Digital Commons Network^™

Object Detection And Classification For Man-Made Structures To Aid In Search And Rescue (Sar), Mio A. Nakagawa

Master's Theses

This project explores the use of various object detection and classification models to identify permanent man-made structures, specifically cell towers, water towers, watch towers as well as its corresponding shadows (attributes), from aerial imagery. The goal is to evaluate those models and test the feasibility of current models to detect man-made structures in aerial images, in an effort to support search and rescue operations as well as update network infrastructure databases. Multiple object detection models, as well as classification models, including YOLOv8 and VGG19 are implemented and trained on annotated aerial images to determine the presence or absence of man-made …

Prototype X-Band Front End Upconverter & Transmitter With An Integrated Pll, Mont Ziadoon Murad

Master's Theses

In recent years, there has been growing interest in high-speed communication for small satellites. Achieving higher communication speeds will enable any experimental CubeSat to conduct experiments at higher rates and allow further research into SAR and deep-space exploration. At Cal Poly, the CubeSat Lab has mainly operated at 9600 baud and utilized the Ultra High Frequency (UHF) amateur radio band. While it has proven itself resilient, the UHF band lacks the infrastructure to support higher-bandwidth communication systems. To address this gap, this work presents a prototype space-side downlink RF front end comprising an upconverter, a power amplifier (PA), and a …

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 …

Hamster: Hybrid-Actuated Mobile Spherical Terrain Exploration Rover, Winnie Gao

Master's Theses

The expansion of space exploration to increasingly challenging planetary environments requires mobility systems capable of extreme traversal capabilities and operational reliability. This thesis presents the design, development, and testing of a low-cost Hybrid-Actuated Mobile Spherical Terrain Exploration Rover (HAMSTER) intended for use on a planetary surface exploration mission. HAMSTER uses a pendulum-based actuation method for steering and an actuated internal shaft to propel the vehicle forward. The internal structure includes a two-tiered central case composed of the navigation control module, accelerometer, motor controller, primary DC motor, battery, voltage regulators, Raspberry Pi, pendulum servo motor, and drive shafts. Additive manufacturing through …

Trustworthy Intelligence Fusion For Search And Rescue: Designing Grounded And Secure Multi-Agent Ai For Mission Decision Support, Yayun Tan

Master's Theses

Search and rescue (SAR) operations require teams to integrate uncertain information under severe time pressure. Large language model (LLM)-based multi-agent systems (MAS) can support decision-making, but they also risk producing hallucinated outputs and processing unreliable or malicious data. This thesis addresses these risks through three linked studies. First, it proposes a modular eight-agent SAR MAS architecture that reflects the structure of real SAR missions by assigning specialized roles to different agents. Second, it introduces a post-hoc probabilistic verification framework that checks LLM agent outputs against a probabilistic knowledge graph built from historical SAR incidents.  Third, the thesis examines indirect adversarial …

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. …

Uncertainty-Weighted Fusion Of Sensor And Monocular Foundation-Model Depth For 3d Gaussian Splatting In Indoor Rgb-D Capture, Brandon S. Howell

Master's Theses

Depth-supervised 3D Gaussian Splatting can improve scene geometry in indoor RGB-D capture, but noisy commodity depth measurements can also reduce rendered image quality. This thesis studies that trade-off in room-scale indoor reconstruction using two complementary depth sources: Kinect-class RGB-D sensor depth, which is metric but noisy and incomplete, and Depth Anything 3 (DA3) monocular depth, which is dense and meter-valued but not calibrated to the sensor or laser-reference geometry. 

The proposed method constructs a per-pixel depth supervision target by inverse-variance fusion of the sensor depth and the monocular depth prediction. The fused target is used to train a depth-supervised 3D …

Space Quacker Advanced Development (Squad): Lora Modulation On A Leo Cubesat Mission For Evaluation Of 916 Mhz Uplink, Samantha Brunton

Master's Theses

The LoRa Modulation format was developed by SEMTECH in 2018 and has revolutionized terrestrial Internet of Things (IoT) networks. LoRa (Long Range) has been successfully demonstrated as a long-range, low-data-rate communication modulation format and packet protocol for low-power terrestrial applications. LoRa offers low power consumption, low cost, robust signal sensitivity, and long communication range. Recently, interest has grown in using LoRa communication in Low Earth Orbit (LEO) satellite systems, especially for global IoT connectivity. Previous studies have investigated the theoretical feasibility and simulated the performance of LoRa satellite communication. Companies such as Lacuna Space have demonstrated the practical potential of …

Comparative Analysis And Optimization Of Control Strategies For Single Axis Tracking Solar Arrays On Skewed Topography, Emerson Nicholas

Master's Theses

Photovoltaic solar farms on uneven terrain present consistent challenges to performance optimization. Standard backtracking algorithms can generate potential losses due to interrow shading caused by sloped terrain as well as a lack of plane of array irradiance that can occur even on level ground. The purpose of this thesis is to use the Gold Tree site as a case study to develop and evaluate different solar tracking control strategies. Specifically, it compares the relative performance of fixed, direct tracking, closed-form backtracking, and global optimization strategies. It is done under a two-dimensional, idealized predictive power model of a representative portion of …

Development Of A Video-Based Tool To Measure Motor Asymmetry In Infants At Risk For Hemiparesis, Roha Ali

Master's Theses

Congenital hemiparesis is a unilateral motor impairment stemming from brain injury in utero or early postnatally. Hemiparesis can be difficult to detect in early infancy with current clinical tools. Yet, early identification of motor asymmetry could play a key role in the design of effective early intervention and rehabilitation strategies. This thesis presents the development and validation of a video-based tool designed to extract infant limb movement data using DeepLabCut’s (DLC) machine learning network. The pipeline was developed using videos of typically developing (TD) infants and infants with Asymmetric Perinatal Brain Injury (APBI), all at or under 3 months corrected …

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 …

A Security Framework For Pacemaker Lead Failure: Anomaly Detection System And Failsafe Policy Considerations, Ethan Wagner

Master's Theses

Embedded system security in implantable medical devices (IMDs) remains an underexplored challenge due to the unique constraints of these systems. Specifically, pacemakers are optimized for ultra-low power consumption to maximize device lifespan, are highly resource constrained, and demand reliable and correct operation to prevent severe health consequences. These systems rely on sensing electrodes, called leads, to detect cardiac activity and stimulate the patient’s heart when appropriate. Therefore, pacemaker lead integrity is a critical issue, as malfunction or compromise can result in device failure jeopardizing patient safety.

The security framework presented in this thesis integrates several works to proactively detect and …

Controllable Tile-Based Level Generation For Vertical Platformers, Aiden P. Smith

Master's Theses

Procedural Content Generation (PCG) has had much research poured into it in recent years, as it is a way to more easily create content and levels for player replayability. Historically, this type of level generation has been done by algorithms with strict rules and black-and-white decision making. However, in recent years Large Language Models (LLMs) have been fine-tuned for this task in research in games such as Super Mario Bros and other 2D platformers. In this thesis, we apply a similar approach to level generation for a vertical platformer called Kid Icarus. We create a tile-based level generation system that …

Large Scale Kmer-Based Proteomic Analysis: An Application Towards Evolutionary Constraint Discovery, Matthew Chak

Master's Theses

Large protein databases now make it possible to study short peptides across natural protein sequence space at unprecedented scale, but exhaustively counting k-mers across billions of protein sequences remains computationally difficult. This thesis develops an exact amino-acid k-mer counting method based on direct addressing, in which fixed-length amino-acid strings are encoded as base-20 integers and updated with a sliding-window recurrence. By avoiding key storage and collision resolution, this approach removes overhead inherent to hash-map-based methods when the k-mer space is sufficiently dense. A memory analysis shows when direct addressing is preferable to open-addressing hash tables, and expected-saturation calculations motivate its …

Effect Of The Stacking Sequence And Number Of Ply Orientation In A Quasi-Isotropic Laminated Plate On In-Plane Shear Modulus And Failure Modes, Ann Larson

Master's Theses

Maximizing the shear modulus and strength, as well as predicting failure mode and location, when designing a stacking sequence of quasi-isotropic carbon fiber laminated plates is essential to predict stability, resistance to deformation, and overall stiffness of the structure. This research investigates the effect of the stacking sequence of quasi-isotropic laminated composite plate materials in accordance with ASTM D5379: Standard Test Method for Shear Properties of Composite Materials by the V-Notched Beam Method.

In this research, experimental testing and Finite Element Analysis (FEA) were first used on aluminum to validate the simulation process before applying it to composite materials. The …

Analysis And Design Of Auger Cast Piles With Isolation Casing, Zachary Lindsay

Master's Theses

This research addresses the analysis and design of double cased piles. Bay Area Rapid Transit (BART) runs a large rail system both above and below ground that connects the entire Bay Area. BART requires that all new constructions avoid transmitting axial load to their tunnels from adjacent piles. If piles fall within the zone of influence, builders must install double cased piles. Double casing is where there is an extra casing around the pile, with an air gap between them. The air gap prevents load from transferring to the outer casing. The length of this casing is called the isolation …

Structured Dynamic Factor Analysis Of Environmental Time Series With Application To Morro Bay Estuary, Jose Garcia

Master's Theses

This thesis develops a structured dynamic factor analysis (sDFA) framework for decomposing multivariate environmental time series into latent biological and physical components. The methodology is applied to five years of high-resolution passive monitoring data collected from two sites in Morro Bay, California from 2020 through 2024. Relative contribution indices are developed based on the structured DFA that measure how much each latent process contributes to each observed variable at any given time. Structured DFA models fit to the application data suggest site-specific patterns in how biological and physical processes affect water quality variables. At the bay mouth location, physical processes …

A2s Uplink Latency Minimization For Wildfire Monitoring Systems Using Mbse And Stochastic Modeling, Luis Giovanni Wang

Master's Theses

Wildfire response depends on how quickly a detection reaches the people who act on it, and the slowest remaining step is often the link that carries an alert from a remote sensing platform to a satellite. This thesis models the latency of that link, the Air-to-Space uplink, for a wildfire-monitoring UAV that carries a Starlink terminal and sends an ALERT packet to a serving Low Earth Orbit satellite. The uplink is difficult to predict because both the UAV and the satellite move, and because the wildfire environment degrades the channel at the moment the data matters most.

The thesis uses …

Evaluating The Cost-Benefit Tradeoffs Of Simt Control Mechanisms In Resource-Constrained Gpus, Nikolas Tambornini

Master's Theses

This thesis conducts a hardware-level analysis of the cost–benefit tradeoffs associated with increasingly complex SIMT control mechanisms in a resource-constrained GPU core. Four design implementations are evaluated: a Base Tiny GPU without warp scheduling capability; a Warp Scheduler using round-robin warp selection; a Branch Divergence implementation incorporating a dedicated divergence stack and post-dominator reconvergence mechanism; and a Dynamic Warp Allocation implementation that replaces the static warp structure with a runtime warp manager, regrouping threads by current program counter to recover SIMD lane utilization during active divergence. Each design is evaluated using two complementary measurements: functional simulation implemented using the CocoTB …

Multimodal Machine Learning For Soil Burn Severity Mapping Across California Wildfires, Sanjana Checker

Master's Theses

Accurate mapping of soil burn severity (SBS) is critical for post-fire watershed management, erosion risk assessment, and ecological recovery planning, yet traditional field-based approaches remain costly, time-intensive, and spatially limited. This thesis presents a machine learning pipeline for wall-to-wall SBS classification across California wildfires using multi-sensor satellite imagery, terrain derivatives, and bioclimatic covariates. Field-collected SBS observations (n = 2,180) from 52 wildfires occur- ring between 2013 and 2025, sourced from the U.S. Forest Service and CAL FIRE, were used to train and evaluate multiple classification architectures within a Google Earth Engine and Google Cloud-based prediction framework. After upsampling the unburned …

Limiting Inconsistencies In Legal Languages, Sarah B. Lawsky - Professor Of Law

Vanderbilt Journal of Entertainment & Technology Law

Inconsistencies play different roles in law and in logic, respectively, and programming languages designed to code law should therefore, when possible, be designed to prevent the encoding of inconsistencies. While inconsistencies in standard logic “explode” the argument, allowing anything at all to be proven, apparent inconsistencies in law simply indicate that further guidance is needed. Programming languages should be limited not because such inconsistencies do not exist in the statute, but rather exactly because they do. Inconsistencies in the law should, as they are now, be addressed by Congress, the courts, and administrative agencies, and any computer code implementing the …

Neuron Notes, Araceli Franco, Ethan Diec, Max Blennemann, Shibo Cong

Computer Science and Engineering Senior Theses

Mainstream digital note-taking tools such as Notion, Microsoft OneNote, and Evernote organize knowledge around linear documents and rigid folder hierarchies, a structure that strays from the associative, graph-like nature of human semantic memory. Mind-mapping and linked-note systems such as XMind, Obsidian, Roam Research, and Logseq move closer to that associative model but still constrain users to short labels, automatic layouts, or page-centric workflows that underutilize spatial and visual recall. This thesis presents Neuron Notes, a spatial, graph-based note-taking system designed to align digital organization with how people actually form and retrieve ideas. The system is implemented as a three-tier web …

Accessibility In The Edtech Era: The Growth In Implementation Oflearning Technologies And Thestudents Who Are Left Behind, Madeleine Braksick

Vanderbilt Journal of Entertainment & Technology Law

Educational Technology (EdTech) has gained popularity in recent years, enabling distance learning and connectedness across school districts, and among students, teachers, and families alike. However, vague or nonexistent standards for regulating these technologies have led to students with rights to special education services not having those services upheld to the same standard as traditional educational mechanisms. While the Individuals with Disabilities Education Act (IDEA) has been modified over time to form heightened standards for making education appropriate for all students, it has consistently fallen short in its regulation of both assistive and educational technologies. This Note explores the consequences of …

Linking (Imagined) Communities: World Language Students' Stereotypical Attributions To Native Speakers And Teachers Of German., Lucian Rothe

Faculty and Staff Scholarship

Abstract This study explores language learners' stereotypical descriptions of native speakers (NSs) of German and their relationship with participants' perceptions of teachers of German. It expands motivation research that employs stereotypes to gain insight into university students' views of target language (TL) speakers (Rothe, 2022, 2025). Sixty‐seven learners of German and 43 learners of other world languages (WLs) pro vided responses about NSs and instructors, while also rating the stereotypes' perceived accuracy. Participants held various stereotypical notions about NSs, reflecting broader societal narratives. Learners of German pro vided more detailed stereotypical descriptions. Both groups considered favorable stereotypes as more accurate …

2026 June - Tennessee Monthly Climate Report, Tennessee Climate Office, East Tennessee State University

Tennessee Climate Office Monthly Reports

Hi All,

The main weather and climate stories for Tennessee in June 2026 were several rounds of heavy rainfall that produced flash flooding in different parts of the state. Early in the month slow moving storms produced heavy downpours in different parts of the state from June 7 to 14 including areas in or around Knoxville, Nashville, and Memphis, as well as portions of Henry, Weakley, and Carroll counties in northwestern Tennessee. Four different locations across the state reported daily rainfall records between these dates.

Later in the month, more widespread heavy rains impacted southern sections of West and Middle …

A Simulation To Compare Models For A Longitudinal Ordinal Response With A Multilevel Cross-Classified Data Structure, Rachel S. Perlin

Dissertations, Theses, and Capstone Projects

This is a simulation study that compares four models for analyzing three-level longitudinal cross-classified data with an ordinal outcome, treatment effect and a category-specific effect. The models include the cumulative model, the sequential model, the adjacent category model, and a metric model. Data were generated for each of the first three models with 27,000 generated datasets each, totaling 81,000. The datasets vary along three continuous variables: the number of level-3 units, the ratio of treatment groups to control groups, and the treatment effect size. The outcome has four ordinal response categories. Each model had two predictor variables: treatment and time. …

Unrepresentable Objects: Neoliberalism In The Contemporary Novel In French, Alicen Marie

Dissertations, Theses, and Capstone Projects

This dissertation operates at the intersections of textual analysis, political theory, psychoanalytic theory, and aesthetics to investigate the prevalence of uncanny imagery in ten examples of contemporary fiction, while also interrogating the notion of the uncanny as a category of analysis. Entitled “Unrepresentable Objects: Neoliberalism in the Contemporary Novel in French,” it examines a group of novels by Marie Darrieussecq, Virginie Despentes, Marie NDiaye, and Linda Lê, published in France between 1993 and 2017. These novels share an aesthetic of hauntedness and breakdown, incongruous affect, and a continual presence of the uncanny; they depict a world split from history and …

Essays On The Economics Of Aging: Structural And Machine Learning Approaches, Alexander S. Kwon

Dissertations, Theses, and Capstone Projects

Population aging has made the study of older workers’ economic behavior increasingly important for understanding labor markets, retirement systems, and public policy. In many advanced economies, rising old-age dependency ratios have increased the need to understand labor-supply, retirement, and savings decisions later in life (OECD, 2025). In the United States, these issues are especially important because Social Security faces long-run financing pressure, with the Old-Age and Survivors Insurance Trust Fund projected to be depleted around 2033 (U.S. Social Security Administration, Office of the Chief Actuary, 2025). Longer life expectancy increases the expected length of retirement and raises the fiscal importance …

Technology Before, During, And After Incarceration: Current Product Landscape, Sociotechnical Concerns, And Legal Considerations In The U.S. Context, Yael Eiger, Taylor Hansen, Teanna Barrett, Jevan Hutson, Bryce Clayton Newell, Franziska Roesner

Articles

Emerging technology, including AI, is proliferating throughout the U.S. carceral system. These technologies are marketed to prisons and police departments and then procured using taxpayer money. Previous investigative reporting has exposed troubling kickback schemes, unconstitutional data collection practices, and biased algorithmic outcomes in a handful of prominent technologies (e.g., Flock, Palantir, Clearview AI, COMPAS). In this work, we consider the broader ecosystem of carceral technologies: we catalog 122 products from 53 companies selling technology to carceral institutions. In a collaboration among computer science, law, and surveillance studies scholars, we surface sociotechnical, ethical, and legal concerns related to the use and …