Digital Commons Network^™

Photoionization Of Spin-Polarized Rydberg Atoms Out Of A Continuous Wave Optical Dipole Trap, Kevin Lee Romans

Doctoral Dissertations

"Recent research has demonstrated the need for a fully differential experiment on the photoionization of ⁶Li Rydberg atoms in a continuous wave (cw) laser field, as this would provide a new path forward for studying never before accessible atom-light interactions. Rydberg atoms are back in the focus of intense research due to their peculiar properties, which make them interesting candidates for quantum optics and information applications. In this work, we study the ionization of such Rydberg atoms, due to their interaction with a trapping laser field, by utilizing a reaction microscope (ReMi) capable of measuring photoelectron momentum distributions with …

Parallel Algorithms For Large Scale Dynamic Graph Analysis, Arindam Khanda

Doctoral Dissertations

A complex system of interacting entities in contemporary scenarios, be it biological, technological, or social, can be represented using graphs. Dynamic graphs, unlike their static counterparts, are ones in which the underlying topology changes over time. These networks act as a model for numerous systems, from transportation to social interactions, capturing the ever-evolving nature of real-world phenomena. However, the inherent temporality of these networks presents a unique set of challenges and the traditional static graph algorithms often fall short in efficiency and applicability. In our research, we delve into the complexities presented by large dynamic networks and suggest various methodologies …

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 …

Power Supply Induced Jitter Analysis In High-Speed Drivers, Yifan Ding

Doctoral Dissertations

The Input/Output Buffer Information Specification (IBIS) model faces challenges in accurately simulating power-supply-induced jitter (PSIJ), particularly under nonlinear and time-varying power noise conditions with pre-driver stages. This work introduces advancements in IBIS model modification algorithms to enhance PSIJ simulation accuracy for high-speed drivers.

First, a correction coefficient-based approach was developed to adjust switching coefficients K_pu and K_pd using pre-driver DC jitter sensitivity, significantly improving model robustness under DC and AC power noise. However, its effectiveness diminished under large noise amplitudes due to coefficient shape dominance.

To address this, a simplified algorithm bypassed correction coefficient, directly correlating switching transitions with jitter …

Implication And Applications Of Machine Learning On Biomedical Images, Jason Hagerty

Doctoral Dissertations

Medical imaging ranges in modality including computer tomography imaging, x-ray imaging, digital microscopy, and macro-focus dermoscopy images. The latter two modalities are the focus of the presented work.

To perform a diagnostic evaluation on the captured dermoscopy image, it begins with what is usually a labor-intensive operation that requires an expert to perform the initial segmentation for localizing a region of interest (ROI). Once that ROI is obtained, a physician with years of training and experience will observe biological markers that can be used to visually differentiate whether a lesion is benign or malignant. A similar process is used for …

Experimental Study Of Defects In Coaxial Wire-Based Laser Metal Deposition, Remy Mathenia

Doctoral Dissertations

This work seeks to improve the usability and capability of coaxial wire-based laser metal deposition (LMD) through the experimental study of process parameters on output geometry, directional effects, and defect formation. Wire-based LMD is a directed energy deposition (DED) strategy that uses a focused laser heat source to melt and fuse metal wire as it is deposited. This process is used to build parts layer-by-layer until a desired geometry is accomplished. LMD enables the creation of complex components at a high build rate with low material and energy waste. This work focuses on the deposition of titanium wire in the …

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) …

Applying Human System Integration Principles To The Investigation, Design And Validation Of Interventions For Self-Escape In Underground Mines, Eugene Adubofour Gyawu

Doctoral Dissertations

This dissertation investigates the use of human systems integration (HSI) to develop technologies for miners’ self-escape during a mine emergency, addressing barriers that compromise miner safety during emergencies.

Recognizing the inherently hazardous nature of underground mining, this study has three core objectives: (1) assessing miners' perceptions of proposed self-escape interventions, (2) designing interventions based on these insights, and (3) validating their effectiveness using experimental testing. This work evaluates self-escape interventions for both coal and metal/non-metal miners using scenario-based surveys, information design reviews, label designs and experimental testing methods varying across three distinct studies.

Results reveal that miners identified improvements to …

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 …

The Real-Time Detection Infrastructure Of Ligo, Virgo, And Kagra: Data Products, Current Performance, And Future Developments, Sushant Sharma Chaudhary

Doctoral Dissertations

The discovery of the binary neutron star merger event GW170817 marked the dawn of Multi-Messenger Astronomy (MMA) with Gravitational Waves (GWs). Such multi-messenger events are of immense scientific interest due to the wealth of information they provide through joint observations across different messengers. In this rapidly evolving field, prompt identification and timely distribution of alerts is critical for follow-up observations.

This work offers a comprehensive overview of the LIGO-Virgo-KAGRA (LVK) Collaboration’s low-latency analysis pipeline for GW events, covering key stages from calibration and data analysis to the issuance of public alerts. I examine the latency and accuracy of each stage …

Systematic Esd Analysis And Modeling For Electronic Device, Zhekun Peng

Doctoral Dissertations

Systematic ESD analysis provides good pre-compliance to ESD robustness evaluation on the electronic device from device level to component/system level to on-chip level. The whole process involves corona discharge on display, system level ESD analysis on PCB for race condition and transient response and 3D IC package impact to on-die ESD.

ESD to the display cover glass can damage touchscreen traces by sparkless corona discharges on the glass surface. A non-linear time dependent transmission-line model is proposed to model corona streamer propagation in terms of the coupling current and propagation speed. Results are highly promising to model the corona discharge …

Optical Detection Of Instantaneous Microwave Frequency And Displacement, Behzad Boroomandisorkhabi

Doctoral Dissertations

Research presented in this research is focused on developing and implementing novel photonic systems for instantaneous microwave frequency and displacement measurement, emphasizing cost-effectiveness, scalability, and high resolution. The research is encapsulated in three core studies: the design of all-fiber ultrafast ranging Lidar for medical motion management, the application of dispersive interferometry using picosecond laser pulses for laser ranging, and the integration of microwave photonic systems with digital signal processing (DSP) for enhanced measurement precision.

The work achieves micrometer-scale displacement accuracy and microwave frequency resolutions within ±1 MHz across wide dynamic ranges by leveraging dispersive interferometry and time-stretch techniques. The studies …

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 …

Enhanced Optimization Of Mass Transfer For Carbon Capture And Wastewater Remediation In Algal Systems Through Algorithmic And Bioprocessing Techniques, Peter Ofuje Obidi

Doctoral Dissertations

The scalability and industrial deployment of algal cultivation systems are limited by suboptimal mass transfer, constraining their effectiveness in carbon capture and wastewater remediation. This research investigated these challenges through integrated optimization methodologies that combine algorithmic frameworks with enhanced bioprocessing techniques to enhance efficiency, economy, and scalability. A System-of-Systems (SoS) meta-architecture was developed using genetic algorithms and fuzzy assessor functions to demonstrate a pathway toward cost reduction. Rigorous mechanical and chemical characterizations were quantitatively analyzed to reveal existing optimization strategies and further evaluated the best strategies to use in enhancing mass transfer for improved biomass yield. The work also integrates …

Supporting Human-Ai Interaction From User Expectations To Mental Models, Harishankar Vasudevanallur Subramanian

Doctoral Dissertations

Explainable AI (XAI) aims to unravel the "black box" nature of AI systems and provide insights into the inner workings that lead to a prediction. However, the best XAI communication varies depending on the individual, task, and broader context. It is challenging to anticipate the best XAI for a particular use case. One strategy is for users to build an appropriate mental model of AI with both prediction and system level XAI. To date, little research has focused on quantitatively measuring users interacting with system-level XAI. This dissertation has three primary contributions. The first contribution is a scoping review paper …

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 …

Products Of Laser Ablated Actinides And Actinide Comparators In The Presence Of Carbonyl Sulfide Characterized By Rotational Spectroscopy, Joshua Edward Isert

Doctoral Dissertations

As the consumption of energy continues to rise globally, so too has interest in alternative energy sources such as nuclear power. However, a fundamental understanding of the actinide series is needed in order to safely and efficiently utilize these elements. Rotational or microwave spectroscopy, depending on if one is speaking of the physical outcome of the experiment or the region of the electromagnetic spectrum being operated in, is a gas phase molecular study utilized for structural determination. This technique can be utilized to gain an in depth understanding of bonding within the actinide series. However, when studying species that are …

Characterization And Deportment Of Anode Impurities In Copper Electrorefining, Charles Michael Campbell

Doctoral Dissertations

The objective of this research was to study the deportment of the group 15 elements, arsenic, antimony and bismuth during copper electrorefining. Samples were collected from six industrial copper anodes with different compositions. Specimens were physically characterized and electro refined to understand the differences in the behavior of selected impurities. Inclusions in the cast metal structures were characterized using automated scanning electron microscopy and energy dispersive spectroscopy to measure and correlate their size, shape and composition. Arsenic and lead were found to have a positive correlation between concentration and size of inclusions. Using wavelength dispersive spectroscopy, multiphase inclusions were examined, …

Data-Driven Mulitiscale Modeling Of Electrochemical Transport, Non-Linear Electrical Contact, And Additive Manufacturing Processes, Emmanuel Olugbade

Doctoral Dissertations

The growing demand for high-efficiency energy systems and advanced manufacturing technologies requires predictive frameworks that link atomic-scale physics with engineering-scale performance. This dissertation develops a unified multiscale modeling approach that integrates molecular dynamics, density functional theory, finite-element analysis, and machine learning to connect structure, transport, and performance across materials and processes. Depending on the interactions involved, the framework employs loose coupling for parameter transfer, tight coupling for two-way feedback, and hybrid coupling where machine-learning surrogates accelerate high-fidelity simulations while retaining physical interpretability. In electrochemical systems, an XGBoost-enhanced single-particle model reproduces P2D-level electrolyte potential dynamics at roughly one-hundredth the computational cost, …

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, …

Radio Frequency Wave Propagation Modeling Within Obstructed Underground Mining Environments For Effective Miner Localization During Mine Emergencies, Emmanuel Atta Antwi

Doctoral Dissertations

The reliability of underground wireless communication systems remains a significant challenge, particularly during emergencies when the mine environment becomes severely obstructed by debris, dust, and humidity. These environmental and geometric conditions result in significant attenuation of electromagnetic (EM) waves and multipath effects that undermine miner localization and rescue operations. Existing Vector Parabolic Equation (VPE) models are efficient for straight or mildly curved tunnels but fail to account for the random and obstructive conditions typically encountered during underground emergencies. This research develops a novel radio propagation model for EM wave behavior in underground mine drifts under geometrically obstructed conditions. The model …

Optical Sensor Instrumentation For Enhanced Continuous Caster Development, Hanok Wondimagegnehu Tekle

Doctoral Dissertations

Fiber-optic sensors are an emerging technology that can enhance process monitoring and control in steelmaking. They are especially valuable in the continuous caster’s harsh environment. This dissertation presents the industrial application and demonstration of three sensor types: single-mode silica fiber with Rayleigh-based Optical Frequency Domain Reflectometry (OFDR), sapphire fiber (single-crystal alumina) with Fiber Bragg Gratings (sFBG), and an in-line Raman spectroscopy probe. Each sensor served a distinct role in the continuous caster. Rayleigh OFDR sensors were embedded in tundishes for distributed thermal mapping at 7-mm spatial resolution across ≈4 m. Measurements were taken during preheating, casting, and ladle exchanges, and …

Improving The Operator-Swarm Dynamic Under Mental Fatigue Constraints In Search And Rescue Operations, Jordan Morrow

Masters Theses

"Human-robot applications that allow for work to be done remotely are largely dependent on the lassitude of the operators. The exhaustion of these operators is a result of work completion and duration. Previous research attempts to evaluate the impact on reaction by quantiying human weariness. This paper examines how human weariness affects the human-robot dynamic in UAV-assisted search and rescue missions. An explanation of the connection between mental exhaustion and operator responsiveness over prolonged durations is provided by the search and rescue operations using UAV swarms (SAROUS) model. Through the use of artificial intelligence, SAROUS is modernized. This allows the …

Advanced 3d Lidar-Based Systems For Urban Traffic And Pedestrian Monitoring: Integrating Elevated Lidar, Data Collection, And Deep Learning For Precise Detection And Activity Classification, Nawfal Guefrachi

Masters Theses

"Accurate and real-time monitoring of urban traffic and pedestrian activities is crucial for intelligent transportation systems (ITS) and smart cities. Traditional camera-based methods struggle with issues like lighting and privacy. This research leverages advanced three-dimension light detection and ranging (3D LiDAR) technology and computational frameworks to address these challenges, providing transformative solutions for urban traffic management and pedestrian safety. By strategically deploying elevated LiDAR sensors, detailed 3D point cloud data is captured, enabling precise monitoring of urban environments. Enhancements to LiDAR-based frameworks, such as fine-tuning the Point Voxel Region-Based Convolutional Neural Network (PV-RCNN), improve the detection of vehicles and pedestrians …

Bond Behavior Of Magnesium Potassium Phosphate Cement (Mkpc) Coating For Steel Reinforcement, Eric Williams

Masters Theses

"This research investigates the bond behavior of magnesium potassium phosphate cement (MKPC) coated mild steel deformed bars in conventional concrete and concrete repair materials. For typical steel reinforcement in concrete, a thin “passive layer” develops around the reinforcement, which protects the reinforcement from corrosion. The concrete carbonates over time, reducing the protection of the passive layer and allowing chlorides, which corrode the reinforcement, to penetrate at an increasing rate. In some cases, to combat this corrosion, a protective layer is added to the reinforcement prior to installation. Common protective layers include epoxy coatings or zinc galvanization. MKPC is a novel …

Transfection Of Ionizable Lipid Nanoparticles On Raw 264.7 And Mda-Mb-231, Lavanya Bhargava

Masters Theses

"This thesis investigates the preparation, characterization, and transfection efficiency of various ionizable lipid nanoparticles (LNPs) formulated for the delivery of mRNA encoding enhanced green fluorescent protein (EGFP) in RAW 264.7 macrophages and MDA-MB-231 breast cancer cell lines. The ionizable cationic lipid studied are ALC-035, C12-200, C14-4, PPZ-A10, DLin-MC3-DMA. The study addresses the need for effective gene delivery systems to provide a safe and versatile platform that protects and transports nucleic acids into target cells. LNPs were synthesized using microfluidic mixing methods, incorporating lipid components such as the cationic lipids, DSPE, DOPE, cholesterol and PEG lipids to achieve controlled particle sizes, …

On Optimizing Sensor Data Collection, Processing, And Storage For Industrial Additive Manufacturing, Steven Thompson

Masters Theses

The widespread adoption of digital data management methods for transformative technologies, such as additive manufacturing (AM), within the aerospace industry is impeded by poor interoperability between AM component manufacturing processes. Moreover, data quality may be compromised due to sensor failures or other corruptions. Additionally, massive amounts of data are collected during these processes, often needing to remain accessible for decades. These storage costs can place a significant financial burden on smaller suppliers. This work aims to make digital data management methods more affordable and, therefore, approachable for smaller suppliers.

First, the design and initial implementation of an affordable and adaptable …

Augmentation Of Quality Of Service, Security, And Trust In Edge-Enhanced Iot Networks Leveraging Blockchain, Kyle Matthew Whitlatch

Masters Theses

The meteoric rise of the Internet of Things (IoT) has led to multiple architectural schemas to handle the data these devices create. Edge-enhancement is a technique where groups of IoT report to a median layer to aggregate the data before relaying to the endpoint. These edges also open opportunities to perform more operations to ensure devices are behaving properly before committing the data to long term storage. By interconnecting these edges with a technology like blockchain, it is possible to have an interconnected and responsive system to ensure the Quality of Service (QoS) of the IoT devices within the architecture …

System Design For Highly Accurate And Efficient Target Detection In Triaxial Testing, Qingqing Fu

Masters Theses

Accurate and automated recognition of coded targets is crucial for high-precision photogrammetry-based measurements in triaxial testing. Traditional recognition methods, including those based on deep learning and table decoding, often struggle with issues such as perspective distortion, rotation, and variable lighting, leading to unreliable results. While deep learning approaches offer some improvements, they remain computationally intensive and sensitive to environmental factors.

This thesis introduces an innovative system that replaces deep learning algorithms with a blob analysis-based method for efficient and robust recognition of coded targets. The system also employs newly designed solid points of varying sizes and patterns, eliminating the need …

Development Of A Method To Measure Blast Overpressure Exposure Using Orthogonal Sensor Orientations, Nicholas Kuehl

Masters Theses

Measuring and recording blast exposure to military personnel from shoulder-fired weaponry or improvised explosive devices to correlate health outcomes like mild traumatic brain injury has been a goal for many years. As such, many wearable sensors have been developed and tested for accuracy and reliability. Despite this, knowing the sensor orientation in relation to the blast source is important to fully correlate the actual personnel exposure to clinical outcomes. This research investigates whether pressures recorded at three independent orientations in the x, y and z planes can be combined to a representative pressure that is independent of orientation. Important metrics …