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Automatic simulated computation of remote sensing information model based on semantic

Journal of Chemical and Pharmaceutical Research 2014年第7期6卷 521-529页

作者： Sun, Shengtao Wu, Aizhi The Key Laboratory for Computer Virtual Technology and System Integration of Hebei Province School of Information Science and Engineering Yanshan University Qinhuangdao China College of Vehicles and Energy Yanshan University Qinhuangdao China

This paper discusses the simulated computation methods of remote sensing information model, and tries to put forward a more available solution. It presents our research works on the description and simulation methods of remote sensing information model: the service on demand method provides a basic methodology of model analysis, the semantic relationship description of information processing procedure supports the basic knowledge of resource selection and matching based on user’s demand, and the hierarchical mapping method of remote sensing information model shows the transformation from abstract model to executable data processing workflow. © 2014, Journal of Chemical and Pharmaceutical Research. All rights reserved.

关键词： Semantics

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A Robust Collaborative Recommendation Algorithm Based on k-distance and Tukey M-estimator

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China Communications 2014年第9期11卷 112-123页

作者： YI Huawei ZHANG Fuzhi LAN Jie School of Information Science and Engineering Yanshan University Qinhuangdao 066004 Hebei Province E R.China The Key Laboratory for Computer Virtual Technology and System Integration of Hebei Province Qinhuangdao 066004 P. R. China Liaoning University of Technology Jinzhou 121001 Liaoning Province P. R. China

The existing collaborative recommendation algorithms have lower robustness against shilling *** this problem in mind,in this paper we propose a robust collaborative recommendation algorithm based on k-distance and Tukey ***,we propose a k-distancebased method to compute user suspicion degree(USD).The reliable neighbor model can be constructed through incorporating the user suspicion degree into user neighbor *** influence of attack profiles on the recommendation results is reduced through adjusting similarities among ***,Tukey M-estimator is introduced to construct robust matrix factorization model,which can realize the robust estimation of user feature matrix and item feature matrix and reduce the influence of attack profiles on item feature ***,a robust collaborative recommendation algorithm is devised by combining the reliable neighbor model and robust matrix factorization *** results show that the proposed algorithm outperforms the existing methods in terms of both recommendation accuracy and robustness.

关键词： shilling attacks robust collaborative recommendation matrix factori-zation k-distance Tukey M-estimator

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Incremental mining of sequential patterns from multiple item set data streams

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ICIC Express Letters 2014年第10期8卷 2687-2692页

作者： Hao, Xiaobing Chen, Yuping Ren, Jiadong College of Information Science and Engineering Yanshan University No. 438 Hebei Ave. Qinhuangdao 066004 China The Key Laboratory for Computer Virtual Technology and System Integration of Hebei Province No. 438 Hebei Ave. Qinhuangdao 066004 China

Sequential pattern mining has a wide range of applications in data streams. The real data involves multiple data streams and each data stream is itemset-sequence. However, most algorithms mine a single item in a single data stream. So IMASP algorithm (incremental mining of across-stream sequential patterns from multiple item set data streams) is presented to mine sequential patterns from multiple data streams and it is an incremental algorithm with single-pass scanning. What is more, the algorithm uses a multi-streams bitmap temporary table to store the sequence information in the current sliding windows. The partial substitution and the real-time counting of the item in old and new windows are adopted to improve the execution efficiency of the algorithm. A multi-streams Lexicographic Sequence Tree is used to store items, extended sequences and the support. Experimental results show that IMASP algorithm reduces time and memory consumption and has the efficiency and accuracy for mining across-stream sequential pattern from itemset sequence streams. © 2014 ICIC International.

关键词： Efficiency

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A batch-based algorithm for mining weighted sequential patterns in data streams

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ICIC Express Letters 2014年第7期8卷 1821-1826页

作者： Hao, Xiaobing Li, Yabin Huang, Guoyan Ren, Jiadong College of Information Science and Engineering Yanshan University No. 438 Hebei Ave. Qinhuangdao 066004 China The Key Laboratory for Computer Virtual Technology and System Integration of Hebei Province No. 438 Hebei Ave. Qinhuangdao 066004 China

In this paper, we proposed a new sequential pattern mining algorithm called WSPD for mining weighted sequential patterns in data streams. The algorithm produces no false negatives and places a bound on the error of the false positives. WSPD could also satisfy the user's dynamic request for mining weighted sequential patterns from any batches. Experimental results show that WSPD algorithm is effective and scale linearly for mining weighted sequential patterns in data streams. © 2014 ISSN 1881-803X.

关键词： Trees (mathematics)

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An efficient algorithm for mining maximal frequent sequences by Top-Down Delay Decomposition method

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ICIC Express Letters 2014年第7期8卷 2007-2012页

作者： Wang, Qian Ren, Jiadong Liu, Qiang College of Information Science and Engineering Yanshan University No. 438 Hebei Ave. Qinhuangdao 066004 China Key Laboratory for Computer Virtual Technology and System Integration of Hebei Province No. 438 Hebei Ave. Qinhuangdao 066004 China

Maximal frequent sequence mining is an important research issue which has realized the highly compressed storage of frequent sequences. At present, most algorithms are based on bottom-up method and large numbers of candidate sequences are generated. In this paper, an algorithm based on Top-down Delay Decomposition for mining Maximal Frequent Sequence is proposed. TDD MFS uses top-down delay decomposition method, sequences from original database and decomposition are expressed by different tuples to record their direct and indirect occurrence counts. Longest infrequent sequences are recursively decomposed and the decomposition of infrequent sequences that have frequent super sequences is avoided. Only one database scan is needed, no candidate sequences are generated and sequence decomposition times are reduced. Experiment result shows its high efficiency and good scalability. © 2014 ISSN 1881-803X.

关键词： Delay decomposition Frequent sequence Maximal frequent sequence

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Angle historgam model of directional relationship in 3D based on Double-projection and Rounded-subdivision

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Journal of Information and Computational Science 2014年第18期11卷 6471-6478页

作者： Kong, Dehan Liu, Yongshan Ma, Junlei Department of Information Science and Engineering Yanshan University Qinhuangdao China The Key Laboratory for Computer Virtual Technology and System Integration of Hebei Province Yanshan University Qinhuangdao China Data Industry Research Lab Qinhuangdao China

The formal model of spatial directional relations is one of the most important parts in spatial relation research. The most of models are based on Minimum Bounding Rectangle (MBR), and they are not compliant with the regular pattern of human cognition. In order to get a closer conclusion to human cognition on directional relationship, Angle Histogram model based on Double-projection and Rounded-subdivision (AHDPRS) is proposed in this paper. The model uses the maximum inscribed circles to find out the maximum parts of the object, and calculates the directional relationship between the centers of the circles. This model ignores the inessential details to ensure the result which will be closer to human cognition. The experiments show that this model is feasible.

关键词： Graphic methods

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An efficient Subspace Clustering Algorithm based on Attribute Relativity and DBSCAN

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ICIC Express Letters 2014年第6期8卷 1677-1682页

作者： Zeng, Qiang Bai, Yunyue He, Haitao Ren, Jiadong College of Information Science and Engineering Yanshan University No. 438 Hebei Ave. Qinhuangdao 066004 China The Key Laboratory for Computer Virtual Technology and System Integration of Hebei Province Yanshan University No. 438 Hebei Ave. Qinhuangdao 066004 China

In the high-dimensional data traditional clustering algorithms tend to break down because of the curse of dimensionality, high cost of time, etc. This paper proposes a novel algorithm AReSUBCLU, an Effective Subspace Clustering Algorithm based on Attribute Relativity and DBSCAN. Active attribute is defined to reduce the dimension of data, and a subspace search tree which is constructed by attribute correlation matrix is defined to generate subspaces. Firstly, this method uses DBSCAN with the technique of weighted threshold to cluster on every active attribution. Secondly, the correlation matrix is constructed by computing the covariance of attributes. And the subspace search tree is constructed by the matrix which is used to measure the relativity of attributions. The set of nodes in each root branch of the tree is the interesting subspaces that the algorithm discovers. Finally, the subspace clusters are obtained through merging every cluster of active dimension with the usage of similarity of cluster. Evaluation with synthetic and real-world datasets demonstrates that AReSUBCLU has a good clustering quality, and capability of discovering subspace clusters of arbitrary shapes. © 2014 ISSN 1881-803X.

关键词： Clustering algorithms

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Point cloud coarse registration based on 3DSIFT keypoint detection

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Journal of Computational Information systems 2014年第23期10卷 10121-10128页

作者： Gu, Xiaoying Liu, Yongshan Department of Information Science and Engineering Yanshan University Qinhuangdao China The Key Laboratory for Computer Virtual Technology and System Integration of HeBei Province Yanshan University Qinhuangdao China Data Industry Research Lab Qinhuangdao China

Since the SIFT feature point extraction algorithm with scale changes, rotation transformation invariance, is widely used in image registration. In this paper, the SIFT algorithm is applied to three-dimensional point cloud coarse registration, the proposed 3DSIFT extraction algorithm is suitable for three-dimensional point cloud data, then point coordinates, curvature, the nearest neighbor distance mean and other information compose fourteen-dimensional vector to conduct correspondence match, use the interior point rate of Ransac to obtain optimal transformation, and finally transform the coordinates for source point clouds using the optimal transform, complete the point cloud data coarse registration. Experimental results show that our coarse registration algorithm can effectively extract feature points, and it is robust for the point cloud with noisy point, it can provide accurate and effective initial value for the precise registration such as ICP.

关键词： Metadata

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Research on a denoising smoothing algorithm for 3D scattered point cloud

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ICIC Express Letters 2014年第9期8卷 2403-2409页

作者： Gu, Xiaoying Liu, Yongshan Wu, Qiong Department of Information Science and Engineering China The Key Laboratory for Computer Virtual Technology and System Integration of Hebei Province Yanshan University No. 438 Hebei Ave. Qinhuangdao 066004 China Data Industry Research Lab Qinhuangdao 066004 China

In order to effectively eliminate outliers and noise points in 3D scattered point cloud, a denoising smoothing algorithm which is the combination of removing outliers algorithm and trilateral filter is proposed. This is accomplished by rejecting outliers, correcting the normal direction and moving noise points along the modified normal direction within local adaptive neighborhoods. First, the outliers are removed by the method of mathematical statistics, on this basis, estimating normal direction and curvature of point cloud by covariance analysis method. Then, correct the normal direction by combining trilateral filter weighting factor with adaptive optimal neighborhood function. Finally, calculate position offset of data points in the direction of normal amendment by trilateral filter weighting factor in order to smooth the point cloud. Experimental results show that the proposed method is simple and effective, successfully removing noise from point cloud while preserving inherent geometric features. © 2014 ISSN 1881-803X.

关键词： Bandpass filters

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Real-time simulation of foam and sprays based on the Weber number

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Journal of Computational Information systems 2014年第7期10卷 2829-2836页

作者： Zhang, Lihui Zhang, Chao Li, Ying Lv, Mengya Tang, Yong The Key Laboratory for Computer Virtual Technology and System Integration of Hebei Province The College of Information Science and Engineering Yanshan University Qinhuangdao 066004 China Department of Information Engineering Environmental Management College of China Qinhuangdao 066004 China

In this paper, we propose a method based on the Weber number to uniformly model and simulate the foam and sprays generated by the fluid motion. We use the SPH to construct the fluid and calculate the Weber number of each particle. The fluid particles are divided into foam particles, transition particles and water particles by comparing their Weber number with a given critical value. These particles are rendered independently. For the solid-liquid interaction in fluid, we use SPH particles to mark the solid shape, and correct the changed solid particle position using a rotating equation. Finally, a more precise fluid surface illumination model is proposed, and the Fresnel reflection coefficient of this model can be gotten by the Snell law. Experiment results show that our method achieve real-time performance and the visual effect is desirable. © 2014 Binary Information Press.

关键词： Hydrodynamics

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