Digital Commons Network^™

Improving Hexapod Platform Pose Accuracy - A Photogrammetry-Based Approach, Sourabh Karmakar

All Dissertations

The aim of this research is to make a newly constructed Stewart-Gough Platform-based test frame Tiger 66.1 operational by developing control software and estimating the error in its pose accuracy. The accuracy of the platform is affected by one source or multiple sources. The typical error sources are kinematic and structural, some of them originate from manufacturing imperfections, assembly deviations, elastic deformations, thermal deformations, and joint clearances which change the expected kinematic behavior of the manipulator. Also, some non-mechanical errors like transmission error, sensor accuracy, algorithm error, and truncation error in calculation contribute significantly in some cases. Using pose deviations …

New Preconditioned Conjugate Gradient Methods For Some Structured Problems In Physics, Tianqi Zhang

All Dissertations

This dissertation concerns the development and analysis of new preconditioned conjugate gradient (PCG) algorithms for three important classes of large-scale and complex physical problems characterized by special structures. We propose several new iterative methods for solving the eigenvalue problem or energy minimization problem, which leverage the unique structures inherent in these problems while preserving the underlying physical properties. The new algorithms enable more efficient and robust large-scale modeling and simulations in many areas, including condensed matter physics, optical properties of materials, stabilities of dynamical systems arising from control problems, and many more. Some methods are expected to be applicable to …

Hpc-Enabled Fast And Configurable Dynamic Simulation, Analysis, And Learning For Complex Power System Adaptation And Control, Cong Wang

All Dissertations

This dissertation presents an HPC-enabled fast and configurable dynamic simulation, analysis, and learning framework for complex power system adaptation and control. Dynamic simulation for a large transmission system comprising thousands of buses and branches implies the latency of complicated numerical computations. However, faster-than-real-time execution is often required to provide timely support for power system planning and operation. The traditional approaches for speeding up the simulation demand extensive computing facilities such as CPU-based multi-core supercomputers, resulting in heavily resource-dependent solutions. In this work, by coupling the Message Passing Interface (MPI) protocol with an advanced heterogeneous programming environment, further acceleration can be …

Making The Move Toward Meaningfulness In Learning Activities: Enhancing Teacher Self-Efficacy In Student Engagement Through An Instructional Coaching Approach In Improvement Science, Maureen Tiller

All Dissertations

Student engagement is a common problem in schools today and a challenging one to solve. Choosing to dive deeper into this complex problem at one high school, ten teachers participated in a coaching cycle designed to impact self-efficacy in student engagement with the support of the school’s instructional coach in collaboration with the principal. One overarching research question guided this improvement science study: What impact does an instructional coaching cycle focused on meaningfulness in learning activities have on teachers’ self-efficacy in student engagement? To answer the research question, I conducted a quantitative and qualitative data analysis of pre- and …

Nuclear Charge Radius Determination Of Iridium Using Euv Spectroscopy Of Highly Charged Ions, Adam Hosier

All Dissertations

Highly charged ions have emerged on the scene of atomic physics because of their compressed electron cloud enhancing various physical phenomena. While transitions in ions and highly charged ions provide valuable information to different communities, their application in nuclear charge radius measurements becomes increasingly prominent. In this work, we report the extreme ultra-violet spectroscopy of Na-like ions and x-ray spectroscopy of Cu-like, Co-like, and Ni-like ions that explore nuclear charge distributions and the identification of new transitions, respectively.

In the first part of this work, extreme ultra-violet spectroscopy of highly charged ions of Na-like osmium and iridium was performed using …

Short-Term Load Forecasting Using Nonlinear Dynamic Time Series Autoregressive With Feedback For Azadi Control-Station Erbil-Iraq, Wafeeq Sh. Hanna, Velar H., Dlawer R. Maruf

Iraqi Journal of Computers, Communications, Control and Systems Engineering

The load forecasting is a human or computational technique for accurate preanticipation of electrical load to enhance reliable operation and optimal planning control of system plant for electrical energy flowing without facing any economical and technical limitations, therefore appropriate estimation for present and future consumption cost of electrical loads which are necessary to predict the load demand for generating near to accurate power. During advanced technology at the last few decades, artificial neural networks(ANNs) have been extensively employed in electrical system, they are trained using historical data obtained from plant station. This work is intended to be a study of …

Analytical And Comparative Study For Optimization Problems, Sanaa Ali Jabber, Soukaena H., Shatha H. Jafer

Iraqi Journal of Computers, Communications, Control and Systems Engineering

Finding an optimal solution to some problem, like minimizing and maximizing the objective function, is the goal of Single-Objective Optimization (SOP). Real-world problems, on the other hand, are more complicated and inVolve a wider range of objectives, several objectives should be maximized in such problems. No single solution could be enhanced in all objectives without deteriorating at least one other goal, which is the definition of Pareto-optimality. Understanding the idea of MultiObjective Optimization (MOP) is thus necessary to find the optimum solution. Multiobjective eVolutionary algorithm (MOEA) are made to simultaneously assess many objectives and find Pareto-optimal solutions, MOEA can resolve …

The Use Of Deception In Dementia-Care Robots: Should Robots Tell "White Lies" To Limit Emotional Distress?, Samuel R. Cox, Grace Cheong, Wei Tsang Ooi

ROSA Journal Articles and Publications

With projections of ageing populations and increasing rates of dementia, there is need for professional caregivers. Assistive robots have been proposed as a solution to this, as they can assist people both physically and socially. However, caregivers often need to use acts of deception (such as misdirection or white lies) in order to ensure necessary care is provided while limiting negative impacts on the cared-for such as emotional distress or loss of dignity. We discuss such use of deception, and contextualise their use within robotics.

Damage Detection With An Integrated Smart Composite Using A Magnetostriction-Based Nondestructive Evaluation Method: Integrating Machine Learning For Prediction, Christopher Nelon

All Dissertations

The development of composite materials for structural components necessitates methods for evaluating and characterizing their damage states after encountering loading conditions. Laminates fabricated from carbon fiber reinforced polymers (CFRPs) are lightweight alternatives to metallic plates; thus, their usage has increased in performance industries such as aerospace and automotive. Additive manufacturing (AM) has experienced a similar growth as composite material inclusion because of its advantages over traditional manufacturing methods. Fabrication with composite laminates and additive manufacturing, specifically fused filament fabrication (fused deposition modeling), requires material to be placed layer-by-layer. If adjacent plies/layers lose adhesion during fabrication or operational usage, the strength …

Understanding The Interaction Of Environmental Contaminants With Polystyrene Nanoparticles And Dna Using Nuclear Magnetic Resonance Spectroscopy And Density Functional Theory, Saduni Arachchi

All Dissertations

The objective of the thesis is to study the effect of environmental pollutants on polystyrene nanoparticles and biomolecules. This is done in two different techniques, particularly NMR and density functional theory. In this thesis, we use a combination of 1H NMR, Saturation-Transfer Difference (STD) NMR and relaxation experiments to study the interactions, kinetics and dynamics of antibiotics with polystyrene nanoparticles. (PS NPs) Density functional theory (DFT) is used to study the binding of commonly used non-oxidative hair dyes to biomolecules (DNA and amino acids) and PS particles.

Educational Robotics And Computational Thinking In Elementary School Students, Sonia D. Jordan

Electronic Theses and Dissertations

This study examined the role of educational robotics in fostering computational thinking in elementary settings, both in classrooms and extracurricular programs. Among growing concerns over K–12 students’ computational thinking deficits, the research evaluated the impact of Lego EV3 and VEX IQ platforms. Data was sourced from lesson plans, student work surveys, and teacher interviews and then subjected to thematic analysis using a qualitative approach. The participants were Texas educators engaged in robotics instruction, even though specific robotics statistics are absent in the Texas Education Agency. Instructional strategies varied from hands-on experiences to translating mathematical concepts into robotic actions. A key …

Electrodeposition Studies Of Gold Nanoparticles And Alginate Hydrogel Films., Harikrishnan Nambiathan Nambiar

Electronic Theses and Dissertations

This dissertation investigates the electrochemical deposition (ECD) and electrophoretic deposition (EPD) processes involving citrate (cit)-stabilized Au nanoparticles (NPs) and calcium alginate (Ca-Alg-Au NP) hydrogel films. The first part of the dissertation investigates the influence of NP size, surface area (SA) coverage, and ligand stabilizers on the electrochemical growth of Au on Au NPs, aiming to enhance our understanding of the growth process during the nucleation and growth of metal NPs. The growth kinetics depend on Au NP size (4 nm > 15 nm > 50 nm) for a constant SA coverage, as determined by the overpotentials for ECD. The growth rate increases …

Educator Perceptions Of The Care And Instruction Of Trauma Exposed Students In A Small, Urban, Christian School., Amanda L. Petters

Electronic Theses and Dissertations

Students of color in low socio-economic, high crime urban areas are exposed to a higher level of trauma than their White contemporaries. The trauma that they bring into school with them create challenges for their teachers working to eliminate barrier to students’ education. Widespread efforts have been attempted to thwart the social injustices that many students of color experience in schools including disproportionality around implementation of school rules and the equitable access to curriculum. I used Critical Race Theory to frame my study around students of color in urban areas experiencing disproportionate levels of trauma, and their teachers’ level of …

Scalable Solution Processing Of Niox Nanoparticles., Peter James Armstrong

Electronic Theses and Dissertations

Perovskite solar cells (PSCs) are a promising alternative to silicon-based photovoltaics. However, PSCs face several challenges due to shortcomings in their stability, module efficiency, and scaled production. Although PSCs is still a young field of research, significant attention has been given to demonstrating power conversion efficiencies that are on par with traditional silicon. With that target reached, converting the laboratory demonstration into practical materials to increase access and abundance of solar energy are among the next large targets for the field. This comes with material challenges for perovskite and their companion charge transport layers (CTLs). Among the charge transport materials …

Cloud Computing In The World Of Generative Ai, Yassine Chahid, Patrick Slattery

Publications and Research

The purpose of this research is to evaluate the progress of cloud computation and generative artificial intelligence, and how the improvements in these respective technologies could be combined for future uses. Cloud computation and generative AI have rapidly developed in their capabilities. By analyzing the ways in which cloud computing and generative AI have been implemented thus far, a better understanding can be established regarding how they may influence current tech solutions within the information technology sector and beyond. The first portion of research consisted of researching the current capabilities of the two technologies respectively. By reviewing relevant publications and …

A Hybrid Cognitive Model For Machine Agents In Project And Action Teams, Joshua A. Lapso

Theses and Dissertations

High performing human teams transcend complex domain uncertainty by achieving an emergent state of shared cognition, in which knowledge is organized, represented, and distributed to team members for rapid execution. However, this requires that individuals emit perceivable qualities upon which other members can make inferences about intent. In pursuit of future human and machine team studies, this research presents a hybrid cognitive model for machine agents in fully cooperative and semi-cooperative action and project teams. The hybrid cognitive model unifies the characteristics of the shared mental model and transactive memory system. The resultant model facilitates anytime selection over the two …

Marss: Multi-Agent Reinforcement Learning For Satellite Swarms, Nicholas J. Yielding

Theses and Dissertations

Multi-agent systems and swarms in spacecraft formation flying are of ever-increasing importance in a contested space environment—use of multiple spacecraft to contribute to a cooperative mission potentially increases positive outcomes on orbit, while autonomy becomes an ever more important requirement to reduce reaction time in dynamic situations and lower the burden on space operators. This research explores difficult swarm Guidance Navigation and Control (GNC) scenarios using Deep Reinforcement Learning (DRL). DRL polices are trained to provide guidance inputs to agents in multi-agent swarm environments for completing complex, teamwork focused objectives in geosynchronous orbit. An example scenario is explored for a …

Federated Active Learning For Network Intrusion Detection, Matthew D. R. Sauer

Theses and Dissertations

This thesis addresses challenges with detecting attacks on computer networks within a Federated Learning (FL) framework, when labeled instances are few. We explore the integration of active learning (AL) and semi-supervised learning (SSL). AL efficiently uses data that would otherwise be wasted or require substantial time for labeling. SSL provides capacity to train models that have a limited amount of labeled data, by utilizing additional unlabeled data that is available. We show how FL combined with AL or SSL can realize a detection system that adapts and trains quickly to new networks, reducing the total amount of data labeling needed. …

Examining The Effects Of Mental Health Barriers On Black Undergraduate Students Attending Predominantly White Institutions, Patrice N. Storey

Graduate Theses and Dissertations

Black college students are experiencing mental health issues at an alarming rate. There is, however, a reluctance among Black college students to seek assistance. There is a stigma surrounding mental health. An individual with a mental illness is often stereotyped as weak, uncontrollable, or paralyzed by demons. Historical incidents such as slavery, the Tuskegee Experiment, Jim Crow, and the forced sterilization of Black women have led the Black community to distrust the medical system. The stigma embedded in the Black community is passed down from generation to generation. This literature review examines existing research on Black students and their perception …

Quantification Of Dye Degradation On Titanium Dioxide-Based Membranes, Elizabeth Carol Wood

Graduate Theses and Dissertations

The purpose of this study was to examine the dye degradation on the titanium dioxide (TiO2)-based membranes. While many studies have shown photocatalytic degradation of dye on TiO2 in solution, few studies have been reported on the solid TiO2 substrate. In this work, a new method is developed to quantify the dye degradation on TiO2-based membranes. A hydrothermal method is used to synthesize the photocatalytic TiO2 nanofibers; vacuum filtration is applied to fabricate a self-assembled membrane. Silver is incorporated into the nanofibers through in situ reduction before vacuum filtration to fabricate Ag/TiO2 membrane in an attempt to red shift the …

Shallow Groundwater Distributions And Changes With Sea Level Rise In Seattle, Washington, Taylor L. Watson

Graduate Theses and Dissertations

Sea level rise (SLR) associated hazards, such as coastal flooding and erosion, are pressing issues of great concern for coastal communities across the globe. Shallow and emergent groundwater can contribute to groundwater hazards such as flooding, landslides, or damage to shallow infrastructure. This study investigates the shallow groundwater within Seattle, Washington, and projects how it will respond to SLR using interpolation and numerical groundwater modeling methods. Then, a geologic modeling method is presented as a preliminary investigation of heterogeneity and anisotropy within the aquifer system. In the results for the present-day interpolation, ~6 % of the coastal buffer –the total …

Geochemistry Of Metal-Rich Black Shales And Their Genetic Relationship To Mississippi Valley-Type Pb-Zn Ore Deposits, Midcontinent U.S., Noah S. Morris

Graduate Theses and Dissertations

The formation of Mississippi Valley-type (MVT) lead-zinc (Pb-Zn) ores is complex, involving an interaction of tectonic compression, hydrothermal fluid migration, and geochemical processes within the subsurface. Fundamental questions regarding this interaction remain unclear, including the source(s) of the Pb and Zn ions that make up the ores. A genetic link between black shales and MVT ores has been thought to exist because of (1) the presence of mature hydrocarbon and brine fluid inclusions within many MVT ores, (2) the association of the hydrothermal fluids that are linked to MVT ore formation with organic compounds and oil-like droplets, and (3) the …

A Simulated Qualitative Study Exploring Higher Education Faculty's Perceptions Of Factors That Influence Dynamic Decision-Making When Choosing Opportunities For Student Engagement In Asynchronous Online Courses, Leticia De La Garza

Graduate Theses and Dissertations

The purpose of this study was to explore higher education faculty’s perceptions of factors that influence dynamic decision-making when choosing opportunities for student engagement in asynchronous online courses. More specifically, this study sought to understand how faculty in higher education perceived these factors to prevent and facilitate dynamic decision-making when designing instructor presence, student-to-student collaboration, and student-to-academic content engagement opportunities in asynchronous online courses, as Garrison et al. (1999) suggest, for a community of inquiry. There has not been much focus on the dynamic decision-making of online instructors in higher education and a call to continue exploring factors that influence …

Bayesian Learning Of Spatiotemporal Source Distribution For Beached Microplastic In The Gulf Of Mexico, David Pojunas

Graduate Theses and Dissertations

Over the last several decades, plastic waste has gradually accumulated while slowly degrading in terrestrial and oceanic environments. Recently, there has been an increased effort to identify the possible sources of plastic to understand how they affect vulnerable beaches. This issue is of particular concern in the Gulf of Mexico due to the presence of oil, natural gas, and plastic production. In this thesis, we expand upon existing Bayesian plastic attribution models and develop a rigorous statistical framework to map observed beached microplastics to their sources. Within this framework, we combine Lagrangian backtracking simulations of floating particles using nurdle beaching …

Maximum Depositional Age Analysis Using Paired La-Icp-Ms And Ca-Id-Tims Detrital Zircon U-Pb Geochronology, Benjamin L. Howard

Graduate Theses and Dissertations

The “law of detrital zircons” states that a sedimentary unit cannot be older than its youngest detrital zircon. The youngest U-Pb date(s) from detrital zircon may thus be used to infer a given sedimentary deposit’s maximum depositional age (MDA). MDAs may be calculated in various ways using dates from zircon U-Pb geochronology. Common dating methods used for U-Pb geochronology are laser ablation-inductively coupled plasma-mass spectrometry (LA-ICP-MS) and chemical abrasion-isotope dilution-thermal ionization mass spectrometry (CA-ID-TIMS), a low- and high-resolution instrument type, respectively. Chapter 2 will systematically compare paired LA-ICP-MS and CA-ID-TIMS dates from the same zircon grains to assess the agreement …

Data-Centric Image Super-Resolution In Magnetic Resonance Imaging: Challenges And Opportunities, Mamata Shrestha

Graduate Theses and Dissertations

Super-resolution has emerged as a crucial research topic in the field of Magnetic Resonance Imaging (MRI) where it plays an important role in understanding and analysis of complex, qualitative, and quantitative characteristics of tissues at high resolutions. Deep learning techniques have been successful in achieving state-of-the-art results for super-resolution. These deep learning-based methods heavily rely on a substantial amount of data. Additionally, they require a pair of low-resolution and high-resolution images for supervised training which is often unavailable. Particularly in MRI super-resolution, it is often impossible to have low-resolution and high-resolution training image pairs. To overcome this, existing methods for …

Influence Of Thermal Gradient On Mechanical Properties In Fused Deposition Modelling (Fdm) Additive Manufacturing, Cori K. Yancy

All Theses

Fused Deposition Modeling (FDM) is a technique that constructs functional parts by extruding thermoplastic filaments layer by layer. The interplay between thermal dynamics and their subsequent effects on mechanical properties remains a field necessitating further exploration. This study introduced ongoing research focused on unraveling the connection between the thermal gradients in the FDM printing process and the resulting mechanical attributes. The primary objective was to increase quality and functionality of 3D printed components. In pursuit of this objective, a series of carefully planned experiments were devised to systematically vary FDM parameters, including print speed, layer thickness, and nozzle temperature. Through …

Multi-Layer Evolution Of Acoustic-Gravity Waves And Ionospheric Disturbances Over The United States After The 2022 Hunga Tonga Volcano Eruption, P. A. Inchin, A. Bhatt, S. A. Cummer, S. D. Eckermann, B. J. Harding, J. Ma, J. J. Makela, J B. Snively

Publications

e Hunga-Tonga Hunga-Ha'apai volcano underwent a series of large-magnitude eruptions that generated in the atmosphere. We investigate the spatial and temporal evolutions of fluctuations driven by atmospheric acoustic-gravity waves (AGWs) and, in particular, the Lamb wave modes in high spatial resolution data sets measured over the Continental United States (CONUS), complemented with data over the Americas and the Pacific. Along with >800 barometer sites, tropospheric observations, and Total Electron Content data from >3,000 receivers, we report detections of volcano-induced AGWs in mesopause and ionosphere-thermosphere airglow imagery and Fabry-Perot interferometry. We also report unique AGW signatures in the ionospheric D-region, measured …

Discourses Across Periods Of Time, Amanda Raquel Moreno

Theses

This literature review explores the revolutionary effect of generative artificial intelligence (AI) and virtual reality (VR) on digital art history, specifically concentrating on their capacity to enable dialogical exchanges with historical figures and deepen the understanding of artworks. This study considers the current state of research, detecting key methodologies, areas of improvement, and possible challenges and ethical concerns. The example historical figure used in this analysis is the iconic Mexican artist Frida Kahlo. Kahlo’s refusal to correspond to a specific artistic style makes her an ideal subject for generative AI and VR-based investigation, offering fresh insights into her work. The …

An Econometric Modeling Of Price Support: The Bitcoin Case, Levent Kutlu

School of Economics and Finance Faculty Publications

In technical analysis, price support plays an important role. In line with the stochastic frontier analysis, we present a formal model to estimate the bottom price support for a stock or cryptocurrency. As an example, we examine Bitcoin's bottom price.