Digital Commons Network^™

A Comparative Evaluation Of Feedback Strategies For Enhancing Student Software Test Suite Writing Outcomes, Ashton Alonge

Master's Theses

Background and Context

Software testing is a fundamental component of computer science education, forming the basis for students’ ability to ensure program correctness and reliability. Despite its importance, many students struggle to design test cases that effectively expose faults and achieve meaningful test coverage. Traditional instructional approaches often emphasize code coverage metrics such as line or branch coverage, but these metrics may not adequately capture the quality of student tests. Mutation analysis, which measures how well tests detect small, artificial faults (mutants) introduced into the program, offers a potentially richer measure of test effectiveness. However, little is known about how …

Real Time Markerless 3d Hand Tracking For Intuitive Robotic Arm Control, Dylan G. Featherson

Master's Theses

This thesis presents a real-time, markerless motion-capture system for intuitive control of a multi-degree-of-freedom robotic arm. Using two synchronized RGB cameras and stereo-vision triangulation, the system reconstructs the three-dimensional position of a user’s hand without the need for physical markers or wearable sensors. The reconstructed 3D coordinates are mapped directly to the end-effector position of the Quanser QArm, a four-degree-of-freedom educational manipulator. Developed entirely in Python, the system integrates stereo camera calibration, 3D hand tracking with MediaPipe, coordinate transformation, and inverse kinematics into a unified real-time control pipeline operating at approximately 200 Hz. Calibration is performed through a checkerboard-based stereo …

Generalized Detection Of Animal Behavior Using Accelerometers, Alexander J. Arrieta

Master's Theses

Animal mounted sensors are becoming increasingly used to passively monitor both domestic and wild animals. Advances in lightweight accelerometer and GPS technology have allowed many animals to be fitted with high accuracy sensors for extended periods of time. This leads to new opportunities to study animal behavior without direct observation. However, interpreting the raw data is difficult due to the high volume and missing context of the information. Machine learning techniques excel at extracting information from raw data streams and are excellent candidates for processing the sensor data. However, due to large variance in how different animals execute the same …

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 …

Origami-Inspired Pneumatic Soft Robotic Gripper, Conor J. Schott

Master's Theses

This thesis presents the design and evaluation of a vacuum-actuated, origami-based soft robotic gripper. A custom Sea Urchin crease pattern forms a lightweight folding skeleton that collapses radially under vacuum. The system emphasizes low cost and accessibility through laser cutting, 3D printing, and silicone molding. The Sea Urchin geometry was selected after digital and physical screening of candidate crease patterns for smooth folding, low strain concentration, and uniform inward motion. The folding skeleton is laser cut from 4 mil drafting film and folded into a compliant core. Four membrane configurations were developed: an origami gripper with a 36-inch balloon (Design …

Hallucination Techniques For Self-Supervised Synthetic Datasets For Mobile Robots, Wyatt D. Colburn

Master's Theses

Classical techniques in autonomous navigation struggle in tightly constrained spaces. Machine learning has been shown to perform better in these difficult environments but most techniques require large amounts of navigation experience for training. Using a new machine learning paradigm learning from hallucination (LfH), training data can be collected in a safe environment and not require supervision. Data is collected in real time while an agent performs a random walk in free space, supervision is not required as there are no obstacles for the robot to run into. After a random walk a post processing pipeline will hallucinate a safety corridor …

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 …

Testing For Local Adaptation In Sympatric Monkeyflowers Growing In Serpentine Seeps And Adjacent Rock Outcrops, Avin Niknafs

Master's Theses

Divergent selection across heterogeneous environments can drive ecological differentiation and the evolution of locally adapted populations, even when gene flow occurs. We tested for local adaptation between two sympatric monkeyflowers, Erythranthe guttata and E. serpentinicola (formerly Mimulus), which co-occur on the central coast of California. Erythranthe guttata is a perennial species primarily found in moist serpentine seeps, whereas E. serpentinicola is an annual species restricted to adjacent serpentine rock outcrops. Using a reciprocal transplant experiment with second-generation, greenhouse-derived seed, we quantified germination, survival, and reproductive success across contrasting microhabitats. We further evaluated the relative contributions of species, lineage, …

Impacts Of Halophila Stipulacea Invasion On Organic Matter Dynamics In Thalassia Testudinum Dominated Seagrass Meadows, Puerto Rico, Jonathan D. Herald

Master's Theses

Halophila stipulacea (Forsskål & Niebuhr) is a tropical seagrass native to the Red Sea, Persian Gulf, and Indian Ocean. In 2002, invasive populations of H. stipulacea were identified in the Caribbean Sea where it now forms large meadows, displaces native seagrasses, alters invertebrate and fish communities, and potentially affects organic matter dynamics in invaded meadows. This study investigated differences in organic matter dynamics between meadows of H. stipulacea and native Thalassia testudinum within the Jobos Bay National Estuarine Research Reserve (JBNERR) on the southern coast of Puerto Rico. From March 2023-March 2024, sampling was conducted across four sites to investigate …

Effects Of Urbanization On The Population Genetics And Morphology Of The White-Footed Mouse (Peromyscus Leucopus) Across An Urban–Rural Gradient, Sydney A. Morton

Master's Theses

Urbanization alters landscapes in ways that can reshape wildlife populations by changing habitat connectivity, resource availability, and selective pressures. To investigate how urbanization influences both genetic differentiation and morphology in small mammals, I examined Peromyscus leucopus (PELE) across an urban–rural gradient in northern Georgia. Using RADseq SNP data from PELE individuals across 13 sites, I quantified pairwise genetic differentiation (F_ST) and tested how various environmental variables, including impervious surface cover, human population density, and tree canopy cover, predict genetic differentiation after accounting for geographic distance. Genetic differentiation increased with geographic distance and, after controlling for isolation by …

An Exploration Of Image Segmentation Techniques For Real-Time Product Detection, Andrew C. Dunton

Master's Theses

Recent progress in LLMs enables advanced multimodal understanding, but their high computational cost necessitates monetization strategies like interactive advertising. While bounding boxes show promise for this concept, they can lack precision and visual appeal. Image segmentation offers a superior solution but faces a dual problem: traditional models demand scarce, costly training data, and open-vocabulary segmentation models like SAM are class-agnostic, unable to semantically identify a "consumer product" object class. In this research, we address these limitations by: 1) developing the Prompt-Guided Inpainting Framework (PGIF), which injects negative prompts to generate robustly annotated synthetic segmented product images; 2) investigating the Class-Agnostic …

Climatology Of Northeast Winds In Northern And Central California: A New Characterization Of The Diablo Wind, Alana R. Macken

Master's Theses

Diablo winds in northern California are known for driving some of the most destructive wildfires in state history. The Camp Fire of 2018, which caused at least 85 civilian fatalities, is just one example of the devastating outcomes associated with these rapidly developing downslope windstorms. While they are known to occur most frequently from fall through spring, much about the structure, evolution, and full spatial extent of these events remains poorly understood. Most previous studies have focused on a limited number of high-impact cases or have defined events using humidity-based thresholds in isolated regions such as the North Bay. As …

A Convolutional Neural Network Approach To Breast Cancer Tumor Boundary Detection, James Leah Matlosz

Master's Theses

Breast cancer is the second most common form of cancer and often goes undetected in its initial stages due to its subtle symptoms. As the tumors grow, they become more difficult to surgically remove with clean borders. To minimize the chance of recurrence, a 2D convolutional neural network is developed in this work for delineating tumor boundaries. Specifically, the U-shaped network model is trained, validated, and tested with longitudinal MRI scans of patients diagnosed with breast cancer and undergoing neoadjuvant therapy. For training, image masks were generated as ground truths using signal enhancement ratio segmentation, thresholding, and contour detection. The …

Deep Learning Framework For Option Pricing, Kyle Rytand Bistrain

Master's Theses

Accurately pricing American options with market data presents a significant challenge, as foundational models like the Black-Scholes-Merton (BSM) model rely on assumptions that deviate from real-world financial data -- such as log-normal returns, constant volatility, and no dividends -- and fail to account for the key early exercise feature of American options. While parametric models can adjust for these features, the complexity of the resulting models renders them prohibitively difficult to apply in practice for nonspecialists. In response, modern machine learning (ML) techniques provide a set of flexible and powerful alternatives, and recent research has explored the application of ML …

Gene Expression Of Anthocyanin Pigments In The California Native Plant Leptosiphon Parviflorus: Interactions Between Flower Color Morphology And Abiotic Stressors, Weston Gonor

Master's Theses

For plants to survive in harsh conditions imposed by abiotic stressors, they must develop mechanisms of adaptation. One of the common types of adaptation seen in plants is the production of anthocyanin pigments, which have been shown to protect plants from UV radiation, metabolic stress, and drought. In this study, we used the flower color polymorphic species Leptosiphon parviflorus to investigate the role of anthocyanin pigments in protecting plants from abiotic stress. To accomplish this, RNA samples were taken from flower, leaf and root tissue of different flower color morphs of Leptosiphon parviflorus (Polemoniaceae) grown in high magnesium and water …

Alpine Plants And Climate Change: Tracking Community Shifts In Yosemite National, Brooke L. Wallasch

Master's Theses

As climate change progresses, alpine plant communities are predicted to shift upslope as they track temperature over time. Relative to lowland environments, alpine areas are experiencing a faster rate of temperature change due to a phenomenon referred to as elevation-dependent warming. A common approach for tracking plant communities shifts over time, is to conduct resurveys of the same area at several time points, as the Global Observational Research Initiative in Alpine Environments (GLORIA) has done on mountain summits around the world since 2001. In 2011-2013, GLORIA developed a supplemental survey method whereby belt transects were established downslope of summits in …

Enhancing Non-Player Character Dialogue In Video Gages: An Evaluation Of Large Language Model-Generated Responses, Lam P. Quach

Master's Theses

As video games increasingly emphasize narrative depth and player immersion, the quality of Non-Player Character (NPC) dialogue has become crucial for creating engaging gaming experiences. This thesis investigates the potential of Large Language Models (LLMs) to generate high-quality NPC dialogue by comprehensively evaluating four state-of-the-art models: Gemma 3 27B, Mistral 7B, QWEN 2.5, and LLAMA 3.1. The study employs a mixed-methods approach, combining human evaluation (N=50 participants) with AI-based assessment across five key benchmarks: coherence, personality expression, engagement, style/tone appropriateness, and overall quality. Participants evaluated 32 dialogue samples (8 per model) generated for a fantasy game context featuring two distinct …

Sparse-Data Orbit Estimation In Low Earth Orbit Using The Markov Chain Monte Carlo Ensemble Gaussian Mixture Filter, Nicholas J. Oden

Master's Theses

The number of space objects (SOs) in low Earth orbit (LEO) continues to increase rapidly, creating challenges for the current ground-based tracking network, which cannot accommodate the projected growth in SOs. Catalog maintenance relies on frequent observations for reliable reacquisition, with Two-Line Element (TLE) sets typically generated daily to mitigate rapid error growth from poor TLE accuracy. This constraint limits the ability to track more objects with existing infrastructure. This work evaluates the Markov Chain Monte Carlo Ensemble Gaussian Mixture Filter (MCMC EnGMF), a nonlinear, non-Gaussian filter well-suited for sparse tracking scenarios where higher post-update accuracy is needed to reduce …

Adjoint Enhanced Panel Methods, Christopher Sheehan

Master's Theses

This thesis describes the development, implementation, and validation of an adjoint-enhanced panel method for two-dimensional airfoil analysis. While conventional panel methods are computationally efficient for flow analysis, they typically rely on relatively computationally expensive finite differencing for gradient calculation in design optimization or sensitivity studies, a limitation addressed by employing the discrete adjoint method. The core of this work involves integrating the discrete adjoint method with a Hess-Smith panel code utilizing Class-Shape Transformation (CST) for airfoil parameterization, which requires the analytical derivation of sensitivities for panel geometry, boundary conditions, and the aerodynamic influence matrix with respect to the CST design …

Building A Novel Question-Answering System Using Retrieval-Augmented Generation For The California Fair Political Practices Commission, Saanvi Dua

Master's Theses

The California Fair Political Practices Commission (FPPC) receives a high volume of inquiries via email from public officials, the general public, and other agencies, which currently requires staff to manually search through informational documents and manuals to provide timely responses. This process is both labor- and time-intensive.

To address this challenge, we design a question-answering (QA) system that drafts responses to emailed questions by retrieving relevant information from the FPPC’s manuals using a retrieval-augmented generation (RAG) framework. Although the current implementation focuses on a single manual, the system is designed to be adaptable to the broader set of FPPC documents. …

Enhancing Preparedness: A Genetic Study Of Sar-Cov-2 And Other Microbial Public Health Threats In Wastewater From A College Town, Christian N. Hutchinson

Master's Theses

Problem

The SARS-CoV-2 (COVID-19) pandemic revealed both the systemic vulnerabilities of our healthcare system as well as the importance of timely, localized data for informing public health responses. Traditional testing approaches were essential but often failed to capture the full extent of viral spread, especially in those with mild or asymptomatic conditions that relied on at home testing. This underreporting hindered effective allocation of resources and made developing effective intervention strategies difficult. We also realized the potential for wastewater surveillance to be applied to tracking antimicrobial resistance gene markers. Taken together, this approach should have important implications for improving public …

Effect Of Seasonal Variability In Methane Emissions And Iron Redox Chemistry At Terrestrial-Aquatic Interfaces, Hermes C. Ruiz

Master's Theses

Methane (CH₄) emissions at terrestrial–aquatic interfaces (TAIs) are significant contributors to the global carbon budget, yet the mechanisms driving methanogenesis remain poorly understood. Limited data exist on how seasonal variations and redox processes influence CH₄ fluxes in these dynamic ecosystems. This study addressed two questions: (1) How are CH₄ fluxes in riverine floodplains and adjacent hillslopes impacted by seasonal variations? (2) What roles do metal redox processes (e.g., iron (Fe)) play in regulating methanogenesis?

In-situ CH₄ flux and solid-phase Fe speciation were quantified in East River, CO, under flooded and drained conditions. Groundwater chemistry, gas flux, and soil physical properties …

The Design Of Coplanar Waveguide Traveling-Wave Kinetic-Impedance Parametric Amplifiers, Jordan Scott Savoie

Master's Theses

Astronomical observations and many physics experiments rely on cryogenic amplifiers for readout. Current sensitivity is limited by the noise figure of high-electronmobility transistor (HEMT) amplifiers, which have proven di!cult to decrease further in recent years. Traveling-wave kinetic-impedance parametric amplifiers (TKIPAs) are an emerging class of amplifiers which have the potential to substantially improve the sensitivity of microwave low-noise amplifiers (LNAs) while also accepting relatively high input powers and amplifying over a wide bandwidth. In this thesis, I present the design, modeling, and testing procedures for coplanar waveguide (CPW) TKIPAs developed by our group at the National Radio Astronomy Observatory. Using …

Alameda Song Sparrow Habitat Use Of Salt Pond Restoration Sites In South San Francisco Bay, Bradley A. Speno

Master's Theses

Restoration is acknowledged worldwide as a conservation need to return ecosystem functions. However, projects require monitoring to track system changes and assess restoration progress. In the San Francisco Bay, several large restoration projects are implementing plans to return salt-producing ponds to the historical ecosystem, tidal salt marsh. The Alameda song sparrow (Melospiza melodia pusillula), a California species of special concern, has been documented to use restored and historic marshes, but their use of restored salt ponds is not fully understood. The birds’ use of restored marshes may be a useful measure of restoration progress. This research investigated the relationships comparing …

A Closer Look At The Relationship Between Cultural Intelligence And Organizational Citizenship Behaviors, Lesli B. Quiroz

Master's Theses

As organizations—particularly in the United States—become more multicultural due to globalization, they increasingly rely on individuals' ability to succeed in complex, cross?cultural environments. Cultural intelligence (CQ), or the ability to successfully adapt to unfamiliar cultural settings, has been previously related to expatriate cross-cultural adjustment, group effectiveness, and more recently, to organizational citizenship behaviors (OCB), which are voluntary extra-role workplace behaviors that lead to positive employee and organizational outcomes. This study mainly sought to theoretically expand the limited research on the relationship between CQ and OCB with some research questions. In a sample of 93 participants based in California, results found …

Modeling Lensed Quasars With Neural Posterior Estimation: Complex Mass Models, Logan C. O’Brien

Master's Theses

The Vera C. Rubin Observatory is expected to discover ∼ 103 galaxy-scale strongly lensed AGN systems during its 10 year operation conducting the Legacy Survey of Space and Time (LSST). I use a machine learning neural posterior estimation method to automatically model these systems with the intention of using them for time-delay cosmography, to constrain the Hubble constant and, ultimately, the properties of Dark Energy. In the work shown here, the neural network that I utilize is trained on simulated lens systems with simple mass distributions that consist of a single main deflecting galaxy. I am testing the robustness of …

Quantifying Erosion Rates Of The Mission Hills Along The Calaveras, Mission, And Hayward Faults In Northern California To Better Understand The Role Of Fault Geometry On Surface Topography, Ian Duncan Lord

Master's Theses

The San Francisco Bay Area lacks publications on erosion rates and their relationship to restraining bend fault geometry. This thesis presents a detailed geochronologic study of erosion rates from the Mission Hills along the Calaveras, Mission, and Hayward faults located northeast of San Jose, California. The goals are to provide erosion rate values where none currently exist and to gain a better understanding of how fault geometry influences topography along restraining bends. To quantify the erosion rate of these faults, river sediments containing 10Be were collected from 14 catchments using well-established protocols. Of the successfully processed samples, the erosion rates …

The Impact Of Early Life Experiences On Math Confidence, Nhu X. Hin

Master's Theses

Students form beliefs about their academic abilities through a combination of emotional experiences and early learning environments. While prior research has documented how math anxiety can undermine performance and how early experiences with math-typed activities can foster positive attitudes, less is known about how these factors collectively influence students’ math confidence. The present study investigates how math anxiety, engagement in childhood math-typed activities, and perceived support for math-related learning contribute to college students’ confidence in their math abilities. Participants (N = 102) completed self-report measures assessing each of these constructs. A multiple regression analysis revealed that the three predictors collectively …

Investigating The Influence Of Experimental Parameters On The Formation Of Gold Nanoparticles: A Green Synthesis And Design Of Experiments Approach, Isaac Opeyemi Subuloye

Master's Theses

This thesis examines the green synthesis of gold nanoparticles using catechin, a naturally occurring plant-derived compound, as both a reducing and capping agent. The synthesis process was guided by a structured Design of Experiments (DOE) methodology to ensure systematic investigation and optimization. A two-phase experimental approach was adopted. First, a full factorial screening design was used to evaluate the effects of catechin concentration, NaOH concentration, and pre-reaction time. This was followed by an optimization phase using a face-centered composite design to identify conditions that produce nanoparticles with ideal characteristics. The nanoparticles were analyzed using UV-visible spectroscopy and dynamic light scattering …

Coyote (Canis Latrans) And Non-Target Wildlife Responses To Livestock Guardian Dogs At Sheep Grazing Sites On The California Central Coast, Tricia T. Nguyen

Master's Theses

Livestock depredation is one of the oldest and most widespread forms of human-wildlife conflict. The coyote (Canis latrans), a midsized canid, represents a significant proportion of domestic sheep depredations in the United States, costing livestock producers an estimated 24.6 million dollars annually. Management strategies for coyote-sheep depredation vary widely in their effectiveness and in their level of public support. Identifying appropriate strategies for farms, ranches, and other sheep grazing sites remains a pressing need due to the potentially negative consequences for surrounding ecosystems and socioeconomic outcomes for sheep producers. The livestock guardian dog (LGD) is a nonlethal control …