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The International Conference on Informatics and systems (INFOS)

作者： Tahani Mahmoud Allam Alsayed Abdelhameed Sallam Hatem M. Abdullkader Computer and Automatic Control Department Faculty of Engineering Tanta University Tanta Egypt Information System Department Faculty of Computers and Information Menofia University Menofia Egypt

N-grams are a building block in natural language processing and information retrieval. It is a sequence of a string data like contiguous words or other tokens in text documents. In this work, we study how N-gram can be computed efficiently using a MapReduce for distributed data processing and a distributed database named Hbase This technique is applied to construct the training and testing processes using Hadoop MapReduce framework and Hbase. We proposed to focus on the time cost and storage size of the model and exploring different structures of Hbase table. By constructing and comparing a different table structures on training 100 million words for unigram, bigram and trigram models we suggest a table based on half ngram structure is a more suitable choice for distributed language model. The results of this work can be applied in the cloud computing and other large scale distributed language processing areas.

关键词： Computational modeling Training Smoothing methods Context Testing Informatics Distributed computing

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Robust control reconfiguration of resource allocation systems with Petri nets and integer programming

Robust control reconfiguration of resource allocation system...

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作者： Li, Jun Zhou, Mengchu Guo, Tao Gan, Yahui Dai, Xianzhong Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education China School of Automation Southeast University Nanjing 210096 China Key Laboratory of Embedded System and Service Computing Ministry of Education Tongji University Shanghai 201804 China Department of Electrical and Computer Engineering New Jersey Institute of Technology Newark NJ 07102 United States

Supervisory control reconfiguration can handle the uncertainties including resource failures and task changes in discrete event systems. It was not addressed to exploit the robustness of closed-loop systems to accommodate some uncertainties in the prior studies. Such exploitation can cost-efficiently achieve reconfigurability and flexibility for real systems. This paper presents a robust reconfiguration method based on Petri nets (PNs) and integer programming for supervisory control of resource allocation systems (RASs) subject to varying resource allocation relationships. An allocation relationship is seen as a control specification while the execution processes requiring resources as an uncontrolled plant. First, a robust reconfiguration mechanism is proposed. It includes updating the P-invariant-based supervisor and evolving the state of the closed-loop system. The latter adapts to the control specification changes by the self-regulation of the closed-loop system's state. Next, two novel integer programming models for control reconfiguration are proposed, called a reconfiguration model with acceptability and reconfiguration one with specification correction. Since both models integrate the firability condition of transitions, no additional efforts are required for the state reachability analysis. Finally, a hospital emergency service system is used as an example to illustrate them. © 2014 Elsevier Ltd. All rights reserved.

关键词： Integer programming

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Support Vector Machine with Nonlinear-Kernel Optimization for Lateralization of Epileptogenic Hippocampus in MR Images

Support Vector Machine with Nonlinear-Kernel Optimization fo...

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Annual International Conference of the IEEE engineering in Medicine and Biology Society

作者： Mohammad-Parsa Hosseini Mohammad R. Nazem-Zadeh Fariborz Mahmoudi Hao Ying Hamid Soltanian-Zadeh Medical Image Analysis Lab. Radiology Department Henry Ford Health System Department of Electrical and Computer Engineering Wayne State University Control and Intelligent Processing Center of Excellence School of Electrical and Computer Engineering University of Tehran

ISBN: (纸本)9781424479276

Surgical treatment is suggested for seizure control in medically intractable epilepsy patients. Detailed pre-surgical evaluation and lateralization using Magnetic Resonance Images (MRI) is expected to result in a successful surgical outcome. In this study, an optimized pattern recognition approach is proposed for lateralization of mesial Temporal Lobe Epilepsy (mTLE) patients using asymmetry of imaging indices of hippocampus. T1-weighted and Fluid-Attenuated Inversion Recovery (FLAIR) images of 76 symptomatic mTLE patients are considered. First, hippocampus is segmented using automatic and manual segmentation methods;then, volumetric and intensity features are extracted from the MR images. A nonlinear Support Vector Machine (SVM) with optimized Gaussian Radial Basis Function (GRBF) kernel is used to classify the imaging features. Using leave-one-out cross validation, this method results in a correct lateralization rate of 82%, a probability of detection for the left side of 0.90 (with false alarm probability of 0.04) and a probability of detection for the right side of 0.69 (with zero false alarm probability). The lateralization results are compared to linear SVM, multi-layer perceptron Artificial Neural Network (ANN), and volumetry and FLAIR asymmetry analysis. This lateralization method is suggested for pre-surgical evaluation using MRI before surgical treatment in mTLE patients. It achieves a more correct lateralization rate and fewer false positives.

关键词： Magnetic Resonance Imaging (MRI) Hippocampus Epilepsy Lateralization Support Vector Machine (SVM)

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A GPU-based Parallel Simulation Platform for Large-scale Wind Farm Integration

A GPU-based Parallel Simulation Platform for Large-scale Win...

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IEEE PES Transmission and Distribution Conference and Exposition

作者： Haixiang Gao Ying Chen Yin Xu Zhitong Yu Laijun Chen State Key Laboratory of Control and Simulation of Power System and Generation Equipments Department of Electrical Engineering Tsinghua University School of Electrical Engineering and Computer Science Washington State University

ISBN: (纸本)9781479936571

Due to the energy crisis of the next fifty years, an increasing number of large-scale wind farms are integrating into power systems. Parallel simulation platforms are indispensable to evaluate the effects of wind farm integration. A GPU-based parallel simulation platform is constructed in this paper to test the feasibility of simulating integration systems on GPU. By adopting previous research work such as averaged model and improved EMTP algorithm, models and algorithm of the platform are firstly introduced. Then the hardware and software architecture of the platform are put forward, which combine CPU configuration and GPU computing. Finally, a wind farm with different numbers of DFIGs are used to test the performance of the platform. Results show that the platform has excellent accuracy, efficiency and scalability. The work of this paper proves the feasibility to simulate wind farm integrating dynamics adopting GPU and its potential to reach tremendous efficiency and scalability.

关键词： Power system simulation Power system modelling

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Fuzzy approximation adaptive control of quadruped robots with kinematics and dynamics uncertainties

Fuzzy approximation adaptive control of quadruped robots wit...

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IEEE International Conference on Fuzzy systems (FUZZ-IEEE)

作者： Zhijun Li Shengtao Xiao Shuzhi Sam Ge The Key Lab of Autonomous System and Network Control South China University of Technology Guangzhou China Electrical & Computer Engineering Department National University of Singapore Singapore

This paper investigates optimal feet forces distribution and control of quadruped robots with uncertainties in both kinematics and dynamics. First, a constrained dynamics of quadruped robots is established. The distribution of required forces and moments on the supporting legs of a quadruped robot can be formulated as a problem for minimizing an objective function subject to form-closure constraints and balance constraints of external force. The dynamics of recurrent neural network for realtime force optimization are proposed. For the obtained optimized tip-point force and the motion of legs, we propose the hybrid motion/force control based on adaptive fuzzy system to compensate for the external perturbation and the task-space tracking errors in the environment. The proposed control can confront the uncertainties including approximation task space error and external perturbation. The verification of the proposed control is conducted using the extensive simulations.

关键词： Force Legged locomotion Dynamics Vectors Friction Jacobian matrices

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Erratum to: RETRACTED ARTICLE: Application of extreme learning machine for estimation of wind speed distribution

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Climate Dynamics 2015年第5期46卷 2025-2025页

作者： Shahaboddin Shamshirband Kasra Mohammadi Chong Wen Tong Dalibor Petković Emilio Porcu Ali Mostafaeipour Sudheer Ch Ahmad Sedaghat Department of Computer System and Technology Faculty of Computer Science and Information Technology University of Malaya Kuala Lumpur Malaysia Faculty of Mechanical Engineering University of Kashan Kashan Iran Department for Mechatronics and Control Faculty of Mechanical Engineering University of Niš Nis Serbia Technical University Federico Santa Maria Valparaíso Chile Industrial Engineering Department Yazd University Yazd Iran Department of Civil and Environmental Engineering ITM University Gurgaon India Department of Mechanical Engineering School of Engineering Australian College of Kuwait Safat Kuwait

Unfortunately, the co-author affiliation Dalibor Petković has been incorrectly published in the original publication.

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Semi-global leader-following consensus of multiple linear systems with position and rate-limited actuators: The state feedback case

Semi-global leader-following consensus of multiple linear sy...

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World Congress on Intelligent control and Automation (WCICA)

作者： Zhiyun Zhao Zongli Lin Department of Automation Key Laboratory of System Control and Information Processing Shanghai China Charles L. Brown Department of Electrical and Computer Engineering University of Virginia Charlottesville VA USA

This paper studies the semi-global leader-following consensus problem for a group of linear systems in the presence of both actuator position and rate saturation. Each follower agent in the group is described by a general linear system subject to simultaneous actuator position and rate saturation. We construct a low gain based linear state feedback control law for each follower agent and show that semi-global leader-following consensus can be achieved by using these control laws when the communication topology among follower agents is a connected undirected graph and the leader is a neighbor of at least one follower. Simulation results illustrate the theoretical results.

关键词： Actuators State feedback Topology Linear systems Multi-agent systems Closed loop systems Vectors

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An Adaptive Predictive control Strategy for RMPPT under Partially Shaded Conditions

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IFAC Proceedings Volumes 2014年第3期47卷 4947-4952页

作者： Chao Ma Jing Wu Ning Li Shaoyuan Li Kang Li Department of Automation Shanghai Jiao Tong University Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai China School of Electronics Electrical Engineering and Computer Science Queen's University Belfast UK

As one of key technologies in photovoltaic converter control, Maximum Power Point Tracking (MPPT) methods can keep the power conversion efficiency as high as nearly 99% under the uniform solar irradiance condition. However, these methods may fail when shading conditions occur and the power loss can over as much as 70% due to the multiple maxima in I – P curve in shading conditions v.s. single maximum point in uniformly solar irradiance. In this paper, a Real Maximum Power Point Tracking (RMPPT) strategy under Partially Shaded Conditions (PSCs) is introduced to deal with this kind of problems. An optimization problem, based on a predictive model which will change adaptively with environment, is developed to tracking the global maxima and corresponding adaptive control strategy is presented. No additional circuits are required to obtain the environment uncertainties. Finally, simulations show the effectiveness of proposed method.

关键词： Photovoltaic systems RMPPT Partial shading Adaptive predictive control

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Team of Bayesian optimization algorithms to solve task assignment problems in heterogeneous computing systems

Team of Bayesian optimization algorithms to solve task assig...

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IEEE International Conference on systems, Man and Cybernetics

作者： Jie Li JunQi Zhang Qi Kang ChangJun Jiang Ministry of Education China Key Laboratory of Embedded System and Service Computing Department of Computer Science and Technology Tongji University Shanghai Department of Control Science and Engineering Tongji University Shanghai China

ISBN: (纸本)9781479938414

A Bayesian optimization algorithm (BOA) belongs to estimation of distribution algorithms (EDAs). It is characterized by combining a Bayesian network and evolutionary algorithms to solve nearly decomposable optimization problems. BOA is less popularly applied to solve high dimensionality complex optimization problems. A key reason is that the cost of training all dimensions by BOA becomes expensive with the increase of problem dimensionality. Since data are relatively sparse in a high dimensional space, even though BOA can train all dimensions simultaneously, the interdependent relations between different dimensions are difficult to learn. Its search ability is thus significantly reduced. In this paper, we propose a team of Bayesian optimization algorithms (TBOA) to search and learn dimensionality. TBOA consists of multiple BOAs, in which each BOA corresponds to a dimension of the solution domain and it is responsible for the search of this dimension's value region. The proposed TBOA is used to solve the real problem of task assignment in heterogeneous computing systems. Extensive experiments demonstrate that the computational cost of the overall training in TBOA is decreased very significantly while keeping high solution accuracy.

关键词： Bayes methods Sociology Statistics Optimization Computational efficiency Joints Probability distribution

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On the Estimation of the Domain of Attraction for Saturated systems via Partitioning of the Input Space

On the Estimation of the Domain of Attraction for Saturated ...

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第三十三届中国控制会议

作者： Yuanlong Li Zongli Lin Department of Automation and Key Laboratory of System Control and Information Processing of the Ministry of EducationShanghai Jiao Tong University Charles L.Brown Department of Electrical and Computer Engineering University of Virginia

ISBN: (纸本)9781479947249

This paper revisits the problem of estimating the domain of attraction for systems with saturation *** divide the input space into several regions. In one of these regions, none of the inputs saturate. In each of the remaining regions, there is a unique input that saturates everywhere with the time-derivative of its saturated signal being zero. These special properties of the inputs in different regions of the input space are combined with an existing piecewise quadratic Lyapunov functions that contains the information of input saturation to arrive at a set of less conservative stability conditions, from which a larger level set of the piecewise quadratic Lyapunov function can be obtained as an estimate of the domain of *** results indicate that the proposed approach has the ability to obtain a significantly larger estimate of the domain of attraction than the existing methods.

关键词： Actuator saturation,constrained control,domain of attraction,input saturation,piecewise quadratic Lyapunov functions,stability analysis

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