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Reliability analysis of web server cluster systems based on proportional hazards model

Journal of Southeast University(English Edition) 2018年第2期34卷 187-190页

作者： Hou Chunyan Wang Jinsong Chen Chen School of Computer Science and Engineering Tianjin University of TechnologyTianjin 300384China College of Computer and Control Engineering Nankai UniversityTianjin 300071China

An approach for web server cluster(WSC)reliability and degradation process analysis is *** reliability process is modeled as a non-homogeneous Markov process(NHMH)composed of several non-homogeneous Poisson processes(NHPPs).The arrival rate of each NHPP corresponds to the system software failure rate which is expressed using Cox s proportional hazards model(PHM)in terms of the cumulative and instantaneous load of the *** cumulative load refers to software cumulative execution time,and the instantaneous load denotes the rate that the users requests arrive at a *** result of reliability analysis is a time-varying reliability and degradation process over the WSC ***,the evaluation experiment shows the effectiveness of the proposed approach.

关键词： web server cluster load-sharing proportional hazards model reliability software aging

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When autonomous systems meet accuracy and transferability through AI: A survey

arXiv

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arXiv 2020年

作者： Zhang, Chongzhen Wang, Jianrui Yen, Gary G. Zhao, Chaoqiang Sun, Qiyu Tang, Yang Qian, Feng Kurths, Jürgen Key Laboratory of Advanced Control and Optimization for Chemical Process Ministry of Education East China University of Science and Technology Shanghai200237 China School of Electrical and Computer Engineering Oklahoma State University StillwaterOK74075 United States Potsdam Institute for Climate Impact Research Potsdam14473 Germany Institute of Physics Humboldt University of Berlin Berlin12489 Germany

With widespread applications of artificial intelligence (AI), the capabilities of the perception, understanding, decision-making and control for autonomous systems have improved significantly in the past years. When autonomous systems consider the performance of accuracy and transferability, several AI methods, like adversarial learning, reinforcement learning (RL) and meta-learning, show their powerful performance. Here, we review the learning-based approaches in autonomous systems from the perspectives of accuracy and transferability. Accuracy means that a well-trained model shows good results during the testing phase, in which the testing set shares a same task or a data distribution with the training set. Transferability means that when a well-trained model is transferred to other testing domains, the accuracy is still good. Firstly, we introduce some basic concepts of transfer learning and then present some preliminaries of adversarial learning, RL and meta-learning. Secondly, we focus on reviewing the accuracy or transferability or both of them to show the advantages of adversarial learning, like generative adversarial networks (GANs), in typical computer vision tasks in autonomous systems, including image style transfer, image super-resolution, image deblurring/dehazing/rain removal, semantic segmentation, depth estimation, pedestrian detection and person re-identification (re-ID). Then, we further review the performance of RL and meta-learning from the aspects of accuracy or transferability or both of them in autonomous systems, involving pedestrian tracking, robot navigation and robotic manipulation. Finally, we discuss several challenges and future topics for using adversarial learning, RL and meta-learning in autonomous systems. Copyright © 2020, The Authors. All rights reserved.

关键词： Reinforcement learning

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Particle size estimation of pulverized fuel in pneumatic pipelines using electrostatic sensing techniques 22

Particle size estimation of pulverized fuel in pneumatic pip...

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22nd World Congress of the International Measurement Confederation, IMEKO 2018

作者： Qian, X. Wei, X. Yan, Y. Shi, D. School of Control and Computer Engineering North China Electric Power University Beijing102206 China School of Engineering and Digital Arts University of Kent Canterbury KentCT2 7NT United Kingdom

Particle size measurement of pulverized fuel (PF) provides useful data for efficiency improvement of a pulverizing system, optimization of fuel combustion and emission reduction on a fired power plant. This paper presents an experimental study of particle size estimation of pneumatically conveyed PF through electrostatic sensing. An electrostatic sensor head consisting of two narrow and one wide ring-shaped electrodes is designed and implemented to measure the PF velocity and quantify the features of the sensor signals. Experimental tests using particles with three different size ranges were conducted on the vertical pipe section of a 74 mm bore gas-solid two-phase flow test facility under various flow conditions. Test results show that the root-mean-square magnitude and power spectral density of electrostatic signals vary with particle size. For the same air velocity, the small change in particle velocity is an indication of particle size as the particle velocity decreases when the particle size is larger. The proposed method is capable of estimating PF particle size and has the potential to offer considerable advantages over its counterparts in power plant applications. © 2018 Institute of Physics Publishing. All rights reserved.

关键词： Particle size

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Coordinated Dispatching and Frequency control Strategy of Power Systems with Large Scale Wind Power Penetration

Coordinated Dispatching and Frequency Control Strategy of Po...

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Chinese Automation Congress (CAC)

作者： Jianhua Zhang Rui Shan Fei Xu Bo Hu Guiping Zhou Guolian Hou Congzhi Huang State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources North China Electric Power University Beijing China School of Control and Computer Engineering North China Electric Power University Beijing China Tsinghua University Beijing China State Grid Liaoning Electric Power Supply Co. Ltd. Shenyang China

ISBN: (数字)9781728176871

ISBN: (纸本)9781728176888

In this paper, a coordinated dispatching and frequency control strategy is presented for wind turbines (WTs) participating in frequency regulation from three levels. Firstly, the coordinated dispatching and frequency control strategy among multi-source power generation systems is given with the aid of the wind power installed capacity penetration rate; Secondly, the coordinated distribution strategy among the wind farms is presented by combing the incremental active power reference with parameters tuning method; Thirdly, the coordinated control is investigated by integrating droop control, inertia control and de-load control for each WT. Simulation results demonstrate that the proposed coordinated dispatching and frequency control strategy can obtain better frequency regulation performance for power systems with large scale wind power penetration.

关键词： Frequency control Wind turbines Wind power generation Dispatching Wind speed Wind farms Rotors

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Learning better generative models for dexterous, single-view grasping of novel objects

arXiv

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arXiv 2019年

作者： Kopicki, Marek S. Belter, Dominik Wyatt, Jeremy L. School of Computer Science University of Birmingham Edgbaston BirminghamB15 2TT United Kingdom Institute of Control and Information Engineering Poznan University of Technology Poland

This paper concerns the problem of how to learn to grasp dexterously, so as to be able to then grasp novel objects seen only from a single view-point. Recently, progress has been made in data-efficient learning of generative grasp models which transfer well to novel objects. These generative grasp models are learned from demonstration (LfD). One weakness is that, as this paper shall show, grasp transfer under challenging single view conditions is unreliable. Second, the number of generative model elements rises linearly in the number of training examples. This, in turn, limits the potential of these generative models for generalisation and continual improvement. In this paper, it is shown how to address these problems. Several technical contributions are made: (i) a view-based model of a grasp;(ii) a method for combining and compressing multiple grasp models;(iii) a new way of evaluating contacts that is used both to generate and to score grasps. These, together, improve both grasp performance and reduce the number of models learned for grasp transfer. These advances, in turn, also allow the introduction of autonomous training, in which the robot learns from self-generated grasps. Evaluation on a challenging test set shows that, with innovations (i)-(iii) deployed, grasp transfer success rises from 55.1% to 81.6%. By adding autonomous training this rises to 87.8%. These differences are statistically significant. In total, across all experiments, 539 test grasps were executed on real objects. Copyright © 2019, The Authors. All rights reserved.

关键词： Machine learning

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Graph wavelet neural network

arXiv

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arXiv 2019年

作者： Xu, Bingbing Shen, Huawei Cao, Qi Qiu, Yunqi Cheng, Xueqi CAS Key Laboratory of Network Data Science and Technology Institute of Computing Technology Chinese Academy of Sciences School of Computer and Control Engineering University of Chinese Academy of Sciences Beijing China

We present graph wavelet neural network (GWNN), a novel graph convolutional neural network (CNN), leveraging graph wavelet transform to address the shortcomings of previous spectral graph CNN methods that depend on graph Fourier transform. Different from graph Fourier transform, graph wavelet transform can be obtained via a fast algorithm without requiring matrix eigendecomposition with high computational cost. Moreover, graph wavelets are sparse and localized in vertex domain, offering high efficiency and good interpretability for graph convolution. The proposed GWNN significantly outperforms previous spectral graph CNNs in the task of graph-based semi-supervised classification on three benchmark datasets: Cora, Citeseer and Pubmed. Copyright © 2019, The Authors. All rights reserved.

关键词： Wavelet transforms

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An Improved Multiple to One Fully Homomorphic Encryption on the Integers

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Journal of computer and Communications 2018年第9期6卷 50-59页

作者： Chaoju Hu Jianwei Zhao School of Control & Computer Engineering North China Electric Power University Baoding China

The public key of the integer homomorphic encryption scheme which was proposed by Van Dijk et al. is long, so the scheme is almost impossible to use in practice. By studying the scheme and Coron’s public key compression technique, a scheme which is able to encrypt n bits plaintext once was obtained. The scheme improved the efficiency of the decrypting party and increased the number of encrypting parties, so it meets the needs of cloud computing better. The security of the scheme is based on the approximate GCD problem and the sparse-subset sum problem.

关键词： Fully Homomorphic Encryption Multipart to One Fully Homomorphism Encryption Approximate GCD Problem Sparse-Subset Sum Problem

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Analysis onto Competence-oriented engineering Education System:A Perspective into the Differences between Chinese and German engineering Education

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计算机教育 2018年第12期 91-97页

作者： Xin Zhang Ying Zhang Hua Li School of Computer Science and Technology Changchun University of Science and Technology School of Control and Computer Engineering North China Electric Power University

Through engineering education, a set of didactical programs and activities are planned to bring the essential knowledge, expertise and training to the students from the corresponding discipline and make them gain the competence of coping with various professional problems independently. Although holding the same views on the importance of developing competence, China and Germany construct the respective education systems in consideration of the different circumstances. In this paper, we propose the analysis onto the engineering education systems in the two countries and characterize the systems as competence-oriented. Through reflecting the differences, we mainly propose three suggestions as the theoretical contribution for deriving advantages from the German engineering education system.

关键词： competence-oriented principles of training students education system comparison

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Combining Lattice-Based Planning and Path Optimization in Autonomous Heavy Duty Vehicle Applications

Combining Lattice-Based Planning and Path Optimization in Au...

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2018 IEEE Intelligent Vehicles Symposium, IV 2018

作者： Oliveira, Rui Cirillo, Marcello Mårtensson, Jonas M. Wahlberg, Bo Department of Automatic Control School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Stockholm Sweden Scania Autonomous Transport Solutions Sodertalje Sweden

ISBN: (纸本)9781538644522

Lattice-based motion planners are an established method to generate feasible motions for car-like vehicles. However, the solution paths can only reach a discretized approximation of the intended goal pose. Moreover, they can be optimal only with respect to the actions available to the planner, which can result in paths with excessive steering. These drawbacks have a negative impact when used in real systems. In this paper we address both drawbacks by integrating a steering method into a state-of-the-art lattice-based motion planner. Un- like previous approaches, in which path optimization happens in an a posteriori step after the planner has found a solution, we propose an interleaved execution of path planning and path optimization. The proposed approach can run in real-time and is implemented in a full-size autonomous truck, and we show experimentally that it is able to greatly improve the quality of the solutions provided by a lattice planner. © 2018 IEEE.

关键词： Motion planning

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A Self-learning Model to Detect Icing Alarm Based on Multi-agents for Wind Park

A Self-learning Model to Detect Icing Alarm Based on Multi-a...

引用

作者： Ting-shun LI Ze-san LIU Yuan-yi XIA School of Control and Computer Engineering North China Electric Power University China Power Information Technology Co. Ltd. State Grid Jiangsu Information & Telecommunication Company

In the middle to high latitudes, the wind turbine often encounters icing on the blade surface in winter, which can not only lower the power energy generation, but also sometimes damages the wind turbine, increasing maintain cost. To improve wind turbine blade icing prediction accuracy, since every wind turbine in wind park is installed different place and has different performance, it's impossible for each wind turbine to use one model to detect blade icing. According to the characteristics of various types wind turbine in wind park, this paper provides a multi-agents model to improve the accuracy of detecting wind turbine blade icing alarm based on machine learning. Every agent is self-learned from recent historic data of some type wind turbine in wind period by machine learning algorithm, hence different agent must have different characteristic of the wind turbine type in different circumstance so that the agent can better predict the blade icing. When each agent could detect icing better, multi-agent to detect icing in wind park would improve more precise.

关键词： Blade Icing Alarm Multi-agent Self-learning Logistic Regression

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