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IEEE International Symposium on Industrial Electronics

作者： Juan Zhao Jinhua She Dianhong Wang Edwardo F. Fukushima Min Wu Hiroshi Hashimoto School of Engineering Tokyo University of Technology Hachioji Tokyo Japan School of Automation China University of Geosciences Wuhan China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan China Master Program of Innovation for Design & Engineering Advanced Institute of Industrial Technology Tokyo Japan

The purpose of this study was to investigate the features of muscle fatigue extracted from surface electromyography (sEMG) signals of lower limbs, and then to present an evaluation method of lower-limb rehabilitation to provide physical basis for the training effect of rehabilitation. Four healthy young university students were invited to perform a pedaling exercise for 40 days. The sEMG signals of four lower-limb muscles are recorded and processed using a Butterworth filter and a Daubechies 10 wavelet. Then, the change of the ratios of the spectrums of Types I and II muscle fibers to the total number of the spectrum along the exercise are examined. The time of the first intersection of the ratios for Types I and II for each muscle is used as a performance index. The increase in the time at the beginning and the end of the training period indicates the improvement of motor function, and thus it verifies the effectiveness of the rehabilitation.

关键词： SEMG Muscle fatigue Rehabilitation evaluation Unequal length segmentation

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The Liver Tumor Segmentation Benchmark (LiTS)

arXiv

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arXiv 2019年

作者： Bilic, Patrick Christ, Patrick Li, Hongwei Bran Vorontsov, Eugene Ben-Cohen, Avi Kaissis, Georgios Szeskin, Adi Jacobs, Colin Mamani, Gabriel Efrain Humpire Chartrand, Gabriel Lohöfer, Fabian Holch, Julian Walter Sommer, Wieland Hofmann, Felix Hostettler, Alexandre Lev-Cohain, Naama Drozdzal, Michal Amitai, Michal Marianne Vivanti, Refael Sosna, Jacob Ezhov, Ivan Sekuboyina, Anjany Navarro, Fernando Kofler, Florian Paetzold, Johannes C. Shit, Suprosanna Hu, Xiaobin Lipková, Jana Rempfler, Markus Piraud, Marie Kirschke, Jan Wiestler, Benedikt Zhang, Zhiheng Hülsemeyer, Christian Beetz, Marcel Ettlinger, Florian Antonelli, Michela Bae, Woong Bellver, Míriam Bi, Lei Chen, Hao Chlebus, Grzegorz Dam, Erik B. Dou, Qi Fu, Chi-Wing Georgescu, Bogdan Giró-I-Nieto, Xavier Gruen, Felix Han, Xu Heng, Pheng-Ann Hesser, Jürgen Moltz, Jan Hendrik Igel, Christian Isensee, Fabian Jäger, Paul Jia, Fucang Kaluva, Krishna Chaitanya Khened, Mahendra Kim, Ildoo Kim, Jae-Hun Kim, Sungwoong Kohl, Simon Konopczynski, Tomasz Kori, Avinash Krishnamurthi, Ganapathy Li, Fan Li, Hongchao Li, Junbo Li, Xiaomeng Lowengrub, John Ma, Jun Maier-Hein, Klaus Maninis, Kevis-Kokitsi Meine, Hans Merhof, Dorit Pai, Akshay Perslev, Mathias Petersen, Jens Pont-Tuset, Jordi Qi, Jin Qi, Xiaojuan Rippel, Oliver Roth, Karsten Sarasua, Ignacio Schenk, Andrea Shen, Zengming Torres, Jordi Wachinger, Christian Wang, Chunliang Weninger, Leon Wu, Jianrong Xu, Daguang Yang, Xiaoping Yu, Simon Chun-Ho Yuan, Yading Yue, Miao Zhang, Liping Cardoso, Jorge Bakas, Spyridon Braren, Rickmer Heinemann, Volker Pal, Christopher Tang, An Kadoury, Samuel Soler, Luc van Ginneken, Bram Greenspan, Hayit Joskowicz, Leo Menze, Bjoern Department of Informatics Technical University of Munich Germany Department of Quantitative Biomedicine University of Zurich Switzerland Ecole Polytechnique de Montréal Canada Department of Medical Imaging Radboud University Medical Center Nijmegen Netherlands Department of Biomedical Engineering Tel-Aviv University Israel Germany Pattern Analysis and Learning Group Department of Radiation Oncology Heidelberg University Hospital Heidelberg Germany Philips Research China Philips China Innovation Campus Shanghai China School of Biomedical Engineering & Imaging Sciences King0s College London London United Kingdom Institute for AI in Medicine Technical University of Munich Germany Department of Computer Science Guangdong University of Foreign Studies China Institute for diagnostic and interventional radiology Klinikum rechts der Isar Technical University of Munich Germany Institute for Diagnostic and Interventional Neuroradiology Klinikum Rechts der Isar Technical University of Munich Germany Department of Hepatobiliary Surgery The Affiliated Drum Tower Hospital Nanjing University Medical School China Department of Computing Imperial College London London United Kingdom Institute for Tissue Engineering and Regenerative Medicine Helmholtz Zentrum München Neuherberg Germany Brigham and Women's Hospital Harvard Medical School United States School of Computer Science and Engineering The Hebrew University of Jerusalem Israel University of Pennsylvania PA United States Pte. Ltd. Singapore Medical Imaging and Reconstruction Lab Department of Engineering Design Indian Institute of Technology Madras India Sensetime Shanghai China Department of Radiology Perelman School of Medicine University of Pennsylvania United States Department of Pathology and Laboratory Medicine Perelman School of Medicine University of Pennsylvania PA United States Co. Ltd China MontréalQC Canada Department of Radiology Radiation Oncology and Nuclear Medicine University of Montréal

In this work, we report the set-up and results of the Liver Tumor Segmentation Benchmark (LiTS), which was organized in conjunction with the IEEE International Symposium on Biomedical Imaging (ISBI) 2017 and the International Conferences on Medical Image Computing and Computer-Assisted Intervention (MICCAI) 2017 and 2018. The image dataset is diverse and contains primary and secondary tumors with varied sizes and appearances with various lesion-to-background levels (hyper-/hypo-dense), created in collaboration with seven hospitals and research institutions. Seventy-five submitted liver and liver tumor segmentation algorithms were trained on a set of 131 computed tomography (CT) volumes and were tested on 70 unseen test images acquired from different patients. We found that not a single algorithm performed best for both liver and liver tumors in the three events. The best liver segmentation algorithm achieved a Dice score of 0.963, whereas, for tumor segmentation, the best algorithms achieved Dices scores of 0.674 (ISBI 2017), 0.702 (MICCAI 2017), and 0.739 (MICCAI 2018). Retrospectively, we performed additional analysis on liver tumor detection and revealed that not all top-performing segmentation algorithms worked well for tumor detection. The best liver tumor detection method achieved a lesion-wise recall of 0.458 (ISBI 2017), 0.515 (MICCAI 2017), and 0.554 (MICCAI 2018), indicating the need for further research. LiTS remains an active benchmark and resource for research, e.g., contributing the liver-related segmentation tasks in http://***/. In addition, both data and online evaluation are accessible via ***. © 2019, CC BY-NC-ND.

关键词： Deep learning

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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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A Combination of Second Level Adaptation and Switching Scheme for Uncertain Linear System

A Combination of Second Level Adaptation and Switching Schem...

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第三十三届中国控制会议

作者： Wei Chen Jie Chen Jian Sun Key Laboratory of Intelligent Control and Design of Complex Systems Beijing Institute of Technology

ISBN: (纸本)9781479947249

This paper deals with the stability issues of multiple model adaptive control(MMAC) with second level adaptation at first,which was proposed as a new concept of adaptive control using multiple *** basic structure of MMAC with second level adaptation is presented and the proof of stability for multiple fixed model set is *** a new approach about the combination of second level adaptation and switching is proposed for the systems where only a little prior information is *** stability of the proposed approach is given and a simulation is used to show the feasibility of the approach.

关键词： Second Level Adaptation,Stability,Switching

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control water level of a photovoltaic pumping system

Control water level of a photovoltaic pumping system

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2013 International Conference on control, Decision and Information Technologies, CoDIT 2013

作者： Khiareddine, Abla Salah, Chokri Ben Mimouni, Mohamed Faouzi ENIM Monastir Tunisia Research Unit on Intelligent Control Optimization Design and Optimization of Complex Systems ENIS Sfax Tunisia

ISBN: (纸本)9781424497966

The purpose of this paper is the regulation of water level in a photovoltaic pumping system. To reach this objective, we have developed an algorithm with Matlab / simulink which gives as result, the value of the reference speed required for vector control of induction motor taking into account the level of water in the tank and the variation of solar illumination. The string of photovoltaic pumping is simulated under matlab-Simulink. © 2013 IEEE.

关键词： Simulink

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Synchronization in complex networks and its application - A survey of recent advances and challenges

Synchronization in complex networks and its application - A ...

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作者： Tang, Yang Qian, Feng Gao, Huijun Kurths, Jürgen Potsdam Institute for Climate Impact Research Potsdam14473 Germany Institute of Physics Humboldt University of Berlin Berlin12489 Germany Key Laboratory of Advanced Control and Optimization for Chemical Processes Ministry of Education East China University of Science and Technology Shanghai200237 China Research Institute of Intelligent Control and Systems Harbin Institute of Technology Harbin150080 China Institute for Complex Systems and Mathematical Biology University of Aberdeen AberdeenAB24 3UE United Kingdom Department of Control Theory Nizhny Novgorod State University Gagarin Avenue 23 Nizhny Novgorod606950 Russia King Abdulaziz University Jeddah21589 Saudi Arabia

complex networks have, in recent years, brought many innovative impacts to large-scale systems. However, great challenges also come forth due to distinct complex situations and imperative requirements in human life nowadays. This paper attempts to present an overview of recent progress of synchronization of complex dynamical networks and its applications. We focus on robustness of synchronization, controllability and observability of complex networks and synchronization of multiplex networks. Then, we review several applications of synchronization in complex networks, especially in neuroscience and power grids. The present limitations are summarized and future trends are explored and tentatively highlighted. © 2014 Elsevier Ltd. All rights reserved.

关键词： Synchronization

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Improving mobile robot robustness in visual servoing application

Improving mobile robot robustness in visual servoing applica...

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IEEE SSD International Multi-Conference on systems, Signals and Devices

作者： Laroussi Hammouda Hassen Mekki Khaled Kaaniche Mohamed Chtourou Intelligent Control design and Optimization of complex Systems University of Sfax Tunisia National School of Engineering of Sousse University of Sousse Tunisia

ISBN: (纸本)9781467364591

This paper proposes a novel method to improve mobile robot robustness with respect to kinematic modeling errors during visual servoing task. Instead of using first-order error-dynamics, as it is usually done, we use the second-order error-dynamics leading to a new control law. The main aim of this approach is to guarantee a robust visual servoing scheme. In fact, the new control law ensures the convergence of the mobile robot to its desired pose even in the presence of modeling errors. Experimental results are presented to validate our approach and to demonstrate its efficiency.

关键词： Visual servoing Mobile robots Visualization Cameras Robot kinematics

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Path planning for 3D visual servoing: For a wheeled mobile robot

Path planning for 3D visual servoing: For a wheeled mobile r...

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International Conference on Individual and Collective Behaviors in Robotics (ICBR)

作者： Hassen Mekki Manel Letaief Intelligent Control design and Optimization of complex Systems University of Sfax Tunisia National School of Engineering of Sousse University of Sousse Tunisia

In this paper, we are interested in 3D visual servoïng path planning and path tracking. In fact, in the 3D visual servoïng task, there is no control in the image space and the object may get out of the camera field of view during servoing. To solve this problem, we have used a new approach based on a flatness concept. The 3D visual servoïng suffer from another major problem, is to determine the relative pose of the camera and the object. Generally, the pose estimation is made by correspondences between points of one image and points of the space that is the 2D-3D correspondence. In our work we have used a 3D visual sensor called Kinect. To show the efficiency of the proposed algorithm, we have implemented it on a wheeled Koala robot.

关键词： Visualization Cameras Robot vision systems Feature extraction Servomotors Mobile robots

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2D visual servoïng of wheeled mobile robot by neural networs

2D visual servoïng of wheeled mobile robot by neural networ...

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International Conference on Individual and Collective Behaviors in Robotics (ICBR)

作者： Rania Zouaoui Hassen Mekki National School of Engineering of Sousse University of Sousse Tunisia Intelligent Control design and Optimization of complex Systems University of Sfax Tunisia

We are interested in this paper in the 2D visual servoïng for a mobile robot type Koala using radial basis function (RBF) neural network (NN). Seen that the interaction matrix, expressing the relationship between the camera motion and the consequent changes on the visual features, contains parameters to be estimated (depth) and requires a calibration phase of the camera. In more, the model of the robot can contain uncertainties engendered the movement with sliding. An online identification, using NN was proposed to overcome these problems. The RBF NN is used to estimate the block formed by the interaction matrix and the model inverts of the robot. The considered images are described by objects given by four points. Seen that the variables number of the estimated function is important, what can cause a problem of the use of an excessive number of RBFs. As remedy, we used a new approach consists in considering that a single point is sufficient to solve the problem of the 2D visual servoïng of the mobile robot.

关键词： Visualization Artificial neural networks Cameras Robot vision systems Jacobian matrices Gold

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Method of model's parameters classification using neural network for meat characterization

Method of model's parameters classification using neural net...

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IEEE SSD International Multi-Conference on systems, Signals and Devices

作者： M. Guermazi O. Kanoun N. Derbel Chair for Measurement and Sensor Technology Chemnitz University of Technology Reichenhainer Straße 70 09126 Chemnitz GERMANY Intelligent Control design & Optimization of complex Systems (ICOS) University of Sfax Sfax Engineering School Sfax TUNISIA Universite de Sfax Sfax TN Intelligent Control design & Optimization of complex Systems (ICOS) University of Sfax Sfax Engineering School BP W 1173-3038 TUNISIA

ISBN: (纸本)9781467364591

The main objective of this work is to develop the classification application for a new promising method for meat characterization getting information about the state of the vacuum packed meat in supermarket. A supervised training using neural networks and according to the back error propagation method is used. The training ensure a classification with high precision and with ability to answer correctly the inputs then with ability to classify the erroneous inputs which do not exist in the data base, without creating new classes. Method classification consist to classify the model parameters of the physical model of the meat according to a data base including the model's parameters for different beef muscle in different days.

关键词： Biomedical measurement Biology Phase measurement Biomembranes Impedance

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