Predicting Superconducting Critical Temperature Using Regression Analysis, Roland Fiagbe

Data Science and Data Mining

This project estimates a regression model to predict the superconducting critical temperature based on variables extracted from the superconductor’s chemical formula. The regression model along with the stepwise variable selection gives a reasonable and good predictive model with a lower prediction error (MSE). Variables extracted based on atomic radius, valence, atomic mass and thermal conductivity appeared to have the most contribution to the predictive model.

Modeling Health Insurance Premium Using Bayesian Hierarchical Models, Bennedict Kongyir, Emil Agbemade

Data Science and Data Mining

Insurance pricing requires pragmatism and creativity due to the unpredictable nature of risk [3]. This paper explores Bayesian hierarchical models to model health insurance premiums using individual and group predictors like demographics, health status, and geography. Data from Kaggle on health insurance policyholders was utilized, with prior distributions enhanc­ing model interpretability and credibility. Bayesian models improve predictive accuracy and provide valuable insights for actuaries and policymakers, highlighting the signifcant impact of factors such as age and BMI on premium pricing.

Predicting Telecommunication Customer Attrition Using The Hopfeld Neural Network Model., Benedict Kongyir, Emil Agbemade, Kelvin Njuki

Data Science and Data Mining

Customer churn prediction has become one of the crucial steps for customer retention. Telecommunication companies rely on loyal customers to make their proft. It is often very easy for customers to switch from one service provider to the other. To prevent or reduce the rate of customer attrition, there needs to be a model that can identify customers who are at risk of churning in the future in advance. Previous literature has shown that predictive models are efective in predicting customer churn. In this work, four tentative machine-learning models are built using data obtained from Kaggle on telecommunication customer attrition …

On Vulnerabilities Of Building Automation Systems, Michael Cash

Graduate Thesis and Dissertation 2023-2024

Building automation systems (BAS) have become more commonplace in personal and commercial environments in recent years. They provide many functions for comfort and ease of use, from automating room temperature and shading, to monitoring equipment data and status. Even though their convenience is beneficial, their security has become an increased concerned in recent years. This research shows an extensive study on building automation systems and identifies vulnerabilities in some of the most common building communication protocols, BACnet and KNX. First, we explore the BACnet protocol, exploring its Standard BACnet objects and properties. An automation tool is designed and implemented to …

Developing A Course Enrollment Simulation Model To Improve College Graduation Outcomes, Rachel Straney

Graduate Thesis and Dissertation 2023-2024

The process of enrolling and completing the courses needed to earn an undergraduate degree involves complex interactions between individual students and institutional policies and procedures, especially because student and institutional priorities do not always align. Traditional social and behavioral statistical methods are ineffective for modeling these interactions. Simulation and algorithm-based modeling approaches have been underutilized in higher education, but their adaptability can accommodate the complexity of the degree attainment process. The purpose of this research was to design, develop, validate, and apply a multi-method Course Enrollment Simulation Model (CESM), which mirrored the process of college students enrolling in courses required …

Efficient Processing Of Convolutional Neural Networks On The Edge: A Hybrid Approach Using Hardware Acceleration And Dual-Teacher Compression, Azzam Alhussain

Graduate Thesis and Dissertation 2023-2024

This dissertation addresses the challenge of accelerating Convolutional Neural Networks (CNNs) for edge computing in computer vision applications by developing specialized hardware solutions that maintain high accuracy and perform real-time inference. Driven by open-source hardware design frameworks such as FINN and HLS4ML, this research focuses on hardware acceleration, model compression, and efficient implementation of CNN algorithms on AMD SoC-FPGAs using High-Level Synthesis (HLS) to optimize resource utilization and improve the throughput/watt of FPGA-based AI accelerators compared to traditional fixed-logic chips, such as CPUs, GPUs, and other edge accelerators. The dissertation introduces a novel CNN compression technique, "Two-Teachers Net," which utilizes …

Privacy And Security Of The Windows Registry, Edward L. Amoruso

Graduate Thesis and Dissertation 2023-2024

The Windows registry serves as a valuable resource for both digital forensics experts and security researchers. This information is invaluable for reconstructing a user's activity timeline, aiding forensic investigations, and revealing other sensitive information. Furthermore, this data abundance in the Windows registry can be effortlessly tapped into and compiled to form a comprehensive digital profile of the user. Within this dissertation, we've developed specialized applications to streamline the retrieval and presentation of user activities, culminating in the creation of their digital profile. The first application, named "SeeShells," using the Windows registry shellbags, offers investigators an accessible tool for scrutinizing and …

Industrial Safety: How Complacency At Industrial Facilities Has Evolved As A Result Of Widespread Corporate Leadership Induced Reductions In Force Of Essential Critical Infrastructure Workers, Christina Kniffin-Downs

Graduate Thesis and Dissertation 2023-2024

With the renewal of interest in nuclear energy as a green energy source, battery plant manufacturing for electric vehicles, and semiconductor fabrication plant construction, it is necessary to address the evolution of complacency as it relates to industrial facility leadership and the widespread reduction in force of essential critical infrastructure workers. As a skilled craft person in the piping trades, with almost two decades of experience in mechanical construction, ten of those years as a nuclear worker, and as a traveling pipefitter working at chemical, refinery, and gasification plants, I am intimately aware of the behaviors, practices, and procedures inherent …

A Case Study Examining The Implementation Of Multi-Tiered System Of Supports During Mathematics Intervention In Grades 3-5, Sarah Lumpkin

Graduate Thesis and Dissertation 2023-2024

ABSTRACT

This case study examined how Multi-Tiered System of Supports were implemented in mathematics at an elementary school, the factors that influenced teachers’ instructional choices, and how school leadership impacted implementation. Participants consisted of four elementary school teachers and four members of the school’s leadership team. The study focused specifically on mathematics teachers in grades 3-5. These three research questions guided the study: (1) How do mathematics teachers implement MTSS in grades 3-5? (2) What influences the teachers’ choices during MTSS implementation? and (3) How does school leadership impact the implementation of MTSS in mathematics intervention? A triangulation of data …

Lobbying As A Means For Expanding The Communication Instructional Base In Higher Education Iii, Craig Newburger, Patricia L. Donat, Sherwyn P. Morreale

Journal of the Association for Communication Administration

Based on several national mandates, this essay examines the support for and importance of active advocacy among our discipline members in framing the conversation about oral communication proficiency, leading instructional design, and assessing student learning on our campuses. Recommended action involves the development and implementation of a coordinated strategy for engaging both institutional accreditors and those charged with the development and modification of individual campus general education requirements regarding the importance of communication scholars and instructors as principal designers of learning goals, subsequent learning activities, and the corresponding assessment of oral communication instruction on college campuses.

Journal Of The Association For Communication Administration: Complete Volume 41

Journal of the Association for Communication Administration

This is the complete volume of JACA Volume 41.

Acausal Modeling And Validation Of Platform Hydrodynamics Of A Floating Offshore Wind Turbine, Doyal Kumar Sarker

Graduate Thesis and Dissertation 2023-2024

This thesis presents the development of a platform hydrodynamics module for floating offshore wind turbines (FOWT) within the Control-oriented, Reconfigurable, and Acausal Floating Turbine Simulator (CRAFTS), which is currently being developed in the Hybrid Sustainable Energy Systems Laboratory at UCF. The CRAFTS simulator is an acausal modeling and simulation environment developed utilizing the Modelica language. CRAFTS is capable of fully coupled multi-physics simulations of various types of FOWTs and facilitates Control Co-Design (CCD) of FOWTs.

This work describes an acausal approach for modeling the structure and hydrodynamics, and for verifying the control of a semi-submersible floating platform for a 15MW …

Altitude And Pitch Control Of A Tethered Multi-Rotor Autogyro Using A Reduced Order Model, Tasnia Noboni

Graduate Thesis and Dissertation 2023-2024

Long-duration deployment of UAVs for surveillance and communication purposes can be very energy-consuming and expensive. Tethered autogyro-based UAVs can provide an energy-efficient solution to this problem and produce energy in the presence of a strong and persistent wind field at higher altitudes. Instead of using an engine, the unpowered autogyro rotors produce lift by creating an upward thrust force while relative airflow passes up through the rotor blades. The tether provides mooring action and can be used bidirectionally for transmitting or receiving power from the autogyro. Thus, tethered autogyros can address recent environmental concerns by reducing carbon footprint via efficient …

Development And Evaluation Of Dns Of Aluminum Droplet Combustion Using The Vof Approach, Soomin Lim

Graduate Thesis and Dissertation 2023-2024

This thesis focuses on the direct numerical simulation of the combustion of a single aluminum droplet with phase change. For this purpose, the Volume of Fluid (VOF) method is employed for the direct numerical simulation of two distinct phases. To model the droplet combustion, the phase change (evaporation) and chemical reactions are modeled by setting source terms for each governing equation. This work proposes a new form of species source term by phase change, derived using the local instant formulation of two-phase flow.

The Stefan problem is used to verify the modified source term. Evaporation fluxes calculated with both modified …

Modelling Of The Viscoelastic Relaxation Of A Stowed Telescope Starshade, Rahul Raghu

Graduate Thesis and Dissertation 2023-2024

The Habitable Worlds Telescope Starshade is an occulting disk that orbits in tandem with a telescope that occludes and diffuses the light from stars to observe the relatively dim exoplanets in orbit around them. It achieves this in part with tailored petals that diffuse light to soften the light from the star. Due to the relative sizes of the star and the planet, NASA considers the shape stability of the Starshade's petals to be a Key Technology Gap. The Starshade is developed to be a deployable composite structure that folds on itself to fit within modern rockets. Due to the …

Characterizing The Material Response Of The Passive Myocardium, Mehlil Ahmed

Graduate Thesis and Dissertation 2023-2024

Cardiovascular diseases remain a major public health concern worldwide, with heart failure emerging as a significant contributor to morbidity and mortality. Among heart failure cases, Heart Failure with preserved Ejection Fraction (HFpEF) presents a substantial clinical challenge due to its poor understanding and diagnostic complexity. Despite its prevalence, HFpEF lacks accurate diagnostic tools, hindering effective prognosis and therapy planning. This study addresses the knowledge gap surrounding HFpEF and diastolic dysfunction by focusing on the passive myocardial response during atrial systole, a critical yet understudied aspect of cardiac function. Current clinical measures, such as left ventricular ejection fraction, have limitations in …

A Cfd Framework To Study Complex Effects Relating To Airborne Viral-Pathogen Transmission, Rajendra Shrestha Mr.

Graduate Thesis and Dissertation 2023-2024

This research used computational fluid dynamics (CFD) to examine the behavior of airborne droplets released during respiratory events. The CFD model utilizes an Eulerian-Lagrangian approach, with turbulence resolved using the Spalart-Allmaras detached eddy simulation. The first part investigates airborne transmission and how modifying saliva during a sneeze impacts this process. The study employs CFD to simulate these respiratory events in a ventilated room. It finds that larger droplets alone are insufficient for droplet settling due to secondary breakdown processes. Modifiers that increase the Ohnesorge number show resistance to aerosolization from secondary breakup, resulting in more droplets with high settling rates, …

Human Performance In Context: Exploring The Effect Of Social Support On Vigilance, Allison E. Garibaldi

Graduate Thesis and Dissertation 2023-2024

Over many decades, vigilance research has consistently found that performance on vigilance tasks decline over time (i.e., the vigilance decrement; Davies & Parasuraman, 1982), and that performing a vigilance task is both mentally demanding and stressful (Warm et al., 2008). Researchers have subsequently implemented a wide range of interventions to both understand and attempt to attenuate the vigilance decrement and its associated affective effects. Among these efforts, little attention has been devoted to understanding the effects of the social environment on vigilance. Nonetheless, a handful of studies have indeed suggested that the presence of others can affect performance, workload, and …

High-Order Harmonic Generation In Bulk And Thin Film Solids, Troie Journigan

Graduate Thesis and Dissertation 2023-2024

High-order harmonic generation (HHG), a non-perturbative nonlinear light-matter interaction resulting in coherent emission of high-frequency light, has demonstrated promise as an optical probe of carrier dynamics, structural symmetries, and other properties of solids. HHG from bulk solids in transmission geometry, however, is influenced by nonlinear propagation of the driving laser, which leads to spectral skewing and temporal phase variations in the harmonic emission. These effects obscure the microscopic underlying physics, making HHG-based spectroscopy of bulk solids difficult to interpret. HHG in few-to mono-layer materials, however, avoids strong nonlinear propagation effects, and can provide novel material properties for HHG studies.

In …

Metaontological Dismissive Strategies: Implications And Applications In Metaphysics Of Race And Gender, Ethan F. Stumpp

Honors Undergraduate Theses

Metaontological discourse, inquiring into the nature, methodology, and aims of ontology, has functioned as the war ground for those skeptical of ontological projects against those who believe that ontological inquiry is substantive (i.e., meaningful, important, worth pursuing). I call the inquiry which engages in determining criteria to distinguish substantive from nonsubstantive inquiry/discourse: “the metaphysics of discourse”. In this project, I identify three frameworks in the metaphysics of discourse: Easy Ontology, The “Merely Verbal” Framework, and Metaphysical Structuralism. My primary concern is to show that these discourse frameworks or dismissive strategies all fail to provide sufficient criteria to properly delineate substantive …

Health Literacy And Maternal Health: A Rapid Systematic Review, Goldy Olivier

Honors Undergraduate Theses

In comparison to other high-income nations, the U.S. maintains the highest maternal mortality rate, especially among Black women. Factors like the growing maternal age and restricted family planning clinics have been noted to contribute to this phenomenon. However, the impact of health literacy on maternal has yet to be reviewed. Health literacy in the U.S. has long been determined to be a social determinant of health more broadly, and it may likely play a role in maternal health as well. Consequently, a systematic review of health literacy and its association with maternal health outcomes is warranted. The goal of this …

Machine Learning Approaches For Cyberbullying Detection, Roland Fiagbe

Data Science and Data Mining

Cyberbullying refers to the act of bullying using electronic means and the internet. In recent years, this act has been identifed to be a major problem among young people and even adults. It can negatively impact one’s emotions and lead to adverse outcomes like depression, anxiety, harassment, and suicide, among others. This has led to the need to employ machine learning techniques to automatically detect cyberbullying and prevent them on various social media platforms. In this study, we want to analyze the combination of some Natural Language Processing (NLP) algorithms (such as Bag-of-Words and TFIDF) with some popular machine learning …

Film Adaptation Of Novels Through Genai, Joshua M. Head

Graduate Thesis and Dissertation 2023-2024

When a production company commits to creating a film based on a novel, it is essential that their team is equipped to manage the extensive responsibilities required to authentically translate the book to the big screen. This study aims to explore and address these challenges by utilizing contemporary Generative Artificial Intelligence technologies, including Large Language Models, Text-To-Speech, and Text-To-Image models. While recent advancements have focused on enhancing these models, there is a gap in research on their practical application and effectiveness in real-world scenarios. This research will detail the steps necessary to deconstruct a novel’s narrative and produce the final …

Enhancing Student Graduation Rates By Mitigating Failure, Dropout, And Withdrawal In Introduction To Statistical Courses Using Statistical And Machine Learning, Shahabeddin Abbaspour Tazehkand

Graduate Thesis and Dissertation 2023-2024

The elevated rates of failure, dropout, and withdrawal (FDW) in introductory statistics courses pose a significant barrier to students' timely graduation from college. Identifying actionable strategies to support instructors in facilitating student success by reducing FDW rates is paramount. This thesis undertakes a comprehensive approach, leveraging various machine learning algorithms to address this pressing issue. Drawing from three years of data from an introductory statistics course at one of the largest universities in the USA, this study examines the problem in depth. Numerous predictive classification models have been developed, showcasing the efficacy of machine learning techniques in this context. Actionable …

Bayesian Variable Selection With Shrinkage Priors And Generative Adversarial Networks For Fraud Detection, Amina Issoufou Anaroua

Graduate Thesis and Dissertation 2023-2024

This research paper focuses on fraud detection in the financial industry using Generative Adversarial Networks (GANs) in conjunction with Uni and Multi Variate Bayesian Model with Shrinkage Priors (BMSP). The problem addressed is the need for accurate and advanced fraud detection techniques due to the increasing sophistication of fraudulent activities. The methodology involves the implementation of GANs and the application of BMSP for variable selection to generate synthetic fraud samples for fraud detection using the augmented dataset. Experimental results demonstrate the effectiveness of the BMSP GAN approach in detecting fraud with improved performance compared to other methods. The conclusions drawn …

Deep Learning One-Class Classification With Support Vector Methods, Hayden D. Hampton

Graduate Thesis and Dissertation 2023-2024

Through the specialized lens of one-class classification, anomalies–irregular observations that uncharacteristically diverge from normative data patterns–are comprehensively studied. This dissertation focuses on advancing boundary-based methods in one-class classification, a critical approach to anomaly detection. These methodologies delineate optimal decision boundaries, thereby facilitating a distinct separation between normal and anomalous observations. Encompassing traditional approaches such as One-Class Support Vector Machine and Support Vector Data Description, recent adaptations in deep learning offer a rich ground for innovation in anomaly detection. This dissertation proposes three novel deep learning methods for one-class classification, aiming to enhance the efficacy and accuracy of anomaly detection in …

A Critical Discursive Analysis Of The Effects Of Confidence Chats On The Positioning Of Students With Disabilities During Mathematics Discourse, Kelly R. Penny

Graduate Thesis and Dissertation 2023-2024

This qualitative study investigated how confidence chats affect how students with disabilities (SWD) position themselves during mathematics discourse and the impact the confidence chats had on a student’s mathematical identity. A critical discourse analysis was conducted over a three-month period using transcripts from classroom observations, student-teacher confidence chats, and teacher interview debriefs. Findings revealed that following the confidence chats, SWD participated in discourse, and students were able to adjust their positioning in relation to others. Over the course of the study, student collaboration increased and their reliance on teacher support decreased. In addition, the findings indicated that confidence chats provided …

University Of Central Florida Graduate Catalog, 2024 - 2025, University Of Central Florida

UCF Catalogs

No abstract provided.

Design Parameters For A Piezoelectric-Based, High-Authority, High-Bandwidth Flow Injection Valve, Sydney A. Giannuzzi

Graduate Thesis and Dissertation post-2024

Aeromechanical Identification Methodology (AIM) is an approach to measure damping in turbomachinery to identify and map flutter boundaries across various operating conditions. Previous approaches required entering, or nearly entering, flutter to produce a binary “flutter” / “no-flutter” boundary. AIM is significantly safer; however, it is limited by actuation authority and bandwidth. A non-contact, high-frequency, high-amplitude piezoelectric-based valve provides a promising solution to bridge these gaps. This valve operates by ejecting high-frequency oscillatory flow from a piezoelectric-based converging nozzle as a non-contact method of imparting a harmonic force. This valve has broad applications for high-frequency flow modulation beyond the motivating structural …

Towards Robust And Accurate Text-To-Code Generation, Saleh Almohaimeed

Graduate Thesis and Dissertation post-2024

Databases play a vital role in today's digital landscape, enabling effective data storage, management, and retrieval for businesses and other organizations. However, interacting with databases often requires knowledge of query (e.g., SQL) and analysis, which can be a barrier for many users. In natural language processing, the text-to-code task, which converts natural language text into query and analysis code, bridges this gap by allowing users to access and manipulate data using everyday language. This dissertation investigates different challenges in text-to-code (including text-to-SQL as a subtask), with a focus on four primary contributions to the field. As a solution to the …