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Advanced Mass Spectrometry Method Development And Applications For Assessment Of Traumatic Brain Injury And Legionella Pneumophila Dissinfection With Copper, Austin Chase Sigler Jan 2024

Advanced Mass Spectrometry Method Development And Applications For Assessment Of Traumatic Brain Injury And Legionella Pneumophila Dissinfection With Copper, Austin Chase Sigler

Doctoral Dissertations

"Pathological processes often involve complex biochemical changes which can be assessed using advanced mass spectrometry. In this present dissertation, two fields were studied: traumatic brain injury (TBI), and water contamination by L. pneumophilia. TBI is a pressing public health concern for which current clinical tools remain inadequate. We present newly developed mass spectrometric methods to access metabolites associated with blast induced TBI. We applied these methods to the biofluids of soldiers conducting explosives training. Significant changes in several metabolites were observed between pre- and post-blast specimens, including changes that increased with repeated exposure. These changes point to the possibility of …


Additive Manufacturing Of Steel And Aluminum Structures: Modeling And Experiments, Manoj Kumar Reddy Rangapuram Jan 2024

Additive Manufacturing Of Steel And Aluminum Structures: Modeling And Experiments, Manoj Kumar Reddy Rangapuram

Doctoral Dissertations

"Additive manufacturing (AM) is defined as the process of joining materials to make objects from three-dimensional model data. Complex geometries can be easily manufactured compared to conventional subtractive methods with more freedom and flexibility in the design process. As the demand for AM process increased, it has become critical to understand the process and various parameters that constitute in affecting the quality of the manufactured part. Conducting experiments can be time intensive and costly to optimize a process. Modeling can be used as an aid to optimize, examine, and predict the process outcome.

The objective of this study is (i) …


Deep Learning Techniques For Image Segmentation In Dermoscopic Skin Cancer Images, Norsang Lama Jan 2024

Deep Learning Techniques For Image Segmentation In Dermoscopic Skin Cancer Images, Norsang Lama

Doctoral Dissertations

"Melanoma is recognized as the most lethal type of skin cancer, responsible for a significant proportion of skin cancer-related deaths. However, early detection of melanoma is essential for successful treatment outcomes. Computer-aided skin cancer diagnosis tools can save lives by enabling earlier detection of skin cancer. Image segmentation is a crucial step in computer-aided diagnosis as it allows the detection of critical features or regions in an image. Thus, an accurate image segmentation method is necessary to create a more precise computer-aided diagnostic tool for skin cancer diagnosis. This dissertation includes investigating and developing deep learning techniques to improve image …


Improvements In Biomedical Image Analysis With Computational Intelligence And Data Fusion Techniques, Akanksha Maurya Jan 2024

Improvements In Biomedical Image Analysis With Computational Intelligence And Data Fusion Techniques, Akanksha Maurya

Doctoral Dissertations

"An estimated 2 million new cases of basal cell carcinoma (BCC) are diagnosed each year in the United States, making it one of the most common skin cancers. Earlier detection of these cancers enables less invasive biopsies. Clinical detection consists of a preliminary visual observation of these skin lesions by an experienced dermatologist making it a specialized task highly dependent on their time, availability, and resources. Hence, there is a need for automating this process that can assist healthcare staff. In recent years, deep learning (DL) has been used extensively and successfully to diagnose different cancers in dermoscopic images. Telangiectasia …


Understanding Catalyst Design Principles In Transition Metal Mixed Anionic Chalcogenides For Electrocatalytic Energy Conversion, Ibrahim Abdullahi Jan 2024

Understanding Catalyst Design Principles In Transition Metal Mixed Anionic Chalcogenides For Electrocatalytic Energy Conversion, Ibrahim Abdullahi

Doctoral Dissertations

"This research focused on the synthetic design of transition metal mixed anionic chalcogenide catalysts containing various ligand types around the central metal atom (chalcogen anion and chalcogen-based organic ligand) generating diverse crystal structure types applied for water splitting and carbon dioxide reduction reactions (CO2RR).

A series of catalysts were synthesized starting with isolated metal complexes (MEn) with a central metal core (M = Co, Ni, Cu, and Cr) through molecular clusters, to bulk nanostructured solids of similar M-E coordination. Bis(dichalcogenoimidodiphosphinato) were employed as ligands in the metal complexes, and anionic chalcogen (E = S, Se, and …


Semiconductor Physics Based Signal Integrity Analysis For 3d Ic, Ze Sun Jan 2024

Semiconductor Physics Based Signal Integrity Analysis For 3d Ic, Ze Sun

Doctoral Dissertations

"Three-dimensional integrated circuits (3DICs) are becoming increasingly popular in high-speed electrical systems. 3DICs are made by stacking multiple dies vertically and connecting them with through-silicon vias (TSVs). In this dissertation, three studies were carried out to model the performance of 3DICs in extreme working conditions and the signal integrity (SI) performance of 3DICs.

First, an in-house Monte Carlo particle simulator was developed to characterize extreme working conditions (ESD/EMP) for ICs at the microscopic level instead of the macroscopic level. The ability of the simulator was demonstrated by modeling a voltage regulator diode under forward and reverse bias. The diode simulation …


Improving Decision-Making Processes In Construction And Infrastructure Bidding: Qualitative And Quantitative Approaches Including Graph Theory, Game Theory, And Machine Learning, Muaz Osman Elzubeir Ahmed Jan 2024

Improving Decision-Making Processes In Construction And Infrastructure Bidding: Qualitative And Quantitative Approaches Including Graph Theory, Game Theory, And Machine Learning, Muaz Osman Elzubeir Ahmed

Doctoral Dissertations

"Construction and infrastructure bidding is a highly competitive process that entails various uncertainties faced by contractors. Contractors weigh various factors to determine the expected benefits of a construction project and decide their bid value. However, the situation is more complex in multi-stage bidding (MSG), where general contractors must account for the bids of their subcontractors and face a greater threat of the winner’s curse (i.e., situation where the winning contractor underestimates the actual cost of the project). As such, bidding-related complexities, risks, and uncertainties, if uncontrolled, can lead to the rise of claims and disputes between stakeholders. Existing research falls …


Development Of Uas And Geophysical Techniques For Agriculture And Environmental Site Characterization, Yunyi Guan Jan 2024

Development Of Uas And Geophysical Techniques For Agriculture And Environmental Site Characterization, Yunyi Guan

Doctoral Dissertations

"Soil properties are critical for agricultural management. Geophysical techniques such as ground penetrating radar (GPR) and electromagnetic induction have been used to measure soil properties for agricultural applications. However, their measurements are only acquired along select traverses within a field, and the data processing can be time-consuming, the instruments can also be expensive. Unmanned aerial vehicles (UAVs) are a recent advancement used for precision agriculture. Compared with geophysical data, UAVs have higher resolution and wider coverage and can quickly collect data across the whole field. The operation is also relatively simpler with a more economical acquisition cost. This research investigates …


Non-Linearity Modeling And Quantifications For Practical Rf Interference Control, Shengxuan Xia Jan 2024

Non-Linearity Modeling And Quantifications For Practical Rf Interference Control, Shengxuan Xia

Doctoral Dissertations

"Radio frequency (RF) interference can degrade the receiving sensitivity of antennas (desense problem). It is essential to model the nonlinearity as it is the root-cause of the unwanted frequency components. Understanding the electromagnetic (EM) coupling or radiated emissions is also important.

Nonlinearity causes modulation-involved desense problems, and it consists of two categories: upconvertion of the baseband noise by the transmitting (TX) signal, and the passive intermodulation (PIM) of the transmitting signal itself. The upconvertion caused desense can be modeled and analyzed with the dipole-moment based coupling framework. PIM has been identified as another nonlinear distortion mechanism, specifically in the metallic …


Modeling And Analysis Of Dc-Dc Converters For Power Distribution Networks Design, Junho Joo Jan 2024

Modeling And Analysis Of Dc-Dc Converters For Power Distribution Networks Design, Junho Joo

Doctoral Dissertations

"Accurate modeling of power distribution networks (PDN) including voltage regulator module (VRM) is critical for high-performance digital systems including low- to high-power applications such as laptops and mobile platforms. As a consolidated end-to-end power source, PDN can be divided into several parts: the VRM to regulate the external voltage source, printed circuit board (PCB) PDN, package PDN, and on-chip PDN. A transient current drawn from the on-die circuitry will produce an instantaneous voltage drop at the bump. The time domain behavior of such a drop and the subsequent recovery is called voltage droop which is strongly associated with the VRM …


Methodology For Parameter Determination For Simulation Software, Aaron Flood Jan 2024

Methodology For Parameter Determination For Simulation Software, Aaron Flood

Doctoral Dissertations

"This research aims to present a methodology for optimizing input datasets to increase the accuracy of mathematical models and accelerate their application to engineering problems. To accomplish this goal, this work focused on the application of mathematical models to metal additive manufacturing (AM), specifically the thermal history of laser directed energy deposition (DED) of aluminum alloys. The initial steps of this body of work were to develop a mathematical model that is capable of simulating the metal AM process and applying it to the laser DED of aluminum. It was validated using the well characterized material Ti-64 and shown to …


Secure And Privacy-Preserving Federated Learning With Rapid Convergence In Leo Satellite Networks, Mohamed Elmahallawy Jan 2024

Secure And Privacy-Preserving Federated Learning With Rapid Convergence In Leo Satellite Networks, Mohamed Elmahallawy

Doctoral Dissertations

"The advancement of satellite technology has enabled the launch of small satellites equipped with high-resolution cameras into low Earth orbit (LEO), enabling the collection of extensive Earth data for training AI models. However, the conventional approach of downloading satellite-related data to a ground station (GS) for training a centralized machine learning (ML) model faces significant challenges. Firstly, the transmission of raw data raises security and privacy concerns, especially in military applications. Secondly, the download bandwidth is limited, which puts a stringent limit on image transmissions to the GS. Lastly, LEO satellites have sporadic visibility with the GS, and orbit the …


Communication Modality And Activity Recognition In Smart Manufacturing, Haodong Chen Jan 2024

Communication Modality And Activity Recognition In Smart Manufacturing, Haodong Chen

Doctoral Dissertations

"Advancements in sensors, computational intelligence, and big data have been rapidly transforming and revolutionizing the manufacturing sector, leading to robot-rich and digitally connected factories. To facilitate such a transformative process, workforce training and coordination between the human workforce and robots have remained a major challenge. This study aims to create intelligent workforce training systems for human-computer interaction and human-robot collaboration. It proposes the use of dynamic gestures and speech commands for seamless communication between a worker and a robot, leveraging Convolutional Neural Networks (CNN) and multiple threading for recognition and integration. Additionally, a fine-grained activity recognition model has been crafted …


Modeling And Control For Precision Robotic Machining, Patrick Bazzoli Jan 2024

Modeling And Control For Precision Robotic Machining, Patrick Bazzoli

Doctoral Dissertations

"Robots are used in a wide variety of manufacturing applications, but machining applications in which robots can excel are limited by their lower accuracy and stiffness relative to traditional CNC machines. This work is composed of two parts: one to evaluate a robot’s accuracy and one to compensate for the vibrations of the robot due to its lower stiffness.

In order to evaluate whether a robot has the necessary accuracy to perform a given machining task, Paper 1 discusses a novel Model Invalidation method. This methodology provides a statistical framework as well as a measurement strategy for determining if a …


Dynamics And Inverse Problems For Nonlinear Schrödinger Equations, Christopher Hogan Jan 2024

Dynamics And Inverse Problems For Nonlinear Schrödinger Equations, Christopher Hogan

Doctoral Dissertations

"The cubic nonlinear Schrödinger equation (NLS) is a model of interest in the study of physical problems including nonlinear optics and Bose-Einstein condensates. Of particular interest is the study of cubic NLS with inhomogeneities such as localizations of the nonlinearity or terms introducing potential barriers. We first address some preliminaries and techniques useful in the study of the cubic NLS and its variations. We then consider the cubic NLS with a localized nonlinearity in dimensions d ≥ 2. We show that solutions with data given by small-amplitude wave packets accrue a nonlinear phase that determines the X-ray transform of the …


Applications Of Computational Intelligence And Data Fusion Techniques For Biomedical Images, Anand Krishnadas Nambisan Jan 2024

Applications Of Computational Intelligence And Data Fusion Techniques For Biomedical Images, Anand Krishnadas Nambisan

Doctoral Dissertations

"The realm of melanoma diagnosis has been significantly advanced by deep learning (DL) techniques, yet the current approaches are not without limitations, including missed diagnoses and the challenge of interpreting these "black box" models. The research is comprised of three studies, each contributing uniquely towards advancing melanoma detection accuracy and interpretability. The first study focuses on improving the detection of specific dermoscopic structures through a deep learning-based segmentation approach, while the second study builds upon this by employing a fusion technique that combines traditional image features with advanced deep learning models. This method significantly improves melanoma detection, particularly in recall …


Mission-Driven Inverse-Design Of Conventional And Unconventional Airplane Configurations Using Machine Learning, Rohan Srinivas Sharma Jan 2024

Mission-Driven Inverse-Design Of Conventional And Unconventional Airplane Configurations Using Machine Learning, Rohan Srinivas Sharma

Doctoral Dissertations

"A key challenge in airplane design has been the long-desired ability to quickly create an airplane design with specific performance properties. To tackle this problem, researchers have traditionally leveraged design space exploration methodologies to iteratively explore a design space via surrogate models. On the other hand, inverse design is a process wherein performance objectives are fixed while a suitable design for satisfying these requirements is calculated. In recent years, artificial neural networks (ANNs) have been explored as viable surrogate models because traditional surrogate models struggle with the large number of output to input mapping needed for inverse design problems. In …


Exploring Seismic Anisotropy In The Crust And Mantle Of The Tibetan Plateau And Analyzing Seismic Velocity Variations In Yellowstone, Cong Shen Jan 2024

Exploring Seismic Anisotropy In The Crust And Mantle Of The Tibetan Plateau And Analyzing Seismic Velocity Variations In Yellowstone, Cong Shen

Doctoral Dissertations

"Seismology is a scientific discipline that utilizes seismic waves to investigate the deep structures within the Earth's interior, which are otherwise inaccessible to direct observation by humans. These seismic waves can be categorized into two types: body waves and surface waves, each with distinct propagation modes and behaviors, carrying valuable information about their travel paths. The first paper concentrates on the analysis and inversion of body waves produced by large seismic events. It employs shear wave splitting and receiver function methods to explore the geodynamic structure of the south-central Tibetan Plateau, near the plate boundary. The investigation covers the depth …


Accurate And Time Efficient Signal Integrity And Power Integrity Modeling Of High-Speed Digital Systems, Chaofeng Li Jan 2024

Accurate And Time Efficient Signal Integrity And Power Integrity Modeling Of High-Speed Digital Systems, Chaofeng Li

Doctoral Dissertations

"Signal integrity (SI) and power integrity (PI) play an important role in the modern high-speed digital system design, which are closely related to the printed circuit board (PCB) dielectric material property, the PCB interconnect performance, and the power delivery network (PDN) on PCB. Generally, the full-wave simulation is used to accurately analyze and evaluate the designed PCB. But full-wave simulation is not a good option for the complex PCB structure with high aspect ratio, for example, PCB vias, and PDN, which will require significant computing time and storage resources. Equivalent circuit models have been developed to efficiently predict the electrical …


Kinetic Modeling And Simulations Of Plasma-Surface-Dust Interactions For Lunar Exploration, David Clifford Lund Jan 2024

Kinetic Modeling And Simulations Of Plasma-Surface-Dust Interactions For Lunar Exploration, David Clifford Lund

Doctoral Dissertations

"Due to the recent relevance of NASA’s focus on lunar missions, a better understanding of the lunar plasma-surface-dust environment is vital for their success. The lunar surface, devoid of an atmosphere and a global magnetic field, is directly exposed to solar radiation and solar wind plasma. This exposure leads to the electrical charging of the lunar surface due to the bombardment of solar wind plasma and the emission/collection of photoelectrons. Therefore, this research developed accurate and efficient computational models of plasma-surface-dust interactions and extend a legacy simulation code, namely the Immersed-Finite-Element Particle-in-Cell (IFE-PIC), to a parallel version: Parallel Immersed-Finite-Element Particle-in-Cell …


Efficient Modeling And Simulation For The Aerothermal Analysis Of Particle-Laden Hypersonic Flows, Andrew Hinkle Jan 2024

Efficient Modeling And Simulation For The Aerothermal Analysis Of Particle-Laden Hypersonic Flows, Andrew Hinkle

Doctoral Dissertations

"Standard approaches for simulating hypersonic flows in particle-laden environments have key limitations in practice, such as high cost and numerical noise. In this work, efficient solution strategies for particle-laden hypersonic flows were developed using both Lagrangian and Eulerian models for the particle phase with the focus on investigating spacecraft surface erosion, as well as convective and radiative heat flux augmentation due to atmospheric particulate encountered during planetary entry.

First, an efficient integration strategy for Lagrangian methods, the Trajectory Control Volume (TCV) method, was developed for steady analysis of dilute particle phase problems on general geometries. The TCV method was shown …


Optimization Of Fire Emergency Preparedness In Underground Mining Environments: An Agent-Based Evacuation Approach, Oluwafemi Babatunde Salami Jan 2024

Optimization Of Fire Emergency Preparedness In Underground Mining Environments: An Agent-Based Evacuation Approach, Oluwafemi Babatunde Salami

Doctoral Dissertations

"Underground mining environments present a complex interplay of thermal and non-thermal hazards, with fires constituting a significant risk due to the release of heat smoke from incomplete combustion. The propagation of these hazards through the ventilation networks underscores the critical need for understanding fire scenarios and their interaction with the underground environment. Existing knowledge regarding past mine fire disasters, and quantification of associated hazards and risks are insufficient for optimizing emergency evacuation strategies in the event of an underground fire emergency.

This research endeavors to bridge this gap by developing advanced quantitative risk assessment and evacuation models tailored specifically for …


Investigation Of Wide Beam And Interfacial Shear Transfer In Reinforced Concrete Structures, Nikkolas Edgmond Jan 2024

Investigation Of Wide Beam And Interfacial Shear Transfer In Reinforced Concrete Structures, Nikkolas Edgmond

Doctoral Dissertations

"The use of reinforced concrete (RC) allows for unique designs of structural elements and connections because of the ability to vary the geometry and reinforcement detailing with ease. However, this freedom in the design process can lead to specialized conditions that have not been extensively studied by means of experimental testing. This is especially true for components or regions of components that are subjected to high shear loads, which are susceptible to undesirable and brittle failures. While many studies have been conducted to investigate the shear behavior of RC structural members and components to determine the critical design parameters, these …


Investigation Wettability Contact Angle Using 2d Imaging Technology, Saleh Alsayegh Jan 2024

Investigation Wettability Contact Angle Using 2d Imaging Technology, Saleh Alsayegh

Doctoral Dissertations

"Investigation wetting preference of tight carbonate reservoir rocks and several other unconventional reservoir rocks, and their relation to oil production, is becoming noticeably important for field development in Kuwait, as in many future unconventional tight carbonate reservoirs in the Middle East. The overall objective of this investigating and modeling study is to discover many fundamental relationships from totality wettability preference as a tool for reservoir recovery predictions and management. The investigation includes advancing position of water wet preference into smaller capillaries of the matrix voids and incrementally more oil-wet into larger capillaries of natural fractures (NF). Also, investigating water/ oil …


Investigating The Potential Of Blended Feedstocks For Biofuel Production Via Pyrolysis Process: Experimental And Aspen Simulation Approach, Hasan Jawad Hammood Al-Abedi Jan 2024

Investigating The Potential Of Blended Feedstocks For Biofuel Production Via Pyrolysis Process: Experimental And Aspen Simulation Approach, Hasan Jawad Hammood Al-Abedi

Doctoral Dissertations

"The development of renewable energy sources has become increasingly urgent considering the climate crisis and the need to reduce greenhouse gas emissions. Pyrolysis, which is decomposition of an organic feedstock without oxygen, is a thermo-chemical process that has garnered significant attention as a promising technology for sustainable energy production, capable of converting biomass and waste materials into biofuels.

The primary objective of this study is to investigate the pyrolysis and co-pyrolysis behaviors of corn stover (CS), refuse-derived fuel (RDF), and oil shale (OS) in equal mass ratios. Utilizing a thermogravimetric analyzer and differential scanning calorimetry (DSC), the co-pyrolysis process is …


Improving Syngas Quality In A Downdraft Biomass Gasifier With Blended Feedstocks, Rania Almusafir Jan 2024

Improving Syngas Quality In A Downdraft Biomass Gasifier With Blended Feedstocks, Rania Almusafir

Doctoral Dissertations

"Biomass gasification is the greatest potential renewable energy source and will play an important role in the energy mix of the future. To achieve a high quality of produced synthesis gas (syngas) in the gasification system, the syngas cleaning and cooling processes pose challenges. The main objectives of the present work are advancing the knowledge of the gasification process and producing syngas in the studied pilot-scale downdraft biomass gasifier.

A Thermogravimetric analysis (TGA) has been developed and utilized to experimentally investigate the impact of biomass feedstock diversity on the performance of the gasification process of hardwood (HW), softwood (SW) pellets, …


Development Of A Comprehensive Multi-Factored Methodology For Identification Of Landslides In The Buffalo National River Of Arkansas, Abdurraouf Okok Jan 2024

Development Of A Comprehensive Multi-Factored Methodology For Identification Of Landslides In The Buffalo National River Of Arkansas, Abdurraouf Okok

Doctoral Dissertations

"In northern Arkansas's Springfield and Boston Mountain Plateaus, distinctive geomorphological landslide features have shown historical continuity. USGS topographic maps (1:24,000, 7.5-minute series) serve as valuable resources for studying terrain characteristics and hydrological patterns.

This study uses a manual mapping approach with high-resolution LiDAR data and geological maps in a GIS environment. The method identifies historic landslide features by analyzing anomalous topographic contour patterns overlaid on LiDAR-derived hillshade maps, revealing various mass movements along the Buffalo National River. Data from the Office of State Geologist and fieldwork reconnaissance were utilized to map older landslide features with high confidence. Some previously unrecognized …


Paleoecological And Paleoclimatic Reconstructions Based On Holocene Sediment Cores, Lake Izabal, Eastern Guatemala, Erdoo Mongol Jan 2024

Paleoecological And Paleoclimatic Reconstructions Based On Holocene Sediment Cores, Lake Izabal, Eastern Guatemala, Erdoo Mongol

Doctoral Dissertations

"The Maya Region in Central America is characterized by pronounced discrepancies in precipitation, resulting in high precipitation gradients that support large-scale differences in vegetation across the region. Several lake deposits and other paleoclimate archives in the region have been studied to reconstruct past climates and palaeoecological conditions. However, actual data from proxy records have not been qualitatively and quantitatively utilized to interpret the behavior of the vegetation in moister areas within the Maya Region, such as the Lake Izabal Basin (LIB). The palynomorphs from two sediment cores in the LIB provided a good opportunity to infer the patterns of past …


In Situ Infrared Thermographic Inspection In Additive Manufacturing, Tao Liu Jan 2024

In Situ Infrared Thermographic Inspection In Additive Manufacturing, Tao Liu

Doctoral Dissertations

"Laser Powder Bed Fusion (LPBF) is a key technique in metal additive manufacturing and has undergone extensive research over the past few decades. It enables the fabrication of complex geometries directly from digital design models. The solidification process in LPBF is heavily influenced by the characteristics of the powder layer, including its thickness and thermal transport properties. Additionally, the performance of the printed part is impacted by the temperature history during solidification and the final residual stress field. While these topics have been the focus of many studies, almost all research has concentrated on ex-situ measurement and testing. These ex-situ …


Effect Of Ai–Si Coating Weights On Corrosion And Weldability Of Ultra-High-Strength Steel Usiborr 1500 Used In Automotive Structures, Hilary Anayochukwu Onyishi Jan 2024

Effect Of Ai–Si Coating Weights On Corrosion And Weldability Of Ultra-High-Strength Steel Usiborr 1500 Used In Automotive Structures, Hilary Anayochukwu Onyishi

Doctoral Dissertations

"There has been increased demand for hot-stamped pre-coated Usibor 1500R in automotive industries due to its excellent properties (ultra-high strength, weight reduction, low spring back and excellent corrosion protection). In this research work, investigation was conducted to better understand the effect of Ai-Si Coating Weights on weldability and corrosion of Ultra-High-Strength Steel Usibor 1500R used in Automotive Structures”. The results show that weld nugget diameter increases with increasing weld current, better spot-weld nugget diameter is recorded at weld currents above 7.5 kA for both AS80 and AS150 and the weld current range decreases as the interdiffusion layer (IDL) thickness increases. …