Digital Commons Network^™

Towards Safe And Reliable Ai Models, Zihang Zou

Graduate Thesis and Dissertation post-2024

With the rapid advancement of artificial intelligence, its applications have become indispensable in our daily lives. Emerging advanced AI models, from general-purpose Large Language Models (LLMs) such as ChatGPT and Deepseek to domain-specific systems such as autopilot for autonomous vehicles, are changing the way we work and live by increasing efficiency and fostering innovation. However, these advancements also bring significant risks, as they may compromise data ownership or yield unreliable outcomes. In response, we focus on two critical areas: data safety and model reliability. To ensure data safety and promote lawful data processing, we investigate anti-neural watermarking techniques designed to …

Contagion Chronicles: A Spatiotemporal Analysis Of Armed Conflict And Infectious Disease, Devyn Escalanti

Graduate Thesis and Dissertation post-2024

This dissertation examines the relationship between armed conflict and infectious disease transmission through a novel theoretical framework that integrates ecological disturbance and health systems resilience theories into epidemiological contexts. The framework conceptualizes diseases along a continuum from "pulse" to "press." Pulse diseases, like Ebola, are characterized by sudden onset, high mortality, and short-term outbreaks. Press diseases, like HIV, progress gradually with lower mortality and long-term persistence. Grounded in this pulse–press disease typology and ecological and health systems resilience, the theory suggests that the absorptive capacity, adaptive capacity, and resilience of community health workers in conflict areas can influence disease transmission, …

Computation-Efficient And Scalable Robotic Motion Planning Techniques To Address Dynamic Environmental Constraints, Apan Dastider

Graduate Thesis and Dissertation post-2024

In modern robotics, effectively computing optimal robotic control policies under dynamically varying environmental constraints poses substantial challenges and remains a unique research endeavor. To compute efficient and safe robotic motion planning while achieving collective objectives, robotic agents have to satisfy two criteria. First, the working robotic entity must be capable of handling a non-stationary working environment with dynamic obstacles and system constraints. Second, to ensure the real-time response, the robotic agent has to compute an effective control policy that meets a real-time learning performance. Despite significant advancements in motion planning with the appearance of extensive computing resources and advanced deep …

On The Dynamic Connectivity And Phase Transition In River Networks, Juthika Roy

Graduate Thesis and Dissertation post-2024

River network (RN) structure has a significant impact on flux transport, aggregation and ecosystem connectivity. In this dissertation, the structural control of RN on flux transport was investigated by the application of integrated framework of dynamic clusters and network graph theory. This new framework has been proposed to determine sub-catchment connectivity using minimum and maximum flow criteria. Our analysis on synthetic and natural RNs across United States demonstrates that basin scale connectivity at low flow conditions is efficiently governed by the abundance of side branching junctions whereas this characteristic slows down the flux convergence rate at maximum flow condition.

Furthermore, …

E-Cskpd: A Frequentist Framework For Multi-Modal High-Order Tensor Regression, Joshua D. White

Graduate Thesis and Dissertation post-2024

Understanding which features drive the outputs of modern learning systems remains a core challenge for regression and classification. While deep neural networks can be highly accurate, their latent representations often obscure how inputs map to decisions, limiting statistical inference, stakeholder trust, and practical use in domain decision-making. Sparse Kronecker Product Decomposition (SKPD) is a frequentist, tensor-structured approach that offers interpretable regression/classification in high dimensions. However, standard SKPD restricts relationships among predictors and covariates and is typically limited to order-2 tensors. This dissertation introduces E-CSKPD, an ensemble framework that (i) revisualizes designs to control non-imaging covariates; (ii) applies invertible, CNN-inspired transforms …

Practical Applications For Biomechanical Modeling Methods, Joseph M. Dranetz

Graduate Thesis and Dissertation post-2024

Models are tools humans use to understand and assess the world around them. The field of biomechanics is one well suited to modeling pursuits. Physiological systems are complex, and modeling may serve as an appropriate method in understanding them. Recently, technologies enabling the collection of biomechanical data have improved greatly and continue to expand. This dissertation serves as an anthology of various attempts to collect and interpret biomechanical data with modeling.

The first study: Electromyographic, ultrasound, and knee torque data was collected from both legs of an individual with a unilateral transtibial amputation. These data were used to generate a …

Integration Of System Dynamics And Agent-Based Simulation To Emulate Cyberattacks In An Iot-Based Smart Grid, Francisco Valdez

Graduate Thesis and Dissertation post-2024

The electric power grid is a cyber-physical system (CPS) that plays a fundamental role in modern society. With the integration of renewable energy sources and advanced communication technologies, Smart Grids (SGs) can enhance both the profitability and reliability of the electric power system. The communication network that interconnects numerous remotely distributed generators, devices, and controllers plays a vital role in grid control, and current trends favor the widespread adoption of Internet of Things (IoT) devices. However, this network is inherently vulnerable to cyberattacks. This dissertation presents a hybrid methodology to model and analyze the dynamic behavior of an electrical Smart …

Critical State-Based Study On Deformations Due To Construction Activities And Blast Densification, Jorge Enrique Orozco-Herrera

Graduate Thesis and Dissertation post-2024

The behavior of geo-structures and foundation systems in densely populated urban areas relies on the successful performance of the supporting soils when subjected to static (e.g., the weight of the structure or service loads) or dynamic (e.g., earthquake-induced ground motions, construction-induced vibrations, wind loads, or traffic) loading scenarios. Construction-related activities and ground improvement operations can also be responsible to alter the stress-strain-strength behavior of supporting soils by causing vibration-induced ground deformations, excessive vibrations, or mobilizing soil shear strength in relation to in situ or as-built conditions. Construction-related activities and ground improvement operations such as blast densification trigger complex dynamic input …

Bim-Based Machine Learning Surrogate Models For Energy And Carbon Prediction To Support Leed Certification Evaluation, Liliane Magnavaca De Paula

Graduate Thesis and Dissertation post-2024

This research developed and validated a Building Information Modeling (BIM)-based Machine Learning (ML) framework for predicting the energy and carbon performance of office buildings during early design stages. The study addresses the need for reproducible data-driven methods supporting sustainable design decisions with reduced simulations time. The proposed approach integrates Revit and Insight with statistical modeling in Weka, creating an automated, transparent, and regionally adaptable workflow for energy and carbon prediction from a BIM-generated data. A reduced-factorial Design of Experiments (DOE) guided the generation of 260 parametric Insight simulations, including base, generalization, and stress-test models distributed across six U.S. climate zones. …

Robust Low-Rank Tensor Discriminant Analysis With Optimal Scoring, Kyle Brinker

Graduate Thesis and Dissertation post-2024

Robust discriminant analysis with optimal scoring has been shown effective for classifying high-dimensional matrix data, particularly in the context of two-dimensional images. The proposed method presents an extension of the Multi-Projection Optimal Scoring Discriminant Analysis framework introduced by Huang \& Zhang (2020), incorporating low-rank Tucker decomposition and regularization techniques to address higher-dimensional cases. The enhanced method is designed to effectively handle tensor-structured data, which is prevalent in imaging applications. The model creates a sparse discriminant projection tensor B that captures class-specific features, such as ball-like patterns in image data and indicators of Alzheimer’s disease in Magnetic Resonance Imaging (MRI) scans. …

Optimizing Emissions And Sustainability Of Alternative Fuel Buses Using Machine Learning And Life-Cycle Modeling, Md Rezwan Hossain

Graduate Thesis and Dissertation post-2024

Public transportation is undergoing a critical transition as agencies seek to balance environmental responsibility, operational efficiency, and economic viability. Alternative fuel buses (AFBs), including electric, compressed natural gas (CNG), propane, and biodiesel, offer opportunities to reduce emissions and advance sustainability, yet their adoption raises complex trade-offs. High upfront costs, infrastructure constraints, range limitations, and variable real-world performance complicate decisions for fleet managers and policymakers. This dissertation addresses these challenges by integrating real-world operational data, life-cycle modeling, and machine learning within a multi-objective optimization framework to evaluate and optimize AFB deployment. Using detailed telematics and GPS datasets from Central Florida's transit …

Design Tool For Ammonia Cracker Hardware, Andrew Menendez

Graduate Thesis and Dissertation post-2024

Ammonia is a promising carbon-free fuel for commercial aviation and represents a viable pathway toward net-zero emissions. However, direct ammonia combustion is inefficient, creating the need for onboard cracking to generate hydrogen for improved combustion characteristics. One pathway for onboard cracking is to have the hardware live around the combustor liner where heat generated from the combustion process can be used to sustain the reaction. This study aims to develop a design tool for the ammonia cracking reactor hardware. A simplified, single-step surface reaction mechanism was implemented using ANSYS FLUENT and CHEMKIN PRO R1, demonstrating strong agreement with experimental data …

Advancing Drug Discovery With Structural And Representation Learning Of Biological Systems, Mehdi Yazdani-Jahromi

Graduate Thesis and Dissertation post-2024

The rapid emergence of global health crises, exemplified by the Coronavirus Disease 2019 (COVID-19) pandemic, underscores the profound limitations of conventional drug discovery methods, which are inherently protracted and resource-intensive. A robust, accelerated response framework demands the sophisticated deployment of Artificial Intelligence (AI) and Machine Learning (ML) across the entire therapeutic pipeline. We propose a unified approach centered on \textbf{Structural and Representation Learning} to capture the intricate topological and chemical nuances of biological systems, thereby transforming complex molecular and genomic data into effective vector embeddings suitable for deep learning, enhancing predictive power, and crucially, interpretability. This dissertation details advancements across …

Large Language Models And Networks: Edge Proposal, Synthetic Corpora, And Adaptive Node Generation, Nathan Gonzalez

Graduate Thesis and Dissertation post-2024

Natural Language Processing (NLP) and Artificial Intelligence (AI) have evolved from brittle rule-based engines through data-driven statistical models to today’s transformer architectures whose multi-head attention enables rich contextual reasoning. Against this backdrop, this dissertation unifies three complementary investigations that deepen our understanding of how large language models (LLMs) can reason over, generate, and strategically adapt language within networked settings. First, instruction-tuned LLMs are recast as latent-relationship detectors: by prompting models to hypothesize links between text-described entities, we recover edge sets that reconstruct social, thematic, and citation graphs with high precision, revealing how attention distributions encode topological cues. Recognizing the difficulty …

Performance Analysis Of A Turbofan Intergrated With An Entropy-Minimized Heat Exchanger For Ammonia-Powered Aviation, Lucas K. Cavalcante

Graduate Thesis and Dissertation post-2024

Ammonia has emerged as a promising aviation fuel due to its carbon-free emissions, well-established production methods, and transportation infrastructure. However, challenges with its slow chemical kinetics and low flame speed necessitate the partial cracking of Ammonia to introduce hydrogen as a combustion promoter. This study addresses these challenges by designing and optimizing a tube bank heat exchanger to transfer heat from the Cooled Cooling Air (CCA) of the High-Pressure Compressor (HPC) to the Ammonia stream, facilitating the necessary cracking. Preliminary heat transfer calculations indicate insufficient heat in the CCA to achieve cracking temperatures, prompting an alternative approach: splitting the Ammonia …

High-Efficiency Dual Active Bridge Converter With Stacked Secondary Phase For Next-Generation Ai Data Center Power Delivery, Anirudh Ashok Pise

Graduate Thesis and Dissertation post-2024

The rapid electrification of hyperscale AI data centers is accelerating a shift from legacy 48 V distribution ladders to ±400 V high-voltage DC backbones, concentrating residual loss and dynamic stress on a single isolated bidirectional interface. This work presents a high-density Dual Active Bridge with Stacked Secondary Phasing (DAB-SSP) architecture as a scalable GaN-based solution for 48 V–800 V rack-level power conversion. By stacking 400 V secondaries, the topology leverages 650 V GaN devices while satisfying 800 V system requirements, reducing clearance and creepage distances, minimizing magnetic path lengths, and embedding leakage inductance necessary for wide-range zero-voltage switching.

A rigorous …

Autoignition Delay Times For Reformate Gas Mixtures From Methane Gas Engines, Matthew Fraze

Graduate Thesis and Dissertation post-2024

Methane slip is a prominent issue in natural gas reciprocating engines that are used in transportation and marine applications. The incomplete combustion that results in methane slip can be resolved with the introduction of hydrogen within the combustion mixture to improve methane oxidation and further enable combustion within the engine crevices where methane has previously remained unreacted. Steam Methane Reforming (SMR) is a common method used to produce hydrogen and can be used to design an onboard device to reduce methane slip from reciprocating engines. The development of this reformer device requires the validation of high-fidelity chemical kinetic mechanisms at …

Integrated Performance-Based Framework For Evaluating Alternative Containment Systems In Subtitle D Landfills Managing Coal Combustion Products, Poyu Zhang

Graduate Thesis and Dissertation post-2024

Designing landfill containment systems that remain effective over decades to centuries poses significant challenges in geoenvironmental engineering, especially for landfills managing coal combustion products (CCPs) with complex hydraulic and chemical behaviors. This dissertation aims to develop an integrated, performance-based framework for evaluating landfill barrier systems by combining numerical modeling, experimental leaching tests, and machine learning prediction. The first component assesses the equivalency of the Florida double liner system relative to the Subtitle D composite liner mandated by the U.S. Environmental Protection Agency (US EPA). Using field leakage observations and COMSOL Multiphysics-based numerical simulations, results demonstrate that the Florida system, when …

Characterization Of Turbulent Flames In Confined Combustors, Max Fortin

Graduate Thesis and Dissertation post-2024

As industry transitions to a net-zero carbon future, turbulent premixed combustion will remain an integral process for power generating gas turbines and are also desired for aviation engines due to their ability to minimize pollutant emissions. However, accurately predicting the behavior of a turbulent reacting flow field remains a challenge. To better understand the dynamics of premixed reacting flows, this study experimentally investigates the evolution of turbulence in a high-speed bluff-body combustor. The combustor operates across a range of equivalence ratios from 0.7-1 to quantify the role of heat release and flame scales on the evolution of turbulence as the …

Aluminum Alloys For Laser Powder Bed Fusion Additive Manufacturing And Process Optimization By Machine Learning, Kevin Graydon

Graduate Thesis and Dissertation post-2024

Laser powder bed fusion (LPBF) additive manufacturing is a promising manufacturing technology enabling enhanced design freedom through layer-by-layer production. However, traditional, wrought aluminum (Al) alloys suffer from solidification cracking during LPBF processing and the initial printer parameter optimization process required for every novel or untested material is time and resource intensive. There exists a need to formulate Al alloys for LPBF and a method to reduce the resources consumed during initial printer parameter optimization studies. Al-9.5Ce-xMo (x = 0.2, 0.6, 1.0 wt. %) alloys have been designed specifically for LPBF utilizing the CALPHAD approach. Additionally, a neural network model was …

The Sociological Engagement In John Coltrane's A Love Supreme: Examining The Impacts Of Race, Music, And Culture In Video-Based Learning Amongst College Students, Kinyel K. Ragland Sr.

Graduate Thesis and Dissertation post-2024

This project consists primarily of the interest in Video Based Learning (VBL) and understanding the impacts of a video based on the connections between John Coltrane’s song Acknowledgement on the Jazz suite A Love Supreme to the Civil Rights movement and systemic racism. Research confirms that VBL has an impact on student learning, yet this project finds that because of the content of the video, it fits into scholarship where there are gaps. The methodological approach, which was qualitative, found that students were overall enlightened, entertained, and were interested in learning more. Other findings include suggestions and recommendations for future …

A Mathematical Modeling Approach To Investigate The Impacts Of Post-Infection Mortality And Partial Immunity On Disease Endemicity, Brendan M. Shrader

Honors Undergraduate Theses

A number of infectious diseases cause post-infection conditions or complications, such as COVID- 19, Q fever, and Polio. These conditions result in recovered individuals having a higher mortality rate than susceptibles, and this can impact disease dynamics. An existing mass-action model in the literature that incorporated post-infection mortality was shown to have limit cycles, or persistent oscillations, in the infected population. To better understand what causes these limit cycles, we develop and analyze a new epidemiological model with standard incidence. We show standard results, including the existence, uniqueness, and stability of the disease-free and endemic equilibria, and we rule out …

Development Of Cerium Oxide Based Polymer Composites With Enhanced Cytocompatability For Biomedical Applications, Roshna Cherugail

Honors Undergraduate Theses

This thesis presents the synthesis and characterization of cerium oxide nanoparticles (CNPs), and silver-doped cerium oxide nanoparticles (AgCNPs) loaded in alginate beads that were designed to be applied in biomedical settings. Cerium oxide was chosen for its antioxidant and anti-inflammatory capabilities, and silver oxide was selected to enhance antimicrobial functionality, both of which are pivotal in expedited wound closure and promoting cellular proliferation. Through the use of an advance electrospray encapsulation apparatus, alginate-based polymer beads were created by incorporating either CNPs or AgCNPs into the matrix. These beads were later characterized using a range of microscopic and FTIR analyses, in …

Towards Supporting Undergraduate Students To Become Lifelong Learners: A Multimethod, Multimodal, And Multigranular Analysis Of Motivation And Self-Regulated Learning In Context, Sierra Outerbridge

Graduate Thesis and Dissertation post-2024

This publication-based dissertation includes three manuscripts with distinct statistical methods to investigate self-reported motivation, self-reported self-regulated learning (SRL), and enacted SRL processes in undergraduate student contexts towards understanding how students learn how they learn.

The first manuscript focused on 1248 undergraduate statistics students, utilized self-reported motivation, and interpreted logfile data of time spent within an online textbook through the lens of SRL using hierarchical cluster analysis followed by k-means cluster analysis to identify four distinct motivation clusters. Results from a repeated measures ANOVA suggest that students did not spend time differently within the textbook, whereas there were differences between motivation …

Exploring The Effects Of Looping On First And Second Grade English Language Learners (Ells) Students' Reading And Science Achievement, Kiera A. Palmer

Honors Undergraduate Theses

The purpose of this study is to compare the reading and science achievement of first grade ELL students who looped with their teacher to second grade with the reading and science achievement of first grade ELL students who had a different teacher in second grade. Looping is an educational practice that allows teachers to stay with their class for two or more years, it was hypothesized that it would have a positive effect on ELL students’ reading and science achievement. Using a comparative methodology, the study tracked the end-of-year scores of the ELL students in their Florida Assessment of Student …

Creating A Criteria Set To Evaluate The Use Of Cai Resources In K-6 Language Arts Education, Matthew T. Bates

Honors Undergraduate Theses

The purpose of this creative project was to research adequate educational practices regarding implementing technology and specifically CAI (Computer-Assisted Instruction) technology in the context of elementary education. This information was compiled into distinct categories based on research articles and policy statements. Then, the implications of each category were explored within the classroom. From this review of research, I created a criteria set for elementary educators to follow to evaluate CAI in the framework of their own educational methods and classroom. This thesis presents an address on the issue of student engagement in elementary literacy classrooms by assisting students in actively …

Rapid Inference Of Atmospheric Feature Parameters From Light Curves Using Bayesian Neural Networks, Eugenio A. Diaz

Honors Undergraduate Theses

Mapping atmospheres using rotationally modulated light curves offers insights into cloud structures and dynamics. Current retrieval methods, primarily based on Markov Chain Monte Carlo (MCMC) techniques like Aeolus, can infer atmospheric features but are computationally prohibitive for large datasets. This project proposes a neural network (NN) framework for the rapid, variational inference of atmospheric structure from light curves, particularly those of brown dwarfs. The primary approach focuses on training a Bayesian NN (BNN) to perform regression, predicting the spot parameters that describe the object's surface brightness map. Given the scarcity of suitable observational training data, the BNN is trained on …

0th Order Solutions Of The Wavefunctions For The Quantum Elliptical Box And Microstrip Antenna, Nishtha Tikalal

Honors Undergraduate Theses

For a quantum particle confined to a two-dimensional elliptical box or electromagnetic wave in a microstrip antenna, geometrical and boundary condition interplay result in a spectrum of spatial patterns. Due to the asymmetrical nature of the ellipse, we are faced with continuous symmetry reductions, leaving both degenerate and nondegenerate solutions. Here, we present a complete derivation of an analytical solution and visualizations of the fundamental wavefunctions for both Dirichlet and Neumann boundary conditions respectively corresponding to the quantum elliptical box and the elliptical microstrip antenna.

We demonstrate that the eigenmodes, governed by eccentricity, directly correspond to the modal field distributions …

Does Money Matter? An Analysis Between Per-Student Funding And Its Link To Student Achievement In Florida, Chloe Zwetschkenbaum

Honors Undergraduate Theses

This study examined the relationship between per-student funding and student achievement within four counties in the state of Florida (Clay County, Duval County, Flagler County, and St. Johns County) and whether higher per-student funding resulted in higher student achievement. Florida recently changed from the usage of the Common Core Standards to the Florida Benchmarks for Excellent Student Thinking (B.E.S.T.) and from the Florida State Assessment (FSA) to the Florida Assessment of Student Thinking (F.A.S.T.) test in 2022 (Sabina, Hartikka, and Viola, 2023). This research focused funding on the results of the F.A.S.T. test and the per-student funding of each district …

Quantifying The Performance Of The Sparta Toolkit For Use In Planetary Regolith Characterization Missions, Abigail S. Glover

Honors Undergraduate Theses

This research investigates the use of the Soil Properties Assessment, Resistance, and Thermal Analysis (SPARTA) Cone Penetration Tester (CPT) to quantify bulk density in lunar regolith simulant LHS-1E. Twenty-five penetration tests were conducted across five density profiles to derive slope parameters (G), which represent the rate of increase in resistance with depth. Results showed a consistent, nonlinear relationship between G and bulk density, validating the use of G slope as a diagnostic parameter and supporting the primary hypothesis that SPARTA CPT measurements vary meaningfully with density. Compared to prior work by Lucas et al. (2024), G values from SPARTA were …