Digital Commons Network^™

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

Enhancing Semantic Search With Human-Crafted Knowledge In Sentence Embeddings, Zachary Weinfeld

College of Engineering Summer Undergraduate Research Program

Semantic search plays a critical role in many domains, with numerous algorithms developed to address it. A common approach involves using sentence transformers to generate embeddings for both search queries and documents, allowing for the comparison of their vectors. While many different embedding models are widely used, our approach integrates these models with human-crafted knowledge in a novel way, resulting in an improvement in the Mean Average Precision (MAP) scores. Traditional embeddings often rely heavily on the specific words used in a query or document. Our technique mitigates this dependency by refining the vectors to capture the overall semantic meaning, …

Optimizing Sensor Placements For Fixed Source Localization: A Distinct Subset Distance Sum Problem, Peter Chinh

College of Engineering Summer Undergraduate Research Program

This research addresses the problem of optimizing sensor placements for fixed source localization using distinct subset distance sums. Given a line L in R² and a set P of n points on one side of L, we seek to locate a minimal set S of points on L such that for any two distinct subsets Q and R of P, there exists a point s∈S where the sum of reciprocal distances from Q to s uniquely identifies Q. Our results show that a minimal sensor set S of size 1 is always feasible, but computing this set exactly proves …

"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 …

Empirical Support For Algorithmic Conjectures, Shayan Daijavad

College of Engineering Summer Undergraduate Research Program

Our project focuses on a particular Markov Chain Monte Carlo algorithm, with applications in statistical physics, known as hardcore model Glauber dynamics. The target distribution of Glauber dynamics is a distribution of all of the independent sets within a graph. An independent set is a set of vertices within a graph with no two vertices in the set containing an edge between them. Our goal is to find whether or not the Glauber dynamics for sampling independent sets on trees mixes in time O(nlogn), and determining how the mixing time changes if we bias the algorithm in favor of larger …

Measurement Automation & Measurement System Research Endowment, Brian Bivinetto, Beneda Loya, Shiron Bendrihem

College of Engineering Summer Undergraduate Research Program

Road travel safety is always the most important issue in transportation systems. In general, several factors cause road accidents, such as human error, vehicle mechanical failure, roadway limitations (e.g. pavement, lane geometry, etc.), and inclement weather conditions. The major focus of today’s transportation developments is related to making highway transportation safer, smarter, and greener to enhance livability. Many accidents are caused when drivers lack a better understanding of the surrounding traffic conditions because the driver not only needs to control his/her vehicle but also needs to be aware of the movements of the vehicles around him/her. A driver cannot be …

Understanding And Enhancing Sustainability Literacy In Cal Poly's College Of Engineering, Kenna Toohill

College of Engineering Summer Undergraduate Research Program

This study uses survey data collected from Cal Poly students to analyze engineering students' sustainability knowledge and their perspectives on Cal Poly's efficacy in teaching concepts in sustainability. It also compares the College of Engineering to other colleges to determine if, and how, CENG is behind in environmental education at Cal Poly.

Significance Of Noninvasive Endothelial Dysfunction And Other Cardiovascular Measurements In Various Communities, Sofi Z. David, Lily Wilcox, Kalia Richard

College of Engineering Summer Undergraduate Research Program

This pilot study aims to raise awareness of endothelial dysfunction in underrepresented communities, where cardiovascular disease is prevalent. By delivering educational presentations and materials, the study seeks to increase participants' understanding and interest in endothelial dysfunction, potentially leading to proactive health behaviors. The results will inform future initiatives to enhance public knowledge and reduce the burden of cardiovascular disease in these communities.

In the future, there will also be a 3 vs 5-minute hyperemia study. Thirty participants without a history of cardiovascular disease will undergo testing using the Cordex SmartCuff™ device. If the three-minute hold proves to accurately measure endothelial …

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 …

Deep-Learning Based Microstructure Reconstruction And Generation, Cameron J. Maloney, Lucas Taliaferro

College of Engineering Summer Undergraduate Research Program

Characterizing the microstructural behavior of materials is crucial for understanding their properties and performance. Traditional imaging methods, such as optical microscopy and electron microscopy, are effective but costly and time-consuming. Computational approaches can reduce costs and time while expanding the accessibility of microstructural analysis through the generation of new microstructure images. Traditional computational approaches, namely descriptor-based approaches, are slow but effective in low-data scenarios. Modern approaches use machine learning (ML), which is faster but often requires a lot of data to approach the performance of descriptor-based methods. This research leverages a special data-efficient Generative Adversarial Network (GAN) architecture to artificially …

Surrogate Models For Stress-Strain Mapping Of Microscale Physics, Samuel Roach, Dr. Eric Ocegueda

College of Engineering Summer Undergraduate Research Program

•Learn the difference between different neural networks within machine learning (ML) •Develop a working understanding of the ML tool Pytorch and machine learning operator: Recurrent Neural Operator •Use MATLAB to create and process time dependent stress/strain matrices to display the hyper-parameters for different RNOs •Apply RNO to train the strain-stress mapping of tri-laminate and granular cases

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.

Enhancing Place-Based Interaction With Emotion Ai And Augmented Reality, Jake Maier, Ivan Martinez

College of Engineering Summer Undergraduate Research Program

This project explores the integration of augmented reality (AR) and Emotion AI technologies to enhance user experiences in physical environments. By seamlessly merging virtual elements with real-world contexts, we aim to deepen individuals’ interactions and perceptions of their surroundings. Leveraging AR technology enables users to access contextual information, engage with interactive content, and navigate spaces with heightened immersion and understanding. Additionally, Emotion AI enhances these experiences by detecting and responding to users’ emotional states, fostering personalized and emotionally resonant interactions. We aim to integrate digital content within physical environments using mixed-reality headsets equipped with eye-tracking capabilities and consumer-grade wireless EEG …

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.

Supporting Neurodivergent Students, William W. Toll

College of Engineering Summer Undergraduate Research Program

Prior work—a 2019 study by Schreffler, Vasquez, Chini, et al.—investigated the efficacy of Universal Design for Learning (UDL) in supporting students with disabilities (SWD) in science, technology, engineering, and mathematics education (STEM). SWD are somewhat more likely than the general population to enroll in STEM majors, but for some disabilities, students are less likely to graduate with those majors. Nonetheless, the authors found a paucity of prior work involving the use of UDL for SWD in STEM. In addition to highlighting the need for future quantitative research overall, the authors noted that it would be interesting to investigate which UDL …

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, …

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 …

Dynamic Maze Puzzle Navigation Using Deep Reinforcement Learning, Luisa Shu Yi Chiu

Master's Theses

The implementation of deep reinforcement learning in mobile robotics offers a great solution for the development of autonomous mobile robots to efficiently complete tasks and transport objects. Reinforcement learning continues to show impressive potential in robotics applications through self-learning and biological plausibility. Despite its advancements, challenges remain in applying these machine learning techniques in dynamic environments. This thesis explores the performance of Deep Q-Networks (DQN), using images as an input, for mobile robot navigation in dynamic maze puzzles and aims to contribute to advancements in deep reinforcement learning applications for simulated and real-life robotic systems. This project is a step …

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 …

Dual Base Sige Is-Hbt For Use In Biosensing Applications, Liam Stephen Hayes

Master's Theses

The proposed research is for a novel SiGe-based Ion-Sensitive Dual Hetero-junction Bipolar Transistor (IS-HBT) to be used in both trans-dermal biological sensing as well as Lab-on-Chip (LOC) applications. The end goals for the device designed are two: For one, the research done for this work will be used to substantiate the claims made by Zafar et al. [1] that an HBT-style structure is better suited for biosensing application rather than a conventional Field Effect Transistor (FET) based geometries. Secondly, it provides the final element to be integrated along with a selectivity membrane, as well as with a reverse-iontophoresis system to …

Of Geese And Grass: Investigating Impacts Of Brant Grazing On Eeelgrass, Dakota L. Osborne

Master's Theses

Grazing pressure is important in structuring plant communities, particularly in aquatic environments. Eelgrass (Zostera marina), a keystone species in estuaries across North America, is experiencing widespread population declines. As a keystone species, eelgrass provides numerous important functions, including: 1) water filtration, 2) sediment stabilization, 3) providing refuge and nursery habitat for numerous species, and 4) carbon sequestration. Benefits which could be lost if eelgrass beds continue to diminish. California has experienced some of the greatest eelgrass declines, and Morro Bay, CA experienced a 96% decrease in eelgrass from 2007 to 2017. Most studies to date have examined bottom-up …

Representation Theory Arising From Groups In Physics, Jaxon Green

Master's Theses

A representation is a group homomorphism whose image is a group of invertible matrices. Representations and their associated matrices are analyzed through well-established techniques from linear algebra. We characterize representations by a unique decomposition into irreducible representations just as we characterize the decomposition of matrices into their eigenspaces. Through the study of these representations, we uncover mathematical relationships that underlie groups with physical applications. Due to physical symmetries, we study how the irreducible representations of groups that embody the actions of even the most basic rotations are utilized in the computation of irreducible representations groups that reflect more complicated mechanics, …

Assessment Of Dune Change Using Historical Aerial And Satellite Photos, Topographic Surveys, And Wave Data At Toro Creek Beach, Owen D. Emerson

Master's Theses

Coastal sand dunes play an important role in the littoral processes of California’s coastline. Functioning as both source and sink for sand, these dunes often protect coastal infrastructure and provide a buffer between anthropogenic development and coastal forces. At Toro Creek Beach, north of Morro Bay California, recent extreme winter storms have raised concerns about the erosion of the sand dunes that front California State Highway 1. This thesis attempts to characterize the historical growth and recession patterns of the Toro Creek dunes since 1977, the dune movement over the 2023-2024 winter seasons, the wave forcings behind recent high erosion …

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 …

Spatial Planning Offshore Wind Energy Farms In California For Mediating Fisheries And Wildlife Conservation Impacts, Crow White, Yi-Hui Wang, Ryan K. Walter, Benjamin Ruttenberg, Danny Han, Eli Newman, Ethan R. Deyle, Sucharita Gopal, Les Kaufman

Physics

Achieving a blue economy will require reconciling the value of emerging ocean uses with their impacts on the seascape and sectors with historical access to marine resources and areas. To meet this challenge, we developed an analytical framework for conducting marine spatial planning through tradeoff analysis, and applied it to prospective offshore wind energy development in the ∼974 km2 Morro Bay, California, USA Wind Energy Area (WEA). We generated spatial data layers estimating MW power production and impacts on fisheries value and marine wildlife conservation (seabird and cetacean populations) from wind farm development. We then quantified each sector's response to …

Gps Accuracy Of Smartphones For Crowdsourcing Research, Derron L. Dike

Master of Science in Environmental Sciences and Management Projects

ABSTRACT GPS Accuracy of Smartphones for Crowdsourcing Research Derron Dike Utilizing crowdsourcing with smartphones as a method for field data collection can contribute an array of data for scientific studies and land management applications. This study used crowdsourcing to examine smartphone built-in GPS performance for providing location-specific information with potential forestry applications. The usability of smartphones for GPS data collection in forestry studies or other practical applications is dependent on the level of accuracy required for those applications. A Smartphone Accuracy Trial was designed to test the GPS accuracy performance of current smartphones. Participants used the ArcGIS Field Maps application …

Power Controller For Insulated Solar Electric Cooker, Ryan Koshy, Justin Tae-Hoon Kim

Electrical Engineering

Insulated Solar Electric Cookers, or ISECookers, are devices created to aid those in impoverished regions improve safety, sustainability, and quality of life regarding their cooking practices. ISECookers present an alternative to traditional biofuel/biomass energy sources and provide a closed-loop, self-sustaining system that can be used in a variety of environments. These devices present solutions to widespread issues such as pollution, deforestation, and hazardous emissions as a result of traditional cooking in developing regions around the world. A notable obstacle of these devices is power delivery. Given the varying conditions experienced by a solar panel (inclement weather, irradiance irregularities, etc.), it …