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IEEE International Conference on Multimedia and Expo (ICME)

作者： Cong Guo Xinmei Tian Tao Mei CAS Key Laboratory of Technology in Geo-spatial Information Processing and Application System University of Science and Technology of China Hefei Anhui China Microsoft Research Beijing China

Social networks nowadays have become an important form of communication in which users can post their current status or share their lives by mobile phones or the Web. In this paper, we develop an effective and efficient model to estimate continuous tie strength between users for friend recommendation with the heterogeneous data from social media community. We categorize those multimodal data into two classes: interaction data (e.g., comments, marking favorite photos) and similarity data(e.g., common friends, groups, tags, geo, visual). We propose to use asymmetric relationship in the interaction data for tie strength estimation instead of using the conventional symmetric ones. Furthermore, by exploring the behavior of users in a social media community, we find that the tie strength between users can be approximately modeled as a linear function of their social connections. Based on this observation, we propose an effective and highly efficient user specific linear model for the tie strength estimation. The experiments on a popular social network show promising results and demonstrate the effectiveness of our proposed method.

关键词： Kernel Social network services Visualization Communities Data models Estimation Vectors

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DEM reconstruction of mountainous area from two anti-parallel aspects of airborne InSAR data

DEM reconstruction of mountainous area from two anti-paralle...

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IEEE International Symposium on Geoscience and Remote Sensing (IGARSS)

作者： Fangfang Li Donghui Hu Jiayin Liu Xiaolan Qiu Chibiao Ding Institute of Electronics Chinese Academy of Sciences Beijing China Key Laboratory of Geo-Spatial Information Processing and Application System Technology Chinese Academy of Sciences Beijing China

The geometry distortion phenomenon of SAR imaging arises in the mountainous scenarios due to the presence of strong terrain slopes. Because of phase discontinuities or the absence of valid phase, for single pass interferometric SAR (InSAR), it is difficult to recover accurate digital elevation model (DEM) in such areas. Fusion of two or more different aspects of InSAR data is practicable to deal with this problem. In this paper, the processing procedures of airborne InSAR data are presented. In order to decrease the processing error of every single aspect data, an iterative motion compensation (MOCO) method is used. Besides, the interferometric phase of shadow area is linearly complemented before phase unwrapping to avoid error spreading. Experimental results using two anti-parallel aspects of airborne InSAR data validate the feasibility of fusion.

关键词： Geometry Motion compensation Iterative methods Surfaces Aerospace electronics Radar polarimetry

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Parallel Factorization Machine Recommended Algorithm Based on MapReduce

Parallel Factorization Machine Recommended Algorithm Based o...

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International Conference on Semantics, Knowledge and Grid (SKG)

作者： Hanxiao Sun Wenjie Wang Zhongzhi Shi School of Computer and Control Engineering University of Chinese Academy of Sciences Beijing China Key Laboratory of Intelligent Information Processing Chinese Academy of Sciences Beijing China

ISBN: (纸本)9781479967162

Factorization Machines [1, 2] is a new factorization model that can combine the merits of SVM model with matrix factorization models. It can model all the interactive actions using factorized parameters. So it could mimic most other matrix factorization models by feature engineering. Due to the superior flexible, Factorization Machines has already been widely used in many recommended algorithm competitions and practical online recommended system. But, because of the prevalence of large dataset, there is a need to improve the scalability of computation in factorization machines model. In this paper, we propose a parallel algorithm can be used on Factorization Machines model. The experimental results show that the proposed algorithm has good speed-up and scalability on big dataset.

关键词： Frequency modulation Computational modeling Data models Computers Parallel algorithms Stochastic processes Algorithm design and analysis

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Crawling Gait Planning for a Quadruped Robot with High Payload Walking on Irregular Terrain

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IFAC Proceedings Volumes 2014年第3期47卷 2153-2158页

作者： Nan Hu Shaoyuan Li Dan Huang Feng Gao Department of Automation Key Laboratory of System Control and Information Processing Ministry of Education Shanghai Jiao Tong University Shanghai 200240 China School of Aeronautics and Astronautics Shanghai Jiao Tong University Shanghai 200240 China School of Mechanical Engineering Shanghai Jiao Tong University Shanghai 200240 China

Walking on irregular terrain is usually a common task for a quadruped robot. It is however difficult to control the robot in this situation as undesirable impulse force by collision between the foot of robot and obstacles makes the robot unstable. This paper presents a hybrid Force-Posture Feedback Compensation (FPFC) controller for a quadruped robot with high payload walking on irregular terrain. In order to make the robot walk stably on irregular terrain, the proposed controller utilizes the feedback signals detected by force sensor and gyroscope to adjust every leg of the robot in real-time. The foot trajectory is scheduled based on the Bezier curve method in order to improve the stability of quadruped robot. Simulations of crawling gait on irregular terrain have been performed. The results have verified that the proposed methods have better stability and performance for walking on the irregular terrain.

关键词： Quadruped robot gait planning trajectory planning kinematics

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Boid-Inspired Harmony Search approach to aircraft parameter estimation

Boid-Inspired Harmony Search approach to aircraft parameter ...

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World Congress on Intelligent control and Automation (WCICA)

作者： Junnan Li Haibin Duan Science and Technology on Aircraft Control Laboratory Beihang University (BUAA) Beijing China Science and Technology on Aircraft Control Laboratory Beihang University (BUAA) Bejing China Provincial Key Laboratory for Information Processing Technology Soochow University Suzhou China

Aircraft parameter estimation is a vital technology in aeronautical industry. It is the fundamental of control law design and aircraft performance evaluation. Harmony Search (HS) is proposed in 2001, which mimics music players composing fantastic music. Its performance has been verified by many benchmark problems. In 1986, Reynolds proposed a mathematical model describing animals' group behavior, and he generally named the flocking creature “boids”, which can be interpreted as “bird like objects”. We modify the pitch adjustment step of HS inspired by the boid model. Our new method is named Boid-Inspired Harmony Search (BIHS). This paper investigates the application of BIHS to aircraft parameter estimation problem. In this work, the longitudinal state-space model of F-18 jet is used. It is shown that the BIHS approach is efficient, and in some ways, has an advantage over the classical Maximum Likelihood (ML) method.

关键词： Parameter estimation Mathematical model Vectors Aircraft Educational institutions Equations Pollution measurement

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Direct adaptive neural network control for wastewater treatment process

Direct adaptive neural network control for wastewater treatm...

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World Congress on Intelligent control and Automation (WCICA)

作者： Wei Zhang Jun-fei Qiao College of Electronic Information and Control Engineering Beijing University of Technology Beijing China Beijing Key Laboratory of Computational Intelligence and Intelligence System Beijing China

In this paper, a direct adaptive neural network control (DANNC) method is developed to deal with the multi-variable (dissolved oxygen concentration and nitrate concentration) tracking control problem in wastewater treatment processes (WWTPs), which avoids the perplex issue of establishing the plant model of WWTP and has the excellent adaptive ability. The DANNC system is composed of neural controller and compensation controller. The neural controller is employed to approximate an ideal control law, and the compensation controller is designed to offset the network approximation error. The controller parameters' adaptive laws are deduced by the Lyapunov theorem. Simulation results, based on the international benchmark simulation model No.1 (BSM1), show that the control accuracy and dynamic performance of the DANNC method are improved nicely.

关键词： Effluents Mathematical model Neural networks Biological system modeling Inductors Process control

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An input-output clustering approach for structure identification of T-S fuzzy neural networks

An input-output clustering approach for structure identifica...

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IEEE Symposium on Computational Intelligence in control and Automation, CICA

作者： Wei Li Honggui Han Junfei Qiao College of Electronic Information and Control Engineering Beijing University of Technology Beijing China Beijing Key Laboratory of Computational Intelligence and Intelligence System Beijing China

ISBN: (纸本)9781479945290

This paper proposes a novel input-output clustering approach for structure identification of T-S fuzzy neural networks. This approach consists of two phases. Firstly, k-means clustering method is applied to the input data to provide the initial clusters of the input space. Secondly, check whether the sub-clustering is needed for each input cluster by considering the corresponding output variation and then apply the k-means method to further partition those input clusters needed sub-clustering. Applying the above process recursively leads to the structure identification of a T-S fuzzy neural network and then the parameter identification is completed by using the gradient learning algorithm. The experiments by applying the proposed method to several benchmark problems show better performance compared with many existing methods and then verify the effectiveness and usefulness of the proposed method.

关键词： Clustering methods Fuzzy neural networks Accuracy Clustering algorithms Context Fuzzy control Partitioning algorithms

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A Combined Approach for Master-slave Robotic Surgery system control Based on Jacobian and PD Algorithm

A Combined Approach for Master-slave Robotic Surgery System ...

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2014 4th IEEE International Conference on information Science and Technology

作者： Zhonglin Zhang Jing Xiong Yangzhou Gan Dongwen Zhang Zeyang Xia Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences School of Electronic Engineering and Automation Guilin University of Electronic Technology Department of Automation Shanghai Jiao Tong University and Key Laboratory of System Control and Information ProcessingMinistry of Education of China

In this paper, a semi-physical simulation platform of robot teleoperation system is designed, and a combined control approach using Jacobian matrix and Proportional-Derivative(PD) algorithm is proposed. A digital low-pass filter is designed to eliminate noise signal caused by hand-vibration of surgeons. The advantages of the proposed approach include easy implementation, real-time response and accurate master-slave tracking. The results of semi-physical simulation validated that the proposed approach realized accurate master-slave tracking for puncture surgery and the noise caused by hand-vibration was eliminated effectively.

关键词： robotic puncture surgery teleoperation Jacobian matrix PD control algorithm vibration elimination

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Optimal Dynamic Sensing Policy for Cognitive Radio Network:A POMDP model Based Method

Optimal Dynamic Sensing Policy for Cognitive Radio Network:A...

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第三十二届中国控制会议

作者： LI Li'an CHEN Cailian LIN Feilong GUAN Xinping Department of Automation Shanghai Jiao Tong Universityand Key Laboratory of System Control and Information ProcessingMinistry of Education of China

ISBN: (纸本)9781479900305

In the cognitive radio(CR) network,the secondary user(SU) are allowed to utilize the frequency channels of the licensees primary user(PU) when these channels are not currently being *** support spectrum reuse functionality,the SU are required to sense the channel to detect the PU activity accurately for each time *** are two parameters associated with spectrum sensing:probability of detection and probability of false *** the probability of detection,the long sensing time reduce the false alarm probability,however the left time used for transmission is *** is a trade off between the sensing cost and successful transmission *** we combined the PU activity property with the discounted utility of the SU,how to improve the SU utility under the unreliable spectrum sensing situation is still a challenge problem and rarely be *** this paper we propose a new optimal dynamic sensing policy,called sleep-sensing-transmission strategy based on partially observable Markov Decision Process(POMDP).At the beginning of each slot,the SU can choose three different possible actions:Sleep,spectrum sensing and then access the channel based on the sensing result or directly transmission to maximize the expected discounted utility in the long *** this model we have shown that the optimal strategy has a simple threshold structure,and the simulation result validate the efficiency of our policy compared with the traditional spectrum sensing and access mechanism.

关键词： Cognitive Radio network Spectrum sensing POMDP Threshold policy

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Distributed sequential estimation algorithm for steel temperature in hot strip mill

Distributed sequential estimation algorithm for steel temper...

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第三十二届中国控制会议

作者： LI Wenshuang CHEN Cailian ZHU Shanying Li Li'an GUAN Xinping Department of Automation Shanghai Jiao Tong University and Key Laboratory of System Control and Information Processing Ministry of Education of China

ISBN: (纸本)9781479900305

This paper is concerned with the steel temperature estimation problem in hot strip mill. We focus on the steel bar temperature estimation during the rough rolling process with the aid of industrial wireless network for its high reliability communication and low power consumptions. However, the mobility of the steel bar and the complexity of the industrial environments have posed new challenges for the temperature monitoring. According to the steel bar's mobility, we propose a distributed sequential estimation algorithm to realize the continuous temperature tracking and gradually remove the estimation error. It consists of a cluster-based estimation algorithm and an initialized fusion algorithm, whose design are based on two criteria, namely, unbiasedness and optimality. Finally, simulation studies are presented to validate the performance of the proposed algorithm.

关键词： Distributed sequential estimation, steel bar, temperature monitoring

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