Physical Sciences and Mathematics Commons^™

Modeling The Spread Of Covid-19 Over Varied Contact Networks, Ryan L. Solorzano

Master's Theses

When attempting to mitigate the spread of an epidemic without the use of a vaccine, many measures may be made to dampen the spread of the disease such as physically distancing and wearing masks. The implementation of an effective test and quarantine strategy on a population has the potential to make a large impact on the spread of the disease as well. Testing and quarantining strategies become difficult when a portion of the population are asymptomatic spreaders of the disease. Additionally, a study has shown that randomly testing a portion of a population for asymptomatic individuals makes a small impact …

Scenarios For Offshore Wind Power Production For Central California Call Areas, Yi-Hui Wang, Ryan K. Walter, Crow White, Matthew D. Kehrli, Benjamin Ruttenberg

Physics

In response to the growing interest in offshore wind energy development in California, the U.S. Bureau of Ocean Energy Management delineated three Call Areas for potential leasing. This study provides a comprehensive characterization and comparison of offshore wind power potential within the two Central California Call Areas (Diablo Canyon and Morro Bay) using 12-and 15-MW turbines under different inter-turbine spacing and wind farm size scenarios. Our analysis shows similar daily and seasonal patterns of wind power produced within the Call Areas, which peak in spring and during evening hours. Per-turbine power production is higher in the Morro Bay Call Area …

Direct Drive Solar Panel Control Circuit, Marcorios Bekheit

Physics

A control circuit is built for insulated solar electric cookers (ISEC). Power delivery and temperature safety are the focus. Using a maximum power point tracking (MPPT) algorithm, Arduino Nano, voltage and current sensors, and a buck converter, the solar panel’s output power was maximized for a direct load heat resistor with 3.5Ω for a range of solar intensities. Using a resistance temperature detector, a temperature sensor is built for safety shutoff.

A Retrospective Analysis Of The Impact Of Wind Power Generation On Residential Natural Gas Prices In The United States, Maya Vikstrom

Economics

Heightened concern over the environmental impact and price volatility of natural gas has led to an increased demand for renewable energy. Wind energy is one of the fastest-growing sources of electricity and is the United States’ top renewable energy source. As a substitute for natural gas, wind energy has a direct impact on the demand for natural gas and consequently, the price. Using data from the U.S. Energy Information Administration, the Bureau of Economic Analysis, and the U.S. NOAA, this paper determines a causal relationship between wind generation and natural gas prices because of the random component of weather. Employing …

A Mobile Application For Optimally Matching Real Estate Clients, Yu Karen Asai, Steven Andrew Luu

Computer Science and Software Engineering

Real estate agents are often tasked with finding their clients’ ideal properties. This can be difficult because multiple clients may have varying preferences, such as number of bedrooms, square footage, or price. Furthermore, different clients may weight their individual preferences differently. Existing applications do not consider multiple clients’ satisfaction, nor do they allow clients to weigh their preferences, potentially leading to less-than-ideal matchings between clients and properties.

In this project, we design and implement an iOS application whereby real estate agents can match multiple clients with individually weighted preferences to properties scraped from web listings. We model this client-property matching …

Analyzing Student Experience On Group Work With The Application Of Different Group Allocation Approaches, An Yee Tan

Management and HR

Working as a group can be as challenging as working by oneself. Common issues like ineffective group work, unequal work contribution, and poor communication are believed to be the reasons why many students preferred to work individually. The purpose of this study is to understand if there is a disparity in student experience on group work by implementing different methods of group formation, which are, intentional group formation and random assignment. Topics around team well-being, team communication, and team effectiveness are the main focus of this study. The second emphasis of this study is students’ opinions on whether or not …

Characteristics And Management Implications Of Mollic Soils In Forest Versus Grassland Settings In Central California, Brian Charles Clark

Master's Theses

Efforts to sequester soil carbon (C) should consider soils intrinsically capable at C retention. Of the mineral soil orders, Mollisols have minimum requirements for soil organic C (SOC; over 0.06 %) and basic saturation (over 50 %). In the U.S., grasslands comprise 93% of the vegetation mapped above Mollisols. Soils beneath the southern extent of Sequoia sempervirens (redwood) forests in central California are mapped as Molliols. It widely accepted that redwood forests harbor considerable biomass C, but the extent to which aboveground C is retained in the soil is not well understood. This study aimed to: (i) to gather baseline …

Potential Environmental Effects Of Deepwater Floating Offshore Wind Energy Facilities, Hayley Farr, Benjamin Ruttenberg, Ryan K. Walter, Yi-Hui Wang, Crow White

Physics

Over the last few decades, the offshore wind energy industry has expanded its scope from turbines mounted on foundations driven into the seafloor and standing in less than 60 m of water, to floating turbines moored in 120 m of water, to prospecting the development of floating turbines moored in ~1,000 m of water. Since there are few prototype turbines and mooring systems of these deepwater, floating offshore wind energy facilities (OWFs) currently deployed, their effects on the marine environment are speculative. Using the available scientific literature concerning appropriate analogs, including fixed-bottom OWFs, land-based wind energy facilities, wave and tidal …

Seasonal Controls On Nearshore Hypoxia In A Small Coastal Embayment, Stephen Alexander Huie

Physics

Dissolved oxygen (DO) is an important biogeochemical factor that strongly influences nearshore coastal ecosystems. Low DO (hypoxic) events can cause physiological stressful environments for ecological and economically important species, potentially leading to mass mortalities. In order to better assess drivers of coastal hypoxia, we collected data from monthly cruises on the inner shelf and nearshore moorings inside and outside a small coastal embayment (San Luis Obispo Bay on the Central California Coast) across the full upwelling season (March to August). During the late spring and early summer, we found that the nearshore near-bottom temperature-DO (T-DO) relationship aligned with the shelf …

Comparing The Environmental Impacts Of Using Mass Timber And Structural Steel, Khang Hoang Nguyen, Steelee Knight Morgan

Construction Management

Although mass timber has seen a gradual rise in demand in the past, there has been a lack of extensive research on the environmental impacts of using mass timber as a primary structural framing material. This paper compares structural steel, and mass timber’s total embodied carbon emissions. Accurate estimates were made using plans and specs for different projects retrieved from semi-structured interviews. The estimates were input through the EC3 Calculator to provide extensive total carbon emissions measurements between each construction material. Using structural steel framing increased the project’s overall environmental impact by roughly 84% compared to using mass timber. The …

Node Classification On Relational Graphs Using Deep-Rgcns, Nagasai Chandra

Master's Theses

Knowledge Graphs are fascinating concepts in machine learning as they can hold usefully structured information in the form of entities and their relations. Despite the valuable applications of such graphs, most knowledge bases remain incomplete. This missing information harms downstream applications such as information retrieval and opens a window for research in statistical relational learning tasks such as node classification and link prediction. This work proposes a deep learning framework based on existing relational convolutional (R-GCN) layers to learn on highly multi-relational data characteristic of realistic knowledge graphs for node property classification tasks. We propose a deep and improved variant, …

Brain Tumor Detection And Classification From Mri Images, Anjaneya Teja Sarma Kalvakolanu

Master's Theses

A brain tumor is detected and classified by biopsy that is conducted after the brain surgery. Advancement in technology and machine learning techniques could help radiologists in the diagnosis of tumors without any invasive measures. We utilized a deep learning-based approach to detect and classify the tumor into Meningioma, Glioma, Pituitary tumors. We used registration and segmentation-based skull stripping mechanism to remove the skull from the MRI images and the grab cut method to verify whether the skull stripped MRI masks retained the features of the tumor for accurate classification. In this research, we proposed a transfer learning based approach …

Physics Engine On The Gpu With Opengl Compute Shaders, Quan Huy Minh Bui

Master's Theses

Any kind of graphics simulation can be thought of like a fancy flipbook. This notion is, of course, nothing new. For instance, in a game, the central computing unit (CPU) needs to process frame by frame, figuring out what is happening, and then finally issues draw calls to the graphics processing unit (GPU) to render the frame and display it onto the monitor. Traditionally, the CPU has to process a lot of things: from the creation of the window environment for the processed frames to be displayed, handling game logic, processing artificial intelligence (AI) for non-player characters (NPC), to the …

Towards A Complete Formal Semantics Of Rust, Alexa White

Master's Theses

Rust is a relatively new programming language with a unique memory model designed to provide the ease of use of a high-level language as well as the power and control of a low-level language while preserving memory safety. In order to prove the safety and correctness of Rust and to provide analysis tools for its use cases, it is necessary to construct a formal semantics of the language. Existing efforts to construct such a semantic model are limited in their scope and none to date have successfully captured the complete functionality of the language. This thesis focuses on the K-Rust …

Gpu High-Performance Framework For Pic-Like Simulation Methods Using The Vulkan® Explicit Api, Kolton Jacob Yager

Master's Theses

Within computational continuum mechanics there exists a large category of simulation methods which operate by tracking Lagrangian particles over an Eulerian background grid. These Lagrangian/Eulerian hybrid methods, descendants of the Particle-In-Cell method (PIC), have proven highly effective at simulating a broad range of materials and mechanics including fluids, solids, granular materials, and plasma. These methods remain an area of active research after several decades, and their applications can be found across scientific, engineering, and entertainment disciplines.

This thesis presents a GPU driven PIC-like simulation framework created using the Vulkan® API. Vulkan is a cross-platform and open-standard explicit API for graphics …

Quantum Computing: Resolving Myths, From Physics To Metaphysics, Jacob R. Mandel

Physics

As the field of quantum computing becomes popularized, myths or misconceptions will inevitably come along with it. From the sci-fi genre to the casual usage of the term quantum, idealism begins to take over our projections of the technological future. But what are quantum computers? And what does quantum mean? How are they any different than the computers we use on an everyday basis? Will there be quantum computing smartphones? Are quantum computers just a faster version of conventional computing or a wholly new way of computing altogether? The objective of this paper is to resolve common myths or misconceptions …

Lorentz Violation In Neutrino Interactions, Pranav Jayaram Seetharaman

Physics

Both the Standard Model of particle physics and General Relativity require Lorentz symmetry as a fundamental building block. In this paper, we learn about a framework called the Standard Model Extension that allows us to determine how physical phenomenon would change if we deviated from Lorentz invariance in the Standard Model and General Relativity. We use the Standard Model Extension to analyze a specific high-energy, astrophysical neutrino interaction that is only possible if Lorentz symmetry can be broken. The interaction we look at is the decay of a neutrino into an electron-positron pair, which is not possible in conventional physics. …

Comparing Radiation Shielding Potential Of Liquid Propellants To Water For Application In Space, John Czaplewski

Master's Theses

The radiation environment in space is a threat that engineers and astronauts need to mitigate as exploration into the solar system expands. Passive shielding involves placing as much material between critical components and the radiation environment as possible. However, with mass and size budgets, it is important to select efficient materials to provide shielding. Currently, NASA and other space agencies plan on using water as a shield against radiation since it is already necessary for human missions. Water has been tested thoroughly and has been proven to be effective. Liquid propellants are needed for every mission and also share similar …

Clustering Web Users By Mouse Movement To Detect Bots And Botnet Attacks, Justin L. Morgan

Master's Theses

The need for website administrators to efficiently and accurately detect the presence of web bots has shown to be a challenging problem. As the sophistication of modern web bots increases, specifically their ability to more closely mimic the behavior of humans, web bot detection schemes are more quickly becoming obsolete by failing to maintain effectiveness. Though machine learning-based detection schemes have been a successful approach to recent implementations, web bots are able to apply similar machine learning tactics to mimic human users, thus bypassing such detection schemes. This work seeks to address the issue of machine learning based bots bypassing …

Assessing Stream-Aquifer Connectivity In A Coastal California Watershed, Bwalya Malama, Devin Pritchard-Peterson, John J. Jasbinsek, Christopher Surfleet

Physics

We report the results of field and laboratory investigations of stream-aquifer interactions in a watershed along the California coast to assess the impact of groundwater pumping for irrigation on stream flows. The methods used include subsurface sediment sampling using direct-push drilling, laboratory permeability and particle size analyses of sediment, piezometer installation and instrumentation, stream discharge and stage monitoring, pumping tests for aquifer characterization, resistivity surveys, and long-term passive monitoring of stream stage and groundwater levels. Spectral analysis of long-term water level data was used to assess correlation between stream and groundwater level time series data. The investigations revealed the presence …

Space Telescope And Optical Reverberation Mapping Project. Ix. Velocity–Delay Maps For Broad Emission Lines In Ngc 5548, Keith Horne, G. De Rosa, B. M. Peterson, A. J. Barth, Vardha N. Bennert, Y. Zu

Physics

In this contribution, we achieve the primary goal of the active galactic nucleus (AGN) STORM campaign by recovering velocity–delay maps for the prominent broad emission lines (Lyα, C IV, He II, and Hβ) in the spectrum of NGC 5548. These are the most detailed velocity–delay maps ever obtained for an AGN, providing unprecedented information on the geometry, ionization structure, and kinematics of the broad-line region. Virial envelopes enclosing the emission-line responses show that the reverberating gas is bound to the black hole. A stratified ionization structure is evident. The He II response inside 5–10 lt-day has a broad single-peaked velocity …

The Structure Function Relationship Of Disordered Networks Using Young's Modulus And Floppy Modes, Melinda Grace Tajnai

Physics

Disordered networks may have the ability to store information that can be retrieved using a Young’s modulus measurement. The effect of the number of floppy modes a network has on the value of this Young’s modulus measurement is unknown. This experiment uses 28 networks consisting of 3D printed edges in a sliding frame to determine how the Young’s modulus of a network is related to the number of floppy modes.

Effects Of Estuary-Wide Seagrass Loss On Fish Populations, Jennifer K. O'Leary, Maurice C. Goodman, Ryan K. Walter, Kariss Willits, Daniel J. Pondella

Physics

Globally, habitat loss in coastal marine systems is a major driver of species decline, and estuaries are particularly susceptible to loss. Along the United States Pacific coast, monospecific eelgrass (Zostera marina) beds form the major estuarine vegetated habitat. In Morro Bay, California, eelgrass experienced an unprecedented decline of > 95%, from 139 ha in 2007 to < 6 ha by 2017. Fish populations were compared before and after the eelgrass decline using trawl surveys. Beach seines surveys were also conducted during the post-decline period to characterize species within and outside of remnant eelgrass beds.While the estuary-wide loss of eelgrass did not result in fewer fish or less biomass, it led to changes in species composition. The post-eelgrass decline period was characterized by increases in flatfish (mainly Citharichthys stigmaeus) and staghorn sculpin (Leptocottus armatus), and decreases in habitat specialists including bay pipefish (Syngnathus leptorhynchus) and shiner perch (Cymatogaster aggregata). There were similar trends inside and outside of remnant eelgrass patches. These findings support evidence across multiple ecosystems suggesting that the predominance of habitat-specialists predicts whether or not habitat loss leads to an overall decline in fish abundance. In addition, loss of critical habitats across seascapes can restrict population connectivity and lead to range contraction. For bay pipefish, the loss of eelgrass in Morro Bay is likely to create a population biogeographic divide. Currently, Morro Bay is dominated by flatfish and sculpins, and the longevity of this new ecosystem state will depend on future eelgrass recovery dynamics supported by ecosystem-based management approaches.

Machine Learning Based Predictions Of Dissolved Oxygen In A Small Coastal Embayment, Manuel Valera, Ryan K. Walter, Barbara A. Bailey, Jose E. Castillo

Physics

Coastal dissolved oxygen (DO) concentrations have a profound impact on nearshore ecosystems and, in recent years, there has been an increased prevalance of low DO hypoxic events that negatively impact nearshore organisms. Even with advanced numerical models, accurate prediction of coastal DO variability is challenging and computationally expensive. Here, we apply machine learning techniques in order to reconstruct and predict nearshore DO concentrations in a small coastal embayment while using a comprehensive set of nearshore and offshore measurements and easily measured input (training) parameters. We show that both random forest regression (RFR) and support vector regression (SVR) models accurately reproduce …

Eelgrass (Zostera Marina) Population Decline In Morro Bay, Ca: A Meta-Analysis Of Herbicide Application In San Luis Obispo County And Morro Bay Watershed, Tyler King Sinnott

Master's Theses

The endemic eelgrass (Zostera marina) community of Morro Bay Estuary, located on the central coast of California, has experienced an estimated decline of 95% in occupied area (reduction of 344 acres to 20 acres) from 2008 to 2017 for reasons that are not yet definitively clear. One possible driver of degradation that has yet to be investigated is the role of herbicides from agricultural fields in the watershed that feeds into the estuary. Thus, the primary research goal of this project was to better understand temporal and spatial trends of herbicide use within the context of San Luis …

Attentional Parsing Networks, Marcus Karr

Master's Theses

Convolutional neural networks (CNNs) have dominated the computer vision field since the early 2010s, when deep learning largely replaced previous approaches like hand-crafted feature engineering and hierarchical image parsing. Meanwhile transformer architectures have attained preeminence in natural language processing, and have even begun to supplant CNNs as the state of the art for some computer vision tasks.

This study proposes a novel transformer-based architecture, the attentional parsing network, that reconciles the deep learning and hierarchical image parsing approaches to computer vision. We recast unsupervised image representation as a sequence-to-sequence translation problem where image patches are mapped to successive layers …

A Hydrologic Model Of The Northern Limb Of The San Luis Obispo Valley Aquifer By Use Of Comsol Multiphysics® Simulation Software, Claire Momberger

Master of Science in Environmental Sciences and Management Projects

The passage of the Sustainable Groundwater Management Act in 2014 by the State of California was the first of its kind in the State’s history to legislate the management of groundwater resources. This legislation is state-governed but locally and regionally implemented. The Sustainable Groundwater Management Act requires local water management agencies to create their own sustainable management plans for groundwater resources that meet state-defined sustainability goals 20 years after implementation. Such plans require hydrologic conceptual models that describe flow within the groundwater basin setting, predict use, and anticipate demand. The high-level detail of the hydrologic conceptual models requires the power …

Predicting Personality Type From Writing Style, Tanay Gottigundala

Master's Theses

The study of personality types gained traction in the early 20th century, when Carl Jung's theory of psychological types attempted to categorize individual differences into the first modern personality typology. Iterating on Jung's theories, the Myers-Briggs Type Indicator (MBTI) tried to categorize each individual into one of sixteen types, with the theory that an individual's personality type manifests in virtually all aspects of their life. This study explores the relationship between an individual's MBTI type and various aspects of their writing style. Using a MBTI-labeled dataset of user posts on a personality forum, three ensemble classifiers were created to predict …

Envrment: Investigating Experience In A Virtual User-Composed Environment, Matthew Key

Master's Theses

Virtual Reality is a technology that has long held society's interest, but has only recently began to reach a critical mass of everyday consumers. The idea of modern VR can be traced back decades, but because of the limitations of the technology (both hardware and software), we are only now exploring its potential. At present, VR can be used for tele-surgery, PTSD therapy, social training, professional meetings, conferences, and much more. It is no longer just an expensive gimmick to go on a momentary field trip; it is a tool, and as with the automobile, personal computer, and smartphone, it …

Dataset And Evaluation Of Self-Supervised Learning For Panoramic Depth Estimation, Ryan Nett

Master's Theses

Depth detection is a very common computer vision problem. It shows up primarily in robotics, automation, or 3D visualization domains, as it is essential for converting images to point clouds. One of the poster child applications is self driving cars. Currently, the best methods for depth detection are either very expensive, like LIDAR, or require precise calibration, like stereo cameras. These costs have given rise to attempts to detect depth from a monocular camera (a single camera). While this is possible, it is harder than LIDAR or stereo methods since depth can't be measured from monocular images, it has to …