Digital Commons Network^™

Volunteer Spotlighting: Costly Signaling To Promote Volunteerism, Clyde A. Raible V

Master's Theses

Prosocial behaviors, because they are initially costly and do not guarantee a direct benefit to the actor, can nonetheless increase social status by signaling a willingness to incur cost on behalf of another. Given this signal value, nonprofit organizations may be able to leverage this knowledge to increase donations, such as through the provisioning of attention to, and recognition of, volunteers through social media. I predicted that the costliness of spotlighted behavior and the target signal clarity (i.e., individual vs. group spotlight) would interact with participants’ dispositional dominance and prestige-based status motives to influence volunteerism interest. To explore these associations, …

The Impact Of High-Cadence Cycling On Overground Running Performance In Recreational Runners, Matthew Ott

Master's Theses

Cycling is a commonly used exercise because it provides a controllable cardiovascular and musculoskeletal demand while imposing relatively low impact on the rider. High-cadence cycling (HCC) has been shown to influence subsequent running performance and gait performance by increasing cadence and reducing work rate when cycling prior to running. However, most of this work has focused on triathletes and older adults. Therefore, the purpose of this study was to examine the acute effects of HCC on subsequent 800 m running performance and spatiotemporal parameters in adult recreational runners. Thirty recreational runners completed two testing sessions. On Day 1, participants performed …

Design And Reliability Analysis Of A Radiation-Tolerant On-Board Computer System For Martian Surface Missions, Jack Ryan

Master's Theses

Space environments present complex challenges for electronic devices, perhaps most notably in the form of radiation effects; the natural protections provided by Earth’s atmosphere and magnetosphere are largely absent in deep space and extraterrestrial environments, making single-event effects (SEE) a critical concern. Although radiation-hardened components offer near-immunity to SEE, they possess tremendous drawbacks in both cost and performance. To circumvent such issues, this thesis investigates the feasibility of leveraging a commercial-off-the-shelf (COTS) device, the AMD KRIA K24 system-on-module (SOM), for use in Martian surface missions.

Detailed models were used to predict SEE rates in the system, and system-level fault tree …

Humor And The Politics Of Belonging: Race, Gender, And Radicalization In Online Spaces, Reese Chatman

Master's Theses

This thesis argues that post-ironic and meta-ironic humor acts as an affective gateway to far-right radicalization within online masculine subcultures. Examining incel forums and Groyper spaces, it traces how humor operates as the architecture through which extremist ideology is introduced, normalized, and internalized. Drawing on a synthesis of meme studies, digital rhetoric, and theories of irony and affect, and using digital ethnography and critical discourse analysis, the study examines recurring meme figures, especially the Wojak and its NPC variant, as portable diagnostic devices that sort participants into the "awake" and the unconscious regardless of ideological content. Case studies include incel …

An Investigation Of Data Granularity In Rag Pipelines For Personalized Medicine, Paritosh Pandey

Master's Theses

Generative AI, exemplified by large language models like the OpenAI GPT and Meta LLaMA families, can produce diverse content in response to prompts. This capability offers a promising solution to challenges in precision medicine, which seeks to tailor treatments to individual clinical profiles but often struggles with data collection, cost, and privacy concerns. By generating realistic, privacy-preserving patient data, generative AI has the potential to transform patient-centric healthcare. With such motivation, this research develops a comprehensive Generative AI pipeline emphasizing data granularity for accurate prediction of personalized treatments. The pipeline features a central Large Language Model interacting with a Machine …

Agentcite: Trustworthy Ai Agents For Information Verification Across Referenced Documents, Eymen Yigit

Master's Theses

This thesis presents AgentCite, a multi-agent framework for automated verification of referenced numerical data in research documents. The framework employs a hybrid design in which LLM-based agents handle document understanding and evidence retrieval, while deterministic components manage structured parsing and value comparison, improving consistency and reproducibility while reducing token consumption and execution time compared to fully agentic approaches.

AgentCite consists of three autonomous agents: a Negotiator, a Main Document Agent, and a Source Documents Agent, coordinated through a fixed tool-call pipeline. The Negotiator orchestrates verification by extracting tabular data from the main document, retrieving evidence from per-source vector stores, and …

Probing Representational Emergence In Large Language Models, Shawn Ismail

Master's Theses

This thesis investigates whether abrupt behavioral gains in large language models under scaling are accompanied by systematic changes in internal representations. It combines a behavioral screen of 65 tasks per family with targeted layerwise probing across eight decoder-only, open-weight model families. Behavioral emergence is defined for each family-task trajectory using an empirical jump detector, with segmented regression retained only as a diagnostic. The representational follow-up analyzes 27 selected MMLU subtasks shared across all families, spanning 37 checkpoints and 216 family-task units.

For each follow-up checkpoint, frozen linear probes are trained on every layer's hidden states to measure how much task-relevant …

Long Run Effect Of Industrial Place-Based Policy On County Level Complexity, An Investigation Of The Tennessee Valley Authority, Anita Ifeyinwa Umunnah

Master's Theses

This paper studies the long-term effects of large federal investments in place-based industrial policies on regional economic development, contributing new evidence on how industrial policies shape regional local productive capabilities over time. While extensive research show that industrial policies impact regional development by advancing productive technology (capabilities), the fundamental question remains how to measure this technological transformation. The study employs the use of Economic Complexity Index (ECI) as a measure of “technological advancements” resulting from large federal investments in place-based industrial policies. Previous evaluations of such investment were based on livelihood, employment and income outcomes, with productive capability of receiving …

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 …

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. …

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 …

Evaluating Carbon Risk And Benefit Under Improved Forest Management Prescriptions In A California Mixed Conifer Stand, Jonathan A. Garcia

Master's Theses

Improved forest management (IFM) prioritizes carbon accumulation through practices such as extended rotations and retention harvesting. These management strategies, increase fuel loads and elevate the potential fire intensity, may offset the benefits of carbon sequestration. Additionally, IFMs use spatially complex silvicultural treatments that may introduce prediction errors into the simulation processes used for long-term projections, and carbon accounting.

We evaluated the extent to which calibration in the Forest Vegetation Simulator (FVS) reduces error in aboveground carbon stock predictions and tested whether modeling approaches and calibration influence the magnitude and direction of basal area increment (BAI) prediction error using generalized mixed-effects …

Time-Dependent Amplification Of Growth Rates In A Plankton-Oxygen Model, Rapha Coutin

Master's Theses

Near-bottom hypoxia occurs when dissolved oxygen levels drop to a level that is harmful to marine biology, creating biological dead zones along the ocean floor. Recent years have seen a dramatic increase in the percentage of coastal, near-bottom, hypoxic water, with the average in 2021 nearly double that of the average from 2009 to 2018 and about twenty-eight times the average from 1950 to 1980. Recent literature has linked this increase in oceanic hypoxia to the increase in upwelling-favorable winds caused by climate change. Upwelling brings low-oxygen, nutrient-rich water up to the surface, leading to plankton blooms and mass consumption …

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 …

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, …

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 …

Empirical Comparisons Of Partial Dimension Reduction Algorithms In High-Dimensional Regression, Nathan Greenfield

Master's Theses

In high-dimensional regression problems, dimension reduction methods are often used to address the challenges of multicollinearity and estimation instability. Partial dimension reduction extends these ideas by applying dimension reduction to a subset of the predictors, while the remaining predictors are modeled without compression. This approach is particularly useful when it is important to retain variability and interpretability in certain predictors.

This thesis investigates the empirical performance of partial dimension reduction algorithms and introduces a novel algorithm, Iterative Partial Residual (IPR). Two algorithms are considered: a baseline algorithm, Marginal Residual (MR), and the proposed IPR method. Their predictive performance is evaluated …

Opioid Use Knowledge And Attitudes Among U.S. Adults, Jadyn E. Knox

Master's Theses

The opioid epidemic remains a public health crisis, with overdose rates continuing to rise. Associations between individuals opioid use and knowledge of and attitudes toward opioid substances and overdoses have been investigated to inform educational interventions. However, many studies utilize college student or adolescent samples, and findings remain inconclusive. An assessment of opioid knowledge and attitudes across broader adult populations is lacking. Concurrently, replication literature in the social sciences is limited, therefore, the present study replicated and expanded upon Williams et al. (2013) and Vyas et al. (2023) studies. Reliability and validity of the Opioid Knowledge scale, Opioid Overdose Knowledge …

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 …

Defining Limited English Proficiency: Implications For Assessment And Special Education Placement Decisions, Christine Vernon

Master's Theses

Problem

The problem addressed was the lack of a clear, consistent definition of Limited English Proficiency, despite its influence on funding, programming, assessment, and student placement. The purpose of the study was to clarify how LEP is constructed and used in educational literature and to explore its impact on assessment practices. This study examines the definition of Limited English Proficiency and its implications for educational assessment and special education placement decisions.

Methodology

An integrative literature review, guided by meta-narrative methodology and structural coding, was conducted using 119 peer-reviewed sources from APA PsycInfo, ERIC, and JSTOR (2001–2023).

Findings

Findings revealed that …

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, …

Estimating Prey Capture Attempts And Activity Costs In Foraging Emperor Penguins (Aptenodytes Forsteri) Using Integrated Biologging Data, Taylor Rose Azizeh

Master's Theses

To forage efficiently in patchy and unpredictable prey landscapes, marine predators must optimize energy intake while minimizing costs. Central place foragers like emperor penguins face greater energetic constraints during demanding periods of high investment like chick-rearing. I used high-resolution tri-axial acceleration, depth, and GPS data from 25 birds from two feeding seasons (2019 and 2022) to quantify prey capture attempts and a proxy for energy expenditure (overall dynamic body acceleration; ODBA) across dive types (epipelagic, mesopelagic, benthic), phases (descent, bottom, ascent), and over time at-sea. While prey capture attempts per minute did not differ when looking across dive types alone, …

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 …

The Effects Of Educational Materials On Knowledge And Attitudes Toward Psilocybin, Lindsey Elise Wade

Master's Theses

Depression is one of the most prevalent and burdensome mental health conditions worldwide, affecting millions and contributing to over 700,000 deaths by suicide annually. Nearly half of patients with major depressive disorder fail to respond adequately to standard antidepressant treatments such as selective serotonin reuptake inhibitors (SSRIs). Psilocybin-assisted therapy (PAT) has emerged as a promising alternative for treatment-resistant depression (TRD), yet public understanding of this therapy remains limited. The present study examined whether a brief psychoeducational intervention could affect knowledge and attitudes toward PAT among members of the general public in the United States. Participants were randomly assigned to read …