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.

Investigation Of Hot Mix Asphalt Aging Effect On Binder Performance, Zahra Mohajeri

Open Access Theses & Dissertations

Asphalt roads continuously experience physicochemical changes under the combined influence of oxygen, heat, ultraviolet (UV) radiation, and water. Oxidation increases molecular polarity and association, causes maltenes loss, and continues hardening the asphalt binder, reducing ductility, stress-relaxation capacity, and resistance to cracking (Petersen 1982; Colbert and You 2012). Because aging is a cumulative process beginning at plant production, accelerating during construction/compacting, and continuing in service, the laboratory tests and indices must capture the extent of short-and long-term aging to support performance-related specification and Balanced Mix Design (BMD) (AASHTO R30 2022; Kim et al. 2017). This chapter reviews: (i) laboratory and field-representative …

Decoupling Piezoelectric And Pyroelectric Effects In Anisotropic Polymer-Ceramic Lattices Produced Via Fused Filament Fabrication, Sofia Alexandra Perez

Open Access Theses & Dissertations

This thesis investigates how multi-material fused filament fabrication (FFF) can be used to engineer lattice structures that decouple piezoelectric and pyroelectric responses within a single polymer–ceramic composite. A hybrid ABS–BaTiO3/PLA lattice—referred to as the Hybrid PIZCAL—was designed to direct mechanical strain along the Z-axis while suppressing deformation in the transverse directions. After thermal poling, the lattice exhibited a 293% increase in Z-axis voltage sensitivity compared to a monolithic ABS–BaTiO3 cube and significantly reduced off-axis electromechanical output. Finite element simulations and directional compression testing confirmed that geometric anisotropy and material zoning produce strong, axis-selective piezoelectric behavior. The second part of this …

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 …

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) …

Predicting Newsworthiness Of California Bill Discussions, Venkata Kedarnath Chaturvedula

Master's Theses

Among various California bill hearings, it is crucial to identify which hearings are most likely to receive media coverage, as this highlights the importance of the bill and the hearing, while also underscoring its societal impact. Digital Democracy, established at Cal Poly’s Institute for Advanced Technology and Public Policy, provides users access to a distinctive dataset and information about state legislative committee hearings, hearing transcripts, assets, bill information, etc.

This thesis presents a machine learning framework for predicting whether California legislative bills are likely to receive media coverage. Drawing on a dataset of legislative ”tip sheets” provided by Digital Democracy …

Analyzing Patterns In Hofstede’S Cultural Dimensions Towards Individual Ai Receptiveness For Affective Experiences, Maggie Yang

Master's Theses

The use of artificial intelligence (AI) has significantly advanced efficient decision-making, with trust in algorithmic decisions shown to vary by cultural upbringing [1]. As AI becomes increasingly embedded in everyday life, it is essential to examine how cultural values affect trust in AI in subjective contexts that extend beyond purely quantitative analysis, like the personal interpretation of art. This work utilizes Hofstede’s cultural dimensions to investigate potential patterns in receptiveness towards AI predictions during art interpretation, providing insight into individual susceptibility to bias in AI-assisted affective analysis.

The study leveraged a cultural dimension survey and a custom Java program connected …

Birds In Changing Landscapes: Community Diversity And Breeding Phenology, Lindsay Peria

Master's Theses

Humans are altering the environment in varied and widespread ways. Increasing urban and agricultural development causes changes to habitat and resource availability as well as changes to the sensory environment via light and noise pollution. Climate change also causes more extreme temperature anomalies, storms, and droughts that challenge birds in a multitude of ways. In this thesis, we assessed these impacts of these changes on a local and continental scale. In the first chapter, we assessed the impact of natural, anthropic, and structural characteristics of viticultural land on both taxonomic and structural avian diversity. Loss of habitat from agriculture is …

Divergent Responses Of Branched-Chain And Straight-Chain Lipid Membranes To Butanol Stress Revealed By All-Atom Molecular Dynamics Simulations, Joshua Olaf Aggrey

Electronic Theses and Dissertations

Membrane integrity under chemical stress is critical to cellular survival and industrial microbial bioproduction, yet the molecular basis of bilayer resilience remains poorly understood. Using all-atom molecular dynamics simulation, we compare the effect of increasing concentrations of 1‑butanol on membranes composed of straight-chain (1,2-dipalmitoyl-sn-glycero-3-phosphocholine, DPPC) and branched-chain (1-anteiso-palmitoyl-2-palmitoyl-sn-glycero-3-phosphocholine, APPC) lipids, which differ in the point of attachment of a single methyl group. In the absence of butanol, both membranes exhibit well-ordered architectures consistent with experimental benchmarks; however, under increasing solvent stress, their behaviors diverge markedly. DPPC membranes display gradual thinning, modest area per lipid …

Immersive Learning In Action: A Qualitative Case Study Of High School Teachers’ Experiences With Prisms Learning In Science And Mathematics, Hilary A. Cassidy

Dissertations

The use of virtual reality (VR) in the secondary STEM educational space is increasing as costs to access VR technology decrease. There is a current lack of research supporting the efficacy of virtual reality use in the secondary space to improve student success criteria, particularly for specific VR-based instructional products like Prisms. The purpose of this study was to explore the impact of Prisms VR curriculum from the teacher perspective, with specific attention to student engagement, conceptual understanding, and instructional practices. The goal of the study was to contribute to existing research about the paradigm shift toward active student participation …

A Joint Mindfulness And Growth Mindset Intervention For Reducing Math Anxiety For Pre-Service Elementary Teachers, Evan Czysz

Dissertations

Pre-service elementary teachers (PSTs) have often exhibited high levels of math anxiety, which can negatively influence their confidence, learning, and future teaching in mathematical settings. The purpose of this phenomenological case study was to understand the influences an intervention focused on growth mindset and mindfulness-based practices has on preservice elementary school teachers’ perceptions of mathematics at a mid-sized university in the Rocky Mountain Region of the United States, and sought to answer the following questions: Q1 Does a joint mindfulness-based and growth mindset intervention impact pre-service teachers’ levels of math anxiety? Q2 What were pre-service elementary teachers’ experiences with a …

Using The Time We Have: Exploring Collaborative Instructional Planning For 8th Grade Georgia Studies In A Title I School, Bambara Timmerman

Dissertations

Teacher collaboration in middle schools is often emphasized in educational research and policy, yet content-specific collaboration, specifically for Georgia Studies (GAS), remains underexplored. This participatory qualitative case study explored how middle school GAS teachers perceive the influence of collaborative planning on their self-efficacy, the obstacles they face when attempting to collaborate, and what they perceive would foster a culture that supports ongoing collaborative planning. Grounded in constructivist theory, including social learning theory, situated learning, and social constructivism, this study focused on teachers in a rural Title I middle school. Data collection included demographic questionnaires, interviews, observations, document analysis, and researcher …

Civics Teachers’ Perceptions Of Disciplinary Literacy Strategies That Use Primary Sources: A Case Study, Whitney Williams

Dissertations

This study has been designed as a case study to examine teachers’ perceptions of document-based strategies when combined with primary sources as pedagogical tools. The participants were ninth grade civics teachers. Semi-structured interviews, focused observations, and artifact collection were the sources of collected data. As the researcher, my constructivism guided this study through the lens of Albert Bandura’s social cognitive theory (SCT). Therefore, the participants’ perception will be interpreted through SCT concepts such as personal influences, behavioral influences, and environmental influences. Findings show a handful of disciplinary literacy strategies that occurred most often across all participants. Teachers valued an emphasis …

Detection Of Phase-Binning And Interpolation Artifacts In 4-Dimensional Computed Tomography Imaging Using Deep Learning And Rule-Based Approaches, Jorge Cisneros, Nathan H. Feldt, Yevgeniy Vinogradskiy, Richard Castillo, Edward Castillo

Department of Radiation Oncology Faculty Papers

BACKGROUND: Four-dimensional computed tomography (4DCT) imaging is a crucial component to lung cancer radiotherapy planning and enables CT-ventilation-based functional avoidance planning to mitigate radiation toxicity. However, 4DCT scans are frequently impaired by acquisition artifacts that corrupt downstream analyses that depend on lung segmentation and deformable image registration, such as CT-ventilation and dose accumulation.

PURPOSE: This study develops 3D deep learning models to identify phase-binning artifacts at the voxel level and a heuristic, rule-based method to identify interpolation slices within 4DCT images.

METHODS: We introduce a generator that systematically inserts synthetic phase-binning and interpolation artifacts into any artifact-free breathing phase obtained …

Reducing Sleep-Related Infant Deaths In Douglas County, Lauren J. Maskin

Capstone Experience: Master of Public Health

Douglas County, including the city of Omaha, covers 339.6 square miles along the border of the Missouri River in Nebraska with a population of 517,110 (https://www.douglascounty-ne.gov/) and is one of seven large urban counties in the state. There are approximately 8,000 infants born in Douglas County annually (Nebraska Vital Statistics Birth Dashboard). The Douglas County Health Department (DCHD), established in 1854, is one of the oldest county health departments in the state and manages multiple public health projects annually. In 2024-2025, a renewed focus for DCHD has been its infant mortality rate (IMR). In 2024, 44 infant mortalities occurred in …

Silent Cries: Analyzing The Psychological Profiles Of High School Shooters, Kayla N. Martinez

Honors Program Theses and Research Projects

Over the past two decades, school shootings have increased in frequency and severity in the United States, leaving schools, families, and communities with long-lasting trauma. Despite experiencing school shootings for more than 20 years, protocols put in place regarding school shootings seem to only be reactive rather than proactively identifying and preventing the occurrence. The purpose of this thesis was to analyze behavioral patterns high school shooters tend to exhibit using multiple factors and propose potential preventative strategies to reduce the number of incidents. This study relies on secondary data analysis in which behavioral, mental, and environmental factors were examined …

Evaluating The Impact Of Evidence-Based Guidelines On Corticosteroid Prescribing For Acute Upper Respiratory Infections In Outpatient Primary Care, Cody Allen Boyd Hyatt

Doctoral Projects

Inappropriate corticosteroid prescribing for acute upper respiratory tract infections (AURTIs) remains a prevalent issue in outpatient primary care despite limited evidence supporting their use in otherwise healthy adults. This Doctor of Nursing Practice (DNP) project aimed to reduce inappropriate corticosteroid prescribing for AURTIs by implementing an evidence-based clinical practice guideline over an eight-week period in a rural primary care setting.

The doctoral project employed pre- and post-intervention design. Providers were introduced to the corticosteroid guideline derived from the 5-Minute Clinical Consult, emphasizing appropriate use criteria for corticosteroids in AURTI cases (Unbound Medicine Inc., 2025). Educational outreach and clinical reminders …

Outcomes And Impact Of An E-Commerce Extension Program In Rural Utah, Amanda D. Ali, Paul Hill

Outcomes and Impact Quarterly

Utah State University Extension’s E-commerce Accelerator (ECA), a mentoring service of the Rural Online Initiative, provides hands-on e-commerce training to small rural businesses in Utah. From January 2024 to July 2025, thirty-five (35) businesses have successfully created online sales websites, with 27 (68%) reporting increased sales revenue.

Floodplain Lake Hydrodynamic And Morphodynamic Connections Through Hydraulic Modeling Along The Pee Dee River, Sc, Charles Cj Mina

Electronic Theses and Dissertations

Rivers have been essential in the success of humankind. This reliance has created a vested interest in studying the rivers' environmental history through using floodplain deposits, with the assumption that coarser sediments correlate to higher discharge floods. However, shifting hydrological connectivity and hydrodynamics can complicate this correlation in primary repositories of flood deposits, oxbow lakes, by altering the texture of sediments delivered to them. Studying these complications is essential for quantifying paleoflood magnitude using the sediment record, but has been difficult, as the currently used index of hydrological connectivity relies on water stage, which does not reflect the sediment flux …

Collective Action Under Repressive Conditions: Integration Of Individual, Group, And Structural Level Research, Recommendations, And Reflections, Arin H. Ayanian, Aya Adra, Fouad Bou Zeineddine, Rim Saab, Johanna Vollhardt, Nicole Tausch

Psychology

Social scientific research from different traditions on collective action under repressive conditions is fragmented across different levels of analysis. The current paper takes a first step toward remedying this fragmentation by reviewing research findings on repression and collective action and organizing them into a multilevel framework. We describe the impact of repression on antecedents of collective action at the (a) individual level (including grievances, emotions, efficacy beliefs, politicized identity, and individual differences), (b) group level (including community cohesion and norms), and (c) structural level (including political opportunities and socioecological conditions). We then present an integrative summary reflecting on the broad …

Essays On The Economics Of Farmland Valuation And Investment In U.S. Agriculture, Colson Tester

Graduate Theses and Dissertations

This dissertation presents three empirical essays that collectively advance the understanding of farmland valuation in key U.S. agricultural regions, emphasizing the critical advantages of comprehensive, transaction-based data over traditional survey methods. Farmland represents a significant portion of agricultural wealth, and its accurate valuation is crucial for farmers, investors, and policymakers, influencing everything from credit access to investment strategies. Historically, research has often relied on subjective survey data, which can suffer from biases, inaccuracies, and insufficient granularity. This dissertation addresses these limitations by leveraging extensive datasets of arm’s-length farmland transactions, offering a more precise and market-driven perspective on land values. The …

Computational Fluid Dynamics Based Optimization Method Applied To Hydrokinetic Turbine Devices, Stuart Glenn Fletcher

Graduate Theses and Dissertations

This thesis presents a computational investigation of optimal kinematic operating parameters governing various hydrokinetic turbines (HKT) systems for the use of power generation within river and tidal environments. Two separate studies are performed. The first study investigates optimal cycle parameters for simple and complex kinematic modes governing the motion of oscillating foil energy harvesters (OFEH). An iterative gradient-ascent optimization method is used to search for local efficiency optima based on an initial set of kinematic parameters. To search the operational space for up to eight degrees of freedom (DOF), a maximin space filling condition was implemented to efficiently compute initial …

Validation Studies Of A Dynamic Hybrid Rans-Les Turbulence Modeling Strategy For Cfd Simulation Of Gas Turbine Component Film Cooling, Cole Simmonds

Graduate Theses and Dissertations

Computational prediction of the flow physics associated with gas turbine film cooling is important for ensuring effective heat transfer design. These flow fields are highly turbulent and anisotropic, making the accuracy and efficiency of the chosen turbulence model an important aspect of performing high quality computational fluid dynamics (CFD) based analysis. Current industry standard Reynolds-averaged Navier-Stokes (RANS) turbulence models such as RANS k-ω SST, while computationally efficient, are subject to relatively high levels of uncertainty in their ability to predict these turbulent flow fields. In contrast, high fidelity methods such as Large Eddy Simulation (LES) are computationally very expensive, while …

Diagnostic Accuracy Of Nanopore Sequencing For Detecting Mycobacterium Tuberculosis And Drug-Resistant Strains: A Systematic Review And Meta-Analysis, Timothy Hudson David Culasino Carandang, Dianne Jaula Cunanan, Gail S. Co, John David Pilapil, Juan Ignacio Garcia, Blanca I. Restrepo, Marcel Yotebieng, Jordi B. Torrelles, Kin Israel Notarte

Ateneo School of Medicine and Public Health Publications

Tuberculosis (TB), caused by Mycobacterium tuberculosis (MTB) infection, remains a significant public health threat. The timeliness, portability, and capacity of nanopore sequencing for diagnostics can aid in early detection and drug susceptibility testing (DST), which is crucial for effective TB control. This study synthesized current evidence on the diagnostic accuracy of the nanopore sequencing technology in detecting MTB and its DST profile. A comprehensive literature search in PubMed, Scopus, MEDLINE, Cochrane, EMBASE, Web of Science, AIM, IMEMR, IMSEAR, LILACS, WPRO, HERDIN Plus, MedRxiv, and BioRxiv was performed. Quality was assessed using the Quality Assessment of Diagnostic Accuracy Studies-2 tool. Pooled …

Two Uncited Latin Resources In King Robert Of Naples’ Sermon On Friendship For The Lombard League, Chris Nighman

History Faculty Publications

This article demonstrates the reception of Thomas of Ireland’s Manipulus florum (1306) and John of Wales’ Communiloquium (ca. 1270) in a sermon by King Robert of Naples (1276-1343) promoting the revival of the military alliance known as the Lombard League, and also his use of the Manipulus in another sermon. A full edition of Robert’s sermon “pro liga Lombardie” is appended. It also corrects the misattribution to Robert of a collection of anecdotes and quotations attributed to ancient philosophers and provides a brief comparative analysis of the short and long recensions of the Communiloquium.

Dielectric Properties Of Surface-Doped Partially Stabilised Zirconia With Ceramic Nanomaterials, Lara Al-Hakeem, Shihab Zaidan, Wafaa Khalef

Journal of Applied Sciences and Nanotechnology

The microstructural and dielectric properties of Yttria-partially stabilized zirconia (Y-PSZ) were studied before and after sintering with BaTiO3 and WO3 doping. After sintering, FE-SEM analysis revealed increased grain coalescence and growth, with BaTiO3 causing 300 nm grain expansion and WO3 promoting uniform grain distribution without significant grain size increase (~200 nm). These microstructural changes dramatically altered dielectric behavior. All sintered samples had higher dielectric constants than pre-sintered ones between 100–1000 kHz due to reduced porosity and enhanced homogeneity. Dielectric constant was highest in BaTiO3-doped Y-PSZ at lower frequencies, while WO-doped showed superior frequency stability and lower dielectric loss across the …

Exploring Synthetic Data Generation For Machine Learning And Statistical Analysis, Aditi S. Gajjar

Master's Theses

In the data-driven machine learning and statistical analysis world, real-world data availability is often constrained by privacy concerns, access restrictions, or resource limitations. To address these challenges, synthetic data provides a groundbreaking solution, enabling academics and data scientists to generate artificial datasets that mimic real-world data for model development and testing in a controlled, privacy-preserving environment. The syntheticDatasets package represents an R-based counterpart to Python's widely-used Scikit-learn dataset generators, adapted to meet the needs of statisticians, educators, and data scientists primarily working in the R programming ecosystem.

This thesis explores the design and implementation of the syntheticDatasets package, focusing on …

Performance Enhancement For Rufa: Rapid Urban Forest Assessment, Nicholas Tan

Master's Theses

Urban forests are crucial to the livability and resilience of cities, offering critical ecosystem benefits such as air quality enhancement, temperature regulation, and biodiversity. Managing said urban forests is essential to ensure their sustainability and adaptability to rapidly changing environmental and climate conditions. The Rapid Urban Forest Assessment (RUFA) tool was developed to address the need for a standardized approach to evaluating and comparing urban and community forestry programs. By analyzing and aggregating tree-specific data across California, such as canopy cover, tree counts, and diversity scores, RUFA assigns a comprehensive urban forestry score for each city. This score allows for …

An Analysis Of Neuroidal Memory Formation Within D. Melanogaster, Jerry Chang

Master's Theses

The Neuroidal model poses a neurobiologically plausible theory for modeling the brain. This symbolic network has been shown to capture realistic memorization behaviors using the JOIN algorithm. The model has also been recently improved by incorporating Watts-Strogatz small-worlds within its base structure. From the efforts of neuroscience researchers, we have access to the Drosophila melanogaster (D. melanogaster) fruit fly’s connectome, which has been found to also contain small-worlds in this thesis. By synthesizing the Ocellar Ganglion (OCG) region of Drosophila, we compare a digitized version of a real-world brain with an instance of the Neuroidal model. In this thesis, we …

Reverse Design Of Solid Rocket Grain Geometry, Yechan Kang

Master's Theses

The reverse design of solid rocket motors remains a challenging process due to the nonlinear relationship between the grain geometry and the internal ballistics. The reverse design process involves obtaining an optimal grain geometry given a target performance curve set by mission requirements, which is the inverse problem of the forward design. The purpose of this study is to assess the validity and implementation of neural network and simulated annealing algorithms to perform the reverse design process. A modified phase field model of the eikonal equation is derived to simulate the evolution of combustion surfaces over time, enabling burn back …