Digital Commons Network^™

From Tree To Shrub? The Fate Of Tanoak Through Fire And Nonnative Disease, Jacqueline Rose

Master's Theses

Invasive plant pathogens have killed an uncountable number of trees and disrupted ecosystem processes throughout the world. Newly introduced pathogens may interact with historically occurring disturbances in unexpected ways to cause amplified mortality and change to ecosystem processes. Here, I examine the a natural experiment created by three wildfires in Big Sur, a portion of the central coast of California impacted by the nonnative pathogen Phytophthora ramorum, to forecast the future of a species susceptible to the pathogen. Using a plot network which spans the length of Big Sur, I track the survival of individual tanoak (Notholithocarpus densiflorus) stems and …

Design, Analysis, And Implementation Of An Improved Zero Voltage Switching Hybrid Voltage Divider, Luke V. Cerda

Master's Theses

This thesis entails the study, design, and construction of a novel DC-DC converter topology, the Zero Voltage Switching Hybrid Voltage Divider (ZVS-HVD), with improved modularization, optimization, and compactness. The ZVS-HVD facilitates higher load currents and accomplishes DC-DC voltage division through switching inductors and capacitors. Low switching loss is achieved through zero voltage switching (ZVS) and the use of GANFET switches. An analysis of duty cycle and high-frequency operation is conducted, enabling 1 MHz switching and improvements in output voltage ripple, voltage drooping, board size, and efficiency at higher load currents. Two versions of ZVS-HVD prototypes were constructed with on-board signal …

Frequent Itemset Mining With Tidyclust In R, Andrew D. Kerr

Master's Theses

Unsupervised learning is closely associated with clustering, however other methods fall under this umbrella such as data mining. In R, the tidyclust package provides a unified interface for clustering models, yet lacks support for data mining. This thesis addresses this gap by introducing the Apriori and ECLAT algorithms into tidyclust, with a focus on frequent itemset mining. Unlike traditional clustering models, frequent itemsets produce groupings of column variables, rather than cluster labels or partitions of observations. To address this, a novel clustering approach is proposed: items (columns) are grouped based on their ”dominant” frequent itemset. A key contribution is a …

Stability Insights From Modeling Chronic Myelogenous Leukemia, Giovani Thai

Master's Theses

This thesis centers around a model for chronic myelogenous leukemia (CML) as it behaves under imatinib treatment, a common medication for CML patients, and the anti-leukemia immune response. The dynamics are represented with a system of nonlinear delay-differential equations first constructed by Kim et al. in 2008, capturing population changes of T-cells and various CML growth stages. We investigate stability in both the clinical and mathematical sense. Through numerical simulations, we computationally incorporate a supplementary treatment plan to determine its effectiveness in aiding immune response and medication in achieving remission and full elimination. The primary goal is to conduct a …

Structural Color Pigments For Waterborne Coatings, Kyle William Liston

Master's Theses

Structural colors offer unique alternatives to conventional pigments, utilizing their microstructures to produce vibrant colors. These pigments offer an alternative source for colorants without the need for less environmentally friendly conventional pigments. In keeping with the sustainability approach, the use of waterborne coatings was chosen over solvent-based coatings. Here we report the synthesis of brushite platelet, silica supraball, and inverse opal pigments. Brushite platelets were produced through a condensation reaction, while silica supraballs were synthesized via the Stöber process and assembly was attempted using an oil-in-water emulsion. Inverse opal was produced through the templating of silica on poly(methyl methacrylate) (PMMA) …

Functionalization Of A Calcium-Based Squaric Acid Metal Organic Frameworks With Amine-Based Polymers For Enhancing Post Combustion Carbon Capture, Corinne D. Watson

Master's Theses

The primary driver of climate change is the release of carbon dioxide (CO₂) from fossil fuel combustion. Global climate change has resulted in sea level rise, adverse weather patterns, and countless other negative global effects. Several carbon-reduction frameworks emphasize the transition to clean energy sources; however, other strategies must be concurrently pursued to immediately and effectively reduce atmospheric carbon dioxide point source emissions. Metal organic frameworks (MOFs) are a promising new technology for post-combustion carbon dioxide capture. The materials are synthesized using organic linker molecules and metal ion joints. Notably, there are several challenges with various types of …

Langlands Reciprocity And The Splitting Behavior Of Primes In Number Fields, Skip E. Moses

Master's Theses

This thesis explores the evolution of reciprocity laws in number theory in order to provide a conceptual bridge between the classical ideas of quadratic reciprocity and the modern framework of the Langlands program. We develop the necessary algebraic background to understand how the splitting behavior of primes in number fields reflects deep arithmetic structure in ℚ. Starting with quadratic fields and cyclotomic extensions, we motivate the development of the Kronecker–Weber theorem and the characterization of abelian extensions of ℚ. We then introduce Artin reciprocity and show how it generalizes quadratic reciprocity through the formalism of Frobenius elements and Artin L-functions. …

A Case Study Of Leveraging Auxiliary Data To Improve Treatment Effect Estimation Precision In An Hiv Clinical Trial, Lana Mai Huynh

Master's Theses

Randomized controlled trials (RCTs) are typically the gold standard for evaluating treatment efficacy in the medical field, yet they can have small sample sizes due to logistical, ethical, and financial constraints. This limitation can result in imprecise treatment effect estimates. Recent methods have sought to enhance the precision of RCT estimates by incorporating information from large, observational, “auxiliary” datasets. An auxiliary dataset includes units that were not randomized in the trial itself, but may be similar to the RCT sample. By leveraging predictive models trained on these auxiliary data, researchers can adjust for potentially more powerful covariates, thereby reducing variance …

Catalyzed Chemical Recycling Of Poly(Ethylene Terephthalate) For Enhanced Sustainability, Gilberto J. Hernandez-Leypon Jr.

Master's Theses

Plastics are ubiquitous in the production of consumer and industrial products; their chemical stability, low cost of production, and performance versatility make them the best option for many industries. Their inherent benefits, specifically durability, is the basis for the negative environmental impact of polymers. Improper containment of endof-life polymer products causes unintentional migration into the environment. The monomers for many common polymer types are also fossil fuel based further increasing the environmental impact of the plastic lifecycle. Recycling is a possible method of closing the loop of the plastic lifecycle. Currently most recycling is physical, thermally reprocessing used plastics into …

Studies On The Effects Of Cap Management On The Oxidation–Reduction Potential, Phenolic Composition, And Sensory Properties Of Red Wines, Dallas J. Parnigoni

Master's Theses

Cap management during alcoholic fermentation of red wines plays a critical role in modulating the phenolic and volatile extraction from grape solids, influencing the homogenization of chemical and temperature gradients, while imparting oxygen to the must. Different cap management alternatives are also thought to influence the evolution of the oxidation-reduction potential (ORP). It is critical to understand how different cap management protocols affect these variables to design a cap management protocol tailored to wine style and varietal. This thesis investigated the effects common commercially applied cap management protocols, as well as the efficacy of novel, automated gas mixing protocols as …

Data Driven Analysis Of Samara Seed Kinematics And Dynamics, Shashwat Sparsh

Master's Theses

Samara Seeds are a class of fruit most famously belonging to the Acer species and are characterized by their single-bladed geometry and their auto-rotation response during descent. This steady-state auto-rotation response is the subject of aerodynamic analysis which aim to quantify the performance. The period prior to the beginning of steady-state auto-rotation is classified as the transition regime and has not been the subject of intense scrutiny.

This thesis employs a data-driven approach to analyzing the kinematic and dynamic response of these seeds during both the transition and auto-rotation stages of flight to quantify the performance with respect to the …

Assessing Students’ Attitudes And Self-Efficacy In Introductory Statistics Courses, Kendall Hipes

Master's Theses

This study investigates the cognitive factors that shape students’ experiences in introductory statistics courses, with particular emphasis on the role of self-efficacy sources on student attitudes (mastery experiences, verbal persuasion, vicarious experiences, and physiological and emotional states) measured across multiple time points. Using linear multilevel models and qualitative interview data, the research examines patterns in students’ perceptions of interest, difficulty, effort, value, cognitive competence, and affect throughout an academic quarter. Findings indicate that higher levels of mastery experiences consistently predict more positive outcomes across all attitude dimensions, underscoring the importance of early and ongoing opportunities for success in fostering engagement …

Implementation Of Area-Based Aggregation On Multivariate Continuous Uncertain Data, Rahul Nair

Master's Theses

Uncertain data is incredibly widespread - from sensor data to AI-based learned information, there exists a need to associate information with a certain probability of its veracity. Traditional relational databases lack a built-in functionality to support uncertain data, instead assigning them boilerplate values. Probabilistic databases tackle this problem by assigning non-deterministic data with an associated, often discrete, probability. Variants of probabilistic databases, namely continuous uncertain databases, are used to better model data represented through ranges and distributions. This is especially applicable with sensor-based geographic data as most commercial equipment contains some inherent margin of error.

While uncertain and probabilistic databases …

Spatial And Functional Metrics For Analyzing Seedling Roots, Irina Ivchenko

Master's Theses

To study the complicated structure of a maestro pea seedling root, we investigate three spatial metrics and one functional metric. The spatial metrics are fractal dimension which measures the complexity, convex hull area which measures the occupied space, and Euler characteristic which topologically describes the shape of the root. We discuss the successes of various metrics and the possible limitations they bring to analysis. As a functional metric, we study the rhizosphere: the volume radially around the root branches from which the plant accesses nutrients and water. We investigate the relationship of the rhizosphere to the root, and propose how …

The Effects Of Sirulina And Nannochloropsis Supplementation On Broiler Performance, Intestinal Morphology, And Gut Microbiology, Emily Beckerman

Master's Theses

The poultry industry is constantly searching for new nutritional strategies and better feed conversion ratio to enhance broiler growth and productivity. Microalgae have been shown to improve broiler performance and health depending on species and supplementation levels. The objective of this study was to determine the effects of Spirulina supplementation (Experiment I) and Nannochloropsis supplementation (Experiment II) on broiler production performance, intestinal morphology, and gut microbiology. In Experiment I, a total of 270 broiler chicks (one-day-old Ross 708) were obtained from a local hatchery after vaccinating against Newcastle, Marek’s disease, and Infectious Bronchitis. They were weighed and sorted into 18 …

Comparative Study Of Experimental And Fea Strain Data For Cnt-Coated Fiberglass Sensors, Extensometers, And Metal Foil Strain Gauges, Omar Dwidar

Master's Theses

Material testing is essential across industries such as aerospace, automotive, and construction, playing a critical role in verifying material selection, diagnosing failures, and understanding the development of flaws in structures. These insights are key to designing successful, reliable systems. Conventional metal foil strain gauges are low cost and reliable but provide limited sensitivity with a typical gauge factor around 2. Extensometers provide highly sensitive strain measurements with the disadvantage of a bulky form factor. With advanced materials such as carbon nanotubes, it is possible to manufacture a sensor with the sensitivity closer to that of an extensometer with the small …

Analyzing Player Difficulty Perception In Platformers Through Procedural Level Generation, Sasank Madineni

Master's Theses

Games utilizing Procedural Level Generation (PLG), such as Roguelikes, are becoming increasingly popular in today's gaming sphere. In games employing PLG, levels are generated randomly or pseudo-randomly, and aim to retain player attention through variance in levels between playthroughs. However, when generating levels with variance in structure and design, player enjoyment is often a mixed bag. With low enjoyment, player retention for these games can dwindle. This study explores the efficacy of real-time difficulty adjustment in procedurally generated platformers, as a method for maintaining stable player enjoyment without causing frustration. This thesis focuses on creating a short user experience, MIMEVA, …

Hybrid Computing For Real-Time Model Predictive Control Of A Buck Converter, Grace Paladichuk

Master's Theses

Advancements in power electronics require high switching frequencies which the digital control routines of the systems cannot keep up with. Analog computing is added to digital control systems to prevent bottlenecks and allow real-time implementation. This paper proposes a hybrid computing model predictive control system for a buck converter. The control system implements the gradient dynamics of the optimization function using digital computing, and the gradient dynamics for the penalty function and integrator using analog computing. For the full simulations of the entire system, the PLECS RT Box is used to simulate the controller in real time with a 1 …

Bentonite Erosion And Cation Exchange Effects On Hydraulic Conductivity Of Geosynthetic Clay Liners, Grace Paananen

Master's Theses

Geosynthetic clay liners (GCLs) are used in municipal solid waste landfill (MSW) liner and cover systems as an alternative to thick compacted clay layers. Previous field studies have revealed potential for bentonite erosion in GCLs when subjected to wet-dry cycles that occur when GCLs are placed on slopes, covered with a geomembrane, and left exposed without additional soil cover. A laboratory test program was conducted to quantify the effects of bentonite erosion on hydraulic conductivity of sodium-bentonite geosynthetic clay liners and samples subjected to cation exchange treatment in addition to bentonite erosion. This test program determined what level of bentonite …

Fault Tolerant Dynamic Task Allocation For Heterogeneous Multi-Robot Systems, Jack R. Cline

Master's Theses

This research presents a novel approach to dynamic task allocation in heterogeneous multi-robot systems with integrated fault detection capabilities. As multiple industries are becoming more reliant on multi-robot systems for tasks, maintaining operational efficiency despite robot failures becomes critical. We propose a framework that combines optimization-based task allocation with a Kalman filter that estimates task progress for anomaly detection to identify unreliable agents and dynamically redistribute tasks. Observing values such as the normalized innovation squared (NIS), covariance, and progress rate, the algorithm can designate a robot as faulty. Embedding information about which robots are faulty in the task algorithm allows …

Development Of A Versatile Switching Mode Inverter Laboratory Module, Zachariah Lee Mustar

Master's Theses

DC-AC converters, or inverters, are complex devices that play an essential role in photovoltaic, energy storage, and microgrid systems. Therefore, they constitute a class of power electronics that any power-focused electrical engineering student should be familiar with. This thesis presents the development and testing of a single device that power electronics students will use in a laboratory setting to experiment with each of the four different switching techniques employed in inverters: a simple square wave (SSWI), modified square wave (MSWI), bipolar PWM, and unipolar PWM. The module was built with a physically modifiable control stage and a power stage constituting …

Understanding The Habitat Associations Of Nearshore Rockfishes Inside And Outside Of Marine Protected Areas Using Hook-And-Line Data, Kaila Raeanne Fritch

Master's Theses

Habitat is an important driver in shaping the distribution of a range of species. For demersal fish species, benthic habitat characteristics can drive distribution and community structure. Understanding the relationship between habitat and species distribution in important, especially for exploited species such as rockfishes (Sebastes spp.). Increased data on the relationship between rockfish and benthic habitat characteristics could enhance marine protected areas (MPAs) and management practices which are used to protect rockfishes along the U.S. West Coast. To address this, we used hook-and-line, catch-and-release data that were collected inside two MPAs on the central coast of California, and …

Banach Algebras And The Gelfand Theory Of Group Algebras On Locally Compact Abelian Groups, James Gabriel Bonvanie

Master's Theses

A Banach algebra is a complex algebra that is simultaneously a Banach space in which the norm is submultiplicative. Notably, $L^1(\mathbb{R})$ with the convolutional product is an Abelian, non-unital Banach algebra that admits an approximate identity. We rectify $L^1(\mathbb{R})$ lacking a unit via the unitization $L^1(\mathbb{R})\times\mathbb{C}$ with identity $(0,1)$. Unitization opens the discussion to the spectrum $\sigma(x)$ of a Banach algebra element, in which the spectrum is a nonempty, compact subset of the complex plane. The spectrum of an Abelian Banach algebra is fully characterized with multiplicative linear functionals, and we prove that the Fourier transform is the unique multiplicative …

Compact, Low-Power Underwater Acoustic Modem Characterization And Sensing Network Node Implementation, Lucas W. Lucia

Master's Theses

There is a growing market for compact, power-efficient underwater communication technology. Due to the limited propagation of electromagnetic waves through water, modulated acoustic waves have emerged as an effective means of wireless communication underwater. In decades past, many acoustic modems had been developed primarily for defense customers in larger systems functioning at high power. In recent years, smaller, relatively inexpensive acoustic modems have become available on the market—but data on their performance in a real-world environment is scarce. Companies such as OWL Integrations are interested in employing such acoustic modems as part of sensing networks across multiple mediums. For such …

Deeppanorf: Deep Prior For Neural 3d Reconstruction From Sparse Panoramas, Edward Du

Master's Theses

Advances in neural field representations have led to a significant improvement in view synthesis quality. However, many current novel view synthesis methods rely on a dense set of input views, which can be impractical and inefficient in real-world applications. We propose DeepPanoRF, a novel method for 360◦ scene reconstruction from a sparse set of input equirectangular panoramas. Built upon K-Planes, a radiance field representation that encodes explicit features on orthogonal feature planes, our method does not directly learn feature grids. Instead, we parameterize the feature grids to enable sparse view reconstruction without pretraining or additional regularization. We implement a custom …

Spos: An Attestation Solution For The Detection And Mitigation Of Point Of Sale Malware, Damian Singh Dhesi

Master's Theses

Securing 95% of card present transactions, accounting for billions of transactions a year, has made EMV the premier protocol for card-based payment. Created by and named after Europay, Mastercard, and Visa, the EMV protocol provides multiple solutions to resolve security concerns with the outdated, swipe-based, magnetic stripe payment. Such solutions are Chip and PIN which provides a more secure transaction at a significant time cost and EMV contactless which provides improved security to Chip and PIN at greater ease of use with its quick, tap-to-pay based payment. However, regardless of how secure the EMV protocol makes the card side of …

Cislunar Orbital Debris Removal Feasibility Analysis Using Nrho To Dro Transfers At Varying Solar Angles, Peter C. Lie

Master's Theses

The resurgence of lunar exploration necessitates the expansion of space situational awareness into cislunar space. The current tracking technologies for cislunar objects are insufficient to determine vacant orbital regimes for human spaceflight. Orbital debris generated in the cislunar environment often evolves along complex and chaotic trajectories due to the influence of multi-body dynamics. Current research into methods of removing orbital debris from space is limited to debris in Earth orbits. For cislunar orbits, debris disposal options are slowly gaining research, mostly centered on hypothetical solutions for active missions. Lunar impact and escape to heliocentric space are low-cost options, but serve …

On Diffeomorphism Groups Of Surfaces, Madeleine Goertz

Master's Theses

Let $M$ be a closed, connected, smooth manifold. What are the symmetries of $M$? From a geometric viewpoint, the symmetries of $M$ are precisely its isometries, the self maps which preserve lengths and angles. In the smooth category, the symmetries of $M$ are its diffeomorphisms, the self maps which are smooth and have a smooth inverse. Does expanding our notion of symmetries to include diffeomorphisms result in ``more'' symmetries in a meaningful sense? As a formal conjecture, the claim is that the isometry group of $M$ is a deformation retract of the diffeomorphism group of $M$. If $M$ is the …

Investigating Social Presence In Collaborative Keys For Asynchronous Courses, Lily P. Cook

Master's Theses

Asynchronous virtual courses have become increasingly popular in the years following the global Covid-19 pandemic. These courses, with no set meeting schedule, offer flexibility to both students and instructors, but pose challenges for developing a collaborative learning environment. The Community of Inquiry framework (Rourke et al., 1999) identifies three essential components in an online course necessary to foster a collaborative environment- teaching presence, cognitive presence, and social presence. Social presence is especially impacted in asynchronous learning settings, which presents challenges for the students to display their personalities and connect with the community. This study investigates Collaborative Keys (CKs), structured collaborative …

Minifying Deep Denoising Networks With Knowledge Distillation, Antonio L. Rozzi

Master's Theses

Hearing loss is a prevalent condition, affecting hundreds of millions globally, with a higher incidence among older adults. While hearing aids are the standard treatment, the majority of those who could benefit from hearing aids choose not to wear them, attributing this decision in large part to their inability to perform well in conversations in large groups and in noisy situations. To date, no denoising systems on commercial hearing aids are able to improve speech intelligibility. Recent advances in artificial intelligence research have shown that large deep-learning models can in fact improve speech intelligibility by removing background noise from audio. …