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Articles 1 - 30 of 491
Full-Text Articles in Electrical and Computer Engineering
Microstructural And Thermal Studies Of Niobium On Copper Fabricated By Sputtering And Multicharged Ion Deposition, Md Obidul Islam
Microstructural And Thermal Studies Of Niobium On Copper Fabricated By Sputtering And Multicharged Ion Deposition, Md Obidul Islam
Electrical & Computer Engineering Theses & Dissertations
Niobium-coated copper (Nb/Cu) superconducting radiofrequency (SRF) cavities are a promising alternative to bulk niobium cavities for next-generation particle accelerators due to their reduced material cost and superior thermal conductivity of the copper substrate. However, cavity performance is fundamentally limited by the microstructural quality of sputtered Nb films and thermal transport across the Nb/Cu interface. Reduced thermal diffusivity in thin films and high interfacial thermal resistance contribute to localized heating and performance degradation under high RF fields. This dissertation addresses these challenges through a combined experimental and methodological investigation of thermal transport in Nb thin films, focusing on interface engineering using …
Machine Learning For Anomaly Detection In Neural Network Security And Srf Cavities, Hal Ferguson
Machine Learning For Anomaly Detection In Neural Network Security And Srf Cavities, Hal Ferguson
Electrical & Computer Engineering Theses & Dissertations
This dissertation explores the development and deployment of machine learning approaches to address critical challenges in anomaly detection across two distinct domains: neural network security in federated learning settings and cavity behavior analysis in particle accelerator operations at Jefferson Lab in Newport News, Virginia. Anomaly detection identifies deviations from expected patterns, safeguarding systems in cybersecurity, industry, and research against malicious activities and failures. This dissertation demonstrates how our machine learning approaches enhance detection accuracy and efficiency in both neural network security and industrial applications.
First, we investigate vulnerabilities in deep neural networks deployed in federated learning. Although federated learning preserves …
Enhancing The Design Of Strained Superlattice Gallium Arsenide Based Photocathodes With Distributed Bragg Reflector, Adam D. A. Masters
Enhancing The Design Of Strained Superlattice Gallium Arsenide Based Photocathodes With Distributed Bragg Reflector, Adam D. A. Masters
Electrical & Computer Engineering Theses & Dissertations
Particle accelerators play a crucial role in our understanding of matter and the universe and have numerous practical applications in various fields. These devices enable scientists to examine the smallest components of matter, study the forces that govern their interactions, and probe conditions from the early universe. Moreover, accelerators are valuable in medicine, industry, and research, enhancing imaging methods, cancer therapies, and manufacturing techniques. As the experiments conducted at these facilities evolve and require higher precision, improved particle sources must continue to advance to keep up with their requirements. To do that, we enhanced the design of spin polarized electron …
Computational Modeling For Automatic Superconducting Cavity Fault Prediction And Classification Using Time Series Signals, Md Monibor Rahman
Computational Modeling For Automatic Superconducting Cavity Fault Prediction And Classification Using Time Series Signals, Md Monibor Rahman
Electrical & Computer Engineering Theses & Dissertations
Processing multivariate time series signals collected from sensor networks is challenging because of complex temporal dependencies and non-stationarity. With the advent of artificial intelligence (AI) like machine learning and deep learning, it has become possible to process sensor-driven time series data more effectively than traditional statistical methods.
This dissertation aims to develop machine learning and deep learning models to address machine fault diagnosis using multivariate time series signals collected from the Continuous Electron Beam Accelerator Facility (CEBAF) at Jefferson Lab. The first goal of the proposed work is to develop deep learning–based classification models and an unsupervised fault clustering approach …
Input Structure Based Optimization For Privacy Preserving Ai Systems, Feng Yizhou
Input Structure Based Optimization For Privacy Preserving Ai Systems, Feng Yizhou
Electrical & Computer Engineering Theses & Dissertations
As Artificial Intelligence (AI) systems become increasingly integrated into critical domains, ensuring privacy-preserving model design and system deployment has become a pressing priority. Safeguarding both sensitive user data and proprietary model parameters is critical throughout the AI model and system, from data acquisition and pre-processing to model inference and deployment. However, existing privacy-preserving frameworks face several limitations, including fragmented data ownership, incomplete protection across system stages, substantial computational overhead, and poor scalability to modern architectures such as large language models. This dissertation explores a unifying optimization strategy centered on input structure design to address these challenges. The core idea is …
Multimedia Forensics: Identification And Verification Of Source Camera, Vehicle Speed Estimation, And Deepfakes Detection, Jiajun Jiang
Multimedia Forensics: Identification And Verification Of Source Camera, Vehicle Speed Estimation, And Deepfakes Detection, Jiajun Jiang
Electrical & Computer Engineering Theses & Dissertations
This dissertation advances multimedia forensics by addressing three critical research areas that enhance the authenticity verification and analysis of digital media. Multimedia forensics, which encompasses techniques for examining images, videos, audio, and text, faces increasing challenges due to sophisticated editing tools and massive data volumes. In the first study, a fast source camera identification and verification method based on PRNU analysis is proposed for video forensic investigations. By integrating camera rolling and I-frame analysis, this approach achieves a processing speed improvement of at least 15 times over conventional frame-by-frame methods while reducing false positives. The second study focuses on vehicular …
Streamer Discharge Simulation For Plasma-Assisted Combustion, Stuart Jairo Reyes
Streamer Discharge Simulation For Plasma-Assisted Combustion, Stuart Jairo Reyes
Electrical & Computer Engineering Theses & Dissertations
A common and successful method to achieve atmospheric pressure fuel-air plasma-assisted combustion is through repetitive ns pulsed discharges and dielectric-barrier discharge. The transient phase in these discharges is dominated by transport influenced by strong space charges produced by ionization fronts, this can be best represented by the streamer model. The function of non-thermal plasma in these discharges is to excite the species in the fuel-air mixture to produce radicals which accelerate the chemical conversion reactions which directly lead to temperature rise, ultimately culminating in ignition. Therefore, the characterization of the streamer and its energy partitioning is essential to developing a …
Enhancing Iot Security Using Lightweight Machine Learning Algorithms: A Comprehensive Approach Using Ensemble Learning, Feature Selection, And Federated Transfer Learning, Khawlah Harahsheh
Enhancing Iot Security Using Lightweight Machine Learning Algorithms: A Comprehensive Approach Using Ensemble Learning, Feature Selection, And Federated Transfer Learning, Khawlah Harahsheh
Electrical & Computer Engineering Theses & Dissertations
The rapid expansion of the Internet of Things (IoT) has introduced significant security vulnerabilities due to the resource-constrained nature of IoT devices and their exposure to cyber threats. Traditional security solutions are often infeasible due to the high computational and storage demands they impose. This dissertation presents a lightweight, AI-driven security framework that enhances IoT network resilience by integrating feature selection, ensemble learning, and federated transfer learning while maintaining data privacy and minimizing computational overhead.
The proposed framework consists of three primary components: Feature Selection for Intrusion Detection, which optimizes performance by reducing redundant data and improving detection accuracy with …
Optical Investigation Of A Low-Pressure Plasma In A Superconducting Radio-Frequency Cavity, Zachary A. Caudell
Optical Investigation Of A Low-Pressure Plasma In A Superconducting Radio-Frequency Cavity, Zachary A. Caudell
Electrical & Computer Engineering Theses & Dissertations
The state-of-the-art cryomodules for particle accelerators use superconducting radio-frequency (SRF) cavities. It is known that accumulation of hydrocarbon impurities reduces the cavity surface work function, decreasing cryomodule performance metrics such as field emission, thermal stability, and accelerating gradients. An in-situ method of plasma processing has recently been developed to clean the cavities and restore cryomodule performance [1]. This study is to understand the properties of the low-pressure plasmas generated in a C100 SRF cavity and ultimately to improve the performance of plasma surface cleaning using optical emission spectroscopy. Using a 500 mm focal length Czerny-Turner monochromator coupled with a photomultiplier …
Zero Dynamics Attacks On Unknown Bilinear Systems: Vulnerability And Detection, Mohammad Aminul Haq
Zero Dynamics Attacks On Unknown Bilinear Systems: Vulnerability And Detection, Mohammad Aminul Haq
Electrical & Computer Engineering Theses & Dissertations
Critical infrastructure requires a safe and secure operating environment because of its significant impact on society. Its large-scale size and distributed sensors and actuators make it vulnerable to cyber-physical attacks. A zero dynamics attack is a type of cyber-physical attack where an adversary keeps the output of the target constant (classically zero), while forcing some of the internal states to deviate from their nominal values. Most of the existing work in the literature assumes the system dynamics are linear and available to an adversary. The first goal of this dissertation is to show that an adversary can successfully execute a …
Preserving Location Authenticity: Multi-Sensor System To Thwart Gps Spoofing In Self-Driving Vehicles, Peng Jiang
Preserving Location Authenticity: Multi-Sensor System To Thwart Gps Spoofing In Self-Driving Vehicles, Peng Jiang
Electrical & Computer Engineering Theses & Dissertations
The ubiquity of the Global Positioning System (GPS) has cemented its role as the cornerstone for an array of location-based services and navigation systems, spanning applications from autonomous vehicles and drones to maritime vessels and wearable technology. Nonetheless, ensuring the integrity of reported geographical coordinates poses a formidable challenge, owing to the proliferation of diverse GPS spoofing tools. This predicament is compounded by the pervasive availability of tools like Fake GPS, Lockito, and software-defined radios, enabling even unsophisticated users to commandeer and disseminate counterfeit GPS coordinates. This dissertation undertakes the task of devising an encompassing and resilient framework, integrating a …
Broadband Dielectric Spectroscopic Detection Of Volatile Organic Compounds With Zinc Oxide And Metal-Organic Frameworks As Solid-State Sensor Materials, Papa Kojo Amoah
Broadband Dielectric Spectroscopic Detection Of Volatile Organic Compounds With Zinc Oxide And Metal-Organic Frameworks As Solid-State Sensor Materials, Papa Kojo Amoah
Electrical & Computer Engineering Theses & Dissertations
The industrial revolution drove technological progress but also increased the release of harmful pollutants, posing significant risks to human health and the environment. Volatile organic compounds (VOCs), which have various anthropogenic and natural sources, are particularly concerning due to their impact on public health, especially in urban areas. Addressing these adverse effects requires comprehensive strategies for mitigation as traditional gas sensing techniques have limitations and there is a need for innovative approaches to VOC detection.
VOCs encompass a diverse group of chemicals with high volatility, emitted from various human activities and natural sources. These compounds play a crucial role in …
Deep-Learning-Based Classification Of Digitally Modulated Signals, John A. Snoap
Deep-Learning-Based Classification Of Digitally Modulated Signals, John A. Snoap
Electrical & Computer Engineering Theses & Dissertations
This dissertation presents several novel deep-learning (DL)-based approaches for classifying digitally modulated signals, one method of which involves the use of capsule networks (CAPs) together with cyclic cumulant (CC) features of the signals. These were blindly estimated using cyclostationary signal processing (CSP) and were then input into the CAP for training and classification. The classification performance and the generalization abilities of the proposed approach were tested using two distinct datasets that contained the same types of digitally modulated signals but had distinct generation parameters. The results showed that the classification of digitally modulated signals using CAPs and CCs proposed in …
Framework For Implementing Advanced Radar Plotting Aid Capability For Small Maritime Vessels, Jason Stark Harris
Framework For Implementing Advanced Radar Plotting Aid Capability For Small Maritime Vessels, Jason Stark Harris
Electrical & Computer Engineering Theses & Dissertations
Every year in the United States many people are killed or injured when maritime vessels collide with other vessels or fixed objects. According to the United States Coast Guard, the top contributing factors to these collisions are operator inattention, operator inexperience and an improper lookout. Larger commercial vessels are required to have RADAR systems which support Automatic RADAR Plotting Aid (ARPA) which can automatically detect collisions and alert an operator to change course. These systems can be very expensive which put them out of reach of the average recreational boater. It is however possible to implement a low cost ARPA …
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 …
Generation Of Plasma With A Rotating Electric Field, Franklin Price Mosely
Generation Of Plasma With A Rotating Electric Field, Franklin Price Mosely
Electrical & Computer Engineering Theses & Dissertations
Nonthermal plasma generation is an important area of research that has many applications ranging from semiconductor production to medical applications including the treatment of cancers and sterilization of surfaces. Specific radicals and excited species and discharge powers are critical for the successful completion of these processes. It is important that these excited species are shown to be achievable for a given discharge system without leading to instabilities such as arcing.
The present thesis details the design, fabrication, testing, and analysis of a novel plasma generation system based on multiphase excitation. As predicted by theory, the experimental results demonstrate that a …
Detection, Tracking, And Classification Of Aircraft And Birds From Multirotor Small Unmanned Aircraft Systems, Chester Valentine Dolph
Detection, Tracking, And Classification Of Aircraft And Birds From Multirotor Small Unmanned Aircraft Systems, Chester Valentine Dolph
Electrical & Computer Engineering Theses & Dissertations
The ability for small Unmanned Aircraft Systems (sUAS) to safely operate beyond visual line of sight (BVLOS) is of great interest to governments, businesses, and scientific research. One critical element for sUAS to operate BVLOS is the capability to avoid other air traffic. While many aircraft will be cooperative and broadcast their locations using Automatic Dependent Surveillance Broadcast (ADS-B), it is expected that many aircraft will remain non-cooperative – meaning they do not communicate position or flight plan to other aircraft. Avoiding mid-air collisions with non-cooperative aircraft is a critical limitation to widespread sUAS flying BVLOS. Examples of non-cooperative traffic …
Integrative Physiology-Coupled Pilot-Centered Flight Simulation, Shawn C. Harrison
Integrative Physiology-Coupled Pilot-Centered Flight Simulation, Shawn C. Harrison
Electrical & Computer Engineering Theses & Dissertations
Maintaining the pilot’s physiological performance envelope within the limits of human capabilities may be crucial for avoiding hazardous physiological episodes in fighter aircraft that compromise safety. The main physiological episode of interest is impaired pilot respiration, better known as hypoxia caused by a high fraction of inspired oxygen (FiO2) at high altitudes and variation in accelerative gravitational forces (g-forces). Integrated into fighter aircraft is an Onboard Oxygen Generating System (OBOGS) developed to mitigate the necessity of gaseous and liquid oxygen cannisters [1]. OBOGS act as a life support in hypoxic environments by providing oxygen-rich air, thereby oxygenating the …
E-Beam Irradiation Beamline At Jefferson Lab For Wastewater Treatment, Xi Li
E-Beam Irradiation Beamline At Jefferson Lab For Wastewater Treatment, Xi Li
Electrical & Computer Engineering Theses & Dissertations
Electron beam (e-beam) irradiation is an advanced method for removing the emerging organic contaminants in wastewater, such as 1,4-dioxane, and per- and polyfluoroalkyl substances (PFAS), which have the potential to be regulated in the near future but are difficult to degrade by conventional treatment methods. This dissertation was based on a collaborating study between Jefferson Lab (Jlab) and Hampton Roads Sanitation District (HRSD) to evaluate the impacts of e-beam irradiation on the degradation of 1,4-dioxane and PFAS. It presents the detailed design of an e-beam irradiation beamline, the beamline simulation using general particle tracer (GPT), the installation, and the successful …
Fabrication Of Nb3Sn By Magnetron Sputtering For Superconducting Radiofrequency Application, Md Nizam Sayeed
Fabrication Of Nb3Sn By Magnetron Sputtering For Superconducting Radiofrequency Application, Md Nizam Sayeed
Electrical & Computer Engineering Theses & Dissertations
Particle accelerators are considered as an important device that has wide applications in cancer treatment, sterilizing waste, preserving foods, ion implantation in semiconductor industry, and in production of isotopes for medical applications. Superconducting radiofrequency (SRF) cavities are the building blocks of a linear particle accelerator. Current particle accelerators use niobium (Nb) superconductors as the sheet material to fabricate a single SRF cavity for particle acceleration. With better superconducting properties (critical temperature Tc ~ 18.3 K, superheating field Hsh~ 400 mT), Nb3Sn is considered a potential candidate in SRF technology. Magnetron sputtering is a promising deposition …
Emotion Detection Using An Ensemble Model Trained With Physiological Signals And Inferred Arousal-Valence States, Matthew Nathanael Gray
Emotion Detection Using An Ensemble Model Trained With Physiological Signals And Inferred Arousal-Valence States, Matthew Nathanael Gray
Electrical & Computer Engineering Theses & Dissertations
Affective computing is an exciting and transformative field that is gaining in popularity among psychologists, statisticians, and computer scientists. The ability of a machine to infer human emotion and mood, i.e. affective states, has the potential to greatly improve human-machine interaction in our increasingly digital world. In this work, an ensemble model methodology for detecting human emotions across multiple subjects is outlined. The Continuously Annotated Signals of Emotion (CASE) dataset, which is a dataset of physiological signals labeled with discrete emotions from video stimuli as well as subject-reported continuous emotions, arousal and valence, from the circumplex model, is used for …
Recrystallization Of Cu(In,Ga)Se2 Semiconductor Thin Films Via Metal Halides Treatment, Deewakar Poudel
Recrystallization Of Cu(In,Ga)Se2 Semiconductor Thin Films Via Metal Halides Treatment, Deewakar Poudel
Electrical & Computer Engineering Theses & Dissertations
The advancement of low-cost, highly efficient solar cell devices is a major technological challenge demanding suitable materials and fabrication processes. Polycrystalline Cu(In,Ga)Se2 (CIGS) appear to be one of the most promising semiconductor in thin film photovoltaic technology due to its bandgap tunability, high absorption coefficient, and tendency to produce high efficiency solar cells. High-quality CIGS materials fabricated via a three-stage co-evaporation process can convert primary materials into devices with power conversion efficiency above 23%. Increasing the deposition rate and decreasing the deposition temperature, while maintaining high efficiency, is the major concern for the CIGS solar cells to compete …
Applied Deep Learning: Case Studies In Computer Vision And Natural Language Processing, Md Reshad Ul Hoque
Applied Deep Learning: Case Studies In Computer Vision And Natural Language Processing, Md Reshad Ul Hoque
Electrical & Computer Engineering Theses & Dissertations
Deep learning has proved to be successful for many computer vision and natural language processing applications. In this dissertation, three studies have been conducted to show the efficacy of deep learning models for computer vision and natural language processing. In the first study, an efficient deep learning model was proposed for seagrass scar detection in multispectral images which produced robust, accurate scars mappings. In the second study, an arithmetic deep learning model was developed to fuse multi-spectral images collected at different times with different resolutions to generate high-resolution images for downstream tasks including change detection, object detection, and land cover …
Development Of High Quantum Efficiency Strained Superlattice Spin Polarized Photocathodes Via Metal Organic Chemical Vapor Deposition, Benjamin Belfore
Development Of High Quantum Efficiency Strained Superlattice Spin Polarized Photocathodes Via Metal Organic Chemical Vapor Deposition, Benjamin Belfore
Electrical & Computer Engineering Theses & Dissertations
Spin polarized photocathodes are necessary to examine parity violations and other fundamental phenomena in the field of high energy physics. To create these devices, expensive and complicated growth processes are necessary. While integral to accelerator physics, spin polarized electrons could have other exciting applications in materials science and other fields of physics. In order to explore these other applications feasibly, the relative supply of spin polarized photocathodes with a high rate of both polarization and photoemission needs to be increased. One such way to increase this supply is to develop the means to grow them faster and at a larger …
Machine Learning Classification Of Digitally Modulated Signals, James A. Latshaw
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 …
A Preventive Medicine Framework For Wearable Abiotic Glucose Detection System, Saikat Banerjee
A Preventive Medicine Framework For Wearable Abiotic Glucose Detection System, Saikat Banerjee
Electrical & Computer Engineering Theses & Dissertations
In this work, we present a novel abiotic glucose fuel cell with battery-less remote access. In the presence of a glucose analyte, we characterized the power generation and biosensing capabilities. This system is developed on a flexible substrate in bacterial nanocellulose with gold nanoparticles used as a conductive ink for piezoelectric deposition based printing. The abiotic glucose fuel cell is constructed using colloidal platinum on gold (Au-co-Pt) and a composite of silver oxide nanoparticles and carbon nanotubes as the anodic and cathodic materials. At a concentration of 20 mM glucose, the glucose fuel cell produced a maximum open circuit voltage …
Development Of A Fuzzy Logic Model-Less Aircraft Controller, Christopher M. Scott
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 …
Frequency Agile Ofdm System For Radio Communication In High Frequency Bands, Erin E. Hill
Frequency Agile Ofdm System For Radio Communication In High Frequency Bands, Erin E. Hill
Electrical & Computer Engineering Theses & Dissertations
High Frequency (HF) radio communication existed as the primary source of over-the-horizon communication for decades prior to the wide implementation of satellite and cellular networks. Even today, should satellite communication become unavailable, the robust backup of HF vitally supports long distance data transmission without the need of a cellular infrastructure. This capability is of particular importance to naval applications while at sea. Frequency choice, however, becomes critical in supporting reliable HF communication as too high of a frequency will not return to earth and too low of a frequency will result in high absorption rates within the atmosphere. A potential …
Chen-Fliess Series For Linear Distributed Systems, Natalie T. Pham
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 …
Design And Analysis Of Electrical Power And Communication Systems For 3u Sealion Cubesat Mission, Joseph D. Siciliano
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 …