Digital Commons Network^™

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 …

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 …

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 …

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 …

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 …

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 …

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 …

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 …

Analog Hardware Implementation Of A Linearly Constrained Quadratic Program Real-Time Solver, Claire E. Tylutki, Claire Tylutki

Master's Theses

This thesis presents the design, implementation, and analysis of a hardware system for solving Linearly Constrained Quadratic Programs (LCQPs) in real time. The architecture follows a generalized feedback structure composed of three key elements: gradient descent on the quadratic cost function, saturation-based nonlinearity to enforce inequality constraints, and an integral controller with an anti-windup mechanism to regulate dynamic behavior and determine steady-state error. This majority analog system converges with equilibria that satisfy the Karush-Kuhn-Tucker (KKT) optimality conditions. Using a representative LCQP, this work presents simulation of the circuit in PLECS and LT Spice to confirm the feasibility of the novel …

Adversarial Deep Reinforcement Learning For Tank Duel Simulation Using Lidar-Based Observations, Braedan Kennedy

Master's Theses

Previous research has demonstrated that reinforcement learning agents can learn to steer differential-drive robots around obstacles using 2D lidar scans as observations. However, these studies typically treat all range returns as undifferentiated obstacles—objects to avoid—without distinguishing between different object types. This thesis builds upon previous research by introducing an adversarial task in which an agent must interpret raw range readings to both avoid static obstacles and identify, pursue, and engage a hostile target.

To investigate this problem, this thesis introduces TankGame, a novel, lightweight 2D tank duel simulator. Each agent receives a 360° lidar scan, controls its motion via tread …

Flair: A Fog-Native Workload Placement Framework For Qos-Aware Scheduling In Smart Manufacturing, Daiwik N. Swaminathan

Master's Theses

Smart manufacturing environments utilize a variety of heterogeneous IoT sensors that continuously stream large volumes of data. To detect and mitigate critical events such as fires or accidents in real time, this data must be promptly analyzed by machine learning (ML) image classifiers. These classifiers are typically deployed on fog computing nodes located within the manufacturing warehouse facilities to ensure low-latency responses and to protect data privacy. Although fog nodes offer a better alternative to remote cloud data centers for such latency-sensitive tasks, they are often resource-constrained and highly sensitive to the composition of workloads, particularly in heterogeneous environments where …

Opening The Black Box With Regal: A Novel Explainable Ai Approach To Uncover Key Predictors In Search And Rescue Success, Brandon Hyunjun Kim

Master's Theses

The outcome of a search and rescue (SAR) operation is influenced by a complex, non-linear interplay among numerous factors, including geographic context, subject-specific characteristics, and environmental conditions. The high dimensionality and intricate dependencies among these variables pose significant challenges to traditional exploratory modeling approaches, limiting their ability to uncover meaningful patterns and relationships associated with mission success. This study introduces Rules Based Explanations for Generated neighborhoods Around Localized cases (REGAL), a novel adaptation of the Local Interpretable Model-agnostic Explanations (LIME) framework to explain deep multimodal neural networks and what key features it assesses to determine search and rescue success. REGAL …

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 …

Sentry V3: Extending Context Switches On A Trusted Secure Coprocessor, Mark Kong

Master's Theses

Software correctness and integrity is only ensured through trust in the un- derlying hardware. However, modern computer systems are complex to design and secure. Thus, given the choice between performance and security, companies will often prioritize performance, resulting in vulnerable systems. This creates exploitable systems that must be patched retroactively because business value performance over security. One approach to this issue is to separate the root of security from the rest of the system to create a minimal trusted computing base. Trustguard is one instance of this. Trustguard implements a Containment Architecture with Ver- ified Output (CAVO) model which shows …

Data-Driven Product Recommendations: A Decision Support Framework Utilizing Customer Reviews, Tyler A. Lopez

Master's Theses

With the considerable presence of e-commerce in society, vast number of purchasable goods, and increasing brand variety, consumers are faced with the challenge of buying products that they perceive to be of greatest value to them. To assist consumers with making better informed decisions, e-commerce websites allow individuals to post their own experiences and score the products that they purchase. Despite this information, the variety of experiences and feedback that consumers share do not always lead to clarity on whether a product is best suited for the purchaser. To help guide customers through a simplified purchasing process from the perspective …

Design And Development Of A Laboratory Star Tracker System, Kevin D. Iverson

Master's Theses

This thesis presents the design, calibration, and validation of a low-cost star tracker system and hardware-in-the-loop testbed intended for small satellite applications. The system is composed entirely of commercial off-the-shelf components and integrates both a custom star tracker and a screen-based star field simulator for controlled, repeatable testing. An analytical modeling approach was used in the early design phase to predict system accuracy based on key optical and geometric parameters, informing the selection and configuration of components and guiding the development of calibration routines.

A simulation environment was developed to validate the star tracker software and assess the impact of …

Using Hydrologic And Hydraulic Simulations To Predict Near-Term Effects Of Beaver Habitat Restoration On Flood Flows, Luke S. Stewart

Master's Theses

There is a growing need to predict the complex hydrologic and hydraulic effects of beaver-maintained wetlands. This study uses relatively simple inputs and a replicable methodology to predict flood flow impacts of beaver habitat restoration at the site design scale using the engineering industry’s customary hydrology and hydraulic modeling approach. This study focuses on Toro Creek, the primary drainage for a 15.2 square mile watershed on the California Central Coast.

A hydrologic model of Toro Creek watershed was developed in HEC-HMS to approximate saturated soil conditions typical of late-spring flooding events observed in the region. The hydrologic model was calibrated …

Vertical And Latitudinal Variability Of Marine Heatwaves In The California Current, Gavin M. Plume

Master's Theses

Marine heatwaves (MHWs) are increasing in frequency and intensity globally, with grave effects on marine ecosystems and their dependent industries. There are significant gaps in knowledge of the subsurface behavior and geographic distribution of MHWs, especially in eastern boundary upwelling systems like the California Current. Here, two decades of full water-column temperature observations from a shallow autonomous profiler in San Luis Obispo Bay (~10m) revealed that while MHWs have similar average durations and intensities across all depths, one-third of bottom MHWs occur without a concurrent surface signal. MHWs across the water column initiated during anomalously weak upwelling or downwelling conditions …

Identifying Interchromosomal Interactions Using A Graph-Based Computational Pipeline, Ethan Outangoun

Master's Theses

Current computational tools for analyzing chromatin organization are mainly focused on intrachromosomal interactions, despite growing evidence that suggests long-range interactions across chromosomes contribute to transcriptional regulation and disease development. This thesis aims to address this gap in interchromosomal genome analysis, presenting a robust computational pipeline that identifies a clique (i.e., a subgraph) of highly interacting trans-chromosomal regions anchored at a user-specified seed genomic locus. A weighted interaction network is constructed from an input Hi-C contact matrix, a widely used experimental assay for measuring genome-wide chromatin interactions. We model this input contact matrix as a graph and devise three different strategies …

Investigating And Evaluating Poison Unlearning Under Imperfect Detection, Mitashi D. Parikh

Master's Theses

Machine unlearning is an emerging field focused on removing the influence of specific data points from trained machine learning models. Early work in this field has primarily focused on privacy-oriented unlearning, often motivated by data protection regulations such as the GDPR. More recently, security-oriented unlearning has emerged as a response to data poisoning attacks, where malicious inputs are injected into training data to manipulate model behavior. In these security-oriented settings, unlearning methods aim to reverse the influence of malicious training data after a model has already been deployed. However, existing methods assume access to an accurately identified portion of poisoned …

Effect Of Manufacturing And Machining Process On Recycled Composite Connecting Rods Under Tension And Compression, Walter W. Oppelt

Master's Theses

Carbon fiber reinforced polymer (CFRP) is an engineering material renowned for its high-strength and low-density material properties. Such properties make CFRPs especially useful for applications across many industries, including aerospace, automotive, marine, sporting goods, oil and gas, and more. However, with such favorable material properties comes the cost of high energy usage required to produce raw carbon fiber. Recycled carbon fiber (rCF) has emerged as a promising alternative, offering a significant reduction in energy usage. This research explores the viability of applying recycled CFRPs to internal combustion engines to both reduce energy costs during manufacturing and while in use. Mechanical …