Digital Commons Network^™

An Exploratory Latent Segmentation Approach To Account For Temporally Shifting Parameters In Driver Injury-Severity Models, Tanmoy Bhowmik, Shahrior Pervaz, Fred Mannering, Naveen Eluru

Civil and Environmental Engineering Faculty Publications and Presentations

Temporally shifting parameters in crash severity modeling is a well-documented phenomenon, with growing evidence suggesting that the influence of explanatory variables changes over time due to shifts in driver behavior, vehicle technology, and roadway conditions. Many studies have examined this issue by comparing the temporal stability of adjacent-year data using a variety of modeling frameworks that have often assumed a homogenous effect of explanatory variables across the entire crash population. The current research effort departs from past work in two ways. First, it compares data separated by multiple years (instead of comparing adjacent years), and second, it tests the homogeneous …

Evidence Brief: Shifting Attitudes And Social Norms On Fgm Through Community-Based Interventions In Somaliland, Stella Muthuri, Dennis Matanda, Francis Obare, Stephen Kizito, Chi-Chi Undie

Sexual and Reproductive Health, Rights, and Choices

This study, conducted in Sool and Sanaag regions of Somaliland within the context of The Girl Generation Support to the Africa-Led Movement (TGG-ALM), provides insights into how community-based, dialogue-driven interventions influence attitudes, social norms, and behavioural intentions related to FGM and gender.

Findings show that while personal opposition to FGM is relatively high, this does not consistently translate into perceived or collective opposition. Individuals tend to view their own attitudes as more progressive than those of their families and communities, pointing to a critical “norms misalignment” that constrains behaviour change. This gap suggests that entrenched social expectations – particularly around …

Paidar: Private Sector Allied For Inclusive Delivery Of Accessible Reproductive Health, Population Council Pakistan

Sexual and Reproductive Health, Rights, and Choices

Pakistan continues to face critical challenges in increasing contraceptive use and reducing the unmet need for family planning (FP). While public-sector facilities remain key providers, a substantial proportion of healthcare seekers rely on private family physicians as their initial point of contact.

Recognizing this strategic opportunity, the PAIDAR study was designed to strengthen the role of private- sector male family physicians in FP service delivery. Implemented across six diverse districts of Punjab, supported by Health Care Commission Punjab and Department of Health and Population Punjab, the intervention enhanced providers' capacity to deliver quality FP counselling, contraceptive services, structured referrals, and …

Making Better Use Of Data For Improved Health Service Delivery In Punjab: Transforming Data Into Action Evidence, Population Council Pakistan

Sexual and Reproductive Health, Rights, and Choices

Strong health systems depend not only on collecting data, but on using it effectively for planning, monitoring, and decision-making. To strengthen evidence-based management across Punjab's health sector, the Population Council partnered with the Health and Population Department, Punjab, particularly the Health Information and Service Delivery Unit (HISDU), to improve the utilization of routine health information. This brief summarizes the collaboration's focus on three complementary areas: (1) Development of the ASET (Analytics for Service Efficiency and Tracking) platform to transform routine data into actionable information; (2) Strengthening the Capacity of Data Users through specialized training in data analytics, visualization, and use …

Table Tennis Training Instrument (Ping Pongers), Derick Alvarado, Peter Sandberg, Andrew Wong

Mechanical Engineering Senior Theses

Table Tennis is an extremely popular sport worldwide, boasting an extensive market. However, it is a sport that generally requires other people to both play and practice with. The goal of this project was to create a machine that would serve table tennis balls for the purpose of individual practice. The machine was meant to fill the niche that other machines of the same type filled by allowing individuals to practice on their own without the assistance of another player or a coach. The main goal of the project was to offer a market competitive device, sharing the same basic …

Social Relationships, Mental Health, And Stigma: A Qualitative Study Of Social Networks And Hiv Disclosure In Western Kenya, Sarah Obatsa, Adel Mburia-Mwalili, Salvador Jauregui, Karla Wagner, Lukoye Atwoli, Francesca Odhiambo, Jayne Lewis-Kulzer, Suzanne Goodrich, Kara Wools-Kaloustian, Jennifer Syvertsen

Internal Medicine, East Africa

The disclosure of one’s HIV-positive status is a personal decision that can play an important role in engagement in HIV treatment and care. Social network approaches situate individuals within broader webs of social connections that influence health and wellbeing and thus hold the potential to elucidate key social factors shaping the process of disclosure. As part of a larger clinical study examining how substance use and mental health shape HIV outcomes, we recruited 61 individuals newly diagnosed with HIV at two clinics in Western Kenya to participate in an egocentric social networks study. We conducted a survey that generated a …

Social Media Is A Juggernaut: Lagged Correlation Analysis Using Ngram Data On “Internet” And “Social Media” With Amplification By The Advent Of The “Iphone”, William Zywiak, Gao Niu, Nicolas Petrell, Victoria Nichele, Kirsten Hokeness

Mathematics and Economics Faculty Journal Articles

The amount of new information transmitted per day can be overwhelming. The data available through Ngram Viewer allows statistical examination to determine the most salient topics, as well as lagged correlation and lagged variance to support possible causal connections between concepts. Using this database, we determined that COVID, crypto, microplastics, and especially social media are important topics of the last few years. We also present results that suggest the development of the internet and the iPhone fueled the prominence of social media, and the access of the iPhone also increased access to the internet.

Integrating Multi-Scale And Multi-Filtration Topological Features For Medical Image Classification, Pengfei Gu, Huimin Li, Haoteng Tang, Dongkuan Xu, Erik Enriquez, Dongchul Kim, Bin Fu, Danny Z. Chen

Computer Science Faculty Publications

Modern deep neural networks have shown remarkable performance in medical image classification. However, such networks either emphasize pixel-intensity features instead of fundamental anatomical structures (e.g., those encoded by topological invariants), or they capture only simple topological features via single-parameter persistence. In this paper, we propose a new topology-guided classification framework that extracts multi-scale and multi-filtration persistent topological features and integrates them into vision classification backbones. For an input image, we first compute cubical persistence diagrams (PDs) across multiple image resolutions/scales. We then develop a "vineyard" algorithm that consolidates these PDs into a single, stable diagram capturing signatures at varying granularities, …

The Impact Of New York's 2026 Climate Law Retreat, Jonathan A. Binder, Vincent M. Nolette

Sabin Center for Climate Change Law

On May 26, 2026, New York State enacted significant revisions to its 2019 Climate Leadership and Community Protection Act (CLCPA). The 2026 Amendments, which include changes to the greenhouse gas (GHG) emission accounting methodology, the statewide GHG emission limits, and the requirement to adopt implementing regulations, collectively weaken the Act's ambition. New York’s retreat from state climate action after championing it for years reflects a broader national trend of de-prioritizing mitigation efforts.

The 2026 Amendments will have vast and important consequences for the implementation of the CLCPA. Numerous actions will need to be updated through rulemaking, guidance, or other administrative …

Mitigating Disparities In Diagnosis Of Dementia, Lycia Tramujas Vasconcellos Neumann, Simin Mahinrad, Erin L. Abner, Soo Borson, Goldie S. Byrd, Maria Carrillo, Lindsay Clark, Anthony N. Correro Ii, Kacie D. Deters, Gladys E. Maestre

School of Medicine Publications

The field of Alzheimer's disease and related dementias (AD/ADRD) is undergoing a transformative shift with a better understanding of disease biology, biomarker-based diagnostics, and disease-modifying therapies. Yet, these advancements risk exacerbating existing disparities in diagnosis and care. The 2024 Alzheimer's Association International Conference (AAIC) Advancements: Exploring Equity in Diagnosis convened interdisciplinary experts to address these inequities and chart a path toward population-generalizable research and practice. This article synthesizes key insights from the conference, highlighting considerations for inclusive and representative research design, ethical approaches in diagnostic disclosure, as well as challenges and solutions at individual, community, and systemic levels to advance …

Cut And Cultivate: Process And Practice, Kailey Atkinson

Master of Fine Arts in Visual Arts

Using a candy-coated, flower-ridden, bright palette and maximalist sense of composition, my artwork builds community through narrative collage, photography, painting, sculpture, poetry, and social practice. Through a feminist lens, these bright works explore body image, gender roles, and social issues. Obsessively collecting and repurposing an archive of vintage imagery, my work draws parallels between traditional and contemporary topics through the language of collage and redaction.  My nascent social practice has led me to engage with narratives outside my own experience and offer my process as a healing modality to other women.

In a tumultuous political climate where art can serve …

Darkness Seen By Candlelight: Painting To Discover Feeling, Shelby Feltoon

Master of Fine Arts in Visual Arts

This thesis discusses the ways that a phenomenological experience can translate itself through the medium of painting. This translation evokes deep feelings through physical considerations of materiality, light, context, distance, and time. Through a series of intimate and abstracted oil paintings created in thin layers, the work conveys an interdependent relationship between light and darkness. This project draws from research on art movements like Suprematism, Minimalism, and Expressionism, as well as larger practices and philosophies about photography and the sublime. The body of work draws direct reference to Junichiro Tanazaki’s essay In Praise of Shadows. Ultimately, the work described …

Determinants Of Extended Postanesthesia Care Unit Stay, Jonathan Vaughn

Nursing Publications

Frustration is a common emotion felt by up to 70% of workers in high-stress environments.1 As a Certified Registered Nurse Anesthetist, I can attest to the postanesthesia care unit (PACU) as being a high-stress environment. The PACU Registered Nurses and staff provide expert care to postoperative patients. The PACU offers postoperative patients a safe recovery from anesthesia through monitoring and stabilization, as well as pain and symptom management through prevention and early intervention. It prepares patients for timely discharge or transfer.2 At times, some patients may experience adverse effects in the PACU, resulting in a longer than 90-minute length of …

Skinclusive Ai: Towards Equitable Skin Cancer Detection For Deployment On Edge Devices, Joseph Galicinao

Master's Theses

Skin cancer is one of the most prevalent cancers worldwide, yet existing deep-learning models exhibit significant racial disparities because many widely used datasets are heavily skewed toward lighter skin tones. In addition, many approaches are not designed for deployment on resource-constrained devices, which limits accessibility. This work presents a comprehensive evaluation of classical machine learning and deep-learning based models for binary skin lesion classification, identifying the Swin-Tiny transformer architecture as the most effective backbone. To address bias, we curate a skin-tone balanced dataset, and introduce fairness-aware training through adversarial training, and joint distribution oversampling, to improve performance across protected attributes. …

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 …

Trim-Transfer: A Transfer Learning Approach For Cross-Trim Level Can Intrusion Detection, Baylor J. Whitehead

Master's Theses

Modern vehicles contain many Electronic Control Units (ECUs) that communicate through CAN. While CAN enables efficient data communication, it lacks built in authentication and encryption, allowing adversarial actors to inject malicious CAN messages. This limitation has motivated the development of CAN intrusion detection systems (IDS). However, deploying IDS across a vehicle lineup requires collecting large labeled datasets and retraining models, increasing development cost and limiting scalability.

This thesis investigates the use of transfer learning with LSTM-based deep neural networks to reduce retraining cost while maintaining model detection performance. A baseline LSTM model is trained using CAN data from a base …

Exploring Regenerative Vegetable Systems On The Central Coast Of California, Una S. O'Connell

Master's Theses

As climate change and current agricultural practices place pressure on the long term sustainability and resilience of food production systems, there is growing interest in whether existing agricultural systems can adapt to maintain productivity while improving environmental outcomes.

This study evaluated the effects of regenerative versus standard organic vegetable production systems on yield, insect communities, and weed suppression across three field trials conducted on California's Central Coast. In addition, I collected baseline soil health data for all trials. Trials 1 and 2 were carried out at the Cal Poly San Luis Obispo Organic Farm using cabbage and broccoli as cash …

A Comparative Study Of Model Predictive Control And The Stanley Method For Vehicle Path Tracking Applications, Noah S. Fitzgerald

Master's Theses

This thesis compares a model predictive controller (MPC) and a lateral Stanley controller for vehicle path-tracking applications under simulation-based and perception-driven operating conditions. Both controllers were evaluated in simulation using a nonlinear dynamic bicycle model executing single and double lane change maneuvers. Following simulation-based evaluation, both controllers were implemented on hardware within a perception-driven steering-control pipeline. This pipeline utilized recorded sensor data from the MXcarkit 1/8^th-scale autonomous vehicle platform, incorporating lane instance segmentation and homography-based roadway estimation.

Under idealized simulation conditions, the MPC demonstrated improved trajectory-tracking performance during aggressive maneuvers while requiring greater steering activity and computational effort …

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 …

Constructing Orthonormal Bases With The Residuals Of Successive Approximations, An Introduction To Multiresolution Analysis, Elijah J. Guptill

Master's Theses

Wavelets and wavelet analysis are used in the study of signal processing, quantum field theory, functional analysis, multifractal analysis, and various other areas of mathematics. Multiresolution analysis provides a framework for building a wavelet basis of $\mathcal{L}^{2}(\mathbb{R})$ from a scaling function $\phi$, whose dyadic dilations and translations, $\{2^{j /2}\phi(2^{j}x-k):j,k\in \mathbb{Z}\}$, approximate $\mathcal{L}^{2}(\mathbb{R})$. One of the key properties of  $\phi$ is that it must satisfy $\phi(x)=\sum_{k\in \mathbb{Z}}{p_{k}2^{j /2}\phi(2^{j}x-k)}$ with respect to the norm on $\mathcal{L}^{2}(\mathbb{R})$. This equation is called a two-scale difference equation. Such equations enforce a regularity on the ordinary generating function $2^{-1 /2}\sum_{k\in \mathbb{Z}}{p_{k}z^{k}}$, known as the quadrature condition. …

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, …

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 …

Evaluation Of Ultraviolet-C Light For Control Of Mites And Western Tarnished Plant Bug In Strawberry & Interactive Lethal Effects Of Common Strawberry Fungicides And Adjuvants On Phytoseiulus Persimilis, Colin T. Koubek

Master's Theses

California strawberry production relies heavily on chemical pesticides to manage arthropod pests and diseases, but pesticide resistance, regulatory pressure, and the need to conserve biological control agents have increased interest in alternative pest management tools. This thesis evaluated ultraviolet-C (UV-C) light as a nonchemical management tool for key strawberry arthropod pests and assessed the compatibility of common strawberry fungicides and adjuvants with the predatory mite Phytoseiulus persimilis Athias-Henriot. The first objective was to determine the ovicidal and lethal effects of UV-C light on Lygus hesperus Knight eggs and nymphs. Laboratory and field ovicide assays were conducted using UV-C doses relevant …

Developing A Humpback Whale Vocalization Detector Using Machine Learning Models, Lucas Kantorowski

Master's Theses

Humpback whale songs are notoriously complex. Identification of humpback whale song units requires bioacousticians to tediously listen, analyze, and annotate collected sound data. Even sparse data requires listening to the entirety of the collected acoustic data. In this study, three hours of audio containing over one-thousand humpback whale song units was collected in Monterey Bay, California.

Prior studies have seen success using convolutional neural networks by performing image classification on hundreds of hours worth of spectrograms. Our study uses traditional machine learning models, as they are less computationally demanding, and require less data.

We use time splitting and Mel-frequency cepstrum …

Discovering Differentially Correlated Sets Across Multiple Treatments, Tyler J. Stoen

Master's Theses

When comparing data sampled under several different conditions, we often want to study not only the overall treatment effect but also how treatments influence the relationships among variables. Differential Correlation Mining (DCM) is an existing method for identifying groups of variables whose average pairwise correlation differs significantly between exactly two sampling conditions. We extend this framework to the setting of three or more treatments, where the goal is to identify variable sets whose pairwise correlation structure varies across all conditions simultaneously. Our proposed method, VSAT for three or more treatments, generalizes the DCM search procedure using a multi-treatment hypothesis test …

Discrete S-Band Low-Noise Amplifier Designs For High Data-Rate Cubesat Uplink, Alejandro Martin Cosper, Alejandro Cosper

Master's Theses

In the world of small satellites, there is growing interest in higher-data-rate systems and the technologies that enable them. Due to limitations in the extremely reliable and proven Ultra-High Frequency (UHF) systems, the current CubeSats developed by the Cal Poly CubeSat Laboratory operate at 9600 Baud. However, the low Baud rate is rooted in decades of proven flights and is very resistant to many forms of signal degradation. While a slow but simple system was critical to past successes, future satellite payloads may require higher data rates to drastically reduce the number of passes needed to transfer large amounts 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 …

How Human Vs. Ai Chatbots Support Psychological Needs Of Students, Tymon T. Vu

Master's Theses

AI auto graders and virtual assistants are increasingly prevalent in educational set- tings. Although current literature demonstrates that AI chatbots can positively im- pact student motivation, there is little definitive evidence exploring whether these systems can replicate the effective motivational methods used by human teachers. Thus, in this experiment, we investigate how the perception of the identity of a tutor (AI versus human) impacts the psychological needs of students. 27 undergraduates taking introductory computer science courses were asked to explain code in plain English (EiPE). Participants received feedback from two tutors in within-subjects fashion: one human and one labeled as …

The Effects Of Maceration And Enzymes On The Chemical Characteristics Of Hard Apple Cider, Manou De Pelsmaeker

Master's Theses

The purpose of this study was to analyze the effects of maceration and pectinase enzymes on the base chemical, polyphenolic, and volatile characteristics of cider. The apples (Fuji) were milled and macerated for 0, 4, 12, 24, or 36 hours, both with and without an enzymatic pectinase addition. While base chemical characteristics such as sugar content and ABV were unaffected, the acidity of cider was influenced maceration and enzymes. Extended maceration time resulted in lower concentrations of malic acid, and enzymes resulted in a lower pH compared to the control. Polyphenols were extracted during maceration time, resulting in higher concentrations …

Investigating The Structural Barriers And Opportunities For End-Of-Life Management Of Agricultural Plastic Waste Within California's Strawberry Industry, Rory M. O'Toole

Master's Theses

Agricultural plastic waste (APW) accounts for a significant and growing share of global plastic pollution, yet no study has documented how APW management functions across a specific crop system from production through end-of-life (EOL). This thesis addresses that gap by examining the structures and valuations that shape current EOL management of plastic mulch (PM) and drip tape (DT) in California's strawberry industry, one of the nation's most plastic-dependent crop systems. Drawing on an ethnographic approach that included 27 semi-structured interviews with stakeholders, as well as site visits, this study traces how APW is produced, valued, and discarded within a structurally …