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Chinese automation Congress (CAC)

作者： Sheng Liu Xisong Dong Gang Xiong Zhen Shen Bin Hu Xiaoyu Chen State Key Laboratory for Management and Control of Complex System Institute of Automation Chinese Academy of Sciences Beijing China Guangdong Engineering Research Center of 3D Printing and Intelligent Manufacturing Cloud Computing Center Chinese Academy of Sciences Dongguan China Beijing Engineering Research Center of Intelligent Systems and Technology Institute of Automation Chinese Academy of Sciences Beijing China Institution of Intelligent Manufacturing Qingdao Academy of Intelligent Industries Qingdao China School of Artificial Intelligence University of Chinese Academy of Sciences Beijing China

ISBN: (纸本)9781665426480

With the development of industrialized building and intelligence technology, it becomes necessary and possible to realize building process intelligence management. In recent years, digital twins and parallel management get more and more attentions in academic research and industrial applications. This paper addresses how parallel building system performs intelligence management on industrialized building process. Firstly, actual building model and artificial building model are created according to actual building system. Then business driving engine and simulation engine drive actual building model and artificial building model, respectively. Participants receive and send messages by software interfaces. Business driving engine changes the status of actual building model and sends the changes to simulation engine. Simulation engine updates the status of artificial building model and runs artificial building model with various parameters. Then it sends the parameter with the best effect to business driving engine. Business driving engine sends recommendations to participants according to the best parameter. Thus, building process intelligence management is achieved.

关键词： automation Digital twin Buildings User interfaces Software Engines Business

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Review on Teacher's Online Practice in Community

Review on Teacher's Online Practice in Community

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2019 IEEE International Conference on Service Operations and Logistics, and Informatics, SOLI 2019

作者： Wang, Xinzhu Gong, Xiaoyan Liu, Xiwei Yan, Yan Zhang, Nan Luo, Jie State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China Faculty of Education Beijing Normal University Beijing China Institute of Smart Education Qingdao Academy of Intelligent Industries Qingdao China Chinese Association of Automation Beijing China State Key Laboratory of Software Development Environment Beihang University Beijing100191 China

ISBN: (纸本)9781728128535

Teacher's Online Practice in Community (TOPIC) is an informal and practical online learning community that improves teachers' professional development. Domestic researches on TOPIC have begun to take shape. By sorting out relevant literature retrieved from China National Knowledge Infrastructure (CNKI), this article summarizes research topics such as knowledge management, teacher professional development, and community management and summarizes qualitative and quantitative research methods commonly used by domestic researches. This article finally puts forward some limitations of current researches in this field and forecasts the possible future research directions. © 2019 IEEE.

关键词： Knowledge management

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Acupoint Detection Based on Deep Convolutional Neural Network

Acupoint Detection Based on Deep Convolutional Neural Networ...

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第三十九届中国控制会议

作者： Lingyao Sun Shiying Sun Yuanbo Fu Xiaoguang Zhao State Key Laboratory of Management and Control for Complex Systems Institute of AutomationChinese Academy of Sciences University of Chinese Academy of Sciences school of Artificial Intelligence The Department of Acupuncture and Moxibustion Beijing Hospital of Traditional Chinese MedicineCapital Medical UniversityBeijing Key Laboratory of Acupuncture Neuromodulation

As an important component of Traditional Chinese Medicine(TCM),science of acupoint therapy has achieved significant results in clinical practice,but recognizing and positioning acupoints is heavily depends on the skills of *** recent years,researchers have proposed a few methods of automatic acupoints detection and positioning,but most of the methods are still based on manual designed *** this paper,we propose an acupoints detection method based on deep convolutional neural network,and an evaluation method is proposed for acupoint ***'s more,we build an acupoint detection *** are performed and a promising result is achieved.

关键词： convolutional neural network deep learning acupoint detection convolutional pose machine

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Hexagonally ordered microbowl arrays decorated with ultrathin CuInS_(2) nanosheets for enhanced photoelectrochemical performance

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Journal of Energy Chemistry 2020年第12期29卷 134-142页

作者： Ming Li Le Chen Yanjie Su Huan Yin Kexiang Hu State Key Laboratory of Transducer Technology Shanghai Institute of Microsystem and Information TechnologyChinese Academy of SciencesShanghai 200050China School of Electronic Engineering and Automation Guilin University of Electronic TechnologyKey Laboratory of Optoelectronic Information Processing of Guangxi Colleges and Uniy/ersitiesGuilin 541004GuangxiChina Key Laboratory for Thin Film and Microfabrication of the Ministry of Education Department of Micro/Nano ElectronicsSchool of ElectronicsInformation and Electrical EngineeringShanghai Jiao Tong UniversityShanghai 200240China National and Local Joint Engineering Laboratory of Internet Technology on Mine School of Information and Control EngineeringChina University of Mining and TechnologyXuzhou 221008JiangsuChina School of Physics and Telecommunication Engineering Guangxi Colleges and Universities Key Lab of Complex System Optimization and Big Data ProcessingYulin Normal UniversityYulin 537400GuangxiChina

This paper demonstrates the design and fabrication of three-dimensional(3 D) hexagonally ordered microbowl arrays(MBAs) decorated with Cu In S2 nanosheets for enhanced photoelectrochemical(PEC) performance. The 3 D MBAs are fabricated by a micro-fabrication technique. The ultrathin CuInS2 nanosheets are grown on the 3 D electrodes by solvothermal transformation of Cu film. The photocurrent density of 3 D photocathode(CuInS2@MBAs) is about two times higher than that of the planar counterpart(CuInS2@Planar). The improved PEC performance can be ascribed to the elevated light trapping ability and the increased surface area for loading photocatalysts. In addition, CdS quantum dots as cocatalysts are modified onto the Cu In S2 nanosheets to further enhance the PEC activity because the formed p-n heterojunction can accelerate the separation of photogenerated carriers. As a result, the 3 D photocathode of CuInS2/CdS@MBAs shows an optimal incident photon to current efficiency of 10% at the wavelength of400 nm. It is believed that this work can be generalized to design other hierarchical 3 D photoelectrodes for improved solar water splitting.

关键词： Microbowl array CuInS_(2) Nanosheet Photocathode Photoelectrochemical performance

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Review on Development of Smart Education

Review on Development of Smart Education

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2019 IEEE International Conference on Service Operations and Logistics, and Informatics, SOLI 2019

作者： Shi, Wanruo Liu, Xiwei Gong, Xiaoyan Niu, Xiaojie Wang, Xinzhu Jing, Sifeng Lu, Hao Zhang, Nan Luo, Jie State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China Faculty of Education Beijing Normal University Beijing China Institute of Smart Education Qingdao Academy of Intelligent Industries Qingdao China Chinese Association of Automation Beijing China State Key Laboratory of Software Development Environment Beihang University Beijing100191 China

ISBN: (纸本)9781728128535

Smart education is leading the development direction of Chinese education informatization and becoming a main theme of education development in the era of which technology changes education. There are seven main branches of smart education, namely Intelligent Tutoring System (ITS), smart campus, Big Data in Education (BDE), knowledge graph, educational robots, virtual teachers, and personalized education. Based on literature survey and market research, this paper gives a comprehensive overview of the research and application of smart education from above seven aspects and proposes its development based on the status of smart education development. © 2019 IEEE.

关键词： Intelligent vehicle highway systems

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Improving Road Detection Results Based on Ensemble Learning and key Samples Focusing

Improving Road Detection Results Based on Ensemble Learning ...

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International Conference on Intelligent Transportation

作者： Siqi Fan Fenghua Zhu Hui Zhang Yisheng Lv Xiao Wang Gang Xiong Fei-Yue Wang State Key Laboratory 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 Clouding Computing Center Chinese Academy of Sciences Dongguan Guangdong China

ISBN: (数字)9781728141497

ISBN: (纸本)9781728141503

Road detection is fundamental for many applications, especially vision-based autonomous driving systems. To improve the accuracy of the detection results, most of previous research focus on designing feature encoders and classifiers. In this paper, a road detection method is proposed based on ensemble learning and key samples focusing. A road detection network is designed, which integrates classification results based on different feature combinations by weighted voting. The outputs of the network are further processed by morphological transformation. To focus on key samples, a novel loss function is proposed. The loss function can attach importance to hard samples and pay different attention to missed detection and false detection. The method is evaluated on KITTI dataset, and its effectiveness is verified.

关键词： Roads Feature extraction Training Decoding Focusing Bagging Image color analysis

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3D Face Reconstruction System From A Single Photo Based On Regression Neural Network

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IFAC-PapersOnLine 2020年第5期53卷 71-76页

作者： Yatai Ji Keqiang Li Huaiyu Wu Gang Xiong Zhen Shen Xiuqin Shang Bangwen Xi The State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences Beijing 100190 China Department of Automation Tsinghua University Beijing 100084 China University of Chinese Academy of Sciences Beijing 100049 China The Guangdong Engineering Research Center of 3D Printing and Intelligent Manufacturing Cloud Computing Center Chinese Academy of Sciences Donggguan 523808 China The Beijing Engineering Research Center of Intelligent Systems and Technology Institute of Automation Chinese Academy of Sciences Beijing 100190 China

3D human face modeling is one of the most popular research directions in the field of computer stereo vision. On the one hand, the complex physiological structure of human face as well as various expressions and attitude changes bring great challenges to three-dimensional modeling, which makes the modeling method of human face have high research value and reference significance. On the other hand, 3D face reconstruction has a broad application prospect, and the application demand attracts more researchers to invest in it. Based on the 3DMM and 3DDFA method, this paper utilizes regression neural network to realize end-to-end face reconstruction. After that, we build a visualization program with the training model to realize face modeling based on a single face image of any pose or expression. It’s a 3D face reconstruction system which has functions such as face alignment, face rotation and so on.

关键词： face reconstruct 3DMM 3DDFA regression network

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Identification of muscle morphology with noncontact capacitive sensing: Preliminary study

Identification of muscle morphology with noncontact capaciti...

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Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)

作者： Enhao Zheng Jiacheng Wan Dongfang Xu Qining Wang Hong Qiao The State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China School of Information Engineering China university of geosciences (Beijing) Beijing China The Robotics Research Group College of Engineering Peking University Beijing China

ISBN: (数字)9781728119908

ISBN: (纸本)9781728119915

Human-machine interface with muscle signals serves as an important role in the field of wearable robotics. To compensate for the limitations of the existing surface Electromyography (sEMG) based technologies, we previously proposed a noncontact capacitive sensing approach that could record the limb shape changes. The sensing approach frees the human skin from contacting to the metal electrodes, thus enabling the measurement of muscle signals by dressing the sensing front-ends outside of the clothes. We validated the capacitive sensing in human motion intent recognition tasks with the wearable robots and produced comparable results to existing studies. However, the biological significance of the capacitance signals is still unrevealed, which is an indispensable issue for robot intuitive control. In this study, we address the problems of identifying the relationships between the muscle morphological parameters and the capacitance signals. We constructed a measurement system that recorded the noncontact capacitive sensing signals and the muscle ultrasound (US) images simultaneously. With the designed device, five subjects were employed and the US images from the gastrocnemius muscle (GM) and the tibialis anterior (TA) muscle during level walking were sampled. We fitted the calculated muscle morphological parameters (the pinnation angles and the muscle fascicle length) and the capacitance signals of the same gait phases. The results demonstrated that at least one-channel capacitance signal strongly correlated to the muscle morphological parameters (R 2 > 0.5, quadratic regression). The average R 2 s of the most correlated channels were up to 0.86 for pinnation angles and 0.83 for the muscle fascicle length changes. The interesting findings in this preliminary study suggest the biological physical significance of the capacitance signals during human locomotion. Future efforts are worth being paid in this new research direction for more promising results.

关键词： Muscles Robot sensing systems Capacitance Legged locomotion Electrodes Ultrasonic variables measurement

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Distributed disturbance-observer-based vibration control for a flexible-link manipulator with output constraints

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Science China(Technological Sciences) 2018年第10期61卷 1528-1536页

作者： YANG HongJun LIU JinKun HE Wei State Key Laboratory of Management and Control for Complex System Institute of Automation Chinese Academy of Sciences School of Automation Science and Electrical Engineering Beihang University School of Automation and Electrical Engineering University of Science and Technology Beijing

The issue of output constraints is studied for a flexible-link manipulator in the presence of unknown spatially distributed disturbances. The manipulator can be taken as an Euler-Bernoulli beam and its dynamic is expressed by partial differential equations. On account of the uncertainty of disturbances, we present a disturbance observer to estimate infinite dimensional disturbances on the beam. The observer is proven exponentially stable. Considering the problem of output constraints in the practical engineering, we propose a novel distributed vibration controller based on the disturbance observer to fulfill the position regulation of the joint angle and suppress elastic deflections on the flexible link, while confining the regulating errors of output in a suitable scope that we can assign. The closed-loop system is demonstrated exponentially stable based on an integral-barrier Lyapunov function. Simulations validate the effectiveness of the design scheme.

关键词： flexible manipulator distributed vibration control disturbance observer partial differential equation output constraint distributed parameter system

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Improving the Data Quality for Credit Card Fraud Detection

Improving the Data Quality for Credit Card Fraud Detection

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IEEE International Conference on Intelligence and Security Informatics, ISI

作者： Rongrong Jing Hu Tian Yidi Li Xingwei Zhang Xiaolong Zheng Zhu Zhang Daniel Zeng The State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China School of Artificial Intelligence University of Chinese Academy of Sciences Beijing China Shenzhen Artificial Intelligence and Data Science Institude (Longhua) Shenzhen China

ISBN: (数字)9781728188003

ISBN: (纸本)9781728188010

label imbalance and data missing are two major challenges in the problem of credit card fraud detection. However, existing matrix completion algorithms are generally difficult and cannot be easily applied to real-world credit card fraud detection since the scale of the normally used dataset is oversized. In this paper, we develop a spectral regularization algorithm to complete the large-scale sparse matrices, and further utilize an over-sampling algorithm to tackle the problem of the imbalance between positive and negative samples. Experimental results on a real-world dataset demonstrate that our model can outperform the state-of-the-art baseline methods. The proposed method could also be extended to other large-scale scenarios where data is missing or labels are imbalanced.

关键词： Data integrity Conferences Credit cards Sparse matrices Security Informatics

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