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12th International Conference on e-Learning and Games, Edutainment 2018

作者： Zhao, Yanni Wang, Yinghui Wang, Ningna Ning, Xiaojuan Shi, Zhenghao Zhao, Minghua Lv, Ke Huang, Liangyi Institute of Computer Science and Engineering Xi’an University of Technology Xi’an China Shaanxi Key Laboratory of Network Computing and Security Technology Xi’an China Department of Computer Science Shannxi Vocational and Technical College Xi’an China Booking B.V. Herengracht 597 Amsterdam1017 CE Netherlands Institute of Automation Chinese Academy of Sciences Beijing China School of Engineering and Applied Science George Washington University Washington D.C. United States

ISBN: (纸本)9783030237110

The repairing of 3D point cloud holes has an important meaning to ensure the integrity of cloud data. We present a slice-based repairing method for 3D point cloud in this paper. Firstly, the model is horizontal sliced and each slice is projected on a two-dimensional plane, then the band-shaped points obtained during projection are clustered to select boundary points of the hole. Combined with optimal fitting points, the hole repairing point sets in the projection layer are re-sampled based on the cubic B-spline curve to fit boundary points. Finally, all hole repairing point sets in the projection layer are combined in 3D space to finish the entire hole recovery. The experimental results show that the proposed method can effectively repair complex holes for various point cloud models. © 2019, Springer Nature Switzerland AG.

关键词： Curve fitting

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Transfer Learning for EEG-Based Brain-Computer Interfaces: A Review of Progress Made Since 2016

arXiv

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arXiv 2020年

作者： Wu, Dongrui Xu, Yifan Lu, Bao-Liang The Ministry of Education Key Laboratory of Image Processing and Intelligent Control School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan430074 China The Center for Brain-Like Computing and Machine Intelligence Department of Computer Science and Engineering Key Laboratory of Shanghai Education Commission for Intelligent Interaction and Cognitive Engineering Brain Science and Technology Research Center Qing Yuan Research Institute Shanghai Jiao Tong University 800 Dong Chuan Road Shanghai200240 China

A brain-computer interface (BCI) enables a user to communicate with a computer directly using brain signals. The most common non-invasive BCI modality, electroencephalogram (EEG), is sensitive to noise/artifact and suffers between-subject/within-subject non-stationarity. Therefore, it is difficult to build a generic pattern recognition model in an EEG-based BCI system that is optimal for different subjects, during different sessions, for different devices and tasks. Usually, a calibration session is needed to collect some training data for a new subject, which is time-consuming and user unfriendly. Transfer learning (TL), which utilizes data or knowledge from similar or relevant subjects/sessions/devices/tasks to facilitate learning for a new subject/session/device/task, is frequently used to reduce the amount of calibration effort. This paper reviews journal publications on TL approaches in EEG-based BCIs in the last few years, i.e., since 2016. Six paradigms and applications - motor imagery, event-related potentials, steady-state visual evoked potentials, affective BCIs, regression problems, and adversarial attacks - are considered. For each paradigm/application, we group the TL approaches into cross-subject/session, cross-device, and cross-task settings and review them separately. Observations and conclusions are made at the end of the paper, which may point to future research directions. Copyright © 2020, The Authors. All rights reserved.

关键词： Brain computer interface

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Towards a FAIR-DICE IAM: Combining DICE and FAIR Models

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IFAC-PapersOnLine 2018年第5期51卷 126-131页

作者： Faulwasser, Timm Nydestedt, Robin Kellett, Christopher M. Weller, Steven R. Institute for Automation and Applied Informatics Karlsruhe Institute of Technology Eggenstein-Leopoldshafen76344 Germany Department of Mathematics Royal Institute of Technology Lindstedtsvägen 25 Stockholm Sweden School of Electrical Engineering and Computing University of Newcastle CallaghanNew South Wales2308 Australia

The estimation of the Social Cost of Carbon Dioxide (SC-CO2) is one of the essential purposes of Integrated Assessment Models (IAMs) used in the economics of climate change. One of the most widely used IAMs in this context is DICE. However, the DICE geophysical subsystem fails to account for feedback from the climate subsystem to the carbon subsystem, an effect recently observed in climate physics. This paper investigates how to combine the recently proposed FAIR climate model with the socioeconomic subsystem of DICE. Based on an analysis of its differential-algebraic structure, we propose an efficient discretization of FAIR that provides a new discrete-time hybrid of DICE and FAIR denoted as FAIR-DICE. Finally, we compare estimates of the SC-CO2 obtained with DICE2013 with those obtained via FAIR-DICE. © 2018

关键词： Climate models Algebra Carbon dioxide Climate change Differential equations Economics DICE Differential algebraic equations FAIR Integrated assessment models Optimal controls

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Set stability for switched Boolean networks with open-loop and closed-loop switching signals

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中国科学（信息科学） 2018年第9期61卷 226-234页

作者： Xiaohua LI Jianquan LU Jianlong QIU Xiangyong CHEN Xiaodi LI Fuad E.ALSAADI School of Automation and Engineering and Key Laboratory of Complex Systems and Intelligent Computing in Universities of Shandong Linyi University Linyi 276005 China School of Mathematics and Statistics Shandong Normal University Jinan 250014 China School of Mathematics Southeast University Nanjing 210096 China School of Automation and Engineering and Key Laboratory of Complex Systems and Intelligent Computing in Universities of Shandong Linyi University Linyi 276005 China School of Automation and Engineering and Key Laboratory of Complex Systems and Intelligent Computing in Universities of Shandong Linyi University Linyi 276005 China School of Mathematics Southeast University Nanjing 210096 China School of Mathematics and Statistics Shandong Normal University Jinan 250014 China Department of Electrical and Computer Engineering King Abdulaziz University Jeddah 21589 Saudi Arabia

This paper mainly analyzes the set stability of switched Boolean networks (SBNs) by considering two different methods of switching signals in the form of open-loop and closed-loop ***,the definitions of set stability are proposed for SBNs with such switching ***,we propose two different algorithms to find the largest open-loop switching invariant set and largest closed-loop switching invariant ***,the corresponding set stability conditions for SBNs are given in each *** addition,the constructive procedures are presented to design the switching signal sequence to achieve set stability under the two different methods of switching ***,the effectiveness of the proposed algorithms and research results are demonstrated using two numerical examples.

关键词： switched Boolean network set stability semi-tensor product switching signal design

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Semantic Segmentation Using Deep Learning to Extract Total Extraocular Muscles and Optic Nerve from Orbital Computed Tomography Images

arXiv

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arXiv 2020年

作者： Zhu, Fubao Gao, Zhengyuan Zhao, Chen Zhu, Zelin Liu, Yanyun Tang, Shaojie Jiang, Chengzhi Li, Xinhui Zhao, Min Zhou, Weihua School of Computer and Communication Engineering Zhengzhou University of Light Industry ZhengzhouHenan China School of Automation Xi'an University of Posts and Telecommunications Xi'anShaanxi China Department of PET-CT Center Hunan Cancer Hospital Changsha China College of Computing Michigan Technological University 1400 Townsend Dr HoughtonMI49931 United States Department of Nuclear Medicine Xiangya Hospital Central South University 87 Xiangya Road Changsha Hunan410008 China

Objectives: Precise segmentation of total extraocular muscles (EOM) and optic nerve (ON) is essential to assess anatomical development and progression of thyroid-associated ophthalmopathy (TAO). We aim to develop a semantic segmentation method based on deep learning to extract the total EOM and ON from orbital CT images in patients with suspected TAO. Materials and Methods: A total of 7,879 images obtained from 97 subjects who underwent orbit CT scans due to suspected TAO were enrolled in this study. Eighty-eight patients were randomly selected into the training/validation dataset, and the rest were put into the test dataset. Contours of the total EOM and ON in all the patients were manually delineated by experienced radiologists as the ground truth. A three-dimensional (3D) end-to-end fully convolutional neural network called semantic V-net (SV-net) was developed for our segmentation task. Intersection over Union (IoU) was measured to evaluate the accuracy of the segmentation results, and Pearson correlation analysis was used to evaluate the volumes measured from our segmentation results against those from the ground truth. Results: Our model in the test dataset achieved an overall IoU of 0.8207;the IoU was 0.7599 for the superior rectus muscle, 0.8183 for the lateral rectus muscle, 0.8481 for the medial rectus muscle, 0.8436 for the inferior rectus muscle and 0.8337 for the optic nerve. The volumes measured from our segmentation results agreed well with those from the ground truth (all R>0.98, P Copyright © 2020, The Authors. All rights reserved.

关键词： Semantic Segmentation

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Analysis of Harmonics Detection and their Filtration by using Active Band Pass Filter for Domestic Appliances

Analysis of Harmonics Detection and their Filtration by usin...

引用

IEEE International Conference on automation Science and engineering (CASE)

作者： Ehtisham Lodhi Zeeshan Lodhi Zhu Fenghua Gang Xiong Feiyue Wang Waheed ur Rehman Tariku Sinshaw The SKL for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China School of Artificial Intelligence University of Chinese Academy of Sciences Beijing China Department of Electrical and Computer Engineering COMSATS University Islamabad Abbottabad Campus Pakistan Guangdong Engineering Research Center of 3D Printing and Intelligent Manufacturing Cloud Computing Center Chinese Academy of Sciences Dongguan Guangdong China Beijing Engineering Research Center of Intellectual System and Technology Chinese Academy of Sciences Beijing China College of Mechanical Engineering and Applied Electronics Technologies Beijing University of Technology Beijing China

ISBN: (数字)9781728169040

ISBN: (纸本)9781728169057

In modern era, one of the rising power quality (PQ) concern is harmonics distortion (HD). The HD is usually produced by increase in the utilization of nonlinear user loads at domestic level. It not only spoils the PQ but also have harmful effects on electrical appliances. So, this paper presents a new approach to mitigate the HD in home appliances rapidly by utilizing the active band pass filter (ABPF). The fast Fourier transform (FFT) technique is employed for the detection of harmonics in appliances. The band pass filter dramatically affects the response time of active filter. The suggested control methodology is capable to eliminate harmonics from distorted input voltage waveform and provides a pure sinusoidal waveform. The prototype of this model is also implemented. Experimental results along with simulation show that the proposed model is quite effective in eliminating HD despite load variations and also useful to compensate the reactive power in electronic home appliances. Hence, this technique is cost effective for domestic users with high quality performance in all aspects.

关键词： Power harmonic filters Harmonic analysis Band-pass filters Harmonic distortion Home appliances

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A threshold effect of coupling delays on intra-layer synchronization in duplex networks

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Science China(Technological Sciences) 2018年第12期61卷 1907-1914页

作者： TANG LongKun LU JunAn Lü JinHu Fujian Province University Key Laboratory of Computation Science School of Mathematical Sciences Huaqiao University Department of Mathematics & Statistics Georgia State University School of Mathematics and Statistics Wuhan University School of Automation Science and Electrical Engineering State Key Laboratory of Software Development Environment and Beijing Advanced Innovation Center for Big Data and Brain Computing Beihang University

This paper investigates the impact of inter-layer coupling functions and intra-layer coupling delays on intra-layer synchronization regions and sychronizability. It is found that the inter-layer coupling functions have great influence on intra-layer synchronization regions, as well as on the intra-layer synchronizability. In particular, there exists an inter-layer coupling function such that the inter-layer coupling strength neither improves nor weakens the intra-layer synchronizability. Furthermore, no matter which one of three inter-layer coupling functions is chosen, a small intra-layer delay always keeps the intra-layer synchronized regions almost unchanged, implying that the small delay neither enhances nor suppresses the intra-layer synchronizability. At the same time the delay greatly frustrates the synchronizability in each layer when it is greater than some threshold. Our results may have potential applications for interconnected technological networks where communication delays are inevitably present.

关键词： multiplex network master stability function intra-layer synchronization synchronized region time delay

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Design and low-cost FPGA implementation of the fuzzy decision system 30

Design and low-cost FPGA implementation of the fuzzy decisio...

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30th International Conference on Microelectronics, ICM 2018

作者： Junior, Egidio Ieno Manuel Garces Socarras, Luis Pimenta, Tales Cleber Department of Mechatronics Centro Federal de Educação Tecnológica Varginha Brazil Department of Automation and Computing Technological University of Havana Havana Cuba Institute of Systems Engineering and Information Technology Universidade Federal de Itajubá Itajuba Brazil

ISBN: (纸本)9781538681671

Methods of moving object detection for General Purpose Processors (GPPs) present an approach that does not allow a successful implementation in the Field Programmable Gate Array (FPGA). This is because correct pixel classification is directly related to the need for many resources in terms of memory or complex mathematical operations to model the reference image. Therefore, these implementations do not allow real-time processing. In addition, these methods implement only conventional techniques of digital imaging processing. Thus, we propose an architecture for FPGA that combines filter operations with fuzzy integral to improve the detection of moving vehicles. This proposed fuzzy decision system for detecting moving vehicles seeks to not compromise the results in terms of pixel classification, even validating the system through a reference image obtained by a simple modeling mechanism. Results are verified in terms of the resources occupied, maximum frequency of operation and similarity measure in the FPGA Spartan-6 LX100. The implementation of the proposed low-cost FPGA system processes high-definition images in real time and improves pixel classification. © 2018 IEEE.

关键词： Object recognition

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Novel Design of a Soft Lightweight Pneumatic Continuum Robot Arm with Decoupled Variable Stiffness and Positioning

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Soft Robotics 2018年第1期5卷 54-70页

作者： Giannaccini, Maria Elena Xiang, Chaoqun Atyabi, Adham Theodoridis, Theo Nefti-Meziani, Samia Davis, Steve Centre for Autonomous Systems and Advanced Robotics School of Computing Science and Engineering University of Salford Stoke Gifford BristolBS16 1QY United Kingdom School of Mechanical Engineering and Automation Institute of Mechatronics Engineering Northeastern University Shenyang China Department of Pediatrics University of Washington SeattleWA United States Seattle Children's Research Institute SeattleWA United States

Soft robot arms possess unique capabilities when it comes to adaptability, flexibility, and dexterity. In addition, soft systems that are pneumatically actuated can claim high power-to-weight ratio. One of the main drawbacks of pneumatically actuated soft arms is that their stiffness cannot be varied independently from their end-effector position in space. The novel robot arm physical design presented in this article successfully decouples its end-effector positioning from its stiffness. An experimental characterization of this ability is coupled with a mathematical analysis. The arm combines the light weight, high payload to weight ratio and robustness of pneumatic actuation with the adaptability and versatility of variable stiffness. Light weight is a vital component of the inherent safety approach to physical human-robot interaction. To characterize the arm, a neural network analysis of the curvature of the arm for different input pressures is performed. The curvature-pressure relationship is also characterized experimentally. © Copyright 2018, Mary Ann Liebert, Inc. 2018.

关键词： Stiffness

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The softness of tumour-cell-derived microparticles regulates their drug-delivery efficiency (vol 3, pg 729, 2019)

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NATURE BIOMEDICAL engineering 2021年第5期5卷 481-481页

作者： Liang, Qingle Bie, Nana Yong, Tuying Tang, Ke Shi, Xiaolong Wei, Zhaohan Jia, Haibo Zhang, Xiaoqiong Zhao, Haiyan Huang, Wei Gan, Lu Huang, Bo Yang, Xiangliang National Engineering Research Center for Nanomedicine College of Life Science and Technology Huazhong University of Science and Technology Wuhan China Hubei Key Laboratory of Bioinorganic Chemistry and Materia Medica Huazhong University of Science and Technology Wuhan China Department of Biochemistry and Molecular Biology Tongji Medical College Huazhong University of Science and Technology Wuhan China Department of Immunology and National Key Laboratory of Medical Molecular Biology Institute of Basic Medical Sciences Chinese Academy of Medical Sciences Peking Union Medical College Beijing China Institute of Computing Science and Technology Guangzhou University Guangzhou China School of Artificial Intelligent and Automation Huazhong University of Science and Technology Wuhan China Key Laboratory of Molecular Biophysics of Ministry of Education College of Life Science and Technology Huazhong University of Science and Technology Wuhan China

A Correction to this paper has been published: https://***/10.1038/s41551-021-00694-0.

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