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Real-time simulation of action-driven 3D subtle facial expressions

Journal of Computational Information systems 2014年第5期10卷 2137-2144页

作者： Tang, Yong Liang, Haiyan Guo, Dan Lv, Mengya Zhao, Jing College of Information Science and Engineering Yanshan University Qinhuangdao 066004 China The Key Laboratory for Computer Virtual Technology and System Integration of Hebei Province Qinhuangdao 066004 China

While the large-scale deformations such as the Laplacian deformation method could not synthesize new expressional details, this paper proposes a method for simulating different subtle facial expressions based on the Kinect acquisition system and the facial expressional reconstruction technique. Firstly, we generate the coarse skin textures with pore details and those normal maps. Secondly, we use blending wrinkle maps to render animated details on a human face based on a GPU shader program. Finnaly, according to the action units captured by the Kinect, we calculate the dynamic texture mapping and the weight of wrinkles, and apply the wrinkles function to simulate the motion of wrinkles. Experimental results show that our method can generate facial details in real time. The method suits the fields such as digital entertainment and video conferences. © 2014 Binary Information Press.

关键词： Blending

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3-SPS+RRS+PS mechanism analysis and hessian matrix solution

3-SPS+RRS+PS mechanism analysis and hessian matrix solution

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2014 International Conference on Logistics Engineering, Management and computer Science, LEMCS 2014

作者： Zhang-Yuan Wangzhen Guoansong Guoi-Juan Xi, Feng-Feng Key Laboratory for Computer Virtual Technology and System Integration of Hebei Province Yanshan University Qinhuangdao066004 China Hebei Normal University of Science and Technology Qinhuangdao Hebei066004 China Force Equipment Research Institute Airlines Beijing100076 China China National Heavy Machinery Research Institute Xian710032 China Department of Aerospace Engineering Ryerson University Toronto Canada

ISBN: (纸本)9789462520103

3-SPS+RRS+PS is a new type of mechanism. There is good application prospect in the field of aerospace. Especially some key kinetic characteristic calculation algorithms are implemented, which makes its calculation mechanized, thus it will contribute to make the dynamics performance of this mechanism optimized and ascended. In the paper, firstly, the degree of freedom is calculated and freedom nature is analyzed. Then the reverse solution is calculated, started with the nature of degree of freedom. And the mechanism velocity and acceleration inverse solutions are calculated in the direct derivation method. Although there are shortcomings that calculation process is complicated in direct derivation method, its calculation process is easy to realize mechanization. Then a kind of fast numerical calculation algorithm is given and MATLAB program is implemented. The algorithm has universal applicability to the mechanism of continuous differentiable inverse equation, and can be applied to general parallel mechanism. © 2014. The authors - Published by Atlantis Press.

关键词： Mechanisms

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IMSPMIS-Stream: incremental mining of top-k short sequential pattern over multiple item set streams

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Journal of Computational Information systems 2014年第6期10卷 2305-2312页

作者： Hao, Xiaobing Han, Gaowei Chen, Yuping Wang, Peilong Ren, Jiadong College of Information Science and Engineering Yanshan University Qinhuangdao 066004 China The Key Laboratory for Computer Virtual Technology and System Integration of Hebei Province Qinhuangdao 066004 China

Many previous algorithms in data streams are about single stream, which can only process single items. The algorithms about data streams are always extended by sequential pattern algorithms about static database, they can't satisfy the requirement of scanning streams only once and online mining. Moreover, top-k short sequential pattern hasn't been studied yet. Therefore, IMSPMIS-Stream algorithm is proposed to mine online multiple streams with the single scan by the incremental method in this paper. The streams are continuous transactions, which is also called item set streams. Several streams are mined interactively based on sliding windows at the same time. An approach to count the support of every sub item set is designed to get the support during one scan. The short sequential pattern is deffned, whose item sets are shorter than all the item sets with the same occurring time. When the arrival transactions reach to the capacity of the window, sequential patterns will be output by combining top-k short item sets. The experiments show that the IMSPMIS-Stream algorithm overcomes the memory limitation and its execution time is reduced compared with some previous algorithms under the same conditions. Copyright © 2014 Binary Information Press.

关键词： Information systems

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Mining time-interval weighted closed sequential patterns based on memory indexing

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Journal of Computational Information systems 2014年第1期10卷 293-300页

作者： Zeng, Qiang Chen, Dengxi Ren, Jiadong Han, Gaowei College of Information Science and Engineering Yanshan University Qinhuangdao 066004 China The Key Laboratory for Computer Virtual Technology and System Integration of Hebei Province Qinhuangdao 066004 China

General weighted sequential pattern mining algorithms ignore or do not make good use of the time and time-interval information of data elements. Besides some algorithms require to scan the database many times or build temporary databases. To solve these problems, we propose a memory-based algorithm MITWCSpan (Memory Indexing for time-interval Weighted Closed Sequential pattern mining) for timeinterval weighted closed sequential pattern mining. The algorithm takes full account of the importance of the time-interval of data elements. Moreover, an improved index set based on time-interval, p-tidx, is defined. During mining process, the algorithm adopts the find-then-index technique recursively to find the items which can constitute a time-interval weighted sequential pattern and construct p-tidx for the possible sequential pattern. Finally the algorithm uses closing detection to get the whole time-interva l weighted closed sequential patterns. The experimental results show that the algorithm is more efficient in finding more important sequential patterns. Copyright © 2014 Binary Information Press.

关键词： Indexing (of information)

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Robust recommendation algorithm based on user rating matrix block and modified LTS-estimator

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Journal of Information and Computational Science 2014年第6期11卷 1889-1898页

作者： Xu, Yuchen Liu, Zhen Zhang, Fuzhi School of Information Science and Engineering Yanshan University Qinhuangdao 066004 China The Key Laboratory for Computer Virtual Technology and System Integration of Hebei Province Qinhuangdao 066004 China

The most widely-used collaborative recommendation algorithms are vulnerable to shilling attacks. To this end, in this paper we propose a robust recommendation algorithm based on user rating matrix block and modified LTS-estimator. Firstly, we construct user rating matrix blocks using user rating matrix block algorithm based on k-median clustering. Secondly, we apply the modified LTS-estimator to matrix factorization model in order to produce user feature matrix and item feature matrix. Finally, we devise a robust recommendation algorithm to generate recommendations for the target users. Experimental results on the MovieLens dataset show that the proposed algorithm outperforms the existing methods in terms of both the prediction accuracy and robustness. © 2014 Binary Information Press.

关键词： Matrix factorization

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A density grid-based uncertain data stream clustering algorithm

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Journal of Computational Information systems 2014年第9期10卷 3619-3626页

作者： He, Haitao Zhao, Jintian The Key Laboratory for Computer Virtual Technology and System Integration of Hebei Province Qinhuangdao 066004 China College of Information Science and Engineering Yanshan University Qinhuangdao 066004 China

The existing grid-based uncertain data stream clustering algorithms are fast but low-accuracy, and sensitive to user-specified threshold. In order to solve the above problems, a density grid-based uncertain data stream clustering algorithm UG-Stream is proposed in this paper. In UG-Stream algorithm, a dynamic threshold is defined by taking uncertainty and grid feature into account, dense grid can be distinguished by the threshold. The probability variance is defined to describe the distribution of internal data points in grid. If grid distribution can be taken as uniform, dense grid can be classified as core dense grid by probability variance. Core dense grid can be clustered directly, the rest of dense grids will be merged into current existing clusters by probability center distance. Contrast experiments show that UG-Stream algorithm is superior to UMicro algorithm in both clustering accuracy and clustering rate. © 2014 Binary Information Press.

关键词： Clustering algorithms

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Density-based clustering for evolving uncertain data stream

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Journal of Computational Information systems 2014年第1期10卷 419-426页

The current clustering algorithms for evolving uncertain data stream are sensitive to user specified threshold, and unstable in noise processing. In this paper, DUStream is presented, a density-based algorithm for discovering clusters in evolving uncertain data stream. Probability distance is introduced as a new similarity measure, giving consideration to probability attribute and distance attribute. Probability Radius is used as a self-adaption dynamic threshold to reduce the effect of user specified input. The experimental results demonstrate the effectiveness and Effciency of the algorithm on Artificial and real data sets. Copyright © 2014 Binary Information Press.

关键词： Probability

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WCSPMPD-stream: Mining weighted closed sequential patterns with pattern decay over data streams

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Journal of Computational Information systems 2014年第1期10卷 435-442页

作者： Zeng, Qiang Han, Gaowei Li, Weina Ren, Jiadong College of Information Science and Engineering Yanshan University Qinhuangdao 066004 China The Key Laboratory for Computer Virtual Technology and System Integration of Hebei Province Qinhuangdao 066004 China

Many of the previous incremental methods in data streams are deleting the old patterns and adding to the new patterns directly, which may delete useful patterns too early. Both different real data and the data occurring time can lead to the diverse importance, which are not considered at the same time in previous studies. Therefore, WCSPMPD-Stream, a weighted closed sequential pattern algorithm with pattern decay based on sliding windows over data streams is proposed in this paper. Firstly, the sliding windows are separated into several fragments to be mined respectively. Secondly, Time Weight Decay and No Updating Decay methods are designed to control the decay rate. Thirdly, a method of calculating the time weight is defined which varies linearly with the length of time interval between each stream fragment and the current stream fragment. Fourthly, an approach of getting the item weight is defined to calculate any sequence weight by the items in it. Fifthly, a new data structure WFPS-Tree is advanced to store and update the mining results. The experiments show that WCSPMPD-Stream algorithm overcomes the memory limitation and mines patterns with higher interest. And its execution time is reduced compared with the previous algorithms under the same conditions. Copyright © 2014 Binary Information Press.

关键词： Trees (mathematics)

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Sequential pattern mining with gap constraints for discovery of the software bug features

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Journal of Computational Information systems 2014年第2期10卷 673-680页

作者： Zeng, Qiang Chen, Yuping Han, Gaowei Ren, Jiadong College of Information Science and Engineering Yanshan University Qinhuangdao 066004 China The Key Laboratory for Computer Virtual Technology and System Integration of Hebei Province Qinhuangdao 066004 China

In order to process the software bug feature sequences, this paper presents a gap-constrained sequential pattern mining algorithm, MEMIGCSP algorithm. The length of the interval between items is limited in the original sequences so as to find interested sequences. The gap constrained prefix index set (P-Gidx) based on memory indexing provides the position information of the bug sequence patterns. Strategy of divide-and-conquer is used to deal with the sequences which are in the P-Gidx and others respectively. What's more, pattern growth is advanced to extend the prefix pattern after the local extension items are searched from the forward and backward space, thus the complete set of sequential patterns can be found. The performance evaluation demonstrates the scalability of MEMIGCSP and shows the efficiency and accuracy for mining sequential pattern with gap constraints. Copyright © 2014 Binary Information Press.

关键词： Indexing (of information)

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Inuence maximization algorithm based on genetic algorithm

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Journal of Computational Information systems 2014年第21期10卷 9255-9262页

作者： Guo, Jingfeng Liu, Yuanying Shen, Jiali Wei, Zhenzhen Lv, Jiaguo College of Information Science and Engineering Yanshan University Qinhuangda China College of Information Technology Hebei University of Economics and Business Shijiazhuang China The Key Laboratory for Computer Virtual Technology and System Integration of Hebei Province Qinhuangdao China

The inuence maximization problem is defined as providing a given initial integer k, mining top-k inuential nodes from a social network such that the spread of inuence in the network is maximized. Some existing studies are based on Greedy algorithm, but their time complexity is very high. In this paper, a different method based on Genetic Algorithms, denoted as MAGA is proposed. In the MAGA algorithm, the set of k nodes is seen as a candidate solution, and the expected inuence value as fitness. Use the genetic algorithm to get the optimal solution. Experiments show that the algorithm achieved a balance in inuence spread and running time.

关键词： Genetic algorithms

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