Digital Commons Network^™

Barbie Vlogger As Teen Influencer For Little Girls, Brilynn A. Janckila

Dissertations, Master's Theses and Master's Reports

Mattel’s YouTube Barbie Vlogs series (2015-2022) targets 6–11-year-old girls with short narratives and prosocial messages addressing their prevalent interests and everyday experiences. While the vlog is clearly an attempt by Mattel to appeal to a market sector that includes both little girls and their Millennial parents, this analysis examines Barbie Vlogger as a social media influencer in order to explore how little girls learn to become older girls through the performance of teenage girlhood as enacted in the Barbie Vlogs. What is Barbie doing in the vlogs to show little girls who a teen girl is and what she …

Processing And Densification Of Multi-Phase High-Entropy Ceramics, Steven Smith

Doctoral Dissertations

"This work focuses on the processing and densification of multiphase, high-entropy ceramics to promote their use in friction stir welding technologies. Several high-entropy systems including high-entropy borides, carbides, and their composites were produced. Boro/carbothermal and carbothermal synthesis were used to produce high-entropy powders from oxide powder mixtures. Composites of high-entropy borides and high-entropy carbides were produced using a sequential approach to produce both phases. The carbide was first produced using carbothermal reduction, then ZrH2 and B4C were added to the carbide powder to produce the high-entropy boride phase. The resulting powder was densified by spark plasma sintering and pressureless sintering, …

Application Of Artificial Intelligence Techniques To Improve Leadership Decision Making With Uncertainty, Michael David Parrish

Doctoral Dissertations

"Every good leader is a good manager, but not every good manager is a good leader. The difference between the leader and the manager is critical decision-making. Today’s decision-making environment is characterized as Volatile, Uncertain, Complex, and Ambiguous (VUCA). With the exponential increase in the technical capabilities of systems, the human has become the weakest link in the use of such systems. To remain relevant, good leaders must continuously adapt to new advances in technology and processes.

The research contributions of this work provide several unique and novel solutions for leaders to utilize artificial intelligence tools to improve and optimize …

A Hybrid Data Processing, Computational Intelligence, And Complex Systems Modeling Approach For Describing And Predicting The Bitcoin Market, Oluwadamilare Akinpelu Omole

Doctoral Dissertations

"The Bitcoin market, like traditional financial markets, is a complex system with intricate interdependencies and nonlinear interactions among various market elements. This, coupled with the inherent uncertainty and high volatility present, makes predicting Bitcoin price movements difficult. The lack of understanding of the underlying market dynamics often results in significant losses for investors and traders. Existing studies have focused on the use of predictive models, which have not sufficiently captured the complexities of the market and cannot forecast extreme market events. This research endeavors to bridge this gap by combining data processing techniques, computational intelligence, and complex systems theory to …

Atmospheric Transport Of Radionuclides, Meteorological Data Mining & Synthesis For Site Data Supplementation, Ben Yao Sonpon

Doctoral Dissertations

"This research aligns with the NRC's vision of implementing risk-informed decision-making to support its regulatory charter. The suite of tools developed includes automated procedures for data mining and extracting meteorological (met) data from various national and regional repositories. A second data analytics tool automates the process of data fusion into a uniform format while preserving data fidelity. Autocorrelations were then established, and correlation coefficients were calculated between the Callaway Nuclear Power Plant (Callaway) and nearby off-site weather stations. The complexity of these correlations depends on factors such as physical proximity, geographic features, and topology, potentially necessitating multivariate analysis (MVA). Furthermore, …

Lifelong Machine Learning With Adaptive Resonance Theory, Sasha Petrenko

Doctoral Dissertations

"This publication option dissertation is composed of three papers concerning the study of the problem lifelong machine learning with Adaptive Resonance Theory (ART) algorithms. Lifelong learning (L2) is a challenging machine learning paradigm that both encompasses and formalizes the fields of continual learning and incremental learning. The field is concerned with the mitigation of the phenomenon of catastrophic forgetting whereby learning agents that are faced with incrementally novel information deleteriously overwrite previous knowledge if that learning process is not regularized to counteract this consequence. ART algorithms solve this stability-plasticity dilemma by optimally assigning learning to categories or instantiating new knowledge …

Nmr Relaxometry Approach For The Detection Of Asphalt Binder Performance Properties, Rebecca Herndon

Doctoral Dissertations

"Asphalt is a necessary material for transportation infrastructure. Understanding the material properties of asphalt binders is critical for improving infrastructure and enhancing the lifetime of pavements. While the physical properties of asphalt binders are well-defined by standard procedures and parameters, the chemical environment lacks definition. Physical parameters like viscosity and stiffness are traditionally used to differentiate asphalt binders, describe aging, and indicate the impact of additives. However, these tests have limited insight into the material's chemical environment. Therefore, a nondestructive analytical technique, nuclear magnetic resonance (NMR) relaxometry, was employed to investigate the chemical environment of asphalt binders. Although NMR relaxometry …

Sensor Embedding And Thermal Monitoring Strategies For Laser-Foil-Printing Additive Manufacturing, Tunay Turk

Doctoral Dissertations

"This work investigates Laser Foil Printing (LFP), a novel metal additive manufacturing (AM) process that fabricates parts layer-by-layer using metal foils. To enhance LFP productivity, the process steps were optimized, and an 88.1% reduction in processing duration was achieved. A unique aspect of this study was the introduction of laser polishing as an edge polishing technique within the LFP process. This innovative approach, employing an overlapping spiral pattern, leverages selective laser remelting and erosion to effectively suppress elevated edges. To stabilize the molten melt pool, a discrete spot scanning strategy was implemented. The fabricated parts were subjected to detailed analysis, …

New Topologies For High Voltage Gain Dc-Dc Power Electronic Converters – Theoretical Analysis And Experimental Validation, Saeed Habibi

Doctoral Dissertations

"This dissertation is focused on developing and analyzing new high voltage gain DC-DC power electronic converters. The proposed converters in this dissertation are suitable candidates for connecting low voltage sources such as photovoltaic (PV) panels or fuel cell (FC) stacks to a DC microgrid or DC link of an inverter. The proposed converters provide desired characteristics such as high voltage gain at a low or medium duty cycle values, low voltage stress on power semiconductors, and continuous input current. Initially, the research introduces three novel converter topologies: First, two quadratic converters based on the combination of a three-winding coupled inductor …

Advancing Refuge Alternatives In Mine Emergencies Using Advanced Numerical Simulation, Kutay Emre Karadeniz

Doctoral Dissertations

"Incidents and emergencies within underground coal mines can result in severe injuries or even loss of life, particularly due to the hazardous nature of mine explosions. One of the options for the miners to protect themselves from these hazards is to be sheltered in a refuge alternative (RA). However, the literature lacks an analysis of survivability constraints and the structural integrity of RAs when exposed to geomechanical changes and the ability to withstand the impact of coal mine explosions. In this study, based on the utilization and survivability constraints, basic human requirements and the required physical specifications of RAs during …

Vibration Modeling Of Rectangular Plates And Application To Solar Cell Dust Mitigation, Jeremiah John Rittenhouse

Doctoral Dissertations

"Many engineering structures can be modeled as rectangular plates, including solar cells. Carefully controlled plate vibration can be useful to solve an engineering problem, such as lunar dust accumulation on solar cells, which blocks light and reduces power generation. For this application, plate vibration at resonance is studied and used experimentally to eject lunar dust from a solar cell.

Piezoelectric actuator placement on the inactive side of a solar cell to induce vibration dust mitigation from the active side of the cell is presented in this work. Three solar cell prototypes were created and tested for efficacy, resulting in an …

Characterizations Of Eco-Friendly Class C Fly Ash-Based Alkali-Activated Mixtures For Various 3d-Printing Techniques, Fareh Abudawaba

Doctoral Dissertations

This study explored the potential of using high-calcium class C fly ash (FA) as the main precursor for synthesizing alkali-activated mortar (AAM) suitable for 3D-printed concrete (3DPC) applications. The objective was to broaden the selection of AAMs, designed to suit various printing techniques, including continuous mixing and pumping, large batch mixing, and set-on-demand processes. The study began by assessing the fresh properties of various mixtures, utilizing tests such as open time (OT), initial setting time (IST), immediate axial deformation, and penetration test (PT), to determine the mixtures' extrudability and buildability. The study optimized mixtures with a broad spectrum of cycle …

Nano-Micro Engineering For Advanced Energy Devices, Tazdik Patwary Plateau

Doctoral Dissertations

The development of advanced materials and manufacturing techniques for energy storage devices is continuously growing. The research emphasizes micro-engineering, nano-engineering, and advanced materials science, with the goal of enhancing the performance and scalability of manufacturing methods of different materials processing with a view of achieving sustainability. In the micro-engineering domain, novel methods for fabricating thick electrodes with short diffusion paths are introduced, enabling higher mass loading and improved battery performance. Additionally, innovative strategies for optimizing the performance of carbon nanofibers (CNFs) as anode materials in LIBs are explored in the nano-engineering domain. These studies address key challenges such as inter-bonding …

A Comprehensive Analysis Of Climate Resilience Strategies For Small Island Developing States, Ashley-Ann Davis

Doctoral Dissertations

Small Island Developing States (SIDS) face unique and disproportionate challenges in their efforts to achieve climate resilience due to their geographic vulnerabilities, limited resources, and systemic economic and social constraints. This dissertation provides a comprehensive analysis of climate resilience strategies tailored to SIDS, addressing critical systemic issues and exploring interdisciplinary solutions. It synthesizes findings across four interconnected studies, including an analysis of disaster preparedness and response mechanisms in developing countries to identify gaps and opportunities for improving resilience in extreme events. The research investigates economic factors influencing energy portfolio transitions in the Caribbean, emphasizing the complexities of renewable energy adoption. …

Thermal Hydraulics Investigation Of A Horizontal Dual Channel Setup Representing Micro Nuclear Reactors Using Integrated Advanced Measurement Techniques, Zeyad Zeitoun

Doctoral Dissertations

The urgency to reduce greenhouse gas emissions has spotlighted nuclear energy as a carbon-free solution. Despite its promise, nuclear safety concerns, highlighted by the 2011 Fukushima disaster, necessitate advancements in reactor technology. The United States has prioritized the development of safer, prismatic micronuclear reactors for the coming decade, focusing on the safe operation of these facilities. These reactors' design addresses potential hazards, particularly in loss of flow accident scenarios, making the understanding of natural circulation gas flow dynamics critical. Experiments on a horizontal dual-channel plenum-to-plenum facility (P2PF) were conducted to closely mimic the conditions within prismatic micronuclear reactors. This study …

Experimental Investgation Of Core Fluid And Heat Transfer Of Pwr By Using Advanced Measurments Techniques, Saud Aldawood

Doctoral Dissertations

This comprehensive study investigates the thermal-hydraulic mechanisms and convective heat transfer characteristics within (PWRs), with a focus on (SMRs) under both single-phase and two-phase bubbly flow conditions. Specifically, the research investigates the complex bubble dynamics in two-phase flow rod bundles, which are crucial for understanding reactor behavior during loss-of-coolant accidents (LOCA). Employing an advanced experimental setup developed at the (mFReel) at MST, this work measures critical parameters such as void fraction, bubble passage frequency, bubble velocity, bubble chord length, and interfacial area concentration (IAC) using a four-tip optical probe across various locations in the rod bundle. The findings reveal that …

Provenance Of The Uppermost Carboniferous–Lower Triassic Sandstones, Bogda Mountains, Nw China: Implications On The Late Paleozoic Tectonic History Of The Southern Central Asian Orogenic Belt, Sixuan Wu

Doctoral Dissertations

"The Permian-Triassic period represents a significant but insufficiently understood tectonic transition stage in the southern Central Asian Orogenic Belt (CAOB) between the Paleozoic continental amalgamation and Cenozoic orogenic reactivation. This study integrates fieldwork, petrographic, and detrital zircon geochronological data to document the trend of depositional environments, framework grain compositions, and dates of detrital zircon grains of the uppermost Carboniferous–Lower Triassic sandstones from three study areas in Bogda Mountains, the greater Turpan-Junggar basin, NW China, to decipher the spatial and temporal changes in the provenance lithology and area and reconstruct the unroofing history of the southern CAOB.

In the first part …

Metal-Organic Thin Film Coated On Optical Fiber, Nahideh Salehifar

Doctoral Dissertations

This dissertation explores the development of metal-organic framework (MOF)-based optical fiber sensors for detecting volatile organic compounds (VOCs) at low concentrations (parts-per-billion to parts-per-million). In the first part of the study, theoretical calculations were performed using effective medium approximation (EMA) models, including Lorentz–Lorentz, Maxwell–Garnett, and Bruggeman equations, to predict the refractive index changes of MOFs upon gas adsorption. These models were applied to MOFs such as ZIF-7, ZIF-8, ZIF-90, MIL-101(Cr), and HKUST-1 to evaluate their potential for gas sensing.

In the second part of the dissertation, experimental work was conducted to validate the theoretical predictions. MOF-coated optical fibers were fabricated …

Evaluating And Relaxing The Limits On Flexural Reinforcement Ratio Of Masonry Shear Walls, Tousif Mahmood

Doctoral Dissertations

Reinforced masonry shear walls (RMSWs), essential for lateral and out-of-plane load-resisting systems in modern construction are constrained by TMS 402/602 code limits on reinforcement ratios ("ρ" _"max" ) and axial compressive stresses (≤10% of masonry compressive strength, f_m^'), undermining masonry’s inherent compression capacity under high axial loads. This dissertation investigates the seismic performance of reinforced masonry shear walls (RMSWs) subjected to high axial compressive stresses (10–20% of f_m^'), with a focus on walls violating the maximum reinforcement ratio ("ρ" _"max") and axial load limits of TMS 402-22. Through experimental testing of 30 large-scale fully grouted (FG) and partially grouted (PG) …

Measurement Method And Applications Of Transfer Function In Rf Desensitization Problem, Xiangrui Su

Doctoral Dissertations

Radio frequency (RF) desensitization issues comprise two components: noise radiation sources and the transfer function from noise sources to the victim antenna. RFI is a critical challenge in modern electronic systems, particularly in densely packed environments. This work presents a comprehensive study of RFI, addressing key aspects through three novel contributions. First, a transfer function measurement method is developed for compact metallic enclosures. This method provides a precise characterization of the electromagnetic (EM) environment within confined spaces, enabling accurate identification of interference pathways. Second, an EM emission management analysis framework is proposed, leveraging transfer functions to quantify and mitigate interference …

Topics On Ai Fairness Preferences In Kidney Transplantation, Mukund Telukunta

Doctoral Dissertations

Modern kidney transplantation incorporates artificial intelligence (AI) decision-support systems which exhibit social discrimination due to biases inherited from training data. Although researchers have proposed various group-based fairness notions to assess biases in AI, it remains uncertain which criterion is most suitable for evaluating biases in such complex healthcare systems. This dissertation explores human perception of fairness to identify the most appropriate fairness criterion for assessing AI tools in kidney transplantation, focusing on the preferences of non-expert (e.g. public, patients) stakeholders. The study examines two distinct AI systems employed in kidney transplantation: a classification model and a regression model. Human subject …

Deep Learning And Adaptive Clustering Approaches For Flood Prediction And Efficient Sensor Placement In Missouri, Fahimeh Sharafkhani

Doctoral Dissertations

Floods represent formidable natural calamities, posing a significant threat to communities and infrastructure due to their unpredictable and often devastating consequences. The occurrence of floods is influenced by a convergence of meteorological, hydrological, and geographical factors, resulting in changes to the patterns of rising water levels. Machine learning models have emerged as favored tools in recent times for modeling water levels and enhancing the precision of flood predictions. This research employs both supervised and unsupervised machine learning models, with the main objective of improving the accuracy of flood predictions and sensor placement. Four distinct deep learning models are used to …

Design Of Real-Time And Energy-Efficient Driver Assist Systems Using Electroencephalogram And Neuromorphic Computing, Nathan Alan Lutes

Doctoral Dissertations

Despite the technological breakthroughs in advanced driver assist systems, distracted driving persists as a major challenge to roadway safety. This investigation advances the body of knowledge towards a solution by developing an individualized driver-state detection method using electroencephalogram (EEG) and neuromorphic computing to provide a less invasive and more energy efficient ADAS solution. It furthermore explores the changes in brain functional connectivity under distracted conditions to better understand brain state information that could be used for neuro-feedback intervention systems. The first contribution introduces the concept of using Convolutional Spiking Neural Networks (CSNNs) for recognition of patterns with movement-intention predictive power …

Higher-Order Statistics And Normalized Decay Analysis For Detector Deadtime Characterization, Abdallah Wazzan

Doctoral Dissertations

Detector deadtime limits radiation measurement accuracy at high count rates, yet current methods rely on idealized paralyzable or non-paralyzable models. Real detectors exhibit hybrid behavior requiring advanced characterization approaches. This study explores deadtime characterization using two Monte Carlo simulation approaches: higher-order statistical analysis of inter-arrival times and simplified deadtime correction with hybrid models.

Using MATLAB (PULSE-WIZ), we analyzed full decay curves spanning ~4.5 half-lives of Cobalt-60 and Vanadium-52, examining coefficient of variation (CV), skewness, and kurtosis of inter-arrival times, plus normalized decay curves with Full Width at Half Maximum (FWHM) analysis. Hybrid models incorporated paralyzable and non-paralyzable components with dead …

Advancing Thermodynamic Modeling In Materials Design: From Phase Stability In Metallic Systems To Ferroelectric Property Prediction In Functional Oxide, Kyaw Hla Saing Chak

Doctoral Dissertations

This dissertation advances the CALPHAD (CALculation of PHase Diagrams) approach for thermodynamic modeling which often lacks sufficient description of crystal lattices for critical phases in multicomponent system. Additionally, CALPHAD does not consider the structural features and its connection with functional properties for functional materials. To address these issues, a novel dual-ordered sublattice model for the κ-phase in Fe-Al-C system, (Fe,Al)3(Fe,Al)1(C,Va)1(C,Va)3, is introduced that improves predictions of equilibrium compositions and phase stability by accounting for both substitutional and interstitial ordering. For the Fe-B-C system, new sublattice formulations for FCC [(Fe)1(C,B,Va)1] and BCC [(Fe,B)1(C,B,Va)3], phases enhance boron solubility predictions and reveal insights …

Dynamic Response, Assessment, And Retrofitting Of Prestressed Concrete Bridge Girders Subjected To Lateral Impact Loads, Haitham A. Abdelmalek

Doctoral Dissertations

Over height vehicle collisions pose a growing threat to the resilience of bridge infrastructure across the United States. According to the American Road & Transportation Builders Association (ARTBA, 2024), approximately 36% of all U.S. bridges require major repair or replacement, with an estimated cost of $400 billion. This dissertation investigates the structural dynamic response, damage assessment, and retrofitting strategies for prestressed concrete (PC) bridge girders subjected to lateral impact loading.

The research comprised two main phases: (1) numerical modeling and (2) experimental testing. A validated 3D nonlinear finite element (FE) model was developed to conduct parametric studies on impact behavior, …

Nutrient Fate, Mass Balance, Species Selection, And Plant Management Strategies With Floating Treatment Wetlands, Carla Campbell

Doctoral Dissertations

Excess nutrients in shallow urban ponds can lead to harmful algal blooms, low dissolved oxygen, and internal phosphorus cycling. These effects can compromise municipal water supplies and cause negative impacts on fisheries and recreation. Floating treatment wetlands (FTWs) show promise to mitigate surface water nutrient pollution. However, despite recent research, many aspects of FTWs remain poorly characterized. The contribution of FTW components to nutrient removal, local species selection, and plant management strategies were the focus of this dissertation. Mesocosm experiments revealed that the combination of plants and coir fiber growth media in FTWs appeared to positively affect plant biomass gain …

Advancements In Signal Processing And Image Reconstruction For Active Microwave Thermographic Measurements, Logan Martin Wilcox

Doctoral Dissertations

Active microwave thermography, or AMT, is a coupled electromagnetic-thermographic nondestructive testing and evaluation technique. AMT has found success in a variety of inspection needs in the aerospace, space, and infrastructure fields due to its unique type of thermal excitation. During an AMT inspection, a specimen is exposed to microwave energy from a radiating source (i.e., an antenna). This exposure to microwave energy results in dielectric/magnetic heating, which causes an increase in temperature and potential defect indications to manifest on an inspection surface (which is measured via an infrared camera). Due to the use of an antenna, there is a spatially …

Machine Learning Models For Location Prediction, Message Routing And Path Planning For Rescue Of Underground Miners, Abhay Goyal

Doctoral Dissertations

Self-rescue during underground mine disasters is vital for miner safety. Evolving hazards and post-disaster conditions demand solutions that enable navigation under severe communication and computational constraints. Centralized systems often fail in such rugged settings, while decentralized methods—particularly Delay Tolerant Networks (DTNs), proven in battlefields and space missions—offer distinct advantages for underground applications. This research addresses five core challenges: (i) predicting miners’ next locations on low-power devices using points of interest and movement sequences; (ii) delivering timely updates on safe routes, evacuation zones, and hazardous areas; (iii) evaluating energy efficiency and comparing graph-based approaches to existing methods; (iv) enabling edge-ready frameworks, …

Investigating The Effects Of Fly Ash On The Properties Of Silica-Deficient High Alumina Materials, Sai Akshay Ponduru

Doctoral Dissertations

This research is made up of five studies mainly focused on attaining sustainability in high alumina cements like calcium aluminate cement (CAC) and calcium sulfoaluminate belite cements (CSAB) by partially replacing them with additives and supplementary cementitious materials (SCMs) like fly ash (FA). The first study focused on understanding the reaction kinetics of CAC and FA binders at different replacement levels (i.e. between 10%-to-50% by mass) and their effect on mechanical properties. It was also shown that the reactive nature of FAs can be determined by calculating a single parameter called number of constraints (nc) derived from topological constraint theory. …