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High-accuracy ultrasonic positioning through optimization of the extended Kalman filter algorithm

Computer Modelling and New Technologies 2014年第12期18卷 277-283页

作者： JunZheng, Li Da, Yuan Bin, Wang School of Information Science and Engineering Shandong Normal University Jinan China Key Laboratory of Intelligent Information Processing in Universities of Shandong Shandong Institute of Business and Technology Yantai China

The application of extended Kalman filter algorithm to ultrasonic positioning systems has difficulty in meeting the requirements of precision positioning because the algorithm produces a new calculation error when the system is linearized. Modal optimization of the extended Kalman filter algorithm is thus investigated. The received ultrasonic signal is first decomposed by empirical mode decomposition, the intrinsic mode functions that best represent the original signal are then selected to restructure the waveform, and the transition time is finally corrected. Meanwhile, the ultrasonic wave velocity can be corrected. Traditional ultrasonic positioning can also be improved by combining with a radio-frequency module. It is experimentally shown that the proposed method limits positioning error to within ±5 cm and within ±1 cm after multiple recursions.

关键词： Intrinsic mode functions

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Mobile user stability prediction with Random Forest model

Mobile user stability prediction with Random Forest model

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International Conference on Data Science and Advanced Analytics (DSAA)

作者： Danqin Wang Xiaolong Zhang Intelligent Information Processing and Real-time Industrial Systems Hubei Province Key Laboratory Wuhan China School of Computer Science and Technology Wuhan University of Science and Technology

Accompanying increasing competition among the communication industry, maintaining and improving the stability and loyalty of customers has become the key determinant of profitability. In order to prevent the loss of customers, we need to identify the stable users by data mining model. Through the evaluation of three models, Random Forest model performs with better robustness. This model can describe and predict most of the stable users in a shorter period of time. Consequently, the result will provide operators with the advantage of adopting reasonable marketing tactics timely.

关键词： Stability analysis Profitability Analytical models Prediction algorithms Logistics Accuracy

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Robust point pattern matching based on spectral context

Robust point pattern matching based on spectral context

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作者： Tang, Jun Shao, Ling Zhen, Xiantong Key Laboratory of Intelligent Computing and Signal Processing Ministry of Education Anhui University Huangshan Road Hefei 230039 China College of Electronic and Information Engineering Nanjing University of Information Science and Technology Nanjing 210044 China Department of Electronic and Electrical Engineering University of Sheffield Mappin Street Sheffield S1 3JD United Kingdom

Finding correspondences between two related feature point sets is a basic task in computer vision and pattern recognition. In this paper, we present a novel method for point pattern matching via spectral graph analysis. In particular, we aim to render the spectral matching algorithm more robust for positional jitter and outlier. A local structural descriptor, namely the spectral context, is proposed to describe the attribute domain of point sets, which is fundamentally different from the previous methods. Furthermore, the approximate distance order is defined and employed as the metric for geometric consistency of neighboring points in this work. By combining these two novel ingredients, we formulate feature point set matching as an optimization problem with one-to-one constraints. The correspondences are then obtained by maximizing the given objective function via the technique of probabilistic relaxation. Comparative experiments conducted on both synthetic and real data demonstrate the effectiveness of the proposed method, especially in the presence of positional jitter and outliers. © 2013 Elsevier Ltd. All rights reserved.

关键词： Jitter

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2-D shape completion with shape priors

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Chinese Science Bulletin 2013年第27期58卷 3430-3436页

作者： GUO Ge JIANG TingTing WANG YiZhou GAO Wen Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Graduate University of Chinese Academy of Sciences National Engineering Laboratory for Video Technology Key Laboratory of Machine Perception School of EECS Peking University

We propose new techniques for 2-D shape/contour completion, which is one of the important research topics related to shape analysis and computer vision, e.g. the detection of incomplete objects due to occlusion and noises. The purpose of shape completion is to find the optimal curve segments that fill the missing contour parts, so as to acquire the best estimation of the original complete object shapes. Unlike the previous work using local smoothness or minimum curvature priors, we solve the problem under a Bayesian formulation taking advantage of global shape prior knowledge. With the priors, our methods are expert in recovering significant shape structures and dealing with large occlusion cases. There are two different priors adopted in this paper: (i) A generic prior model that prefers minimal global shape transformation (including non-rigid deformation and affine transformation with respect to a reference object shape) of the recovered complete shape; and (ii) a class-specific shape prior model learned from training examples of an object category, which prefers the reconstructed shape to follow the learned shape variation models of the category. Efficient contour completion algorithms are suggested corresponding to the two types of priors. Our experimental results demonstrate the advantage of the proposed shape completion approaches compared to the existing techniques, especially for objects with complex structure under severe occlusion.

关键词：形状结构计算机视觉贝叶斯公式电子相关最佳估计最小曲率先验知识仿射变换

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Research of data secure based on cloud computing

Research of data secure based on cloud computing

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IEEE Workshop on Electronics, Computer and Applications (IWECA)

作者： Yan-rong Shi Xiao-fang Zhao Shu-yin Chen Key Laboratory of Intelligent Information Processing in Universities of Shandong Shandong Institute of Business and Technology Yantai China School of Computer Science and Technology Shandong Institute of Business and Technology Yantai China

Cloud computing has brought new opportunities for the development of traditional industries, but also appeared some new security risks. This paper analyzes the main data security problems in cloud computing field, and... 详细信息

关键词： Educational institutions Instruction sets Servers Character recognition Monitoring Computational modeling Data models

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Nonlinear H ∞ observer design for one-sided Lipschitz systems

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Neurocomputing 2014年 145卷 505-511页

作者： Wei Zhang Housheng Su Shengchao Su Dazhong Wang Laboratory of Intelligent Control and Robotics Shanghai University of Engineering Science Shanghai 201620 China School of Automation Image Processing and Intelligent Control Key Laboratory of Education Ministry of China Huazhong University of Science and Technology Wuhan 430074 China College of Information Science and Technology Donghua University Shanghai 201620 China

This paper is considered with the H ∞ observer design problem for a class of nonlinear systems with the one-sided Lipschitz condition. The systems under consideration include the well-studied Lipschitz system as a special case and possess inherent advantages with respect to conservativeness. For such systems in the presence of noises, we develop a Linear Matrix Inequality (LMI) based approach to design a nonlinear H ∞ observer by carefully dealing with the one-sided Lipschitz condition together with the quadratic inner-bounded condition. The resulting nonlinear H ∞ observer guarantees asymptotic stability of the estimation error dynamics with a prescribed H ∞ performance. Moreover, for the design purpose, the existence condition of the proposed nonlinear H ∞ observer is formulated in terms of LMIs by using a matrix generalized inverse technique. Finally, a simulation example is given to illustrate the effectiveness of the proposed design.

关键词： One-sided Lipschitz nonlinear systems Nonlinear H ∞ observers Observer design State estimation

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Genetic Algorithm based Neural Network for the Displacement of Landslide Forecasting

Genetic Algorithm based Neural Network for the Displacement ...

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第三十三届中国控制会议

作者： Jiejie Chen Zhigang Zeng Ping Jiang Huiming Tang The School of Automation Huazhong University of Science and Technology Key Laboratory of Image Information Processing and Intelligent Control Ministry Education Faculty of Engineering China University of Geosciences

This paper proposes two hybrid prediction models using for predicting the displacement of landslide, Genetic Algorithm-Radial Basis Function Neural Network (GA-RBFN) and Genetic Algorithm- Back Propagation Neural Network (GA-BPNN). A case study of Yuhuangge landslide in the Three Gorges reservoir in China is used to illustrate the capability and merit of our schemes. In addition, the result shows that GP-BPNN get better accuracy than GA-RBFN in the same measurements.

关键词： Terrain factors Genetic algorithms Neural networks Forecasting Training Transfer functions Educational institutions

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A novel classification method based on the ensemble learning and feature selection for aluminophosphate structural prediction

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Microporous and Mesoporous Materials 2014年 186卷 201-206页

作者： Minghai Yao Miao Qi Jinsong Li Jun Kong School of Computer Science and Information Technology Northeast Normal University Key Laboratory of Intelligent Information Processing of Jilin Universities Changchun 130117 China School of Mathematics and Statistics Northeast Normal University Changchun 130024 China Key Laboratory for Applied Statistics of MOE Northeast Normal University Changchun 130024 China

In this paper, a novel classification algorithm based on the ensemble learning and feature selection is proposed for predicting the specific microporous aluminophosphate ring structure. The proposed method can select the most significant synthetic factors for the generation of (6, 12)-ring-containing structure. First, the clustering method is employed for making each training subset contains all the structural characteristics of samples. Then, the method takes full account of the discrimination and class information of each feature by calculating the scores. Specially, the scores are fused for getting a weight for each feature. Finally, we select the significant features according to the weights. The result of feature selection will help to predict the (6, 12)-ring-containing AlPO structure well. Moreover, we compare our method with several classical feature selection methods and classification method by theoretical analysis and extensive experiments. Experimental results show that our method can achieve higher predictive accuracy with less synthetic factors.

关键词： Zeolites Polymer processing Feature selection Ensemble learning Simulation

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Priority-based IEEE 802.15.4 CSMA/CA mechanism for WSNs

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The Journal of China Universities of Posts and Telecommunications 2013年第1期20卷 47-53页

作者： ZHAO Lu BAI Guang-wei SHEN Hang TANG Zhen-min Key Laboratory of Intelligent Perception and System for High-dimensional Information for Ministry of Education of China Nanjing University of Science and Technology School of Electronics and Information Engineering Nanjing University of Technology

The IEEE 802.15.4 standard is widely used in wireless sensor networks （WSNs）. In this paper, we propose a priority-based IEEE 802.15.4 carrier sense multiple access with collision avoidance （CSMA/CA） mechanism for WSNs. Considering traffic load and traffic type of sensor nodes, we classify sensor nodes into three types. In our mechanism, different contention parameters are set for nodes with different priority levels, in order that nodes with high priority achieve high probability to access the channel. By modeling the proposed mechanism using a Markov chain, we analyze and compute the successful transmission probability, throughput and energy consumption for nodes with different priority levels. Finally, our numerical results demonstrate that our mechanism performs well for WSNs.

关键词： WSNs 1EEE 802.15.4 MAC Markov chain priority real-time data

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A Coupling-Based Approach for Class Integration and Test Order

A Coupling-Based Approach for Class Integration and Test Ord...

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IEEE Asia-Pacific Conference on Services Computing (APSCC)

作者： Hao Liu Jianxun Chen Processing and Real-time Industrial System Hubei Province Key Laboratory of Intelligent Information Wuhan China School of Computer Science and Technology Wuhan University of Science and Technology Wuhan China

Software testing is one of the most important techniques used to assure the quality of software service. An intricate issue in software testing is the determination of test orders for the integration test of classes, known as the class integration and test order (CITO) problem. The determination of such order has an influence on the cost of created stubs for classes, which is an error-prone and costly process. To minimize the cost of stubbing, this paper describes a coupling measure technique to estimate the complexity of each test stub, and presents a graph-based heuristic algorithm of removing node with the highest weights to break cycles for minimizing overall complexity of stubbing. Also, an adjacency matrix and depth-first search for finding all the paths is presented. Simulation experimental results show that the overall test stub complexity decreased which greatly improves test efficiency and reduces the test cost to some extent compared with others.

关键词： Couplings Complexity theory Testing Software Weight measurement Genetic algorithms Object oriented modeling

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