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作者： Wu, Junfeng Chen, Honglong Lou, Wei Wang, Zhibo Wang, Zhi State Key Lab. of Industrial Control Technology Zhejiang University China Dept. of Computing Hong Kong Polytechnic University Hong Kong Hong Kong Dept. of Electronic and Computer Engineering Hong Kong University of Science and Technology Hong Kong Hong Kong

ISBN: (纸本)9780769541341

Node localization becomes an important issue in the wireless sensor network as its broad applications in environment monitoring, emergency rescue and battlefield surveillance, etc. Basically, the DV-Hop localization mechanism can work well with the assistance of beacon nodes that have the capability of self-positioning. However, if the network is invaded by a wormhole attack, the attacker can tunnel the packets via the wormhole link to cause severe impacts on the DV-Hop localization process. The distance-vector propagation phase during the DVHop localization even aggravates the positioning result, compared to the localization schemes without wormhole attacks. In this paper, we analyze the impacts of wormhole attack on DV-Hop localization scheme. Based on the basic DV-Hop localization process, we propose a label-based secure localization scheme to defend against the wormhole attack. Simulation results demonstrate that our proposed secure localization scheme is capable of detecting the wormhole attack and resisting its adverse impacts with a high probability. © 2010 IEEE.

关键词： Sensor nodes

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Sensor selection for an accurate closed form localization in cognitive radio networks: The trade-off between model accuracy and geometry structure

Sensor selection for an accurate closed form localization in...

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IEEE Conference on industrial Electronics and Applications (ICIEA)

作者： Bin Zhao Kai Ma Xinping Guan Wengdong Xiao Key Laboratory of Industrial Computer Control Engineering of Hebei province Institute of Electrical Engineering Yanshan University슠 Qinhuangdao China Institute for Infocomm Research Agency for Science Technology and Research Singapore

In cognitive radio networks (CRNs), localization of primary user is the key problem for location-aware spectrum allocation. In order to improve spectrum utilization and decrease interference to primary users, localization should be computationally efficient and as accurate as possible. Based on an accurate closed form localization method, the tradeoff between model accuracy and geometry structure is analyzed. By selecting part of the secondary users, the estimation accuracy is increased and the computation amount is reduced at the same time. Finally, the simulations are performed and the proposed tradeoff analysis is done. The simulation results show the significant improvement on the localization performance by sensor selection.

关键词： Accuracy Geometry Cognitive radio Computational modeling Estimation Signal to noise ratio

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Performance analysis of object tracking algorithm

Performance analysis of object tracking algorithm

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International Conference on Image Analysis and Signal Processing, IASP

作者： Rongtai Cai Qingxiang Wu Ping Wang Xuguang Zhang Shuo Hu School of Physics Optics Electronic Science and Technology Fujian Normal University Fuzhou China Key Laboratory of Industrial Computer Control Engineering Yanshan University Qinhuangdao Hebei China

This paper analyzes the performance of object tracking algorithms. The issues that affect precision in object tracking are analyzed first and how the parameters in tracking algorithms affect the precision in object tracking are introduced. Then, the time complexity of those object-tracking algorithms is discussed. At last, the holistic analysis and evaluation of these object-tacking algorithms are parsed from application range, tracking precision and time complexity.

关键词： Adaptive filters Complexity theory Radar tracking Target tracking Filtering algorithms Least squares approximation Prediction algorithms

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Wind turbine bearing condition monitoring based on high frequency resonance method

Wind turbine bearing condition monitoring based on high freq...

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International Conference on Electronics, Communications and control (ICECC)

作者： Xueyan Zhang Shenggang Yang Xiaoli Li Department of Information Technology Ningbo TV & Radio University Ningbo Zhejiang China Key Laboratory of Industrial Computer Control Engineering of Hebei Province Institute of Electrical Engineering Yanshan University Qinhuangdao China

Bearing is the most frequently used component in a wind turbine, and its' faults would lead to completely stall of a machine. Therefore, bearing Fault Diagnosis is an important part of condition monitoring in a wind turbine. This paper presented a High Frequency Resonance (HFR) method to implement bearing fault detection and fault diagnosis. This technique extracted the amplitude and frequency modulations of the vibration signals which measured from a wind turbine system. For the amplitude demodulation is inherent in the vibration signals, the fault frequency will be detected from the spectrum of the transformed original signals. And the effectiveness of this approach has been validated by simulated signal and experimental data.

关键词： Vibrations Resonant frequency Wind turbines Noise measurement Harmonic analysis Power harmonic filters Fault detection

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A Ship Power Sharing Strategy Based on Shapley Value Method and Cartel Mechanism

A Ship Power Sharing Strategy Based on Shapley Value Method ...

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Complex Systems and Intelligent Science (CSIS-IAC), International Annual Conference on

作者： Zhengxu Zhang Jie Yang Kai Ma Shiliang Guo Hui Li School of Electrical Engineering Yanshan University Qinhuangdao China Key Laboratory of Power Electronics for Energy Conservation and Drive Control of Hebei Province Yanshan University Qinhuangdao China Key Laboratory of Industrial Computer Control Engineering of Hebei Province Yanshan University Qinhuangdao China Key Laboratory of Intelligent Control and Neural Information Processing of the Ministry of Education Yanshan University Qinhuangdao China

ISBN: (数字)9798331504755

ISBN: (纸本)9798331504762

With the development of the maritime industry, the number and capacity of existing port cold-ironing (CI) equipment can no longer meet the power demand of ships during berthing, resulting in significant carbon emissions from ships within the port area. Therefore, a ship power sharing strategy based on Shapley value method and Cartel mechanism is proposed. Firstly, the rolling optimization model of ship power scheduling is established to adjust the ship power scheduling strategy according to the real-time information. Secondly, the cooperative game model of ship power sharing is established, and the cost sharing among cooperative ships is realized by Shapley value method. Finally, in order to reduce the situation that ships increase their own profits by deviating from cooperation and affect the overall profits, this paper introduces Cartel mechanism to punish the behavior of deviating from cooperation. The simulation results show that the power sharing strategy proposed in this paper can reduce the total ship cost and carbon emission by 5.28% and 3.78%, respectively. The introduction of Cartel mechanism can increase the cost of non-cooperative behavior, thus ensuring that all ships take cooperative behavior. The power sharing strategy based on Shapley method and Cartel mechanism proposed in this paper is helpful to the construction of green ports.

关键词： Costs Job shop scheduling Optimization models Simulation Carbon dioxide Microgrids Games Seaports Real-time systems Marine vehicles

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VTube: Towards the media rich city life with autonomous vehicular content distribution

VTube: Towards the media rich city life with autonomous vehi...

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Annual IEEE Communications Society Conference on Sensor and Adhoc Communications and Networks

作者： Luan, Tom H. Cai, Lin X. Chen, Jiming Shen, Xuemin Bai, Fan Department of Electrical and Computer Engineering University of Waterloo Waterloo ON N2L 3G1 Canada State Key Lab. of Industrial Control Technology Zhejiang University Hangzhou 310027 China Electrical and Controls Integration Lab. General Motors Global R and D Warren MI 48105 United States

ISBN: (纸本)9781457700934

The copious social and user generated contents, like Facebook and Youtube, are re-shaping the way people share, access, and digest information. Although flourishing in Internet, content sharing services are still considered expensive and not ready for mobile users of vehicular networks. In this paper, we propose VTube, an autonomous and cost-effective infrastructure, to facilitate the localized content publish/subscribe in an urban area. VTube relies on the distributed low-cost light-weight storage buffers, namely roadside buffer, installed in the city facilities, such as stores, museums, cafeteria, etc., to cache and publish contents for mobile users. The contents at different storage buffers are then transported to different locations by moving vehicles and cached collaboratively in both vehicles and storage buffers across the city. In this work, we unfold the design of VTube by first presenting the detailed design principles and practices of VTube. Given the content availability and capacity of the buffer storage, we then develop a mathematical model to evaluate the mean download delay of mobile users. Using the delay as an input, we formulate the content replication problem in roadside buffers as a stochastic programming problem to attain the mean system-wide minimum download delay. Finally, we propose a fully distributed random walk based algorithm to solve the optimization problem. Extensive simulations demonstrate that VTube can minimize the download delay of users because of the exploitation of vehicle mobility and distributed buffer storage at different locations. © 2011 IEEE.

关键词： Buffer storage

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Integral Sliding Mode control for PMSM with Uncertainties and Disturbances via Nonlinear Disturbance Observer

Integral Sliding Mode Control for PMSM with Uncertainties an...

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Chinese control Conference (CCC)

作者： Jianxiong Li Hongmei Ren Songhua Wang Yiming Fang Research Center of the Ministry of Education for Intelligent Control System and Intelligent Equipment Yanshan University Qinhuangdao China The Key Lab of Industrial Computer Control Engineering of Yanshan University Qinhuangdao China

ISBN: (数字)9789881563903

ISBN: (纸本)9781728165233

In this paper, a nonlinear disturbance observer-based (NDOB) integral sliding mode control (SMC) algorithm is proposed for speed control of permanent magnet synchronous motor (PMSM) in the presence of uncertain parameters and external time-varying load toque. Firstly, three nonlinear disturbance observers (NDOs) are constructed to estimate the lumped disturbances comprising of uncertain parameters and/or disturbances in speed loop and two current loops, respectively. Secondly, an integral sliding mode controller is developed based on the NDOs. It can be proved that the resulting closed loop system is asymptotically stable and the speed tracking error converges to zero asymptotically in theory. Finally, experiment results are given to validate the proposed control method.

关键词： Torque Disturbance observers Sliding mode control Uncertainty Velocity control Mathematical model Upper bound

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Fast Covariance Matching Based on Genetic Algorithm

Fast Covariance Matching Based on Genetic Algorithm

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International Conference on Wireless Communications, Networking and Mobile Computing (WiCom)

作者： Xuguang Zhang Shuo Hu Limin Zhang Yuanhao Wu Key Laboratory of Industrial Computer Control Engineering of Hebei Province Institute of Electrical Engineering Yanshan University슠 Qinhuangdao China Changchun Institute of Optics Fine Mechanics and Physics Chinese Academy and Sciences Changchun China

This paper proposes an effective framework to boost the efficiency of covariance matching. In this framework, covariance matrices are used to match object in complex environment by fusing multiple features. Then, Genetic Algorithm (GA) is employed to improve the processing speed of covariance matching. To take advantage of the property of GA for the optimization in large search spaces to covariance matching, a fitness function is designed using the distances between the covariance matrices of model and candidate regions. Experimental results show that the proposed approach can improve the processing speed of covariance matching observably. The computing speed of the proposed method is at least 7 times than that of exhaustive searching.

关键词： Covariance matrix Gallium Feature extraction Pixel Robustness Genetic algorithms Computational modeling

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Adaptive position tracking control for electro-hydraulic servo system with input saturation

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ICIC Express Letters 2012年第10期6卷 2699-2704页

作者： Shi, Shengli Fang, Yiming Li, Jianxiong Jiao, Zongxia Key Lab of Industrial Computer Control Engineering of Hebei Province Yanshan University No. 438 Hebei Ave. Qinhuangdao 066004 China College of Science Yanshan University No. 438 Hebei Ave. Qinhuangdao 066004 China College of Automation Beijing University of Aeronautics and Astronautics No. 37 Xueyuan Road Haidian Dist. Beijing 100191 China

An adaptive controller is proposed for the position tracking of an electrohydraulic servo system with uncertainties and input saturation. Firstly, fuzzy logic is employed to approximate the unknown nonlinear uncertainties. And a nonlinear tracking controller is developed by combining the adaptive backstepping with H∞ control method. In addition, in order to tackle the input constraint, an auxiliary design system based on Lyapunov method is presented. The proposed controller not only can effectively avoid the problem of input saturation, but also can guarantee that the output tracking error satisfies the H-infinity performance. Finally, the simulation results testify the effectiveness of the proposed method. © 2012 ISSN.

关键词： Tracking (position)

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Weakly Supervised and Semi-Supervised Semantic Segmentation Makes Full Use of a Small Amount of labeled Data

SSRN

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SSRN 2023年

作者： Zhang, Wenming Li, Yaqian Li, Haibin Wang, Zhe Engineering Research Center Ministry of Education for Intelligent Control System and Intelligent Equipment Yanshan University Qinhuangdao China Key Laboratory of Industrial Computer Control Engineering of Hebei Province Yanshan University Qinhuangdao China School of Electrical Engineering Yanshan University Qinhuangdao066004 China

Semi-supervised and weakly supervised semantic segmentation are very challenging tasks and have been studied in recent years. The purpose is to reduce the high cost of semantic segmentation label production. In this paper, we propose a weakly supervised assistant supervision strategy (ASS), which introduces more semantic segmentation for the shallow network by introducing additional classification tasks to the classification network, and enhances the fusion of shallow features and deep features. In addition, we propose a multi-scale global correlation module (MSG). This module uses the correlation degree of different scale regions to improve the weight of the nondiscriminative part, which solves the problem of insufficient CAMs activation. In most scenarios, weak supervision and semi-supervision are inseparable. We creatively propose a training strategy that integrates semi-supervision and weak supervision, adding pixel-level supervision in the training process of weak supervision to give full play to the role of pixel-level annotation. Extensive experiments on PASCAL VOC 2012 dataset show that our weakly supervised training strategy achieves the state of the art, and the combination of weakly supervised and semi-supervised training strategy can make more effective use of pixel-level labels. © 2023, The Authors. All rights reserved.

关键词： Semantic Segmentation

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