Digital Commons Network^™

Signature-Based Attribution Of Images Generated By Stable Diffusion, Bella White

Master's Theses

Generative AI is powerful yet controversial technology capable of spreading misinformation, non-consensual imagery, and offensive materials when not properly safeguarded against such abuse. Synthetic image alteration and generation have always been abused, from photo editing software to Generative Adversarial Nets, and now Diffusion Models. The Internet Watch Foundation and the National Center for Missing and Endangered Children have reported a consistent increase in reported AI generated child sexual assault materials (CSAM) and sextortion scams since the introduction of DMs. New digital forensics tools must evolve to adapt to the ever-changing landscape of AIG CSAM abuse. This work provides a comprehensive …

Why The Long Face? The Distribution And Niche Of The Imperiled Narrow-Faced Kangaroo Rat (Dipodomys Venustus), Garrett L. Gimbel

Master's Theses

Distribution models provide a practical use case of connecting ecological niche theory with species’ occurrence and assemblages. By explicitly linking Hutchinson’s “niche space” with geographic space researchers can gain valuable information on a species’ niche characteristics and interactions, thereby informing conservation and management practices. The narrow-faced kangaroo rat (Dipodomys venustus) is a highly understudied kangaroo rat species endemic to the central coast of California and is an ideal species to explore niche theory in distribution modeling. Three subspecies are currently recognized: The Santa Cruz kangaroo rat (D. v. venustus), the elephant-eared kangaroo rat (D. v. …

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

Master's Theses

ABSTRACT

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

Aged 539 Graduate Internship Report- Liberty High School, Brittany N. Johnson

Agricultural Education: Graduate Internship Reports

This document documents the AGED 539 Internship in Agricultural Education and examines the Liberty High School–Brentwood FFA and Agriculture Department’s alignment with the three-component model of agricultural education: classroom instruction, FFA leadership development, and Supervised Agricultural Experience (SAE). Grounded in experiential learning theory, the report reflects on program strengths, challenges, and growth across all twelve California Career Technical Education (CTE) Quality Criteria, supported by narrative reflection and evidence. The internship project focused on developing a formal FFA Program of Activities (POA) to improve chapter organization, goal-setting, and long-term sustainability. Overall, the project highlights intentional program planning and leadership development as …

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

Master's Theses

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

Forecasting Floral Demand To Reduce Operational Cost And Optimize Production, Mackenzi Saleh Mehlberg-Smith

Master's Theses

The floral industry faces rising operational costs, increasingly strict environmental regulations, and high market volatility, all of which threaten the sustainability of flower production. Accurate demand forecasting and production planning are therefore critical to minimize waste and reduce costs while maintaining competitiveness.

This thesis develops mathematical models for optimization, forecasting, and production planning in the floral industry, extending recent work on production planning and trapezoidal demand modeling. We integrate time-series forecasting methods with optimization techniques from production planning and operations research to model both short-term demand fluctuations and medium-term capacity constraints. The mathematical framework links linear and nonlinear optimization, time-series …

Accelerating Relationship Discovery In Chronic Lower Back Pain Through Knowledge Graph And Ontology Enhanced Large Language Models, Damon Lin

Master's Theses

Chronic lower back pain (cLBP) is a widespread public health burden linked to anxiety, depression, and opioid addiction. Interventions aimed at treating cLBP have shown minimal improvements in pain outcomes, leading researchers to reexamine our understanding of cLBP through constructing a causal model. However, constructing causal models through Randomized Controlled Trials are often unfeasible, and relying on domain expertise requires extensive and time-consuming research, posing a serious bottleneck for designing effective treatments. To accelerate this process, we apply Knowledge Graphs, Ontologies, and Large Language Models (LLMs) to aid researchers in determining possible causal relationships. First, we demonstrate how LLMs can …

A Comparative Evaluation Of Feedback Strategies For Enhancing Student Software Test Suite Writing Outcomes, Ashton Alonge

Master's Theses

Background and Context

Software testing is a fundamental component of computer science education, forming the basis for students’ ability to ensure program correctness and reliability. Despite its importance, many students struggle to design test cases that effectively expose faults and achieve meaningful test coverage. Traditional instructional approaches often emphasize code coverage metrics such as line or branch coverage, but these metrics may not adequately capture the quality of student tests. Mutation analysis, which measures how well tests detect small, artificial faults (mutants) introduced into the program, offers a potentially richer measure of test effectiveness. However, little is known about how …

Real Time Markerless 3d Hand Tracking For Intuitive Robotic Arm Control, Dylan G. Featherson

Master's Theses

This thesis presents a real-time, markerless motion-capture system for intuitive control of a multi-degree-of-freedom robotic arm. Using two synchronized RGB cameras and stereo-vision triangulation, the system reconstructs the three-dimensional position of a user’s hand without the need for physical markers or wearable sensors. The reconstructed 3D coordinates are mapped directly to the end-effector position of the Quanser QArm, a four-degree-of-freedom educational manipulator. Developed entirely in Python, the system integrates stereo camera calibration, 3D hand tracking with MediaPipe, coordinate transformation, and inverse kinematics into a unified real-time control pipeline operating at approximately 200 Hz. Calibration is performed through a checkerboard-based stereo …

Generalized Detection Of Animal Behavior Using Accelerometers, Alexander J. Arrieta

Master's Theses

Animal mounted sensors are becoming increasingly used to passively monitor both domestic and wild animals. Advances in lightweight accelerometer and GPS technology have allowed many animals to be fitted with high accuracy sensors for extended periods of time. This leads to new opportunities to study animal behavior without direct observation. However, interpreting the raw data is difficult due to the high volume and missing context of the information. Machine learning techniques excel at extracting information from raw data streams and are excellent candidates for processing the sensor data. However, due to large variance in how different animals execute the same …

Predicting Newsworthiness Of California Bill Discussions, Venkata Kedarnath Chaturvedula

Master's Theses

Among various California bill hearings, it is crucial to identify which hearings are most likely to receive media coverage, as this highlights the importance of the bill and the hearing, while also underscoring its societal impact. Digital Democracy, established at Cal Poly’s Institute for Advanced Technology and Public Policy, provides users access to a distinctive dataset and information about state legislative committee hearings, hearing transcripts, assets, bill information, etc.

This thesis presents a machine learning framework for predicting whether California legislative bills are likely to receive media coverage. Drawing on a dataset of legislative ”tip sheets” provided by Digital Democracy …

Origami-Inspired Pneumatic Soft Robotic Gripper, Conor J. Schott

Master's Theses

This thesis presents the design and evaluation of a vacuum-actuated, origami-based soft robotic gripper. A custom Sea Urchin crease pattern forms a lightweight folding skeleton that collapses radially under vacuum. The system emphasizes low cost and accessibility through laser cutting, 3D printing, and silicone molding. The Sea Urchin geometry was selected after digital and physical screening of candidate crease patterns for smooth folding, low strain concentration, and uniform inward motion. The folding skeleton is laser cut from 4 mil drafting film and folded into a compliant core. Four membrane configurations were developed: an origami gripper with a 36-inch balloon (Design …

Hallucination Techniques For Self-Supervised Synthetic Datasets For Mobile Robots, Wyatt D. Colburn

Master's Theses

Classical techniques in autonomous navigation struggle in tightly constrained spaces. Machine learning has been shown to perform better in these difficult environments but most techniques require large amounts of navigation experience for training. Using a new machine learning paradigm learning from hallucination (LfH), training data can be collected in a safe environment and not require supervision. Data is collected in real time while an agent performs a random walk in free space, supervision is not required as there are no obstacles for the robot to run into. After a random walk a post processing pipeline will hallucinate a safety corridor …

Birds In Changing Landscapes: Community Diversity And Breeding Phenology, Lindsay Peria

Master's Theses

Humans are altering the environment in varied and widespread ways. Increasing urban and agricultural development causes changes to habitat and resource availability as well as changes to the sensory environment via light and noise pollution. Climate change also causes more extreme temperature anomalies, storms, and droughts that challenge birds in a multitude of ways. In this thesis, we assessed these impacts of these changes on a local and continental scale. In the first chapter, we assessed the impact of natural, anthropic, and structural characteristics of viticultural land on both taxonomic and structural avian diversity. Loss of habitat from agriculture is …

Testing For Local Adaptation In Sympatric Monkeyflowers Growing In Serpentine Seeps And Adjacent Rock Outcrops, Avin Niknafs

Master's Theses

Divergent selection across heterogeneous environments can drive ecological differentiation and the evolution of locally adapted populations, even when gene flow occurs. We tested for local adaptation between two sympatric monkeyflowers, Erythranthe guttata and E. serpentinicola (formerly Mimulus), which co-occur on the central coast of California. Erythranthe guttata is a perennial species primarily found in moist serpentine seeps, whereas E. serpentinicola is an annual species restricted to adjacent serpentine rock outcrops. Using a reciprocal transplant experiment with second-generation, greenhouse-derived seed, we quantified germination, survival, and reproductive success across contrasting microhabitats. We further evaluated the relative contributions of species, lineage, …

Executive Committee - Agenda, 11/04/2025, Academic Senate

Academic Senate Agendas

No abstract provided.

A Convolutional Neural Network Approach To Breast Cancer Tumor Boundary Detection, James Leah Matlosz

Master's Theses

Breast cancer is the second most common form of cancer and often goes undetected in its initial stages due to its subtle symptoms. As the tumors grow, they become more difficult to surgically remove with clean borders. To minimize the chance of recurrence, a 2D convolutional neural network is developed in this work for delineating tumor boundaries. Specifically, the U-shaped network model is trained, validated, and tested with longitudinal MRI scans of patients diagnosed with breast cancer and undergoing neoadjuvant therapy. For training, image masks were generated as ground truths using signal enhancement ratio segmentation, thresholding, and contour detection. The …

Cal Poly (Cp) Legged Robot, Sebastian Barboza, Jonathan Mchale, Isabella Sorensen, Isaac Golan

Mechanical Engineering

The Navy spends $60 billion annually on dangerous ship maintenance performed by sailors. To save lives and resources, the Naval Surface Warfare Center (NSWC) is looking for robots to replace sailors and navigate ships to perform various tasks. Robots with tracks and wheels have been most recently explored by NSWC, however they have encountered significant problems navigating the ships, especially through naval ship doorways with a significant ledge. By using a legged robot, our team hopes to solve these problems and have a robot that can navigate the ship with relative ease and stability.

Academic Senate - Agenda, 10/28/2025, Academic Senate

Academic Senate Agendas

No abstract provided.

Academic Senate - Minutes, 10/28/2025, Academic Senate

Academic Senate Minutes

No abstract provided.

Executive Committee - Agenda, 10/21/2025, Academic Senate

Academic Senate Agendas

No abstract provided.

Atlas Of Ai: Power, Politics And The Planetary Costs Of Artificial Intelligence - Book Review, Jelena Popov

Feminist Pedagogy

No abstract provided.

Review Of Ai Needs You: How We Can Change Ai’S Future And Save Our Own, Tracy A. Fernandez Rysavy

Feminist Pedagogy

AI Needs You: How We Can Change AI’s Future and Save Our Own urges citizens to band together now, while A.I. is still in its nascent stages, to head off its potentially destructive repercussions and ensure that the technology serves more than just a wealthy few. While such efforts might seem out of reach in our polarized society, author Verity Harding points to three cases from history where policy was heavily influenced by multistakeholder collaborations. This review encourages educators to use the book as a way to study business ethics; out-of-the-box thinking; and intersectional, inclusive consensus-building over a top-down approach.

Spatially Resolved [O Iii] Emission Line Kinematics Of Reverberation-Mapped Active Galactic Nuclei With The Keck Cosmic Web Imager, Raymond P. Remigio, Vivian U, Aaron J. Barth, Nico Winkel, Vardha N. Bennert, Tommaso Treu, Matthew A. Malkan, Sebastian Contreras, Peter R. Williams, Jordan N. Runco

Physics

We present optical integral-field spectroscopic data of ten nearby (0.02 ≤ z ≤ 0.05) Seyfert 1 galaxies taken with the Keck Cosmic Web Imager. We map the spatially resolved kinematics of the [O iii] gas and stars, and investigate the alignments between their global kinematic position angles (PAs). Large-scale gas motions are primarily dominated by rotation and are kinematically aligned with the stars (ΔPA ≤ 30°). However, eight galaxies exhibit nonrotational kinematic signatures (e.g., kinematic twists, possible outflows) in their ionized gas velocity fields near the nucleus. We compare aperture-wide measurements of the gas and stellar velocity dispersions (σ …

Evaluating Machine-Learning Models For Drone-Based Image Analysis Of Coastal Ecosystem Dynamics, Katharine Mcdaniel, Pragati Toppo

College of Engineering Summer Undergraduate Research Program

Previous work from our group utilized drone-based images and a novel machine learning classification model to quickly and accurately quantify spatial variability in eelgrass in Morro Bay. In this SURP project we aim to develop and evaluate quantifiable estimates of the model’s prediction uncertainty. Our model produces a binary labeling indicating the presence or absence of eelgrass at each pixel. However, internally the model produces a probabilistic output indicating the likelihood of detection at each pixel that we propose to use to produce uncertainty estimates and a confidence interval for the cumulative extent of eelgrass detected. This would allow for …

Building An Inclusive Ai Chatbot For Diverse Student Communities At Cal Poly: Uplift Ai, Gideon Telahun

College of Engineering Summer Undergraduate Research Program

This research project will investigate the ability of advanced Large Language Models (LLMs) to identify and assess misinformation across diverse forms of media, including text, images, and video. In an age where misleading content spreads rapidly across digital platforms, evaluating the reliability and integrity of AI systems tasked with fact-checking is critical. We will develop a comprehensive dataset composed of factual and misleading examples drawn from various well-known and reliable fact-checking organizations. Each item will be independently reviewed and transparently labeled to ensure reproducibility. We will then prompt a curated group of state-of-the-art LLMs—including GPT-4, Claude, Gemini, Perplexity, Grok, and …

Approximating The Maximum Weighted Independent Set Problem Empirically, Sue Sue

College of Engineering Summer Undergraduate Research Program

In this project we investigate approximation algorithms for the maximum weighted independent set (MWIS) problem in random graphs that approximate real-world graphs, such as social networks. The problem involves finding a large collection of nodes in a network (vertices in a graph) such that no two nodes are directly connected to one another. Applications of the MWIS problem are broad and include clique-finding algorithms as well as the use of large independent sets in distributed algorithms. We build on prior work by the mentor with a SURP 2024 and senior project, in which preliminary findings suggested that a standard greedy …

Machine Unlearning: The Right To Be Forgotten, Colin Ngo

College of Engineering Summer Undergraduate Research Program

The objective of this SURP proposal is to investigate machine unlearning as a viable approach to support the right to be forgotten in artificial intelligence (AI) systems, many of which rely heavily on personal data. The capability to selectively remove user-specific information upon request—without necessitating full model retraining—is critical for safeguarding individual privacy and enhancing computational and energy efficiency. This project will undertake a systematic review of state-of-the-art unlearning techniques, evaluate their performance using standard benchmark datasets, and assess their feasibility in real-world applications. In addition, the project will provide participating students with practical experience in implementing and analyzing machine …

Relational Algebra Interpreter, Sydney Lynch

College of Engineering Summer Undergraduate Research Program

We would like to build a compiler for relational algebra that converts it to SQL. This compiler will be used in database labs to give the students hands-on experience to write relational algebra code. Current relational algebra compilers that are open source are not very good and are hard for the students to use.

Orbital Mechanics And Ai, Daniella Luciani, Cliodhna Mcguigan

College of Engineering Summer Undergraduate Research Program

Traditional orbital mechanics courses typically start with simpler problems that can be solved on paper, gradually progressing to more complex problems that require computational tools. In the AERO department, we have traditionally used MATLAB for these computational tasks. However, the industry is increasingly shifting toward platforms like Python for coding these types of problems. Additionally, with the rapid rise of AI, tools like ChatGPT are now at the forefront of code generation. To stay ahead, students need to learn how to generate code using AI and assess whether the generated code is functioning as expected. This SURP will have students …