Digital Commons Network^™

Hear Their Voices: Black Male Student Perceptions Of Retention Initiatives At An Hsi In The Midwest, Joshua Watson

Dissertations

The enrollment of Black male students in colleges and universities over the last 30 years increased yet Black male retention rates have not increased proportionately to the enrollment rates of Black male students. Many colleges and universities recognized the importance of increasing Black male retention and invested millions of dollars in Black male retention initiatives, mentorship initiatives as well as hiring additional staff dedicated to Black male retention. Black male students use a variety of social support systems and coping strategies to persist in college despite facing economic, social, and political barriers to persistence. However, many Black male retention initiatives …

The Fourth Wall Of Dialogue: A Co-Constructive Collaboration On Bipoc Student Sense Of Belonging In Higher Education, Valarie Lindsey

Dissertations

Black, Indigenous, People of Color (BIPOC) students’ sense of belonging (SOB) at higher education institutions has decreased over the last 30 years despite numerous initiatives aimed at increasing a sense of belonging for this group of students and addressing the challenges they face from various intersectionalities including cultural biases, gender marginalization, and racial subjectivities. Sense of belonging is often subjective in nature because it refers to an individual's lived experience, it is important for higher education institutions to tailor their Diversity, Equity, and Inclusive (DEI) initiatives to meet the needs of the students on their campus. This initiative should include …

Why Not Community College As A Pathway To A Degree, Gretchen Jorndt Reyes

Dissertations

This qualitative phenomenological study aimed to understand if Gen X parents are motivating their Gen Z students' college choice not to attend community college. The few studies that focused on parent involvement in choosing a community college did not focus on the generational differences between parents and their children when it came to college choice, they also did not focus on whether parents influenced their children to attend community college or not (Bers, 2005; Bers & Galowich, 2002).

The study explored Ajzen’s Theory of Planned Behavior and how his theory and the college choice process are intertwined during the college …

A Program Evaluation Of 3de Schools By Junior Achievement, Audra Lewis-Hoesch

Dissertations

3DE Schools by Junior Achievement is a framework for instruction designed to reshape the instructional ecosystem through a high school model that uses project-based learning and case-study methodology to help students acquire core competencies. The context of this inquiry includes various states in America where 3DE Schools are implemented. I utilized a mixed methods approach to collect data and gauge the influence of the 3DE instructional framework on students' readiness for college and career pursuits. Key outcomes showed that students in 3DE cohorts scored higher in math and English than the national average, contributing to an overall higher graduation rate …

The Role Of Work-Based Learning In Developing Future Skills And Competencies For The Workforce In The Fourth Industrial Revolution, Dorith Johnson

Dissertations

The study investigated the impact of work-based learning on developing skills and competencies required for the Fourth Industrial Revolution. Educators must adapt to what students need to succeed in this era. In this study, seven participants who oversee or have overseen a portion of various work-based learning initiatives engaged in a semi-structured interview process. The interview questions inquired about teacher preparation, practical strategies, programs or models of work-based learning, challenges and limitations, sustainability, and the impacts of different work-based models on employability skill development. The results provide hope that work-based learning can play a crucial role in today’s more technologically …

A Modified Grounded Theory Analysis Of Luke’S Understanding Of His Thought Disorder, Daniel Dresher

Dissertations

This current Clinical Research Project examines patterns of therapeutic processing in “Luke”, a male diagnosed with schizophrenia, and how his understanding of his psychotic breaks and mental illness evolved over the course of person-centered psychotherapy. A modified grounded theory approach was used by multiple coders to analyze transcribed text samples from selected archival therapy sessions selected between 1996 and 2019 to develop further hypotheses as to how "Luke" uses schizophrenic language to process experience in ways that are clinically effective as well as ways that hinder his understanding of his experience. Results of this study demonstrated that while Luke’s use …

Printed Graphite Electrodes For Fast-Charging Lithium-Ion Batteries, Guanyi Wang

Dissertations

The rapid growth of the electric vehicle (EV) market has demanded lithium-ion batteries (LIBs) with high energy density and fast charging capability. However, charging energy-dense LIBs with thick graphite electrodes at high current densities is typically facing challenges and leading to adverse performance, such as low energy density, short cycle life, rapid temperature rises and safety issues. The root cause is the onset of Li plating. During fast charging application, the sluggish lithium ions accumulated at the surface of graphite due to kinetic limitation and formed Li plating, especially when lithiated to a high state of charge (SOC). It has …

Empirical Exploration Of Software Testing, Samia Alblwi

Dissertations

Despite several advances in software engineering research and development, the quality of software products remains a considerable challenge. For all its theoretical limitations, software testing remains the main method used in practice to control, enhance, and certify software quality. This doctoral work comprises several empirical studies aimed at analyzing and assessing common software testing approaches, methods, and assumptions. In particular, the concept of mutant subsumption is generalized by taking into account the possibility for a base program and its mutants to diverge for some inputs, demonstrating the impact of this generalization on how subsumption is defined. The problem of mutant …

Sustainable And Cost-Effective Work Zone Scheduling On Two-Lane Highways With Managed Lanes, Ahmed Z. Edrees

Dissertations

Roadway maintenance projects greatly influence the roadway capacity, resulting in potential traffic disturbances captured by delays. Additionally, costs associated with these projects tend to be exorbitantly extensive. Most agencies and planners try to find a solution that minimizes roadway maintenance costs, traffic delays, crash risks, and environmental impact.

Work zones on two-way two-lane roadway typically avoids high-demand periods. Lane-closure scenario is commonly used and converts the open lane into a phantom intersection, alternating two-direction movements on one lane with the help of a flagger or a temporary signal. Alternatively, using shoulders as temporarily managed lanes allows for simultaneous two-way movements …

Network Slicing And Noma Enabled Mobile Edge Computing For Next-Generation Networks, Mohammad Arif Hossain

Dissertations

The advent of next-generation wireless networks ushers in a new era of potential, harnessing cutting-edge technologies like mobile edge computing (MEC), non-orthogonal multiple access (NOMA), and network slicing as pivotal drivers of transformation. Within this landscape, an innovative approach is proposed by introducing a NOMA-enabled network slicing technique within MEC networks. This approach aims to achieve multiple objectives: meeting stringent quality of service requirements, minimizing service latency, and enhancing spectral efficiency. By seamlessly integrating NOMA with network slicing in edge computing environments, significant reductions in overall latency are achieved, alongside ensuring optimal resource allocation for NOMA users. To address these …

Integrating Laser Charging And Drones For Secure Edge Computing, Weiqi Liu

Dissertations

Drone-mounted base stations (DBSs) have emerged as a promising solution to enhance the flexibility and coverage of wireless networks, potentially revolutionizing communication systems. This dissertation explores the integration of DBSs into 5G and beyond networks, focusing on methodologies to optimize their deployment and performance. A laser charging-enabled DBS framework is proposed to extend flight time and enhance network coverage. By leveraging laser charging technology, the DBS can receive continuous energy transmission from a ground-based charging station while providing communication services to users. The framework is formulated as an optimization problem to jointly maximize flight time and communication data rate, while …

On The Ubiquity, Properties And Evolution Of Small-Scale Magnetic Flux Ropes In The Heliosphere, Hameedullah Farooki

Dissertations

The solar wind is a plasma constantly blowing out from the Sun with a large-scale magnetic field having significant local complexity at small scales. Small-scale magnetic flux ropes (SMFRs), plasma structures with twisted field lines, are an important element of this complexity. This dissertation contributes several studies that further our understanding of SMFRs. The first study applies machine learning to measurements from Wind labeled by the presence of SMFRs and magnetic clouds (MCs). MCs were distinguished from non-MFRs with an AUC of 94% and SMFRs with an AUC of 89% and had distinctive plasma properties, whereas SMFRs appeared to be …

Computational Microscopy For Biomedical Imaging With Deep Learning Assisted Image Analysis, Yuwei Liu

Dissertations

Microscopy plays a crucial role across various scientific fields by enabling structural and functional imaging with microscopic resolution. In biomedicine, microscopy contributes to basic research and clinical diagnosis. Conventionally, optical microscopy derives its contrast from the amplitude of the optical wave and provides visualization of the physical structure of the sample qualitatively. To understand the function at the cellular or tissue level, there is a need to characterize the sample quantitatively and explore contrast mechanisms other than light intensity. Image enhancement or reconstruction from microscopic imaging systems is known as computational microscopy, and it involves the application of computational techniques …

Interaction Of Particles With Plasma And Shock Produced By Pulsed Spark Discharge, Shomik Mukhopadhyay

Dissertations

Interactions of powders with high-temperature plasma and shockwaves occur in diverse scenarios, such as nuclear blasts, accidental industrial dust explosions, solid propellant combustion in explosive charges and when removing contaminants from surfaces. Electrostatic Discharge (ESD), known for generating shock and plasma, is a promising lab-scale technique for simulating these interactions. Studies with ESD involved placing powders near a spark-producing gap between electrodes and observing mechanical and chemical processes like particle motion and ignition. A limited range of spark conditions and material properties have been tested, which facilitated the development and validation of preliminary computational models describing this system. Significant gaps …

Machine Learning-Based Design Of Doppler Tolerant Radar, Kyle Peter Wensell

Dissertations

In this work, machine learning theory is applied to the design of a radar detector in order to train a machine learning-based detector that is robust against Doppler shifts. The radar system is designed to work with data that would be otherwise intractable to conventional optimal detector design, such as transmitted noise waveforms and the effects of one-bit quantization at the receiver. The detection performance of the one-bit receiver is shown to match the performance of the derived square-law sign correlator detector. The resulting learning-based detector also introduces Doppler tolerance to the system, which allows for the successful detection of …

Decentralized Control Of Renewable Generation Systems, Milad Shojaee

Dissertations

As the global community struggles with the escalating challenges of climate change and environmental degradation, the transition to renewable energy sources has emerged as a paramount solution. Harnessing energy from renewable sources such as solar, wind, and hydro power not only alleviates the adverse effects of conventional fossil fuel energy sources, but also establishes a foundation for a sustainable and resilient future. Microgrids have been utilized as a feasible platform to integrate renewable energy sources into the electrical power generation networks. They include one or more generation units connected to nearby users, and are able to operate in both grid-connected …

Information Theoretic Bounds For Capacity And Bayesian Risk, Ian Zieder

Dissertations

In this dissertation, the problem of finding lower error bounds on the minimum mean-squared error (MMSE) and the maximum capacity achieving distribution for a specific channel is addressed. Presented are two parts, a new lower bound on the MMSE and upper and lower bounds on the capacity achieving distribution for a Binomial noise channel. The new lower bound on the MMSE is achieved via use of the Poincare inequality. It is compared to the performance of the well known Ziv-Zakai error bound. The second part considers a binomial noise channel and is concerned with the properties of the capacity-achieving distribution. …

Financial Time Series Fusion, Completion, And Prediction With Deep Neural Networks, Dan Zhou

Dissertations

Time-series analysis is essential for a wide range of financial applications, including but not limited to bond valuation, firm earnings forecasts, firm fundamentals predictions, and firm characteristics imputations. Given its considerable value, the financial community has shown a strong interest in refining and advancing time-series analysis techniques. The study in this dissertation contributes to this field by employing advanced machine learning approaches, specifically graph neural networks, deep neural networks, and matrix/tensor methods. The primary objectives are twofold: first, to reveal complex correlations within financial time series to improve prediction accuracy, and second, to enhance the process of integrating and imputing …

Sensing With Integrity: Responsible Sensor Systems In An Era Of Ai, David Eisenberg

Dissertations

Deep and machine learning now offer immense benefits for consumer choice, decision-making, medicine, mental health and education, smart cities, and intelligent transportation and driver safety. However, as communication and Internet technology further advances, these benefits have the potential to be outweighed by compromises to privacy, personal freedom, consumer trust, and discrimination. While ethical consequences for personal freedom and equity rise from these technological advances, the issue may not be the technology itself but a lack of regulation and policy that allow abuses to occur. A first study examines how emerging sensor-based technologies, limited to only accelerometer and gyroscope data from …

A Molecular Dynamics Study On The Destruction Mechanism Of Per And Polyfluoroalkyl Substances Due To Ultrasound Technology, Bruno Bezerra De Souza

Dissertations

Per- and polyfluoroalkyl substances (PFAS) are a group of stable synthetic chemicals that are highly persistent and harmful pollutants to the environment and human health. PFAS have caused a strong public and regulatory response due to their ubiquitous presence in the environment and toxicity to humans. The application of ultrasound is one of the most effective treatment technologies for the mineralization of PFAS in contaminated water. However, this technology is treated as a black box causing the inability to be optimized. Therefore, there is a pressing need to investigate the intricate dynamics of PFAS degradation under ultrasound to unlock its …

Molecular-To-Continuum Scale Modeling Of Aerosols: Atmospheric Application And Beyond, Ella Ivanova

Dissertations

Aerosol modeling is critical for various applications, such as climate forecasting, air quality, and human health impact assessment. During their lifetime, aerosols undergo a complex evolution, usually divided into several stages — formation, processing, transport, and removal — that occur on different scales. Thus, the choice of modeling methods depends on the stage considered. For example, certain stages of particle formation may require nano-scale modeling while aerosol-cloud interactions span from microscale to mesoscale. This study examines the modeling of aerosol behavior over a wide range of scales, from nano to microscale, with implications to mesoscale.

This dissertation focuses on two …

Microplastic Abundance And Removal In Stormwater Using Green Infrastructure, Meghana Parameswarappa Jayalakshmamma

Dissertations

Microplastics (MPs) are increasingly recognized as a pervasive environmental contaminant, conveying other contaminants, accumulating in aquatic organisms, and posing ecological risks. The existing research has primarily focused on MPs in wastewater treatment plant effluents in surface waters. However, the role of stormwater systems in MP transport has been less explored. Given the rise in MPs from urban sources, stormwater runoff from urban areas may serve as a critical conduit for transporting land-based MPs into aquatic environments. Green infrastructures (GIs) have been recognized for mitigating flooding and improving water quality from minor storms by trapping stormwater pollutants. Yet, the capability of …

A Machine Learning-Assisted Steering And Scheduling Framework For Big-Data Scientific Workflows On Heterogeneous Computing Platforms, Yijie Zhang

Dissertations

In next-generation scientific applications, the exponential growth of big data necessitates advanced techniques for efficient data storage, processing, and analysis. This has led to the construction of intricate computing workflows, managed and orchestrated by powerful engines in big data systems as exemplified by Hadoop. As scientific applications increasingly shift towards simulation-centric approaches, traditional methodologies face new challenges in accommodating the complexity of extreme-scale numerical modeling with numerous tunable parameters. To address these challenges, this dissertation propose to develop a machine learning-assisted framework that enables autonomous computational steering of scientific simulations and optimized execution of big-data workflows on heterogeneous platforms. This …

Reproducible Fluid Structure Interaction For Complex Flows In Engineered Systems, Allen Prasad Varghese

Dissertations

This dissertation focuses on the application of numerical models to study Fluid Structure Interaction (FSI) in the industrial context. The emphasis is on a series of case studies belonging to practical applications in design and manufacturing and that are solved by a synergistic use of theoretical and computational models. The first study looks into the hydrodynamic actions experienced by vibrating slender structures immersed in viscous fluids near the free surface. This study case is relevant to applications such as, for example, marine propulsion, micro-electro-mechanical systems, and atomic force microscopy. The hydrodynamic problem is governed by three parameters, namely the frequency, …

Development Of Super Hydrophobic Membranes And Their Applications, Sumona Paul

Dissertations

Effective liquid phase separation is vital across industries, especially in aviation, chemicals, fuels, and textiles. Membrane technology offers advantages over traditional methods like distillation, with low energy consumption and protection for heat-sensitive molecules. Membrane performance is assessed based on factors such as materials, surface modification, and interactions. This research targets superhydrophobic membranes for liquid-liquid filtration and antiwetting omniphobic membranes for membrane distillation, focusing on properties like contact angle and thermal resistance.

This study presents a highly hydrophobic membrane achieved by immobilizing carbon nanotubes (CNTs) onto a PTFE microfiltration membrane. It's designed for dewatering organic-water mixtures with trace water content via …

Building Agency Through Sensemaking: The Transformational Journey And Identity Development Process Of Working Mother Leaders During The Covid-19 Pandemic, Lynn Levis

Dissertations

Working mothers in America have long juggled a multitude of responsibilities while navigating several systemic barriers in the very society that claims to support them. The COVID-19 pandemic had an outsized impact on mothers when children were sent home from daycares and schools to reduce the spread of the virus. This study sought to address an important gap in the literature by using a mixed methods constructivist grounded theory approach to examine how working mothers in leadership positions navigated their various roles and systems during the COVID-19 pandemic. Data collection consisted of a survey with 105 respondents, followed by individual, …

Evaluating The Health Literacy Practices Of A Primary Care Health System Serving A Diabetic Population At High Risk For Low Health Literacy, Alana D. Norris-Bermudez

Dissertations

Health literacy (HL) is a powerful determinant of patient health outcomes, yet a minority of the U.S. population possesses proficient health literacy. Healthy People 2030 positions HL prominently among the new overarching goals as follows, "Eliminate health disparities, achieve health equity, and attain health literacy to improve the health and well-being of all" (The Office of Disease Prevention and Health Promotion, 2023). HL comprises two interlinked components: personal HL and organizational HL, (Office of Disease Prevention and Health Promotion, n.d.). Implementing HL practices within healthcare system facilities such as hospitals, FQHCs, and/or primary care practices to support universal HL precautions …

A Non-Weight Centered Approach To Modifying Eating Attitudes In Polycystic Ovarian Syndrome, Jo'quishia A. Lethermon

Dissertations

Polycystic Ovarian Syndrome (PCOS) is an anovulatory disorder characterized by insulin resistance and endocrine dysfunction. Infertility and abnormal weight gain in women of childbearing age are often a result of PCOS, impacting quality of life and posing potential long-term health sequelae. Prescribing weight loss has been adopted by clinicians as an effective intervention to improve insulin resistance. For some patients, this practice has led to the negative effects of weight cycling and disordered eating attitudes which can result in long term adverse cardiometabolic outcomes. A quasi-experimental pre-and-post-test study was conducted to evaluate how a non-weight centered program influences eating attitudes …

Wellness Promotion Quality Improvement Project, Jacqueline K. Cantor

Dissertations

The purpose of this capstone project was to bring evidence-based wellness promotion through physical activity (PA) using the World Health Organization (WHO) (2020) guidelines to Psychiatric Mental Health Advanced Practice Nurses (PMH-APRNs) to improve mental health care and provider self-care. The guiding PICOT question was "For PMH-APRNs in community-based mental health practices, will the consistent implementation of the evidence-based intervention of a wellness prescription promoting physical activity based on WHO's (2020) PA Guidelines, compared to no consistent use in current practice, increase the promotion/prescription of PA to their mental health patients and increase the PMH-APRNs' own physical activity over eight …

Influence Of Social Media On Mothers' Decision-Making Regarding Vaccinations, Wendy M. Patterson

Dissertations

This study involved determining why mothers hesitate to vaccinate their children and where they get their information about vaccinations. This descriptive qualitative study guided by the health belief model explored the influence social media has on mothers' perceived barriers to vaccinating their children. A descriptive qualitative approach was used, and one-on-one audio interviews were conducted via Zoom or in person with 19 participants. Participants were mothers 19 or older, had children between zero and 18, made medical decisions for their children who resided in their household, and sought information about vaccinations via healthcare providers, social media platforms, friends, or family. …