Digital Commons Network^™

Hardware Control Unit For Trusted Program Verification System, Jake Owen Alt

Master's Theses

Trust in the underlying hardware is the foundational step towards trusting the correctness and integrity of a software application. However, verifying that today's extremely complex processors work exactly as intended has not been feasible, as evidenced by several recent hardware bugs. Trustworthy, formally verified processors currently forego intricate performance enhancements such as out-of-order execution, hampering them substantially versus their less secure counterparts.

The Containment Architecture with Verified Output (CAVO) system solves this problem by isolating the host system and requiring the result of each instruction to be validated by a small, trusted hardware module called the Sentry. Any transmissions to …

Solubility Characterization Of Organic Molecules For Aqueous Organic Redox Flow Batteries, Anthony W. Ferrell, Harkeerith K. Vij, Seamus D. Jones

College of Engineering Summer Undergraduate Research Program

The major obstacle to renewable energy sources is a lack of long-term energy storage capabilities. Energy produced during the day dissipates, leaving insufficient electricity for at night. The goal of the project is to design an Aqueous Organic Redox Flow Battery (AORFB) to act as long-term energy storage. Work has been done using machine learning to identify suitable compounds for the batteries. In this work there was no indication as to the aqueous solubility of the molecules; this controls the device’s energy storage capabilities. We used a machine learning model to determine the aqueous solubility of slightly more than 3000 …

Targeting Federated Learning: A Study Of Membership Inference Attacks On Healthcare Data, Brett W. Hillyard, Aditi S. Lappathi

College of Engineering Summer Undergraduate Research Program

This study investigates the vulnerabilities of federated learning models in the healthcare domain, specifically focusing on membership inference attacks (MIA). Federated learning allows local models to train on sensitive healthcare data without sharing the data itself, making it an attractive method for protecting privacy. However, even in this decentralized framework, models remain vulnerable to MIAs, where attackers can infer whether certain data points were used to train a model by analyzing model updates. Using the Texas100 dataset, this study demonstrates that as the number of local models increases, the attack accuracy of MIAs also increases due to higher bias …

Fast And High-Resolution View Synthesis From A Single Input Panorama, Nam Nguyen, Angela V. Chen, Theresa Zhu, Seth Johnson, Pranav Dumpa, Benjamin Geil

College of Engineering Summer Undergraduate Research Program

We introduce a novel method to convert a single input panorama into a 3D colored mesh representation of the scene. Unlike recent methods based on neural rendering, which are limited to low-resolution inputs and offline rendering, our approach supports 4k resolution inputs and real time rendering in a virtual reality headset. We first estimate a depth map and produce an initial layered depth image (LDI) representation. We fill unseen regions behind objects by iteratively cutting and inpainting the LDI. We then convert the LDI into an optimized, texture mapped mesh to achieve a compact representation

"Deep Learning For Microscope Image Denoising", Nasreen Buhn, Sriya Adunur, Guy Hagen, Jonathan Ventura

College of Engineering Summer Undergraduate Research Program

In order to avoid damaging live cells, optical microscope imaging must be conducted under low-excitation light intensity and/or short exposure times, resulting in low signal-to-noise ratios (SNR). Deep learning methods offer an effective solution for removing microscope noise, utilizing algorithms that are able to reconstruct finer features in low SNR images. This research explores the denoising capability of several deep learning methods based on PSNR and SSIM. Tested methods include traditional approaches (BMED), supervised learning (CARE and Restormer), and unsupervised methods (Noise2Fast, N2V, SSD-Unsupervised, and SASSID). The Restormer model, which employs an encoder-decoder transformer architecture and progressive learning, stood out …

Promoting Retention And Success Of Underrepresented Minorities In Engineering, Sebastian Macias-Gonzalez

College of Engineering Summer Undergraduate Research Program

Equity gaps in higher education have long been a pressing concern, with factors like race, ethnicity, and socioeconomic status influencing college attendance, retention, and success rates. While CSU-wide initiatives have been implemented to reduce these disparities, Cal Poly's distinctive role as the only campus transitioning into a Hispanic-serving institution calls for heightened efforts on our campus. Additionally, the persistence of equity gaps in STEM fields, combined with Cal Poly’s strong engineering program, makes it essential to focus on retaining and supporting underrepresented minorities (URM) in engineering disciplines.

Gamified Machine Embroidery, Sai Rama Balakrishnan, Vince Thanh Doan

College of Engineering Summer Undergraduate Research Program

This project aims to improve accessibility to the embroidery field by developing an application that captures the utility of a embroidery software (controlling an embroidery machine to produce embroidered output) and combines it with the playfulness of a game, to put those advanced controls in the hands of novices.

Agentic Ai In Search & Rescue, Belal Elshenety

College of Engineering Summer Undergraduate Research Program

No abstract provided.

Wearable Sensor-Based Gait And Balance In Elementary And Middle Schools, Sofie Zalatimo, Catherine Semaan

College of Engineering Summer Undergraduate Research Program

No abstract provided.

Digital Twin For Shelf Intelligence: Ai-Driven Inventory Management For Minimizing Food Waste, Charlotte Maples, Marvin Velazquez

College of Engineering Summer Undergraduate Research Program

This project aims to develop a solution for improving grocery store inventory management by leveraging AI-driven image recognition. Traditional inventory methods, which rely on manual counting or barcode scanning, are inefficient, labor-intensive, and prone to human error. Over an 8-week period, we designed and developed a basic iPad app capable of identifying specific types of fruit and automatically updating inventory records in real time. By utilizing the iPad’s camera and machine learning algorithms, the app demonstrates the potential to streamline inventory tracking, reduce manual labor, and improve accuracy in managing perishable goods. Future work will focus on expanding the app’s …

Optimizing Medical School Enrollment, Justin Koida, Nicholas Quattrocchi

College of Engineering Summer Undergraduate Research Program

The increasing physician shortage, coupled with an aging population, presents significant challenges for healthcare systems. With higher education facing a projected enrollment cliff, and a decline in youth math and reading scores, identifying the most qualified medical school applicants is imperative. With thousands of applications received annually for only 300 spots at Western University of Health Sciences (WesternU), it is crucial to streamline the selection process while minimizing applicant attrition and melt.

In our research project, we develop a predictive model to identify candidates for interviews based on success data from students at WesternU. We utilized a dataset provided by …

Computational Modeling Of High Yttrium Refractory High Entropy Alloy Microstructures, Kaleb C. Ryan, Marissa M. Baker

College of Engineering Summer Undergraduate Research Program

Refractory high entropy alloys (RHEAs) are advanced metals made up of five or more principal elements in roughly equal amounts. The microstructural effects of alloying with yttrium as a principal element for RHEAs are currently not well understood. This project compared RHEA microstructures from literature with simulations using the High Entropy Alloy Predicting Software (HEAPS), which computes 10 screening criteria to predict the microstructure of a RHEA composition. The accuracy of HEAPS predictions was assessed by comparing them with experimentally validated microstructures found in literature. A combination of criteria was found to have a 95.8% accuracy rate, and a new …

Attitude Control Of A Flexible Flapping Wing Uav Based On Fuzzy Logic, Reed M. Paulson, Tyson Chen, Diego Del Real, Nico Morrison

College of Engineering Summer Undergraduate Research Program

This project revolves around creating an a attitude controller for a hovering flexible flapping wing UAV that is based on a flying hummingbird. We based our model from a paper by Banazadeh and Taymourtash1 , First replicating the open-loop results using the nonlinear dynamic model and the equations of motion (seen below) while considering aerodynamic loads. Once replicated, we then used fuzzy logic to model the dynamic model. Subsequently, we designed a fuzzy controller to stabilize the hovering mode. We then considered and detailed future work needed to make further progress in this area.

Seismic Resilience Of Timber Homes, Melia R. Costa

College of Engineering Summer Undergraduate Research Program

The vast majority of residential buildings in California are wood-frame structures. A home is typically a very large investment for families, and damage to the home can be detrimental to a family’s economic success. Thus, reducing the economic impacts of an earthquake on residential timber housing is crucial. A full scale, two-story section of a residential timber house is in construction in the Parson’s Geotechnical and Earthquake Engineering Laboratory on the Cal Poly campus in San Luis Obispo, California. Once built it will be put through earthquake simulation tests on a shake table with various magnitudes of seismic activity. Next, …

Leveraging Tradespace-Exploration For A Senior Project Team Formation Application, Miguel Saenz

College of Engineering Summer Undergraduate Research Program

This project revolves around the development of an app in MATLAB that leverages the VASSAR rule-based system and a genetic algorithm to form groups of teams for the Mechanical Engineering Senior Design project class. We leveraged the iterative design process to eventually attain a functional app with a reasonable runtime that works provided correctly formatted rulesheets describing student project preference and member preference.

Implications Of Persistent Micro-Bioplastics On Biogeochemical Properties Across Soil Types, Casandra R. Leach

Master's Theses

Terrestrial microplastics are increasing in abundance and are an emerging contaminant of concern, particularly in agriculture ecosystems where plastic use and subsequent soil contamination are prevalent. Plastic film mulches make up a significant portion of the plasticulture industry and are directly linked to soil microplastic pollution where negative effects to soil biotic and abiotic functions have been observed. In response to this issue, biodegradable film mulches have been promoted as a sustainable alternative to conventional polyethylene-based mulches. These biodegradable mulches, composed of various bioplastics, are designed to be tilled back into the soil where they are expected to decompose. However, …

Concrete Design: Underwater Concrete Forms In A Saltwater Environment, Noah Z. Lau

Construction Management

This following project investigated the effects of salt on the concrete curing process. Concrete possesses numerous strengths, making it extremely versatile. This makes it one of the most utilized construction materials. New improved methods are constantly being developed for concrete’s application as a construction material. While concrete is a flexible material with many strengths, it is not without its flaws. Concrete, while strong in compression is weak in tension. It has long cure times and doesn’t generally handle moisture well. This paper evaluates concrete’s change in strength from letting concrete cure in a salt-based underwater environment. To determine the full …

Community-Based Disability Accessibility Assessment, Elspeth Slayter, Rose C. B. Singh

Feminist Pedagogy

No abstract provided.

Media Review: Disability, Not Invisibility: My Experience With Chronic Illness (2019), Amanda Watson Joyce

Feminist Pedagogy

No abstract provided.

A Review Of Neurodivergent, Madison Marshall

Feminist Pedagogy

No abstract provided.

Review Of The Heumann Perspective Podcast, Jennifer Woody Collins

Feminist Pedagogy

This media review of the Heumann Perspective podcast encourages educators to use it as a way to discuss and teach disability justice and activism.

Creating Classroom Integrity By Eliminating Punitive Course Policies, Rachel E. Silverman

Feminist Pedagogy

No abstract provided.

Practicing Feminist Disability Pedagogy: Building Interdependence Through A Classroom Participation Menu, Kristen L. Cole

Feminist Pedagogy

Following the lead of Parsloe & Smith (2022), this article explains and advocates possible modes of participation that consider the disabled, chronically ill, and systemically vulnerable students and faculty who are fighting to succeed in higher education. The way participation is measured in college classes is often ableist in nature; thus, it is important to unpack the ableist assumptions that undergird how we arrange and assess participation. Utilizing Knoll’s (2009) explication of interdependency as a practice of feminist disability pedagogy, this article offers a semester long activity called a participation menu, which provides a framework for distributing the responsibility of …

Making (Virtual) Space For Disability Equity In Academia, Melissa Vosen Callens, Cali Anicha, Larry Napoleon Jr.

Feminist Pedagogy

Virtual or hybrid options provide a way for marginalized faculty and staff to fully participate in their fields and on their campuses. As such, an equitable and pandemic-informed academic workplace should include fully accessible and well-resourced hybrid participation options for department meetings and events, office work, and classroom duties. In spring 2023, we created a work group on our campus to address the challenges of hybrid work and co-create campus-wide recommendations for hybrid workspaces. In this article, we share our findings and evidence-based recommendations, many of which draw on Universal Design for Learning, as well as offer suggestions on how …

Teaching Disability (Self-)Advocacy As We “Return To Normal”: Addressing Ableism In Higher Education, Sarah M. Parsloe

Feminist Pedagogy

No abstract provided.

Executive Committee - Agenda, 9/24/2024, Academic Senate

Academic Senate Agendas

No abstract provided.

Finite Element Analysis Of The Bearing Component Of Total Ankle Replacement Implants During The Stance Phase Of The Gait Cycle, S J. Hazelwood, Mohammad N. Noori, Naudereh B. Noori, Timothy S. Jain, Amanda Anderson, Joseph Rencis

Biomedical Engineering

Total ankle arthroplasty (TAA) is a motion-preserving treatment for end-stage ankle arthritis. An effective tool for analyzing these implants’ mechanical performance and longevity in silico is finite element analysis (FEA). An FEA in ABAQUS was used to statically analyze the mechanical behavior of the ultra-high-molecular-weight polyethylene (UHMWPE) bearing component at varying dorsiflexion/plantarflexion ankle angles and axial loading conditions during the stance phase of the gait cycle for a single cycle. The von Mises stress and contact pressure were examined on the articulating surface of the bearing component in two newly installed fixed-bearing TAA implants (Wright Medical INBONE II and Exactech …

Enabling Emg-Based Silent Speech Transcription Through Speech-To-Text Transfer Learning, Alexander T. Garcia

Master's Theses

In recent years, advances in deep learning have allowed various forms of electrographic signals, such as electroencephalography (EEG) and electromyography (EMG), to be used as a viable form of input in artificial intelligence applications, particularly for applications in the medical field. One such topic that EMG inputs have been used is in silent speech interfaces, or devices capable of processing speech without an audio-based input. The goal of this thesis is to explore a novel method of training a machine learning model to be used for silent speech interface development: using transfer learning to leverage a pre-trained speech recognition model …

Investigation Of Temperature, Solution Strength, And Applied Stress Effects On Cation Exchange Processes In Different Geosynthetic Clay Liner Products, Kendra Fuller

Master's Theses

An extensive laboratory test program was conducted to analyze and compare the cation exchange processes in three different varieties of sodium bentonite (Na-B) geosynthetic clay liners (GCLs) over increased conditioning durations up to 32 days and investigate the effects of temperature, solution strength, and applied stress. The goal of this test program was to establish whether the variables of temperature, solution strength, and applied stress improved or degraded the engineering properties of GCLs in laboratory testing and municipal solid waste (MSW) landfill applications. The GCLs were conditioned in liquids of increasing ionic strength, using deionized water and 2, 50, and …

History & Evolution Of Plastic Mulching Technology: An Ethnography Of California Strawberry Plasticulture, Kalea Conrad

Master's Theses

This ethnography draws on key informant interviews and participant observation to produce a case study about plastic mulching as an important industry standard in specialty crop production. It documents the historic adoption and present role of plastic mulching technology in California strawberry production and addresses the characteristics of commercial standard management that inhibit the adoption of alternative mulching practices. It complements extensive research on strawberry pathology and fumigation, breeding innovations, fertilizer and pesticide treatments, and maximization of yields to incorporate participants’ lived experiences and knowledge of mulch origins, the technology adoption process, mulch benefits and drawbacks, the state of agricultural …