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World Congress on Intelligent control and Automation

作者： Yifei Zhao Jing Wang Fei-Yue Wang Xiaobo Shi Yisheng Lv State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Institute of Smart Healthcare System Qingdao Academy of Intelligent Industries

ISBN: (纸本)9781467384155

Internet inquiry is playing an increasingly important role as the complement of the traditional medical service system, especially the similar cases recommendation. It can not only save the patients' waiting time, but also make use of the historical resources, for many cases with the same purpose have been solved perfectly. However, because of the diversity and non-standard of the patients' descriptions, the inquiry platform cannot find the cases with similar semantic easily. Most traditional retrieval methods require the overlap of two sentences, and this is not suitable with the diversity and non-standard descriptions. In this paper, we try to utilize the sentences' semantic representation in a continuous space to understand the cases, and then recommend the similar cases. We also incorporate it into query likelihood language models, trying to get better results. Our experimental data are all collected from a real internet inquiry platform, and the results show that our methods significantly outperform the state-of-the-art translation based methods for similar cases recommendation.

关键词： Semantics Internet Medical services Context MONOS devices Optimization Information retrieval

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Teleoperation control of Baxter Robot based on Human Motion Capture

Teleoperation Control of Baxter Robot based on Human Motion ...

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IEEE International Conference on Information and Automation

作者： Guangzhu Peng Chenguang Yang Yiming Jiang Long Cheng Peidong Liang Key Lab of Autonomous Systems and Networked Control Ministry of Education South China University of Technology Guangzhou China State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences China State Key Laboratory of Robotics and System Harbin Institute of Technology China

ISBN: (纸本)9781509041039

The traditional 3D human motion capture methods require operators to wear tracking sensors on their body. However, these devices would bring operators much inconvenience. Currently, vision based motion capture systems provide us an alternative approach for motion capture technology. In this paper, based on human kinematics and function approximation technique (FAT), a novel method is presented for the trajectory control of Baxter robot. Each arm of the Baxter robot has seven degrees of freedom. The geometry vector approach is applied to capture human motion trajectory by using Microsoft Kinect sensor. A FAT control system is employed to make the robot follow the trajectory of human motion. The UDP communication protocol is employed to send the reference human joint angle data to the robot. We carry out preliminary experiments on Baxter robot to verify the validity of the control approach and the results demonstrate that the method has achieved satisfactory performance.

关键词： Teleoperation control Baxter Robot Human Motion Capture

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Exploring Optimal Frequency Caps in Real Time Bidding Advertising

Exploring Optimal Frequency Caps in Real Time Bidding Advert...

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IEEE International Conference on Big Data and Cloud Computing (BdCloud)

作者： Rui Qin Yong Yuan Fei-Yue Wang Beijing Engineering Research Center of Intelligent Systems and Technology Beijing China The State Key Laboratory of Management and Control for Complex Systems Chinese Academy of Sciences Beijing China Research Center of Military Computational Experiments and Parallel System National University of Defense Technology Changsha China

ISBN: (纸本)9781509039371

Benefited from the high-speed development of Internet and the popularization of big data technology, Real Time Bidding (RTB) emerged and developed quickly, and has become one of the most important and popular model for online computational advertising. In the pay-per-impression based RTB advertising, frequency capping is undoubtedly one of the most crucial issues faced by advertisers and Demand Side Platforms (DSPs), since there are generally vast amount of ad requests in RTB markets, among which many may be triggered by the same target audience. As such, choosing the optimal frequency cap considering all the advertisers becomes a critical issue faced by DSPs. Considering that displaying one advertisement multiple number of times to the same user will diminish the advertising effect, we introduce the concept of discount factor and establish an optimization model of frequency capping to seek for the optimal frequency cap for each advertiser. We also design some experiments to validate our proposed model by utilizing the computational experiment approach, and the experimental results show that the optimal frequency cap can be influenced by the values of the discount factors, and higher value of the discount factor can deduce the advertising effect of larger frequency cap. Moreover, when the discount factors of the advertisers take different values, there also exists an optimal frequency cap, at which the advertisers can get the expected maximum revenue in the long run.

关键词： Advertising Digital signal processing Computational modeling Big data Time-frequency analysis Radio spectrum management Real-time systems

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Optimizing Market Segmentation Granularity in RTB Advertising: A Computational Experimental Study

Optimizing Market Segmentation Granularity in RTB Advertisin...

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IEEE International Conference on Big Data and Cloud Computing (BdCloud)

ISBN: (纸本)9781509039371

Real Time Bidding (RTB) is a novel business model of online computational advertising with the integration of Internet economy and big data analysis. It can help advertisers achieve the precision marketing through the market segmentation strategies of Demand Side Platforms (DSPs). Based on a mathematical programming approach, this paper studied DSPs' strategies for market segmentation, and established a selection model of the granularity for segmenting RTB advertising markets. We proposed to validate our model using the computational experiment approach, and the experimental results show that: 1) with the increasing refinement of the market segmentation granularity, the total revenue has a tendency of a rise first followed by a decline, 2) the optimal granularity of market segmentation will be significantly influenced by the number of advertisers on the DSP, but less influenced by the number of ad requests. Our findings show the crucial role of market segmentation on the RTB advertising effect, and indicate that the DSPs should adjust their market segmentation strategies according to their total number of advertisers. Our findings also highlight the importance of advertisers as well as the characteristics of the target audiences in DSPs' market segmentation decisions.

关键词： Digital signal processing Computational modeling Advertising Numerical models Big data complex systems Automation

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Paragraph Vector Based Retrieval Model for Similar Cases Recommendation

Paragraph Vector Based Retrieval Model for Similar Cases Rec...

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第六届全国语言动力系统研讨会

作者： Yifei Zhao Jing Wang Fei-Yue Wang Xiaobo Shi The State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chine Institute of Smart Healthcare System Qingdao Academy of Intelligent Industries Qingdao China

Internet inquiry is playing an increasingly important role as the complement of the traditional medical service system,especially the similar cases *** can not only save the patients' waiting time,but also make use of the historical resources,for many cases with the same purpose have been solved ***,because of the diversity and non-standard of the patients' descriptions,the inquiry platform cannot find the cases with similar semantic *** traditional retrieval methods require the overlap of two sentences,and this is not suitable with the diversity and non-standard *** this paper,we try to utilize the sentences' semantic representation in a continuous space to understand the cases,and then recommend the similar *** also incorporate it into query likelihood language models,trying to get better *** experimental data are all collected from a real internet inquiry platform,and the results show that our methods significantly outperform the state-of-the-art translation based methods for similar cases recommendation.

关键词： internet inquiry similar cases recommendation distributed representation data mining

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Shared control for teleoperation enhanced by autonomous obstacle avoidance of robot manipulator

Shared control for teleoperation enhanced by autonomous obst...

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IEEE/RSJ International Conference on Intelligent Robots and systems

作者： Xinyu Wang Chenguang Yang Hongbin Ma Long Cheng Centre for Robotics and Neural Systems Plymouth University Plymouth UK State Key Lab of Intelligent Control and Decision of Complex System Beijing Institute of Technology Beijing China Ministry of Education South China University of Technology Guangzhou China State Key Laboratory of Management and Control for Complex Systems Chinese Academy of Sciences Beijing China

In this paper, a human robot shared control strategy is developed and tested on a Baxter robot. Using the proposed method, the human operator only needs to consider the motion of the end-effector of the manipulator, while the manipulator will avoid obstacle by itself without sacrificing the end effector motion performance. An improved obstacle avoidance strategy based on the joint space redundancy of the manipulator is designed. A dimension reduction method is presented to solve the over defined problem of avoiding velocity to achieve a more efficient use of the redundancy. By employment of an artificial parallel system of the teleoperate manipulator and the task switching weighting factor, the proposed control method enable the robot restoring back to the commanded pose smoothly when the obstacle is removed. By implementing the dimension reduction method, the trajectory of each joint of the manipulator can be controlled at the same time to achieve the restoring task. Thus, the proposed control method can eliminate the impact of the obstacle on the remaining task. Satisfactory experiment results demonstrate the effectiveness of the proposed methods.

关键词： Manipulators Collision avoidance Robot kinematics Trajectory Kinematics Robot sensing systems

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Large scale online kernel learning

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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 scalable 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 scalable. 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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Linguistic dynamic analysis for single lane's traffic status based on FCM

Linguistic dynamic analysis for single lane's traffic status...

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2014 International Conference on Informative and Cybernetics for Computational Social systems, ICCSS 2014

作者： Jie, Wang Hong, Mo Fenghua, Zhu College of Electrical AndInformation Engineering Changsha University of Science and Technology Changsha China State Key Laboratory of Management and Control for Complex System Beijing China

ISBN: (纸本)9781479947522

The results of traditional traffic status analysis are mostly single values, whose accuracy can't be determined;fuzzy c-means clustering (FCM) algorithm based on fuzzy theory can calculate the clustering center of plenty data quickly and easily;linguistic dynamic systems could describe the dynamic rules of complex systems in the language level. In this paper, membership functions are decided by FCM;result of a specific time period taken as one example is obtained;it's discussed that linguistic dynamic analysis of traffic status in different period within a day by the same method. © 2014 IEEE.

关键词： Linguistics

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Linguistic Dynamic Analysis for Single Lane's Traffic Status Based on FCM

Linguistic Dynamic Analysis for Single Lane's Traffic Status...

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2014 International Conference on Informative and Cybernetics for Computational Social systems(ICCSS2014)

作者： Wang Jie Mo Hong Zhu Fenghua College of Electrical &Information Engineering Changsha University of Science &Technology State Key Laboratory of Management and Control for Complex System

The results of traditional traffic status analysis are mostly single values,whose accuracy can’t be determined;fuzzy c-means clustering(FCM)algorithm based on fuzzy theory can calculate the clustering center of plenty data quickly and easily;linguistic dynamic systems could describe the dynamic rules of complex systems in the language *** this paper,membership functions are decided by FCM;result of a specific time period taken as one example is obtained;it’s discussed that linguistic dynamic analysis of traffic status in different period within a day by the same method.

关键词： fuzzy c-means clustering algorithm linguistic dynamic systems traffic flow

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Improving guide-based vulnerability detection with hybrid symbolic execution

Improving guide-based vulnerability detection with hybrid sy...

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International Conference on systems and Informatics (ICSAI)

作者： Yongji Ouyang Shuai Zeng Chao Yang Qingxian Wang State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou China State Key Laboratory of Management and Control for Complex System Institute of Automation Chinese Academy of Sciences Beijing China

ISBN: (纸本)9781479954599

Symbolic Execution is a key and useful technology in current refinement software test, but there still exists some problems such as space explosion. In order to mitigate this problem and improve the ability for detecting vulnerabilities, this paper presents the improving guide-based vulnerability detection with hybrid symbolic execution, which aims to test suspicious objects. This method conducts path traversal with a hybrid symbolic execution model, which alternates between dynamic and static symbolic execution, and verify whether it is vulnerability through summarizing the characteristics of vulnerabilities and generating a constraint expression. Experimental result shows that this method can successfully detect errors in 56 seconds, which exceeds any other modern mainstream symbolic execution tools including CUTE, KLEE, S2E and Cloud9. Compared with CUTE, this method alleviates the problem of space explosion. Besides, this papaer successfully verifies the vulnerabilities of OpenSSL and some other commonly used software.

关键词： Testing Algorithm design and analysis Software Explosions Refining Context Hybrid power systems

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