inquiry With Vanessa Machado De Oliveira, Dorothy Cococinno Ladybugboss, Aiden Cinnamon Tea, And Aiden Senior, Raphael Borges, Witneiris Constanzo, Samantha Encarnacion, Kaley Klapisch, Carolyne J. White

Turning Toward Being: The Journal of Ontological Inquiry in Education

An unconventional and collaboratively written text begun as a Book Review that expands into a hybrid Book Review-Notes From The Field-Article as we sought to do justice to our encounter with three provocative books that elicit ontological inquiry inside and outside our classrooms, inquiry that challenges us, confuses us, confronts us to unlearn and loosen the grip of ontological constraints we were thrown into within modernity and our embeddedness within the everyday life. Our reading of these books elicits much needed hope for the precarious times we are living through with this earth.

Historical Context In Mathematics Education: Improving Student Engagement And Achievement, Colette Chilton-Carr

Electronic Theses and Dissertations 2020 - Present

There are many informational gaps in contemporary mathematics education. Students see the mathematical topics they are being taught as facts and procedures unrelated to each other or to themselves as mathematicians. Many ancient developments in the realm of mathematics are still relevant today, showcasing the needs that motivated their longstanding evolution. By including the stories behind the formulas in mathematics classrooms, students from diverse backgrounds can feel seen and connected to their education. The inclusion of the holistic background of mathematics cannot be nurtured in the classroom without buy-in on the parts of both students and instructors, as well as …