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arXiv 2017年

作者： Turan, Mehmet Almalioglu, Yasin Araujo, Helder Konukoglu, Ender Sitti, Metin Physical Intelligence Department Max Planck Institute for Intelligent Systems Germany Computer Engineering Department Bogazici Univesity Turkey Institute for Systems and Robotics Universidade de Coimbra Portugal Computer Vision Laboratory Department of Information Technology and Electrical Engineering ETH Zurich Switzerland

Ingestible wireless capsule endoscopy is an emerging minimally invasive diagnostic technology for inspection of the GI tract and diagnosis of a wide range of diseases and pathologies. Medical device companies and many research groups have recently made substantial progresses in converting passive capsule endoscopes to active capsule robots, enabling more accurate, precise, and intuitive detection of the location and size of the diseased areas. Since a reliable real time pose estimation functionality is crucial for actively controlled endoscopic capsule robots, in this study, we propose a monocular visual odometry (VO) method for endoscopic capsule robot operations. Our method lies on the application of the deep Recurrent Convolutional Neural Networks (RCNNs) for the visual odometry task, where Convolutional Neural Networks (CNNs) and Recurrent Neural Networks (RNNs) are used for the feature extraction and inference of dynamics across the frames, respectively. Detailed analyses and evaluations made on a real pig stomach dataset proves that our system achieves high translational and rotational accuracies for different types of endoscopic capsule robot trajectories. Copyright © 2017, The Authors. All rights reserved.

关键词： Vision

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Frequency aware robust economic dispatch

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Journal of Modern Power systems and Clean Energy 2016年第2期4卷 200-210页

作者： Donglei SUN Xueshan HAN Bo ZHANG Mingqiang WANG Tianyu DING Key Laboratory of Power System Intelligent Dispatch and Control of Ministry of Education Shandong UniversityJinan 250061China Department of Electrical and Computer Engineering University of AlbertaEdmontonAB T6G 2G7Canada

This paper proposes a novel frequency aware robust economic dispatch (FARED) approach to exploit the synergistic capability of accommodating uncertain loads and renewable generation by accounting for both the frequency regulation effect and optimal participation mechanism of secondary regulation reserves for conventional units in response to uncertainties in the robust optimization counterpart of security constrained economic *** FARED is formulated as a robust optimization *** this formulation the allowable frequency deviation and the possible load or renewable generation curtailments are expressed in terms of variable uncertainty *** variables in the formulation are described as interval variables and treated in affine *** order to improve the computational tractability,the dominant constraints which canbe the candidates of tight transmission constraints are determined by complementarity *** the robust optimization problem is simplified to a bilinear programming problem based on duality ***,the effectiveness and efficiency of the proposed method are illustrated based on several study cases.

关键词： Economic dispatch Frequency regulation effect Interval uncertainty Robust optimization Affine policy Complementarity constraints

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Self adaptation of chimera states

arXiv

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arXiv 2018年

作者： Yao, Nan Huang, Zi-Gang Ren, Hai-Peng Grebogi, Celso Lai, Ying-Cheng Department of Applied Physics Xi’an University of Technology Xi’an710048 China School of Life Science and Technology Xi’an Jiao Tong University Xi’an710049 China Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Xi’an University of Technology Xi’an710048 China Institute for Complex Systems and Mathematical Biology King’s College University of Aberdeen AberdeenAB24 3UE United Kingdom School of Electrical Computer and Energy Engineering Arizona State University TempeAZ85287 United States Department of Physics Arizona State University TempeAZ85287 United States

Chimera states in spatiotemporal dynamical systems have been investigated in physical, chemical, and biological systems, and have been shown to be robust against random perturbations. How do chimera states achieve their robustness? We uncover a self-adaptation behavior by which, upon a spatially localized perturbation, the coherent component of the chimera state spontaneously drifts to an optimal location as far away from the perturbation as possible, exposing only its incoherent component to the perturbation to minimize the disturbance. A systematic numerical analysis of the evolution of the spatiotemporal pattern of the chimera state towards the optimal stable state reveals an exponential relaxation process independent of the spatial location of the perturbation, implying that its effects can be modeled as restoring and damping forces in a mechanical system and enabling the articulation of a phenomenological model. Not only is the model able to reproduce the numerical results, it can also predict the trajectory of drifting. Our finding is striking as it reveals that, inherently, chimera states possess a kind of "intelligence" in achieving robustness through self adaptation. The behavior can be exploited for controlled generation of chimera states with their coherent component placed in any desired spatial region of the system. Copyright © 2018, The Authors. All rights reserved.

关键词： Dynamical systems

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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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Robust Multi-Exposure Image Fusion: A Structural Patch Decomposition Approach

Robust Multi-Exposure Image Fusion: A Structural Patch Decom...

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作者： Ma, Kede Li, Hui Yong, Hongwei Wang, Zhou Meng, Deyu Zhang, Lei Department of Electrical and Computer Engineering University of Waterloo WaterlooONN2L 3G1 Canada Department of Computing Hong Kong Polytechnic University Hong Kong Hong Kong Department of Computing. Hong Kong Polytechnic University Hong Kong Hong Kong Institute for Information and System Sciences and Ministry of Education Key Laboratory of Intelligent Networks and Network Security Xi'an Jiaotong University Xi'an710049 China Inst. for Info. and Syst. Sci. and Min. of Educ. Key Lab. of Intelligent Networks and Netwk. Secty. Xi'an Jiaotong University Xi'an710049 China

We propose a simple yet effective structural patch decomposition approach for multi-exposure image fusion (MEF) that is robust to ghosting effect. We decompose an image patch into three conceptually independent components: signal strength, signal structure, and mean intensity. Upon fusing these three components separately, we reconstruct a desired patch and place it back into the fused image. This novel patch decomposition approach benefits MEF in many aspects. First, as opposed to most pixel-wise MEF methods, the proposed algorithm does not require post-processing steps to improve visual quality or to reduce spatial artifacts. Second, it handles RGB color channels jointly, and thus produces fused images with more vivid color appearance. Third and most importantly, the direction of the signal structure component in the patch vector space provides ideal information for ghost removal. It allows us to reliably and efficiently reject inconsistent object motions with respect to a chosen reference image without performing computationally expensive motion estimation. We compare the proposed algorithm with 12 MEF methods on 21 static scenes and 12 deghosting schemes on 19 dynamic scenes (with camera and object motion). Extensive experimental results demonstrate that the proposed algorithm not only outperforms previous MEF algorithms on static scenes but also consistently produces high quality fused images with little ghosting artifacts for dynamic scenes. Moreover, it maintains a lower computational cost compared with the state-of-The-Art deghosting schemes.11The MATLAB code of the proposed algorithm will be made available online. Preliminary results of Section III-A [1] were presented at the IEEE International Conference on Image Processing, Canada, 2015. © 1992-2012 IEEE.

关键词： Image fusion

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Nonsmooth Dynamic Filtering for Mechanical Servo-systems

Nonsmooth Dynamic Filtering for Mechanical Servo-systems

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IEEE International Conference on Control and Automation

作者： Yonghong Tan Ruili Dong Yanyan Li Xiang Chen Hong He Department of Electrical Engineering Shanghai Normal University Institute of Robotics and Automatic Information System Tianjin Key Laboratory of Intelligent Robotics Nankai University Department of Electrical and Computer Engineering University of Windsor

ISBN: (纸本)9781509017393

In this paper, a nonsmooth dynamic filtering approach is proposed for stochastic noise filtering of mechanical servo-systems. In this approach, a stochastic nonsmooth state-space model with sandwich structure is developed to describe the nonsmooth dynamic feature of the system in random noisy case. Then, an approach for observability test of the nonsmooth system with sandwich architecture is proposed. Afterwards, a nonsmooth dynamic filtering method motivated by the structure of Kalman filter is proposed for noise suppression. The proposed nonsmooth Kalman filtering method is applied to random noise filtering of a servo-system with dead-zone feature.

关键词： CONTRAST FILTERS Servo systems noise filtering Noise suppression Kalman filters sandwich structures Models, Space Sandwiches

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A hybrid model and kinematic-free control framework for a low-cost deformable manipulator using in home service

A hybrid model and kinematic-free control framework for a lo...

引用

2016 IEEE International Conference on Automation Science and engineering, CASE 2016

作者： Li, Gaofeng Sun, Lei Xu, Shan Song, Dezhen Liu, Jingtai Institute of Robotics and Automatic Information System NanKai University Tianjin300350 China Tianjin Key Laboratory of Intelligent Robotics NanKai University Tianjin300350 China Department of Computer Science and Engineering Texas A and M University College StationTX77843 United States

ISBN: (纸本)9781509024094

Home service robot works in unstructured environments with various tasks, where a low-cost, dexterous, and intrinsically safe manipulator is important. Traditionally, a redundant manipulator with high degrees of freedom (DOFs) is employed. However, high DOFs bring problems like high cost, complex physical designing, and heavy weight. Here a novel low-cost deformable manipulator for home service robot, which is composed of rigid joints and deformable links, is introduced. The deformable manipulator can obtain relatively dexterous and extended workspace with fewer joints by bending its deformable links. Considering the typical hybrid behaviors caused by bending operation, a hybrid model and a practical kinematic-free control framework with no prior kinematic information are proposed to describe and control the deformable manipulator. The model and controller have been implemented on a 4-DOF deformable manipulator with two deformable links in simulation. The simulation results validate the proposed deformable manipulator and kinematic-free control. © 2016 IEEE.

关键词： Manipulators

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Assessment of a quality control procedure of hourly solar irradiations at Fez city, Morocco

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IOP Conference Series: Earth and Environmental Science 2018年第1期161卷

作者： Z Bounoua M Marzouq A Mechaqrane Laboratory of Renewable Energies and Intelligent System Electrical Engineering department Faculty of Sciences and Technologies Sidi Mohamed Ben Abdellah University of Fez PO. Box 2202 Fez Morocco Laboratory of Computer Sciences and Interdisciplinary Physics National School of Applied Sciences Sidi Mohamed Ben Abdellah University –Fez

In order to properly dimension solar power plants, it is necessary to have long series of relevant measurements of the available solar components at the site chosen for the installation. It is, however, well known that the quality of the measurements of solar irradiations can fail from time to time. Therefore, a quality control of the recorded data must be carried out before their use. This paper describes an assessment of a quality control procedure which is implemented for the hourly horizontal global and diffuse solar irradiations. A set of four quality control tests are applied to remove the erroneous data.

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Integrated mechatronics design of flexure joint and controller in dual-drive gantry: a constrained H2 optimization approach

Integrated mechatronics design of flexure joint and controll...

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2017 IEEE International Conference on Advanced intelligent Mechatronics, AIM 2017

作者： Ma, Jun Chen, Si-Lu Kamaldin, Nazir Teo, Chek Sing Tay, Arthur Mamun, Abdullah Al Tan, Kok Kiong Department of Electrical and Computer Engineering SIMTech-NUS Joint Lab on Precision Motion Systems National University of Singapore 117582 Singapore Department of Electrical and Computer Engineering National University of Singapore 117576 Singapore Mechatronics Group Singapore Institute of Manufacturing Technology 138634 Singapore Zhejiang Provincial Key Laboratory of Robotics and Intelligent Manufacturing Equipment Technology Ningbo Institute of Industrial Technology Chinese Academy of Sciences Ningbo Zhejiang315121 China NUS Grad. School for Inte. Sci. and Eng. and Department of Electrical Computer Engineering National University of Singapore 119077 Singapore

ISBN: (纸本)9781509059980

The dual-drive H gantry is widely used in many industrial processes that require high precision Cartesian motion. The conventional rigid-link version suffers breaking down of joints if any de-synchronization between the two carriages occurs. To prevent above potential risk, a novel biaxial gantry with flexure-links is designed to allow a small rotation angle of the cross-Arm. Nevertheless, the chattering of control signals and inappropriate design of the flexure joint will possibly induce resonant modes of the end effector. Thus, in this work, the design requirements in terms of tracking accuracy, biaxial synchronization, and resonant mode suppression are achieved by integrated optimization of the stiffness of flexures and PID controller parameters for a class of point-To-point trajectories with same dynamics but different steps. From here, an H2 optimization with defined constraints is formulated, and an efficient iterative solver is proposed by hybridizing direct computation of constrained projection gradient and line search of optimal steps. Comparative experiments results obtained on the testbed are presented to verify the effectiveness of proposed method. © 2017 IEEE.

关键词： Constrained optimization

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ANN-based modelling and prediction of daily global solar irradiation using commonly measured meteorological parameters

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IOP Conference Series: Earth and Environmental Science 2018年第1期161卷

作者： M Marzouq Z Bounoua A Mechaqrane H E Fadili Z Lakhliai K Zenkouar Laboratory of Computer Sciences and Interdisciplinary Physics National School of Applied Sciences USMBA Fez PO. Box 72 Fez Morocco Laboratory of Renewable Energies and Intelligent Systems Electrical Engineering department Faculty of Sciences and Technologies USMBA Fez PO. Box 2202 Fez Morocco Intelligent System and Application Laboratory Faculty of Sciences and Technologies USMBA Fez PO. Box 2202 Fez Morocco

The aim of this work is to develop an artificial neural network (ANN) based model for accurately predicting the daily global solar irradiation in the city of Fez. The potential of the developed model is verified and appraised through the local collected database for the period 2009-2015 from the radiometric station of the Faculty of Sciences and Technology of Fez. The obtained model is MLP with feed forward back-propagation algorithm containing three input parameters and a single hidden layer with nine neurons. Coefficient of determination R 2, the mean absolute percentage error MAPE and the relative root mean square error RRMSE are respectively equal to 97.16%, 21.77% and 18.79%.

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