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IEEE/CAA Journal of Automatica Sinica 2016年第4期3卷 345-348页

作者： Fei-Yue Wang Xiao Wang Lingxi Li Li Li IEEE State Key Laboratory of Management and Control for Complex Systems (SKL-MCCS) Institute of AutomationChinese Academy of Sciences (CASIA) Research Center of Computational Experiments and Parallel Systems the National University of Defense Technology Qingdao Academy of Intelligent Industries (QAII) QingdaoShandongChinaand SKL-MCCSCASIA Department of Electrical and Computer Engineering Purdue School of Engineering and TechnologyIndiana University-Purdue University Indianapolis Department of Automation Tsinghua University Jiangsu Province Collaborative Innovation Center of Modern Urban Traffic Technologies

The origin of artificial intelligence is investigated, based on which the concepts of hybrid intelligence and parallel intelligence are presented. The paradigm shift in Intelligence indicates the ''new normal'' of cyber-social-physical systems (CPSS), in which the system behaviors are guided by Merton's Laws. Thus, the ACP-based parallel intelligence consisting of Artificial societies, Computational experiments and Parallel execution are introduced to bridge the big modeling gap in CPSS. © 2014 Chinese Association of automation.

关键词： control systems Electrical engineering

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Colored petri net based diagnosis of process systems 30

Colored petri net based diagnosis of process systems

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30th European Simulation and Modelling Conference, ESM 2016

作者： Pózna, Anna I. Gerzson, Miklós Leitold, Adrien Hangos, Katalin M. Department of Electrical Engineering and Information Systems Hungary Deparment of Mathematics University of Pannonia P.O.B. 158 VeszprémH-8201 Hungary Process Control Research Group Computer and Automation Research Institute P.O.B. 63 BudapestH-1518 Hungary

ISBN: (纸本)9789077381953

An improved diagnosis method of technological systems is proposed in this paper that is based on their qualitative colored Petri-net model (Leitold et al. 2014). The proposed diagnosis method can be used when more than one fault occur in the system and if the fault evolves during the operation of the system. In order to make the diagnosis of complex process systems computationally feasible, a structural decomposition method is introduced to reduce the size of their occurrence graphs and to make the diagnosis easier. The proposed methods are illustrated on examples.

关键词： Fault detection

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Scene-specific pedestrian detection based on parallel vision

arXiv

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arXiv 2017年

作者： Zhang, Wenwen Wang, Kunfeng Qu, Hua Zhao, Jihong Wang, Fei-Yue School of Software Engineering Xi’an Jiaotong University Xi’an710049 China State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences Beijing100190 China Qingdao Academy of Intelligent Industries Qingdao266000 China School of Software Engineering Xi’an Jiaotong University Xi’an710049 China Department of Communication and Information Engineering Xi’an Jiaotong University Xi’an710049 China Research Center for Computational Experiments and Parallel Systems Technology National University of Defense Technology Changsha410073 China

As a special type of object detection, pedestrian detection in generic scenes has made a significant progress trained with large amounts of labeled training data manually. While the models trained with generic dataset work bad when they are directly used in specific scenes. With special viewpoints, flow light and backgrounds, datasets from specific scenes are much different from the datasets from generic scenes. In order to make the generic scene pedestrian detectors work well in specific scenes, the labeled data from specific scenes are needed to adapt the models to the specific scenes. While labeling the data manually spends much time and money, especially for specific scenes, each time with a new specific scene, large amounts of images must be labeled. What’s more, the labeling information is not so accurate in the pixels manually and different people make different labeling information. In this paper, we propose an ACP-based method, with augmented reality’s help, we build the virtual world of specific scenes, and make people walking in the virtual scenes where it is possible for them to appear to solve this problem of lacking labeled data and the results show that data from virtual world is helpful to adapt generic pedestrian detectors to specific scenes. Copyright © 2017, The Authors. All rights reserved.

关键词： Virtual reality

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Cluster synchronization for networks of generic linear systems and nonlinear oscillators via intermittent pinning control

Cluster synchronization for networks of generic linear syste...

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第28届中国控制与决策会议

作者： Jiahu Qin Qichao Ma Huijun Gao Wei Xing Zheng Department of Automation University of Science and Technology of China Research Institute of Intelligent Control and Systems Harbin Institute of Technology School of Computing Engineering and MathematicsWestern Sydney University

ISBN: (纸本)9781467397155

This paper is concerned with applying intermittent pinning controllers to synchronization of interacting clusters of linearly coupled heterogeneous linear systems and nonlinear oscillators under general coupling *** cluster synchronization is analyzed via a unified approach to convergence *** key idea of the work is based on the observation that the given cluster synchronization patterns can be realized if the underlying topology of each extended cluster has a directed spanning tree and an algebraic condition is *** structural conditions are developed to ensure the related algebraic ***,for linear systems,the algebraic condition can be guaranteed if the strength of the intra-cluster couplings are sufficiently strong and meanwhile the work time of the pinning controller in each period is sufficiently long;for nonlinear oscillators,the work time of the pinning controller can be arbitrarily short as long as the intra-cluster coupling strength for each cluster is sufficiently ***,both the lower bounds for such coupling strengths and length of the work time of the pinning controller in each period are explicitly specified.

关键词： Cluster synchronization intermittent pinning control heterogeneous systems generic linear systems nonlinear oscillators

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Attitude synchronization of multiple rigid bodies in SE(3) over proximity networks

Attitude synchronization of multiple rigid bodies in SE(3) o...

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第35届中国控制会议

作者： Juan Deng Zhixin Liu Lin Wang John S.Baras Key Laboratory of Systems and Control Academy of Mathematics and Systems ScienceCAS Department of Automation Shanghai Jiao Tong Universityand the Key Laboratory of System Control and Information ProcessingMinistry of Education Department of Electrical and Computer Engineering and the Institute for Systems Research University of MarylandCollege Park

ISBN: (纸本)9781509009107

This paper investigates the attitude synchronization of a group of moving rigid bodies whose states including positions and rotation matrices evolve in the Lie group SE(3).The commonly used circular neighborhood is adopted,and the neighbor graphs are described by proximity *** order to avoid introducing discussions on the abrupt changes of neighbor graphs,a dwell time is *** distributed sampled-data control law for the angular velocity is *** the assumptions on the initial states,we provide sufficient conditions for the attitude synchronization of multiple rigid body *** with the existing results,our condition depends only on the neighborhood radius,the moving velocity and the dwell time.

关键词： rigid body SE(3) attitude synchronization sampled-data control proximity network

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Identifying the best machine learning algorithms for brain tumor segmentation, progression assessment, and overall survival prediction in the BRATS challenge

arXiv

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arXiv 2018年

作者： Bakas, Spyridon Reyes, Mauricio Jakab, Andras Bauer, Stefan Rempfler, Markus Crimi, Alessandro Shinohara, Russell Takeshi Berger, Christoph Ha, Sung Min Rozycki, Martin Prastawa, Marcel Alberts, Esther Lipkova, Jana Freymann, John Kirby, Justin Bilello, Michel Fathallah-Shaykh, Hassan M. Wiest, Roland Kirschke, Jan Wiestler, Benedikt Colen, Rivka Kotrotsou, Aikaterini Lamontagne, Pamela Marcus, Daniel Milchenko, Mikhail Nazeri, Arash Weber, Marc-Andr Mahajan, Abhishek Baid, Ujjwal Gerstner, Elizabeth Kwon, Dongjin Acharya, Gagan Agarwal, Manu Alam, Mahbubul Albiol, Alberto Albiol, Antonio Albiol, Francisco J. Alex, Varghese Allinson, Nigel Amorim, Pedro H.A. Amrutkar, Abhijit Anand, Ganesh Andermatt, Simon Arbel, Tal Arbelaez, Pablo Avery, Aaron Azmat, Muneeza Pranjal, B. Bai, Wenjia Banerjee, Subhashis Barth, Bill Batchelder, Thomas Batmanghelich, Kayhan Battistella, Enzo Beers, Andrew Belyaev, Mikhail Bendszus, Martin Benson, Eze Bernal, Jose Bharath, Halandur Nagaraja Biros, George Bisdas, Sotirios Brown, James Cabezas, Mariano Cao, Shilei Cardoso, Jorge M. Carver, Eric N. Casamitjana, Adri Castillo, Laura Silvana Cat, Marcel Cattin, Philippe Cérigues, Albert Chagas, Vinicius S. Chandra, Siddhartha Chang, Yi-Ju Chang, Shiyu Chang, Ken Chazalon, Joseph Chen, Shengcong Chen, Wei Chen, Jefferson W. Chen, Zhaolin Cheng, Kun Choudhury, Ahana Roy Chylla, Roger Clrigues, Albert Colleman, Steven Colmeiro, Ramiro German Rodriguez Combalia, Marc Costa, Anthony Cui, Xiaomeng Dai, Zhenzhen Dai, Lutao Daza, Laura Alexandra Deutsch, Eric Ding, Changxing Dong, Chao Dong, Shidu Dudzik, Wojciech Eaton-Rosen, Zach Egan, Gary Escudero, Guilherme Estienne, Tho Everson, Richard Fabrizio, Jonathan Fan, Yong Fang, Longwei Feng, Xue Ferrante, Enzo Fidon, Lucas Fischer, Martin French, Andrew P. Fridman, Naomi Fu, Huan Fuentes, David Gao, Yaozong Gates, Evan Gering, David Gholami, Amir Gierke, Willi Glocker, Ben Gong, Mingming Gonzlez-Vill, Sandra Grosges, T. Guan, Yuanfang Guo, Sheng Gupta, Sudeep Han, Woo-Sup Han, Il Song Harmuth, Ko Center for Biomedical Image Computing and Analytics University of Pennsylvania PhiladelphiaPA United States Department of Radiology Perelman School of Medicine University of Pennsylvania PhiladelphiaPA United States Department of Pathology and Laboratory Medicine Perelman School of Medicine University of Pennsylvania PhiladelphiaPA United States Institute for Surgical Technology and Biomechanics University of Bern Bern Switzerland Center for MR-Research University Children's Hospital Zurich Zurich Switzerland Support Centre for Advanced Neuroimaging Inselspital Institute for Diagnostic and Interventional Neuroradiology Bern University Hospital Bern Switzerland University Hospital of Zurich Zurich Switzerland Center for Clinical Epidemiology and Biostatistics University of Pennsylvania Philadelphia United States Image-Based Biomedical Modeling Group Technical University of Munich Munich Germany Icahn School of Medicine Mount Sinai Health System New YorkNY United States Leidos Biomedical Research Inc. Frederick National Laboratory for Cancer Research FrederickMD21701 United States Cancer Imaging Program National Cancer Institute National Institutes of Health BethesdaMD20814 United States Department of Neurology University of Alabama at Birmingham BirminghamAL United States Department of Diagnostic Radiology University of Texas MD Anderson Cancer Center HoustonTX United States Department of Psychology Washington University St. LouisMO United States Neuroimaging Informatics and Analysis Center Washington University St. LouisMO United States Department of Radiology Washington University St. LouisMO United States Institute of Diagnostic and Interventional Radiology Pediatric Radiology and Neuroradiology University Medical Center Rostock Ernst-Heydemann-Str. 6 Rostock18057 Germany Tata Memorial Centre Homi Bhabha National Institute Mumbai India Shri Guru Gobind Singhji Institute of Engineering and Technology Nanded India NVIDIA Santa Clara

Gliomas are the most common primary brain malignancies, with different degrees of aggressiveness, variable prognosis and various heterogeneous histologic sub-regions, i.e., peritumoral edematous/invaded tissue, necrotic core, active and non-enhancing core. This intrinsic heterogeneity is also portrayed in their radio-phenotype, as their sub-regions are depicted by varying intensity profiles disseminated across multi-parametric magnetic resonance imaging (mpMRI) scans, reflecting varying biological properties. Their heterogeneous shape, extent, and location are some of the factors that make these tumors difficult to resect, and in some cases inoperable. The amount of resected tumor is a factor also considered in longitudinal scans, when evaluating the apparent tumor for potential diagnosis of progression. Furthermore, there is mounting evidence that accurate segmentation of the various tumor sub-regions can offer the basis for quantitative image analysis towards prediction of patient overall survival. This study assesses the state-of-the-art machine learning (ML) methods used for brain tumor image analysis in mpMRI scans, during the last seven instances of the International Brain Tumor Segmentation (BraTS) challenge, i.e., 2012-2018. Specifically, we focus on i) evaluating segmentations of the various glioma sub-regions in pre-operative mpMRI scans, ii) assessing potential tumor progression by virtue of longitudinal growth of tumor sub-regions, beyond use of the RECIST/RANO criteria, and iii) predicting the overall survival from pre-operative mpMRI scans of patients that underwent gross total resection. Finally, we investigate the challenge of identifying the best ML algorithms for each of these tasks, considering that apart from being diverse on each instance of the challenge, the multi-institutional mpMRI BraTS dataset has also been a continuously evolving/growing dataset. Copyright © 2018, The Authors. All rights reserved.

关键词： Tumors

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Contributions of Social Manufacturing to Sustainable Apparel Industry

Contributions of Social Manufacturing to Sustainable Apparel...

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2016年IEEE/INFORMS服务运筹、物流与信息化国际会议

作者： Babak Mohajeri Timo Nyberg Jesse Karjalainen Mark Nelson Gang Xiong Aalto University Department of Industrial Engineering and Management Human Sciences and Technologies Advanced Research Institute (H-STAR)Stanford University The State Key Laboratory of Management and Control for Complex Systems Institute of AutomationChinese Academy of Science

The global apparel and textile market has been changed considerably during the recent years. At the one hand, new trends and consumer preferences for different styles and fashion products emerge continuously, thus the apparel industry becomes more mass customized. On the other hand, attention to social and environmental sustainability has been dramatically increased in the entire industry. However, the current fast-changing fashion trends result to significant environmental and resource depletion problems in the textile lifecycle. As a result, the apparel industry should consider sustainable manufacturing strategies. The current options such as organic fibers and environmentally safe dyes seem promising. Nonetheless, there are significant challenges for apparel manufacturers and retailers to capitalize sustainability. To address these problems, in this paper, we develop a conceptual model of Social Manufacturing for the apparel industry. We study the current value chain of the apparel industry and identify its challenges from the sustainability's view. Then, we propose a new model to improve the sustainability throughout the value chain of the apparel industry

关键词： Social Manufacturing Apparel Industry Value chain sustainability

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Social Manufacturing Development with Sino-Finnish Innovation Cooperation

Social Manufacturing Development with Sino-Finnish Innovatio...

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2016年IEEE/INFORMS服务运筹、物流与信息化国际会议

作者： Jian Liu Gang Xiong Xiuqin Shang Timo R.Nyberg Yiming Wang Tongkai Ji The State Key Laboratory of Management and Control for Complex Systems Institute of AutomationChinese Academy of Sciences College of Information Science and Technology Beijing University of Chemical Technology Cloud Computing Center Chinese Academy of Sciences Department of Industrial Engineering and Management School of ScienceAalto University Beijing Engineering Research Center of Intelligent Systems and Technology Institute of AutomationChinese Academy of Sciences

Innovation is changing the world every day by offering new technical solutions for the society, and the technology development powered by innovation has been changing the operation and structure of traditional manufacturing. Social manufacturing is the new trend of manufacturing development, especially in the field of apparel industry. Social manufacturing can create opportunities for customers to participate in the produce process of tailoring, and to make more personalizing clothes, which will also benefit for the related companies' brand making process. With the assistance of internet technology and industry globalization, we can establish several modes about the trend of social manufacturing and new related technology, social manufacturing can also prompt the international division of labor by reducing the producing costs and enlarging the market capacity, we will analyze the advance of Sino-Finland cooperation in the field of innovation and apparel industry, the international cooperation in manufacturing industry will benefit both customers and industry revolution with the assistance of social manufacturing.

关键词： social manufacturing innovation apparel industry international cooperation

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Globally stabilizing state feedback control design for Lotka-Volterra systems based on underlying linear dynamics

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IFAC-PapersOnLine 2015年第11 11期48卷 1000-1005页

作者： Magyar, Attila Hangos, Katalin M. Department of Electrical Engineering and Information Systems University of Pannonia Egyetem street 10. Veszprém H-8200 Hungary Process Control Research Group Control and Automation Research Institute HAS Kende street 13-17 BudapestH-1111 Hungary

Using translated X-factorable phase space transformations and nonlinear variable transformations a dynamically similar linear ODE model is associated to the Lotka-Volterra system models with a positive equilibrium point. This enables to use a linear full state feedback controller to stabilize the system in controllable cases, that leaves the open loop equilibrium point unchanged. The linear state feedback controller design problem in the general case has also been formulated to ensure the compartmental property of the closed loop system from which the existence of a diagonal Lyapunov function follows. Further extension has been obtained by using the time re-parametrization transformation defined for quasi-polynomial models. © 2015

关键词： Mathematical transformations Biological systems Closed loop systems controllers Feedback control Linear transformations Lyapunov functions Phase space methods Polynomial approximation Predator prey systems State feedback Diagonal Lyapunov functions Linear state feedback Lotka Volterra models Lotka Volterra systems Nonlinear variables Phase space transformation Positive equilibrium Quasi poly nomial

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Distributed k-means algorithm for sensor networks based on multi-agent consensus theory

Distributed k-means algorithm for sensor networks based on m...

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IEEE International Conference on Industrial Technology (ICIT)

作者： Qiuhong Liu Weiming Fu Jiahu Qin Wei Xing Zheng Huijun Gao Research Institute of Intelligent Control and Systems Harbin Institute of Technology Harbin China Department of Automation University of Science and Technology of China Hefei China School of Computing Engineering and Mathematics Western Sydney University Sydney NSW Australia Harbin Institute of Technology Harbin Heilongjiang CN

ISBN: (纸本)9781467380768

This paper is concerned with developing a distributed k-means algorithm for the wireless sensor networks (WSN) where each node is equipped with sensors. The underlying topology of the WSN is supposed to be strongly connected. The consensus algorithm in multi-agent consensus theory is utilized to exchange the measurement information of the sensors in WSN. To obtain a faster convergence speed as well as a higher possibility of having the global optimum, a distributed k-means++ algorithm is firstly proposed to find the initial centroids before executing the distributed k-means algorithm. The proposed distributed k-means algorithm is capable of partitioning the data observed by the nodes into measure-dependent groups which have small in-group and large out-group distances. Simulation results show that the proposed distributed algorithms can achieve almost the same results as that achieved by the centralized clustering algorithms.

关键词： Clustering algorithms Partitioning algorithms Nickel Wireless sensor networks Computational complexity Distributed databases Network topology

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