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An Image Reconstruction Algorithm Based on the Regularized Minimax Estimation for Electrical Capacitance Tomography

Journal of Mathematical Imaging and Vision 2010年第3期39卷 269-291页

作者： Lei, Jing Liu, Shi Key Laboratory of Condition Monitoring and Control for Power Plant Equipment Ministry of Education North China Electric Power University Beijing China School of Control and Computer Engineering North China Electric Power University Beijing China

Electrical capacitance tomography (ECT) is considered as a promising process tomography (PT) technology. Image reconstruction algorithms play an important role in the successful applications of ECT. In this paper, a generalized objective functional, which has been developed using the combinational minimax estimation and a generalized stabilizing functional, is proposed. The Newton algorithm is employed to solve the proposed objective functional. The algorithm is tested by the noise-free capacitance data and the noise-contaminated capacitance data, excellent numerical performances and good results are observed. In the cases considered in this paper, the quality of the reconstructed images is markedly improved, which indicates that the algorithm is successful in solving ECT inverse problem. At the same time, the reconstructed results derived from the noise-contaminated capacitance data indicate that the proposed algorithm is competent to treat with the inaccuracy in the capacitance data. As a result, a promising algorithm is introduced for ECT image reconstruction.

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Weighted syncmer sampling improves long-read mapping

Weighted syncmer sampling improves long-read mapping

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IEEE International Conference on Bioinformatics and Biomedicine (BIBM)

作者： Wei Quan Jinjun Kang Yanfei Deng Zhuang Liu Xiao Zhu Guangri Quan School of Computer and Control Engineering Yantai University Yantai China School of Information and Network Security Xinjiang University of Political Science and Law Tumxuk China

ISBN: (数字)9798350386226

ISBN: (纸本)9798350386233

Syncmers represent a novel class of methods for selecting k-mers that exhibit robustness against mutations in flanking sequences and demonstrate superior conservation in mutated sequences. Nevertheless, syncmers may generate a higher frequency of repetitive seed matches compared to alternative techniques, such as minimizers, which can result in increased computational time. In this article, we introduce weighted minimizer sampling, which integrates weighted minimizer sampling and syncmer sampling to enhance the sensitivity and accuracy of long-read mapping. We modified two state-of-the-art long-read mappers, Minimap2 and Winnowmap, by substituting the sketching sampling methods with weighted minimizer sampling. We assessed their sensitivity and accuracy using simulated and real datasets. The experimental results indicate that weighted minimizer sampling significantly improves the sensitivity and accuracy of long-read mapping. The source code is available at GitHub: https://***/hexinkaoan/weighted-syncmer.

关键词： Hash functions Time-frequency analysis Sequential analysis Sensitivity Accuracy Source coding Sampling methods Robustness Bioinformatics Software development management

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Salinity Sensing by the Radio-Frequency Power Based on the Michelson Interferometer

Salinity Sensing by the Radio-Frequency Power Based on the M...

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Asia Communications and Photonics Conference and Exhibition (ACP)

作者： Lin Gui Xuhui Chen Chengxin Mao Qiankun Li Yu Peng Mengmeng Wu School of Computer and Information Engineering Shanghai polytechnic university Shanghai China School of Intelligent Manufacturing and Control Engineering Shanghai polytechnic university Shanghai China School of resources and environmental Engineering Shanghai polytechnic university Shanghai China

ISBN: (数字)9798350379266

ISBN: (纸本)9798350379273

The salinity sensing technology based on the microwave photonic method is proposed and experimentally verified. The microwave photonic filter is formed by the microwave photonic interferometry of the Michelson interferometer. Contrast to the traditional method based on the optical spectrum measurement, the salinities information can be measured by extracting the minimum values of radio frequency(RF) response curves of microwave photonic filter(MPF). Due to amount of noise and the nonlinearity in the MPF, the minimum values of RF response of MPF vary with time, so the averaged values of several measurements are utilized in data analyzing process. Experimental results show that the salinity sensitivity of 0.284dB/‰ is achieved with the brine concentration in the range of 31‰-40‰ and the value of R-square can reach 0.88 by linearity fitting for salinity sensing, and the value can be improved to 0.979 by Cubic fitting.

关键词： Microwave measurement Radio frequency Optical interferometry Salinity (geophysical) Optical variables measurement Microwave communication Information filters Microwave filters Microwave photonics Optical fiber filters

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Passivity properties for regulation of DC networks with stochastic load demand ⁎

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IFAC-PapersOnLine 2020年第2期53卷 13113-13118页

作者： Amirreza Silani Michele Cucuzzella Jacquelien M.A. Scherpen Mohammad Javad Yazdanpanah Jan C. Wilems Center for Systems and Control ENTEG Faculty of Science and Engineering University of Groningen Nijenborgh 4 9747 AG Groningen the Netherlands. Control & Intelligent Processing Center of Excellence School of Electrical and Computer Engineering University of Tehran Tehran Iran

In this paper we present new (stochastic) passivity properties for Direct Current (DC) power networks, where the unknown and unpredictable load demand is modelled by a stochastic process. More precisely, the considered power network consists of distributed generation units supplying ZIP loads, i.e., nonlinear loads comprised of impedance (Z), current (I) and power (P) components. Differently from the majority of the results in the literature, where each of these components is assumed to be constant, we consider time-varying loads whose dynamics are described by a class of stochastic differential equations. Finally, we prove that an existing distributed control scheme achieving current sharing and (average) voltage regulation ensures the asymptotic stochastic stability of the controlled network.

关键词： DC power networks Nonlinear systems Stochastic modelling Passivity theory

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ACCNet: Attention-based Contextual Convolutional Network for Crowd Counting

ACCNet: Attention-based Contextual Convolutional Network for...

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Chinese Automation Congress (CAC)

作者： Yaoying Huang Aichun Zhu Guoxiu Duan Fangqiang Hu Yifeng Li School of Computer Science and Technology Nanjing Tech University Nanjing China School of Information and Control Engineering China University of Mining and Technology Xuzhou China

ISBN: (数字)9781728176871

ISBN: (纸本)9781728176888

In recent years, crowd counting has been widely used in computer vision. But on many issues like large scale variations, perspective distortions and complex backgrounds, it remains a challenging task. Previous methods usually adopted dilation convolution to enlarge the receptive field, these methods can generate poor density maps. To solve this problem, in this paper, we proposed a novel structure called Attention-based Contextual Convolution Network for crowd counting. ACCNet contains two components. The Contextual Convolution Network first gets the relative influence of different scale-aware feature and attention module to further enlarge the range of scales while getting the final crowd density map in the network. The key section of our network is the dense dilated module, this method can make the front and back dilation layers tightly connected to preserve information from changing scales. Other than that, attention mechanism also plays an important role in learning density maps from input images. To verify the feasibility of our method, we compare it against the state-of-the-art structure on four crowd counting datasets (ShanghaiTech Part_A, ShanghaiTech Part_B, WorldEXPO'10 and UCF_CC_50), which demonstrates that ACCNet is effective and robust for complex scenes.

关键词： Convolution Feature extraction Training computer science Task analysis Semantics Image segmentation

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A Hybrid Approach to Predict Churn

A Hybrid Approach to Predict Churn

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IEEE Asia-Pacific Conference on Services Computing (APSCC)

作者： Javad Basiri Fattaneh Taghiyareh Behzad Moshiri School of Electrical and Computer Engineering University of Tehran Tehran Iran Control and Intelligent Processing Center of Excellence School of ECE University of Tehran Tehran Iran

Acquiring new customers in any business is much more expensive than trying to keep the existing ones. As a result, many prediction algorithms have been proposed to detect churning customers. In this paper, the ordered weighted averaging (OWA) technique is brought to the attention of marketing researchers. We have applied OWA technique to improve the prediction accuracy of existing churn management systems. The decision lists of underlying prediction algorithms have been fused using OWA algorithm. Applied to the database of a telecommunication company, this method is found to significantly improve accuracy in predicting churn compared to the best existing result in the literature of the churn management. Our findings lead us to believe that using OWA technique could cause to increase profit for the companies.

关键词： Classification algorithms Prediction algorithms Open wireless architecture Bagging Boosting Artificial neural networks Classification tree analysis

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3D Interactive Clothing Animation

3D Interactive Clothing Animation

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The 2010 International Conference on computer Application and System Modeling(2010计算机应用与系统建模国际会议 ICCASM 2010)

作者： Shi Min Mao Tianlu Wang Zhaoqi School of Control and Computer Engineering North China Electric Power University Graduate School of Institute of Computing Technology Chinese Academy of Sciences Beijing China

ISBN: (纸本)9781424472352

A framework for clothing animation is developed in this paper. It integrates several key techniques involved in clothing animation. Firstly, an improved mechanical model with real material parameters are used to simulate various types of cloth realistically. Secondly, efficient distance constraints are introduced into our cloth model that effectively limits cloth extensible deformation in the plane without breaking bending deformation. Thirdly, an accelerated algorithm on GPU in collision detection process ensures responsible cloth animation. At last, an interactive system is set up on the three-tier architecture that provides users with some basic functionalities including cloth animation, human model editing and clothing simulation. The interactive editor provides a set of intuitive tools for animators to design a rich variety of human shapes and cloth animation. As a prototype system for clothing animation and virtual dressing, it is fast, reliable and expandable.

关键词： cloth animation particle-spring model virtual dressing constraints model implicit integration

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An optimization approach for 3D environment mapping using normal vector uncertainty

An optimization approach for 3D environment mapping using no...

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International Conference on control, Automation, Robotics and Vision (ICARCV)

作者： Sheraz Khan Nikos Mitsou Dirk Wollherr Costas Tzafestas Institute for Automatic Control Engineering Technische Universität München Munchen Germany School of Electrical and Computer Engineering Division of Signals Control and Robotics National Technical University of Athens (NTUA) Greece

In this paper a novel approach for 3D environment mapping using registered robot poses is presented. The proposed algorithm focuses on improving the quality of robot generated 3D maps by incorporating the uncertainty of 3D points and propagating it into the normal vectors of surfaces. The uncertainty of normal vectors is an indicator of the quality of the detected surface. A controlled random search algorithm is applied to optimize a non-convex function of uncertain normal vectors and number of clusters in order to find the optimal threshold parameter for the segmentation process. This approach leads to an improved cluster coherence and thus better maps.

关键词： Vectors Uncertainty Clustering algorithms Cost function Robot sensing systems

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An Image Reconstruction Algorithm for Electrical Capacitance Tomography

An Image Reconstruction Algorithm for Electrical Capacitance...

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2013 the Second International Conference on Innovative Computing and Cloud Computing(ICCC 2013)

作者： Pai Wang Jzau-Sheng Lin Mei Wang Yu-Lei Zhao School of Electrical and Control Engineer Xi'an University of Science and Technology Department of Computer Science & Information Engineering of National Chin-Yi University of Technology Institute of Intelligent Control and Image Engineering Xidian University

In this paper, we provided an algorithm to reconstruct images with Least Squares Support Vector Machines(LS-SVM) and Simulated Annealing Particle Swarm Optimization(APSO), named SAP. This algorithm introduces simulated annealing ideas into PSO, adopts cooling process functions to replace the inertia weight function and construct the time variant inertia weight function featured in annealing mechanism;takes use of the APSO algorithm to search for the optimized resolution of Electrical Capacitance Tomography(ECT) reconstruction image. In order to overcome the soft field characteristics of ECT sensitivity field, we exercised some image samples of typical flow pattern with LSSVM so as to predict the capacitance error caused by the soft field characteristics and then construct the fitness function of the particle swarm optimization on basis of the capacitance error. The simulation results show that SAP algorithm is featured in quick convergence rate and higher imaging precision. Compared with Landweber algorithm, the quality of reconstruction image with SAP is significantly improved.

关键词： Electrical Capacitance Tomography Simulated Annealing Algorithm Least Squares Support Vector Machines Particle Swarm Optimization

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Adaptive decentralized vibration control of a cable-stayed bridge in the presence of seismic excitation

Adaptive decentralized vibration control of a cable-stayed b...

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ASME 1999 Design engineering Technical Conferences, DETC 1999

作者： Luo, Ningsu Rodellar, Jose Sen, Manuel De La Veh, Josep Campus Montilivi P-ll Dept of Electronics Automatic Control and Computer Engineering University of Girona Girona17071 Spain Department of Applied Mathematics III School of Civil Engineering Technical University of Catalonia Barcelona08034 Spain Department of Electricity and Electronics Faculty of Science University of Basque Country Bizkaia Leioa48940 Spain

ISBN: (纸本)9780791819760

In this paper, an adaptive decentralized controller is presented to attenuate the transversal vibration of a flexible cablestayed bridge induced by seismic excitation, in which only local sensor information has been used to generate the control signal that is sent to the actuator. The dynamic behavior of the beam structure is characterized by a nonlinear mathematical model with interconnection terms, which was obtained by using technique of finite element. The controller design is made based on the principle of sliding mode such that a priori knowledge on the exact value of system parameters, structural disturbances and the seismiic excitation is not required. In particular, it is assumed that the upper and lower bounds for the seismic excitation are also unknown. The closed-loop robust stability has been achieved through the generation of a sliding motion in the system. Nu-merical simulation is done to illustrate the effectiveness of the proposed control scheme for a scaled model of the bridge subject to the Taft earthquake. © 1999 American Society of Mechanical Engineers (ASME). All rights reserved.

关键词： controllers

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