Physical Sciences and Mathematics Commons^™

The Transformative Integration Of Artificial Intelligence With Cmmc And Nist 800-171 For Advanced Risk Management And Compliance, Mia Lunati

Cybersecurity Undergraduate Research Showcase

This paper explores the transformative potential of integrating Artificial Intelligence (AI) with established cybersecurity frameworks such as the Cybersecurity Maturity Model Certification (CMMC) and the National Institute of Standards and Technology (NIST) Special Publication 800-171. The thesis argues that the relationship between AI and these frameworks has the capacity to transform risk management in cybersecurity, where it could serve as a critical element in threat mitigation. In addition to addressing AI’s capabilities, this paper acknowledges the risks and limitations of these systems, highlighting the need for extensive research and monitoring when relying on AI. One must understand boundaries when integrating …

Potential Security Vulnerabilities In Raspberry Pi Devices With Mitigation Strategies, Briana Tolleson

Cybersecurity Undergraduate Research Showcase

For this research project I used a Raspberry Pi device and conducted online research to investigate potential security vulnerabilities along with mitigation strategies. I configured the Raspberry Pi by using the proper peripherals such as an HDMI cord, a microUSB adapter that provided 5V and at least 700mA of current, a TV monitor, PiSwitch, SD Card, keyboard, and mouse. I installed the Rasbian operating system (OS). The process to install the Rasbian took about 10 minutes to boot starting at 21:08 on 10/27/2023 and ending at 21:18. 1,513 megabytes (MB) was written to the SD card running at (2.5 MB/sec). …

Integrating Ai Into Uavs, Huong Quach

Cybersecurity Undergraduate Research Showcase

This research project explores the application of Deep Learning (DL) techniques, specifically Convolutional Neural Networks (CNNs), to develop a smoke detection algorithm for deployment on mobile platforms, such as drones and self-driving vehicles. The project focuses on enhancing the decision-making capabilities of these platforms in emergency response situations. The methodology involves three phases: algorithm development, algorithm implementation, and testing and optimization. The developed CNN model, based on ResNet50 architecture, is trained on a dataset of fire, smoke, and neutral images obtained from the web. The algorithm is implemented on the Jetson Nano platform to provide responsive support for first responders. …

Knowing Just Enough To Be Dangerous: The Sociological Effects Of Censoring Public Ai, David Hopkins

Cybersecurity Undergraduate Research Showcase

This paper will present the capabilities and security concerns of public AI, also called generative AI, and look at the societal and sociological effects of implementing regulations of this technology.

Machine Learning Approach To Activity Categorization In Young Adults Using Biomechanical Metrics, Nathan Q. C. Holland

Mechanical & Aerospace Engineering Theses & Dissertations

Inactive adults often have decreased musculoskeletal health and increased risk factors for chronic diseases. However, there is limited data linking biomechanical measurements of generally healthy young adults to their physical activity levels assessed through questionnaires. Commonly used data collection methods in biomechanics for assessing musculoskeletal health include but are not limited to muscle quality (measured as echo intensity when using ultrasound), isokinetic (i.e., dynamic) muscle strength, muscle activations, and functional movement assessments using motion capture systems. These assessments can be time consuming for both data collection and processing. Therefore, understanding if all biomechanical assessments are necessary to classify the activity …

Optics Studies For Multipass Energy Recovery At Cebaf: Er@Cebaf, Isurumali Neththikumara

Physics Theses & Dissertations

Energy recovery linacs (ERLs), focus on recycling the kinetic energy of electron beam for the purpose of accelerating a newly injected beam within the same accelerating structure. The rising developments in the super conducting radio frequency technology, ERL technology has achieved several noteworthy milestones over the past few decades. In year 2003, Jefferson Lab has successfully demonstrated a single pass energy recovery at the CEBAF accelerator. Furthermore, they conducted successful experiments with IR-FEL demo and upgrades, as well as the UV FEL driver. This multi-pass, multi-GeV range energy recovery demonstration proposed to be carried out at CEBAF accelerator at Jefferson …

Faster, Cheaper, And Better Cfd: A Case For Machine Learning To Augment Reynolds-Averaged Navier-Stokes, John Peter Romano Ii

Mechanical & Aerospace Engineering Theses & Dissertations

In recent years, the field of machine learning (ML) has made significant advances, particularly through applying deep learning (DL) algorithms and artificial intelligence (AI). The literature shows several ways that ML may enhance the power of computational fluid dynamics (CFD) to improve its solution accuracy, reduce the needed computational resources and reduce overall simulation cost. ML techniques have also expanded the understanding of underlying flow physics and improved data capture from experimental fluid dynamics.

This dissertation presents an in-depth literature review and discusses ways the field of fluid dynamics has leveraged ML modeling to date. The author selects and describes …

A Unit-Load Approach For Reliability-Based Design Optimization Of Linear Structures Under Random Loads And Boundary Conditions, Robert James Haupin, Gene Jean-Win Hou

Mechanical & Aerospace Engineering Faculty Publications

The low order Taylor’s series expansion was employed in this study to estimate the reliability indices of the failure criteria for reliability-based design optimization of a linear static structure subjected to random loads and boundary conditions. By taking the advantage of the linear superposition principle, only a few analyses of the structure subjected to unit-loads are needed through the entire optimization process to produce acceptable results. Two structural examples are presented in this study to illustrate the effectiveness of the proposed approach for reliability-based design optimization: one deals with a truss structure subjected to random multiple point constraints, and the …

A Comparative Study Of Vinti-Based Orbit Propagation And Estimation For Cubesats In Very Low Earth Orbits, Ethan Michael Senecal

Mechanical & Aerospace Engineering Theses & Dissertations

In recent years, there has been a growing interest in CubeSats and very low Earth orbit (VLEO) space missions. Mission SeaLion, a collaborative CubeSat mission between Old Dominion University, the U.S. Coast Guard Academy, and U.S. Air Force Institute of Technology, planned to launch a 3U CubeSat into VLEO. The VLEO mission is a particularly challenging environment for navigation and orbit propagation because drag introduces a significant perturbation for orbit models such as SGP4. Additionally, mission requirements left no capacity for attitude determination or control, further reducing knowledge of drag behavior of the satellite in flight. This deficiency is a …

Experimental And Computational Aerodynamic Studies Of Axially-Oriented Low-Fineness-Ratio Cylinders, Forrest Miller

Mechanical & Aerospace Engineering Theses & Dissertations

For the successful completion of atmospheric entry, descent, and landing (EDL) missions, a body geometry must be selected which provides favorable dynamic aerodynamic properties. The types of experimental facilities capable of collecting information on these properties are limited; however, their numbers are growing thanks to the continued work by the aerodynamics community. NASA Langley Research Center (LaRC) is conducting dynamic aerodynamic testing using a subsonic magnetic suspension and balance system (MSBS), with the end goal of implementing a supersonic MSBS facility at NASA Glenn Research Center. MSBSs are also currently used at the Institute of Fluid Science (IFS) at Tohoku …

Towards Intelligent Runtime Framework For Distributed Heterogeneous Systems, Polykarpos Thomadakis

Computer Science Theses & Dissertations

Scientific applications strive for increased memory and computing performance, requiring massive amounts of data and time to produce results. Applications utilize large-scale, parallel computing platforms with advanced architectures to accommodate their needs. However, developing performance-portable applications for modern, heterogeneous platforms requires lots of effort and expertise in both the application and systems domains. This is more relevant for unstructured applications whose workflow is not statically predictable due to their heavily data-dependent nature. One possible solution for this problem is the introduction of an intelligent Domain-Specific Language (iDSL) that transparently helps to maintain correctness, hides the idiosyncrasies of lowlevel hardware, and …

Study Of Microphonic Effects On The C100 Cryomodule For High Energy Electron Beam Accelerators, Caleb James Hull

Mechanical & Aerospace Engineering Theses & Dissertations

The Continuous Electron Beam Accelerator Facility (CEBAF) at Thomas Jefferson National Laboratory (JLab) is a particle accelerator which can accelerate an electron beam to relativistic speeds and apply the beam onto target samples. The C100 superconducting radio frequency (SRF) cavity is the primary accelerating structure of the C100 cryomodule, one of the many cryomodules which compose the CEBAF linear accelerator. SRF cavities are particularly sensitive to internal and external vibrations that can result in a phenomenon called microphonics which degrade the operational stability of a cryomodule.

The purpose of this thesis is to investigate the significance of mechanical disturbances on …

Towards A Robust Defense: A Multifaceted Approach To The Detection And Mitigation Of Neural Backdoor Attacks Through Feature Space Exploration And Analysis, Liuwan Zhu

Electrical & Computer Engineering Theses & Dissertations

From voice assistants to self-driving vehicles, machine learning(ML), especially deep learning, revolutionizes the way we work and live, through the wide adoption in a broad range of applications. Unfortunately, this widespread use makes deep learning-based systems a desirable target for cyberattacks, such as generating adversarial examples to fool a deep learning system to make wrong decisions. In particular, many recent studies have revealed that attackers can corrupt the training of a deep learning model, e.g., through data poisoning, or distribute a deep learning model they created with “backdoors” planted, e.g., distributed as part of a software library, so that the …

Reinforcing Digital Trust For Cloud Manufacturing Through Data Provenance Using Ethereum Smart Contracts, Trupti Narayan Rane

Engineering Management & Systems Engineering Theses & Dissertations

Cloud Manufacturing(CMfg) is an advanced manufacturing model that caters to fast-paced agile requirements (Putnik, 2012). For manufacturing complex products that require extensive resources, manufacturers explore advanced manufacturing techniques like CMfg as it becomes infeasible to achieve high standards through complete ownership of manufacturing artifacts (Kuan et al., 2011). CMfg, with other names such as Manufacturing as a Service (MaaS) and Cyber Manufacturing (NSF, 2020), addresses the shortcoming of traditional manufacturing by building a virtual cyber enterprise of geographically distributed entities that manufacture custom products through collaboration.

With manufacturing venturing into cyberspace, Digital Trust issues concerning product quality, data, and intellectual …

Evaluating Direct Filtration As An Alternative To Conventional Carbon-Based Advanced Treatment For Indirect Potable Reuse, Savannah M. Flemmer

Civil & Environmental Engineering Theses & Dissertations

Hampton Roads Sanitation District (HRSD) is recharging purified wastewater into the Potomac Aquifer via the Sustainable Water Initiative for Tomorrow (SWIFT) project. Conventional SWIFT treatment applies coagulation, flocculation, sedimentation, ozonation, biofiltration, granular activated carbon (GAC) adsorption, and ultraviolet disinfection to secondary effluent to produce water that meets drinking water standards for managed aquifer recharge. HRSD is considering implementing direct filtration as an alternative to conventional treatment for two additional SWIFT facilities. Direct filtration presents an opportunity for significant cost savings by eliminating sedimentation, shortening flocculation detention time, and reducing coagulant usage. Without upstream removal of solids and organics, however, biofilters …

Assessing The Prevalence And Archival Rate Of Uris To Git Hosting Platforms In Scholarly Publications, Emily Escamilla

Computer Science Theses & Dissertations

The definition of scholarly content has expanded to include the data and source code that contribute to a publication. While major archiving efforts to preserve conventional scholarly content, typically in PDFs (e.g., LOCKSS, CLOCKSS, Portico), are underway, no analogous effort has yet emerged to preserve the data and code referenced in those PDFs, particularly the scholarly code hosted online on Git Hosting Platforms (GHPs). Similarly, Software Heritage is working to archive public source code, but there is value in archiving the surrounding ephemera that provide important context to the code while maintaining their original URIs. In current implementations, source code …

Biocrude Production From Lignin In Hydrothermal Medium: Effect Of Rapid Heating And Short Residence Time, Kyoko Hirayama

Civil & Environmental Engineering Theses & Dissertations

This study aims to address knowledge gaps in the production of valuable products from waste streams generated during lignocellulosic biofuel production. The primary objective is to develop a process that converts lignin, a byproduct of bioethanol refineries, into a sustainable biolubricant.

The first chapter examines recent advancements in synthesizing biolubricants and investigates their scalability. It explores innovative materials, catalysts, chemical modification approaches, and additives that have emerged in the field. A particular hurdle is the oxidative stability of biolubricants derived from plant oils, which are prone to autooxidation due to their C=C bonds. To overcome this, the study aims to …

Optimal Domain-Partitioning Algorithm For Real-Life Transportation Networks And Finite Element Meshes, Jimesh Bhagatji, Sharanabasaweshwara Asundi, Eric Thompson, Duc T. Nguyen

Civil & Environmental Engineering Faculty Publications

For large-scale engineering problems, it has been generally accepted that domain-partitioning algorithms are highly desirable for general-purpose finite element analysis (FEA). This paper presents a heuristic numerical algorithm that can efficiently partition any transportation network (or any finite element mesh) into a specified number of subdomains (usually depending on the number of parallel processors available on a computer), which will result in “minimising the total number of system BOUNDARY nodes” (as a primary criterion) and achieve “balancing work loads” amongst the subdomains (as a secondary criterion). The proposed seven-step heuristic algorithm (with enhancement features) is based on engineering common sense …

Gradient-Based Trade-Off Design For Engineering Applications, Lena A. Royster, Gene Hou

Mechanical & Aerospace Engineering Faculty Publications

The goal of the trade-off design method presented in this study is to achieve newly targeted performance requirements by modifying the current values of the design variables. The trade-off design problem is formulated in the framework of Sequential Quadratic Programming. The method is computationally efficient as it is gradient-based, which, however, requires the performance functions to be differentiable. A new equation to calculate the scale factor to control the size of the design variables is introduced in this study, which can ensure the new design achieves the targeted performance objective. Three formal approaches are developed in this study for trade-off …

Iot Health Devices: Exploring Security Risks In The Connected Landscape, Abasi-Amefon Obot Affia, Hilary Finch, Woosub Jung, Issah Abubakari Samori, Lucas Potter, Xavier-Lewis Palmer

School of Cybersecurity Faculty Publications

The concept of the Internet of Things (IoT) spans decades, and the same can be said for its inclusion in healthcare. The IoT is an attractive target in medicine; it offers considerable potential in expanding care. However, the application of the IoT in healthcare is fraught with an array of challenges, and also, through it, numerous vulnerabilities that translate to wider attack surfaces and deeper degrees of damage possible to both consumers and their confidence within health systems, as a result of patient-specific data being available to access. Further, when IoT health devices (IoTHDs) are developed, a diverse range of …

Fabrication Of Solid Oxide Fuel Cell Components Using Stereolithography 3d Printing, Hannah Dyer

Mechanical & Aerospace Engineering Theses & Dissertations

Transitioning from fossil fuel supplied energy to renewable technology must meet cost efficient parameters throughout the manufacturing process while possessing the characteristics of a functioning and reliable power source. With a significant demand in renewable energy products, developmental techniques require adaptive approaches and procedures for novel materials in the manufacturing phase. This report proposes how a solid oxide fuel cell (SOFC), a renewable energy system, can employ additive manufacturing for directly 3D printing its components by utilizing stereolithography (SLA) 3D printing techniques. Fabrication of the printed components from the mixtures were first mixed with varying concentrations of ceramic powder and …

Nb3Sn Coating Of Twin Axis Cavity And Other Complex Srf Cavity Structures, Jayendrika Kumari Tiskumara

Physics Theses & Dissertations

In the field of Accelerator Science, for the low cost and increased quality factor, thin films coated niobium cavities are used in the modern SRF research. Within the potential substances, Nb₃Sn has shown higher critical temperature than niobium. Here the tin vapor diffusion method is used as the preferred technique to coat niobium cavities. So far, only elliptical cavities have been coated with Nb₃Sn and this technique has not yet been applied to cavities with complex geometries, which are also helpful in the accelerator science field. The Half-wave resonator could provide us data across frequencies of …

Measurements Of Magnetic Field Penetration Of Materials For Superconducting Radiofrequency Cavities, Iresha Harshani Senevirathne

Physics Theses & Dissertations

Superconducting Radio Frequency (SRF) cavities used in particle accelerators are typically formed from or coated with superconducting materials. Currently high purity niobium is the material of choice for SRF cavities which have been optimized to operate near their theoretical field limits. This brings about the need for significant R&D efforts to develop next generation superconducting materials which could outperform Nb and keep up with the demands of new accelerator facilities. To achieve high quality factors and accelerating gradients, the cavity material should be able to remain in the superconducting Meissner state under high RF magnetic field without penetration of quantized …

Wearable Sensor Gait Analysis For Fall Detection Using Deep Learning Methods, Haben Girmay Yhdego

Electrical & Computer Engineering Theses & Dissertations

World Health Organization (WHO) data show that around 684,000 people die from falls yearly, making it the second-highest mortality rate after traffic accidents [1]. Early detection of falls, followed by pneumatic protection, is one of the most effective means of ensuring the safety of the elderly. In light of the recent widespread adoption of wearable sensors, it has become increasingly critical that fall detection models are developed that can effectively process large and sequential sensor signal data. Several researchers have recently developed fall detection algorithms based on wearable sensor data. However, real-time fall detection remains challenging because of the wide …

Automatic Generation Of Virtual Work Guide For Complex Procedures: A Case, Shan Liu, Yuzhong Shen

Modeling, Simulation and Visualization Student Capstone Conference

Practical work guides for complex procedures are significant and highly affect the efficiency and accuracy of on-site users. This paper presents a technique to generate virtual work guides automatically for complex procedures. Firstly, the procedure information is extracted from the electronic manual in PDF format. And then, the extracted procedure steps are mapped to the virtual model parts in preparation for animation between adjacent steps. Next, smooth animations of the procedure are generated based on a 3D natural cubic spline curve to improve the spatial ability of the work guide. In addition, each step's annotation is automatically adjusted to improve …

The Legacy Of Colonization And Civil Societies In South Africa, Erika Frydenlund, Melissa Miller-Felton, Bolu Ayankojo

Modeling, Simulation and Visualization Student Capstone Conference

This research analyzes the unique ways that civil societies operate in Sub-Saharan Africa in the context of post-apartheid Cape Town, South Africa. Decades after the demise of apartheid, remnants of inequality remain without the promise of actionable change. We used a computational modeling approach to understand the dynamics of migrants in the receiving community as derived from qualitative interviews conducted with 24 stakeholders in Cape Town, South Africa between 2020 and 2021. Our findings show that the presence of NGOs can promote access to resources and reduce xenophobia if they can have the right influence on government policies.

Digital Game-Based Approach To Math Learning For Students, Gul Ayaz, Katherine Smith

Modeling, Simulation and Visualization Student Capstone Conference

Mathematics is an important subject that is pervasive across many disciplines. It is also a subject that has proven to be challenging to both teach and learn. Students face many challenges with learning math such as a lack of motivation and anxiety. To address these challenges, game-based learning has become a popular approach to stimulate students and create a more positive classroom environment. It can serve as an alternative or supplement to traditional teaching and can better engage students while developing a positive attitude toward learning. The use of games in a classroom can create a more exciting and engaging …

Gpu Utilization: Predictive Sarimax Time Series Analysis, Dorothy Dorie Parry

Modeling, Simulation and Visualization Student Capstone Conference

This work explores collecting performance metrics and leveraging the output for prediction on a memory-intensive parallel image classification algorithm - Inception v3 (or "Inception3"). Experimental results were collected by nvidia-smi on a computational node DGX-1, equipped with eight Tesla V100 Graphic Processing Units (GPUs). Time series analysis was performed on the GPU utilization data taken, for multiple runs, of Inception3’s image classification algorithm (see Figure 1). The time series model applied was Seasonal Autoregressive Integrated Moving Average Exogenous (SARIMAX).

Lidar Buoy Detection For Autonomous Marine Vessel Using Pointnet Classification, Christopher Adolphi, Dorothy Dorie Parry, Yaohang Li, Masha Sosonkina, Ahmet Saglam, Yiannis E. Papelis

Modeling, Simulation and Visualization Student Capstone Conference

Maritime autonomy, specifically the use of autonomous and semi-autonomous maritime vessels, is a key enabling technology supporting a set of diverse and critical research areas, including coastal and environmental resilience, assessment of waterway health, ecosystem/asset monitoring and maritime port security. Critical to the safe, efficient and reliable operation of an autonomous maritime vessel is its ability to perceive on-the-fly the external environment through onboard sensors. In this paper, buoy detection for LiDAR images is explored by using several tools and techniques: machine learning methods, Unity Game Engine (herein referred to as Unity) simulation, and traditional image processing. The Unity Game …

Assessing Frustration Towards Venezuelan Migrants In Columbia: Path Analysis On Newspaper Coded Data, Brian Llinás, Guljannat Huseynli, Erika Frydenlund, Katherine Palacia, Jose Padilla

Modeling, Simulation and Visualization Student Capstone Conference

This study analyzes the impact of Venezuelan migrants on local frustration levels in Colombia. The study found a relationship between the influx of Venezuelan migrants and the level of frustration among locals towards migrants, infrastructure, government, and geopolitics. Additionally, we identified that frustration types have an impact on other frustrations. The study used articles from a national newspaper in Colombia from 2015 to 2020. News articles were coded during a previous study qualitatively and categorized into frustration types. The code frequencies were then used as variables in this study. We used path modeling to statistically study the relationship between dependent …