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IEEE International Conference on Mechatronics and Automation

作者： Ying Wu Qiang Huang Xuechao Chen Zhangguo Yu Libo Meng Gan Ma Peisen Zhang Weimin Zhang Intelligent Robotics Institute Beijing Institute of Technology Beijing China State Key Laboratory of Intelligent Control and Decision of Complex System Beijing China International Joint Research Laboratory of Biomimetic Robots and Systems Ministry of Education Beijing China

ISBN: (纸本)9781479970995

This paper introduces the similarity evaluation on humanoid facial expression. For the purpose of understanding easily, firstly, the process of designing humanoid robot's facial expressions is explored in brief. Then, a similarity function is proposed to evaluate the similarity of the robot facial motion compared with the human being quantitatively based on both the kinematics and dynamics factors, also including how to select the key value of parameter in similarity function. Finally, the effectiveness of the similarity function is confirmed by an experiment of facial expressions based on BHR-4 robot.

关键词： Joints Kinematics Dynamics Trajectory Humanoid robots Rhythm

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Event-based state Estimation of a Discrete-state Hidden Markov Model through a Reliable Communication Channel

Event-based State Estimation of a Discrete-State Hidden Mark...

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第三十四届中国控制会议

作者： Dawei Shi Robert J.Elliott Tongwen Chen State Key Laboratory of Intelligent Control and Decision of Complex Systems School of Automation Beijing Institute of Technology School of Mathematical Sciences University of Adelaide SA 5005 Australia the Haskayne School of Business University of Calgary

ISBN: (纸本)9781467374439

In this work, a state estimation problem is considered for a hidden Markov model subject to event-based sensor measurement updates sent through a reliable communication channel. The change of probability approach is utilized to consider the estimation problem, and an analytical expression for the probability distributions of the states conditioned on all the past hybrid point- and set-valued measurement information caused by the event-triggering scheme is obtained. Also, it is shown that the scenario with a lossy channel, but without the event-trigger, can be treated as a special case of the reliable channel results,and thus can be solved by applying the proposed results.

关键词： Event-based estimation,Hidden Markov models,Optimal estimation

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Visualisation of the Early-Stage Vibration of the Automatic-Gauge-control Hydraulic Cylinder Based on the Acoustic Emission Hits-Density Imaging

Visualisation of the Early-Stage Vibration of the Automatic-...

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2015年中国智能自动化学术会议

作者： Hongzhi Chen Yongli Zhao Jie Huang Chang Cheng State Key Laboratory of Hybrid Process Industry Automation System and Equipment Technology Automation Research and Design Institute of Metallurgical Industry Key Laboratory of Intelligent Control and Decision of Complex Systems School of Automation Beijing Institute of Technology Fujian Institute of Education

By taking into account the hits-density imaging technique that has been introduced by authors' previous publications, the acoustic emission bursts emitted from the automatic-gauge-control hydraulic cylinder under normal loading and early-stage vibration were investigated. First, six acoustic emission descriptors that showed significance regarding the cumulative probability distribution were visualised, followed by the reconstruction of the hits-density images using these features;Through the visual examination of the hits-density images regarding the cylinders' normal loading and early-stage vibration, apparent visual differences between normal and early-stage vibration under the same loading can be observed;By projecting the hits-density images onto the principal component space, a trajectory which represents the condition developments was observed, which shows a visual-based resolution for dealing with vast transient bursts data reduction,reconstruction and visualisation.

关键词： Visualisation Hits-density imaging Early-stage vibration Acoustic emission

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Emotion extraction and entrainment in social media: The case of U.S. immigration and border security 13

Emotion extraction and entrainment in social media: The case...

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13th IEEE International Conference on Intelligence and Security Informatics, ISI 2015

作者： Chung, Wingyan He, Saike Dajun Zeng, Daniel Benjamin, Victor Dept. of Decision and Info. Sciences School of Business Administration Stetson University DeLandFL United States State Key Lab of Management and Control for Complex Systems Chinese Academy of Sciences Beijing China Dept. of MIS U. of Arizona TucsonAZ United States Dept. of MIS Eller College of Management University of Arizona TucsonAZ United States

ISBN: (纸本)9781479998883

Emotion plays an important role in shaping public policy and business decisions. The growth of social media has allowed people to express their emotion publicly in an unprecedented manner. Textual content and user linkages fostered by social media networks can be used to examine emotion types, intensity, and contagion. However, research into how emotion evolves and entrains in social media that influence security issues is scarce. In this research, we developed an approach to analyzing emotion expressed in political social media. We compared two methods of emotion analysis to identify influential users and to trace their contagion effects on public emotion, and report preliminary findings of analyzing the emotion of 105,304 users who posted 189,012 tweets on the U.S. immigration and border security issues in November 2014. The results provide strong implication for understanding social actions and for collecting social intelligence for security informatics. This research should contribute to helping decision makers and security personnel to use public emotion effectively to develop appropriate strategies. © 2015 IEEE.

关键词： decision making

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Large scale online kernel learning

The Journal of Machine Learning Research

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The Journal of Machine Learning Research 2016年第1期17卷

作者： Kevin Murphy Bernhard Schölkopf Jing Lu Steven C. H. Hoi Jialei Wang Peilin Zhao Zhi-Yong Liu Google MPI for Intelligent Systems School of Information Systems Singapore Management University Singapore Department of Computer Science University of Chicago Chicago IL Institute for Infocomm Research A*STAR Connexis Singapore State Key Lab of Management and Control for Complex System Chinese Academy of Sciences Beijing China

In this paper, we present a new framework for large scale online kernel learning, making kernel methods efficient and scalab.e for large-scale online learning applications. Unlike the regular budget online kernel learning scheme that usually uses some budget maintenance strategies to bound the number of support vectors, our framework explores a completely different approach of kernel functional approximation techniques to make the subsequent online learning task efficient and scalab.e. Specifically, we present two different online kernel machine learning algorithms: (i) Fourier Online Gradient Descent (FOGD) algorithm that applies the random Fourier features for approximating kernel functions; and (ii) Nyström Online Gradient Descent (NOGD) algorithm that applies the Nyström method to approximate large kernel matrices. We explore these two approaches to tackle three online learning tasks: binary classification, multi-class classification, and regression. The encouraging results of our experiments on large-scale datasets validate the effectiveness and efficiency of the proposed algorithms, making them potentially more practical than the family of existing budget online kernel learning approaches.

关键词： kernel approximation large scale machine learning online learning

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state Estimation of Finite-state Hidden Markov Models Subject to Stochastically Event-triggered Measurements

State Estimation of Finite-State Hidden Markov Models Subjec...

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IEEE Annual Conference on decision and control

作者： Wentao Chen Junzheng Wang Ling Shi Dawei Shi State Key Laboratory of Intelligent Control and Decision of Complex Systems School of Automation Beijing Institute of Technology Beijing 100081 P.R. China Department of Electronic and Computer Engineering Hong Kong University of Science and Technology Clear Water Bay Kowloon Hong Kong

ISBN: (纸本)9781479978878

We consider the event-triggered state estimation of a finite-state hidden Markov model with a general stochastic event-triggering condition. Utilizing the change of probability measure approach and the event-triggered measurement information availab.e to the estimator, analytical expressions for the conditional probability distributions of the states are obtained, based on which the minimum mean square error event-based state estimates are further calculated. We show that the results also cover the case of packet dropout, under a special parameterization of the event-triggering conditions. With the results on state estimation, a closed-form expression of the average sensor-to-estimator communication rate is also presented. The effectiveness of the proposed results is illustrated by a numerical example and comparative simulations.

关键词： state estimation Hidden Markov models Event trigger Probability distribution Mean square error numerical example

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Biomimetic inspiration for PKM torso design in humanoid robots

Biomimetic inspiration for PKM torso design in humanoid robo...

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IEEE International Conference on Mechatronics and Automation

作者： Hulin Huang Ceccarelli Marco Weimin Zhang Qiang Huang Zhangguo Yu Xuechao Chen Ministry of Education Key Laboratory of Biomimetic Robots and Systems (Beijing Institute of Technology) Beijing China Laboratory of Robotics and Mechatronics University of Cassino and South Latium Cassino Italy Ministry of Education International Joint Research Laboratory of Biomimetic Robots and Systems (Beijing Institute of Technology) Beijing China State Key Laboratory of Intelligent Control and Decision of Complex System Beijing China

ISBN: (纸本)9781479970995

A new torso design of humanoid robot is proposed as a 3-DOF PKM (Parallel Kinematic Manipulator) structure by using results of a biomimetic analysis of torso in humans and animals. Main characteristics of torso in nature are presented from which design requirements are outlined for a solution in humanoid robot. The PKM torso is consist of two platforms and four UPU mechanisms. The usefulness of such a biomimetic inspiration is proved by a numerical simulation of the proposed PKM torso in its basic movements.

关键词： Torso Humanoid robots Joints Thorax Horses Payloads

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Continuous Travel Time Prediction for Transit Signal Priority Based on a Deep Network

Continuous Travel Time Prediction for Transit Signal Priorit...

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International Conference on intelligent Transportation

作者： Xiong Gang Wenwen Kang Feiyue Wang Fenghua Zhu Yisheng Lv Xisong Dong Jukka Riekki Susanna Pirttikangas State Key Lab. of Manage. & Control for Complex Syst. Institute of Automation Chinese Academy of Sciences Beijing Beijing CN The State Key Laboratory of Management and Control for Complex Systems Chinese Academy of Sciences Beijing China Cloud Computing Center Chinese Academy of Sciences Dongguan CHINA Faculty of Information Technology and Electrical Engineering University of Oulu Finland

It has been recognized by many researchers that accurate bus travel time prediction is critical for successful deployment of traffic signal priority (TSP) systems. Although there exist a lot of studies on travel time prediction for Advanced Traveler Information systems (ATIS), this problem for TSP purpose is a little different and the amount of literature is limited. This paper proposes a deep learning based approach for continuous travel time prediction problem. Parameters of the deep network are fine-tuned following a layer-by-layer pre-training procedure on a dataset generated by traffic simulations. Variables that may affect continuous travel time are selected carefully. Experiments are conducted to validate the performance of the proposed model. The results indicate that the proposed model produces prediction with mean absolute error less than 4 seconds, which is accurate enough for TSP operations. This paper also reveals that, except for obvious factors like speed, travel distance and traffic density, the signal time when the prediction is made is also an important factor affecting travel time.

关键词： Vehicles Predictive models Object oriented modeling Training Artificial neural networks Data models

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Emotion extraction and entrainment in social media: The case of U.S. immigration and border security

Emotion extraction and entrainment in social media: The case...

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IEEE International Conference on Intelligence and Security Informatics, ISI

作者： Wingyan Chung Saike He Daniel Dajun Zeng Victor Benjamin Dept. of Decision and Info. Sciences Stetson University DeLand Florida U.S.A. State Key Lab of Management and Control for Complex Systems Chinese Academy of Sciences Beijing China Dept. of MIS U. of Arizona Tucson Arizona U.S.A. Dept. of MIS University of Arizona Arizona U.S.A.

关键词： Media Security Informatics Communities Public policy Couplings

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Haptic intelligent interfaces for NAO robot hand control

Haptic intelligent interfaces for NAO robot hand control

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International Conference on Advanced Mechatronic systems (ICAMechS)

作者： Octavian Melinte Luige Vladareanu Ligia Munteanu Hongnian Yu Shuang Cang Zeng-Guang Hou Gui-Bin Bian Hongbo Wang Dept. Robotics and Mechatronics Institute of Solid Mechanics of Romanian Academy Bucharest Romania Engineering and Computing Bournemouth University Dorset UK State Key Laboratory of Management and Control for Complex Systems Chinese Academy of Sciences Beijing China Parallel Robot and Mechatronic Sys. Lab. Yanshan University Qinhuangdao China

The paper presents a new approach on haptic interface control for NAO robotic hand. The haptic teleoperation of NAO robot hand raises some issues, mapping the haptic device dynamic being the most important. The mapping was achieved through Neural Network by determining a dynamic gain of robot haptic feedback. The results lead to the achievement of the haptic intelligent interfaces for the NAO robot hand control which can be integrated into an innovative haptic robot control system.

关键词： decision support systems Humanoid robots Haptic interfaces Economic indicators Joints Mechatronics

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