Digital Commons Network^™

Evaluating Design Choices For Gpu-Accelerated Finite-Difference Time-Domain Simulation On Resource-Constrained Devices, Joel Manesh

Master's Theses

The Finite-Difference Time-Domain (FDTD) method is a numerical technique for solving partial differential equations. It was first developed to solve Maxwell’s equations for electromagnetic wave propagation and has since been extended to model other physical phenomena governed by wave propagation. Because the FDTD method is data-parallel, it is well-suited for GPU acceleration; modern FDTD-based simulations run offline on large GPU clusters. There is, however, very little research on running FDTD on resource-constrained embedded GPUs, which are increasingly popular for real-time applications.

This thesis explores a CUDA-based FDTD solver for the 3D wave equation on the Nvidia Jetson Orin Nano. This …

Trace: Temporal Rhetorical Analysis And Consistency Evaluation For Legislative Speech, David Hernandez

Master's Theses

Legislators frequently discuss the same policy issues across multiple hearings and legislative sessions, sometimes maintaining consistent positions and other times modifying or reframing their stance over time. Understanding how these positions evolve is important for analyzing political discourse and democratic accountability, yet identifying such shifts at scale remains difficult.

We introduce TRACE (Temporal Rhetorical Analysis and Consistency Evaluation), a system built on the Digital Democracy Database (DDDB) for detecting rhetorical inconsistency in California legislative hearing testimony. TRACE organizes utterances into speaker-anchored timelines indexed by bill and session, then applies hybrid semantic retrieval — combining dense BGE embeddings with BM25 lexical …

Design And Parametric Study Of A Mems-Based Reservoir Computer For Reinforcement Learning, Andrew P. Carr

Master's Theses

Single-node reservoir computing (RC) is a hardware-efficient approach to machine learning, leveraging the dynamics of physical systems. In this work, two reinforcement learning algorithms, Q-learning and Proximal Policy Optimization (PPO), are applied to a simulated micro-electro-mechanical system (MEMS)-based reservoir computer to solve both discrete and continuous control tasks. MEMS-based reservoirs are low-power, compact, and their natural frequencies (kHz to MHz) pair well with real-time control loops. To explore the relationship between reservoir dynamics and learning performance, a parametric study is conducted on two reservoir hyperparameters, reservoir size and neuron separation, using CartPole-v1 and MountainCar-v0. The RC successfully learns multiple tasks …

Crab: A Novel Clustering Score Using Clustering With Rivals And Buddies For Unsupervised Learning, Allen Choi

Master's Theses

Unsupervised clustering algorithms today are used across a wide variety of fields such as biology, engineering, and industry in order to classify observations into groups where labels are not provided. This can provide important latent information regarding the observations within groups, as well as insight regarding the groups themselves. In order to judge the optimal number of clusters for an unsupervised clustering algorithm, many methods exist such as the Elbow Method and Silhouette Score; however, these methods come with drawbacks and are not necessarily flexible across many unsupervised methods. We present a novel clustering score framework relying on a resampling-based …

Marine Heatwaves And Fish Reproduction: Endocrine Responses In The Eurythermal Sheepshead Minnow (Cyprinodon Variegatus), Isabel Villafuerte

Master's Theses

Marine heatwaves associated with climate change are increasing in frequency and severity, posing significant threats to fish populations in shallow habitats such as estuaries and salt marshes. Because temperature is a primary regulator of fish reproduction, understanding how heatwaves affect reproductive physiology is critical for anticipating the biological consequences of ongoing climate change for coastal fishes. Here we examined how simulated heatwave conditions affect the reproductive hypothalamic-pituitary-gonadal (HPG) endocrine axis in the estuarine sheepshead minnow (Cyprinodon variegatus), a eurythermal fish well suited to studying thermal stress responses in estuarine environments. Adult sheepshead minnows acclimated to a daily oscillating …

On The Number Of Ways To Express A Set As A Union Of Individually Interesting Sets, Alison Watson

Master's Theses

In a dataset that contains what ought rightly to be several distinct datasets placed in juxtaposition with each other, grouping datapoints based on observed similarities can be done in many ways. Topological Data Analysis (TDA) is a field of math that seeks to impose geometric structure onto datasets, thereby translating problems in statistics to problems in geometry or topology. A common truism in this field is “Data has shape and shape has meaning.” In this thesis, we use combinatorial and categorical arguments to demonstrate some shortcomings of a TDA approach on a class of inverse problems inspired by marine wildlife …

50,000 Spectra And Counting: Preparing For A Roman Spectral Atlas, Maya Jordan Seagraves

Master's Theses

Slitless spectroscopy with the Hubble Space Telescope's Wide Field Camera 3 \linebreak (WFC3/IR) enables simultaneous spectral coverage of all sources in a field, but large-scale single-orientation datasets remain challenging to process. We developed a pipeline that automates HSTaXe spectral extraction across hundreds of Hubble Space Telescope observations, enabling efficient processing of 84 fields and producing over 50,000 spectra from three filters (F110W, F125W, and F160W) and two grisms (G102 and G141). This was achieved by creating a companion Python package, the Module for Infrared Label Analysis (MILA), that integrates data calibration, extraction, and visualization. To assess the scientific utility of …

Analyzing A Hot Player: A Holistic Approach To The Hot Hand, Faran Igani

Master's Theses

This paper develops a continuous-time, continuous-state framework for studying “hot hand” performance within NBA games. Rather than defining performance in terms of discrete shot outcomes or short streaks of makes and misses, it tracks a player’s contribution using John Hollinger’s Game Score continuously throughout the game. The Game Score metric aggregates multiple on-court contributions through weighted in-game statistics, evolving as play progresses. This approach allows for the construction of a single metric that indexes a player’s performance over the course of the game. To evaluate whether observed within- game surges reflect genuine “heat” rather than random variation, a simulation-based null …

Optimization Of Repeat Ground Track Constellation Design For Complex Discontinuous Regional Coverage, Paige Jewell

Master's Theses

The continued growth of low Earth orbit (LEO) satellite constellations motivates efficient constellation design methods to reduce cost and complexity. Although brute-force methods are commonly employed in the preliminary design of satellite constellations, pairing analytic methods with optimization algorithms provides a more efficient means of searching the design space. Constellation design for continuous global and regional coverage is well-established; however, strategies for discontinuous regional coverage remain underdeveloped. This thesis focuses on an analytic geometry-based method for computing satellite coverage and revisit metrics, coupled with genetic algorithm optimization to efficiently explore the design space. The viability of this method is shown …

`Youdrawitr`: Integrating Interactive Graphical Testing Into The `Ggplot2` Ecosystem, Alisa Krasilnikov

Master's Theses

`youdrawitR` is an R package inspired by the New York Times ‘You Draw It’ series, where readers are invited to sketch their own predictions before seeing the actual data. In a similar spirit, `youdrawitR` allows users to draw predicted values directly onto statistical graphics, creating a more engaging way to study how people interpret visual patterns. Earlier versions of the tool required knowledge of JavaScript D3 to extend or adapt the package, which created a barrier to entry for many statistical researchers. Further, the package was limited in scope, supporting only scatterplots. The redesigned `youdrawitR` builds on the familiar `ggplot2` …

Integer Quantization And Embedded Deployment Of Cnn Star Trackers For Cubesats, Meora R. Giusiano

Master's Theses

A star tracker determines spacecraft orientation by photographing the star field, detecting stars in the image, matching them against a catalog, and computing the rotation between observed and cataloged directions. Convolutional neural networks (CNNs) have been proposed as replacements for the detection and centroiding stage, offering improved sub-pixel accuracy and recovering faint stars that classical thresholds lose to stray light and sensor noise. The improvement comes at higher computational cost; the PolySat systemboard targeted in this work lacks the floating-point hardware these networks assume.

This thesis closes the gap between floating-point desktop evaluation and embedded integer deployment. Nine encoder-decoder CNN …

Evaluation Of Solar Reflective Pigments For Use In Direct-To-Metal Coatings, William J. Diment

Master's Theses

Solar reflective coatings offer a promising strategy to mitigate the urban heat island effect by reducing absorption of near-infrared solar energy. This thesis project investigates the feasibility of incorporating near-infrared reflective pigments into waterborne direct-to-metal (DTM) latex coating systems while maintaining acceptable color comparison characteristics and coating performance. An all acrylic latex DTM formulation with titanium dioxide as the sole pigment was prepared and tinted with a variety of conventional and solar reflective commercial colorants across the yellow, red, blue, and green color ranges. Coatings were evaluated for solar reflectance, CIELAB color, gloss, contrast ratio, rheological behavior, accelerated ultraviolet weathering …

What Makes A Modern Attention Implementation?, Brian H. Slonim

Master's Theses

Since the seminal assertion by Vaswani et al. in 2017 that “Attention Is All You Need,” transformer models have risen to ubiquity due to their ability to learn extremely complex patterns from sequence data, culminating in the unprecedented generative capabilities of large language models. These models’ strength lies in their scale: hundreds of millions (e.g., BERT-LARGE) to billions or trillions of learned parameters. Running inference with these models, let alone training them, would be intractable without significant innovations in the hardware and software that support them. This need has driven an enormous demand for GPU compute and associated software ecosystems, …

On M-Estimation: From Theory To Examples, Alexander Yuan

Master's Theses

M-estimation provides a unified framework for statistical procedures defined as optimizers of data-dependent criterion functions. This thesis gives an expository account of M-estimation in classical and high-dimensional settings. The classical part develops weak convergence, empirical process tools, and the argmax framework for studying consistency, rates of convergence, and weak limits. Examples including least squares, maximum likelihood, robust location estimation, change-point estimation, and empirical risk minimization illustrate regular and non-regular asymptotic behavior.

The high-dimensional part studies regularized M-estimators, where the focus shifts to finite-sample error bounds and model selection guarantees. Topics include decomposable regularizers, restricted strong convexity, non-convex penalties, and sparsistency. …

Hot Hands Or Chance Happenings? A Simulation-Based Approach For Wnba Teams, Ruben Jimenez

Master's Theses

The hot hand is a polarizing topic in basketball analytics: fans, stakeholders, and even players themselves assert confidently their belief or disbelief in the idea that players who perform well will continue to do so over an extended period of time. Statistical research has been conducted since as early as 1985 to attempt to disprove or prove the existence of this phenomenon. More recent works have refuted the earliest objections to the hot hand’s existence, with conclusions aided by robust simulation techniques. In this work, we compare hypothesis tests using multiple simulation techniques to explore the hot hand at the …

Is The Hot Hand Real? Evidence From A Permutation And Hierarchical-Based Analysis, Cameron Z. An

Master's Theses

The hot-hand phenomenon, often described as the tendency for individuals to experience prolonged streaks of success that exceed what would be expected under random performance, has been widely studied across many disciplines, particularly basketball. Early studies attempted to evaluate this effect through various techniques, often concluding that the hot-hand phenomenon was largely a myth. However, recent studies have begun to revisit previous analyses using improved statistical techniques, with some claiming evidence of a discernible hot-hand effect. This study examines the presence of the hot-hand effect in the modern NBA by testing whether observed shooting patterns deviate from those simulated under …

High-Resolution Queries, Low-Resolution Context: Scaling Vision Transformers With Asymmetric Spatial Reduction, James M. Dwyer

Master's Theses

Vision Transformers (ViTs) have demonstrated great performance on image classifica tion benchmarks, however, the quadratic complexity of the self-attention mechanism with respect to sequence length limits their scalability to higher resolution inputs. The attention score matrix grows as O(N2) in both compute and memory, where N is the number of patch tokens, making ViTs computationally expensive and memory intensive for applications that require real-time inference or operate under resource constraints.

This thesis investigates whether the key and value sequences of the self-attention mechanism can be compressed using the local spatial structure of the image — while keeping queries at full …

A Higher Order Panel Method With Vortex Particle Wake, Luca Flick-Kaiser

Master's Theses

Panel codes were some of the earliest methods for computing the flow around aircraft. Despite the availability of higher fidelity CFD methods, panel methods remain an essential tool for the development of modern aircraft, allowing engineers to quickly iterate during the conceptual design phase.

This work develops and implements a high order panel method using Python. The wake is modeled using vortex particles, resulting in an accurate wake representation with minimal user input. The integration of the higher order singularity distributions has been extended to include the calculation of the velocity gradients necessary for the vortex particle implementation. The use …

Computer Vision Methods For Detecting Counterfeit Usd Bills, Tyler W. Jones

Master's Theses

This thesis addresses the global challenge of counterfeit paper currency by proposing a classical computer vision framework for distinguishing genuine United States Dollar (USD) bills from counterfeit ones using image data. In contrast to existing approaches that rely on a large number of easily reproducible visual features, this work prioritizes the detection of a single, robust security feature: the ultraviolet (UV) reactive security strip embedded in genuine USD bills of denominations $5 and above. By focusing on a feature that is inherently difficult to replicate, the proposed method reduces the likelihood of counterfeit bills being misclassified as genuine.

The system …

Development Of A Free-Floating Space Robotic Simulator, Truman: Terrestrial Robotic Unit For Multibody Analysis And Navigation, Jackson W. Cordova

Master's Theses

This work describes the development of a 3 Degree-of-Freedom (DOF) robotic manipulator for use on a free-floating planar air-bearing vehicle. The system developed aims to serve as a foundation for future space robotics research at the California Polytechnic State University (Cal Poly)’s Space Robotics Laboratory. Systems doc- umentation describes conceptual operation and architecture of the proposed system: Terrestrial Robotic Unit for Multibody Analysis and Navigation (TRUMAN). The key operation of TRUMAN is to study a self launch maneuver of a free-floating ve- hicle including 4 distinct phases: launch off a fixed rail, coast, reorientation using manipulator motion, and capture of …

Spaceotter: A Floating Spacecraft Simulator Air Bearing Vehicle For Hardware-In-The-Loop Experiments And Research, Alexander Debartolo

Master's Theses

Growing interest in nanosatellites has increased demand for accessible ground-testing methods, which have historically been expensive and restricted. Floating Spacecraft Simulators (FSS), built around Air Bearing Vehicles (ABVs), address this gap by approximating a zero-gravity, friction-minimized environment suitable for testing spacecraft control systems, robotics, and propulsion on the ground.

This thesis presents the design, realization, and initial performance characterization of the Space Optically Tracked Testbed for Experiments and Research (SpaceOTTER) ABV, developed for the Cal Poly Space Robotics Lab. SpaceOTTER is the first step toward emulating the 3 degree of freedom (3-DOF) planar dynamics of a simulated spacecraft and is …

When Agents Spend Watts: Measuring Performance-Energy Trade-Offs In Agentic Ai Systems With Agenticbench, Logan J. Barker

Master's Theses

Agentic AI systems increasingly transform a single user request into a multi-step workflow of reasoning, tool use, retries, and framework coordination. Standard benchmark reporting emphasizes task accuracy, but this can hide the latency and energy-related cost of producing an answer. This thesis presents AgenticBench, a modular harness for evaluating agentic AI systems with task performance and execution-cost signals recorded together. AgenticBench integrates benchmark-owned scoring, framework adapters, deterministic task selection, energy profiling, SQLite persistence, and Pareto-style analysis. The main campaign evaluated an 84-cell matrix across four models, three agent frameworks, and six benchmarks on a Windows workstation with an NVIDIA RTX …

Efficient Mathematical Modeling And Synthesis Of Realistic Musical Instrument Sounds, Andrew Chookaszian

Master's Theses

This thesis develops and evaluates a compact parametric additive synthesis model for isolated musical instrument tones. The method analyzes a single-note recording, estimates its fundamental frequency, extracts harmonic amplitude and frequency behavior, and stores the sound as a reduced set of interpretable parameters. These parameters include the note duration, pitch, per-harmonic amplitude envelopes, phase information, and amplitude- and frequency-modulation vibrato parameters. The stored model is then used to resynthesize the tone without directly using the original audio waveform.

The model was evaluated using synthetic signals, real instrument samples, objective error metrics, storage comparisons, pitch and duration modification tests, and listening …

Challenges And Opportunities Of Mastery-Based Learning: A Student-Centered Analysis In An Upper Division Programming Languages Course, Parshana Sekhon

Master's Theses

Traditional grading structures in computer science courses reward performance on a few high-stakes assessments that may not accurately reflect a student’s mastery of concepts. Mastery-Based Learning (MBL) offers students multiple opportunities to demonstrate understanding through iterative feedback and reassessment, promoting their persistence and self-regulation. However, MBL can promote student behaviors like procrastination, “minimal effort” attempts, or de-prioritizing the course in favor of other courses with inflexible deadlines, which may undermine its effectiveness. This case study investigates how students navigated MBL in an upper-division computer science course at Cal Poly in San Luis Obispo. The course explores the fundamentals of programming …

Scorespeak: An Agentic System For Natural Language Control Of Musical Scores, Nathan S. Lim

Master's Theses

With the recent popularization of large language models (LLMs), natural language has become one of the most accessible and powerful ways for people to interact with creative tools. Although they have become common in mainstream domains like image and audio editing, there is currently no robust AI-based system that can reliably turn free-form language into edits for symbolic musical scores. This gap represents a missed opportunity to improve human workflows for creating and editing sheet music, but it is also a fundamental limitation for other agentic music systems; without a robust mechanism for translating free-form language into structured scores, AI …

Design And Implementation Of An Embedded Control System For The Cal Poly Spacecraft Attitude Dynamics Simulator, Neil Mahesh Bedagkar

Master's Theses

This thesis presents the development of a cascaded reaction wheel control system for Cal Poly's Spacecraft Attitude Dynamics Simulator. This work considers system architecture, empirical modeling, high-fidelity simulation, embedded firmware, hardware integration, and experimental characterization. In discrete-time simulation, it is shown that nonlinear direct model reference adaptive control (NDMRAC) enables a nonlinear, partially known plant with realistic actuator dynamics to track the response of a canonical second-order transfer function, with settling time within 4.67% and percent overshoot within order of magnitude of the second-order response. In hardware, the feasibility of a cascaded reaction wheel control architecture is experimentally demonstrated, achieving …

Empirical Comparsion Of Traveling Salesperson Approximation Algorithms, Shayan Daijavad

Master's Theses

The traveling salesperson problem deals with optimizing the route a traveling sales- person might take to visit a set of places exactly once and return back to their starting point. The problem is NP-hard, and it is hard to approximate in general, but special cases have many approximation algorithms, which come with tradeoffs. In this thesis we compare the runtime, approximation ratio, and overall implementation complexity of two approximation algorithms for the Euclidean version of the problem, a classical 2-approximation algorithm and the multifragment heuristic. We run both algorithms on randomly generated point sets and real world data from TSPLIB. …

Characterization Of The Thermally Driven Red Hue Effect In Coated And Uncoated Concrete Systems: Implications For Post-Fire Assessment In Wildland Urban Interface Communities, Juan C. Palominos Jr

Master's Theses

The increasing frequency and intensity of Wildland-Urban Interface (WUI) wildfires, such as the destructive 2025 Pacific Palisades Fire that destroyed over 6,000 structures, have underscored the urgent need for rapid post-fire safety assessment methodologies. This study sought to quantitatively characterize the Thermally Driven Red Hue Effect (TRHE), a unique, irreversible color shift observed in architectural coatings and concrete substrates, to determine its reliability as a permanent visual record of thermal exposure. Concrete substrates were formulated with three distinct coarse aggregates: gold granite (14.7% Fe), red cinder (22.4% Fe), and green rock (33.6% Fe) and coated with a 20 PVC waterborne …

Evaluating The Commercial Aquaculture Potential Of The Native Pacific Littleneck Clam (Leukoma Staminea) As A Climate Resilient Alternative To The Non-Native Manila Littleneck Clam (Ruditapes Philippinarum)., Skylar M. Wuelfing

Master's Theses

The California shellfish industry’s near-exclusive reliance on the non-native Manila littleneck clam (Ruditapes philippinarum) creates an economic vulnerability to climate-driven disturbances, which can cause mortality events that eradicate up to 80% of stocks. This singular reliance on an introduced species highlights a need for the evaluation of native alternatives like the Pacific littleneck clam (Leukoma staminea). Our goal was to assess the feasibility of using the native Pacific littleneck in commercial aquaculture by comparing their performance to the non-native Manila littlenecks across the following conditions: 1) a five-month field outplant trial at high and low intertidal …

Political Inconsistency Detection Across Legislative Speech And Public Communications, Scott M. Pramuk

Master's Theses

Political actors communicate about legislation across multiple contexts, including committee hearings, recorded votes, and public-facing press releases. Differences between these forms of communication can provide useful signals for journalists and researchers seeking to understand how legislators present policy positions to different audiences.

This thesis extends the Digital Democracy Project, a legislative transparency initiative that provides access to California state legislative hearing transcripts, voting records, and related legislative data. Specifically, this work incorporates publicly accessible, legislator-authored news releases into the Digital Democracy Database and develops a pipeline for analyzing legislative communication across multiple sources. The system collects news releases from California …