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RNA secondary structure prediction based on density-based clustering

ICIC Express Letters 2015年第7期9卷 1965-1970页

作者： Wang, Changwu Wang, Xiuqin Wang, Baowen Liu, Wenyuan Wei, Zhenzhen Li, Yongqiang School of Information Science and Engineering Yanshan University No. 438 Hebei Ave Qinhuangdao China The Key Laboratory for Computer Virtual Technology and System Integration of Hebei Province Yanshan University No. 438 Hebei Ave Qinhuangdao China Department of Information The First Hospital of Qinhuangdao No. 258 Hebei Ave Qinhuangdao China

The ribonucleic acid (RNA) secondary structure prediction has designed to characterize the ensemble of structures, instead of only computing the minimum free energy structure. Clustering methods are brought to aid in the characterization of the structure ensemble. These methods group the structures into a small number of clusters. A representative structure for each cluster is computed to characterize the central tendency for the structures in each cluster and used to predict the true secondary structure. This paper introduces a density based clustering with extensible radius dubbed ER-DBSCAN for handling varying density clustering. The basic idea of ER-DBSCAN is to use different values of radius for different densities. It starts from the highest density object towards the lowest density object, and the radius of the cluster is automatically adjusted during cluster expansion according to the density distribution and density variation. Our results indicate that ER-DBSCAN can detect and handle clusters of varying density, and cluster RNA secondary structures effectively. © 2015, ISSN 1881-803X.

关键词： RNA

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The study of a hierarchical hadoop architecture in multiple data centers environment

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Open Cybernetics and systemics Journal 2015年第1期9卷 131-137页

作者： Shengtao, Sun Aizhi, Wu Xiaoyang, Liu School of Information Science and Engineering Yanshan University QinhuangdaoHebei066004 China College of Vehicles and Energy Yanshan University QinhuangdaoHebei066004 China Data Industry Research Institute Limited Company QinhuangdaoHebei066004 China Key Laboratory for Computer Virtual Technology and System Integration of Hebei Province QinhuangdaoHebei066004 China

Hadoop is a reasonable tool for cloud computing in big data era and MapReduce paradigm may be a highly successful programming model for large-scale data-intensive computing application, but the conventional MapReduce model and Hadoop framework limit themselves to implement jobs within single cluster. Traditional single-cluster Hadoop may not suitable for situations when data and compute resources are widely distributed this paper focuses on the application of Hadoop across multiple data centers and clusters. A hierarchical distributed computing architecture of Hadoop is designed and the virtual Hadoop file system is proposed to provide global data view across multiple data centers. The job submitted by user can be decomposed automatically into several sub-jobs which are then allocated and executed on corresponding clusters by location-aware manner. The prototype based on this architecture shows encouraging results. © Shengtao et al.

关键词： MapReduce

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Dynamic spectrum allocation scheme with real-time traffic and its performance optimization

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ICIC Express Letters, Part B: Applications 2015年第8期6卷 2243-2250页

作者： Shi, Guoying Jin, Shunfu Li, Yongqiang School of Information Science and Engineering Yanshan University No. 438 Hebei Avenue Qinhuangdao China Key Laboratory for Computer Virtual Technology and System Integration of Hebei Province Yanshan University No. 438 Hebei Avenue Qinhuangdao China The First Hospital of Qinhuangdao No. 258 Wenhua Road Qinhuangdao China

Aiming at relieving the shortage problem of wireless frequency resource, sec- ondary users in cognitive radio networks occupy the spectrum hole opportunistically. In cognitive radio networks, primary users have preemptive priority for the licensed spectrum, and the data transmission of a secondary user is possible to be interrupted by a primary user at any time. For the applications with real-time traffic, the interrupted data is supposed to be discarded by the system. A continuous time queueing model with potential transmission interruption is established accordingly. By using the Laplace transform, the performance measures, such as the average latency, the normalized throughput and the spectrum switching ratio, are presented. The individually and socially optimal strategies are investigated with a non-cooperative game theory, and then a pricing policy for the secondary users is proposed. Experimental results show that the dynamic spectrum allocation scheme with real-time traffic can be optimized socially. © 2015, ICIC International.

关键词： Laplace transforms

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

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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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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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Performance evaluation of an enhanced Ethernet energy saving mechanism in IEEE 802.3az

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Journal of Information and Computational Science 2014年第5期11卷 1605-1613页

作者： Zhi, Shengyang Jin, Shunfu Meng, Chao College of Information Science and Engineering Yanshan University Qinhuangdao 066004 China Key Laboratory for Computer Virtual Technology and System Integration of Hebei Province Qinhuangdao 066004 China

In order to reduce the energy consumption and improve the response performance, by introducing the strategies of sleep-delay, pre-awake and split timing to IEEE 802.3az, an enhanced Ethernet energy saving mechanism is proposed. Considering the digital nature of modern communications, a discrete-time queueing model with multiple-vacation and N-strategy is built. With the method of an embedded Markov chain, we evaluate the energy saving efficiency of the system and the response performance of the data frames mathematically. Numerical experiments and simulation results show that, in the enhanced Ethernet energy saving mechanism, the average packet latency is reduced, while the energy saving ratio is satisfactory. © 2014 by Binary Information Press.

关键词： Energy conservation

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Mining weighted frequent traversal pattern from software executing graph

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ICIC Express Letters 2015年第11期9卷 2893-2900页

作者： He, Haitao Yin, Tengteng Pei, Caiyan Wu, Hongfei Ren, Jiadong College of Information Science and Engineering 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 School of Mathematics and Information Science and Technology Hebei Normal University of Science and Technology No. 360 West Hebei Street Qinhuangdao China

Mining important patterns in complex software executing network plays an important role in analyzing software security. The general sequential pattern mining algorithms may lead to poor performance due to the lack of consideration on the continuous property of software path traversals and the different importance of functions. To address the issue, a novel approach called weighted frequent traversal pattern miner (WFTPMiner) to mine weighted frequent traversal pattern from software executing graph is presented in this paper. In WFTPMiner, weighted software executing graph (WSEG) is modeled firstly. Secondly, software path traversals are extracted from WSEG by depthfirst- search (DFS) strategy. Thirdly, according to continuity characteristics of software path traversals, a potential frequent suffix sequence tree (PFSS-Tree) is defined to store the potential weighted frequent traversal patterns. A pruning strategy is adopted by PFSSTree. The pruning strategy can prune infrequent patterns effectively. The experimental results show that WFTPMiner has better efficiency compared with some previous algorithms. © 2015 ICIC International.

关键词： Forestry

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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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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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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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