Digital Commons Network^™

Using Hydraulic And Hydrologic Modeling To Determine Scour At Toro Creek Under Climate Change Conditions, Gabriel E. Alaniz

Master's Theses

ABSTRACT

This study evaluates bridge scour at the Toro Creek crossing of Highway 1 in Morro Bay, California, under present conditions and future climate conditions with more frequent extreme rainfall events. California infrastructure is becoming increasingly vulnerable to extreme storm events and increased intense precipitation events brought by climate change. This analysis focuses on the calculation of scour for both the northbound and southbound spans. Highway 1 plays a vital role in California’s coastal transportation infrastructure by carrying more than 20,000 vehicles daily (Caltrans, 2017). In this thesis, a hydrological model (HEC-HMS) is used to simulate runoff under present-day and …

Llm-Powered Question Answering For Object States In Virtual Reality, Shiyi Ding

Master's Theses

Recent advances in large language models (LLMs) and multimodal large language models (MLLMs) enable natural language–based querying in virtual reality (VR). However, VR environments are highly localized, personalized, and dynamic, making it challenging for general-purpose models to answer environment-specific queries or reason about subtle object state changes. To address these challenges, this thesis develops two systems for 3D question answering in VR.

First, we present RAG-VR, the first retrieval-augmented 3D question-answering system designed for VR. RAG-VR augments an LLM with external knowledge retrieved from a localized knowledge database and includes a pipeline for extracting environmental and user-related information. To improve …

Moving Beyond The Tiktok Frame: Exploring Middle School Students' Understanding Of Dance Composition Through The Use Of Choreographic Exercises, Heather Barrett

Master's Theses

The purpose of this study was two-fold: (a) to measure student initial understanding of choreography against student final understanding of choreography and (b) to measure student dependency on social media for choreographic initiation. This study focused on the impact of choreographic exercises on participants’ abilities to create dance. This study also focused on the impact of using social media for inspiration on participants’ abilities to create dance. Participants were given a survey, choreographic exercises, reflections, an interview, and a rubric for a final performance project as metrics. These instruments measured participants’ responses in comparison to the beginning of the study …

A Study On Deepsea Fish Detection Using Convolutional Neural Networks, Poojitha Priyadarshini Madari

Master's Theses

This study investigates automated deep-learning methodologies for two primary tasks, firstly fish and its habitat classification and deep-sea fish detection using the DeepFish dataset. A pretrained ResNet-50 model attained a validation accuracy of 82.8% for multi-class habitat classification, demonstrating robust performance in most habitats based on 6,517 images, although exhibiting lower recall for visually similar or underrepresented classes. A binary ResNet-50 classifier achieved 99.8% accuracy in distinguishing fish from. no-fish images using approximately 40,000 images. The YOLOv5s model, trained on 4,505 images containing 15,463 bounding-box annotations, achieved a mean average precision ([email protected]) of 98.2% All models were trained on the …

Seagrass Carbon Standing Stock In The Northern Gulf Of Mexico: The Role Of Seagrass Beds In Mississippi As Potential Blue Carbon Sinks, Devan Hildebrand

Master's Theses

Organic carbon stored in marine ecosystems is known as blue carbon. Seagrass beds have the ability to contribute to global blue carbon standing stocks through the uptake and sequestration of carbon from the water column. Through coastal management and conservation best practices, blue carbon habitats have the potential to help mitigate the effects of climate change. Although widely studied, knowledge gaps exist on the sediment carbon standing stock of seagrasses. I aim to better understand how persistent seagrass meadows surrounding barrier islands in the northcentral Gulf of Mexico contribute to long-term blue carbon standing stocks. Subaqueous sediment cores were collected …

Mississippi Dugout Canoes: An Ethnohistorical And Archaeological Analysis From 1538-1900s, Sean N. Mccraw

Master's Theses

Watercraft remains an overlooked aspect of Southeastern historical and archaeological scholarship. A more complete understanding has the potential to illuminate aspects of the human social process in anthropology and a more accurate construction of historical events. Recent Developments in Southeastern Archaeology, published in 2012, mentions the importance of the connections that water travel facilitated, but the work does not mention any serious investigation. While history has investigated the role native trails played in the development of the region, and while Andrew Lippmann has illustrated the agency that boat skills and watercraft gave Natives in the coastal North American region during …

Life History And Distribution Of Two Species Of Cownose Ray, Rhinoptera Bonasus And Rhinoptera Brasiliensis, In Mississippi Coastal Waters, Anna Millender

Master's Theses

Historically, the American Cownose Ray (Rhinoptera bonasus) was considered the only rhinopterid residing in the northern Gulf of Mexico (GOM); however, recent studies have confirmed the presence of the Brazilian Cownose Ray (Rhinoptera brasiliensis) throughout this region. The current study investigated the life history and distribution of both species within Mississippi waters, an area that previously represented a data gap for both species. From April 2016 – July 2025, 193 R. bonasus and 94 R. brasiliensis were analyzed to describe the reproductive biology. Reproductive timing, mating, gestation length, and parturition were similar among species. Although more …

Isolation Of The 2019 Bonnet Carré Spillway Effects On The Habitat Suitability Of Brown Shrimp (Farfantepenaeus Aztecus) And Blue Crab (Callinectes Sapidus) Using A Modeling Approach, Mallory Dyson

Master's Theses

In 2019, an unprecedented flood year, the Bonnet Carré Spillway (BCS) was opened on two separate occasions (February 27^th to April 11^th, and May 10^th through July 27^th) diverting a volume 6 times the volume of Lake Pontchartrain into the surrounding coastal waters of Louisiana, Mississippi, and Alabama. The goal of this research was to determine the spatio-temporal influence of these freshwater releases on two economically and ecologically important species (Farfantepenaeus aztecus and Callinectes sapidus) with variable responses to salinity and temperature depending on the age class. The Habitat Suitability Index (HSI) …

Computational Study On Protein Docking With Vascular Disease Application, Lohitha Reddy Shanigaram

Master's Theses

This thesis investigates how computational methods can help us understand protein docking and vascular diseases by integrating machine learning. The main goal of this research is to develop a system that can predict whether variants in the SOX17 gene are associated to Pulmonary Arterial Hypertension (PAH), a significant vascular condition. To do this, a dataset of 1,063 SOX17 variants was created using publicly available sources such as ClinVar, gnomAD, LOVD, and Ensembl. The study included cleaning and structuring the dataset, encoding genomic data and training a Random Forest classifier to classify variants as positive, negative, or unknown for disease association. …

On Sobolev Spaces And The Existence Of Weak Solutions To Boundary Value Problems, Skye X. Paul

Master's Theses

Many boundary value problems that arise in mathematical models have close connections to second order elliptic partial differential equations. This thesis introduces the idea of weak derivatives and Sobolev Spaces to generalize possible solutions. Using functional analysis centered around the Lax-Milgram theorem, we show the existence of these generalized solutions to boundary value problems including Laplace's Equation, 2nd order linear ODEs, and ultimately a general second order elliptic PDE. The work cumulates with recovering a number of central theorems of functional analysis in the context of Sobolev Spaces, creating a new perspective on the solvability of these boundary value problems.

Enhancing Ad/Adrd Management Through Ihelpcare: A Compliant And Culturally Sensitive Ai-Driven Digital Healthcare Platform, Trisha Bhowmick

Master's Theses

The digital healthcare field is expanding fast, and now it requires platforms that use advanced technology and maintain robust data security and compliance practices. In the present paper, we present the main structure, key methods, and compliance strategies of the digital healthcare system iHelpCare, which, while fully meeting the HIPAA/GDPR requirements, provides health services more accessible, efficient, and inclusive. The proposed platform is powered by AI for personalized care solutions, with the main emphasis on preventive health management and providing tools for people with disabilities.

iHelpCare achieves real-time patient monitoring while securing medical data management and easy communication between patients, …

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 …

Retrieval Augmented Framework For Deepfake Audio Detection, Avinash Saxena

Master's Theses

The widespread use of AI-based audio deepfakes threatens severely to undermine media integrity and public trust. Speech synthesis techniques have improved dramatically in voice conversion (VC) and text-to-speech (TTS) in recent years, making forgeries sound highly realistic, and concerns are raised about possible malevolent uses. Existing state-of-the-art techniques for identifying fake speech have proven to be effective in some cases but are still limited in application and robustness when faced with novel attacking strategies, different acoustic conditions, or alternative linguistic domains. To address some of these limitations, the current research presents a novel deepfake audio detection system based on personalized …

Towards A Generalized And Optimized Apriori Approach, Artem Abdikov

Master's Theses

Apriori is a machine learning algorithm developed in 1994 by R. Agrawal and R. Srikant for association rule mining purposes. This family of algorithms takes transactional data and analyzes relationships between variables in large datasets. The typical output of such algorithms is a prediction that if users choose item X, it is highly likely that they will also choose item Y. Apriori is known to be a robust algorithm and is used by many large companies in order to analyze user tendencies and even make recommendations. Although Apriori is a powerful algorithm, its original implementation is known to have limitations, …

A Triple Bottom Line Analysis Of Food Waste-To-Bioenergy At California University Campuses: Social Enablers Break Down Economic Barriers, Anjali Sharma

Master's Theses

Greenhouse gas emissions from food waste (FW) and energy generation are two major hurdles to the climate crisis. Previous research shows that waste-to-energy systems may provide a solution to both these challenges, particularly at university campuses, due to their high FW generation and high energy needs. Despite this, few academic institutions in California, US, have adopted waste-to-energy systems, and campus-specific challenges and opportunities associated with these systems remain underexplored. For this study, I use an Environmental, Economic, and Social (EES) lens to document the current landscape of FW management and implementation of food waste-to-bioenergy at campuses in each of the …

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 …

Radiation Hardness Study Of Finfet And Gate-All-Around Fet Sram, Albert Lu

Master's Theses

Radiation, such as alpha particles or neutrons, is hard to control and can come from sources such as trace impurities or cosmic rays from space. These can then strike a semiconductor device, such as a Static Random Access Memory (SRAM) cell, and cause the SRAM to have its bit flipped. This bit flip is often just a temporary effect and is thus called a single event upset (SEU). Although it is temporary, a bit flip can cause severe consequences, such as affecting program functionality by causing incorrect data to be used. This is made worse in critical environments that need …

Development Of New Design Criteria For Coastal Highway Embankment Under Wave-Induced Loading, Udaya Bilas Panta

Master's Theses

In the face of intensifying hurricanes and rising sea levels, Louisiana’s coastal highways, lifelines for communities and commerce, stand increasingly vulnerable. This thesis introduces a pioneering methodology for designing geosynthetic-reinforced highway embankments capable of withstanding wave-induced loading and rapid drawdown scenarios, the most critical failure condition identified in coastal environments. By integrating statistical wave modeling, advanced numerical simulations using SEEP/W and SLOPE/W, and a comprehensive parametric analysis, the study develops a novel hybrid regression formula that accurately predicts optimal reinforcement lengths based on site-specific geotechnical and hydraulic parameters. Validated against Hurricane Katrina data and real-world soil profiles from Cameron Parish, …

The Potential Co-Occurrence Of Perfectionism, Food Insecurity, And Gpa With Orthorexia Nervosa Risk, Samantha Kay Gould

Master's Theses

There are indeterminate risk, prevalence, and correlation data on orthorexia nervosa (ON) as shown by current literature on disordered eating (Rodgers et al., 2021). As a roughly defined disordered eating pattern, ON may be better understood after identifying associations among other attributes in a college student sample (Abdullah et al., 2020; Mavrandrea & Gonidakis, 2023; Parra-Fernández, 2019; Rogowska et al., 2021). A cooccurrence and influence of perfectionism, food insecurity, and grade point average (GPA) with ON risk was hypothesized since current literature suggests college students exhibit each of these characteristics independently (Abdullah et al., 2020; Ambwani et al., 2019; Caferoglu …

Exploring The Effectiveness Of Virtual Reality Learning Through Use Of Visual Eye-Tracking Analytics (Veta) And Biological Measurements, Mckinley Anne Sherman

Master's Theses

Virtual Reality (VR) offers an immersive and interactive platform for experiential learning. The purpose of this thesis was to evaluate the relationship between physiological responses and cognitive workload within a VR learning environment and to explore VR as an effective instructional tool. This research compared participant engagement, stress, and learning performance within a 6th-grade science module developed in VR by incorporating biometric data collected via Polar H10 heart rate monitor and Varjo Areo VR headset eye-tracking. Thirty-three participants completed a pre-lesson demographic survey, post-lesson survey, VR sickness questionnaire, and the NASA Task Load Index (NASA-TLX). While completing the lesson, the …

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 …

Towards Automated And Explainable Insider Threat Response In Electronic Health Records: A Role-Aware Machine Learning Framework, Luca Lippi Ornstil

Master's Theses

Healthcare remains a prime target for cyberattacks, with insider misuse and credential compromise posing major risks to Electronic Health Records (EHRs). This thesis introduces a role-aware, explainable anomaly detection and response framework integrated with OpenEMR to address post-authentication threats. Four models—Local Outlier Factor (LOF), Isolation Forest, Autoencoder, and Graph Neural Network (GNN)—detect behavioral deviations across temporal, device, and role-based features, with LOF serving as the primary runtime detector. A configurable policy engine maps anomaly severity to proportional actions, from email alerts to read-only restrictions or account suspension, all reversible and auditable. Evaluation on real EHR logs shows the system’s operational …

Development Of A Colorectal Cancer Spheroid Model To Improve The Accuracy Of Preclinical Drug Testing, Jillian Trilevsky

Master's Theses

Colorectal cancer is the second leading cause of cancer related deaths worldwide. It currently affects millions of people across the globe and is only expected to increase in impact over the coming years. The most common treatment for metastatic colon cancer is chemotherapy, however, the development of chemotherapeutic drugs is a long and expensive process. A large portion of this development process is spent in preclinical drug testing. However, the models used often lack enough physiological relevance to guarantee the drug’s success in a clinical trial. Due to this gap in testing, researchers seek to develop a more physiologically relevant …

System Characterization Of A Distributed Pressure Sensor Array, Bryan C. Hasselman

Master's Theses

This thesis contributes to ongoing research on bluff body aerodynamics at California Polytechnic State University, San Luis Obispo, by introducing a novel technique for the dynamic characterization of a commercially available digital MEMS pressure sensor. The experimental approach combines a new characterization method with comparisons to traditional techniques, offering a comprehensive evaluation of the sensor’s dynamic performance. Both non-parametric and parametric system identification methods are employed to assess the sensor’s frequency response. This thesis supports further investigations into unsteady aerodynamic forces and provides a cost-effective, hands-on platform for students to gain practical experience with instrumentation, system identification, and frequency-domain analysis.

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. …

Using Hydraulic Simulations To Determine The Effects Of Tidal Behavior And Riparian Restoration On Chorro Creek, Jonathan L. Maas

Master's Theses

This thesis examines how tidal backwater effects and riparian restoration influence flooding in the Chorro Creek watershed, a major tributary to the Morro Bay Estuary on California’s Central Coast. Restoration efforts, including levee removal, floodplain reconnection, and revegetation have attempted to improve ecological function and reduce sediment transport. However, recent flood events suggest that these changes may also affect local hydraulics in ways not fully anticipated, particularly under the influence of tides and sea level rise. To analyze these dynamics, a two-dimensional HEC-RAS model was developed using LiDAR terrain, historical imagery, and field data collected from pressure and ultrasonic gauges. …

Experimental Study Of Gas-Dynamic Heating In Hartmann-Sprenger Tubes For Rocket Engine Ignition, Jacob T. Huff

Master's Theses

Ignition systems for chemical rocket engines typically rely on hypergolic propellants or auxiliary electrical hardware to supply the energy required to initiate combustion. The resonance igniter is a simple and robust alternative to these conventional methods, capable of inducing autoignition of non-hypergolic propellants without an external ignition source. At the core of this concept is the Hartmann-Sprenger Tube (HST), a device in which a high-velocity jet of gas impinges on a resonance cavity. This interaction establishes self-sustaining gas oscillations within the cavity that heat the propellants to their autoignition temperature. To facilitate the development of a functional resonance igniter at …

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 …