Digital Commons Network^™

Dual Coalitions Or Dueling Coalitions?: A Comparison Of Single-Issue And Dual-Issue Statewide Domestic Violence And Sexual Assault Coalitions In The U.S., Shannon Sokolowski

Graduate Thesis and Dissertation post-2024

Domestic violence (DV) and sexual assault (SA) are critical social issues requiring a large scale national response. In the U.S., federally designated statewide DV and SA coalitions are nonprofit organizations that play a critical role at the national, state, and local levels. Once individual social movements, DV and SA advocacy coalitions have merged at higher rates in recent decades. Efforts to achieve economic sustainability may drive the decision to merge or reform. However, nonprofit organizations have a double bottom line, needing to consider financial and mission-related performance. With economic uncertainly rising, it is critical to understand the impact that forming …

Program Evaluation Of Behavioral Health Training: Using The Retain Model, Kris J. Toscani

Graduate Thesis and Dissertation post-2024

This study investigated the effectiveness of gamification elements introduced into a well-established behavioral health in-person professional training. The gamification elements were designed with the RETAIN Model and Rubric and intended to increase team member engagement by increasing Relevance, Embedding a fictitious medical-themed story, creating opportunities for knowledge acquisition and Transfer, Adapting the content to the job functions of the participants, creating an Immersive experience in which the team members were fully engaged in the medical mystery, and repetitively applying gameplay concepts to efforts to create a Naturalized learning experience. The methodological approach to assessing …

Every Person A Home Every Home A Person, Emily R. Miller

Graduate Thesis and Dissertation post-2024

Every Person a Home Every Home a Person is a collection of poems that explores the meaning of “home” and the places where our homes are made. The collection consists of intertwining thematic threads that delve into what makes a home, including those found in physical houses, cultural identities and regional areas (in this case, Florida/the American South), other people, and personal identity. Through probing poems inspired by the author’s life and experiences as a queer, neurodivergent woman*, Every Person a Home Every Home a Person asks and tries to answer the question: what makes a home, and how do …

Empathy In Digital Healthcare, Michael R. Powell

Graduate Thesis and Dissertation post-2024

This dissertation investigates how the rapid expansion of telehealth, particularly in response to the COVID-19 pandemic, has reshaped clinician-patient interactions, with a focus on the role of empathy. Telehealth has broadened access to care and introduced new efficiencies, but it also presents distinct challenges in fostering the deep emotional connections traditionally associated with in-person consultations. By exploring how empathy is mediated through digital platforms, this research offers valuable insights into how empathetic connections can be supported, though not fully replicated, in virtual healthcare settings. Through a mixed-methods approach, including qualitative interviews with healthcare providers, the study examines both the barriers …

The Role Of School Culture And Autonomous Motivation In Supporting Academic Achievement And Teacher Retention In A Public Charter School: An Ethnographic Case Study, Amanda W. Reschke

Graduate Thesis and Dissertation post-2024

U.S. public schools are in crisis amid declining student achievement and widespread teacher shortages, particularly in the wake of the Covid-19 pandemic, putting students at risk for poor academic outcomes. Data from the National Center for Education Statistics (NCES) shows 4^th and 8^th grade students’ average reading and math scores have decreased by 5 points and 7 points respectively since 2019. Furthermore, NCES data showed that 53% of public schools reported being understaffed for the upcoming school year in August 2022, and by October 2022, 45% of public schools reported at least one vacant teaching position. While many …

Developing A Multi-Level Model Of Integrated-Organizational Resilience, Reza Bahari

Graduate Thesis and Dissertation 2023-2024

Most contemporary organizations work in unsteady environments and are impacted by various types of disruptions that have profound impacts on performance such as natural disasters, globalization, and financial recessions. Due to this, the concept of integrated organizational resilience (IOR) has become an important issue for both academic researchers and practitioners in recent years. A review of the literature shows that much of the research has focused on identifying and measuring the factors that affect OR in an effort to improve organizations' capacity for resilience. While significant research has been conducted in this area, much of the evidence focuses on a …

Machine Learning Algorithms To Study Multi-Modal Data For Computational Biology, Khandakar Tanvir Ahmed

Graduate Thesis and Dissertation 2023-2024

Advancements in high-throughput technologies have led to an exponential increase in the generation of multi-modal data in computational biology. These datasets, comprising diverse biological measurements such as genomics, transcriptomics, proteomics, metabolomics, and imaging data, offer a comprehensive view of biological systems at various levels of complexity. However, integrating and analyzing such heterogeneous data present significant challenges due to differences in data modalities, scales, and noise levels. Another challenge for multi-modal analysis is the complex interaction network that the modalities share. Understanding the intricate interplay between different biological modalities is essential for unraveling the underlying mechanisms of complex biological processes, including …

Eavesdropping-Driven Profiling Attacks On Encrypted Wifi Networks: Unveiling Vulnerabilities In Iot Device Security, Ibrahim A. Alwhbi

Graduate Thesis and Dissertation 2023-2024

Abstract—This dissertation investigates the privacy implications of WiFi communication in Internet-of-Things (IoT) environments, focusing on the threat posed by out-of-network observers. Recent research has shown that in-network observers can glean information about IoT devices, user identities, and activities. However, the potential for information inference by out-of-network observers, who do not have WiFi network access, has not been thoroughly examined. The first study provides a detailed summary dataset, utilizing Random Forest for data summary classification. This study highlights the significant privacy threat to WiFi networks and IoT applications from out-of-network observers. Building on this investigation, the second study extends the research …

A Multimodal Framework For Automated Content Moderation Of Children's Videos, Syed Hammad Ahmed

Graduate Thesis and Dissertation 2023-2024

Online video platforms receive hundreds of hours of uploads every minute, making manual moderation of inappropriate content impossible. The most vulnerable consumers of malicious video content are children from ages 1-5 whose attention is easily captured by bursts of color and sound. Prominent video hosting platforms like YouTube have taken measures to mitigate malicious content, but these videos often go undetected by current automated content moderation tools that are focused on removing explicit or copyrighted content. Scammers attempting to monetize their content may craft malicious children's videos that are superficially similar to educational videos, but include scary and disgusting characters, …

Analytical And Experimental Verification Of Bistable Composite Laminates For Aerospace Applications, Maxwell J. Booth

Graduate Thesis and Dissertation 2023-2024

Composite laminate structures offer promising aerospace applications owing to their multi-functional capabilities. These composites exhibit the unique ability to transition between stable geometries, passing through an intermediate, predicted unstable geometry. Actuation is achieved through the application of external loading conditions, encompassing both mechanical and thermal stimuli, with a particular emphasis on the latter. The nonlinear response induced by such transitions experimentally motivates this research due to the minimal amount of data on the transition section between geometries. Application of these composites under loading conditions proves interesting for a thermal management application with additional thermal loading present. This use would require …

A Near Field Lagrangian Particle Modeling For The Multiphase Flow Of Reaction Control System Thrusters In Space Environments, Janice Zou

Graduate Thesis and Dissertation 2023-2024

In the current age of space exploration, the push to reach further to deep space presents a greater need for analysis and verification and validation of rocketry components in the space environment. Due to the nature of space, firings of rocket thrusters in space is a multi-regime problem. With the low density, pressure, and temperature of the environment, the resultant plume structure, seeded with unburnt fuel droplets, extends up to multiple orders of magnitude in distance as compared to a plume structure in the Earth’s atmosphere. The frozen droplets, or particles, create concerns including surface contamination and erosion, calling a …

Video Action Understanding: Action Classification, Temporal Localization, And Detection, Praveen Tirupattur

Graduate Thesis and Dissertation 2023-2024

Video action understanding involves comprehending actions performed by humans, depicted in videos. Central to the task of video action understanding are four fundamental questions: What, When, Where, and Who. These questions encapsulate the essence of action classification, temporal action localization, action detection, and actor recognition. Despite notable progress in research related to these tasks, many challenges persist and in this dissertation, we propose innovative solutions to tackle these challenges head-on.

First, we address the challenges in action classification (``What?"), specifically related to multi-view action recognition. We propose a novel transformer decoder-based model, with learnable view and action queries, to enforce …

Advances In High Performance Computing Through Concurrent Data Structures And Predictive Scheduling, Kenneth M. Lamar

Graduate Thesis and Dissertation 2023-2024

Modern High Performance Computing (HPC) systems are made up of thousands of server-grade compute nodes linked through a high-speed network interconnect. Each node has tens or even hundreds of CPU cores each, with counts continuing to grow on newer HPC clusters. This results in a need to make use of millions of cores per cluster. Fully leveraging these resources is difficult. There is an active need to design software that scales and fully utilizes the hardware. In this dissertation, we address this gap with a dual approach, considering both intra-node (single node) and inter-node (across node) concerns. To aid in …

Semiconductor Mode-Locked Lasers For Applications In Multi-Photon Imaging And Microwave Photonics, Srinivas Varma Pericherla

Graduate Thesis and Dissertation 2023-2024

Semiconductor lasers are considered essential for the advancement in the field of photonics where compact and energy-efficient lasers are necessary. Advancements in integrated photonic technologies will help push the performance of semiconductor lasers in the coming years and expand the technology to several other applications. Semiconductor lasers offer several key features such as high energy efficiency, mass production, availability at a myriad of wavelengths, and high integration capabilities. However, limitations in noise performance, pulse energy, and duration hold back semiconductor lasers from being utilized to their full potential. This dissertation reviews the utilization and development of external techniques that enable …

Objective-Driven Strategies For Hpc Job Scheduling, Alexander V. Goponenko

Graduate Thesis and Dissertation 2023-2024

As High-Performance Computing (HPC) becomes increasingly prevalent and resource-intensive, there is a growing need for the development of more efficient job schedulers, which play a crucial role in the performance of HPC clusters. This dissertation manifests a comprehensive approach to this complex issue, contributing to three major components of the problem: (1) metrics of job packing efficiency and fairness, (2) advanced scheduling algorithms, and (3) job resource utilization prediction techniques.

To ensure high relevance of the results, this study emphasizes scheduling objectives. Therefore, scheduling quality metrics are investigated first, yielding a set of metrics that allow comparing alternative schedules and …

Models Of Information Diffusion And The Role Of Influence, Chathura Jj Don Dimungu Arachchige

Graduate Thesis and Dissertation 2023-2024

Information diffusion is significant in fields such as propagation prediction and influence maximization, with applications in viral marketing and rumor control. Despite conceptual differences, existing diffusion models may not represent identical underlying generative structures. A classification of diffusion of information models is developed based on infection requirements and stochasticity. The study involves analyzing seven existing DOI models on directed scale-free networks. The distinctive properties of each model are identified through simulations and analysis of experimental results. Our analysis reveals that similarity in conceptual design does not imply similarity in behavior concerning speed, the final state of nodes and edges, and …

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 …

Rhizophora Mangle (Red Mangrove) Seedling Success In Different Habitats In Mosquito Lagoon, Florida, Usa, Mekail N. Negash

Graduate Thesis and Dissertation 2023-2024

Mangroves provide many ecosystem services in coastal environments around the world. These include water quality improvement, creating habitats for terrestrial and aquatic species, and stabilizing shorelines. In central Florida, the red mangrove Rhizophora mangle is a common species in coastal wetlands, and recently the number of individuals successfully recruiting to intertidal oyster reefs has greatly increased, possibly because biogeochemical hot spots are present on oyster reefs due to nutrient-rich biodeposits from the live oysters. To understand how well R. mangle responds in terms of survival and growth to the suite of variables associated within these two unique habitats, I tracked …

Film As Ritual: Healing From Complex Trauma And Transmuting Pain Through Film, Lorraine I. Sovern

Graduate Thesis and Dissertation 2023-2024

Forward Fast, Always/Never (Together Forever) and Shotgun Baby are three short experimental documentary films as part of the requirements for earning a Master of Fine Arts in Feature Film Production from the University of Central Florida. These films focus on the unique power of cinema and its ability to assist in healing from complex trauma. Three films were produced on an artisanal, micro-budget scale.

This body of work confronts and examines the significant traumas from an abusive childhood upbringing (Shotgun Baby), the effects of misogyny in Western media on my developing filmic sensibilities (Forward Fast), and …

Spotting The Signs: An Investigation Of The Effectiveness Of A Peer Training Program In Increasing Students' Ability To Detect And Report The Warning Signs Of A Peer School Shooting Plot, Ashley T. Winch

Graduate Thesis and Dissertation 2023-2024

To date, there are no evidence-based peer bystander intervention trainings (BIT) aimed at educating peers in school shooting warning behaviors. The purpose of this study was to examine an interactive BIT where peers were taught warning behaviors related to someone planning a school shooting and how to report this information. This training was evaluated against a currently available training method (i.e., PowerPoint presentation based) and a control group to determine the best training approach. College students between 18 and 19 years old (N = 57) completed pre, post, and one-month follow-up assessments. At each timepoint accuracy in detection of …

Adaptation To Hypoxia And Nitrate/Nitrite Assimilation Require Species-Specific Regulation By Dosr And Nnar In Mycobacterium Abscessus, Breven S. Simcox

Graduate Thesis and Dissertation 2023-2024

Mycobacterium abscessus (Mab) is an opportunistic pathogen afflicting immunocompromised patients and individuals with underlying comordibities such as Cystic Fibrosis (CF). Treatment strategies are limited due to inherent antibiotic resistance and restricted accessibility of Mab to antibiotics within macrophage phagosomes, granuloma lesions, and the mucus laden CF airways. Transcriptional adaptation to stresses encountered in these niches such as hypoxia, reactive nitrogen intermediates (RNI) and elevated nitrate and nitrite are not well-understood. In Mycobacterium tuberculosis (Mtb) hypoxia adaptation and nitrate metabolism are linked via induction of the two-component system (TCS) DosRS and nitrate metabolism genes. DosRS_Mtb induces …

Is This The Real Life, Or Is This Just Fantasy? Assessing Species Distribution Model Realism And Applicability With Virtual And Empirical Species, Hannah R. Bevan

Graduate Thesis and Dissertation 2023-2024

Species distribution models (SDMs) can be important tools for proactive conservation management if they are realistic. Unfortunately, achieving and assessing SDM realism is challenging given the general limitations of scientific models and empirical species data. We addressed the issue of achieving realism with high model quality and reproducibility by reviewing 200 SDMs and cataloguing methods for data availability, response and predictor variables, model fitting, and model performance. We addressed the issue of assessing SDM realism by comparing known and predicted distributions of habitat suitability with simulated data for various model fitting choices. Finally, we applied and compared subsequent lessons to …

Next-Generation High-Performance Virtual Reality And Augmented Reality Light Engines, Zhiyong Yang

Graduate Thesis and Dissertation 2023-2024

The immersive virtual reality (VR) and the optical see-through augmented reality (AR) are expected to revolutionize human lives in work, education, entertainment, healthcare, spatial computing, and digital twins, just to name a few. Next-generation VR/AR devices should exhibit a wide field-of-view (FoV), crisp image without screen-door effect, high dynamic range, compact form factor and lightweight, and low power consumption. Such demanding requirements pose a significant challenge to traditional direct-view display panels. To address these technical challenges, novel approaches need to be proposed. This dissertation is devoted to developing next-generation high-performance display light engines toward high resolution density, high optical efficiency, …

Breaking Molds: Transformative Processes In Art Making, Materials, And Life, James M. Wysolmierski

Graduate Thesis and Dissertation 2023-2024

Drawing upon traumatic moments of my past as a catalyst, I pursue understanding and acceptance of physical and emotional pain. In this thesis body of work, I employ the intersection of industrial and body imagery in sculptural forms and installation as a corporeal and allegorical account of my lived experience using visual narratives of trepidation and metamorphosis. In my creative practice, I incorporate various materials that create a reference of specific moments from my past. The artworks draw from principles rooted in Buddhism, affect theory, phenomenology, and materiality; incorporating them as tools to comprehend my position in the world and …

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 …

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 …

Software Company Workplace Bias In Technical Communication, Amanda Altamirano

Graduate Thesis and Dissertation 2023-2024

This dissertation is an interdisciplinary work that explores the intersection of humanities and technical communication by focusing on the presence and impact of software company workplace bias in technical professional communication. It focuses on workplace bias in technical communication because, when present, bias can impact the experiences that technical communicators and end-users (people who use the software) have with the software. This mixed-methods study consists of a survey, an interview, and a new diagram designed to help technical communicators mitigate biases in technical documentation. To understand better the presence and impact of bias in these workplace contexts, this study surveys …

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 …