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arXiv 2021年

作者： Jarchi, Delaram Andreu-Perez, Javier Kiani, Mehrin Vysata, Oldrich Kuchynka, Jiri Prochazka, Ales Sanei, Saeid Smart Health Technologies Group School of Computer Science and Electronic Engineering University of Essex ColchesterCO4 3SQ United Kingdom Embedded and Intelligent Systems Laboratory School of Computer Science and Electronics University of Essex ColchesterCO4 3SQ United Kingdom Department of Computing and Control Engineering University of Chemistry and Technology in Prague Prague 6166 28 Czech Republic Department of Neurology Faculty of Medicine in Hradec Králové Charles University Hradec Králové500 05 Czech Republic Czech Institute of Informatics Robotics and Cybernetics Czech Technical University in Prague Prague 6160 00 Czech Republic School of Science and Technology Nottingham Trent University NottinghamNG11 8NS United Kingdom

Accurately diagnosing sleep disorders is essential for clinical assessments and treatments. Polysomnography (PSG) has long been used for detection of various sleep disorders. In this research, electrocardiography (ECG) and electromayography (EMG) have been used for recognition of breathing and movement-related sleep disorders. Bio-signal processing has been performed by extracting EMG features exploiting entropy and statistical moments, in addition to developing an iterative pulse peak detection algorithm using synchrosqueezed wavelet transform (SSWT) for reliable extraction of heart rate and breathing-related features from ECG. A deep learning framework has been designed to incorporate EMG and ECG features. The framework has been used to classify four groups: healthy subjects, patients with obstructive sleep apnea (OSA), patients with restless leg syndrome (RLS) and patients with both OSA and RLS. The proposed deep learning framework produced a mean accuracy of 72% and weighted F1 score of 0.57 across subjects for our formulated four-class problem. © 2021, CC BY-NC-ND.

关键词： Wavelet transforms

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[Retracted] An IoT-Enabled Intelligent and Secure Manufacturing Model Using Blockchain in Hybrid Cloud Communication System

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Security and Communication Networks 2023年第1期2023卷

作者： Sudipto Bhattacharyya Senthil Athithan Souvik Pal Bikramjit Sarkar D. Akila Subrata Chowdhury Karthik Chandran Saravanakumar Gurusamy Department of Computer Science and Engineering Global Institute of Management and Technology Krishnagar Indiagimt-india.in Department of Computer Science and Engineering Koneru Lakshmaiah Education Foundation Vaddeswaram Andhra Pradesh Indiakluniversity.in Department of Computer Science and Engineering Sister Nivedita University Kolkata Indiasnuniv.ac.in Sambalpur University Sambalpur Indiasuniv.ac.in Department of Computer Science and Engineering JIS College of Engineering Kalyani Indiajiscollege.ac.in Department of Computer Applications Saveetha College of Liberal Arts and Sciences SIMATS Deemed University Chennai *** Department of Computer Science and Engineering Sreenivasa Institute of Technology and Management Studies Chittoor Andra Pradesh India Department of Robotics and Automation Jyothi Engineering College Thrissur Kerala Indiajecc.ac.in Department of Electrical and Electronics Technology Federal TVET Institute Addis Ababa Ethiopiaftveti.edu.et

The smart manufacturing system can become a linked network with the help of the Internet of Things (IoT). Devices connected to the IoT are susceptible to various attacks and assaults. An effective protection plan is needed to ensure that the billions of IoT nodes are protected from these hazards. The security mechanisms on IoT devices are ineffective due to resource limitations. As a result, the academic community has recently paid attention to the cloud-, fog-, and edge-based IoT systems. A robust cloud provider is in the cloud or fog to perform computationally demanding activities, including safety, data analysis, decision-making process, and monitoring. Hash identities and upgraded Rivest–Shamir–Adleman (RSA) have been used to secure the IoT device’s data. A four-prime integer of 512 bits makes up the proposed security algorithm. A hash signature is used to provide device authentication. An effective clustering method for sensing devices based on the node level, separation from the clusters, remaining energy, and fitness has been presented for long network life. The suggested swarm-based method determines the sensor nodes’ fitness. A deep neural network- (DNN-) based resource scheduling algorithm (DNN-RSM) is meant to reduce the delay and communications overhead for IoT components in the hybrid cloud system. For optimum resource allocation, all queries originating from the cluster head are categorised using DNN based on their storage, processing, and bandwidth needs. The suggested structure delivers better outcomes, particularly regarding energy use, delay, and safety level. The results of the simulation provide credence to the concept that the proposed strategy is superior to the current system. The suggested scheme includes stringent security, decreased energy usage, decreased latency, and efficient resource utilization.

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Home automation monitoring system based on Internet-of-Things application

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Journal of Physics: Conference Series 2020年第1期1502卷

作者： N. A. Ali A.R. Syafeeza A. S. Ja'afar Norihan Abdul Hamid Ts Saleha binti Mohamad Saleh Machine Learning and Signal Processing (MLSP) Research Group Centre for Telecommunication Research & Innovation (CeTRI) Faculty of Electronics and Computer Engineering (FKEKK) Universiti Teknikal Malaysia Melaka (UTeM) Melaka. Rehabilitation Engineering and Assistive (REAT) Research Group Centre for Robotics & Industrial Automation (CeRIA) Faculty of Electrical and Electronic Engineering Technology (FTKEE) Universiti Teknikal Malaysia Melaka (UTeM) Melaka.

The design of a smart green environment of home automation for appliances monitoring systems is developed based on an IoT(Internet of Things) application. The smart home concept represents a motivating platform for innovation of information technology services to produce more operative house devices and system that can improve the standard of life. This project aims at controlling home appliances via Smartphone using Wi-Fi as a communication protocol and the Raspberry Pi as a server system. The user here can move directly with the system through a web-based interface over the net. The designed system not solely monitors the sensor data but also actuates a process according to the need. Therefore, globally accessible automation of electronic appliances is created attainable with the utilization of a Raspberry Pi micro-controller board, a web affiliation and relay switches in a user-friendly way for the users to regulate home electronic appliances with high flexibility and security.

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Wearable Flexible Hybrid electronics: Advanced Soft Materials, Sensor Integrations, and Applications of Wearable Flexible Hybrid electronics in Healthcare, Energy, and Environment (Adv. Mater. 15/2020)

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Advanced Materials 2020年第15期32卷

作者： Hyo‐Ryoung Lim Hee Seok Kim Raza Qazi Young‐Tae Kwon Jae‐Woong Jeong Woon‐Hong Yeo George W. Woodruff School of Mechanical Engineering Institute for Electronics and Nanotechnology Georgia Institute of Technology Atlanta GA 30332 USA Department of Mechanical Engineering University of South Alabama Mobile AL 36608 USA Department of Electrical Computer & Energy Engineering University of Colorado Boulder Boulder CO 80309 USA School of Electrical Engineering Korea Advanced Institute of Science and Technology Daejeon 34141 South Korea George W. Woodruff School of Mechanical Engineering Wallace H. Coulter Department of Biomedical Engineering Institute for Electronics and Nanotechnology Parker H. Petit Institute for Bioengineering and Biosciences Center for Flexible and Wearable Electronics Advanced Research Neural Engineering Center Institute for Materials Institute for Robotics and Intelligent Machines Georgia Institute of Technology Atlanta GA 30332 USA

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Placental Vessel Segmentation and Registration in Fetoscopy: Literature Review and MICCAI FetReg2021 Challenge Findings

arXiv

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arXiv 2022年

作者： Bano, Sophia Casella, Alessandro Vasconcelos, Francisco Qayyum, Abdul Benzinou, Abdesslam Mazher, Moona Meriaudeau, Fabrice Lena, Chiara Cintorrino, Ilaria Anita De Paolis, Gaia Romana Biagioli, Jessica Grechishnikova, Daria Jiao, Jing Bai, Bizhe Qiao, Yanyan Bhattarai, Binod Gaire, Rebati Raman Subedi, Ronast Vazquez, Eduard Plotka, Szymon Lisowska, Aneta Sitek, Arkadiusz Attilakos, George Wimalasundera, Ruwan David, Anna L. Paladini, Dario Deprest, Jan De Momi, Elena Mattos, Leonardo S. Moccia, Sara Stoyanov, Danail Department of Computer Science University College London United Kingdom Department of Advanced Robotics Istituto Italiano di Tecnologia Italy Department of Electronics Information and Bioengineering Politecnico di Milano Italy The BioRobotics Institute Department of Excellence in Robotics and AI Scuola Superiore Sant'Anna Italy Fetal Medicine Unit Elizabeth Garrett Anderson Wing University College London Hospital United Kingdom EGA Institute for Women's Health Faculty of Population Health Sciences University College London United Kingdom Department of Development and Regeneration University Hospital Leuven Belgium Department of Fetal and Perinatal Medicine Istituto Giannina Gaslini Italy ENIB UMR CNRS 6285 LabSTICC 29238 France Department of Computer Engineering and Mathematics University Rovira i Virgili Spain ImViA Laboratory University of Bourgogne Franche-Comté France Physics Department Lomonosov Moscow State University Russia Fudan University China Medical Computer Vision and Robotics Group Department of Mathematical and Computational Sciences University of Toronto Canada Co. Ltd China NepAL Applied Mathematics and Informatics Institute for Research Nepal Redev Technology United Kingdom Sano Center for Computational Medicine Poland Quantitative Healthcare Analysis Group Informatics Institute University of Amsterdam Amsterdam Netherlands Center for Advanced Medical Computing and Simulation Massachusetts General Hospital Harvard Medical School BostonMA United States

Fetoscopy laser photocoagulation is a widely adopted procedure for treating Twin-to-Twin Transfusion Syndrome (TTTS). The procedure involves photocoagulation pathological anastomoses to restore a physiological blood exchange among twins. The procedure is particularly challenging, from the surgeon's side, due to the limited field of view, poor manoeuvrability of the fetoscope, poor visibility due to amniotic fluid turbidity, and variability in illumination. These challenges may lead to increased surgery time and incomplete ablation of pathological anastomoses, resulting in persistent TTTS. computer-assisted intervention (CAI) can provide TTTS surgeons with decision support and context awareness by identifying key structures in the scene and expanding the fetoscopic field of view through video mosaicking. Research in this domain has been hampered by the lack of high-quality data to design, develop and test CAI algorithms. Through the Fetoscopic Placental Vessel Segmentation and Registration (FetReg2021) challenge, which was organized as part of the MICCAI2021 Endoscopic Vision (EndoVis) challenge, we released the first large-scale multi-center TTTS dataset for the development of generalized and robust semantic segmentation and video mosaicking algorithms with a focus on creating drift-free mosaics from long duration fetoscopy videos. For this challenge, we released a dataset of 2060 images, pixel-annotated for vessels, tool, fetus and background classes, from 18 in-vivo TTTS fetoscopy procedures and 18 short video clips of an average length of 411 frames for developing placental scene segmentation and frame registration for mosaicking techniques. Seven teams participated in this challenge and their model performance was assessed on an unseen test dataset of 658 pixel-annotated images from 6 fetoscopic procedures and 6 short clips. The challenge provided an opportunity for creating generalized solutions for fetoscopic scene understanding and mosaicking. In this paper,

关键词： Pixels

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Steady‐state security evaluation of electrical power systems by means of artificial neural network

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European Transactions on Electrical Power 1995年第2期5卷 91-97页

作者： Chiodo, E. Menniti, D. Testa, A. Picardi, C. Elio Chiodo (1959) received the degree in Electronics Engineering in 1985 and the Ph.D. degree in Computational Statistics both from the University of Naplefltaly. He is a Researcher at the Department of Electrical Engineering of the University of Naples and a member of the Italian Statistical Society. His areas of interest include probabilistic methods applied to electric power systems analysis. (University of Naples Fedrrico 11. Electrical Engineering Dept.via Claudio 21 1-80125 Naplefltaly T +3981/7683226 Fax+3981/2396897) Daniele Menniti (1958) received the degree in Electrical Engineering from the University of Calabria. Cosenzataly and the Ph.D. degree in Electrical Engineering from the University of NapleslItaly in 1984 and 1989 respectively. He is a researcher at the Electronic. Computer and Systems Science Department of the University of Calabria. Italy. Hiscurrent research interests concern electric power system analysis real-time control and automation. (University of Calabria Electronic Computer and Systems Science Dep. Arcavacataji Rende (CS). 1-87036 CosenzdItaly T +39984/494707. Fax +39984/4947 13) Alfredo Testa (1950) received the degree in Electrical Engineering from the University of Naples/Italy in 1975. He is an Associate Professor in Electrical Power Systems at the Department of Electrical Engineering of the University of Naples. He is engaged in researches on electrical power systems reliability and harmonic analysis. (University of Naples Federico 11. Electrical Engineering Dep. via Claudio '2 1 1-80 I25 NapleslItaly T + 39 8 I/7 68 3'2 11. Fax+3981/2396897) Ciro Picardi (1949) received the degree in Electronics Engineering from the University of Naples/Italy in 1975. He is currently Associate Professor in Process Control at the Department of Electronic Computer and System Science of the University of Calabria. Italy. His current research interests are in the area of electrical drives robotics neural networks and fuzzy control. (University of Calabria Electronic. Compu

An artificial‐neural‐network (ANN) application for steady‐state security evaluation of electrical power systems is presented. Such application is based upon a combined use of a multilayer back‐propagation neural network and of an opportune electrical system model, previously proposed by some of the authors. In the paper, the definition of steady‐state security and the problems arising from its on‐line evaluation are briefly recalled. Then, the ANN utilized is described with particular reference to the solutions adopted by the authors. Afterwards, some remarks on the system model utilized are reported. Finally, numerical applications on the AEP‐14 bus system are presented and the results obtained with different ANN configurations are analyzed. Copyright © 1995 John Wiley & Sons, Ltd.

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Electronic Stuctures: Mechanically Guided Post‐Assembly of 3D Electronic Systems (Adv. Funct. Mater. 48/2018)

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Advanced Functional Materials 2018年第48期28卷

作者： Bong Hoon Kim Fei Liu Yongjoon Yu Hokyung Jang Zhaoqian Xie Kan Li Jungyup Lee Ji Yoon Jeong Arin Ryu Yechan Lee Do Hoon Kim Xueju Wang KunHyuck Lee Jong Yoon Lee Sang Min Won Nuri Oh Jeonghyun Kim Ju Young Kim Seong‐Jun Jeong Kyung‐In Jang Seungmin Lee Yonggang Huang Yihui Zhang John A. Rogers Department of Materials Science and Engineering Simpson Querrey Institute and Feinberg Medical School Center for Bio‐Integrated Electronics Northwestern University Evanston IL 60208 USA Center for Mechanics and Materials Center for Flexible Electronics Technology AML Department of Engineering Mechanics Tsinghua University Beijing 100084 China Frederick Seitz Materials Research Laboratory University of Illinois at Urbana‐Champaign Urbana IL 61801 USA Department of Civil and Environmental Engineering Mechanical Engineering and Materials Science and Engineering Northwestern University Evanston IL 60208 USA AML Department of Engineering Mechanics Center for Mechanics and Materials Tsinghua University Beijing 100084 China Division of Materials Science and Engineering Hanyang University Seoul 04763 Republic of Korea Department of Electronics Convergence Engineering Kwangwoon University Seoul 01897 Republic of Korea Multidisciplinary Sensor Research Group Electronics and Telecommunications Research Institute (ETRI) Daejeon 34129 Republic of Korea Department of Organic Materials and Fiber Engineering Department of Information Communication Materials and Chemistry Convergence Technology Soongsil University 369 Sangdo‐ro Dongjak‐gu Seoul 06978 Republic of Korea Department of Robotics Engineering Daegu Gyeongbuk Institute of Science and Technology (DGIST) Daegu 42988 Republic of Korea Department of Energy Electronics Convergence Kookmin University Seoul 02707 Republic of Korea Department of Civil and Environmental Engineering Mechanical Engineering Materials Science and Engineering Northwestern University Evanston IL 60208 USA Department of Materials Science and Engineering Department of Biomedical Engineering Department of Chemistry Department of Neurological Surgery Department of Mechanical Engineering Department of Electrical Engineering and Computer Science Simpson Querrey Institute and Feinberg Medical School Center for Bio‐Integrated Electronics Northwestern University Evanston IL 60208 USA

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Oximetry: Miniaturized Battery‐Free Wireless Systems for Wearable Pulse Oximetry (Adv. Funct. Mater. 1/2017)

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Advanced Functional Materials 2017年第1期27卷

作者： Jeonghyun Kim Philipp Gutruf Antonio M. Chiarelli Seung Yun Heo Kyoungyeon Cho Zhaoqian Xie Anthony Banks Seungyoung Han Kyung‐In Jang Jung Woo Lee Kyu‐Tae Lee Xue Feng Yonggang Huang Monica Fabiani Gabriele Gratton Ungyu Paik John A. Rogers Department of Materials Science and Engineering Frederick Seitz Materials Research Laboratory University of Illinois at Urbana‐Champaign Urbana IL 61801 USA Departments of Materials Science and Engineering Northwestern University Evanston IL 60208 USA Beckman Institute University of Illinois at Urbana‐Champaign Urbana IL 61801 USA Departments of Biomedical Engineering Northwestern University Evanston IL 60208 USA Department of Electrical and Computer Engineering Frederick Seitz Materials Research Laboratory University of Illinois at Urbana‐Champaign Urbana IL 61801 USA Department of Civil and Environmental Engineering Northwestern University Evanston IL 60208 USA AML Department of Engineering Mechanics Center for Mechanics and Materials Tsinghua University Beijing 100084 China Department of Robotics Engineering Daegu Gyeongbuk Institute of Science and Technology (DGIST) Daegu 42988 South Korea Departments of Civil and Environmental Engineering Mechanical Engineering Materials Science and Engineering Center for Engineering and Health Skin Disease Research Center Northwestern University Evanston IL 60208 USA Department of Energy Engineering Hanyang University Seoul 133‐791 Republic of Korea Departments of Materials Science and Engineering Biomedical Engineering Chemistry Neurological Surgery Mechanical Engineering Electrical Engineering and Computer Science Simpson Querrey Institute & Feinberg Medical School Center for Bio‐Integrated Electronics Northwestern University Evanston IL 60208 USA

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Optofluidic Systems: Miniaturized, Battery-Free Optofluidic Systems with Potential for Wireless Pharmacology and Optogenetics (Small 4/2018)

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Small 2018年第4期14卷

作者： Kyung Nim Noh Sung Il Park Raza Qazi Zhanan Zou Aaron D. Mickle Jose G. Grajales-Reyes Kyung-In Jang Robert W. Gereau IV Jianliang Xiao John A. Rogers Jae-Woong Jeong Department of Electrical and Computer Engineering University of Illinois at Urbana-Champaign Urbana IL 61801 USA Department of Electrical and Computer Engineering Texas A&M University College Station TX 77843 USA Center for Remote Health Science Technologies Texas A&M University College Station TX 77843 USA Department of Electrical Computer and Energy Engineering University of Colorado Boulder Boulder CO 80309 USA Department of Mechanical Engineering University of Colorado Boulder Boulder CO 80309 USA Department of Anesthesiology Washington University Pain Center Washington University School of Medicine St. Louis MO 63130 USA Department of Robotics Engineering Daegu Gyeongbuk Institute of Science and Technology (DGIST) Daegu 42988 Republic of Korea Department of Neuroscience Washington University Pain Center Washington University School of Medicine St. Louis MO 63130 USA Department of Materials Science and Engineering Biomedical Engineering Neurological Surgery Chemistry Mechanical Engineering Electrical and Computer Science Northwestern University Evanston IL 60208 USA Center for Bio-Integrated Electronics Simpson Querrey Institute for BioNanotechnology Northwestern University Evanston IL 60208 USA School of Electrical Engineering Korea Advanced Institute of Science and Technology (KAIST) Daejeon 34141 Republic of Korea

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25th Annual Computational Neuroscience Meeting CNS-2016, Seogwipo City, South Korea, July 2-7, 2016 Abstracts

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BMC NEUROSCIENCE 2016年第1期17卷 1-112页

作者： [Anonymous] Computational Neurobiology Laboratory The Salk Institute for Biological Studies San Diego USA UNIC CNRS Gif sur Yvette France The European Institute for Theoretical Neuroscience (EITN) Paris France ATR Computational Neuroscience Laboratories Kyoto Japan Krembil Research Institute University Health Network Toronto Canada Department of Physiology University of Toronto Toronto Canada Department of Medicine (Neurology) University of Toronto Toronto Canada Department of Physics University of New Hampshire Durham USA Department of Neurophysiology Nencki Institute of Experimental Biology Warsaw Poland Department of Theory Wigner Research Centre for Physics of the Hungarian Academy of Sciences Budapest Hungary Department of Mathematical Sciences KAIST Daejoen Republic of Korea Department of Mathematics University of Houston Houston USA Department of Biochemistry & Cell Biology and Institute of Biosciences and Bioengineering Rice University Houston USA Department of Biology and Biochemistry University of Houston Houston USA Grupo de Neurocomputación Biológica Dpto. de Ingeniería Informática Escuela Politécnica Superior Universidad Autónoma de Madrid Madrid Spain Department of Biological Sciences University of Southern California Los Angeles USA Center for Neuroscience Korea Institute of Science and Technology Seoul South Korea Department of Neurology Albert Einstein College of Medicine Bronx USA Center for Neuroscience KIST Seoul South Korea Department of Neuroscience University of Science and Technology Daejon South Korea Systems Neuroscience Group QIMR Berghofer Medical Research Institute Herston Australia Department of Psychology Yonsei University Seoul South Korea Department of Psychiatry Kyung Hee University Hospital at Gangdong Seoul South Korea Department of Psychiatry Veterans Administration Boston Healthcare System and Harvard Medical School Brockton USA Department of Electrical and Electronic Engineering The University of Melbourne Parkvil

A1 Functional advantages of cell-type heterogeneity in neural circuits Tatyana O. Sharpee A2 Mesoscopic modeling of propagating waves in visual cortex Alain Destexhe A3 Dynamics and biomarkers of mental disorders Mitsuo Kawato F1 Precise recruitment of spiking output at theta frequencies requires dendritic h-channels in multi-compartment models of oriens-lacunosum/moleculare hippocampal interneurons Vladislav Sekulić, Frances K. Skinner F2 Kernel methods in reconstruction of current sources from extracellular potentials for single cells and the whole brains Daniel K. Wójcik, Chaitanya Chintaluri, Dorottya Cserpán, Zoltán Somogyvári F3 The synchronized periods depend on intracellular transcriptional repression mechanisms in circadian clocks. Jae Kyoung Kim, Zachary P. Kilpatrick, Matthew R. Bennett, Kresimir Josić O1 Assessing irregularity and coordination of spiking-bursting rhythms in central pattern generators Irene Elices, David Arroyo, Rafael Levi, Francisco B. Rodriguez, Pablo Varona O2 Regulation of top-down processing by cortically-projecting parvalbumin positive neurons in basal forebrain Eunjin Hwang, Bowon Kim, Hio-Been Han, Tae Kim, James T. McKenna, Ritchie E. Brown, Robert W. McCarley, Jee Hyun Choi O3 Modeling auditory stream segregation, build-up and bistability James Rankin, Pamela Osborn Popp, John Rinzel O4 Strong competition between tonotopic neural ensembles explains pitch-related dynamics of auditory cortex evoked fields Alejandro Tabas, André Rupp, Emili Balaguer-Ballester O5 A simple model of retinal response to multi-electrode stimulation Matias I. Maturana, David B. Grayden, Shaun L. Cloherty, Tatiana Kameneva, Michael R. Ibbotson, Hamish Meffin O6 Noise correlations in V4 area correlate with behavioral performance in visual discrimination task Veronika Koren, Timm Lochmann, Valentin Dragoi, Klaus Obermayer O7 Input-location dependent gain modulation in cerebellar nucleus neurons Maria Psarrou, Maria Schilstra, Neil Davey, Benjamin Torben-Ni

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