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Communications in Computer and information Science 2014年 461卷 307-318页

作者： Liu, L. Wang, Jingchuan Chen, Weidong Department of Automation Shanghai Jiao Tong University and Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai200240 China

ISBN: (纸本)9783662452820

Driver training systemfor disable and elderly people to use electric wheelchairs has an important role for their independent mobility. In this paper a simulator platform of smart wheelchairs is presented for driver training and evaluation. Based on the smart wheelchair, integrated with kinematics, dynamics, sensors, and the 3D model of real wheelchairs and environment, it is implemented in Gazebo and ROS. The sensors inlcude an encoder, a laser range finder and a set of Kinect. Without nursing staff’s company, the user could complete driver training and assessment procedures by himself. Experiments verify that this platform can be used as a valid tool for driver training and evaluation. © Springer-Verlag Berlin Heidelberg 2014.

关键词： Wheelchairs

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Saturated Output-Based Event-Triggered control for Consensus of Multi-Agent systems

Saturated Output-Based Event-Triggered Control for Consensus...

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第27届中国控制与决策会议

作者： Xiongjun Wu Kun Cai Department of Automation Shanghai Jiao Tong Universityand Key Laboratory of System Control and Information ProcessingMinistry of Education of China Science and Technology on Electromagnetic Scattering Laboratory The Eighth Academy of China Aerospace Science and Technology Corporation

A saturation allowed output-based event-triggered control for consensus of multi-agent systems(MAS for short) design method is proposed in this paper for the linear systems subject to input *** introduced the saturation allowed controller design method into the multi-agent schemes,in which an event-triggered mechanism are *** multi-agent controllers are not activated until the response of the system exceeds some pre-defined eventtriggered limitation,rather than periodically sampling as ***,the output feedback scheme is introduced into the event-triggered MAS *** this case,the output feedback of the plant is activated when it really need to,and then the saturation allowed method is then employed to deal with the saturation *** this proposed scheme,since the saturation is allowed and no hard constraint is needed to imposed on the controller input,we can makes fuller utilization of the available actuator *** proposed saturated output-based event-triggered control scheme provides the system stability and guaranteed event-triggered condition for consensus of multi-agent ***,results are provided for minimizing the frequency of the event-triggered actions.

关键词： Actuator saturation,event-triggered control,multi-agent systems.

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A new automatic mass detection method for breast cancer with false positive reduction

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Neurocomputing 2015年 152卷 388-402页

作者： Xiaoming Liu Zhigang Zeng School of Automation Huazhong University of Science and Technology Wuhan 430074 China Key Laboratory of Image Processing and Intelligent Control of Education Ministry of China Wuhan 430074 China College of Computer Science and Technology Wuhan University of Science and Technology Wuhan 430081 China Hubei Province Key Laboratory of Intelligent Information Processing and Real-time Industrial System Wuhan 430081 China

Mass localization is a crucial problem in computer-aided detection (CAD) system for the diagnosis of suspicious regions in mammograms. In this paper, a new automatic mass detection method for breast cancer in mammographic images is proposed. Firstly, suspicious regions are located with an adaptive region growing method, named multiple concentric layers (MCL) approach. Prior knowledge is utilized by tuning parameters with training data set during the MCL step. Then, the initial regions are further refined with narrow band based active contour (NBAC), which can improve the segmentation accuracy of masses. Texture features and geometry features are extracted from the regions of interest (ROI) containing the segmented suspicious regions and the boundaries of the segmentation. The texture features are computed from gray level co-occurrence matrix (GLCM) and completed local binary pattern (CLBP). Finally, the ROIs are classified by means of support vector machine (SVM), with supervision provided by the radiologist׳s diagnosis. To deal with the imbalance problem regarding the number of non-masses and masses, supersampling and downsampling are incorporated. The method was evaluated on a dataset with 429 craniocaudal (CC) view images, containing 504 masses. Among them, 219 images containing 260 masses are used to optimize the parameters during MCL step, and are used to train SVM. The remaining 210 images (with 244 masses) are used to test the performance. Masses are detected with 82.4% sensitivity with 5.3 false positives per image (FPsI) with MCL, and after active contour refinement, feature analysis and classification, it obtained 1.48 FPsI at the sensitivity 78.2%. Testing on 164 normal mammographic images showed 5.18 FPsI with MCL and 1.51 FPsI after classification. Experiments on mediolateral oblique (MLO) images have also been performed, the proposed method achieved a sensitivity 75.6% at 1.38 FPsI. The method is also analyzed with free response operating characteristi

关键词： Mass detection Breast cancer Level set Local binary pattern Support vector machine

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A Bayesian adaptive weighted total generalized variation model for image restoration

A Bayesian adaptive weighted total generalized variation mod...

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IEEE International Conference on Image processing

作者： Zhenbo Lu Houqiang Li Weiping Li CAS Key Laboratory of Technology in Geo-spatial Information Processing and Application System University of Science and Technology of China Heifei Anhui China

In recent years, the Total Generalized Variation (TGV) model has received lots of attention in image processing community. Though this model can restore image with natural intensity transitions, its spatial identical parameter setting limits its performance. In this paper, we propose a novel Adaptive Weighted Total Generalized Variation model for image restoration. We analyze the TGV model from Bayesian Probability view and derive a novel adaptive parameter calculation scheme for it, exploiting the image's self-similarity. Experiment results on image deblurring and reconstruction show that by adapting the parameters in TGV model to image contents, the proposed model can restore image's edges and details well and achieve significant improvement over state of the art variational based models.

关键词： Adaptation models Image restoration Mathematical model Approximation methods Bayes methods TV Minimization

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Cause analysis for the blurring phenomenon of shadow edges in terms of SAR imaging algorithms

Cause analysis for the blurring phenomenon of shadow edges i...

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Asian and Pacific Conference on Synthetic Aperture Radar (APSAR)

作者： Qi Liu Yueting Zhang Xiaolan Qiu Wenlong Hu University of Chinese Academy of Sciences Beijing China Key Laboratory of Spatial Information Processing and Application System Technology IECAS Beijing China

ISBN: (纸本)9781467372985

The shadow is a particular phenomenon in SAR images, inflecting some information of the target. However, the shadow edges are blurred in SAR images. Thus, we analyze the causes for the blurring phenomenon of shadow edges in terms of SAR imaging algorithms in this paper. Taking the range Doppler algorithm for example, we conduct four simulation experiments to compensate for different processing steps and compare the imaging discrepancy among the refocused shadow edges. The conclusions are that the blurring phenomenon of shadow edges in SAR images is mainly reflected in azimuth, and azimuth compression is the major impact-factor to the shadow imaging quality. It is obvious that optimization of azimuth compression should get more attention for shadow enhancement in SAR images.

关键词： Synthetic aperture radar Azimuth Imaging Image edge detection Radar imaging Image resolution Radar polarimetry

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Metallographic image segmentation based on ridge detection and region-merger

Metallographic image segmentation based on ridge detection a...

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2015 3rd International Conference on Soft Computing in information Communication Technology(SCICT 2015)

作者： Yan Chen Jianxun Chen School of Computer Science and Technology Wuhan University of Science and Technology Key Laboratory of Intelligent Information Processing and Real-time Industrial System

Watershed algorithm was widely applied to have a better recognition and segmentation for the grains in metallographic image,due to its fuzziness,discontinuity and incompleteness around the boundary of metallographic *** this paper,in order to solve the defect of traditional watershed algorithm,metallographic image segmentation based on ridge detection and region-merger was *** the method of ridge region growing reconstructed the discontinuous ridge,making the most pseudo-blobs being marked in this ***,a method of similar adjacent region merging was proposed which could merge the pseudo-blobs,increasing merging *** experiments demonstrate that the proposed algorithm was able to solve over-segmentation and under-segmentation to the greatest extent,which could greatly increase the accuracy of segmentation of metallographic image.

关键词： Metallographic image segmentation based on ridge detection and region-merger image

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A Travel Time Prediction Method for Urban Road Traffic Sensors Data

A Travel Time Prediction Method for Urban Road Traffic Senso...

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International Conference on Identification, information and Knowledge in the Internet of Things (IIKI)

作者： Guangyu Zhu Kang Song Peng Zhang Ministry of Education Key Laboratory of System Control and Information Processing Shanghai China MOE Key Laboratory for Transportation Complex Systems- Theory and Technology Beijing Jiaotong University Beijing China Beijing Municipality Key Laboratory of Urban Traffic Operation Simulation and Decision Support Beijing China

Travel time parameters obtained from road traffic sensors data play an important role in traffic management practice. In this paper, a travel time analysis and prediction model was established for urban road traffic sensors data based on the change point analysis algorithm and ARIMA model. Firstly, time series of travel time parameters were clustered by using change point mining algorithm after traffic sensors data preprocessing. Then, a travel time prediction model was established based on ARIMA model. Finally, the model was verified with high accuracy through simulation by using multiple sets of data and analysis of its practicability was done.

关键词： Predictive models Data models Roads Time series analysis Detectors Analytical models

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Intelligent Setting control Method Based on CBR and iterative learning for Laminar Cooling Process

Intelligent Setting Control Method Based on CBR and iterativ...

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第26届中国过程控制会议（CPCC2015）

作者： Pian Jinxiang Zhu Yunlong Liu Jinxin Chai Tianyou Qi Aiwei School of Information and Control engineering Shenyang Jianzhu University Key Laboratory of Networked Control System Chinese Academy of Sciences State Key Laboratory of Integrated Automation for Process Industry Northeastern University

The hot rolled strip laminar cooling system is a complex industrial process, associated with features of strong nonlinear and changing operating conditions. So, the process is hard to control with traditional close loop control methods. But fortunately, there is the repeated characteristic in the laminar cooling process, which is very suited to apply the iterative learning between the strips. So, PI iterative learning method is proposed in this paper to learn the inner knowledge between the strips with similar working condition. On the other hand, in order to improve the control effect,CBR(case-based reasoning) technology is applied to adjust the parameters P and I according to the changing working conditions. The experiments are conducted with industrial operating data. The results show that, with the proposed method, it is effective to find the right operating point quickly and the strip coiling temperature can be controlled in the suitable range.

关键词： laminar cooling iterative learning CBR(case based reasoning) strip coiling temperature

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Corrigendum to "Efficient detection of internal infestation in wheat based on biophotonics" [J. Photochem. Photobiol., B 155 (February 2016) 137-143]

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Journal of photochemistry and photobiology. B, Biology 2016年 160卷 408页

作者： Weiya Shi Keke Jiao Yitao Liang Feng Wang College of Information Science and Engineering Henan University of Technology Zhengzhou 450001 China Grain Information Processing and Control Key Laboratory of Ministry of Education Henan University of Technology Zhengzhou 450001 China. Electronic address: wyshi@***. College of Information Science and Engineering Henan University of Technology Zhengzhou 450001 China. Grain Information Processing and Control Key Laboratory of Ministry of Education Henan University of Technology Zhengzhou 450001 China.

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A new logistic map based chaotic biogeography-based optimization approach for cluster analysis

A new logistic map based chaotic biogeography-based optimiza...

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IEEE International Conference on Progress in Informatics and Computing (PIC)

作者： Shui-Hua Wang Hui-Min Lu Yu-Jie Li Yang Wang Zhi-Min Chen Yu-Min Wei Wen-Juan Jia Fang-Yuan Liu Yu-Dong Zhang Hunan Provincial Key Laboratory of Network Investigational Technology Hunan Policy Academy Changsha Hunan China School of Computer Science and Technology Nanjing Normal University Nanjing Jiangsu China Department of Electrical Engineering CUNY New York NY USA Department of Mechanical and Control Engineering Kyushu Institute of Technology Fukuoka Prefecture Japan School of Information Engineering Yangzhou University Yangzhou Jiangsu China School of Physics and Electronic Engineering Taizhou University Taizhou Zhejiang China School of Electronic Information Shanghai Dianji University Shanghai China School of Energy and Mechanical Engineering Nanjing Normal University Nanjing Jiangsu China Key Laboratory of Intelligent Computing and Information Processing in Fujian Provincial University Quanzhou Normal University Quanzhou Fujian China

ISBN: (纸本)9781509034857

Cluster analysis is important in scientific and industrial fields. In this study, we proposed a novel chaotic biogeography-based optimization (CBBO) method, and applied it in centroid-based clustering methods. The results over three types of simulation data showed that this proposed CBBO method gave better performance than chaotic particle swarm optimization, genetic algorithm, firefly algorithm, and quantum-behaved particle swarm optimization. In all, our CBBO method is effective in centroid-based clustering.

关键词： Genetic algorithms Optimization Clustering algorithms Particle swarm optimization Algorithm design and analysis Logistics Mathematical model

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