Digital Commons Network^™

Bridging Data And Theory: A Gray-Box Approach To Traffic Flow Dynamics, Shakib Mustavee

Graduate Thesis and Dissertation post-2024

The dissertation demonstrates the applicability of the data-driven dynamical systems (DDS) approach at both macroscopic and microscopic scales to extract mathematical structures from observed traffic data. Firstly, a novel DDS model is developed to capture the evolution of queue lengths in a signalized arterial corridor, dividing the dynamics into quasiperiodic and chaotic components. The proposed model effectively captures nonlinear dynamics from time series data. The Reproducing Kernel Hilbert Space (RKHS) method is employed to estimate mathematically guaranteed Koopman eigenvalues and functions of the system, providing valuable insights into the periodic and chaotic behaviors of the system. Secondly, to further characterize …

Investigation Of Shock/Jet Interactions In A Shock Tube Facility, Michelle Franzen

Graduate Thesis and Dissertation post-2024

The present work explores using non-intrusive diagnostic techniques to investigate high-temperature, high-pressure environments in a shock tube facility. Shock tube facilities are generally used to achieve flow conditions similar to combustors or other supersonic flow regimes to study and validate chemical kinetics models. Traditional probes are unsuited to these extreme conditions due to their limited durability, poor spatial resolution, and slow response times. This study tested three techniques: Schlieren imaging, Background-Oriented Schlieren (BOS), and emission spectroscopy. Schlieren and BOS provide 2D visualization of the flowfield and density gradients with a temporal resolution of 10 μs. At the same time, emission …

Advanced Analysis Of Mode Veering Variations In Academic Blisks, Nicolas Olore

Graduate Thesis and Dissertation post-2024

This thesis presents an in-depth investigation into the vibrational dynamics of bladed disks (blisks), with a focus on understanding the conditions that lead to mode veerings and shifts in natural frequencies under varying geometric configurations. By utilizing maps of frequencies across nodal diameters, this study explores the effects of altering inner and outer disk radii, blade Aspect Ratios, and height ratios on the modal behavior of blisks. The study analyzes these geometric modifications to determine their influence on both mode interactions and frequency shifts, offering insights into how the number of veerings can be controlled. Mode veerings are of particular …

Robust Machine Learning Based Frameworks For Localization And Mmwave Beam Prediction In Massive Mimo Systems, Katarina Vuckovic

Graduate Thesis and Dissertation post-2024

The primary focus of this doctoral dissertation is the investigation of robust massive Multiple Input Multiple Output (MIMO) communication systems. The study centers on two closely related issues: i) single-site user localization, and ii) millimeter Wave (mmWave) beam prediction. The motivation is to develop a system that simultaneously offers users reliable communication and precise localization using a single infrastructure. This dissertation specifically addresses three key challenges in data-driven solution: i) the limited availability of position-labeled training datasets, ii) robustness in time-varying dynamic environments, and iii) the generalization of models to unseen scenarios. The study introduces three localization and two beam …

Non-Contact Lap-Splice Design With Ultra-High-Performance-Concrete For Seismic Buildings, Tiancheng Wang

Graduate Thesis and Dissertation post-2024

Controlling the location and strength of plastic hinges is crucial for maintaining the integrity of seismic-resistant structures during seismic events. Although advanced materials, new structural systems, and supplemental damping devices have been extensively researched, conventional reinforced concrete detailing can also effectively achieve this control. This study explores a controllable slippage mechanism in lap-splice configurations of monolithic ultra-high performance concrete (UHPC) members to regulate the location and capacity of plastic hinges in concrete building frames. UHPC's superior tensile, compressive, and bond strengths, compared to normal strength concrete (NSC), enable the use of strategically placed lap splices with short lap lengths. This …

Towards Label Efficiency And Privacy Preservation In Video Understanding, Ishan Rajendrakumar Dave

Graduate Thesis and Dissertation post-2024

Video understanding involves tasks like action recognition, video retrieval, human pose propagation which are essential for applications such as surveillance, surgical videos, sports analysis, and content recommendation. The progress in this domain has been largely driven by advancements in deep learning, facilitated by large-scale labeled datasets. However, video annotation presents significant challenges due to its time-consuming and expensive nature. This limitation underscores the importance of developing methods that can learn effectively from unlabeled or limited-labeled data, which makes self-supervised learning (SSL) and semi-supervised learning particularly relevant for video understanding. Another significant challenge in video understanding is privacy preservation, as methods …

Computational Approaches To Study Post Transcriptional Regulation Events, Naima Ahmed Fahmi

Graduate Thesis and Dissertation post-2024

A simplistic understanding of the central dogma falls short in correlating the number of genes in the genome to the number of proteins in the proteome. Post-transcriptional regulation, including alternative splicing and alternative polyadenylation contribute to the complexity of the proteome and is critical in understanding gene expression. In this dissertation, we aim to provide genome-wide detection and visualization of the transcript variants and quantify their significance in gene regulation. First, we propose a robust computational program to identify alternative splicing events from RNA-seq data, called AS-Quant. Our extensive experiments on simulated and real datasets demonstrate that AS-Quant can accurately …

Thermal Analysis Of Additively Manufactured Aluminum F357 And Inconel 718 In High-Enthalpy Hypersonic Flows, Andrew La Sorsa

Graduate Thesis and Dissertation post-2024

Hypersonic vehicles are not only limited by the propulsion systems needed to achieve such speeds but also by the conventional materials currently at hand. At speeds of Mach 5 and above, sections of the vehicle can experience local temperatures exceeding 3000 K, which can severely degrade any material not rated to withstand such extreme environments. This warrants the need for developing novel high-temperature resistant materials to be safely integrated into hypersonic vehicles. Additive manufacturing has been identified as a solution to the process of creating these materials and offers increased design flexibility and quality compared to conventional fabrication methods. A …

Comparison Of Bearing Capacity Estimates To The Barcelona Basic Model Implemented Through Finite Element Modeling In Plaxis2d, Carlee M. Shaw

Graduate Thesis and Dissertation post-2024

The design of foundations is greatly influenced by its bearing capacity and settlement behavior, especially for that of shallow foundations which lie within the unsaturated zone of soil. Similarly, bearing capacity of beach sands can be utilized to determine beach trafficability, as vehicular loads may be assumed within the unsaturated zone. Therefore, similar scenarios should be analyzed as partially saturated conditions, unlike conventional bearing capacity estimations. To analyze such conditions, the concept of soil suction has more recently been of consideration. In this paper, the load-settlement behavior of a sand in partially saturated conditions is explored through finite element modelling …

Effective And Efficient Use Of Diffusion Models For Editing In Computer Vision, Umar Khalid

Graduate Thesis and Dissertation post-2024

This doctoral dissertation explores efficient applications of diffusion models in video and 3D scene editing, addressing the high computational demands traditionally associated with these tasks. The research introduces several innovative methods to make diffusion models more practical in real-world video and 3D scenarios while preserving high output quality.

The dissertation first presents parametric efficiency techniques for video understanding, followed by SAVE, a novel approach that leverages Text-to-Image (T2I) diffusion models for video editing, minimizing resource requirements. Building on this, the study introduces LatentEditor, a method that performs fine-grained, localized 3D scene editing in a latent space, thus enhancing Neural Radiance …

Applications Of Plasmonic Biosensors In Chiral And Achiral Sensing, Aritra Biswas

Graduate Thesis and Dissertation 2023-2024

Monitoring biological systems is crucial in healthcare, driving the need for reliable and noninvasive solutions. The proliferation of unverified drugs in the market necessitates reliable methods for their detection and identification, especially amidst advancements in pharmaceuticals. Plasmonic biosensors emerge as a great platform for ultra-sensitive detection, identification, and manipulation of biomolecular systems. This dissertation report addresses the critical need for precise detection and monitoring of biomolecules and drugs, presenting innovative solutions through the design of a plasmonic biosensor to tackle challenges in sensitivity, selectivity, and label-free detection and identification. We introduce a robust and tunable, cavity-integrated plasmonic nanopatterned sensor that …

Silencing Stemness Genes In Glioblastoma Cancer Stem Cells Improve Anticancer Drug Efficacy, Jonhoi C. Smith

Graduate Thesis and Dissertation post-2024

Glioblastoma (GBM) is an aggressive and incurable primary brain tumor characterized by therapy-resistant cancer stem cells (CSCs). Due to the limited effectiveness of conventional chemotherapies and radiation treatments against cancer stem cells (CSCs), there is a critical need for the development of innovative therapeutic approaches. Our previous research revealed the significant expression of embryonic stemness genes, NANOG and OCT4, in CSCs, suggesting their role in enhancing cancer-specific stemness and drug resistance. By suppressing the expression of these genes, we observed increased susceptibility of CSCs to the anticancer drug, Temozolomide (TMZ). Furthermore, suppression of NANOG expression led to an accumulation of …

Mindful Approaches, Transforming Hearts: Cultivating Elementary Students' Positive Mathematics Identity Development Through An Equity-Based Morning Mathematics Club, Kayla N. Blankenship

Graduate Thesis and Dissertation 2023-2024

This dissertation examines how third through fifth-grade students' mathematics identities developed through a strengths-based mathematics club focused on equitable teaching practices. In this study, theories of Communities of Practice (Wenger, 1998) and Figured Worlds (Holland et al., 1998) were combined with recommendations from Catalyzing Change (NCTM, 2020) and equity-based practices (Aguirre et al., 2013) to promote students’ positive mathematics identity development. Students with positive mathematics identities have increased mathematics engagement and achievement, and are more likely to seek careers in STEM. Mathematics identities are developed through and influenced by various sociocultural, personal, and educational factors. Incorporating evidence from student surveys, …

Predicting Post-School Outcomes Of Transition Aged Students With High Incidence Disabilities, Jacob Brewer

Graduate Thesis and Dissertation post-2024

This dissertation explores predictive modeling to forecast post-school outcomes for transition-aged students with high-incidence disabilities, such as Specific Learning Disabilities (SLD) and Other Health Impairments (OHI). Transitioning from secondary to post-secondary environments is critical for students with disabilities, significantly impacting their independence, self-confidence, and employability (Morningstar et al., 2017; Carter et al., 2021). Through a mixed-methods approach, this study integrates Office of Special Education Programs (OSEP) indicators to determine which factors most effectively predict post-secondary enrollment and graduation. Key variables such as parental involvement, socio-economic status (SES), and self-determination skills are analyzed using logistic regression and machine learning techniques, including …

A Comparison Of Combined Scoring And Standard Setting Approaches Applied To An Interim Assessment In Predicting Statewide Assessment Performance, Michelle Paul

Graduate Thesis and Dissertation post-2024

The validity of score interpretation and application for specific purposes is dependent upon both the appropriate assignment of test scores and the methods through which those scores are given meaning by defining performance benchmarks. This study seeks to examine the combined utility of various scoring (i.e., number correct, two-parameter logistic, and nominal response model) and standard setting methods in accurately predicting performance on an external assessment. The study will highlight the implementation of the embedded standard setting method, a newer standard setting procedure that is not yet well represented in the literature. Embedded standard setting will be compared to a …

An Exploratory Sequential Mixed Methods Study On Usable Cybersecurity And The Behaviorial Effects Of Cognitive Load, Corey Leong

Graduate Thesis and Dissertation post-2024

This study investigated individuals’ behaviors and perceptions, and actions of a cybersecurity event after reviewing relevant cybersecurity content published in a cyber alert. As new technologies are developed and released, humans experience pressure to defend against threats while at work to remain productive and meet desired organizational goals (Chowdury & Skinner, 2019). The first part of the study randomly assigned participants to respond to a pre-questionnaire followed by an intervention, reading a cyberalert. Participants then answered a post-questionnaire that included the identical questions from the pre-questionnaire, in addition to, biographical and career related questions as well. The second part of …

An Examination Of The Effect Of Instructional Facility Size On Student Achievement In The State Of Florida, Paul B. Tweed

Graduate Thesis and Dissertation post-2024

This correlational study used publicly available Florida Department of Education (FLDOE) data on attributes of educational facilities and student performance to determine the degree of correlation between the physical size of instructional space and student outcomes. The sample used in this study comprised sixty-seven school districts in Florida. A quantitative correlational analysis was utilized to compare the amount of instructional space available to each student in a district and student outcomes in terms of district graduation rates and district scores on statewide assessments. A statistically significant, negative correlation was found between per capita instructional space, district graduation rates, and district …

First Principles Studies Of Nano-Scale Phenomena At Surfaces: From Characteristics Of Single Atom Catalysts To Molecular Structure Formation, Dave I. Austin

Graduate Thesis and Dissertation 2023-2024

The dissertation explores the electronic structures induced by the adsorption of atoms and molecules on surfaces. It focuses on the physical and chemical properties of dispersed metal atom sites on oxide surfaces and the formation of novel molecular structures at hybrid organic-inorganic interfaces. The study uses density functional theory (DFT) calculations to simulate atomic-scale behaviors and aims to contribute to understanding reaction mechanisms and enhancing catalytic activity. Part one investigates the local environments of single platinum atoms on a cerium oxide surface by analyzing their physical and electronic properties. The next part studies the local environments of single platinum atoms …

Exploring Fraction Comprehension And Interest In Elementary Education Through Ai-Powered Personalized Learning, Kenneth Holman

Graduate Thesis and Dissertation post-2024

Fraction proficiency is crucial for foundational mathematics and broader STEM fields. This dissertation investigates the integration of Artificial Intelligence (AI) in mathematics classrooms, with a primary focus on students with mathematical learning challenges. AI technologies offer unique advantages for personalizing instruction and providing tailored feedback. The empirical study in the dissertation addresses a gap in the research related to AI's application during primary school fraction instruction.

The first manuscript presents a comprehensive literature review of AI in mathematics education, synthesizing research from 2020 - 2024. The second manuscript describes a quasi-experimental study evaluating Mathbot, an AI-based personalized learning platform. Repeated …

A Phenomenological Study Of The Impact Of Anti-Woke Legislation On Higher Education, Brittany Knowles

Graduate Thesis and Dissertation post-2024

The events immediately following the COVID-19 pandemic, to include the uptick of hate crimes against Asian-Americans and the murder of George Floyd had a profound impact on public awareness of diversity, equity and inclusion issues. Where initially it appeared, public perception was supportive of the work- in recent years it has come under increasing scrutiny particularly within the academic space. Diversity, Equity, and Inclusion (DEI) work specifically anti-racism has become increasingly polarizing. The decline in public perception of DEI work was marked by the use of simplified catchphrases like woke agendas and CRT in reference to schools. With then presidential …

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 …