Digital Commons Network^™

In An Immersive Space, Raising Awareness To Universalize The Concept Of Resistance And Hope, Elaheh Jazemi

Graduate Thesis and Dissertation 2023-2024

Inspired by my Iranian heritage, I symbolize my narrative of the social injustice and suppression prevalent in Iran. Through this thesis, I universalize the concept of resistance and hope for equality by raising awareness and giving a voice to the voiceless despite their significant sacrifices. In my studio practice, I sought to achieve a visual density that would enhance the immersive experiences. I constructed this by overlapping transparent materials such as tulle, resin, silk, and transparent sheets, creating a disorienting atmosphere that invites viewers to grapple with visual metaphors. This overwhelming ambiance, mirroring the despondent nature of the emotions conveyed …

Comical, Familial, Satirical: Exploring Visual Culture Through Portraiture And Graphic Narrative, Matthew D. Dunn

Graduate Thesis and Dissertation 2023-2024

My art examines visual culture using a plethora of techniques, formats, and materials. Recent works address family, pop-culture, and politics utilizing portraiture and short-form comics. Much of my art expresses humor through colorful, irreverent imagery, and many works employ satire and parody. Leveraging my experience as a professional illustrator and designer, I tailor my approach to each project, drawing upon divergent styles with an emphasis on polish and accessibility. I frequently adapt well-known images to recontextualize subjects. In my investigation of graphic narrative, I produced political comics, vintage comic book parodies, and experimental, interactive work. This body of work was …

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 …

Exploring The Removal Potential Of Multi-Pollutants From Water Matrices With Innovative Speciality Adsorbents In A Field-Scale Filtration System, Jinxiang Cheng

Graduate Thesis and Dissertation 2023-2024

Driven by excess nutrients in water bodies, eutrophication has long been an issue in water resources management. Harmful algal blooms (HABs) in a highly eutrophic water body lead to hypoxia, creating a “dead zone,” which renders the oxygen levels inadequate for the survival of marine life. This study examined the field-scale filtration performance of two specialty absorbents to improve watershed remediation within a Total Maximum Daily Load program. The goal was to simultaneously remove nutrients and biological pollutants along Canal 23 (C-23) in the St. Lucie River Basin, Florida. The filtration system installed in the C-23 river corridor was equipped …

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 …

Investigating Emerging Technologies In Civil Structural Health Monitoring: Generative Artificial Intelligence And Virtual Reality, Furkan Luleci

Graduate Thesis and Dissertation 2023-2024

Condition assessment of civil engineering infrastructure systems is of growing importance as they face aging and degradation due to both human-made activities and environmental factors. Nevertheless, challenges persist in data collection, leading to "data scarcity", and the need for frequent site visits in inspections, presenting significant obstacles in the assessment of the civil infrastructure systems. This dissertation aims to overcome these challenges by exploring the potential of two emerging technologies: Generative Artificial Intelligence (AI) and Virtual Reality (VR). In tackling the issue of data scarcity, the research question revolves around how Generative AI can be utilized to mitigate data collection-related …

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 …

Psychometric Evaluation Of A Brief Measure For Body Image Concerns Related To Breast Appearance, Sivanne Mendelson

Graduate Thesis and Dissertation 2023-2024

The complexity of breast-specific body image concerns among women considering cosmetic breast surgery (CBS) underscores the need for a nuanced assessment tool. Despite numerous existing body image measures, there remains a need for a concise, validated instrument focusing on satisfaction with breast appearance. The development of the Breast Appearance Concerns Scale (BACS) aimed at assessing the multifaceted nature of breast-specific concerns through a patient centered lens within a population of otherwise healthy young adult women. The BACS was developed through a comprehensive review of existing literature and refined using exploratory and confirmatory factor analyses, in addition to Rasch measurement analysis. …

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 …

An Analysis Of The Relationship Between A Novice Educator Support Team And The Self-Efficacy Of Beginning Teachers In Elementary, Middle, And High Schools, Bailey Holmquist

Graduate Thesis and Dissertation 2023-2024

Over the last twenty years, there has been an increase in teacher turnover and, in attempts to mitigate this issue, states and school districts have developed novice teacher mentoring programs. A Large Suburban School District implemented a novice teacher mentoring program during the 2021–2022 school year with the goal of providing novice teachers with a larger system of support to increase retention rates. The purpose of this research was to examine the relationship between novice teacher perceptions of a mentoring program and novice teacher perceptions of self–efficacy. Novice teachers (i.e., 1 to 3 years of teaching experience) received a survey …

Capable Rhetoric: Embodied Rhetorical Listening And Midwives' Arguments For The Maternal Body On Instagram, Aminta C. Quintero-Jackson

Graduate Thesis and Dissertation post-2024

When women find out they are pregnant, they encounter discourse about their bodies they may not have consciously considered before. Frequently, the information is based on ideologies that consider maternal bodies to be inherently problematic. The discourse in this information informs and shapes women’s choices about the role of medical oversight in their pregnancies and impacts the perceptions they have of themselves.

Midwives argue that mothers and their bodies are not inherently problematic but are powerful and capable of childbirth. They argue that medical oversight has been too aggressive in birth management, interrupting the natural process of birth and causing …

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 …

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 …

A Study Of The Effects Of Microgravity Through Porous Media In Microfluidic Devices, Taylor A. Peterson

Graduate Thesis and Dissertation 2023-2024

In recent years, space exploration has been driving studies that enable sustained human presence in space. In such studies, fluidics relating to biology have become important. Fluids in biological systems span from large-scale flows relevant to circulatory, digestion, and pulmonary systems, but also involve many micro-scale porous flows. Hence, space exploration is driving a novel need to characterize fluidics in microscales in microgravity conditions. In this work, we study the porous flow network within bones that stimulates cellular growth and has the potential to relate to osteoporosis (including driving osteoporosis in astronauts). To study this effect, computational fluid dynamics (CFD) …

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, …

Numerical Modeling Of Cavitation During Shock Droplet Interaction, Khanh Chi Nguyen

Graduate Thesis and Dissertation 2023-2024

This effort explores the complex phenomena of cavitation inside different liquid geometry interacting with a planar shock wave by employing the use of Computational Fluids Dynamics (CFD) modeling. The simulation is an unsteady multiphase simulation utilizing a finite volume commercial code known as STAR-CCM+ . Two primary cavitation models were employed: the Schnerr- Sauer model and the Full Rayleigh-Plesset model. The initial investigation involves validating the numerical simulations against available experimental data. Subsequently, a comprehensive parameter study was conducted, examining the effects of varying Mach numbers, liquid geometries, and seed densities on the cavitation phenomenon. Results indicated that cavitation occurs …

Analyzing The Use Of Plain Language In Brief Summaries On Clinicaltrials.Gov, Megan J. Eddington

Graduate Thesis and Dissertation 2023-2024

ClinicalTrials.gov is a database designed to help clinical researchers make their research publicly available. The clinical trials registered on the database each include a brief summary, which is meant to be a short description that the public can easily understand. In September 2022, ClinicalTrials.gov published a "Plain Language Checklist for Lay Brief Summaries" on their website, which identifies plain language best practices intended to help investigators craft summaries that can be readily understood by the public. This thesis assesses the impact of the checklist on the language use in the brief summaries in the year following the checklist's publication. The …

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 …

Combating Cyberbullying On Social Media: A Machine Learning Approach With Text Analysis On Twitter, Amir Alipour Yengejeh

Data Science and Data Mining

The popularity of the electronic mobile devices along with social media as well as networking websites have been tremendously increased in the recent year. Most people around the world daily engage in the variety of cyberspace additives. Even though the users can take most advantages of these system such as exchange the idea and information, being sociable, and enjoyments, they might be faced with such adverse behaviors such as toxicity, bullying, extremism, and cruelty. The recent statistics reports that such mentioned behaviors has been noticeably grown on the cyberspace such that can threaten the individuals and even any community. Thus, …

Xgboost Hyperberd Model Using Steam Platform, Yuh-Haur Chen

Data Science and Data Mining

This project investigates game pricing strategies in the Steam market using an XGBoost model, drawing motivation from Professor Xie's lecture, and presenting findings through a density plot that delineates two primary pricing strategies. A free-to-play approach, indicated by a significant hot spot, is adopted by developers focusing on post-purchase revenues through DLC, aesthetic purchases, and in-game transactions. This sailing strategy includes community-centric developers aiming to distribute their games for player engagement rather than profit.

The project illustrates the effectiveness of advanced modeling techniques in handling complex datasets, with significant predictive accuracy reflected by a reduced MSE from 0.3472 to 0.1397. …

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 …

Advancing Cancer Classifcation Through Machine Learning Analysis Of Rna-Seq Gene Expression Data, Emil Agbemade, Amina Issoufou Anaroua, Dimitri Bamba

Data Science and Data Mining

This study delves into the classifcation of various cancer types using the RNA-Seq (HiSeq) PANCAN dataset from the UCI Machine Learning Repository, which encompasses a rich collection of gene expression data across multiple tumor samples. To improve cancer diagnosis and treatment, our methodology confronts the challenges inherent in high-dimensional datasets, such as the Hughes Effect and the Curse of Dimensionality, through innovative feature selection methods and machine learning approaches. A key component of our strategy includes the use of tree-based algorithms, particularly Random Forest, to refine the dataset to seventy genes of utmost relevance for tumor classifcation, and the application …

Bootstrap Regression For Investigating Macroeconomics Factors Affecting Usa Home Prices, Benedict Kongyir, Emil Agbemade

Data Science and Data Mining

This study investigates the impact of macroeconomic indicators on US home prices, underscoring the importance of understanding these dynamics due to their signifcant socioeconomic consequences. Utilizing a dataset from Kaggle, originally collected by FRED, the research examines variables like the Consumer Price Index, Population, Unemployment, GDP, Stock Prices, Income, and Mortgage Rate to discern their efect on housing market fuctuations. The analysis identifes multicollinearity among predictors, necessitating a shift from traditional multiple linear regression to a more robust bootstrap regression method due to violations of parametric assumptions. Key fndings reveal that Real Disposable Income is a signifcant predictor of home …

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.

Optimizing Ai With Advanced Data Structuring: A Comparative Analysis Of K-Means And Gmm Clustering Techniques, Amir Alipour Yengejeh

Data Science and Data Mining

This study presents a detailed comparison of Kmeans and Gaussian Mixture Model (GMM) clustering algorithms, illustrating their unique capabilities and limitations across various synthetic datasets. By utilizing metrics such as the Adjusted Rand Index (ARI) and Normalized Mutual Information (NMI), the research provides nuanced insights into how these algorithms handle datasets with varying structures and complexities. For instance, while both K-means and GMM show robust performance on well-separated clusters, GMM demonstrates a distinct advantage in scenarios with overlapping clusters or unbalanced data distributions. Conversely, K-means excels in identifying clear, distinct groupings, highlighting its utility in simpler clustering contexts. This study …

Predicting Road Accident Injury Severity For Drivers In Automobile Crashes In United States Using Machine Learning Models And Ai, Emil Agbemade, Benedict Kongyir

Data Science and Data Mining

This study analyzes data from the National Highway Trafc Safety Administration’s 2021 Crash Report Sampling System to identify key factors contributing to the severity of injuries in car accidents. By utilizing various machine learning algorithms and cross-validation techniques, we assessed metrics such as accuracy, sensitivity, precision, specifcity, and the area under the curve (AUC) to evaluate the efectiveness of predictive models. All data preprocessing and model building was done using KNIME Analytical software [9]. Our fndings reveal signifcant correlations between certain variables such as airbag injection, weather conditions, intoxication, vehicle state, driver distractions, and injury severity. These insights underscore the …

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 …

Ucf Pegasus Plan - 2nd Grade - Supply & Demand, Renata Veronica Nunez Saenz, Valeria Bonilla, Julia Buquicchio, Leah Silverman, Mya Buck

Pegasus Plans: Social Studies Unit Plans for Florida Teachers

During this unit, students will explore the fundamental concepts of economics. Through collaborative discussions, multimedia resources, and formative assessments, students will develop a robust understanding of how markets operate in their community and how people provide goods and services based on societal needs. Students will investigate the production process of familiar goods and learn the roles of producers and consumers in economic systems. They will also examine the concept of supply and demand with real-world applications by analyzing how changes in supply and demand affect prices and consumer behavior. The unit includes vocabulary introductions, practical demonstrations, and visual aids to …