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Communications, Information, Electronic and Energy Systems (CIEES), International Conference on

作者： Perizat Rakhmetova Aldabergen Bektilevov Bakhtiyar Kopenov Makabbat Zhamuratova Saltanat Yussupova Tolkyn Toktamyssova Dept. of Robotics and technical means of automation Satbayev University Almaty Kazakhstan Dept. of Transport engineering and logistics named after M.Tynyshpayev Satbayev University Almaty Kazakhstan Dept. of Motor vehicles and life-safety Academy Logistics and Transport Almaty Kazakhstan Dept. of Electronic Engineering Almaty University of Power Engineering and Telecommunications Almaty Kazakhstan

In recent years, computer vision technology has made significant progress, expanding its application from simple image recognition tasks to complex real-world problems. One such area where computer vision promises to be is the control of manipulators in various fields such as manufacturing, healthcare and robotics. Manipulators, mechanical arms designed to perform tasks, are traditionally controlled using manual input or a preprogrammed sequence. The purpose of this manuscript is to research and analyze computer vision applicable to improve the control and efficiency of manipulators.

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Fuzzy Controlled Adaptive Follow the Gap Obstacle Avoidance Algorithm 21

Fuzzy Controlled Adaptive Follow the Gap Obstacle Avoidance ...

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Proceedings of the 7th International Conference on robotics and Artificial Intelligence

作者： Bilal Yucel Abdurrahman Yilmaz Osman Ervan Hakan Temeltas Control and Automation Engineering Dept. Robotics Laboratory Istanbul Technical University Turkey

ISBN: (纸本)9781450385855

Follow the Gap Method (FGM) and Improved Follow the Gap Method (FGM-I) are geometric obstacle avoidance algorithms for navigation. In these methods, the vehicle detects the gaps around the object and navigates to the midpoint of the optimal gap calculated according to a defined function. One missing point of these algorithms is failure to the goal point when there is an obstacle near to it. Another drawback is that early consideration of obstacles causes long trajectories. In this paper, Adaptive Follow the Gap (A-FGM) is presented to overcome these two points. In A-FGM, a fuzzy controlled evaluation radius is set and only obstacles within this region are included in the evaluation. A differential drive robot is used in simulations and results show that A-FGM increases the success rate of reaching the goal and efficiency of previous algorithms. The source code of the developed approach is shared on GitHub 1.

关键词： Mobile Robots Fuzzy Control Path Planning Robot Navigation Adaptive Control Obstacle Avoidance

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Automated control and interpretation of colour reproduction

Automated control and interpretation of colour reproduction

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Dynamics of Systems, Mechanisms and Machines (Dynamics)

作者： A. V. Golunov V. Yu. Kirnosov A. S. Golunova O. V. Trapeznikova M. A. Fedorova Design and technology of media industry dept. Omsk State Technical University Omsk Russian Federation Automation and Robotics dept. Omsk State Technical University Omsk Russian Federation Foreign languages dept. Omsk State Technical University Omsk Russian

ISBN: (纸本)9781509040513

The paper considers various methodologies of estimating colour gamut of the image information reproduction systems, which provide high precision of determination qualitative and quantitative colour indices. A new approach to the automation of colour coordinates control based on the method of analytical integration and interpretation of colour reproduction with the help of colorimetric software and hardware appliance developed on C++ language in Visual Studio programming environment is presented in the paper. Practical application of the method provides the colour measurement with high calculation precision and the possibility of colour gamut visualization in MKO Lab system, as well as the interpretation of the data concerning colour parameters measurement between MKO XYZ and MKO Lab colorimetric systems. It also helps to assess the reproduction systems colour gamut from the qualitative and quantitative points of view and to compare parameters of various colour reproduction systems. The graphical interpretation of the reproduction systems colour gamut, the efficiency of analytical integration method while calculating colour gamut of reproduction systems, and the efficiency of its software implementation in software and hardware appliance are given.

关键词： Image color analysis Software Hardware Software measurement Home appliances Ink Data visualization

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Identifying the best machine learning algorithms for brain tumor segmentation, progression assessment, and overall survival prediction in the BRATS challenge

arXiv

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arXiv 2018年

作者： Bakas, Spyridon Reyes, Mauricio Jakab, Andras Bauer, Stefan Rempfler, Markus Crimi, Alessandro Shinohara, Russell Takeshi Berger, Christoph Ha, Sung Min Rozycki, Martin Prastawa, Marcel Alberts, Esther Lipkova, Jana Freymann, John Kirby, Justin Bilello, Michel Fathallah-Shaykh, Hassan M. Wiest, Roland Kirschke, Jan Wiestler, Benedikt Colen, Rivka Kotrotsou, Aikaterini Lamontagne, Pamela Marcus, Daniel Milchenko, Mikhail Nazeri, Arash Weber, Marc-Andr Mahajan, Abhishek Baid, Ujjwal Gerstner, Elizabeth Kwon, Dongjin Acharya, Gagan Agarwal, Manu Alam, Mahbubul Albiol, Alberto Albiol, Antonio Albiol, Francisco J. Alex, Varghese Allinson, Nigel Amorim, Pedro H.A. Amrutkar, Abhijit Anand, Ganesh Andermatt, Simon Arbel, Tal Arbelaez, Pablo Avery, Aaron Azmat, Muneeza Pranjal, B. Bai, Wenjia Banerjee, Subhashis Barth, Bill Batchelder, Thomas Batmanghelich, Kayhan Battistella, Enzo Beers, Andrew Belyaev, Mikhail Bendszus, Martin Benson, Eze Bernal, Jose Bharath, Halandur Nagaraja Biros, George Bisdas, Sotirios Brown, James Cabezas, Mariano Cao, Shilei Cardoso, Jorge M. Carver, Eric N. Casamitjana, Adri Castillo, Laura Silvana Cat, Marcel Cattin, Philippe Cérigues, Albert Chagas, Vinicius S. Chandra, Siddhartha Chang, Yi-Ju Chang, Shiyu Chang, Ken Chazalon, Joseph Chen, Shengcong Chen, Wei Chen, Jefferson W. Chen, Zhaolin Cheng, Kun Choudhury, Ahana Roy Chylla, Roger Clrigues, Albert Colleman, Steven Colmeiro, Ramiro German Rodriguez Combalia, Marc Costa, Anthony Cui, Xiaomeng Dai, Zhenzhen Dai, Lutao Daza, Laura Alexandra Deutsch, Eric Ding, Changxing Dong, Chao Dong, Shidu Dudzik, Wojciech Eaton-Rosen, Zach Egan, Gary Escudero, Guilherme Estienne, Tho Everson, Richard Fabrizio, Jonathan Fan, Yong Fang, Longwei Feng, Xue Ferrante, Enzo Fidon, Lucas Fischer, Martin French, Andrew P. Fridman, Naomi Fu, Huan Fuentes, David Gao, Yaozong Gates, Evan Gering, David Gholami, Amir Gierke, Willi Glocker, Ben Gong, Mingming Gonzlez-Vill, Sandra Grosges, T. Guan, Yuanfang Guo, Sheng Gupta, Sudeep Han, Woo-Sup Han, Il Song Harmuth, Ko Center for Biomedical Image Computing and Analytics University of Pennsylvania PhiladelphiaPA United States Department of Radiology Perelman School of Medicine University of Pennsylvania PhiladelphiaPA United States Department of Pathology and Laboratory Medicine Perelman School of Medicine University of Pennsylvania PhiladelphiaPA United States Institute for Surgical Technology and Biomechanics University of Bern Bern Switzerland Center for MR-Research University Children's Hospital Zurich Zurich Switzerland Support Centre for Advanced Neuroimaging Inselspital Institute for Diagnostic and Interventional Neuroradiology Bern University Hospital Bern Switzerland University Hospital of Zurich Zurich Switzerland Center for Clinical Epidemiology and Biostatistics University of Pennsylvania Philadelphia United States Image-Based Biomedical Modeling Group Technical University of Munich Munich Germany Icahn School of Medicine Mount Sinai Health System New YorkNY United States Leidos Biomedical Research Inc. Frederick National Laboratory for Cancer Research FrederickMD21701 United States Cancer Imaging Program National Cancer Institute National Institutes of Health BethesdaMD20814 United States Department of Neurology University of Alabama at Birmingham BirminghamAL United States Department of Diagnostic Radiology University of Texas MD Anderson Cancer Center HoustonTX United States Department of Psychology Washington University St. LouisMO United States Neuroimaging Informatics and Analysis Center Washington University St. LouisMO United States Department of Radiology Washington University St. LouisMO United States Institute of Diagnostic and Interventional Radiology Pediatric Radiology and Neuroradiology University Medical Center Rostock Ernst-Heydemann-Str. 6 Rostock18057 Germany Tata Memorial Centre Homi Bhabha National Institute Mumbai India Shri Guru Gobind Singhji Institute of Engineering and Technology Nanded India NVIDIA Santa Clara

Gliomas are the most common primary brain malignancies, with different degrees of aggressiveness, variable prognosis and various heterogeneous histologic sub-regions, i.e., peritumoral edematous/invaded tissue, necrotic core, active and non-enhancing core. This intrinsic heterogeneity is also portrayed in their radio-phenotype, as their sub-regions are depicted by varying intensity profiles disseminated across multi-parametric magnetic resonance imaging (mpMRI) scans, reflecting varying biological properties. Their heterogeneous shape, extent, and location are some of the factors that make these tumors difficult to resect, and in some cases inoperable. The amount of resected tumor is a factor also considered in longitudinal scans, when evaluating the apparent tumor for potential diagnosis of progression. Furthermore, there is mounting evidence that accurate segmentation of the various tumor sub-regions can offer the basis for quantitative image analysis towards prediction of patient overall survival. This study assesses the state-of-the-art machine learning (ML) methods used for brain tumor image analysis in mpMRI scans, during the last seven instances of the International Brain Tumor Segmentation (BraTS) challenge, i.e., 2012-2018. Specifically, we focus on i) evaluating segmentations of the various glioma sub-regions in pre-operative mpMRI scans, ii) assessing potential tumor progression by virtue of longitudinal growth of tumor sub-regions, beyond use of the RECIST/RANO criteria, and iii) predicting the overall survival from pre-operative mpMRI scans of patients that underwent gross total resection. Finally, we investigate the challenge of identifying the best ML algorithms for each of these tasks, considering that apart from being diverse on each instance of the challenge, the multi-institutional mpMRI BraTS dataset has also been a continuously evolving/growing dataset. Copyright © 2018, The Authors. All rights reserved.

关键词： Tumors

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Unified hysteresis and creep compensation in AFM tip positioning with an extended PI model

Unified hysteresis and creep compensation in AFM tip positio...

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IEEE International Conference on robotics and automation (ICRA)

作者： Zhiyu Wang Lianqing Liu Zhidong Wang Wenxue Wang Dept. of Advanced Robotics Chiba Institute of Technology Japan State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Sciences (CAS) China College of Electrical and Control Engineering Liaoning Technical University and University of Chinese Academy of Sciences China

The nonlinearities such as hysteresis and creep are the major factors inherent in PZT actuation that affect the tip positioning precision and manipulation performance of the AFM system. In this study, an extended PI model is generalized by introducing a creep model to the basic hysteretic operator of the PI model at the inflexion point of the hysteresis loop. Unified compensation for hysteresis and creep can be implemented with the extended PI model. Experiment results demonstrate the validity and effectiveness of the extended PI model and it is implied that the inflexion creep compensation not only improves the tip positioning precision at the inflexion points on the hysteresis loops, but also the localization effectiveness during the whole process of PZT actuation.

关键词： Creep Hysteresis Computational modeling Mathematical model Calibration Trajectory Load modeling

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A stochastic state prediction in AFM based nanomanipulation

A stochastic state prediction in AFM based nanomanipulation

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2012 9th IEEE International Conference on Mechatronics and automation, ICMA 2012

作者： Wang, Zhiyu Liu, Lianqing Wang, Zhidong Dong, Zaili Yuan, Shuai Hou, Jing State Key Laboratory of Robotics Shenyang Institute of Automation CAS Shenyang 110016 China Faculty of Electrical and Control Engineering Liaoning Technical University Huludao 125105 China Dept. of Advanced Robotics Chiba Institute of Technology Chiba Japan Graduate School Chinese Academy of Sciences Beijing 100001 China

ISBN: (纸本)9781467312776

The reliability of AFM based nanomanipulation is one of the prerequisites for nano fabricating, thus uncertainties of the target nano-particle position need to be controlled within a pointed limits, which lead to two problem to be solved: one is how to describe state uncertainties at every different sample times;the other is how to deduce the next state uncertainty according to the current one. This paper provides a method to construct a stochastic predictive model to covering those problems. In the concrete, the predictive model uses Gaussian and Beta distribution as well as Mont Carlo Method to describe and deduce the state uncertainties respectively. The method is also applied to the process of pushing a nano-particle using AFM. © 2012 IEEE.

关键词： Stochastic systems

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Virtual nano-hand: A stable pushing strategy in AFM based sensorless nanomanipulation

Virtual nano-hand: A stable pushing strategy in AFM based se...

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2011 IEEE International Conference on robotics and Biomimetics, ROBIO 2011

作者： Wang, Zhiyu Liu, Lianqing Hou, Jing Wang, Zhidong Yuan, Shuai Dong, Zaili State Key Laboratory of Robotics Shenyang Institute of Automation CAS Shenyang 110016 China Dept. of Advanced Robotics Chiba Institute of Technology Chiba Japan Faculty of Electrical and Control Engineering Liaoning Technical University Huludao 125105 China Graduate School of Chinese Academy of Sciences Beijing 100001 China College of Information Science and Engineering Northeastern University Shenyang 110004 China

ISBN: (纸本)9781457721373

One of the prerequisites for AFM based nanomanipulation is that the position of the target nanoparticle can be stable controlled within a known area, while this prerequisite is still hindered by the uncertainties including the initial position of the nanoparticle and of the AFM tip, together with the uncertain forces from the substrate and so on. In this paper, a Stochastic Pushing (SP) model and a Stable Pushing Strategy are proposed respectively, which can push the nanoparticle into a bounded target area within a given probability. Simulations and experiment based on the proposed SP model demonstrate the validity of the Stable Pushing Strategy. © 2011 IEEE.

关键词： Nanoparticles

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An extended PI model for hysteresis and creep compensation in AFM based nanomanipulation

An extended PI model for hysteresis and creep compensation i...

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2010 IEEE International Conference on robotics and Biomimetics, ROBIO 2010

作者： Wang, Zhiyu Liu, Lianqing Wang, Zhidong Dong, Zaili Yuan, Shuai State Key Laboratory of Robotics Shenyang Institute of Automation CAS Shenyang 110016 China Dept. of Advanced Robotics Chiba Institute of Technology Chiba Japan Graduate School of Chinese Academy of Sciences Beijing 100001 China Faculty of Electrical and Control Engineering Liaoning Technical University Huludao 125105 China

ISBN: (纸本)9781424493173

One of the prerequisites for AFM based nanomanipulation is that the tip position can be controlled accurately, while this prerequisite is still hindered by the large model uncertainties aroused from PZT nonlinearity such as hysteresis and creep. In this paper, an Extended Prandtl-Ishlinskii (EPI) model is proposed to solve these problems. The main advantage of EPI model over conventional PI model is that the EPI model can compensate the positioning error caused by hysteresis and creep simultaneously through adopting the new adaptive basic operator. The experimental results demonstrate the effectiveness and validity of EPI model in depicting the PZT hysteresis and creep prosperities. © 2010 IEEE.

关键词： Creep

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Fuzzy automata for fault diagnosis: A syntactic analysis approach

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3rd Hellenic Conference on Artificial Intelligence, SETN 2004

作者： Rigatos, Gerasimos G. Tzafestas, Spyros G Industrial Systems Institute University Campus of Patras Building A ’ Rion Patras26500 Greece National Technical University of Athens Dept. of Electrical and Computer Engineering Intelligent Robotics and Automation Lab Zografou Campus Athens15773 Greece

ISBN: (纸本)3540219374

Fuzzy automata are proposed for fault diagnosis. The output of the monitored system is partitioned into linear segments which are assigned to pattern classes (templates) with the use of fuzzy membership functions. A sequence of templates is generated and becomes input to fuzzy automata which have transitions that correspond to the templates of the properly functioning system. If the automata reach their final states, i.e. the input sequence is accepted by the automata with a membership degree that exceeds a certain threshold, then normal operation is deduced, otherwise, a failure is diagnosed. Fault diagnosis of a DC motor and detection of abnormalities in the ECG signal are used as case studies. © Springer-Verlag Berlin Heidelberg 2004.

关键词： DC motors

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On-line improvement for the decentralized predictive control of the heat dynamics of a greenhouse 15th

On-line improvement for the decentralized predictive control...

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15th World Congress of the International Federation of Automatic Control, 2002

作者： Kyriannakis, E.J. Arvanitis, K.G. Sigrimis, N. National Technical University of Athens Dept. of Electrical and Computer Engineering Intelligent Robotics and Automation Laboratory Zographou Athens15773 Greece Agricultural University of Athens Department of Agricultural Engineering Athens11855 Greece

ISBN: (纸本)9783902661746

A decentralized model-based predictive controller is used for the design of discrete-time control systems aiming at regulating the air temperature and heat supply in greenhouses. Moreover, alternative techniques are proposed for the approximation of the decentralized part of the control and the on-line improvement of the overall control problem. A state space model is used to predict the corresponding local indoor temperature over a long-range time-period and approximate models are used to predict the interactions among the subsystems. The sun radiation and outdoor temperature are treated as external disturbances that affect the overall system dynamics. A series of energy fluxes consist the heating system and the predictive controllers have proved to be powerful in controlling the supply temperature. Copyright © 2002 IFAC.

关键词： Discrete time control systems

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