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Digital Holography and Three-Dimensional Imaging, DH 2021 - Part of OSA Imaging and Applied Optics Congress 2021

作者： Lahiri, Anish Klasky, Marc L. Fessler, Jeffrey A. Ravishankar, Saiprasad Dept. of Electrical and Computer Engineering University of Michigan Ann ArborMI48109 United States Los Alamos National Laboratory Los AlamosNM87545 United States Depts. of Computational Math Science and Engineering and Biomedical Engineering Michigan State University East LansingMI48824 United States

We present a novel multi-stage algorithm for CBCT reconstruction from very limited projections. Our proposed method uses 3D patch-based supervised and adversarial learning from scarce training data, combined with phys... 详细信息

ISBN: (纸本)9781557528209

关键词： Image reconstruction

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Nanocrystalline Si Films and Devices Produced Using Chemical Annealing with Helium

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MRS Online Proceedings Library 2020年第1期862卷 2061-2066页

作者： Nanlin Wang Vikram L. Dalal Dept. of Electrical and Computer Engineering and Microelectronics Research Center Iowa State University Ames USA

We report on growth of nanocrystalline Si:H films and devices using a layer-by-layer growth technique, where the growth of a thin amorphous layer by PECVD is followed by chemical annealing in a Helium plasma. The films and devices were grown using a remote, low pressure ECR plasma process. It was found that the structure of the films grown using the layer-by-layer technique depended critically upon whether the annealing was done with hydrogen or helium, and the time taken to do the annealing. When the annealing was done in a hydrogen plasma, the films remained amorphous; in contrast, when the annealing was done in helium, and the annealing time was increased to 20 seconds from 10 seconds, the films became crystalline. The crystallinity of the films was confirmed using Raman spectroscopy and x-ray diffraction. The result obtained here shows that it is not necessary to have a high hydrogen dilution to obtain nanocrystalline films. Rather, the amount of hydrogen already present in an amorphous film is enough to cause crystallization, provided that enough ion flux and perhaps energy are available for converting the amorphous structure to a crystalline structure. Proof - of - concept p+nn+ junction devices were fabricated in these chemically annealed materials, and they showed classical nanocrystalline Si solar cell type behavior.

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Anti-Disturbance Full-Order Sliding Mode Control of PMSG-Based Wind Energy Conversion Systems 12

Anti-Disturbance Full-Order Sliding Mode Control of PMSG-Bas...

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12th Annual IEEE Energy Conversion Congress and Exposition, ECCE 2020

作者： Wei, Chun Xu, Jianxing Chen, Qiang Qiao, Wei Zeng, Jianwu Zhejiang University of Technology College of Information Engineering Hangzhou Zhejiang China University of Nebraska-Lincoln Power and Energy System Laboratory Dept. of Electrical and Computer Engineering LincolnNE United States Minnesota State University-Mankato Dept. of Electrical and Computer Engineering Technology MankatoMN United States

ISBN: (纸本)9781728158266

Considering the uncertainty and multi-disturbance in wind energy conversion system (WECS) and the randomness and instability of the wind power, a full-order sliding mode control (FOSMC) strategy based on an extended state observer (ESO) is proposed for the permanent magnet synchronous generator (PMSG)-based WECSs. First, based on the active disturbance rejection control (ADRC) theory, an ESO is developed to estimate the unknown states, uncertainties in the internal machine parameters and external torque disturbance. Second, a full-order sliding mode controller is designed to ensure the convergence of all system states with much reduced chattering phenomenon. Finally, the effectiveness of the proposed ESO-based FOSMC is confirmed by simulation results. The proposed FOSMC strategy will improve the efficiency and the reliability of the WECS. © 2020 IEEE.

关键词： Sliding mode control

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Echocardiogram Vector Embeddings Via R3D Transformer for the Improvement of Ejection Fraction Estimation Instruments

Echocardiogram Vector Embeddings Via R3D Transformer for the...

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IEEE Instrumentation and Measurement Technology Conference

作者： Somin Mindy Lee Daniel Chung Vasu Kaker Yongyi Zhao Irbaz Riaz Sudheesha Perera Prabhu Sasankan George Tang Po-Chih Kuo Jacques Kpodonu Brigitte Kazzi Leo Anthony Celi Dept. of Electrical & Computer Engineering University of Toronto Toronto Canada Sloan School of Management Massachusetts Institute of Technology Cambridge United States Dept. of Electrical Eng. & Comp. Sci. Massachusetts Institute of Technology Cambridge United States Dept. of Medicine Mayo Clinic Scottsdale United States Warren Alpert Medical School Brown University Providence United States Internal Medicine Beth Israel Deaconess Medical Center Boston United States College of Medicine University of California Irvine Irvine United States Dept. of Computer Science National Tsing Hua University Hsinchu City Taiwan Division of Cardiac Surgery Beth Israel Deaconess Medical Center Boston United States Dept. of Medicine Brigham and Women's Hospital Boston United States Laboratory for Computational Physiology Massachusetts Institute of Technology Cambridge United States

ISBN: (数字)9798350380903

ISBN: (纸本)9798350380910

The estimation of ejection fraction (EF) is critical to intensive care. Doctors commonly use estimated EF to create plans for ICU patients, and a low EF can indicate ventricular systolic dysfunction, which increases the risk of adverse events including heart failure. Recently, interest has grown in deep learning (DL) instruments that can measure cardiac activity to estimate EF automatically. In particular, the vector embeddings learned by DL-based EF estimation models provide valuable mappings of echocardiograms within latent space, which can be utilized to understand the error patterns of DL-based EF estimators and thus improve these instruments. In this work, we provide those embeddings. To this end we repurpose an R3D transformer, a state-of-the-art deep learning model for Video Action Recognition, to classify whether patients have ventricular dysfunction or not (ejection fraction below or above 50%) using echocardiogram data. Our R3D model achieves a test AUC of 0.916 and a test accuracy of 87.5%, approaching the performance of previous comparable studies with a fraction of the training time. Most importantly, the vector embeddings learned by this model will enable future analysis of the errors of DL-based EF estimators, democratizing the improvement of these instruments. The quality of these embeddings, furthermore, is evidenced by the strong results of the model that learned them.

关键词： Heart Deep learning Ultrasonic imaging Accuracy Ultrasonic variables measurement Instruments Estimation

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At-Risk People’s Safety in Fire Incidents: Insights Learned from Applying Reliability Index Method

At-Risk People’s Safety in Fire Incidents: Insights Learned...

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International Conference on System Reliability and Science (ICSRS)

作者： Naser Kazemi Eilaki Trond Nordvik Ilona Heldal Carolyn Ahmer Bjarne Christian Hagen Dept. of Civil Engineering Western Norway University of Applied Science Bergen Norway Dept. of Computer Science Electrical Technology and Natural Sciences Western Norway University of Applied Science Bergen Norway Dept. of Safety Chemistry and Biomedical Laboratory Sciences Western Norway University of Applied Science Haugesund Norway

Escaping from a fire to a safe place can take longer and be more difficult for people belonging to at-risk groups. While there are several models addressing uncertainty during evacuation, the effect of these on the elderly and people with disabilities, especially those people who are living alone is seldom exemplified. Considering a common type of detached two-story building with a prevalent layout, this paper illustrates how safety analysis can be developed for these groups based on the fire safety index method. The computations illustrate the probability of being trapped in fire (fatality) and safety index (beta index). The timeline evacuation model for two fire scenarios considers appropriate probability distribution functions for each variable with indeterministic nature. Sensitivity analysis of the variables has been done to find the most important and effective parameters for fire safety for the chosen at-risk groups. The response time to the fire, the area of buildings, and the length of escape route are the most important variables. Also, fire growth is more critical in homes without detection systems. The type of movement disability that needs different kinds of assistive tools, has no great effect on the safety level of people that live in the same home layout and people with visual impairment who need care staff to assist for evacuation encounter the same risk of fatality as other people with movement disabilities approximately.

关键词： Uncertainty Sensitivity analysis Layout Buildings Visual impairment Probability distribution Indexes

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Leveraging team dynamics to predict open-source software projects' susceptibility to social engineering attacks

arXiv

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arXiv 2021年

作者： Giovanini, Luiz Oliveira, Daniela Sanchez, Huascar Shands, Deborah Dept. of Electrical and Computer Engineering University of Florida Gainesville United States Computer Science Laboratory SRI International Menlo Park United States

Open-source software (OSS) is a critical part of the software supply chain. Recent social engineering attacks against OSS development teams have enabled attackers to become code contributors and later inject malicious code or vulnerabilities into the project with the goal of compromising dependent software. The attackers have exploited interactions among development team members and the social dynamics of team behavior to enable their attacks. We introduce a security approach that leverages signatures and patterns of team dynamics to predict the susceptibility of a software development team to social engineering attacks that enable access to the OSS project code. The proposed approach is programming language-, platform-, and vulnerability-agnostic because it assesses the artifacts of OSS team interactions, rather than OSS code. Copyright © 2021, The Authors. All rights reserved.

关键词： Open source software

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Multiple UAS/Multiple Sensors for Intelligence, Surveillance, and Reconnaisance 6

Multiple UAS/Multiple Sensors for Intelligence, Surveillance...

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6th Annual IEEE Research and Applications of Photonics in Defense Conference, RAPID 2023

作者： Jacobs, Eddie L. Furxhi, Orges Renshaw, Kyle Driggers, Ronald Conroy, Joseph University of Memphis Dept. Electrical and Computer Engineering 206 Engr. Science Bldg. MemphisTN38152 United States College of Optics and Photonics University of Central Florida CREOL 4304 Scorpius St. OrlandoFL32816 United States Wyant College of Optical Sciences University of Arizona 1630 E University Blvd TucsonAZ85721 United States FCDD-RLA-PB DEVCOM - Army Research Laboratory 2800 Powder Mill Rd AdelphiMD20783-1138 United States

A system of drones and sensors is designed to obtain situational awareness over large areas for agricultural, environmental assessment, security, and military applications. Sensor roles are divided into wide area cove... 详细信息

ISBN: (纸本)9781665423526

关键词： Military applications

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Data Tables and Best Practices for Post-2000 Nonlinear-Optical Materials and Measurements

Data Tables and Best Practices for Post-2000 Nonlinear-Optic...

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2023 Optica Nonlinear Optics Topical Meeting, NLO 2023

作者： Vermeulen, Nathalie Espinosa, Daniel Ball, Adam Ballato, John Boucaud, Philippe Boudebs, Georges Campos, Cecília L.A.V. Dragic, Peter Gomes, Anderson S.L. Huttunen, Mikko J. Kinsey, Nathaniel Mildren, Rich Neshev, Dragomir Padilha, Lázaro Pu, Minhao Secondo, Ray Tokunaga, Eiji Turchinovich, Dmitry Yan, Jingshi Yvind, Kresten Dolgaleva, Ksenia Van Stryland, Eric W. IR-TONA Vrije Universiteit Brussel Pleinlaan 2 Brussel1050 Belgium School of Electrical Engineering and Computer Science University of Ottawa OttawaONK1N 6N5 Canada Dept. Of Electrical & Computer Engineering Virginia Commonwealth University RichmondVA23284 United States Dept of Materials Science and Engineering Clemson University ClemsonSC29634 United States Université Côte d’Azur CNRS CRHEA Rue Bernard Grégory Sophia-Antipolis06905 France Univ Angers LPHIA SFR MATRIX AngersF-49000 France Departamento de Física Universidade Federal de Pernambuco Recife-PE50670-901 Brazil Dept. Of Electrical & Computer Engineering University of Illinois at Urbana-Champaign UrbanaIL61801 United States Tampere University Photonics Laboratory Physics Unit TampereFI-33014 Finland MQ Photonics Research Centre Macquarie University NSW2109 Australia Department of Electronic Materials Engineering Research School of Physics Australian National University CanberraACT2601 Australia Instituto de Fisica "Gleb Wataghin" Universidade Estadual de Campinas Campinas Sao Paulo13083-970 Brazil Department of Electrical and Photonics engineering Technical University of Denmark Kgs. LyngbyDK-2800 Denmark Department of Physics Faculty of Science Tokyo University of Science 1-3 Kagurazaka Shinjuku-ku Tokyo162-8601 Japan Fakultät für Physik Universität Bielefeld Universitätsstr. 25 Bielefeld33615 Germany CREOL The College of Optics and Photonics University of Central Florida OrlandoFL United States

ISBN: (纸本)9781957171234

On the occasion of 60 years of nonlinear-optical research, we present new data tables listing nonlinear-optical properties for different material categories as reported in the literature since 2000, and provide best practices for performing experiments. Optica Nonlinear Optics Topical Meeting 2023 © Optica Publishing Group 2023 © 2023 The Author(s)

关键词： Nonlinear optics

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Real-World Image Super Resolution via Unsupervised Bi-directional Cycle Domain Transfer Learning based Generative Adversarial Network

arXiv

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arXiv 2022年

作者： Wang, Xiang Yang, Yimin Guo, Zhichang Zhou, Zhili Liu, Yu Pang, Qixiang Du, Shan The Dept. of Computer Science Lakehead University Thunder BayON Canada The Dept. of electrical and computer engineering Western University LondonON Canada The School of Mathematics Harbin Institute of Technology Hei Long Jiang China The School of Computer and Software Nanjing University of Information Science and Technology Jiangsu China The School of Microelectronics Tianjin University Tianjin China The Okanagan College KelownaBC Canada The Dept. of Comp. Sci. Math Physics & Statistics The University of British Columbia OkanaganBC Canada

Deep Convolutional Neural Networks (DCNNs) have exhibited impressive performance on image super-resolution tasks. However, these deep learning-based super-resolution methods perform poorly in real-world super-resolution tasks, where the paired high-resolution and low-resolution images are unavailable and the low-resolution images are degraded by complicated and unknown kernels. To break these limitations, we propose the Unsupervised Bi-directional Cycle Domain Transfer Learning-based Generative Adversarial Network (UBCDTL-GAN), which consists of an Unsupervised Bi-directional Cycle Domain Transfer Network (UBCDTN) and the Semantic Encoder guided Super Resolution Network (SESRN). First, the UBCDTN is able to produce an approximated real-like LR image through transferring the LR image from an artificially degraded domain to the real-world LR image domain. Second, the SESRN has the ability to super-resolve the approximated real-like LR image to a photo-realistic HR image. Extensive experiments on unpaired real-world image benchmark datasets demonstrate that the proposed method achieves superior performance compared to state-of-the-art methods. © 2022, CC BY.

关键词： Convolutional neural networks

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A Point-of-care Biosensor with Subwavelength Grating Waveguide-based Micro-ring Resonator for Detection of COVID-19

A Point-of-care Biosensor with Subwavelength Grating Wavegui...

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Conference on Lasers and Electro-Optics (CLEO)

作者： Shupeng Ning Chao Wang Hao-Chen Chang Kyoung Min Yoo James Fan Devan Shoemaker Maxwell Nakos May H Hlaing Yen-Wen Lu Huiping Tian Ray T. Chen Dept. of Electrical and Computer Engineering The University of Texas at Austin Austin Texas USA State Key Laboratory of Information Photonics and Optical Communications Beijing University of Posts and Telecommunications Beijing China Omega Optics Inc. Austin Texas USA Dept. of Biomechatronics Engineering National Taiwan University Taipei Taiwan

We present an on-chip optical biosensor for the detection of COVID-19. The subwavelength grating waveguide-based micro-ring resonator with high sensitivity and low limit of detection integrates with microfludic channe... 详细信息

ISBN: (数字)9781957171050

ISBN: (纸本)9781665466660

关键词： COVID-19 Performance evaluation Biomedical optical imaging Point of care Optical resonators System-on-chip Biosensors

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