Digital Commons Network^™

Analysis Of Lateral Load Distribution In Steel Girder–Concrete Deck Bridges: Influence Of Diaphragm Behavior Under Wind And Vessel Collision Loads, Bhupesh Chand

Master's Theses

Bridges are critical components of modern transportation infrastructure, and their structural response under extreme loading conditions is essential for ensuring safety and serviceability. A key challenge in current bridge engineering practice is accurately understanding and predicting the lateral load distribution in steel girder–concrete deck bridge systems subjected to wind and vessel collision loads. While the AASHTO LRFD Bridge Design Specifications provide well-established provisions for vertical load distribution, magnitudes and load combinations (Article 3.4), they do not explicitly define lateral load distribution factors (LLDFs) for such extreme lateral loading conditions or address the role of the deck in redistributing these loads …

Design And Validation Of A Wearable Respiratory Protection System For Wildland Firefighters, Oliver Pilon

Master's Theses

Wildland and Wildland–Urban Interface firefighters are routinely exposed to hazardous smoke with fine particulate matter, carbon monoxide, volatile organic compounds, and other toxic combustion products. Existing protective gear has significant limitations and shortcomings for these conditions. Respirators with tight-fitting facepieces make it difficult to breathe and speak. On the other hand, self-contained breathing apparatuses are too heavy, have a limited duration of use, and do not work well with long wildland fire scenes, while smaller protective equipment like N-95’s and gaiters provide very little protection. These constraints contribute to low adoption rates and prolonged occupational exposure.

This thesis presents the …

The Application, Construction, And Validation Of Hidden Markov Model Profiles For Carbonic Anhydrase Enzymes, Samuel F. Kaplan

Master's Theses

Carbonic anhydrases (CAs) catalyze the reversible hydration of CO2 and have evolved independently at least eight times, resulting in structurally distinct enzyme families (α, β, γ, δ, ζ, η, θ, ι). Traditional sequence alignment methods struggle to classify these convergently evolved proteins because their sequential similarity does not reliably indicate functional or evolutionary relationships. Many CA sequences in public databases are annotated generically without family assignments, and prior computational approaches have focused predominantly on the three well characterized families (α, β, γ), leaving the five recently discovered classes without robust classification tools. Family level assignment is often a prerequisite for …

Design And Development Of A 12-Degree-Of-Freedom Quadruped Robot, Kai De La Cruz

Master's Theses

This thesis presents the design, analysis, and experimental validation of a 12-degree-of-freedom (DOF) quadruped robot developed as a research platform for legged locomotion and control. The system builds upon the Cal Poly Legged Robotics Group’s prior 8-DOF quadruped, addressing key limitations in manipulability, load distribution, and mechanical robustness by introducing a 3-DOF leg architecture.

The mechanical design emphasizes lightweight construction, structural integrity, and modularity to support future research extensions. Static and dynamic loading models were developed to inform component sizing and material selection. A carbon-fiber chassis and redesigned leg assemblies were fabricated and validated through finite element analysis and physical …

Sea Level Trends Near Critical Levees In The Sacramento-San Joaquin Delta, Reyna Sanchez Gomez

Master's Theses

The Sacramento-San Joaquin Delta (Delta) levee system faces threats from rising sea levels, land subsidence, and deteriorating levees, all of which pose risks to California’s primary surface water supply. The purpose of this thesis is to assess relative sea level rise (RSLR) and estimate the spatially varying factors that influence water levels in the Delta. This thesis extends the work of Baranes et al. (2023) to the period 1975-2022 by appending recently acquired water-level records (1975-1982) to modern datasets (1982-2022) from 10 water-level stations. These water level datasets were digitized, quality-assured, and referenced to a common geodetic datum, as described …

Demystifying Hardware Formal Verification For Undergraduate Education: A Risc-V Processor Case Study With Coursework Implementation, Riley A. Peters

Master's Theses

Hardware verification engineers apply formal methods to prove that a digital device always behaves according to its specification. This differs from traditional functional verification, in which engineers establish correctness by repeatedly sending test inputs to the device and comparing the outputs against a reference model. With the growing complexity of integrated circuits, the demand for digital verification engineers with formal methods experience has continued to increase. However, California Polytechnic State University: San Luis Obispo's current curriculum lacks dedicated material to prepare students for these roles.

This thesis seeks to address the lack of formal methods material through two efforts. First, …

Measurement And Control Of The Oxidation-Reduction Potential And Its Chemical And Sensory Consequences In Wines, William Jordan Wright

Master's Theses

The oxidation-reduction potential (ORP) is a measurement thought to reflect the overall ability of a solution to oxidize or reduce substances within that solution. In wine, there is no absolute agreement as to which substances control or dominate the ORP; however, oxygen, ethanol, iron-tartrate and copper-tartrate complexes, and glutathione are suspected to play key roles, while sulfur dioxide and phenolics may act as buffers. Anecdotally, some varieties of Vitis vinifera are prone to oxidation while others are prone to reduction, though the chemical basis of this remains unclear. The following works aim to further elucidate the influence of specific chemical …

Designing For Trust In Chat-Based Question Answering Systems: An Exchange-Based Retrieval Approach, Nathan Mccutchen

Master's Theses

Community chat platforms such as Discord and Slack support spontaneous, collaborative communication but make it difficult to retrieve previously discussed information. As conversations accumulate, valuable exchanges become buried, leading to repeated questions and sustained burden on experienced community members.

This work contributes a set of design requirements for question-answering systems operating over unstructured chat data, a Discord bot prototype implementing those requirements named Echo, and an empirical evaluation of how such a system affects user trust. Rather than encoding discrete question-answer pairs or generating synthetic responses with a language model, Echo indexes conversation topics for semantic retrieval and presents results …

Johnson–Lindenstrauss Projections As Architectural Components In Deep Neural Networks, Charles Q. Ray

Master's Theses

Modern deep neural networks are heavily overparameterized, with learned representations occupying lower-dimensional subspaces than their ambient dimensions suggest. This thesis investigates whether fixed random Johnson-Lindenstrauss (JL) projections can exploit this redundancy by functioning as architectural bottlenecks that reduce model size and training cost while preserving task performance.

We systematically evaluate JL-based compression across multiple architectures (convolutional networks, multilayer perceptrons, vision transformers, autoregressive language models) and tasks (reconstruction, classification, language modeling). Experiments reveal that compression tolerance depends critically on placement strategy and compression ratio.

Linear probe analysis quantifies intrinsic dimensionality at different network depths, revealing that CIFAR-10 final representations require only …

Using Ensemble Disagreement To Stabilize Conformal Prediction Under Distribution Shift, Patrick D. Murphy

Master's Theses

Semantic segmentation of eelgrass from drone imagery is crucial for coastal habitat monitoring, restoration, and management, as these habitats continue to see rapid changes due to climate change and human influence. However, the reliability of generalizing a deployed classification model relies on both high-accuracy segmentation as well as robust uncertainty quantification that holds up when conditions change over years or locations. Conformal prediction (CP) is a method that converts a classifier's output into prediction sets with a guaranteed average coverage level for in-distribution data. However, the “vanilla” conformal score can often under-cover in hard or out-of-distribution (OOD) regions under drift. …

Mechanistic Framework Of Wood Decomposition In Post-Storm Vegetative Debris Piles Using Continuous Quality Theory, Thomas T. Lee

Master's Theses

Storm events generate significant quantities of vegetative debris composed of wood, branches, twigs, and other organic materials. Efficient post-storm resource recovery and carbon accounting depend on reliable predictions of decomposition within these large, heterogeneous debris piles. While small-scale wood decay is well studied, decomposition dynamics within multi-layer debris piles remain poorly characterized, limiting municipalities' ability to estimate material longevity and resource recovery potential.

To address this gap, this study develops the WOOD_DK (Wood Organic Oxidation and DegraDation Kinetics) model, a preliminary, exploratory one-dimensional multilayer decomposition framework simulating coupled temperature, moisture, oxygen, and carbon dynamics in MATLAB. Microbial decomposition follows Continuous …

Neurosymbolic Counterpoint Generation, Paul D. Jarski

Master's Theses

Recent advancements in generative artificial intelligence have revolutionized music generation, yet research has predominantly focused on raw audio synthesis over music in symbolic form, i.e. a score. This thesis presents the first neurosymbolic model designed to generate imitative Renaissance counterpoint in symbolic (MIDI) format. By leveraging an autoregressive Transformer architecture, this research explores the capacity of deep learning models to manage independent voices and strict stylistic constraints.

We compare multiple data representation strategies with distinct tokenization methods. The proposed model incorporates a symbolic component that enforces fundamental contrapuntal rules. Additionally, this thesis contributes a preprocessed dataset of Renaissance polyphony, in …

A Simulation Framework For Edge Lane Roads And Bicycle Shared Roadways, Nick Sauciur

Master's Theses

Edge Lane Roads, also referred to as Advisory Bike Lanes, are a shared roadway treatment that designates space for cyclists while allowing flexible use of the roadway by motorists. They are commonly applied on lower speed corridors and can be used both where roadway width is limited and where agencies seek to manage vehicle speeds, clarify cyclist positioning, or improve shared roadway operations. The configuration provides visually designated space for cyclists while allowing motorists to encroach into that space when yielding to opposing traffic. Although interest in these facilities is growing in North America, quantitative tools for evaluating their operational …

Video Generation Techniques For Novel View Synthesis With Flow-Matching Transformers, Xiuyuan Qiu

Master's Theses

Novel view synthesis (NVS) aims to generate images of a scene from unseen camera viewpoints. Recent work, such as Stable Virtual Camera, shows that large-scale image diffusion models like Stable Diffusion can be adapted for pose-conditioned view synthesis by incorporating video-generation techniques with camera conditioning. In this thesis, we introduce MVFlow, a new NVS model that extends this approach to a different image generation architecture: a flow-matching diffusion transformer, specifically FLUX.1, which has demonstrated strong performance in image synthesis. We evaluate MVFlow under varying input view counts and pose distance settings. Our results show that this architectural transfer is feasible; …

A Scalable Iteration Of The Horizon Simulation Framework Using Multithreading Techniques, Jason E. Beals

Master's Theses

The Horizon Simulation Framework (HSF) occupies a unique space in the modern aerospace modeling landscape, enabling flexible, modular modeling of mission-level agent behavior through an object-oriented, hierarchical design. HSF's hallmark breadth-first search scheduling algorithm explores a "multiverse" of possible mission execution pathways, enabling exhaustive evaluation of schedule combinations against user-defined heuristics.

As aerospace systems become increasingly complex, HSF faces critical challenges in establishing verifiable, deterministic behavior. The framework's core scheduling algorithm had not undergone systematic validation, leaving questions about temporal consistency, state management correctness, and reproducibility across different program executions. Furthermore, the exponential growth of schedule combinations creates computational bottlenecks …

A Literature Review On Ethics In Medical Diagnostic Ai & Analysis Therein, Connor J. Turetzky

Master's Theses

Artificial Intelligence presents a very promising future in medicine. Being able to diagnose and recommend treatments quickly is vital in ensuring positive patient outcomes. However, the new technology is not without risk. In this narrative literature review, the risks of AI in terms of bias, ethics, and environmental impact will be explored through existing research. This paper will focus on research published between 2019 and 2026, highlighting the major ethical and systematic problems currently facing diagnostic AI. Historical bias in medical data has led to AI that share those biases, and humans inherit that bias creating a potential negative feedback …

Exploring Math Word Problem Generation With Llms, Trung Hieu Vuong

Master's Theses

Math Word Problem (MWP) is an important building block for learning math. This type of problem is particularly useful for younger audiences because solving it involves two simultaneous skill sets: reading comprehension and mathematical reasoning. With publicly available large language models (LLMs), generating additional MWPs is readily achievable. While researchers have started using LLMs as MWP facilitators, there still exists a gap in studies about the diversity of MWPs generated by unmodified, publicly accessible LLMs. For that reason, our study focused on two goals: (1) to evaluate the diversity of MWPs generated by publicly available LLMs when provided with examples …

Developing A Vietnamese Text Summarization Large Language Model On Limited Hardware, Tin Pho

Master's Theses

Text summarization models have achieved significant growth during the last few years because of major Large Language Model (LLM) technological advancements. The application of LLMs are widely used in news distribution (TL;DR news), translation tools (DeepL Translate), or virtual assistants (ChatGPT, DeepSeek, Claude, etc.). However, the progress has not yet reached all languages equally. The Vietnamese language is used by more than 90 million people, but the language is not as highly developed for LLM as it has many homophones, five different tones that affect meaning of words, and irregular grammar compared to other languages (e.g. English, Spanish, etc.). Also, …

Automatic Guitar Transcription Of Polyphonic Music, Ritwik Patil

Master's Theses

Transcribing guitar music automatically is a complex task due to polyphonic overlap, tuning variations, and diverse playing techniques. Current transcription systems focus on identifying note pitches and timing while ignoring performance techniques that describe how the notes are played, treating guitar recordings as generic polyphonic audio and producing MIDI-like outputs that lose important information about articulation and style. To address these challenges, we propose an end-to-end transformer model for automatic guitar transcription. The system uses a T5-based encoder-decoder architecture that processes the Constant-Q Transform (CQT) of stereo audio input. The stereo representation helps separate individual guitar parts within a mix …

Latent Action Trajectory Optimization, Rahul Milind Kandekar

Master's Theses

Learning from demonstrations offers a path to bypass the sample inefficiency of reinforcement learning, but obtaining action-labeled expert demonstrations remains expensive and often impractical. Learning from Observations (LFO) addresses this by learning policies from observation-only demonstrations. Recent LFO work relies heavily on behavior cloning: VPT and LAPO use observation-only data combined with limited action labels to train BC policies, while AIME offers an alternative policy inference approach but requires the majority of its training data to have action labels. Through systematic experiments in the Lunar Lander environment, we investigate whether latent action methods can function when state and action dimensionalities …

Parameter-Efficient Multimodal Adaptation: Ocr-Integrated Lora For Textvqa And Captioning, Karthik Ganesh Malini

Master's Theses

Vision-Language Models (VLMs) have emerged as transformative technologies for multimodal AI, yet they face significant hurdles in processing text-rich images required for enterprise applications like document understanding, medical imaging, and industrial inspection. Current VLMs struggle with accurate text extraction and reasoning, often exhibiting high hallucination rates and poor Optical Character Recognition (OCR) token utilization. To address these limitations, this research presents a comprehensive framework for optimizing parameter-efficient Low-Rank Adaptation (LoRA) fine-tuning strategies on state-of-the-art architectures, including LLaVA-1.5 and BLIVA-FlanT5. Our methodology integrates enhanced OCR token utilization, faithful caption generation, and specific hallucination mitigation techniques. We employ a multi-dimensional evaluation protocol …

Bicultural Identity, Work-Life Balance And Mental Health Outcomes In Swana Students, Julie M. Salama

Master's Theses

Southwest Asian and North African (SWANA) college students navigate academic demands alongside immigration-salient stressors that may shape their mental health and academic performance. This study examined generational status (Gen 1 vs. Gen 2+), identity conflict, ethnic identity, and work–life balance (WLB) in overall GPA and major GPA, and mental health outcomes of depression (PHQ-9), and anxiety (GAD-7) among SWANA students (N = 35). Two one-way MANOVAs found no generational differences for academics (overall/major GPA) or mental health (PHQ-9/GAD-7). Identity conflict was unrelated to GPA or symptoms but was positively associated with ethnic identity, while WLB was negatively correlated with depression …

Stream Behavior Characterization Of Marin County Coastal Watersheds And Their Influence On Salmonid Habitat, Ellie L. Murdoch

Master's Theses

Coastal watersheds in California are increasingly affected by climatic variability, threatening stream behavior, ecological function, and salmonid habitat suitability. This study evaluated streamflow behavior of seven watersheds in Marin County, California, with detailed analysis of Corte Madera, Olema, and Redwood watersheds, which are not influenced by reservoir releases. Using USGS stream gauge records, PRISM climate data, SSURGO soils, and geologic and vegetation information, streamflow metrics critical to salmonid life cycles were quantified for water years 2014 to 2023. Watersheds with greater storage capacity, such as Redwood, exhibited muted hydrologic responses, including delayed flow activation, lower peak flows, slower recession rates, …

A Methodology To Reconstruct The Extent And Dynamics Of Historic Wildfires (1850-1950) In The Santa Cruz Mountains Of California, David Vásquez Ospina

Master's Theses

This thesis reconstructs the extent and dynamics of historic wildfires in the Santa Cruz Mountains of California between 1850 and 1950 using qualitative archival evidence from historical newspapers, maps, and related documents. A systematically coded database of 225 reports, consolidated into 155 unique wildfire events, was developed to analyze temporal and spatial patterns, ignition sources, vegetation types, suppression strategies, and impacts on communities and infrastructure. Historical rainfall records from the Boulder Creek station were integrated using water-year totals, three-year rolling averages, and standardized precipitation indices to examine how multi-year dryness relates to fire occurrence and size. Linear regressions show only …

Building A Data-Driven Security Ai Framework Using Machine Learning Models, Christopher Chan Vi

Master's Theses

This research project explores a modern approach to Intrusion Detection System (IDS) anomaly detection by leveraging Artificial Intelligence (AI), Machine Learning (ML), Large Language Models (LLM), and Explainable AI (XAI). The purpose is to assess the effectiveness of these technologies in enhancing the understanding of intrusion events. This research study addresses the challenges of threshold determination and the interpretability of anomaly detection results. The proposed solution involves an LLM-based framework with XAI capabilities, integrated with a Retrieval Augmented Generation (RAG) architecture, to provide clear explanations for detected anomalies, utilizing both custom and pre-trained datasets. The study navigated inherent challenges, including …

Fully Integrated Slippage Detection System For Lower Limb Amputees, Christopher E. Miglio

Master's Theses

Lower limb amputees face significant challenges in maintaining a proper prosthetic fit, as improper fit can lead to slippage at the limb-socket interface, resulting in discomfort, pressure sores, and long-term musculoskeletal complications. To address this issue, a fully integrated slippage detection system was developed to monitor an amputee’s daily activities and slippage occurrences to understand their prosthetic fit over time. The system consists of a prosthetic sock embedded with Interlink 406 flexible piezoresistive force-sensing resistors (FSRs). The sock, worn directly on the residual limb, continuously measures pressure at the limb-socket interface. Sensor data from six FSRs is sampled at approximately …

A Novel Microfluidic Device For Preclinical Testing Of Chemotherapeutics, Kaija Saleh Ogan

Master's Theses

This work demonstrates the feasibility of a novel microfluidic tumor model that reproduces physiologically relevant nutrient gradients and endothelium–tumor interactions, validating its potential as a preclinical test platform. Finite element simulations of glutamine diffusion and fluid dynamics aligned with experimental tracer studies, and co-cultures supported directed endothelial migration toward tumor spheroids, confirming the device’s ability to mimic in vivo–like behavior.

Current preclinical models often fail to capture the complexity of the tumor microenvironment (TME), limiting their predictive value for therapeutic testing. Nutrient availability and angiogenic signaling are critical drivers of tumor progression, yet they are poorly represented in traditional …

Muscle Impulse Transducer: Research, Pre-Pilot Experiments, And The Design Of A Pilot Study For Quadriplegic Spinal Cord Injured Subjects For The Development Of A Novel Device, Marta Oreglia

Master's Theses

Paralysis due to spinal cord injury is a challenging condition that affects millions of people around the world. The Muscle Impulse Transducer (MIT) is a novel, wearable device that can be used to improve grip strength in the hand by using functional muscle impulses as a trigger for stimulus delivery to weakened or paralyzed nerves, to induce contraction of a paralyzed or paretic muscle. The MIT is still in development, with proof of concept [1], and functional prototypes [2] achieved. In this thesis, research was conducted on the best methods for functional electrical stimulation, EMG data collection, and nerve stimulus …

Using Noninvasive Calibrated Cuff Plethysmography To Observe The Effects Of Lifestyle Habits On Arterial Compliance, Joshua M. Whitaker

Master's Theses

Cardiovascular disease remains as a leading cause of death for both sexes and across all racial backgrounds. Continuing to research causes, early predictors, and preventative actions are paramount to ensuring that cardiovascular disease starts to decrease in its activity. Endothelial dysfunction is the earliest known predictor of cardiovascular disease, therefore investigating early detection methods of endothelial dysfunction can improve health outcomes. This study revolves around a non-invasive calibrated cuff device that uses the principles of segmental plethysmography and oscilliometry to measure arterial compliance of baseline and induced hyperemic conditions in human subjects to determine how well arteries vasodilate in response …

Short-Arc Angles-Only Initial Orbit Determination For Leo And Geo Objects Using A Genetic Algorithm, Joseph R. Piini

Master's Theses

An ever-growing interest in utilizing space for scientific, commercial, and defense applications has led to an exponential rise in orbital debris recent years. With this sharp increase in space objects comes a greatly increased risk of potential collisions, necessitating an increase in Space Situational Awareness. In order to best mitigate the risk of future collisions in an increasingly congested space environment, it is crucial to be able to accurately determine the orbits of these new objects for trajectory tracking. This process is initial orbit determination (IOD), and is especially difficult when only observation angles are available for short observation times. …