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Russia, Europe And Central Asia Energy Security And Pipeline Politics, Mehmet Kınacı

Graduate Program in International Studies Theses & Dissertations

Energy Security will continue to remain as one of the top security concerns for Europe. Depleting reserves and growing energy demand have increased European dependence on external energy resources. Today, Russia is by far the largest supplier of oil, coal and the natural gas to Europe. Oil and natural gas revenues have played a vital role to rebound the Russian economy and have supported Putin’s ambitions to reestablish Russia as a great power, increasing its influence over the former Soviet space. This complex energy relationship has increasingly been a cause of concern.

The main question this study seeks to answer …

The Expansion Of Nocs: What Strengthening State-Owned Enterprises Means For Global Energy, Alexander L. Fretz

Graduate Program in International Studies Theses & Dissertations

The rise of National Oil Companies (NOCs) in the 20th century has been well documented. However, little work has been done with respect to how these entities have evolved in the 21st century. This study aims to measure the changing strength of contemporary NOCs by comparing them to their privatized counterparts. Using this comparative analysis, the study will explain the changing global energy landscape and the potential internecine effects on the international system.

Foundations Of Plasmas For Medical Applications, T. Von Woedtke, Mounir Laroussi, M. Gherardi

Electrical & Computer Engineering Faculty Publications

Plasma medicine refers to the application of nonequilibrium plasmas at approximately body temperature, for therapeutic purposes. Nonequilibrium plasmas are weakly ionized gases which contain charged and neutral species and electric fields, and emit radiation, particularly in the visible and ultraviolet range. Medically-relevant cold atmospheric pressure plasma (CAP) sources and devices are usually dielectric barrier discharges and nonequilibrium atmospheric pressure plasma jets. Plasma diagnostic methods and modelling approaches are used to characterize the densities and fluxes of active plasma species and their interaction with surrounding matter. In addition to the direct application of plasma onto living tissue, the treatment of liquids …

Development Of A Fuzzy Logic Model-Less Aircraft Controller, Christopher M. Scott

Electrical & Computer Engineering Theses & Dissertations

The Modeling and Control for Agile Aircraft Development (MCAAD) group at NASA Langley Research Center(LaRC) is developing techniques for Real-Time Global Modeling (RTGM) and Robust Learning Control (RLC) for NASA’s Transformational Tools and Technologies Project. This project seeks to develop a systematic approach to reduce the iterative nature of aircraft design by introducing a model-less control law and enabling inflight aerodynamic modeling and controller design. The development of the flight control system without prior knowledge of the aircraft aerodynamic model makes use of TakagiSugeno-Kang fuzzy logic inference systems for pitch and roll controllers and are tested in various simulations and …

Development Of High Conductivity Copper Coatings For Srf Cavity, Himal Pokhrel

Physics Theses & Dissertations

The development of metallic coatings with high purity and high thermal conductivity at cryogenic temperature could be very important for application to the superconducting radiofrequency (SRF) cavity technology. The deposition of such bulk coatings on the outer surface of a niobium cavity could result in higher heat conductance and mechanical stiffness, both of which are crucial for enhancing the cavity performance at a reduced cost.

Cold spray technology was used to deposit bulk coatings of pure copper and copper-tungsten alloys on the niobium substrate and the samples of size 2 mm × 2 mm cross section were cut and subjected …

The Relationship Between Optional Developmental Education Enrollment And The Mathematics Achievement Of Students At One Community College In Florida, Andrea Lisa Lee

Educational Leadership & Workforce Development Theses & Dissertations

Although nearly half of community college students require some type of remediation, less than one-third of the students who start in developmental education graduate within eight years (Park, Tandberg, Hu, & Hankerson, 2016). As such, there is great uncertainty regarding the effectiveness of developmental education (Ari et al., 2016; Bailey et al., 2013). Additionally, because most institutions rely on standardized testing to determine student course placements, many critics blame placement testing procedures for the perceived ineffectiveness of developmental education (Fletcher, 2014; Jaggars & Hodara, 2013). However, rather than adjust placement procedures, some states moved away from mandated placement, and in …

A Case Study The Effects Of Student Engagement On Academic Achievement In African American Women: Comparing Undergraduate Stem Majors To Non-Stem Majors From A Historically Black College And University, Zenora E. Gay

STEMPS Theses & Dissertations

The nation is at a critical juncture in history as it seeks to increase the number of students who enter the Science, Technology, Engineering, and Mathematics (STEM) workforce. The national push to have a properly trained STEM workforce was at the forefront of the past administration’s top priority list. The higher education community has a unique opportunity to contribute to the creation of a sustainable U.S. STEM workforce. Although significant progress has been made in STEM fields, some argue that movement has been too slow in certain cases, as shown in degrees earned by women in engineering (National Academies of …

Tiktok As A Digital Activism Space: Social Justice Under Algorithmic Control, Brittany Haslem

Institute for the Humanities Theses

TikTok, a video sharing application, has become the center of viral internet culture. The app has risen in popularity so quickly that scholarly literature investigating its vast societal impact is still nascent. TikTok is not only used to discuss popular culture topics and create trends, but also being utilized as a tool for social justice activism in the United States in the wake of a tumultuous year with major events such as the coronavirus pandemic, a resurgence of the Black Lives Matter movement, and the 2020 presidential election. TikTok activism is not without critiques, ranging from concerns of foreign government …

Instructional Staff Perceptions Of Culturally Responsive Leadership, Sherrell J. Hendrix

Educational Leadership & Workforce Development Theses & Dissertations

The rise of accountability standards has resulted in an increase of attention regarding the academic achievement of minority student populations. Instructional leadership styles that operate within frameworks that specifically address race and ethnicity have been shown to be positively correlated with academic outcomes of both majority and minority student populations. Culturally responsive leadership is one of these frameworks. While the literature offers a robust vision of the behaviors and subsequent results of culturally responsive leadership, we do not yet know the perceptions held by instructional staff regarding the culturally responsive leadership of their school leader. This lack of knowledge can …

Using Stock And Flow Modeling To Address Knowledge Gaps In Marine Plastic Pollution Data, Daniel P. Martin

OES Theses and Dissertations

As plastic becomes a ubiquitous part of society, its growth outpaces waste disposal infrastructure and enters the environment as physical and chemical pollution. Plastic can also erode during the use cycle and reach the environment without any chance of being arrested by collection efforts. Plastic is a hazard to many parts of the earth’s life support system but there are many knowledge gaps regarding the processes by which plastic moves through the use cycle and environment. In particular, the ocean is generally regarded as a sink for plastic out of which it is difficult to escape, but plastic can sink …

Design And Analysis Of Electrical Power And Communication Systems For 3u Sealion Cubesat Mission, Joseph D. Siciliano

Electrical & Computer Engineering Theses & Dissertations

Old Dominion University (ODU) Space Systems students in conjunction with the United States Coast Guard Academy (USCGA) are designing and developing a 3U Very Low Earth Orbit (VLEO) CubeSat mission aptly named SeaLion. This work specifically details the design of the Electrical Power System (EPS) and Communication System of the satellite. Electrical power in orbit is a precious commodity and must be carefully regulated and distributed to ensure the satellite’s operational health. Commonly, CubeSat electrical power is retained in orbit via outward facing solar cells and stored in onboard rechargeable batteries. This thesis proposes using non-rechargeable primary battery cells and …

Implementation Of An Extended Kalman Filter Using Inertial Sensor Data For Uavs During Gps Denied Applications, Sky Seliquini

Mechanical & Aerospace Engineering Theses & Dissertations

Unmanned Aerial Vehicles (UAVs) are widely used across the industry and have a strong military application for defense. As UAVs become more accessible so does the increase of their applications, now being more limited by one’s imagination as opposed to the past where micro electric components were the limiting factor. Almost all of the applications require GPS or radio guidance. For more covert and longer range missions relying solely on GPS and radio is insufficient as the Unmanned Aerial System is vulnerable to malicious encounters like GPS Jamming and GPS Spoofing. For long range mission GPS denied environments are common …

How Does Parental Involvement Shape Kindergarten Readiness In One Title 1 Classroom?, Kiristen Moriah Boles

Teaching & Learning Theses & Dissertations

The purpose of this action research study was to explore the role parental involvement plays in Kindergarten readiness in Title 1 schools. The theoretical foundation used to support this research was Epstein’s 6 model construct of parental involvement. For this study, a compilation of qualitative and quantitative data was used based upon the question being researched. The target sample was 20 Kindergarten students in a Title 1 elementary school along with 20 of the parents. The data collected was composed from scores from state assessments, teacher created assessment data, a parent climate survey, and parent communication logs.

The results suggested …

Investigating Arrhythmia Potential In Cardiac Myocytes In Presence Of Long Qt Syndrome, Victoria Lin Lam

Biomedical Engineering Theses & Dissertations

Long QT Syndrome (LQTS) is an increasingly studied condition that leads to potentially fatal heart rhythm disorders, called arrhythmias, and sudden cardiac death. The alterations in the electrocardiograms (ECGs) seen in LQTS patients is caused by mutations to genes related to ion channels in cardiac cells. Computational modeling allows the mechanistic study of these ion channel mutations in LQTS by providing quantitative predictors of cardiac behavior in human and rabbit heart models. This work hypothesizes that the repolarization reserve in cardiac Purkinje cells (PC), that form the cardiac conduction system, is lower than that of ventricular myocytes (VM), resulting in …

A Case Study On Targeted Support Using Tpack Model For Newly Hired Secondary Mathematics Teachers, Kristin Leigh Mckitrick-Rojas

STEMPS Theses & Dissertations

As teachers plan for instruction, technology integration is an important factor in the planning and implementation process. This is become imperative in a virtual learning environment for instructors to be competent (Gregory & Lodge, 2015). Problems exist with integrating technology that aligns with teaching and learning in content areas. Among the many possible factors that contribute to these problems is lack of understanding of technology, lack of support for teachers with technology, everchanging technology tools, inadequate training alignment to instruction, technology training that is not content-specific, lack of support with the integration of technology, pedagogy, and content (Koehler et al., …

Temporal Dynamics And Seed Dispersal In Plant-Frugivore Communities Of The Dominican Republic, Spencer Christian Schubert

Biological Sciences Theses & Dissertations

Plant-animal mutualisms are a foundational component of biodiversity in terrestrial ecosystems. Most tropical forest plants have adapted to produce fleshy fruits to attract frugivorous animals to disperse seeds. Interaction patterns among plant taxa and their seed dispersers are driven by a complex suite of factors involving their evolutionary history and environmental context, and the structure of these mutualistic networks are theoretically tied to their ecological function. I carried out a series of field studies to investigate the temporal dynamics of mutualistic interactions of plant and avian frugivore communities in the central Dominican Republic and how their characteristics affect seed dispersal …

Implications Of Metal Coordination In Damage And Recognition Of Nucleic Acids And Lipid Bilayers, Ana Dreab

Chemistry & Biochemistry Theses & Dissertations

Metal ions have a myriad of biological functions from structural stability to enzymatic (de)activation and metabolic electron transfer. Redox-active metals also mediate the formation of reactive oxygen species which may either cause oxidative damage or protect cellular components. Computational modeling is used here to investigate the role of (1) metal-ion binding to antimicrobial peptides, (2) metal-ion removal and disulfide formation on zinc finger (ZF) proteins, and (3) coordination of thiones/selones for the prevention of metal-mediated redox damage.

Piscidins, natural-occurring antimicrobial peptides, efficiently kill bacteria by targeting their membranes. Their efficacy is enhanced in vitro by metal-binding and the presence of …

Machine Learning Classification Of Digitally Modulated Signals, James A. Latshaw

Electrical & Computer Engineering Theses & Dissertations

Automatic classification of digitally modulated signals is a challenging problem that has traditionally been approached using signal processing tools such as log-likelihood algorithms for signal classification or cyclostationary signal analysis. These approaches are computationally intensive and cumbersome in general, and in recent years alternative approaches that use machine learning have been presented in the literature for automatic classification of digitally modulated signals. This thesis studies deep learning approaches for classifying digitally modulated signals that use deep artificial neural networks in conjunction with the canonical representation of digitally modulated signals in terms of in-phase and quadrature components. Specifically, capsule networks are …

Chen-Fliess Series For Linear Distributed Systems, Natalie T. Pham

Electrical & Computer Engineering Theses & Dissertations

Distributed systems like fluid flow and heat transfer are modeled by partial differential equations (PDEs). In control theory, distributed systems are generally reformulated in terms of a linear state space realization, where the state space is an infinite dimensional Banach space or Hilbert space. In the finite dimension case, the input-output map can always be written in terms of a Chen-Fliess functional series, that is, a weighted sum of iterated integrals of the components of the input function. The Chen-Fliess functional series has been used to describe interconnected nonlinear systems, to solve system inversion and tracking problems, and to design …

Transparscit: A Transformer-Based Citation Parser Trained On Large-Scale Synthesized Data, Md Sami Uddin

Computer Science Theses & Dissertations

Accurately parsing citation strings is key to automatically building large-scale citation graphs, so a robust citation parser is an essential module in academic search engines. One limitation of the state-of-the-art models (such as ParsCit and Neural-ParsCit) is the lack of a large-scale training corpus. Manually annotating hundreds of thousands of citation strings is laborious and time-consuming. This thesis presents a novel transformer-based citation parser by leveraging the GIANT dataset, consisting of 1 billion synthesized citation strings covering over 1500 citation styles. As opposed to handcrafted features, our model benefits from word embeddings and character-based embeddings by combining the bidirectional long …

Development Of Modeling And Simulation Platform For Path-Planning And Control Of Autonomous Underwater Vehicles In Three-Dimensional Spaces, Sai Krishna Abhiram Kondapalli

Mechanical & Aerospace Engineering Theses & Dissertations

Autonomous underwater vehicles (AUVs) operating in deep sea and littoral environments have diverse applications including marine biology exploration, ocean environment monitoring, search for plane crash sites, inspection of ship-hulls and pipelines, underwater oil rig maintenance, border patrol, etc. Achieving autonomy in underwater vehicles relies on a tight integration between modules of sensing, navigation, decision-making, path-planning, trajectory tracking, and low-level control. This system integration task benefits from testing the related algorithms and techniques in a simulated environment before implementation in a physical test bed. This thesis reports on the development of a modeling and simulation platform that supports the design and …

Pedestrian Evacuation: Vulnerable Group Member Influence On The Group Leaders’ Decision-Making And The Impact On Evacuation Time, Terra Lynne Elzie

Computational Modeling & Simulation Engineering Theses & Dissertations

As pedestrian evacuations of buildings, outdoor venues, and special events occur, dynamic interactions between pedestrians and vehicles during egress are possible. To model pedestrian and vehicle evacuations, simulation models have evolved to incorporate more realistic crowd characteristics and behaviors to provide improved results. Past studies using modeling and simulation, specifically agent-based modeling, have explored pedestrian behaviors such as decision-making, navigation within a virtual environment, group formations, intra-group interactions, inter-group dynamics, crowd behaviors such as queuing and herding, and pedestrianvehicle interactions. These studies have led to relevant insights helpful to improving the accuracy of evacuation times for normal and emergency egress …

Data-Driven Framework For Understanding & Modeling Ride-Sourcing Transportation Systems, Bishoy Kelleny

Civil & Environmental Engineering Theses & Dissertations

Ride-sourcing transportation services offered by transportation network companies (TNCs) like Uber and Lyft are disrupting the transportation landscape. The growing demand on these services, along with their potential short and long-term impacts on the environment, society, and infrastructure emphasize the need to further understand the ride-sourcing system. There were no sufficient data to fully understand the system and integrate it within regional multimodal transportation frameworks. This can be attributed to commercial and competition reasons, given the technology-enabled and innovative nature of the system. Recently, in 2019, the City of Chicago the released an extensive and complete ride-sourcing trip-level data for …

Odu Researchers Will Put Buoys In The Mediterranean Sea To Help Schools Teach Climate Change, Mindy Ayala-Diaz

News Items

No abstract provided.

Deep Learning: The Many Approaches Of Intrusion Detection System Can Be Implemented And Improved Upon, Trinity Taylor

Cybersecurity Undergraduate Research Showcase

For my research topic I decided to look at Deep learning. Deep learning can be used in many ways for example in web searching. Deep learning can also can improve new businesses and products. Deep learning could lead to amazing discoveries. Deep learning is making a neural network learn something. In my research I talk about Intrusion detection system, traditional approach for intrusion detection, existing intrusion detection, machine learning and deep learning based intrusion detection system, and future work.

A Discussion On Supplier Selection Modeling Approaches, Sheida Etemadidavan, Andrew J. Collins

Modeling, Simulation and Visualization Student Capstone Conference

Supplier selection is a subfield of supply chain management that involves multiple steps in order for decision-makers to find suitable suppliers. Supplier selection is important as it could influence the whole company positively or negatively. It has, recently, become a topic of interest because of the recent pandemic and its effect on the global supply chain, which causes supply shortages. As such, the focus of this paper is on characteristics of decision-making modeling approaches, specifically agent-based modeling and multi-agent systems, in supplier selection, as its modeling has always been a challenge for companies due to its complex nature.

Deapsecure Computational Training For Cybersecurity: Third-Year Improvements And Impacts, Bahador Dodge, Jacob Strother, Rosby Asiamah, Karina Arcaute, Wirawan Purwanto, Masha Sosonkina, Hongyi Wu

Modeling, Simulation and Visualization Student Capstone Conference

The Data-Enabled Advanced Training Program for Cybersecurity Research and Education (DeapSECURE) was introduced in 2018 as a non-degree training consisting of six modules covering a broad range of cyberinfrastructure techniques, including high performance computing, big data, machine learning and advanced cryptography, aimed at reducing the gap between current cybersecurity curricula and requirements needed for advanced research and industrial projects. By its third year, DeapSECURE, like many other educational endeavors, experienced abrupt changes brought by the COVID-19 pandemic. The training had to be retooled to adapt to fully online delivery. Hands-on activities were reformatted to accommodate self-paced learning. In this paper, …

Medical Manikin Augmented Reality Simulation (M2ars), Pauline Delacruz, Jacob Gibson, Daniel Howard, Jaclyn Peacock, Kendall Robbins

Modeling, Simulation and Visualization Student Capstone Conference

The Medical Manikin Augmented Reality Simulation (M2ARS) is an augmented reality simulation application built for the Microsoft HoloLens 2 that uses the principles of anatomy transfer to overlay human anatomical structures onto a medical manikin digitally. These structures currently consist of the skeletal, muscular, and circulatory systems. In addition, a model of the lungs and an animated heart are also available within the simulation. M2ARS allows the user to view these structures in a manner that is both visually and spatially accurate to the human body. This application contains two modes; an augmented reality mode, which uses a manikin, and …

Multi-Modality Breast Mri Segmentation Using Nn-Unet For Preoperative Planning Of Robotic Surgery Navigation, Motaz Alqaoud, John Plemmons Md, Eric Feliberti Md, Facs, Krishnanand Kaipa, Siqin Dong, Gabor Fichtinger, Yimming Xiao, Michel Audette

Modeling, Simulation and Visualization Student Capstone Conference

Segmentation of the chest region and breast tissues is essential for surgery planning and navigation. This paper proposes the foundation for preoperative segmentation based on two cascaded architectures of deep neural networks (DNN) based on the state-of-the-art nnU-Net. Additionally, this study introduces a polyvinyl alcohol cryogel (PVA-C) breast phantom based on the segmentation of the DNN automated approach, enabling the experiments of navigation system for robotic breast surgery. Multi-modality breast MRI datasets of T2W and STIR images were acquired from 10 patients. Segmentation evaluation utilized the Dice Similarity Coefficient (DSC), segmentation accuracy, sensitivity, and specificity. First, a single class labeling …

Is Explainability Always Necessary? Discussion On Explainable Ai, Gayane Grigoryan, Andrew J. Collins

Modeling, Simulation and Visualization Student Capstone Conference

The explainability of a model has been a topic of debate. Some research states explainability is unnecessary, and some ”white-box” models, such as regression models or decision trees, are inherently explainable. This paper conducts a multiple regression model analysis with highly correlated features to illustrate how the model’s explainability fails when dealing with complex data. In this case, trusting the model explanations can be problematic. The Shapley net effect technique, which helps determine the marginal contribution of the features, is employed to improve the model explainability and reveal more information about the prediction. The work concludes that explainability is necessary …