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Real-time simulation of large-scale water environments with interacting objects

Journal of Computational Information systems 2015年第9期11卷 3257-3264页

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

We present a new GPU scheme for real-time simulation in large-scale water environments with physics-based object interaction. To improve the simulation efficiency, we divide surface waves into ambient waves and interactive waves. A fast and stable Verlet integration method is applied to solve the wave equation to simulate the propagation of interactive waves. To solve the problem that the interactive area caused by the moving object is uncertain, we propose a moving grid suited to LOD (Levels of Detail) surface with multiple resolutions, which reduces the computation cost. The extension of multiple moving grids makes the interaction of water and various objects possible. We propose a volume conservation based method to generate interactive waves and apply rigid body dynamics to demonstrate the effect of water reaction against the object. Experimental results show that our approach achieves higher visual realism and performance. ©, 2015, Binary Information Press. All right reserved.

关键词： Wave equations

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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 novel algorithm for outlier mining in the internet of things

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ICIC Express Letters 2013年第1期7卷 215-219页

作者： Chen, Wei Liu, Yongshan Zhang, Yang 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

Most of the traditional outlier mining algorithms are not suitable for high dimensional datasets. However, the dimensionality of the dataset in the field of the Internet of Things is high. Therefore, Hypergraph-based Outlier Mining (HOM) algorithm is proposed to solve the problem. Two different hypergraph models are constructed in the HOM algorithm. One is itemset hypergraph. One-itemset in transaction database is itemset hypergraph's vertices, and the transactions are itemset hypergraph's hyperedges. The other one is transaction hypergraph. The transactions are its vertices, and frequent itemsets are the hyperedges. The outliers are found by hypergraph partitioning. Experiments show that HOM algorithm can effectively find the outliers in high dimensional space. ©2013 ICIC International.

关键词： Statistics

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Multi-Update Patterns and Validity Verification for Robust Visual Tracking

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Journal of computers (Taiwan) 2020年第4期31卷 77-90页

作者： Wen, Jia Wang, Hong-Jun Li, Yan-Nan Zhao, Ji-Wei Yang, Yu-Ying School of Information Science and Engineering Yanshan University Qinhuangdao China Key Laboratory for Computer Virtual Technology and System Integration of Hebei Province China Key Laboratory of Software Engineering of Hebei Province China

The Object tracking is a challenging problem in computer vision field. Now, deep learning has made outstanding achievements in feature extraction. There are already some examples of deep learning applications in visual tracking. But, they almost paid attention to precision and sacrificed efficiency. So we propose a tracker named adaptive combination tracker(ACT), based on neural network model, which gives consideration to both precision and efficiency. Our ACT tracker gets rich features offline through Stacked Denoising Autoencoders (SDAE) and transfers them to online tracking. In tracking, a dynamic particle filter algorithm is proposed to speed up tracking. We update our tracker with different patterns according to the change in appearance. In order to ensure efficiency, our tracker regulates speed adaptively. Our tracker regulates speed precisely to avoid drift caused by fast motion as much as possible, and confirm and optimize the effectiveness of the results by comparison with previous target. We evaluate our tracker on OTB2013 datasets. Extensive experiments on OTB2013 datasets demonstrate that the proposed tracker performs favorably in relation to the state-of-the-art methods. © 2020 computer Society of the Republic of China. All rights reserved.

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 energy saving strategy in digital cognitive radio networks and its performance assessment

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ICIC Express Letters 2016年第6期10卷 1367-1373页

作者： Jin, Shunfu Chen, Si School of Information Science and Engineering Yanshan University No. 438 Hebei Ave Qinhuangdao066004 China Key Laboratory for Computer Virtual Technology and System Integration of Hebei Province Yanshan University No. 438 Hebei Ave Qinhuangdao066004 China

With the explosive growth of wireless application, how to improve the spectrum efficiency as well as reduce the communication consumption is a hot topic of research. In this paper, we propose a novel energy saving strategy in digital cognitive radio networks (CRNs). The key idea of this strategy is to set the base station (BS) of CRNs into sleep state when there are not any packets to be transmitted. Accordingly, we develop a Markov chain model to assess the average latency of secondary user (SU) packets and the energy saving ratio of system. Finally, we provide numerical results to show that there is a tradeoff when setting the sleep timer length for the proposed energy saving strategy. © 2016 ISSN.

关键词： Energy conservation

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Performance analysis of the centralized channel allocation strategy in cognitive radio networks

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ICIC Express Letters 2013年第7期7卷 2189-2196页

作者： Dai, Yu Jin, Shunfu Meng, Chao 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 Yanshan University No. 438 Hebei Ave Qinhuangdao 066004 China

Based on the centralized channel allocation strategy in the Cognitive Radio Networks, considering the opportunistic channel access for Secondary Users, a discretetime queueing model with a general transmission time and possible transmission interruption is established. By using the method of an embedded Markov chain, the system model is analyzed in steady state, and the performance metrics in terms of the average latency, the throughput for the Secondary User, the channel switching ratio and the channel utilization are given accordingly. Analysis results and simulation experiments are provided to investigate the influence of the traffic load for the Secondary User and the arrival rate for the Primary User packets on the system performance. © 2013 ICIC International.

关键词： Cognitive radio

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New construction of quaternary sequence with even period based on cyclotomic classes of order two

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ICIC Express Letters 2015年第7期9卷 1959-1964页

作者： Jia, Yanguo Shi, Yan Duan, Xiaobei Shen, Xiumin School of Information Science and Engineering Yanshan University No. 438 West Hebei Street Qinhuangdao China The Key Laboratory for Computer Virtual Technology and System Integration of Heibei Province No. 438 West Hebei Street Qinhuangdao China

In this paper, we present a new method for constructing quaternary sequence with even period 2f based on cyclotomic classes of order two. Under the premise of v = 2f +1, we construct two binary sequences with period 2f. Then we can construct a new quaternary sequence from those two binary sequences by using the reverse Gray Mapping. The distribution of autocorrelation function of the proposed quaternary sequence is also derived, which is decided by the parity of f. © 2015, ISSN 1881-803X.

关键词： Binary sequences

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Efficiently mining top-k high utility path patterns in software dynamic call graph

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ICIC Express Letters 2016年第1期10卷 211-218页

作者： He, Haitao Yin, Tengteng Wu, Hongfei Ren, Jiadong College of Information Science and Engineering Yanshan University No. 438 West Hebei Ave Qinhuangdao China The Key Laboratory for Computer Virtual Technology and System Integration of Hebei Province Yanshan University No. 438 West Hebei Ave Qinhuangdao China

Software behavior mining is a very meaningful work. Finding that desirable patterns can assist the program maintainers to comprehend the software adequately. Although the existing high utility pattern mining algorithms can discover all the patterns satisfying a given minimum utility, it is often dicult for users to set a proper minimum utility. In this paper, an ecient algorithm TUPP is presented to mine top-k high utility path patterns in software dynamic call graph. In TUPP, software paths are extracted from software dynamic call graph and the utility of functions is dened rstly. Secondly, a novel structure called PUAList is put forward. The structure stores both the adjacency items and the utility information which is heuristic information for pruning the search space. In addition, two strategies for raising the threshold and one pruning strategy are incorporated into TUPP to increase the eciency. At last, our experiments are conducted on both synthetic and real datasets. The results show that TUPP incorporating the eciency-enhanced strategies demonstrates impressive performance. © 2016 ICIC International.

关键词： Graph theory

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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 scalab.lity. © 2014 ISSN 1881-803X.

关键词： Delay decomposition Frequent sequence Maximal frequent sequence

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