Digital Commons Network^™

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 …

A Gift For Teaching, Ella Kassis, Ranica Zaydvarg, Renata Silva

High Impact Practices Student Showcase Fall 2024

Our service-learning project involved volunteering at A Gift for Teaching in Orlando, Florida. A Gift for Teaching is a nonprofit organization with the goal of providing free school supplies to underfunded schools and teachers. We assisted in sorting through donated supplies, such as pencils, notebooks, art materials, and other resources, and preparing them for distribution to local teachers and schools. By working with this organization, we were able to support teachers and students within our community, helping to provide students with the learning experience they deserve

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 …

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 …

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. …

A Handheld, Biomimetic, Phase Change Microsystem For Breath Condensate Based Point-Of-Use (Pou) Diagnostics Assays, Pablo Morales-Cruz

Graduate Thesis and Dissertation 2023-2024

A variety of biomimetic [Stenocara gracilipes (Namib desert beetle), Dendrocalamus brandissii (Velvet Leaf Bamboo), and Opuntia microdasys (Bunny Ear Cactus)]-based microsystems, were developed to collect exhaled breath for use in point-of-use (POU) settings. The overall platform consists of a 50 x 50 mm 3D printed micro-chamber which is decorated with a PDMS micromolded Breath Condensate Collection Chip (BCCC) emulating the morphology of the biomimetic architectures. The micro-chamber and BCCC are further treated with a nanoscale superhydrophobic coating and infused with oil for enhancement in condensate collection. Different designs and setups were tested for optimum breath collection along with different …

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 …