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World Congress on intelligent control and Automation (WCICA)

作者： Songhyok Ri Jian Huang Chunjing Tao Myonghyok Ri Yongsok Ri Daeho Han School of Automation Huazhong University of Science and Technology Wuhan CHINA Department of Control Science University of Sciences Pyongyang D.P.R. of Korea Key Laboratory of Ministry of Education for Image Processing and Intelligent Control Huazhong University of Science and Technology Wuhan CHINA R&D department National Research Center for Rehabilitation Technical Aids Beijing Automation school Kim Chaek University of Technology Pyongyang D.P.R. of Korea Department of Phisics University of Sciences Pyongyang D.P.R. of Korea

ISBN: (纸本)9781467384155

In this paper, a novel disturbance observer (DO) for the Mobile Wheeled Inverted Pendulum (MWIP) system is proposed. A choice method of optimal gain matrices is also proposed for a given robust gain, which can improve the estimation precision of the DO. Combining the proposed DO and Sliding Mode control (SMC), a new sliding mode velocity control method is designed for the MWIP system. The convergency of the DO is proved by Lyapunov theorem. And the stability of the closed-loop system is achieved through the appropriate selection of sliding surface coefficients. The effectiveness of all proposed methods is verified by simulation results for the MWIP system.

关键词： Wheels Automation Velocity control Uncertainty Observers Robustness

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Thermal management solutions for a traction robot for use in downhole extreme conditions

Thermal management solutions for a traction robot for use in...

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Intersociety Conference on Thermal and Thermomechanical Phenomena in Electronic Systems (ITHERM)

作者： Shuang Gao Aihua Tao Jingjing Cheng Ming Zhou Zhiyu Gong School of Automation Huazhong University of Science and Technology Wuhan P. R. China Well-Tech R&D Institutes China Oilfield Service Limited Beijing P. R. China Key Laboratory of Image Processing and Intelligent Control Ministry of Education Wuhan P. R. China School of Energy and Power Engineering Huazhong University of Science and Technology Wuhan P. R. China

Accurate techniques for testing production sections are important when developing horizontal wells, but appropriate methods are also needed for transporting loggers through horizontal well segments. The reciprocating grip traction robot is a pipeline robot that has already been tested and broadly accepted for use in horizontal wells. Reciprocating grip traction robots have received a great deal of attention because they are very (more than 40%) efficient, although many other tractors are only 10% to 20% efficient, the remaining energy being converted to waste heat. However, even an efficiency of 40% may constitute a serious thermal problem in high-temperature environments, and cooling methods must be used to remove the heat produced by the waste energy. The research presented here is mainly focused on the development of a thermal management system for the electronics in traction robots. Numerical simulations are used to optimize heat sink and skeleton structure to mitigate the effects of high temperature.

关键词： Heat sinks Robots Heat transfer Resistance Resistance heating Skeleton

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A novel computational approach to predict activity of nuclear export signals

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Journal of Computational and Theoretical Nanoscience 2015年第12期12卷 6016-6019页

作者： Chen, Zhihua Zhang, Pan Wu, Tingfang Shi, Xiaolong Wang, Xun Key Laboratory of Image Information Processing and Intelligent Control School of Automation Huazhong University of Science and Technology WuhanHubei430074 China College of Computer and Communication Engineering China University of Petroleum QingdaoShandong266580 China

A nuclear export signal (NES) is a sequence of amino acids, which is a protein localization signal, and contributes to regulate localization of cellular proteins. In recent peering works, activity of NESs were introduced in computational methods, which perform significantly well in identifying unknown NESs even from huge datasets, but suffer from a shortage that only a small number of NESs are associated with experimental verified active scores. In this work, we propose a novel computational method to predict active score of NESs. Specifically, we firstly abstract relevant features to NES activity, and then construct a mathematical model based on principal component analysis (PCA) to find each feature's contribution to activity. In this way, a method to calculate active score of unknown NESs is achieved. In data experiments, it is obtained that our method can achieve accuracy rate 80%. The activity of an unknown NES candidate can give us a preliminary understanding of it, and can be used to identify positive NESs from the negative ones. To the best acknowledge of the authors, this is the first time computational method is proposed to predict NESs' activity. Copyright © 2015 American Scientific Publishers All rights reserved.

关键词： Computational methods

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Frequency-specific Alterations of Large-scale Functional Brain Networks in Patients with Alzheimer＇s Disease

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Chinese Medical Journal 2015年第5期128卷 602-609页

作者： Yuan-Yuan Qin Ya-Peng Li Shun Zhang Ying Xiong Lin-Ying Guo Shi-Qi Yang Yi-Hao Yao Wei Li Wen-Zhen Zhu Department of Radiology Tongji Hospital Tongji Medical College Huazhong University of Science and Technology Wuhan Hubei 430030 China Department of Control Science and Engineering Image Processing and Intelligent Control Key Laboratory of Education Ministry of China Huazhong University of Science and Technology Wuhan Hubei 430074 China

Background：Previous studies have indicated that the cognitive deficits in patients with Alzheimer＇s disease （AD） may be due to topological deteriorations of the brain ***,whether the selection of a specific frequency band could impact the topological properties is still not *** hypothesis is that the topological properties of AD patients are also ***：Resting state functional magnetic resonance imaging data from l0 right-handed moderate AD patients （mean age：64.3 years; mean mini mental state examination [MMSE]：18.0） and 10 age and gender-matched healthy controls （mean age：63.6 years; mean MMSE：28.2） were enrolled in this *** global efficiency,the clustering coefficient （CC）,the characteristic path length （CpL）,and ＂small-world＂ property were calculated in a wide range of thresholds and averaged within each group,at three different frequency bands （0.01-0.06 Hz,0.06-0.11 Hz,and 0.11-0.25 Hz）.Results：At lower-frequency bands （0.01-0.06 Hz,0.06-0.11 Hz）,the global efficiency,the CC and the ＂small-world＂ properties of AD patients decreased compared to *** at higher-frequency bands （0.11-0.25 Hz）,the CpL was much longer,and the ＂small-world＂ property was disrupted in AD,particularly at a higher *** topological properties changed with different frequency bands,suggesting the existence of disrupted global and local functional organization associated with ***：This study demonstrates that the topological alterations of large-scale functional brain networks inAD patients are frequency dependent,thus providing fundamental support for optimal frequency selection in future related research.

关键词： Alzheimer＇s Disease Frequency Network

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On string languages generated by spiking neural P systems with astrocytes

Communications in Computer and Information Science

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Communications in Computer and information Science 2014年 472卷 225-229页

作者： Kong, Yuan Zhang, Zheng Liu, Yang Key Laboratory of Image Information Processing and Intelligent Control School of Automation Huazhong University of Science and Technology Wuhan Hubei430074 China

ISBN: (纸本)9783662450482

Spiking neural P systems with astrocytes (SNPA systems, for short) are a class of distributed parallel computing devices inspired from the way spikes pass through the synapses between the neurons. In this work, we investigate the language generation power of SNPA systems. Specifically, we prove that SNPA systems without the forgetting rules can generate recursively enumerable languages and characterize regular languages. Furthermore, we give a finite language that can be generated by SNPA systems, but which cannot be generated by spiking neural P systems without astrocytes. These results show that astrocyte is a powerful ingredient for generating languages by spiking neural P systems. © Springer-Verlag Berlin Heidelberg 2014.

关键词： Distributed computer systems

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Data-Based Health State Analysis for the Axle of High Speed Train

Data-Based Health State Analysis for the Axle of High Speed ...

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International Conference on Computational Intelligence and Security

作者： Guo Xie Minying Ye Xinhong Hei Jinwei Zhao Fucai Qian Xi'an University of Technology Xi'an China Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Xi'an China

Taking into account that the present popular methods, such as the judgement of the axle failure based on temperature threshold, and the early warning of axle based on real-time temperature analysis, cannot analyze the changing of performance trends, a health state analysis method for the axle of high-speed train based on long-term temperature monitoring data is proposed in this paper, which including the following main steps: (1) Preprocessing of the original data to correct the singular zero value and complement the missing values, (2) Smoothing of the processed data in order to automatically extract the beginning and end points of every temperature rising stage of axles, (3) Establishment of the calculation method of temperature rising rate, and evaluating the health sate of axles based on the temperature rising rate. Finally, the proposed method is validated based on the data from a test line, the results demonstrate the effectiveness and practicability of the method.

关键词： Axles Temperature distribution Aging Safety Data mining Fault diagnosis Monitoring

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Almost periodic solutions for a memristor-based neural networks with leakage, time-varying and distributed delays

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Neural networks : the official journal of the International Neural Network Society 2015年 68卷 34-45页

作者： Ping Jiang Zhigang Zeng Jiejie Chen School of Automation Huazhong University of Science and Technology Wuhan 430074 China School of Computer Science and Technology Hubei PolyTechnic University Huangshi 435003 China. Electronic address: jiangping20140209@***. Key Laboratory of Image Processing and Intelligent Control of Education Ministry of China Wuhan 430074 China. Electronic address: hustzgzeng@***. Key Laboratory of Image Processing and Intelligent Control of Education Ministry of China Wuhan 430074 China.

In this paper, we study the existence and global exponential stability of almost periodic solution for memristor-based neural networks with leakage, time-varying and distributed delays. Using a new Lyapunov function method, we prove that this delayed neural network has a unique almost periodic solution, which is globally exponentially stable. Moreover, the obtained conclusion on the almost periodic solution is applied to prove the existence and stability of periodic solution (or equilibrium point) for this delayed neural network with periodic coefficients (or constant coefficients).

关键词： Almost periodic solution Global exponential stability Leakage Memristor-based neural networks Time-varying and distributed delays

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Parallel programming in spiking neural P systems with synapses states

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Journal of Computational and Theoretical Nanoscience 2015年第10期12卷 3418-3423页

作者： Yuan, Kong Dongming, Zhao School of Automation Wuhan University of Technology Wuhan Hubei China Key Laboratory of Image Processing and Intelligent Control School of Automation Huazhong University of Science and Technology Wuhan Hubei China

Spiking neural P systems with synapses states characterize the movement of spikes among the neurons. The number of the spikes in neurons can be represented by integers, which provide a way to represent increment, decrement, relational operations and assignment statement using spiking neural P systems with synapses states. According to these basic structures, it is possible to represent programming languages constructs. In this work, a kind of parallel programming language dealing with integer variables is considered, and it is simulated by spiking neural P systems with synapses states. Copyright © 2015 American Scientific Publishers.

关键词： Parallel programming

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Application of multi-gene genetic programming based on separable functional network for landslide displacement prediction

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Neural Computing and Applications 2015年第6期27卷 1771-1784页

作者： Chen, Jiejie Zeng, Zhigang Jiang, Ping Tang, Huiming School of Automation Huazhong University of Science and Technology Wuhan China Key Laboratory of Image Processing and Intelligent Control of Education Ministry of China Wuhan China Faculty of Engineering China University of Geosciences Wuhan China

Complexity of analysis of landslide hazard is due to uncertainty. In this study, a novel approach multi-gene genetic programming based on separable functional network (MGGPSFN) is presented for predicting landslide displacement. Moreover, Pearson's cross-correlation coefficients and mutual information are adopted to look for the potential input variables for a forecast model in the paper. The performance of new model is verified through one case study in Baishuihe landslide in the Three Gorges Reservoir in China. In addition, we compared it with two methods, back-propagation neural network and radial basis function, and MGGPSFN got the best results in the same measurements.

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AN ADAPTIVE MEMBRANE ALGORITHM FOR SOLVING COMBINATORIAL OPTIMIZATION PROBLEMS

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Acta Mathematica Scientia 2014年第5期34卷 1377-1394页

作者：贺娟娟肖建华邵泽辉 Key Laboratory of Image Processing and Intelligent Control School of AutomationHuazhong University of Science and Technology The Research Center of Logistics Nankai University School of Information Science and Technology Chengdu University

Membrane algorithms （MAs）, which inherit from P systems, constitute a new parallel and distribute framework for approximate computation. In the paper, a membrane algorithm is proposed with the improvement that the involved parameters can be adaptively chosen. In the algorithm, some membranes can evolve dynamically during the computing process to specify the values of the requested parameters. The new algorithm is tested on a well-known combinatorial optimization problem, the travelling salesman problem. The em-pirical evidence suggests that the proposed approach is efficient and reliable when dealing with 11 benchmark instances, particularly obtaining the best of the known solutions in eight instances. Compared with the genetic algorithm, simulated annealing algorithm, neural net-work and a fine-tuned non-adaptive membrane algorithm, our algorithm performs better than them. In practice, to design the airline network that minimize the total routing cost on the CAB data with twenty-five US cities, we can quickly obtain high quality solutions using our algorithm.

关键词： membrane algorithm adaptation travelling salesman problem

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