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IEEE International Geoscience and Remote Sensing Symposium

作者： Yanxia Wu Ye Yuan Jian Guan Libo Yin Jinyong Chen Ge Zhang Pengming Feng College of Computer Science and Technology Harbin Engineering University Harbin China China Industrial Control Systems Cyber Emergency Response Team Beijing China The 54th Research Institute of China Electronics Technology Group Corporation Shijiazhuang China State Key Laboratory of Space-Ground Integrated Information Technology Beijing China

Ship classification using synthetic aperture radar (SAR) imagery is a challenge problem in maritime surveillance. Because of the scale limitation of ship targets in SAR image, convolutional neural networks (CNNs) can not achieve similar performance as for natural image classification. In this paper, we propose a joint CNNs framework for small-scale ship targets classification in SAR image, where a generator and a classifier are jointly connected. The generator can reconstruct the small-scale low-resolution (LR) images to large-scale super-resolution (SR) images, and the classifier is used for ship classification. A novel joint loss optimization strategy is introduced to solve the problem, where an MSE-based content loss is employed to generate high quality SR images, and a classification loss is applied to enable the generator and the classifier to be trained in a joint way. Experiments are conducted to demonstrate the superior performance of our proposed method, as compared with the state-of-the-art methods.

关键词： Marine vehicles Generators Synthetic aperture radar Containers Radar polarimetry Convolutional neural networks Training

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Emergence of the First Strains of SARS-CoV-2 Lineage B.1.1.7 in Romania: Genomic Analysis

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JMIRx med 2021年第3期2卷 e28049页

作者： Andrei Lobiuc Mihai Dimian Olga Sturdza Roxana Filip Mihai Covasa Department of Human Health and Development College of Physical Exercise and Sport Stefan cel Mare University of Suceava Suceava Romania. Department of Computers Electronics and Automation College of Electrical Engineering and Computer Science Stefan cel Mare University of Suceava Suceava Romania. Integrated Center for Research Development and Innovation in Advanced Materials Nanotechnologies and Distributed Systems for Fabrication and Control Stefan cel Mare University of Suceava Suceava Romania. Suceava County Emergency Hospital Suceava Romania.

BACKGROUND:The United Kingdom reported the emergence of a new and highly transmissible SARS-CoV-2 variant (B.1.1.7) that rapidly spread to other countries. The impact of this new mutation-which occurs in the S protein-on infectivity, virulence, and current vaccine effectiveness is still under evaluation. OBJECTIVE:The aim of this study is to sequence SARS-CoV-2 samples of cases in Romania to detect the B.1.1.7 variant and compare these samples with sequences submitted to GISAID. METHODS:SARS-CoV-2 samples were sequenced and amino acid substitution analysis was performed using the CoV-GLUE platform. RESULTS:We have identified the first cases of the B.1.1.7 variant in samples collected from Romanian patients, of which one was traced to the region of the United Kingdom where the new variant was originally sequenced. Mutations in nonstructural protein 3 (Nsp3; N844S and D455N) and ORF3a (L15F) were also detected, indicating common ancestry with UK strains as well as remote connections with strains from Nagasaki, Japan. CONCLUSIONS:These results indicate, for the first time, the presence and characteristics of the new variant B.1.1.7 in Romania and underscore the need for increased genomic sequencing in patients with confirmed COVID-19.

关键词： COVID-19 Romania case study epidemiology genetics genome impact infectious disease lineage mutation sequencing spread strain transmission variant virology virus

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Fuzzy Clustering based Anomaly Detection for Distributed Multi-view Data

Fuzzy Clustering based Anomaly Detection for Distributed Mul...

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IEEE International Conference on Fuzzy Systems

作者： Hongmei Wang Tianhua Chen Hongtao Wang Xuqiang Shao Pan Su Science and Technology College North China Electric Power University China Department of Computer Science University of Huddersfield UK School of Control and Computer Engineering North China Electric Power University China

Anomaly detection aims to identify the abnormal instances, whose behavior deviates significantly from the others. Nowadays owing to the existence of diverse data generation sources, different attributes of the same instances may be located on distributed parties forming a multi-view dataset. Thus multiview anomaly detection has become a key task to discover outliers across various views. Traditionally, to perform multiview anomaly detection, one needs to centralize data instances from all views into a single machine. However, in many real-world scenarios, it is impractical to send data from diverse views to a master machine due to the privacy issues. Inspired by this, we propose a fuzzy clustering based distributed approach for multiview anomaly detection that simultaneously learns a membership degree matrix for each view and then detects anomalies for all parties. Specifically, we first introduce a combined fuzzy c-means clustering method for multi-view data and then design an anomaly measurement criterion to quantify the abnormal score from membership degree matrix. To solve the proposed model, a protocol is provided to unify all parties performing a well-designed optimization in an iterative way. Experiments on three datasets with different anomaly settings demonstrate the effectiveness of our approach.

关键词： Anomaly detection Distributed databases Optimization Protocols Data privacy Privacy Entropy

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Shell analysis and optimisation of a pure electric vehicle power train based on multiple software

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World Electric Vehicle Journal 2018年第4期9卷

作者： Guo, Shaocui Tong, Xiangrong Yang, Xu Yantai Vocational College Shandong Yantai264005 China School of computer and control engineering Yantai University Shandong Yantai264005 China Department of Computer Science and Technology Tongji University Shanghai201804 China

Motor end cover mounting fracture is a problem recently encountered by novel pure electric vehicles. Regarding the study of the traditional vehicle engine mount bracket and on the basis of the methods of design and optimisation available, we have analysed and optimised the pure electric vehicle end cover mount system. Multi-body dynamic software and finite element software have been combined. First, we highlight the motor end cover mount bracket fracture engineering problems, analyse the factors that may produce fracture, and propose solutions. By using CATIA software to establish a 3D model of the power train mount system, we imported it into ADAMS multi-body dynamic software, conducted 26 condition analysis, obtained five ultimate load conditions, and laid the foundations for subsequent analysis. Next, a mount and shell system was established by the ANSYS finite element method, and modal, strength, and fatigue analyses were performed on the end cover mount. We found that the reason for fracture lies in the intensity of the end cover mount joint, which leads to the safety factor too small and the fatigue life not being up to standard. The main goal was to increase the strength of the cover mount junction, stiffness, safety coefficient, and fatigue life. With this aim, a topology optimisation was conducted to improve the motor end cover. A 3D prototype was designed accordingly. Finally, stiffness, strength, modal, and fatigue were simulated. Our simulation results were as follows. The motor end cover suspension stiffness increases by 20%, the modal frequency increases by 2.3%, the quality increases by 3%, the biggest deformation decreases by 52%, the maximum stress decreases by 28%, the minimum safety factor increases by 40%, and life expectancy increases 50-fold. The results from sample and vehicle tests highlight that the component fracture problem has been successfully solved and the fatigue life dramatically improved. © 2018 by the authors.

关键词： Fracture

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State-control-limit-based rejuvenation modelling and optimisation of the virtualised cloud server

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International Journal of Reliability and Safety 2018年第4期12卷 406-428页

作者： Dang, Weichao Zeng, Jianchao College of Electrical and Information Engineering Lanzhou University of Technology Lanzhou730050 China Division of Industrial and System Engineering Taiyuan University of Science and Technology Taiyuan030024 China School of Computer Science and Control Engineering North University of China Taiyuan030051 China

Software rejuvenation modelling and optimisation of the virtualised cloud server has been studied. A software rejuvenation policy on the virtual machines and the virtual machine monitor has been proposed in order to ensure high availability of the virtualised cloud server. The multi-component system, composed of the virtual machines and the virtual machine monitor, which are structurally dependent, has been reduced to the multiple two-component systems. The state-control-limit-based rejuvenation policy has been proposed and the joint probability density of the degraded state of the two-component VM-VMM has been derived. Furthermore, the solution to the joint probability density has been proposed. Finally, the stationary unavailability of the virtualised cloud server has been modelled. Numerical experiments have verified the correctness of the probability density function and the feasibility of the rejuvenation policy. The state-control-limit-based rejuvenation policy leads to lower unavailability of the virtualised cloud server in comparison with the lifetime-based rejuvenation policy. Copyright © 2018 Inderscience Enterprises Ltd.

关键词： Availability

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Optimization of software rejuvenation policy based on state-control-limit

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International Journal of Performability engineering 2018年第2期14卷 210-222页

Software Rejuvenation is a proactive software control technique used to improve computing system performance when a system suffers from software aging. In this paper, a state-control-limit-based rejuvenation policy with periodical inspection has been proposed. The steady-state system availability model has been constructed based on the semi-renewal process. The steady-state probability density of degradation system stated as a function of the inspection interval and the rejuvenation threshold have been derived. The average unavailable time of when a soft failure occurs within an inspection cycle has been taken into account to calculate the steady-state system availability. Finally, the system availability with corresponding optimal inspection time interval and rejuvenation threshold have been obtained numerically. © 2018 Totem Publisher, Inc. All rights reserved.

关键词： Availability

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Group maintenance strategy for stochastic selective maintenance

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International Journal of Wireless and Mobile Computing 2018年第4期14卷 362-368页

作者： Zhao, Jing Zeng, Jianchao Division of Industrial and System Engineering Taiyuan University of Science of Technology Taiyuan030024 China College of Information Engineering Guangdong Mechanical and Electrical Polytechnic Guangzhou510515 China School of Computer Science and Control Engineering North University of China Taiyuan030051 China

Selective maintenance is often applied to many industrial environments when the maintenance actions are performed between sequence missions. When the length of maintenance or work mission time is stochastic and there are multiple maintenance workers with different capacity, previous works to determine maintenance and mission times are unsuitable for it. Assuming that the time of work mission is random and maintenance time is determined, to maximise system reliability of next work mission, this paper proposes a stochastic model for a two-state system comprising several series-parallel components with multiple maintenance workers under the maintenance time limit. The optimal maintenance plan is obtained by hybrid intelligent optimisation algorithm. The validity and feasibility of the model are verified by the simulation. Copyright © 2018 Inderscience Enterprises Ltd.

关键词： Stochastic models

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State-control-limit-based rejuvenation modeling of virtualized cloud server

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International Journal of Performability engineering 2018年第3期14卷 473-482页

Software rejuvenation modeling of the virtualized Cloud Server has been studied. A software rejuvenation policy on the virtual machines and the virtual machine monitor has been proposed in order to ensure high availability of the virtualized Cloud Server. The multi-component system, composed of the virtual machines and the virtual machine monitor, which are structurally dependent, has been reduced to the multiple two-component systems. The state-control-limit-based rejuvenation policy has been proposed and the stationary probability density of the two component system state has been derived. Furthermore, the stationary unavailability of the virtualized Cloud Server has been modeled. Numerical experiments have verified the correctness of the probability density function and the feasibility of the rejuvenation policy. The state-control-limit-based rejuvenation policy leads to lower unavailability of the virtualized Cloud Server in comparison with the lifetime-based rejuvenation policy. © 2018 Totem Publisher, Inc. All rights reserved.

关键词： Virtual machine

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Stochastic LQ Problem with Delayed control 36

Stochastic LQ Problem with Delayed Control

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第36届中国控制会议

作者： Yuan-Hua Ni Cedric Ka-Fai Yiu Huanshui Zhang Ji-Feng Zhang College of Computer and Control Engineering Nankai University Department of Applied Mathematics The Hong Kong Polytechnic University School of Control Science and Engineering Shandong University Academy of Mathematics and Systems Science Chinese Academy of Sciences

ISBN: (纸本)9781538629185

A discrete-time stochastic LQ problem with multiplicative noises and state transmission delay is studied in this paper,which does not require any definiteness constraint on the cost weighting matrices. Necessary and sufficient conditions are derived for the case with a fixed time-state initial pair. A set of coupled discrete-time Riccati-like equations can be derived to characterize the existence and the form of the delayed optimal control. Furthermore, the convexity of the cost functional is fully characterized via certain properties of the solution of the Riccati-like equations.

关键词： Indefinite stochastic linear-quadratic optimal control input delay forward-backward stochastic difference equation convexity

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Adaptive neural output consensus control of stochastic nonlinear strict-feedback multi-agent systems

Adaptive neural output consensus control of stochastic nonli...

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2018 Australian and New Zealand control Conference, ANZCC 2018

作者： Yang, Yang Miao, Songtao Xu, Chuang Yue, Dong Tan, Jie Tian, Yu-Chu College of Automation College of Artificial Intelligence Nanjing University of Posts and Telecommunications Nanjing210023 China Institute of Advanced Technology Nanjing University of Posts and Telecommunications Nanjing210023 China Jiangsu Engineering Laboratory of Big Data Analysis and Control for Active Distribution Network Nanjing University of Posts and Telecommunications Nanjing China School of Electrical Engineering and Computer Science Queensland University of Technology BrisbaneQLD4001 Australia

ISBN: (纸本)9781538666173

An adaptive neural output consensus control issue is considered for stochastic nonlinear strict-feedback multi-agent systems (MASs). The traditional backstepping framework is employed combing with the graph theory, as well as neural networks (NNs) technology. NNs are utilized for the approximation of unknown functions, and the Itô's lemma is used to deal with stochastic dynamics of the system. It is proved that all signals remain bounded in probability and that the tracking errors of all followers converge to a small neighborhood of the origin in the sense of mean quartic value by suitable choice of parameters. A simulation example is provided. © 2018 IEEE.

关键词： Multi agent systems

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