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Articles 31 - 60 of 208
Full-Text Articles in Physical Sciences and Mathematics
Arithfusion: An Arithmetic Deep Model For Temporal Remote Sensing Image Fusion, Md Reshad Ul Hoque, Jian Wu, Chiman Kwan, Krzysztof Koperski, Jiang Li
Arithfusion: An Arithmetic Deep Model For Temporal Remote Sensing Image Fusion, Md Reshad Ul Hoque, Jian Wu, Chiman Kwan, Krzysztof Koperski, Jiang Li
Electrical & Computer Engineering Faculty Publications
Different satellite images may consist of variable numbers of channels which have different resolutions, and each satellite has a unique revisit period. For example, the Landsat-8 satellite images have 30 m resolution in their multispectral channels, the Sentinel-2 satellite images have 10 m resolution in the pan-sharp channel, and the National Agriculture Imagery Program (NAIP) aerial images have 1 m resolution. In this study, we propose a simple yet effective arithmetic deep model for multimodal temporal remote sensing image fusion. The proposed model takes both low- and high-resolution remote sensing images at t1 together with low-resolution images at a …
Qu-Brats: Miccai Brats 2020 Challenge On Quantifying Uncertainty In Brain Tumor Segmentation - Analysis Of Ranking Scores And Benchmarking Results, Raghav Mehta, Angelos Filos, Ujjwal Baid, Chiharu Sako, Richard Mckinley, Michael Rebsamen, Katrin Dätwyler, Raphael Meier, Piotr Radojewski, Gowtham Krishnan Murugesan, Sahil Nalawade, Chandan Ganesh, Ben Wagner, Fang F. Yu, Baowei Fei, Ananth J. Madhuranthakam, Joseph A. Maldjian, Laura Daza, Catalina Gómez, Pablo Arbeláez, Chengliang Dai, Shuo Wang, Hadrien Reynaud, Yuan-Han Mo, Elsa Angelini, Yike Guo, Wenjia Bai, Subhashis Banerjee, Lin-Min Pei, Murat Ak, Sarahi Rosas-González, Ilyess Zemmoura, Clovis Tauber, Minh H. Vu, Tufve Nyholm, Tommy Löfstedt, Laura Mora Ballestar, Veronica Vilaplana, Hugh Mchugh, Gonzalo Maso Talou, Alan Wang, Jay Patel, Ken Chang, Katharina Hoebel, Mishka Gidwani, Nishanth Arun, Sharut Gupta, Mehak Aggarwal, Praveer Singh, Elizabeth R. Gerstner, Jayashree Kalpathy-Cramer, Nicholas Boutry, Alexis Huard, Lasitha Vidyaratne, Md. Monibor Rahman, Khan M. Iftekharuddin, Joseph Chazalon, Elodie Puybareau, Guillaume Tochon, Jun Ma, Mariano Cabezas, Xavier Llado, Arnau Oliver, Liliana Valencia, Sergi Valverde, Mehdi Amian, Mohammadreza Soltaninejad, Andriy Myronenko, Ali Hatamizadeh, Xue Feng, Quan Dou, Nicholas Tustison, Craig Meyer, Nisarg A. Shah, Sanjay Talbar, Marc-André Weber, Abhishek Mahajan, Andras Jakab, Roland Wiest, Hassan M. Fathallah-Shaykh, Arash Nazeri, Mikhail Milchenko1, Daniel Marcus, Aikaterini Kotrotsou, Rivka Colen, John Freymann, Justin Kirby, Christos Davatzikos, Bjoern Menze, Spyridon Bakas, Yarin Gal, Tal Arbel
Qu-Brats: Miccai Brats 2020 Challenge On Quantifying Uncertainty In Brain Tumor Segmentation - Analysis Of Ranking Scores And Benchmarking Results, Raghav Mehta, Angelos Filos, Ujjwal Baid, Chiharu Sako, Richard Mckinley, Michael Rebsamen, Katrin Dätwyler, Raphael Meier, Piotr Radojewski, Gowtham Krishnan Murugesan, Sahil Nalawade, Chandan Ganesh, Ben Wagner, Fang F. Yu, Baowei Fei, Ananth J. Madhuranthakam, Joseph A. Maldjian, Laura Daza, Catalina Gómez, Pablo Arbeláez, Chengliang Dai, Shuo Wang, Hadrien Reynaud, Yuan-Han Mo, Elsa Angelini, Yike Guo, Wenjia Bai, Subhashis Banerjee, Lin-Min Pei, Murat Ak, Sarahi Rosas-González, Ilyess Zemmoura, Clovis Tauber, Minh H. Vu, Tufve Nyholm, Tommy Löfstedt, Laura Mora Ballestar, Veronica Vilaplana, Hugh Mchugh, Gonzalo Maso Talou, Alan Wang, Jay Patel, Ken Chang, Katharina Hoebel, Mishka Gidwani, Nishanth Arun, Sharut Gupta, Mehak Aggarwal, Praveer Singh, Elizabeth R. Gerstner, Jayashree Kalpathy-Cramer, Nicholas Boutry, Alexis Huard, Lasitha Vidyaratne, Md. Monibor Rahman, Khan M. Iftekharuddin, Joseph Chazalon, Elodie Puybareau, Guillaume Tochon, Jun Ma, Mariano Cabezas, Xavier Llado, Arnau Oliver, Liliana Valencia, Sergi Valverde, Mehdi Amian, Mohammadreza Soltaninejad, Andriy Myronenko, Ali Hatamizadeh, Xue Feng, Quan Dou, Nicholas Tustison, Craig Meyer, Nisarg A. Shah, Sanjay Talbar, Marc-André Weber, Abhishek Mahajan, Andras Jakab, Roland Wiest, Hassan M. Fathallah-Shaykh, Arash Nazeri, Mikhail Milchenko1, Daniel Marcus, Aikaterini Kotrotsou, Rivka Colen, John Freymann, Justin Kirby, Christos Davatzikos, Bjoern Menze, Spyridon Bakas, Yarin Gal, Tal Arbel
Electrical & Computer Engineering Faculty Publications
Deep learning (DL) models have provided the state-of-the-art performance in a wide variety of medical imaging benchmarking challenges, including the Brain Tumor Segmentation (BraTS) challenges. However, the task of focal pathology multi-compartment segmentation (e.g., tumor and lesion sub-regions) is particularly challenging, and potential errors hinder the translation of DL models into clinical workflows. Quantifying the reliability of DL model predictions in the form of uncertainties, could enable clinical review of the most uncertain regions, thereby building trust and paving the way towards clinical translation. Recently, a number of uncertainty estimation methods have been introduced for DL medical image segmentation tasks. …
Deeppose: Detecting Gps Spoofing Attack Via Deep Recurrent Neural Network, Peng Jiang, Hongyi Wu, Chunsheng Xin
Deeppose: Detecting Gps Spoofing Attack Via Deep Recurrent Neural Network, Peng Jiang, Hongyi Wu, Chunsheng Xin
Electrical & Computer Engineering Faculty Publications
The Global Positioning System (GPS) has become a foundation for most location-based services and navigation systems, such as autonomous vehicles, drones, ships, and wearable devices. However, it is a challenge to verify if the reported geographic locations are valid due to various GPS spoofing tools. Pervasive tools, such as Fake GPS, Lockito, and software-defined radio, enable ordinary users to hijack and report fake GPS coordinates and cheat the monitoring server without being detected. Furthermore, it is also a challenge to get accurate sensor readings on mobile devices because of the high noise level introduced by commercial motion sensors. To this …
Deep Learning Based Superconducting Radio-Frequency Cavity Fault Classification At Jefferson Laboratory, Lasitha Vidyaratne, Adam Carpenter, Tom Powers, Chris Tennant, Khan M. Iftekharuddin, Md. Monibor Rahman, Anna S. Shabalina
Deep Learning Based Superconducting Radio-Frequency Cavity Fault Classification At Jefferson Laboratory, Lasitha Vidyaratne, Adam Carpenter, Tom Powers, Chris Tennant, Khan M. Iftekharuddin, Md. Monibor Rahman, Anna S. Shabalina
Electrical & Computer Engineering Faculty Publications
This work investigates the efficacy of deep learning (DL) for classifying C100 superconducting radio-frequency (SRF) cavity faults in the Continuous Electron Beam Accelerator Facility (CEBAF) at Jefferson Lab. CEBAF is a large, high-power continuous wave recirculating linac that utilizes 418 SRF cavities to accelerate electrons up to 12 GeV. Recent upgrades to CEBAF include installation of 11 new cryomodules (88 cavities) equipped with a low-level RF system that records RF time-series data from each cavity at the onset of an RF failure. Typically, subject matter experts (SME) analyze this data to determine the fault type and identify the cavity of …
Bitcoin Selfish Mining Modeling And Dependability Analysis, Chencheng Zhou, Liudong Xing, Jun Guo, Qisi Liu
Bitcoin Selfish Mining Modeling And Dependability Analysis, Chencheng Zhou, Liudong Xing, Jun Guo, Qisi Liu
Electrical & Computer Engineering Faculty Publications
Blockchain technology has gained prominence over the last decade. Numerous achievements have been made regarding how this technology can be utilized in different aspects of the industry, market, and governmental departments. Due to the safety-critical and security-critical nature of their uses, it is pivotal to model the dependability of blockchain-based systems. In this study, we focus on Bitcoin, a blockchain-based peer-to-peer cryptocurrency system. A continuous-time Markov chain-based analytical method is put forward to model and quantify the dependability of the Bitcoin system under selfish mining attacks. Numerical results are provided to examine the influences of several key parameters related to …
Spectrum Sensing With Energy Detection In Multiple Alternating Time Slots, Călin Vlădeanu, Alexandru Marţian, Dimitrie C. Popescu
Spectrum Sensing With Energy Detection In Multiple Alternating Time Slots, Călin Vlădeanu, Alexandru Marţian, Dimitrie C. Popescu
Electrical & Computer Engineering Faculty Publications
Energy detection (ED) represents a low complexity approach used by secondary users (SU) to sense spectrum occupancy by primary users (PU) in cognitive radio (CR) systems. In this paper, we present a new algorithm that senses the spectrum occupancy by performing ED in K consecutive sensing time slots starting from the current slot and continuing by alternating before and after the current slot. We consider a PU traffic model specified in terms of an average duty cycle value, and derive analytical expressions for the false alarm probability (FAP) and correct detection probability (CDP) for any value of K . Our …
Beamline For E-Beam Processing At Uitf, G. Ciovati, C. Bott, S. Gregory, F. Hannon, Xi Li, M. Mccaughan, R. Pearce, M. Poelker, H. Vennekate
Beamline For E-Beam Processing At Uitf, G. Ciovati, C. Bott, S. Gregory, F. Hannon, Xi Li, M. Mccaughan, R. Pearce, M. Poelker, H. Vennekate
Electrical & Computer Engineering Faculty Publications
No abstract provided.
Grand Challenges In Low Temperature Plasmas, Xinpei Lu, Peter J. Bruggeman, Stephan Reuter, George Naidis, Annemie Bogaerts, Mounir Laroussi, Michael Keidar, Eric Robert, Jean-Michel Pouvesle, Dawei Liu, Kostya (Ken) Ostrikov
Grand Challenges In Low Temperature Plasmas, Xinpei Lu, Peter J. Bruggeman, Stephan Reuter, George Naidis, Annemie Bogaerts, Mounir Laroussi, Michael Keidar, Eric Robert, Jean-Michel Pouvesle, Dawei Liu, Kostya (Ken) Ostrikov
Electrical & Computer Engineering Faculty Publications
Low temperature plasmas (LTPs) enable to create a highly reactive environment at near ambient temperatures due to the energetic electrons with typical kinetic energies in the range of 1 to 10 eV (1 eV = 11600K), which are being used in applications ranging from plasma etching of electronic chips and additive manufacturing to plasma-assisted combustion. LTPs are at the core of many advanced technologies. Without LTPs, many of the conveniences of modern society would simply not exist. New applications of LTPs are continuously being proposed. Researchers are facing many grand challenges before these new applications can be translated to practice. …
Real-Time Cavity Fault Prediction In Cebaf Using Deep Learning, Md. M. Rahman, K. Iftekharuddin, A. Carptenter, T. Mcguckin, C. Tennant, L. Vidyaratne, Sandra Biedron (Ed.), Evgenya Simakov (Ed.), Stephen Milton (Ed.), Petr M. Anisimov (Ed.), Volker R.W. Schaa (Ed.)
Real-Time Cavity Fault Prediction In Cebaf Using Deep Learning, Md. M. Rahman, K. Iftekharuddin, A. Carptenter, T. Mcguckin, C. Tennant, L. Vidyaratne, Sandra Biedron (Ed.), Evgenya Simakov (Ed.), Stephen Milton (Ed.), Petr M. Anisimov (Ed.), Volker R.W. Schaa (Ed.)
Electrical & Computer Engineering Faculty Publications
Data-driven prediction of future faults is a major research area for many industrial applications. In this work, we present a new procedure of real-time fault prediction for superconducting radio-frequency (SRF) cavities at the Continuous Electron Beam Accelerator Facility (CEBAF) using deep learning. CEBAF has been afflicted by frequent downtime caused by SRF cavity faults. We perform fault prediction using pre-fault RF signals from C100-type cryomodules. Using the pre-fault signal information, the new algorithm predicts the type of cavity fault before the actual onset. The early prediction may enable potential mitigation strategies to prevent the fault. In our work, we apply …
Facial Landmark Feature Fusion In Transfer Learning Of Child Facial Expressions, Megan A. Witherow, Manar D. Samad, Norou Diawara, Khan M. Iftekharuddin
Facial Landmark Feature Fusion In Transfer Learning Of Child Facial Expressions, Megan A. Witherow, Manar D. Samad, Norou Diawara, Khan M. Iftekharuddin
Electrical & Computer Engineering Faculty Publications
Automatic classification of child facial expressions is challenging due to the scarcity of image samples with annotations. Transfer learning of deep convolutional neural networks (CNNs), pretrained on adult facial expressions, can be effectively finetuned for child facial expression classification using limited facial images of children. Recent work inspired by facial age estimation and age-invariant face recognition proposes a fusion of facial landmark features with deep representation learning to augment facial expression classification performance. We hypothesize that deep transfer learning of child facial expressions may also benefit from fusing facial landmark features. Our proposed model architecture integrates two input branches: a …
Hybridization From Guest-Host Interactions Reduces The Thermal Conductivity Of Metal-Organic Frameworks, Mallory E. Decoster, Hasan Babaei, Sangeun S. Jung, Zeinab M. Hassan, John T. Gaskins, Ashutosh Giri, Emma M. Tiernan, John A. Tomko, Helmut Baumgart, Pamela M. Norris, Alan J.H. Mcgaughey, Christopher E. Wilmer, Engelbert Redel, Gaurav Giri, Patrick E. Hopkins
Hybridization From Guest-Host Interactions Reduces The Thermal Conductivity Of Metal-Organic Frameworks, Mallory E. Decoster, Hasan Babaei, Sangeun S. Jung, Zeinab M. Hassan, John T. Gaskins, Ashutosh Giri, Emma M. Tiernan, John A. Tomko, Helmut Baumgart, Pamela M. Norris, Alan J.H. Mcgaughey, Christopher E. Wilmer, Engelbert Redel, Gaurav Giri, Patrick E. Hopkins
Electrical & Computer Engineering Faculty Publications
We experimentally and theoretically investigate the thermal conductivity and mechanical properties of polycrystalline HKUST-1 metal–organic frameworks (MOFs) infiltrated with three guest molecules: tetracyanoquinodimethane (TCNQ), 2,3,5,6-tetrafluoro-7,7,8,8-tetracyanoquinodimethane (F4-TCNQ), and (cyclohexane-1,4-diylidene)dimalononitrile (H4-TCNQ). This allows for modification of the interaction strength between the guest and host, presenting an opportunity to study the fundamental atomic scale mechanisms of how guest molecules impact the thermal conductivity of large unit cell porous crystals. The thermal conductivities of the guest@MOF systems decrease significantly, by on average a factor of 4, for all infiltrated samples as compared to the uninfiltrated, pristine HKUST-1. This reduction in thermal conductivity goes in …
Runtime Power Allocation Based On Multi-Gpu Utilization In Gamess, Masha Sosonkina, Vaibhav Sundriyal, Jorge Luis Galvez Vallejo
Runtime Power Allocation Based On Multi-Gpu Utilization In Gamess, Masha Sosonkina, Vaibhav Sundriyal, Jorge Luis Galvez Vallejo
Electrical & Computer Engineering Faculty Publications
To improve the power consumption of parallel applications at the runtime, modern processors provide frequency scaling and power limiting capabilities. In this work, a runtime strategy is proposed to maximize performance under a given power budget by distributing the available power according to the relative GPU utilization. Time series forecasting methods were used to develop workload prediction models that provide accurate prediction of GPU utilization during application execution. Experiments were performed on a multi-GPU computing platform DGX-1 equipped with eight NVIDIA V100 GPUs used for quantum chemistry calculations in the GAMESS package. For a limited power budget, the proposed strategy …
Generation Of Excited Species In A Streamer Discharge, Shirshak K. Dhali
Generation Of Excited Species In A Streamer Discharge, Shirshak K. Dhali
Electrical & Computer Engineering Faculty Publications
At or near atmospheric pressure, most transient discharges, particularly in molecular gases or gas mixture containing molecular gases, result in a space charge dominated transport called a streamer discharge. The excited species generation in such discharges forms the basis for plasma chemistry in most technological applications. In this paper, we simulate the propagation of streamers in atmospheric pressure N2 to understand the energy partitioning in the formation of various excited species and compare the results to a uniform Townsend discharge. The model is fully two-dimensional with azimuthal symmetry. The results show a significantly larger fraction of the energy goes …
Joint Modeling Of Rnaseq And Radiomics Data For Glioma Molecular Characterization And Prediction, Zeina A. Shboul, Norou Diawara, Arastoo Vossough, James Y. Chen, Khan M. Iftekharuddin
Joint Modeling Of Rnaseq And Radiomics Data For Glioma Molecular Characterization And Prediction, Zeina A. Shboul, Norou Diawara, Arastoo Vossough, James Y. Chen, Khan M. Iftekharuddin
Electrical & Computer Engineering Faculty Publications
RNA sequencing (RNAseq) is a recent technology that profiles gene expression by measuring the relative frequency of the RNAseq reads. RNAseq read counts data is increasingly used in oncologic care and while radiology features (radiomics) have also been gaining utility in radiology practice such as disease diagnosis, monitoring, and treatment planning. However, contemporary literature lacks appropriate RNA-radiomics (henceforth, radiogenomics) joint modeling where RNAseq distribution is adaptive and also preserves the nature of RNAseq read counts data for glioma grading and prediction. The Negative Binomial (NB) distribution may be useful to model RNAseq read counts data that addresses potential shortcomings. …
Rapid Quantification Of Biofouling With An Inexpensive, Underwater Camera And Image Analysis, Matthew R. First, Scott C. Riley, Kazi Aminul Islam, Victoria Hill, Jiang Li, Richard C. Zimmerman, Lisa A. Drake
Rapid Quantification Of Biofouling With An Inexpensive, Underwater Camera And Image Analysis, Matthew R. First, Scott C. Riley, Kazi Aminul Islam, Victoria Hill, Jiang Li, Richard C. Zimmerman, Lisa A. Drake
Electrical & Computer Engineering Faculty Publications
To reduce the transport of potentially invasive species on ships' submerged surfaces, rapid-and accurate-estimates of biofouling are needed so shipowners and regulators can effectively assess and manage biofouling. This pilot study developed a model approach for that task. First, photographic images were collected in situ with a submersible, inexpensive pocket camera. These images were used to develop image processing algorithms and train machine learning models to classify images containing natural assemblages of fouling organisms. All of the algorithms and models were implemented in a widely available software package (MATLAB©). Initially, an unsupervised clustering model was used, and three …
Reflection And Transmission Of Electromagnetic Pulses At A Planar Dielectric Interface: Theory And Quantum Lattice Simulations, Abhay K. Ram, George Vahala, Linda Vahala, Min Soe
Reflection And Transmission Of Electromagnetic Pulses At A Planar Dielectric Interface: Theory And Quantum Lattice Simulations, Abhay K. Ram, George Vahala, Linda Vahala, Min Soe
Electrical & Computer Engineering Faculty Publications
There is considerable interest in the application of quantum information science to advance computations in plasma physics. A particular point of curiosity is whether it is possible to take advantage of quantum computers to speed up numerical simulations relative to conventional computers. Many of the topics in fusion plasma physics are classical in nature. In order to implement them on quantum computers, it will require couching a classical problem in the language of quantum mechanics. Electromagnetic waves are routinely used in fusion experiments to heat a plasma or to generate currents in the plasma. The propagation of electromagnetic waves is …
Formal Power Series Approach To Nonlinear Systems With Static Output Feedback, G.S. Venkatesh, W. Steven Gray
Formal Power Series Approach To Nonlinear Systems With Static Output Feedback, G.S. Venkatesh, W. Steven Gray
Electrical & Computer Engineering Faculty Publications
The goal of this paper is to compute the generating series of a closed-loop system when the plant is described in terms of a Chen-Fliess series and static output feedback is applied. The first step is to reconsider the so called Wiener-Fliess connection consisting of a Chen-Fliess series followed by a memoryless function. Of particular importance will be the contractive nature of this map, which is needed to show that the closed-loop system has a Chen-Fliess series representation. To explicitly compute the generating series, two Hopf algebras are needed, the existing output feedback Hopf algebra used to describe dynamic output …
Continuity Of Chen-Fliess Series For Applications In System Identification And Machine Learning, Rafael Dahmen, W. Steven Gray, Alexander Schmeding
Continuity Of Chen-Fliess Series For Applications In System Identification And Machine Learning, Rafael Dahmen, W. Steven Gray, Alexander Schmeding
Electrical & Computer Engineering Faculty Publications
Model continuity plays an important role in applications like system identification, adaptive control, and machine learning. This paper provides sufficient conditions under which input-output systems represented by locally convergent Chen-Fliess series are jointly continuous with respect to their generating series and as operators mapping a ball in an Lp-space to a ball in an Lq-space, where p and q are conjugate exponents. The starting point is to introduce a class of topological vector spaces known as Silva spaces to frame the problem and then to employ the concept of a direct limit to describe convergence. The proof of the main …
Transient Behavior Of Drift And Ionization In Atmospheric Pressure Nitrogen Discharge, S. K. Dhali
Transient Behavior Of Drift And Ionization In Atmospheric Pressure Nitrogen Discharge, S. K. Dhali
Electrical & Computer Engineering Faculty Publications
The fluid models are frequently used to describe a non-thermal plasma such as a streamer discharge. The required electron transport data and rate coefficients for the fluid model are parametrized using the local field approximation (LFA) in first order models and the local-mean-energy approximation (LMEA) in second order models. We performed Monte Carlo simulations in Nitrogen gas with step changes in the E/N (reduced electric field) to study the behavior of the transport properties in the transient phase. During the transient phase of the simulation, we extract the instantaneous electron mean energy, which is different from the steady state mean …
The Resistive Barrier Discharge: A Brief Review Of The Device And Its Biomedical Applications, Mounir Laroussi
The Resistive Barrier Discharge: A Brief Review Of The Device And Its Biomedical Applications, Mounir Laroussi
Electrical & Computer Engineering Faculty Publications
This paper reviews the principles behind the design and operation of the resistive barrier discharge, a low temperature plasma source that operates at atmospheric pressure. One of the advantages of this plasma source is that it can be operated using either DC or AC high voltages. Plasma generated by the resistive barrier discharge has been used to efficiently inactivate pathogenic microorganisms and to destroy cancer cells. These biomedical applications of low temperature plasma are of great interest because in recent times bacteria developed increased resistance to antibiotics and because present cancer therapies often are accompanied by serious side effects. Low …
Simulation Studies On The Interactions Of Electron Beam With Wastewater, X. Li, S. Wang, Helmut Baumgart, G. Ciovati, F. Hannon
Simulation Studies On The Interactions Of Electron Beam With Wastewater, X. Li, S. Wang, Helmut Baumgart, G. Ciovati, F. Hannon
Electrical & Computer Engineering Faculty Publications
The manufactured chemical pollutants, like 1,4 dioxane and PFAS (per- and polyfluroralkyl substances), found in the underground water and/or drinking water are challenging to be removed or biodegraded. Energetic electrons are capable of mediating and removing them. This paper utilizes FLUKA code to evaluate the beam-wastewater interaction effects with different energy, space and divergence distributions of the electron beam. With 8 MeV average energy, the electron beam exits from a 0.0127 cm thick titanium window, travels through a 4.3 cm distance air and a second 0.0127 cm thick stainless water container window with 2.43 cm radius, and finally is injected …
Cylindrical Magnetron Development For Nb₃Sn Deposition Via Magnetron Sputtering, Md. Nizam Sayeed, Hani Elsayed-Ali, C. Côté, M. A. Farzad, A. Sarkissian, G. V. Eremeev, A-M. Valente-Feliciano
Cylindrical Magnetron Development For Nb₃Sn Deposition Via Magnetron Sputtering, Md. Nizam Sayeed, Hani Elsayed-Ali, C. Côté, M. A. Farzad, A. Sarkissian, G. V. Eremeev, A-M. Valente-Feliciano
Electrical & Computer Engineering Faculty Publications
Due to its better superconducting properties (critical temperature Tc~ 18.3 K, superheating field Hsh~ 400 mT), Nb3Sn is considered as a potential alternative to niobium (Tc~ 9.25 K, Hsh~ 200 mT) for superconducting radiofrequency (SRF) cavities for particle acceleration. Magnetron sputtering is an effective method to produce superconducting Nb3Sn films. We deposited superconducting Nb3Sn films on samples with magnetron sputtering using co-sputtering, sequential sputtering, and sputtering from a stoichiometric target. Nb3Sn films produced by magnetron sputtering in our previous experiments have achieved DC superconducting critical temperature up to …
Matters Of Biocybersecurity With Consideration To Propaganda Outlets And Biological Agents, Xavier-Lewis Palmer, Ernestine Powell, Lucas Potter, Thaddeus Eze (Ed.), Lee Speakman (Ed.), Cyril Onwubiko (Ed.)
Matters Of Biocybersecurity With Consideration To Propaganda Outlets And Biological Agents, Xavier-Lewis Palmer, Ernestine Powell, Lucas Potter, Thaddeus Eze (Ed.), Lee Speakman (Ed.), Cyril Onwubiko (Ed.)
Electrical & Computer Engineering Faculty Publications
The modern era holds vast modalities in human data utilization. Within Biocybersecurity (BCS), categories of biological information, especially medical information transmitted online, can be viewed as pathways to destabilize organizations. Therefore, analysis of how the public, along with medical providers, process such data, and the methods by which false information, particularly propaganda, can be used to upset the flow of verified information to populations of medical professionals, is important for maintenance of public health. Herein, we discuss some interplay of BCS within the scope of propaganda and considerations for navigating the field.
Using Ai For Management Of Field Emission In Srf Linacs, A. Carpenter, P. Degtiarenko, R. Suleiman, C. Tennant, D. Turner, L. S. Vidyaratne, Khan Iftekharuddin, Md. Monibor Rahman
Using Ai For Management Of Field Emission In Srf Linacs, A. Carpenter, P. Degtiarenko, R. Suleiman, C. Tennant, D. Turner, L. S. Vidyaratne, Khan Iftekharuddin, Md. Monibor Rahman
Electrical & Computer Engineering Faculty Publications
Field emission control, mitigation, and reduction is critical for reliable operation of high gradient superconducting radio-frequency (SRF) accelerators. With the SRF cavities at high gradients, the field emission of electrons from cavity walls can occur and will impact the operational gradient, radiological environment via activated components, and reliability of CEBAF’s two linacs. A new effort has started to minimize field emission in the CEBAF linacs by re-distributing cavity gradients. To measure radiation levels, newly designed neutron and gamma radiation dose rate monitors have been installed in both linacs. Artificial intelligence (AI) techniques will be used to identify cavities with high …
Initial Studies Of Cavity Fault Prediction At Jefferson Laboratory, L.S. Vidyaratne, A. Carpenter, R. Suleiman, C. Tennant, D. Turner, Khan Iftekharuddin, Md. Monibor Rahman
Initial Studies Of Cavity Fault Prediction At Jefferson Laboratory, L.S. Vidyaratne, A. Carpenter, R. Suleiman, C. Tennant, D. Turner, Khan Iftekharuddin, Md. Monibor Rahman
Electrical & Computer Engineering Faculty Publications
The Continuous Electron Beam Accelerator Facility (CEBAF) at Jefferson Laboratory is a CW recirculating linac that utilizes over 400 superconducting radio-frequency (SRF) cavities to accelerate electrons up to 12 GeV through 5-passes. Recent work has shown that, given RF signals from a cavity during a fault as input, machine learning approaches can accurately classify the fault type. In this paper we report on initial results of predicting a fault onset using only data prior to the failure event. A data set was constructed using time-series data immediately before a fault (’unstable’) and 1.5 seconds prior to a fault (’stable’) gathered …
Design Of A 10 Mev Beamline At The Upgraded Injector Test Facility For E-Beam Irradiation, Xi Li, Helmut Baumgart, Gianluigi Ciovati, F.E. Hannon, S. Wang
Design Of A 10 Mev Beamline At The Upgraded Injector Test Facility For E-Beam Irradiation, Xi Li, Helmut Baumgart, Gianluigi Ciovati, F.E. Hannon, S. Wang
Electrical & Computer Engineering Faculty Publications
Electron beam irradiation near 10 MeV is suitable for wastewater treatment. The Upgraded Injector Test Facility (UITF) at Jefferson Lab is a CW superconducting linear accelerator capable of providing an electron beam of energy up to 10 MeV and up to 100 µA current. This contribution presents the beam transport simulations for a beamline to be used for the irradiation of wastewater samples at the UITF. The simulations were done using the code General Particle Tracer with the goal of obtaining an 8 MeV electron beam of radius (3-σ) of ~2.4 cm. The achieved energy spread is ~74.5 keV. The …
Assessment Of Cu(In, Ga)Se₂ Solar Cells Degradation Due To Water Ingress Effect On The Cds Buffer Layer, Deewakar Poudel, Benjamin Belfore, Shankar Karki, Grace Rajan, Sina Soltanmohammad, Angus Rockett, Sylvain Marsillac
Assessment Of Cu(In, Ga)Se₂ Solar Cells Degradation Due To Water Ingress Effect On The Cds Buffer Layer, Deewakar Poudel, Benjamin Belfore, Shankar Karki, Grace Rajan, Sina Soltanmohammad, Angus Rockett, Sylvain Marsillac
Electrical & Computer Engineering Faculty Publications
The effect of water ingress on the surface of the buffer layer of a Cu(In, Ga)Se2 (CIGS) solar cell was studied. Such degradation can occur either during the fabrication process, if it involves a chemical bath as is often the case for CdS, or while the modules are in the field and encapsulants degrade. To simulate the impact of this moisture ingress, devices with a structure sodalime glass/Mo/CIGS/CdS were immersed in deionized water. The thin films were then analyzed both pre and post water soaking. Dynamic secondary ion mass spectroscopy (SIMS) was performed on completed devices to analyze impurity diffusion …
High Voltage Design And Evaluation Of Wien Filters For The Cebaf 200 Kev Injector Upgrade, Gabriel Palacios-Serrano, Helmut Baumgart, C. Hernández-García, P. Adderley, J. Benesch, D. Bullard, J. Grames, A. Hofler, D. Machie, M. Poelker, M. Stutzman, R. Suleiman
High Voltage Design And Evaluation Of Wien Filters For The Cebaf 200 Kev Injector Upgrade, Gabriel Palacios-Serrano, Helmut Baumgart, C. Hernández-García, P. Adderley, J. Benesch, D. Bullard, J. Grames, A. Hofler, D. Machie, M. Poelker, M. Stutzman, R. Suleiman
Electrical & Computer Engineering Faculty Publications
High-energy nuclear physics experiments at the Jefferson Lab Continuous Electron Beam Accelerator Facility (CEBAF) require highly spin-polarization electron beams, produced from strained super-lattice GaAs photocathodes, activated to negative electron affinity in a photogun operating at 130 kV dc. A pair of Wien filter spin rotators in the injector defines the orientation of the electron beam polarization at the end station target. An upgrade of the CEBAF injector to better support the upcoming MOLLER experiment requires increasing the electron beam energy to 200 keV, to reduce unwanted helicity correlated intensity and position systematics and provide precise control of the polarization orientation. …
Three-Event Energy Detection With Adaptive Threshold For Spectrum Sensing In Cognitive Radio Systems, Alexandru Martian, Mahmood Jalal Ahmad Al Sammarraie, Calin Vladeanu, Dimitrie Popescu
Three-Event Energy Detection With Adaptive Threshold For Spectrum Sensing In Cognitive Radio Systems, Alexandru Martian, Mahmood Jalal Ahmad Al Sammarraie, Calin Vladeanu, Dimitrie Popescu
Electrical & Computer Engineering Faculty Publications
Implementation of dynamic spectrum access (DSA) in cognitive radio (CR) systems requires the unlicensed secondary users (SU) to implement spectrum sensing to monitor the activity of the licensed primary users (PU). Energy detection (ED) is one of the most widely used methods for spectrum sensing in CR systems, and in this paper we present a novel ED algorithm with an adaptive sensing threshold. The three-event ED (3EED) algorithm for spectrum sensing is considered for which an accurate approximation of the optimal decision threshold that minimizes the decision error probability (DEP) is found using Newton’s method with forced convergence in one …
Work-In-Progress: Augmented Reality System For Vehicle Health Diagnostics And Maintenance, Yuzhong Shen, Anthony W. Dean, Rafael Landaeta
Work-In-Progress: Augmented Reality System For Vehicle Health Diagnostics And Maintenance, Yuzhong Shen, Anthony W. Dean, Rafael Landaeta
Electrical & Computer Engineering Faculty Publications
This paper discusses undergraduate research to develop an augmented reality (AR) system for diagnostics and maintenance of the Joint Light Tactical Vehicle (JLTV) employed by U.S. Army and U.S. Marine Corps. The JLTV’s diagnostic information will be accessed by attaching a Bluetooth adaptor (Ford Reference Vehicle Interface) to JLTV’s On-board diagnostics (OBD) system. The proposed AR system will be developed for mobile devices (Android and iOS tablets and phones) and it communicates with the JLTV’s OBD via Bluetooth. The AR application will contain a simplistic user interface that reads diagnostic data from the JLTV, shows vehicle sensors, and allows users …