Digital Commons Network^™

Criminal Defenses In The Age Of Ai: An Examination Of How Technological Advancements Are Challenging Traditional Duress And Mistake Of Fact Defenses, Lauren Lepage

Honors Undergraduate Theses

AI has rapidly evolved into a defining force of modern life, transforming industries by automating tasks, streamlining workflows, and enhancing everyday experiences. However, the same advancements, especially in deepfakes, now enable highly convincing manipulation of audio, images, and video, blurring the line between truth and fabrication. As these technologies grow more accessible, they not only reshape digital interactions but also challenge core principles of criminal law and culpability. This research examines the rapid advancement of Artificial Intelligence (AI) and deepfake technology and analyzes the challenges they pose to traditional criminal defenses. Employing a doctrinal legal research approach, it evaluates statutory …

Florida Statewide Coastal Restoration Guide, Melinda J. Donnelly, Matthew Martin, Christen Fleming, Kelly Kibler, Linda Walters, Patrick Shearer, Lauren Jennison, Erika Lin, George Zaragoza

Faculty Scholarship and Creative Works

The Statewide Coastal Restoration Guide (SCRG) is a comprehensive planning resource developed through a collaboration between Florida Department of Environmental Protection (FDEP), University of Central Florida (UCF), and Resource Environmental Solutions (RES) to strengthen and unify shoreline restoration efforts across Florida. With over 4,500 miles of estuarine shoreline, Florida’s coasts are vital to the state’s ecological health, economic prosperity, and community resilience. However, they face increasing threats from sea level rise, stronger storms, erosion, habitat degradation, and development. The SCRG responds to these challenges by providing science-based, non-regulatory guidance for implementing resilient, nature-based restoration strategies that protect both ecosystems and …

123 Studies Use In The Review, Abdul-Akeem Sadiq

Faculty Scholarship and Creative Works

No abstract provided.

Reimagining Main Street: Themed Experience Design As A Tool For Small Town Revitalization, Carrie L. Schweiger

Graduate Thesis and Dissertation post-2024

The idea of the American main street is deeply embedded in popular culture, often seen through layers of nostalgia that can obscure the real-world conditions of today. While an idealized nostalgia may benefit some towns, decades of change have left many struggling to fit the mold. This thesis explores how core principles of themed experience design can be integrated into existing American main streets, reimagining the way residents interact and identify with these spaces.

Examining historical upheavals alongside decades of media portrayals brings insight into the different stories embedded in America’s small towns, many of which remain focused on the …

Predicting Superconducting Critical Temperature From Composition-Derived Features: A Transparent Linear And Regularized Regression Study, Md Ahiduzzaman

Data Science and Data Mining

We study prediction of superconducting critical temperature (Tc) from 81 composition-derived descriptors across 21,263 materials. To keep the analysis transparent and repro- ducible, we focus on linear models: Ordinary Least Squares (OLS), Ridge, Lasso, and Elastic Net (ENet). All models share a single evaluation protocol (5-fold cross-validation with standardized inputs) and are compared on RMSE, MAE, and R2. On this feature set, OLS attains the best cross-validated performance (RMSE = 17.6 K, MAE = 13.3 K , R2 = 0.735), with Lasso/ENet essentially tied next (RMSE ≈ 17.7 K , R2 ≈ 0.734); Ridge underperforms (RMSE = 18.9 K , …

Comparative Analysis Of Estimation Techniques On Human Performance In Seek-And-Place Tasking, Adam J. Wehr

Graduate Thesis and Dissertation post-2024

Accurate parameter estimation is fundamental to statistical modeling, shaping the validity of inference, prediction, and decision-making. Although Maximum Likelihood Estimation (MLE) and Bayesian methods are well established theoretically, their performance relative to alternative estimators in small-sample, skewed-data contexts remains less clear. This thesis addresses this gap through a systematic evaluation of estimation techniques applied to human response time data from a controlled seek-and-place jigsaw puzzle task, where distributions are characteristically right-skewed.

A performance-modified lognormal model was developed to capture the relationship between task complexity and response times. Four estimation approaches were investigated: MLE, Method of Moments (MoM), Bayesian estimation under …

Fast Differentiable Projection Layers Onto High-Dimensional Polytopes For Large-Scale Predictive Modeling, Camilo Gomez

Graduate Thesis and Dissertation post-2024

Recent trends in statistical machine learning have revealed the power of integrating optimization procedures as first-class components within end-to-end large-scale predictive systems. These structured computations—often formulated as projections onto geometric objects like polytopes—enable models to inject domain-specific inductive biases and enforce desirable properties in the learned representations useful in downstream classification or regression tasks. This dissertation explores the role of such projections in enhancing learning performance and generalization, particularly in the context of predictive modeling with data intensive systems.

Motivated by the limitations of traditional surrogate loss functions such as logistic loss for classification or cross-entropy for multiclass problems, this …

A Unified Thermodynamic Framework For Regime Discovery, Entropy-Aware Optimization, And Emergent Leadership In Flocking Systems, Victor Nkwocha

Graduate Thesis and Dissertation post-2024

This thesis presents a unified framework for modeling, optimizing, and analyzing collective behavior in flocking systems through a thermodynamic and statistical lens. In the first study, we employ entropy-regularized Gaussian Mixture Models (GMM) to identify distinct thermodynamic regimes—ordered, transitional, and disordered—based on the energy and entropy profiles of simulated agent-based flocks. The second study introduces the Organic Adaptive Flocking Algorithm (OAFA), a biologically inspired, entropy-aware extension of the Boids model. OAFA dynamically adjusts rule weights based on local entropy signals and is optimized via a multi-objective NSGAII framework to balance cohesion, separation, energy efficiency, and disorder. Results show that entropy …

Sparse Low-Rank Tensor Logistic Regression With Applications In Neuroimaging, Michael Hurtado

Graduate Thesis and Dissertation post-2024

Discriminant analysis techniques, while extensively studied for traditional datasets, have rarely been adapted to address the complexities of high-dimensional tensor data. Recent advances in tensor decomposition, as reviewed by Burch et al. (2025), highlight methods such as CP, Tucker, HOSVD, and t-SVD, which offer robust frameworks for handling multi-dimensional biomedical data, including neuroimaging. In this paper, we propose a novel approach that integrates low-rank regularization techniques with tensor structures to tackle high-dimensional matrix and tensor data. Building on the Multi-Projection Optimal Scoring Discriminant Analysis (ROSDA) method by Huang & Zhang (2020), which employs multi-directional projection pursuit for robust classification, our …

Clustering And Classification Methods For Forensic Science Applications, Slun Booppasiri

Graduate Thesis and Dissertation post-2024

Finite mixture models have been widely used to cluster data consisting of homogeneous subpopulations. In forensic palynology, pollen is used as a proxy to link individuals or items to a crime scene. Mixtures of pollen data-including willow and mustard and blank samples-were analyzed using flow cytometry. Willow and mustard clusters tend to have multivariate normal distributions, while a background cluster has multivariate non-normal distribution. We propose a finite mixture model capable of handling the mixtures of pollen in terms of univariate and multivariate distribution. The proposed methods are applied in simulated and mixture of pollen datasets.

Finite mixture models typically …

How Fiscal And Labor Policies Influence Hospitality Entrepreneurship: A Panel Data Analysis, Mehmet Altin

Journal of Hospitality Financial Management

This study investigates how state-level fiscal and labor policies influence the creation of hospitality firms in the United States from 2002 to 2022. Using a panel dataset and fixed- effects models with Driscoll-Kraay standard errors, we analyze the effects of corporate, sales, property, and income taxes, along with minimum wage laws and educational attain- ment. We separate the results among accommodation and food service subsectors to iden- tify specific policy sensitivities. Our findings disclose that tax and labor policy impacts are highly sector-specific and context-dependent. Especially, minimum wage increases are pos- itively associated with firm formation in lower-income, lower-education states, …

Damping Modulation Of Dampened Kapton Surfaces, Sebastian Esteban

Honors Undergraduate Theses

When droplets are vibrated or disturbed, they can exhibit a complex sloshing motion, an understudied behavior in drop physics. Droplet sloshing involves a complex combination of transverse and longitudinal motion that changes the droplet's effective weight on the surface the droplet is on. Our current understanding stems from preliminary work focusing on a cantilever beam of fixed thickness and variable viscosity of the liquid being sloshed. This investigation will focus on how variable cantilever thickness and constant viscosity for a liquid being sloshed affects the beam's deflection under consistent vibration. It will also investigate how the natural frequency of a …

Integrated Compliant Structure For A Hand Exoskeleton, Tristan R. Koopman

Honors Undergraduate Theses

This thesis presents the design and prototyping of a wearable hand exoskeleton that integrates a flexible structural framework to assist with hand movement while maintaining comfort and anatomical conformity. The goal was to create a device that supports tendon-driven actuation through a compliant structure, combining elements of rigidity and flexibility to match the natural geometry and motion of the human hand. Traditional hand exoskeletons often trade off motion for structure or vice versa. This project aims to bridge that gap with a hybrid compliant design that balances flexibility and support. The design process followed an iterative approach involving rapid prototyping …

Fabricating Silver-Ceria Polymer Nanocomposite Scaffolds For Biomedical Therapeutic Applications, Shreya S. Pawar

Honors Undergraduate Theses

Improper healing of bone fractures and limited regeneration of bone following bone tumor resection remain a prevalent complication worldwide. Long-term effects of this include joint instability, limited movement, and arthritis. Bone infections (osteomyelitis), reactive oxygen species (ROS) generation via excessive inflammation, and underlying conditions such as osteoporosis can contribute to suboptimal bone tissue regeneration. ROS accumulation stimulates osteoblast apoptosis, while promoting osteoclast differentiation. These processes inhibit mineralization and osteogenesis. Conventional therapeutics involve the utilization of drugs and bone grafts. However, these approaches pose limitations and can result in subsequent complications. Microbial infections, ROS accumulation, and excessive inflammations are factors that …

High-Performance Computational Kernels For Algorithm-System Co-Design In Machine Learning: Enabling Efficient Gcn Training And Llm Inference Serving., Shakya D. Jayakody Arachchige

Graduate Thesis and Dissertation post-2024

The rapid advancement of machine learning, from Graph Convolutional Networks (GCNs) to transformer-based Large Language Models (LLMs), continues to expose fundamental limitations in memory efficiency, scalability, and system reliability. GCNs are critical for domains such as biomedical modeling, social networks, and recommendation systems, yet their reliance on sparse general matrix–matrix multiplication (SpGEMM) makes them highly sensitive to GPU memory constraints and irregular access patterns. As graph data scales, out-of-core computation becomes inevitable, but existing systems are hindered by I/O bottlenecks and underutilized GPU resources. Our contribution with AIRES demonstrates how algorithm–system co-design can alleviate these challenges: by introducing block-wise data …

Development Of Generalizable Data-Driven Traffic State Prediction Solutions: A Comprehensive Approach, Md Mobasshir Rashid

Graduate Thesis and Dissertation post-2024

Increased urbanization and population growth lead to more traffic in the transportation system, causing severe congestion. Particularly during disruptive events such as hurricanes or traffic incidents, the traffic flow in the network worsens significantly. As a result, there is a need for data-driven traffic prediction models to reduce congestion in real-time, and the prediction model should be generalizable to be applicable across different dynamic scenarios. Additionally, a robust and adaptable traffic prediction model can help traffic managers to take proactive actions to optimize traffic flow. However, the majority of data-driven traffic prediction models suffer from limited applicability as they are …

Novel Nanomaterial-Based Platforms For Bio-Electrochemical Sensing And Photocatalytic Treatment Of Contaminants Of Emerging Concern In Water, Jonghyun Baik

Graduate Thesis and Dissertation post-2024

This dissertation presents the development of novel nanomaterial-based platforms for bio-electrochemical sensing and photocatalytic treatment of contaminants of emerging concern (CECs) in water, including heavy metals, polycyclic aromatic hydrocarbons (PAHs), per- and polyfluoroalkyl substances (PFAS), and microcystin toxins. Conventional detection and remediation methods are often costly, time-consuming, and impractical for field use. To overcome these limitations, in this dissertation, five distinct platforms were designed, developed, and evaluated under various water conditions.

First, a microbial fuel cell (MFC)-based biosensor was developed for detecting heavy metals (Cu²⁺ and Hg²⁺) and PAHs (benzene and xylene). The system exhibited rapid, linear …

Assessment Of The Safety Culture In Petrochemical Industries In Saudi Arabia: A Cross-Sectional Study, Ahmed Mohammed Alqarfi

Graduate Thesis and Dissertation post-2024

Given the inherently hazardous nature of petrochemical operations, an effective safety culture is critical. Following PRISMA 2020 guidelines, 29 peer-reviewed articles published in open access between 2014 and 2024 were selected to evaluate the status of safety culture dimensions employed in the petrochemical sector. This cross-sectional study assessed safety culture in the Saudi Arabian petrochemical industry and examined the relationships among safety culture dimensions, safety motivation (SM), and safety performance. Safety performance was operationalized as personal error behavior (PEB) and attitudes toward violations (ATV), with SM modeled as a mediating factor. After obtaining IRB approval, a total of 482 employees …

Quantifying Surrogate Safety Measures And Traffic Delays At Mid-Block Pedestrian Crossings Using Video-Based Data Analytics, Md Jamil Ahsan

Graduate Thesis and Dissertation post-2024

This study presents a comprehensive evaluation of midblock pedestrian crossings in terms of safety and traffic efficiency, with a particular focus on the newly implemented Mid-Block Pedestrian Signal (MPS) systems. Extensive CCTV video data were collected across Florida and processed using advanced computer vision techniques, specifically the RT-DETR model for object detection and the ByteTrack algorithm for object tracking, to analyze vehicle-pedestrian interactions in detail. Since there is limited post-implementation crash data available for all locations, Surrogate Safety Measures (SSMs) were employed to assess safety outcomes. Conflict Modification Factors (CoMFs) were estimated using Cross-Sectional (CS), Comparison Group (CG), and Empirical …

Development Of A Data-Driven Decision Support System For Intelligent Traffic Management At Intersections, B M Tazbiul Hassan Anik

Graduate Thesis and Dissertation post-2024

Intersections are complex traffic environments where frequent vehicle and pedestrian interactions can lead to safety- and mobility-critical (SMC) conditions. Identifying these conditions promptly is crucial, as delays may result in missed interventions, thereby heightening crash risk, and diminishing operational efficiency. This dissertation introduces a data-driven, real-time decision support framework for the identification and mitigation of SMC conditions using High-Resolution Traffic Controller Data (HTCD) collected via Automated Traffic Signal Performance Measures (ATSPM) system and Connected Vehicle (CV) data from Signal Analytics. First, an end-to-end analytical pipeline was developed to transform HTCD into actionable safety and mobility measures. A Bayesian beta-binomial framework, …

Determining Essential Attributes For Experience And Satisfaction In The Customer 4.0 Era: A Kano Model Approach, Cintia Z. Buffon

Graduate Thesis and Dissertation post-2024

The world is constantly changing, with rapid technological advancements and increased digital connectivity shaping daily activities. In this evolving landscape, customers have transformed into what is known as Customer 4.0—a new generation of consumers who expect high levels of personalization, digital engagement, and greater transparency from organizations. These expectations extend to higher education, where students demand more customized learning experiences, interactive content, and digital accessibility. This research investigates engineering students' preferences regarding educational attributes aligned with Customer 4.0 characteristics using the Kano model. While the Kano model has been widely applied across industries, its use in higher education remains limited. …

Investigation Of Combustion Properties Of Renewable Biofuel Blends Using A Hot Surface Ignition Assistant Device, Matthew Voigt

Graduate Thesis and Dissertation post-2024

With global warming, fuel supply, rising fuel prices, and energy security becoming major concerns for countries around the globe, many countries have been researching methods to reduce carbon emissions. One option being considered is using Bio-derived fuels as a possible alternative to modern jet fuels due to their ability to produce less emissions. However, while they do produce less emissions, they are also characterized by their low cetane numbers resulting in low reactivity requiring more energy to ignite, lower total heat release values, and longer ignition delays leading to engine problems such as knocking and power loss. Ignition assistant devices …

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 …

Shock Tube Investigation And Chemical Kinetic Modeling Of Green Propellants For Space Missions, Marley Albright

Graduate Thesis and Dissertation post-2024

Hydrazine thrusters have been used for decades to land spacecraft on other planets. While its use is common, handling hydrazine is difficult due to its toxicity; this poses a risk to humans during testing and loading the propellant onto a spacecraft. Occupational Safety and Health Administration has limited human exposure to 1 part per million (ppm) of hydrazine per eight-hour workday. Green propellants are promising alternatives because they have lower toxicity but do not sacrifice performance. Green propellant technology has been demonstrated in space and future missions are planned, such as NASA’s Green-Propulson Dual-Mode technology demonstration. At the University of …

Authorship Attribution Of Ai-Generated Codes, Soohyeon Choi

Graduate Thesis and Dissertation post-2024

The field of code authorship attribution focuses on identifying the author(s) of source code written in a specific programming language. Various methods, including manual crafting, automated crafting, and deep learning-generated features, have been developed for this task. These techniques leverage the unique stylistic patterns inherent in code, such as structure, comments, variable names, and function names, to attribute authorship accurately. This field has practical applications in software forensics, cybersecurity, and code plagiarism detection, enabling investigations into issues like piracy, intellectual property violations, and malware attribution. In educational settings, it helps detect plagiarism in programming assignments. However, traditional methods face challenges …

Structure-Property Relationship For Silver-Incorporated Cerium Oxide Nanoparticles, Shanza Nusrat

Graduate Thesis and Dissertation post-2024

Cerium oxide nanoparticles are known for their applications across several domains due to their biocompatibility, high oxygen storage capacity, redox behavior, and stability. However, their intrinsic electrical conductivity is relatively low, which can limit their performance in energy storage applications. Doping cerium oxide with transition metals has proved to enhance conductive properties and, hence, their performance in related applications. This research investigates the doping of cerium oxide with silver (Ag) and its correlation with the properties of the material. Silver-doped cerium oxide nanoparticles were synthesized by wet-chemical synthesis at room temperature by a facile procedure. Cerium oxide was doped with …

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 …

Assessing Driving Performance And Safety In Managed Lanes: A Human Factors Study On The Effects Of Buffer Separation Treatments With Delineators, Sharfuddin Ahmed

Graduate Thesis and Dissertation post-2024

Buffer separation with delineators is one of the commonly used separation treatments across US highways to distinguish managed lanes (ML) from general purpose lanes (GPLs). As MLs continue to be integrated into US highway system for improving traffic flow and reducing congestion, this separation method has become more popular due to its flexibility and cost efficiency over more robust physical separations. While past studies have explored the effectiveness and safety of buffer separations with delineators compared to other treatments, none have examined how specific changes within the buffer design—like separation width and delineator height—impact driver behavior. It is particularly important …

Evaluating Pedestrian Behavior In Response To Innovative Detection Messages And Wait-Time Indicators At Signalized Intersections: A Virtual Reality Study, Nada K. Ahmed

Graduate Thesis and Dissertation post-2024

Pedestrian safety at signalized intersections remains a growing concern in urban environments, necessitating effective communication between pedestrians and traffic control devices. Traditional approaches often prove inadequate in addressing these challenges. This study utilized virtual reality simulation to examine how innovative detection systems and wait-time indicators affect pedestrian behavior under varying environmental conditions. Ninety participants evenly distributed across three age groups experienced 18 crossing scenarios that differed by detection type, wait indication, crossing time, crossing distance, visibility, traffic density, and time of day. Key behavioral measures including start-up lost time, crossing speed, and total crossing duration were analyzed using linear mixed-effects …

Development Of A Laser Spectroscopic Device For Measurements Of Temperature And Speciation In Detonation Environments, Andrew M. Derusha

Graduate Thesis and Dissertation post-2024

Characterizing novel detonation-based combustion systems is critical to assessing new designs and improving the understanding of their unique operations. Due to the harsh nature of a detonation environment, industry-standard sensing and diagnostic tools can fail to provide adequate methods for in-situ quantitative measurements of key thermodynamic properties. Diagnostic equipment must adapt to meet the needs of new combustion systems. Laser absorption spectroscopy (LAS) is a technique commonly utilized in combustion research to provide such measurements in laboratory settings due to its precision, minimally invasive properties, and high data acquisition rates. To prepare such a sensor for use in a challenging …