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Old Dominion University

Electrical & Computer Engineering Faculty Publications

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Articles 31 - 60 of 289

Full-Text Articles in Physical Sciences and Mathematics

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 Jan 2022

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 …

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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 Jan 2022

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 …

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Using Skeleton Correction To Improve Flash Lidar-Based Gait Recognition, Nasrin Sadeghzadehyazdi, Tamal Batabyal, Alexander Glandon, Nibir Dhar, Babajide Familoni, Khan Iftekharuddin, Scott T. Acton Jan 2022

Using Skeleton Correction To Improve Flash Lidar-Based Gait Recognition, Nasrin Sadeghzadehyazdi, Tamal Batabyal, Alexander Glandon, Nibir Dhar, Babajide Familoni, Khan Iftekharuddin, Scott T. Acton

Electrical & Computer Engineering Faculty Publications

This paper presents GlidarPoly, an efficacious pipeline of 3D gait recognition for flash lidar data based on pose estimation and robust correction of erroneous and missing joint measurements. A flash lidar can provide new opportunities for gait recognition through a fast acquisition of depth and intensity data over an extended range of distance. However, the flash lidar data are plagued by artifacts, outliers, noise, and sometimes missing measurements, which negatively affects the performance of existing analytics solutions. We present a filtering mechanism that corrects noisy and missing skeleton joint measurements to improve gait recognition. Furthermore, robust statistics are integrated with …

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"Mystify": A Proactive Moving-Target Defense For A Resilient Sdn Controller In Software Defined Cps, Mohamed Azab, Mohamed Samir, Effat Samir Jan 2022

"Mystify": A Proactive Moving-Target Defense For A Resilient Sdn Controller In Software Defined Cps, Mohamed Azab, Mohamed Samir, Effat Samir

Electrical & Computer Engineering Faculty Publications

The recent devastating mission Cyber–Physical System (CPS) attacks, failures, and the desperate need to scale and to dynamically adapt to changes, revolutionized traditional CPS to what we name as Software Defined CPS (SD-CPS). SD-CPS embraces the concept of Software Defined (SD) everything where CPS infrastructure is more elastic, dynamically adaptable and online-programmable. However, in SD-CPS, the threat became more immanent, as the long-been physically-protected assets are now programmatically accessible to cyber attackers. In SD-CPSs, a network failure hinders the entire functionality of the system. In this paper, we present MystifY, a spatiotemporal runtime diversification for Moving-Target Defense (MTD) to secure …

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A Channel State Information Based Virtual Mac Spoofing Detector, Peng Jiang, Hongyi Wu, Chunsheng Xin Jan 2022

A Channel State Information Based Virtual Mac Spoofing Detector, Peng Jiang, Hongyi Wu, Chunsheng Xin

Electrical & Computer Engineering Faculty Publications

Physical layer security has attracted lots of attention with the expansion of wireless devices to the edge networks in recent years. Due to limited authentication mechanisms, MAC spoofing attack, also known as the identity attack, threatens wireless systems. In this paper, we study a new type of MAC spoofing attack, the virtual MAC spoofing attack, in a tight environment with strong spatial similarities, which can create multiple counterfeits entities powered by the virtualization technologies to interrupt regular services. We develop a system to effectively detect such virtual MAC spoofing attacks via the deep learning method as a countermeasure. …

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Broadband Dielectric Spectroscopic Detection Of Ethanol: A Side-By-Side Comparison Of Zno And Hkust-1 Mofs As Sensing Media, Papa K. Amoah, Zeinab Mohammed Hassan, Pengtao Lin, Engelbert Redel, Helmut Baumgart, Yaw S. Obeng Jan 2022

Broadband Dielectric Spectroscopic Detection Of Ethanol: A Side-By-Side Comparison Of Zno And Hkust-1 Mofs As Sensing Media, Papa K. Amoah, Zeinab Mohammed Hassan, Pengtao Lin, Engelbert Redel, Helmut Baumgart, Yaw S. Obeng

Electrical & Computer Engineering Faculty Publications

The most common gas sensors are based on chemically induced changes in electrical resistivity and necessarily involve making imperfect electrical contacts to the sensing materials, which introduce errors into the measurements. We leverage thermal- and chemical-induced changes in microwave propagation characteristics (i.e., S-parameters) to compare ZnO and surface-anchored metal-organic-framework (HKUST-1 MOF) thin films as sensing materials for detecting ethanol vapor, a typical volatile organic compound (VOC), at low temperatures. We show that the microwave propagation technique can detect ethanol at relatively low temperatures (<100 >°C), and afford new mechanistic insights that are inaccessible with the traditional dc-resistance-based measurements. In addition, …

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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 Jan 2022

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.

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Work-In-Progress: Rapid Development Of Advanced Virtual Labs For In-Person And Online Education, Yiyang Li, Yuzhong Shen, Charles Sukenik, Brian Sanders, Pauline Delacruz, Justin Mason Jan 2022

Work-In-Progress: Rapid Development Of Advanced Virtual Labs For In-Person And Online Education, Yiyang Li, Yuzhong Shen, Charles Sukenik, Brian Sanders, Pauline Delacruz, Justin Mason

Electrical & Computer Engineering Faculty Publications

During the closure of K-12 schools and universities thanks to the COVID-19 pandemic, many educators turned to web conferencing tools such as Zoom and WebEx to deliver online lectures. For courses with labs, some teachers provide recorded videos of real labs. Watching recorded lab videos is a passive experience, as the procedures and point of view are fixed, and students do not have any control of the lab and thus miss the opportunity to explore different options, including making mistakes that is important part of the learning process. One approach that holds great potential to enhance laboratory experience for online …

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Broadband Dielectric Spectroscopic Detection Of Aliphatic Alcohol Vapors With Surface-Mounted Hkust-1 Mofs As Sensing Media, Papa K. Amoah, Zeinab Mohammed Hassan, Rhonda R. Franklin, Helmut Baumgart, Engelbert Redel, Yaw S. Obeng Jan 2022

Broadband Dielectric Spectroscopic Detection Of Aliphatic Alcohol Vapors With Surface-Mounted Hkust-1 Mofs As Sensing Media, Papa K. Amoah, Zeinab Mohammed Hassan, Rhonda R. Franklin, Helmut Baumgart, Engelbert Redel, Yaw S. Obeng

Electrical & Computer Engineering Faculty Publications

We leveraged chemical-induced changes to microwave signal propagation characteristics (i.e., S-parameters) to characterize the detection of aliphatic alcohol (methanol, ethanol, and 2-propanol) vapors using TCNQ-doped HKUST-1 metal-organic-framework films as the sensing material, at temperatures under 100 °C. We show that the sensitivity of aliphatic alcohol detection depends on the oxidation potential of the analyte, and the impedance of the detection setup depends on the analyte-loading of the sensing medium. The microwaves-based detection technique can also afford new mechanistic insights into VOC detection, with surface-anchored metal-organic frameworks (SURMOFs), which is inaccessible with the traditional coulometric (i.e., resistance-based) measurements.

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Runtime Power Allocation Based On Multi-Gpu Utilization In Gamess, Masha Sosonkina, Vaibhav Sundriyal, Jorge Luis Galvez Vallejo Jan 2022

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 …

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Efficient Removal Of Lead Ions From Aqueous Media Using Sustainable Sources On Marine Algae, Hannah Namkoong, Erik Biehler, Gon Namkoong, Tarek M. Abdel-Fattah Jan 2022

Efficient Removal Of Lead Ions From Aqueous Media Using Sustainable Sources On Marine Algae, Hannah Namkoong, Erik Biehler, Gon Namkoong, Tarek M. Abdel-Fattah

Electrical & Computer Engineering Faculty Publications

The goal of this project is to explore a new method to efficiently remove Pb(II) ions from water by processing Undaria pinnatifida into immobilized beads using sodium alginate and calcium chloride. The resulting biosorbent was characterized by Fourier transform infrared spectroscopy (FTIR) and scanning electron microscopy coupled with energy-dispersive X-ray spectroscopy (SEM-EDS). Using immobilized U. pinnatifida, we investigated the effect of various factors on Pb(II) ion removal efficiency such as temperature, pH, ionic strength, time, and underlying biosorption mechanisms. For Pb(II) ion biosorption studies, Pb(II) ion biosorption data were obtained and analyzed using Langmuir and Freundlich adsorption models. It …

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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 Jan 2022

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. …

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Arithfusion: An Arithmetic Deep Model For Temporal Remote Sensing Image Fusion, Md Reshad Ul Hoque, Jian Wu, Chiman Kwan, Krzysztof Koperski, Jiang Li Jan 2022

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 …

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Facial Landmark Feature Fusion In Transfer Learning Of Child Facial Expressions, Megan A. Witherow, Manar D. Samad, Norou Diawara, Khan M. Iftekharuddin Jan 2022

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 …

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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 Jan 2022

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. …

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Artificial Intelligence And Machine Learning In Optical Information Processing: Introduction To The Feature Issue, Khan Iftekharuddin, Chrysanthe Preza, Abdul Ahad S. Awwal, Michael E. Zelinski Jan 2022

Artificial Intelligence And Machine Learning In Optical Information Processing: Introduction To The Feature Issue, Khan Iftekharuddin, Chrysanthe Preza, Abdul Ahad S. Awwal, Michael E. Zelinski

Electrical & Computer Engineering Faculty Publications

This special feature issue covers the intersection of topical areas in artificial intelligence (AI)/machine learning (ML) and optics. The papers broadly span the current state-of-the-art advances in areas including image recognition, signal and image processing, machine inspection/vision and automotive as well as areas of traditional optical sensing, interferometry and imaging.

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Nb₃Sn Coating Of A 2.6 Ghz Srf Cavity By Sputter Deposition Technique, M. S. Shakel, Wei Cao, H. Elsayed-Ali, G. V. Eremeev, U. Pudasaini, A. M. Valente-Feliciano Jan 2022

Nb₃Sn Coating Of A 2.6 Ghz Srf Cavity By Sputter Deposition Technique, M. S. Shakel, Wei Cao, H. Elsayed-Ali, G. V. Eremeev, U. Pudasaini, A. M. Valente-Feliciano

Electrical & Computer Engineering Faculty Publications

Nb₃Sn is of interest as a coating for SRF cavities due to its higher transition temperature Tc ~18.3 K and superheating field Hsh ~400 mT, both are twice that of Nb. Nb₃Sn coated cavities can achieve high-quality factors at 4 K and can replace the bulk Nb cavities operated at 2 K. A cylindrical magnetron sputtering system was built, commissioned, and used to deposit Nb₃Sn on the inner surface of a 2.6 GHz single-cell Nb cavity. With two identical cylindrical magnetrons, this system can coat a cavity with high symmetry and uniform thickness. Using Nb-Sn multilayer sequential sputtering followed by …

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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 Jan 2021

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 …

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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 Jan 2021

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 …

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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.) Jan 2021

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.

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Generation Of Excited Species In A Streamer Discharge, Shirshak K. Dhali Jan 2021

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 …

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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 Jan 2021

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. …

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Converting Optical Videos To Infrared Videos Using Attention Gan And Its Impact On Target Detection And Classification Performance, Mohammad Shahab Uddin, Reshad Hoque, Kazi Aminul Islam, Chiman Kwan, David Gribben, Jiang Li Jan 2021

Converting Optical Videos To Infrared Videos Using Attention Gan And Its Impact On Target Detection And Classification Performance, Mohammad Shahab Uddin, Reshad Hoque, Kazi Aminul Islam, Chiman Kwan, David Gribben, Jiang Li

Electrical & Computer Engineering Faculty Publications

To apply powerful deep-learning-based algorithms for object detection and classification in infrared videos, it is necessary to have more training data in order to build high-performance models. However, in many surveillance applications, one can have a lot more optical videos than infrared videos. This lack of IR video datasets can be mitigated if optical-to-infrared video conversion is possible. In this paper, we present a new approach for converting optical videos to infrared videos using deep learning. The basic idea is to focus on target areas using attention generative adversarial network (attention GAN), which will preserve the fidelity of target areas. …

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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 Jan 2021

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 …

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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 Jan 2021

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 …

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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 Jan 2021

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 …

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Formal Power Series Approach To Nonlinear Systems With Static Output Feedback, G.S. Venkatesh, W. Steven Gray Jan 2021

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 …

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Continuity Of Chen-Fliess Series For Applications In System Identification And Machine Learning, Rafael Dahmen, W. Steven Gray, Alexander Schmeding Jan 2021

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 …

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Transient Behavior Of Drift And Ionization In Atmospheric Pressure Nitrogen Discharge, S. K. Dhali Jan 2021

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 …

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The Resistive Barrier Discharge: A Brief Review Of The Device And Its Biomedical Applications, Mounir Laroussi Jan 2021

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 …

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