Physical Sciences and Mathematics Commons^™

Investigation Of Social Networks Upon Academic Performance And Mental Health, Rachel Izenson

Master's Theses

It has been shown that computing students have a statistically significantly lower overall sense of belongingness compared to other science students. A sense of community is important for many reasons. For example, there are studies that show that a student's sense of belonging correlates with improved academic performance. Our research aims to analyze the sense of belonging among computing students at Cal Poly San Luis Obispo through a network science lens. We surveyed for their sense of belonging, as well as their social network, to understand how friendships impact one's sense of belonging. When student responses were split by gender, …

Real-Time Network Simulations For Ml/Dl Ddos Detection Using Docker, Luis D. Garcia

Master's Theses

As the integration of artificial intelligence (AI) within cybersecurity continues to

grow, machine learning (ML) and deep learning (DL) models are increasingly used to

detect cyber attacks. However, these models are rarely evaluated in real-time attack

scenarios to see how subtle changes from the real networking environment can affect

their predictions. To address this issue, we propose a scalable, platform-independent

Docker testbed specifically designed for simulating real-time Distributed Denial of

Service (DDoS) attack scenarios that allows researchers to deploy and evaluate their

pre-trained, ML and DL detection models. Our framework is simple to configure

and can run across Intel and …

An Investigation Into The Use Of Amateur Astronomy Equipment For Optical Orbit Determination Using A Mobile Telescope Platform, Johan C. Govaars

Master's Theses

The process of optical orbit determination has long been in the domain of large organizations and stationary observatories with highly specialized scientific equipment. This thesis seeks to determine not only if satellites can be captured regularly using purely commercial-off-the-shelf (COTS) equipment, but also if initial orbit determinations can be made using that data. Moreover, the use of a mobile telescope platform allows users to circumvent the restrictions of fixed observatories such as low horizon viewing restrictions or existing light pollution.

A completely COTS setup was utilized that included an 8-inch Celestron NextStar 8SE telescope with an f/6.3 focal reducer and …

Policies And Price Controls On The Research And Development Of Orphan Drugs In The United States And The European Union, Bena Pearl Filipczak Smith

Master's Theses

There is substantive literature surrounding the impact of price controls on the research and development (R&D) of new pharmaceutical products. The European Union (EU) and United States (US) are often studied in contrast to examine the influence of price controls as the US has fewer pharmaceutical price controls than the EU.

We find moderate evidence that the US spent more on annual domestic pharmaceutical R&D than the EU between 2004 and 2021, on average, before and after adjusting for GDP growth per capita and year. We find strong evidence that the US increased annual domestic R&D spending at a faster …

Jwst Lensed Quasar Dark Matter Survey – Ii. Strongest Gravitational Lensing Limit On The Dark Matter Free Streaming Length To Date, Ryan E. Keeley, A. M. Nierenberg, D. Gilman, C. Gannon, S. Birrer, T. Treu, A. J. Benson, X. Du, K. N. Abazajian, Vardha N. Bennert

Physics

This is the second in a series of papers in which we use JWST Mid Infrared Instrument multiband imaging to measure the warm dust emission in a sample of 31 multiply imaged quasars, to be used as a probe of the particle nature of dark matter. We present measurements of the relative magnifications of the strongly lensed warm dust emission in a sample of nine systems. The warm dust region is compact and sensitive to perturbations by populations of haloes down to masses ~ 10⁶ M☉. Using these warm dust flux-ratio measurements in combination with five previous narrow-line flux-ratio measurements, …

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 …

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.

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 …

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

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 …

Quantifying Ethics And Trust In Human-Ai Collaboration, Oliver Lane, Kevin Klave

College of Engineering Summer Undergraduate Research Program

As AI Chatbots continue to evolve in both prevalence and capability, their role in education is becoming increasingly prominent. With chatbots like ChatGPT becoming commonplace in higher education, there is an evident need to understand the ethics and trust dynamics of human-AI collaboration. This research contributes to the ongoing discussion on AI in education, highlighting the importance of trust when utilizing AI in academic settings. By conducting an empirical analysis, this research seeks to quantify trust in human-AI collaboration in higher education with the aim of offering actionable items for higher education institutions to follow to promote ethical and responsible …

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 …

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 …

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 …

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, …

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 …

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, …

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 …

Analyzing Hubble Space Telescope Images Of Agn Host Galaxies With Keck Integral Field Spectra, Sebastian Contreras

Physics

In the center of most massive galaxies is a supermassive black hole (SMBH) with a mass that can range from millions to billions of solar masses. It has been observed that more massive SMBHs have a more massive host galaxy bulge, as evidenced by the larger bulge luminosity and stellar velocity dispersion, a correlation known as the BH mass - host-galaxy scaling relation. It suggests a close evolutionary connection between the growth of the SMBH and the growth of its host galaxy. If a SMBH develops an accretion disk to fuel an active galactic nucleus (AGN), it will emit radiation …

High Resolution Assessment Of Commercial Fisheries Activity Along The Us West Coast Using Vessel Monitoring System Data With A Case Study Using California Groundfish Fisheries, Yi-Hui Wang, Benjamin Ruttenberg, Ryan K. Walter, Frank Pendleton, Jameal F. Samhouri, Owen R. Liu, Crow White

Physics

Commercial fisheries along the US West Coast are important components of local and regional economies. They use various fishing gear, target a high diversity of species, and are highly spatially heterogeneous, making it challenging to generate a synoptic picture of fisheries activity in the region. Still, understanding the spatial and temporal dynamics of US West Coast fisheries is critical to meet the US legal mandate to manage fisheries sustainably and to better coordinate activities among a growing number of users of ocean space, including offshore renewable energy, aquaculture, shipping, and interactions with habitats and key non-fishery species such as seabirds …

A Screening Life Cycle Analysis Of One-Way And Reusable Crate Designs – Estimating Environmental Impacts Via Lca Software, Nicolas R. Corona

Master's Theses

A comparison analysis conducted via COMPASS life cycle analysis software has indicated that a one-way crate design, rather than a reusable crate design, is in fact the more environmentally friendly packaging system. These results can be interpreted differently, however, as the manufacturer of said crate designs must confirm what impact indicators they would like to reference as environmental goalposts. The conducted analysis provides insight into what the environmental impacts of each packaging system look like as packaging at all three system levels has been identified as a means of reducing environmental impacts globally. As such, the manufacturer of said crate …