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19th IFAC World Congress on International Federation of Automatic control, IFAC 2014

作者： Wang, Tao Liu, Zhong Cui, Kainan Zhang, Jie Wang, Fei-Yue Philip Chen, C.L. College of Information System and Management National University of Defense Technology Changsha410073 China State Key Laboratory of Management and Control for Complex Systems Chinese Academy of Sciences Beijing100190 China Research Center for Computational Experiments and Parallel Systems Technology National University of Defense Technology Changsha410073 China Department of Computer and Information Science Science and Technology University of Macau China

ISBN: (纸本)9783902823625

Cyber Movement Organization (CMO) is a special kind of social movement organization on the Web. In this paper, we propose a model to simulate the mobilizing process of CMO, which consists of the individual unit, organization unit, and the mobilizing mechanisms. The mobilizing mechanisms has three sub-mechanisms: the participation mechanism, the choice mechanism, and the inviting mechanism. A dataset of more than two million "human flesh search" related microblogs is used to validate the model. Empirical results show that our model can capture the key features of the real-world mobilizing process. © IFAC.

关键词： Automation

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A Biologically Inspired Model of Emotional Attention

A Biologically Inspired Model of Emotional Attention

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2013 IEEE 4th International Conference on Software Engineering and Service Science

作者： Dongchun Ren Hong Qiao Jianhua Su State Key Laboratory of Management and Control for Complex System Institute of AutomationChinese Academy of Sciences

ISBN: (纸本)9781467349970

This paper proposes a new biologically inspired emotional attention model to expand existing visual attention models by considering emotional impact on *** our work,we combine color emotion activity and emotional arousal with visual spatial *** the experiments,an affective picture dataset and an eye-tracking dataset are used to test our proposed *** results show that the performance of the emotional attention model is promising.

关键词： visual attention emotional attention affective computing

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Implementation and Experimental Study on the control system of the Stewart Platform Model of FAST

Implementation and Experimental Study on the Control System ...

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第25届中国控制与决策会议

作者： Fengguang He Fengshui Jing Guodong Yang En Li Zize Liang Dongjun Yu State Key Laboratory of Management and Control for Complex System Institute of Automation Chinese Academy of Sciences Nation Astronomical Observatory Chinese Academy of Sciences

ISBN: (纸本)9781467355339

In order to verify the vibration resistance feasibility of the Stewart platform with a flexible base platform in the feed cabin support system of FAST（Five-hundred-meter Aperture Spherical radio Telescope）, this paper presents a scheme on the implementation of the reduced scale Stewart platform model of FAST. A vibration suppressing control algorithm is given, and the experiments related were conducted. The results show that the system is capable of suppressing normal vibrations.

关键词： FAST Stewart platform vibration suppressing

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On Mobilizing Processes of Cyber Movement Organizations

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IFAC Proceedings Volumes 2014年第3期47卷 9853-9857页

作者： Tao Wang Zhong Liu Kainan Cui Jie Zhang Fei-Yue Wang C.L. Philip Chen College of Information System and Management National University of Defense Technology Changsha 410073 China The State Key Laboratory of Management and Control for Complex Systems Chinese Academy of Sciences Beijing 100190 China The Research Center for Computational Experiments and Parallel Systems Technology National University of Defense Technology Changsha 410073 China Department of Computer and Information Science Science and Technology University of Macau Macau China

—Cyber Movement Organization (CMO) is a special kind of social movement organization on the Web. In this paper, we propose a model to simulate the mobilizing process of CMO, which consists of the individual unit, organization unit, and the mobilizing mechanisms. The mobilizing mechanisms has three sub-mechanisms: the participation mechanism, the choice mechanism, and the inviting mechanism. A dataset of more than two million “human flesh search” related microblogs is used to validate the model. Empirical results show that our model can capture the key features of the real-world mobilizing process.

关键词： Cyber Movement Organizations (CMO) Social Network Analysis Human Flesh Search (HFS) Simulation Social Movement Organizations Resource Mobilization

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Online multi-task collaborative filtering for on-the-fly recommender systems 13

Online multi-task collaborative filtering for on-the-fly rec...

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7th ACM Conference on Recommender systems, RecSys 2013

作者： Wang, Jialei Hoi, Steven C.H. Zhao, Peilin Liu, Zhi-Yong School of Computer Engineering Nanyang Technological University Singapore 639798 Singapore State Key Lab of Management and Control for Complex System Chinese Academy of Sciences China

ISBN: (纸本)9781450324090

Traditional batch model-based Collaborative Filtering (CF) approaches typically assume a collection of users' rating data is given a priori for training the model. They suffer from a common yet critical drawback, i.e., the model has to be re-trained completely from scratch whenever new training data arrives, which is clearly non-scalable for large real recommender systems where users' rating data often arrives sequentially and frequently. In this paper, we investigate a novel efficient and scalable online collaborative filtering technique for on-the-fly recommender systems, which is able to effectively online update the recommendation model from a sequence of rating observations. Specifically, we propose a family of online multi-task collaborative filtering (OMTCF) algorithms, which tackle the online collaborative filtering task by exploiting the similar principle as online multitask learning. Encouraging empirical results on large-scale datasets showed that the proposed technique is significantly more effective than the state-of-the-art algorithms. © 2013 ACM.

关键词： Collaborative filtering

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Haptic interfaces for the rescue walking robots motion in the disaster areas

Haptic interfaces for the rescue walking robots motion in th...

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UKACC International Conference on control (control)

作者： Luige Vladareanu Octavian Melinte Adrian Bruja Hongbo Wang Xiaojie Wang Shuang Cang Hongnian Yu Zeng-Guang Hou Xiao-Liang Xie Robotics and Mechatronics Department Institute of Solid Mechanics C-tin Mille 15 Bucharest 1 ROMANIA School of Design Engineering and Computing Boumemouth University Poole Dorset UK Parallel Robot and Mechatronic System Laboratory of Hebei Province University Qinhuangdao CHINA State Key Laboratory of Management and Control for Complex Systems Beijing P.R.CHINA

In the recent years haptic interfaces became a reliable solution in order to solve problems which arise when humans interact with the environment. If in the research area of the haptic interaction between human and environment there are important researches, a innovative approach for the interaction between the robot and the environment using haptic interfaces and virtual projection method is presented in this paper. In order to control this interaction we used the Virtual Projection Method where haptic control interfaces of impedance and admittance will be embedded. The obtained results, validated by simulations assure stability, stiffness, high maneuverability and adaptability for rescue walking robots in order to move in disaster, dangerous and hazardous areas.

关键词： Haptic interfaces Legged locomotion Robot sensing systems Impedance Force

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Large scale online kernel classification

Large scale online kernel classification

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23rd International Joint Conference on Artificial Intelligence, IJCAI 2013

作者： Wang, Jialei Hoi, Steven C.H. Zhao, Peilin Zhuang, Jinfeng Liu, Zhi-Yong School of Computer Engineering Nanyang Technological University Singapore Singapore Microsoft Corporation United States State Key Lab of Management and Control for Complex System Chinese Academy of Sciences China

ISBN: (纸本)9781577356332

In this work, we present a new framework for large scale online kernel classification, making kernel methods efficient and scalable for large-scale online learning tasks. Unlike the regular budget kernel online learning scheme that usually uses different strategies to bound the number of support vectors, our framework explores a functional approximation approach to approximating a kernel function/matrix in order to make the subsequent online learning task efficient and scalable. Specifically, we present two different online kernel machine learning algorithms: (i) the Fourier Online Gradient Descent (FOGD) algorithm that applies the random Fourier features for approximating kernel functions;and (ii) the Nyström Online Gradient Descent (NOGD) algorithm that applies the Nyström method to approximate large kernel matrices. We offer theoretical analysis of the proposed algorithms, and conduct experiments for large-scale online classification tasks with some data set of over 1 million instances. Our encouraging results validate the effectiveness and efficiency of the proposed algorithms, making them potentially more practical than the family of existing budget kernel online learning approaches.

关键词： Budget control

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Deployment and Routing Method for Fast Localization Based on RSSI in Hierarchical Wireless Sensor Network

Deployment and Routing Method for Fast Localization Based on...

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IEEE Internatonal Conference on Mobile Adhoc and Sensor systems (MASS)

作者： Nan Zhou Xiaoguang Zhao Min Tan Institute of Automation The State Key Lab of Management and Control for Complex System Beijing China

This paper proposes a method of hierarchical WSN deployment and routing for fast localization. Position-known anchor nodes form a static upper-layer network organization and several mobile nodes constitute the lower-layer network which need dynamic message exchange with the upper network. In the upper static network, near-optimal routing table is allocated to each anchor node based on their known-position and the strength of signal for communication during network initialization. Mobile nodes in the lower-layer can access to the upper network dynamically and at the same time report the RSSI value of nearby anchors to the control-center. At the center, the computer will calculate the real-time location of the target based on the reported RSSI and node-IDs. Algorithm presented in this paper is low cast, easy to implement and can be used for fast location estimation and motion tracking indoors and outdoors.

关键词： Routing Wireless sensor networks Mobile nodes Organizations Algorithm design and analysis Indoor environments

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A novel sparse auto-encoder for deep unsupervised learning

A novel sparse auto-encoder for deep unsupervised learning

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International Workshop on Advanced Computational Intelligence (IWACI)

作者： Xiaojuan Jiang Yinghua Zhang Wensheng Zhang Xian Xiao State Key Laboratory of Intelligent Control and Management of Complex System at Institute of Automation Chinese Academy of Sciences Beijing

This paper proposes a novel sparse variant of auto-encoders as a building block to pre-train deep neural networks. Compared with sparse auto-encoders through KL-divergence, our method requires fewer hyper-parameters and the sparsity level of the hidden units can be learnt automatically. We have compared our method with several other unsupervised leaning algorithms on the benchmark databases. The satisfactory classification accuracy (97.92% on MNIST and 87.29% on NORB) can be achieved by a 2-hidden-layer neural network pre-trained using our algorithm, and the whole training procedure (including pre-training and fine-tuning) takes far less time than the state-of-art results.

关键词： Training Classification algorithms Data models Principal component analysis Lead

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Identifying peer influence in online social networks using transfer entropy

Identifying peer influence in online social networks using t...

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Pacific Asia Workshop on Intelligence and Security Informatics, PAISI 2013

作者： He, Saike Zheng, Xiaolong Zeng, Daniel Cui, Kainan Zhang, Zhu Luo, Chuan State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing 100190 China Department of Management Information System University of Arizona Tucson AZ 85719 United States School of Electronic and Information Engineering Xi'an Jiaotong University Xi'an China

ISBN: (纸本)9783642396922

The past few years have witnessed the rapid growth of online social networks, which have become important hubs of social activity and conduits of information. Identifying social influence in these newly emerging platforms can provide us with significant insights to better understand the interaction behaviors among online users. However, it is difficult for us to measure the influence quantitatively among user peers, since many key factors such as homophily and heterogeneity, can not be observed in our real world conveniently. More recent work mainly focuses on developing theoretical models based on explicit causal knowledge. Nevertheless, such knowledge is usually not available and often needs to be discovered. In this paper, we introduce a model free approach to formulate causal inferences of behaviors among user peers. Experimental results show that influence measured by our approach could successfully reconstruct the underlying networks structure. Furthermore, two additional case studies based on this approach reveal that influentials wield power through specific venues, which constitute a comparatively small portion of the whole channels. © 2013 Springer-Verlag.

关键词： Social networking (online)

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