Physical Sciences and Mathematics Commons^™

Representations From Group Actions On Words And Matrices, Joel T. Anderson

Master's Theses

We provide a combinatorial interpretation of the frequency of any irreducible representation of Sn in representations of Sn arising from group actions on words. Recognizing that representations arising from group actions naturally split across orbits yields combinatorial interpretations of the irreducible decompositions of representations from similar group actions. The generalization from group actions on words to group actions on matrices gives rise to representations that prove to be much less transparent. We share the progress made thus far on the open problem of determining the irreducible decomposition of certain representations of Sm × Sn arising from group actions on matrices.

Exploring The Mass To Light Ratio Of Massive Galaxies With The Rubin Dp0 Preview Dataset, Denvir Joy Higgins

Physics

The Vera C. Rubin Observatory will perform the 10-year long Legacy Survey of Space and Time expected to begin in 2024. LSST will cover the Southern Hemisphere, collecting over two million images with an 8.4-meter telescope and 3200-pixel camera. In collaboration with the scientific community and based on the Outer Rim Simulation \citep{heit19}, the Rubin Observatory released a simulated dataset (DP0) of the data that is expected to be in hand at the 5-year mark. Using this simulated dataset, I have explored the number and luminosity of the most massive local galaxies. Using a sample of the brightest, closest galaxies …

A Monte-Carlo Simulation Of Gamma Rays In A Sodium Iodide Detector, Ben Kessler

Physics

Gamma rays principally interact with matter through Compton scattering, photoelectric effect, pair production, and triplet production. The focus of this simulation is to study the theoretical energy spectrum created by gamma rays from a Cesium-137 source, which produces gamma photons with an energy of 0.662 MeV. At this energy level, most interactions are results of Compton scatters and the photoelectric effect. Therefore, this simulation only models those two effects on gamma rays. Using Monte Carlo methods and the Metropolis algorithm to sample the probability distributions of the two effects allowed for the simulation of gamma rays in a Sodium Iodide …

Diffusion-Driven Aggregation Of Particles In Quasi-2d Membranes, Oscar Gullickson Rausis

Physics

Many biological membranes can be modeled as two-dimensional (2D) viscous fluid sheets surrounded by three-dimensional (3D) fluids of different viscosity. Such membranes are dubbed quasi-2D as they exhibit properties of both 2D and 3D fluids. The Saffman length is a parameter that describes the energy exchange between the membrane and bulk fluids and controls the cross-over from 2D to 3D hydrodynamics. We aim to model diffusion-driven aggregation of particles embedded in a quasi-2D membrane. It is known that hydrodynamic interactions between solute particles significantly reduce their aggregation rate in 3D fluids. It is expected that in quasi-2D membranes the reduction …

Optimization Of Flagellar Locomotion In The Low Reynolds Number Regime, Aidan M. Trodden, Aidan M. Trodden

Physics

This report investigates the computational and theoretical techniques - modeled by E. Lauga and C. Eloy - used to optimize the shape of an activated flagellum for enhanced cell motility. Cell motility is ubiquitous and has a large affect on biological systems such as marine life ecosystems, reproduction, and infection. The physical principles governing flagellar propulsion are explored using computational fluid dynamics simulations, mathematical modeling, and the sequential quadratic programming (SQP) optimization algorithm. Through iterative refinement, we can identify optimized flagellar shapes that would minimize the energetic cost dependent on a single dimensionless sperm numbers (Sp). The computation of the …

Groups Of Non Positive Curvature And The Word Problem, Zoe Nepsa

Master's Theses

Given a group $\Gamma$ with presentation $\relgroup{\scr{\scr{A}}}{\scr{R}}$, a natural question, known as the word problem, is how does one decide whether or not two words in the free group, $F(\scr{\scr{A}})$, represent the same element in $\Gamma$. In this thesis, we study certain aspects of geometric group theory, especially ideas published by Gromov in the late 1980's. We show there exists a quasi-isometry between the group equipped with the word metric, and the space it acts on. Then, we develop the notion of a CAT(0) space and study groups which act properly and cocompactly by isometries on these spaces, such groups …

An Empirical Evaluation Of Neural Process Meta-Learners For Financial Forecasting, Kevin G. Patel

Master's Theses

Challenges of financial forecasting, such as a dearth of independent samples and non- stationary underlying process, limit the relevance of conventional machine learning towards financial forecasting. Meta-learning approaches alleviate some of these is- sues by allowing the model to generalize across unrelated or loosely related tasks with few observations per task. The neural process family achieves this by con- ditioning forecasts based on a supplied context set at test time. Despite promise, meta-learning approaches remain underutilized in finance. To our knowledge, ours is the first application of neural processes to realized volatility (RV) forecasting and financial forecasting in general.

We …

Predicting Location And Training Effectiveness (Plate), Erik Rolf Bruenner

Master's Theses

Abstract Predicting Location and Training Effectiveness (PLATE)
Erik Bruenner

Physical activity and exercise have been shown to have an enormous impact on many areas of human health and can reduce the risk of many chronic diseases. In order to better understand how exercise may affect the body, current kinesiology studies are designed to track human movements over large intervals of time. Procedures used in these studies provide a way for researchers to quantify an individual’s activity level over time, along with tracking various types of activities that individuals may engage in. Movement data of research subjects is often collected through …

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A Novel Approach To Extending Music Using Latent Diffusion, Keon Roohparvar, Franz J. Kurfess

Master's Theses

Using deep learning to synthetically generate music is a research domain that has gained more attention from the public in the past few years. A subproblem of music generation is music extension, or the task of taking existing music and extending it. This work proposes the Continuer Pipeline, a novel technique that uses deep learning to take music and extend it in 5 second increments. It does this by treating the musical generation process as an image generation problem; we utilize latent diffusion models (LDMs) to generate spectrograms, which are image representations of music. The Continuer Pipeline is able to …

Distributed Control Of Servicing Satellite Fleet Using Horizon Simulation Framework, Scott Plantenga

Master's Theses

On-orbit satellite servicing is critical to maximizing space utilization and sustainability and is of growing interest for commercial, civil, and defense applications. Reliance on astronauts or anchored robotic arms for the servicing of next-generation large, complex space structures operating beyond Low Earth Orbit is impractical. Substantial literature has investigated the mission design and analysis of robotic servicing missions that utilize a single servicing satellite to approach and service a single target satellite. This motivates the present research to investigate a fleet of servicing satellites performing several operations for a large, central space structure.

This research leverages a distributed control approach, …

Deep Learning Recommendations For The Acl2 Interactive Theorem Prover, Robert K. Thompson, Robert K. Thompson

Master's Theses

Due to the difficulty of obtaining formal proofs, there is increasing interest in partially or completely automating proof search in interactive theorem provers. Despite being a theorem prover with an active community and plentiful corpus of 170,000+ theorems, no deep learning system currently exists to help automate theorem proving in ACL2. We have developed a machine learning system that generates recommendations to automatically complete proofs. We show that our system benefits from the copy mechanism introduced in the context of program repair. We make our system directly accessible from within ACL2 and use this interface to evaluate our system in …

Attainable And Sustainable Home Building Solutions, Katrina Matthews

Construction Management

Sustainability has fortunately been a recent concern in the construction industry as climate change continues to impose potentially insurmountable threats to the global environment. Although many new methods have been adopted in efforts to lessen the adverse environmental effects of construction-related activities, as a society, we still have much room for growth as the built environment accounts for almost 50% of global emissions. Many changes and standards must be adopted to make these solutions efficiently beneficial. To set industry standards, we must start with the most basic form of construction- residential building. This report covers two attainable framing solutions for …

Exploring The Potential Of Pavegen’S Kinetic Energy Generating Floor For Sustainable Energy Solutions: A Proposal For Cal Poly Slo, Brandon J. Cuneo

Construction Management

This paper proposes the installation of Pavegen's kinetic energy generating floors at Cal Poly’s campus as a sustainable energy solution. Pavegen has developed a pioneering technology that converts footsteps into clean and renewable energy. The versatility of these floors is demonstrated through successful implementations in various settings, such as transportation hubs and public spaces, generating power from foot traffic. Collaborations with Schneider Electric, installation at Dupont Circle, and integration at Heathrow Airport showcase the potential for sustainable urban infrastructure. This paper outlines research conducted on Pavegen and similar solutions, including communication with company representatives and examining proposed installation locations at …

Xylitol As A Phase Change Material: Exploring The Replacement Of Erythritol By Xylitol As A Phase Change Material, Elsa C. Micklin

Physics

To circumvent the cost and environmental damage associated with batteries, phase change materials have been employed in solar cookpots to enable cooking in unfavorable weather conditions. Researchers at Cal Poly have traditionally employed the sugar alcohol erythritol as a PCM due to its high latent heat and a fusion point above the boiling point of water, but have discovered issues with the polyol’s degradation over extended periods of cycling. This paper explores the viability of erythritol’s sister-compound xylitol as a PCM in insulated solar-electric cookers, or ISECs. An ISEC was constructed with a xylitol PCM, and the data collected from …

Ghostparty Video Game, Tyler Remlinger Hart

Computer Science and Software Engineering

GhostParty is a Unity game that uses a MongoDB database to store players' gameplay values. These values are used to create "Ghosts" that players can compete with in various mini-games. I found that this form of multiplayer using ghosts can create a good gameplay experience without live multiplayer interactions.

Solving Fjssp With A Genetic Algorithm, Michael John Srouji

Computer Science and Software Engineering

The Flexible Job Shop Scheduling Problem is an NP-Hard combinatorial problem. This paper aims to find a solution to this problem using genetic algorithms, and discuss the effectiveness of this. Initially, I did exploratory work on whether neural networks would be effective or not, and found a lot of trade offs between using neural networks and chromosome sequencing. In the end, I decided to use chromosome sequencing over neural networks, due to the scope of my problem being on a small scale rather than on a large scale.

Therefore, the genetic algorithm was implemented using chromosome sequencing. My chromosomes were …

Twitch Trivia Battle Royale: Interactive Entertainment Engineering Game, Noah Tyler Ravetch

Computer Science and Software Engineering

As the world of digital media evolves, so too does the way producers and consumers of entertainment content interact with each other. Live streaming is one such evolution. In this format, one person broadcasts their camera and/or their computer screen to a large audience of viewers in real time. People tuning in can communicate with other viewers and the streamer using the chat feature built-in to the streaming platform.

A new type of entertainment has recently entered the marketplace: interactive entertainment. Concerts are being held virtually in games like Fortnite (Epic Games 2021). TV Shows on Netflix are beginning to …

Analysis And Installation Of A Demonstration Agroforestry Orchard For Californian Mediterranean Plant Communities, Brandon Hurd

Master of Science in Environmental Sciences and Management Projects

Climate-appropriate agroforestry can provide low-input food security and ecosystem services for local Californian Mediterranean climates, while conserving natural resources (e.g., water, nitrogen, etc.). This project showcases a variety of agroforestry methods for five common plant communities of California and other analogous Mediterranean climates at the CAFES Experimental Farm on the campus of Cal Poly San Luis Obispo. Plant community species and their ethnobotanical uses were analyzed to mimic and incorporate aspects of native flora. Agricultural plants were also characterized to represent each of the five selected plant communities. GIS was used to assess the project site for soil, slope, and …

Calculating MBh Scaling Relations For Agns Using 2d Galaxy Decomposition Software To Analyse Hst Images, Jewel A. Capili

Physics

This study uses the 2D galaxy decomposition software GALFIT developed by Dr. Chien Peng to analyse Hubble Space Telescope images of 14 Active Galactic Nuclei (AGNs) and obtain their M_BH-spheroid luminosity scaling relations for comparison with previous studies.

Precious Plastics - Plastic Brick Machine Fabrication, Timothy Ukaobasi Kanu, Evi Paraskevi Troulis

Architectural Engineering

The goal of this research is to determine the structural parameters of the recycled plastic polypropylene when molded into bricks resembling CMU blocks. To accomplish this, three mechanisms had to be assembled: the shredder, the injector, and the 1x1 mold. A tensile and compression test were to be performed on the plastic brick, and the values would be used to compare the tensile and compressive strength of PP plastic bricks, as well as their modulus of elasticity and stress vs. Strain performance. These values would be analyzed to determine whether it would be feasible to build an entire plastic wall. …

Psf Sampling In Fluorescence Image Deconvolution, Eric A. Inman

Master's Theses

All microscope imaging is largely affected by inherent resolution limitations because of out-of-focus light and diffraction effects. The traditional approach to restoring the image resolution is to use a deconvolution algorithm to “invert” the effect of convolving the volume with the point spread function. However, these algorithms fall short in several areas such as noise amplification and stopping criterion. In this paper, we try to reconstruct an explicit volumetric representation of the fluorescence density in the sample and fit a neural network to the target z-stack to properly minimize a reconstruction cost function for an optimal result. Additionally, we do …

Heat Flux Dynamics And Seasonal Variability In Morro Bay, California, Mikaela Romanini

Master's Theses

There is a growing need to better understand the dynamics of small and medium Mediterranean low-inflow estuaries (LIEs), which is addressed here by characterizing a heat budget and associated heat transfer processes. A one-dimensional deterministic model was developed from the advection-diffusion equation and applied to Morro Bay, CA using 15-minute water property (temperature, salinity, pressure) and meteorological (wind speed and direction, air temperature, relative humidity, air pressure, irradiance) data collected over a two-year period (2020 – 2021). Seasonal variability is observed in meteorological components, water temperature, and salinity. There is strong seasonal variability in head-mouth temperature and salinity differences. Temperature …

Modeling Daily Fantasy Basketball, Martin Jiang

Master's Theses

Daily fantasy basketball presents interesting problems to researchers due to the extensive amounts of data that needs to be explored when trying to predict player performance. A large amount of this data can be noisy due to the variance within the sport of basketball. Because of this, a high degree of skill is required to consistently win in daily fantasy basketball contests. On any given day, users are challenged to predict how players will perform and create a lineup of the eight best players under fixed salary and positional requirements. In this thesis, we present a tool to assist daily …

Irreducible Representations From Group Actions On Trees, Charlie Liou

Master's Theses

We study the representations of the symmetric group $S_n$ found by acting on

labeled graphs and trees with $n$ vertices. Our main results provide

combinatorial interpretations that give the number of times the irreducible

representations associated with the integer partitions $(n)$ and $(1^n)$ appear

in the representations. We describe a new sign

reversing involution with fixed points that provide a combinatorial

interpretation for the number of times the irreducible associated with the

integer partition $(n-1, 1)$ appears in the representations.

Wordmuse, John M. Nelson

Computer Science and Software Engineering

Wordmuse is an application that allows users to enter a song and a list of keywords to create a new song. Built on Spotify's API, this project showcases the fusion of music composition and artificial intelligence. This paper also discusses the motivation, design, and creation of Wordmuse.

Assessing The Effectiveness Of Climate Change Science Communication In An Online Carbon Footprint Assessment, Jack Dimmock

Master of Science in Environmental Sciences and Management Projects

Climate change literacy and knowledge are influential in enabling people to take climate change mitigation and adaptation actions. Education about climate change usually takes place through two avenues, formal education and informal institutions, such as museums, television shows, and websites. To help residents reduce their household greenhouse gas emissions and adapt to the local impacts of climate change, the San Luis Obispo Climate Coalition is using the carbon footprint website Bright Action (https://resilientslo.org). Bright Action calculates household carbon footprints, suggests ways to reduce carbon footprints, and provides educational material about climate change mitigation and adaptation. This study seeks to assess …

A Cradle-To-Gate Life Cycle Assessment Of American Hops In The Craft Beer Supply Chain, Carson Bristol

Master of Science in Environmental Sciences and Management Projects

The hop industry represents a culturally and economically significant industry in the United States due to the product’s significant role in the beer industry, but little is known about the environmental impacts associated with hop production. There exists a significant lack of specific research quantifying the emissions contribution of hop production, and the work that has been done lacks consensus in the scientific community. In an effort to overcome this, this study conducts a cradle-to-gate life cycle assessment (LCA) of aroma hop production broken into four phases, beginning with propagation of seedlings by tissue culture and ending with packaged T-90 …

Building Structures From Mycelium, Noah M. Brown

Physics

The purpose of this project was to develop a method for creating bricks from mycelium and agricultural waste. The bulk of the research happened in two parts, the first part being a period in which different substrates, strains, and methods were used build the bricks. This research took place in San Luis Obispo and was aided by a group of students in PSC392 under Dr. Pete Schwartz in early 2022. After developing a method for constructing these bricks, the research was moved to St. Thomas, Jamaica, in collaboration with an ecovillage called The Source Farm from July to September. The …

Predicting Startup Success Using Publicly Available Data, Emily Gavrilenko

Master's Theses

Predicting the success of an early-stage startup has always been a major effort for investors and venture funds. Statistically, there are about 305 million total startups created in a year, but less than 10% of them succeed to become profitable businesses. Accurately identifying the signs of startup growth is the work of countless investors, and in recent years, research has turned to machine learning in hopes of improving the accuracy and speed of startup success prediction.

To learn about a startup, investors have to navigate many different internet sources and often rely on personal intuition to determine the startup’s potential …

Wildfire Spread Prediction Using Attention Mechanisms In U-Net, Kamen Haresh Shah, Kamen Haresh Shah

Master's Theses

An investigation into using attention mechanisms for better feature extraction in wildfire spread prediction models. This research examines the U-net architecture to achieve image segmentation, a process that partitions images by classifying pixels into one of two classes. The deep learning models explored in this research integrate modern deep learning architectures, and techniques used to optimize them. The models are trained on 12 distinct observational variables derived from the Google Earth Engine catalog. Evaluation is conducted with accuracy, Dice coefficient score, ROC-AUC, and F1-score. This research concludes that when augmenting U-net with attention mechanisms, the attention component improves feature suppression …