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International Conference on Communication technology (ICCT)

作者： Xiaoming Wu Yinglong Wang Yifan Hu Sbandong Provincial Key Laboratory of Computer Networks Jinan China Shandong Computer Science Center National Supercomputer Center in Jinan Jinan China College of Information Science and Engineering Shandong University of Science and Technology Qingdao China

ISBN: (纸本)9781467370066

Recent studies have shown that utilizing a mobile sink to harvest and carry data from wireless sensor network (WSN) can enhance network operations and balance the network energy consumption. Because of the sink mobility, the paths between the sensor nodes and the sink change frequently, and have profound influence on the lifetime of WSN. To find an efficient protocol that can maintain the routes between the mobile sink and nodes with few network resources are important. We propose a swarm intelligent algorithm based route maintaining protocol in this paper to resolve this issue. The protocol utilizes the concentric ring mechanism to guide the route researching direction, and the optimal routing selection to maintain the data delivery route. Using the immune based artificial bee colony (IABC) algorithm to optimize the forwarding path, the protocol could find an alternative path efficiently when sink moves. The results of our experiments demonstrate that the protocol could balance the network traffic load.

关键词： Routing protocols Wireless sensor networks Artificial neural networks TV

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Adaptive cultural algorithm for combinational digital circuit sensor design

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Sensor Letters 2015年第2期13卷 127-129页

作者： Yan, Xuesong Hu, Chengyu Yao, Hong Wu, Qinghua Liu, Hanmin School of Computer Science China University of Geosciences Wuhan China Hubei Provincial Key Laboratory of Intelligent Robot Wuhan Institute of Technology Wuhan China School of Computer Science and Engineering Wuhan Institute of Technology Wuhan China Wuhan Institute of Ship Building Technology Wuhan China

Aiming at the disadvantages of basic Cultural Algorithms (CA) like being trapped easily into a local optimum, this paper improves the basic Cultural Algorithms and proposes the improved cultural algorithm with adaptive search operator (ACA) to solve the overcomes of the basic Cultural Algorithms. The new algorithm keeps not only the fast convergence speed characteristic of basic Cultural Algorithms, but effectively improves the capability of global searching as well. For the case studies, the new algorithm means has proved to be efficient and the experiment results show that the new means have got the better results. We also use the proposed algorithm for combinational digital circuit sensor optimization design, from the experiment results shown our algorithm are effective for this problem. Copyright © 2015 American Scientific Publishers All rights reserved.

关键词： Timing circuits

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Multiple SVM-RFE for Multi-class Gene Selection on DNA Microarray Data

Multiple SVM-RFE for Multi-class Gene Selection on DNA Micro...

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International Joint Conference on Neural networks

作者： Li Zhang Xiaojuan Huang School of Computer Science and Technology & Collaborative Innovation Center of Novel Software Technology and Industrialization Soochow University Suzhou 215006 Jiangsu China School of Computer Science and Technology & Provincial Key laboratory for Computer Information Processing Soochow University Suzhou 215006 Jiangsu China

ISBN: (纸本)9781479919611

This paper presents a new multi-class gene selection and classification method based on multiple support vector machine recursive feature elimination (SVM-RFE). For a multi-class DNA microarray problem, we solve it as multiple binary classification problems. First, the one-versus-all method is used to decompose the multi-class task into multiple binary problems. Second, an SVM-RFE is adopted to select genes for each binary problem. Then, an SVM classifier is used to train the selected gene data for a binary problem. Finally, we combine the outputs of multiple SVM classifiers. Experimental results on three DNA Microarray datasets show that the proposed method achieves higher classification accuracy.

关键词： support vector machine feature selection recursive feature elimination multi-class classification DNA microarray data Support Vector Network Feature extraction multi-class DNA Microarrays Phyla Genes Binary Classification Methods

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Primary Exploration of Reliability Evaluation of computer Live Forensics Model on Physical Memory Analysis

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Journal of Harbin Institute of technology(New Series) 2014年第4期21卷 121-128页

作者： Lian-Hai Wang Qiu-Liang Xu School of Computer Science and Technology Shandong University Shandong Provincial Key Laboratory of Computer Network Shandong Computer Science Center( National Supercomputer Center in Jinan)

The integrity and fidelity of digital evidence are very important in live forensics. Previous studies have focused the uncertainty of live forensics based on different memory snapshots. However,this kind of method is not effective in practice. In fact,memory images are usually acquired by using forensics tools instead of using snapshots. Therefore,the integrity and fidelity of live evidence should be evaluated during the acquisition process. In this paper,we study the problem in a novel viewpoint. Firstly,several definitions about memory acquisition measure error are introduced to describe the trusty. Then,we analyze the experimental error and propose some suggestions on how to reduce it. A novel method is also developed to calculate the system error in detail. The results of a case study on Windows 7 and VMware virtual machine show that the experimental error has good accuracy and precision,which demonstrate the efficacy of the proposed reducing methods. The system error is also evaluated,that is,it accounts for the whole error from 30% to 50%.

关键词： digital investigation live forensics volatile memory acquisition trusted probability

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An improved social force evacuation model with grouping and guiding

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Journal of Computational Information Systems 2015年第20期11卷 7553-7562页

作者： Lv, Yuanyang Liu, Hong Lu, Dianjie School of Information Science and Engineering Shandong Normal University Ji'nan China Shandong Provincial Key Laboratory for Distributed Computer Software Novel Technology Ji'nan China

Crowd evacuation simulation is of great significance for strategy design in emergency, resulting in serious injuries and casualties. A majority of existing evacuation models overlooked the interactions and influences between pedestrians. Therefore, a crowd evacuation model based on grouping and guiding was come up with, which is based on an improved social force model. The improved model optimized the trend selecting strategy of movement and added a force called relationship attractive force. The movement is determined by pedestrian's trend and composite force. According to the results of experiments, this proposed model can realize that pedestrians having intimate relationships with each other would get together gradually in process of crowd evacuation and made the effects more realistically. Copyright © 2015 Binary Information Press.

关键词： Crowd evacuation Group partition Social force model Social relationship

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LTFML: Multi-label learning based on label typical features

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Journal of Computational Information Systems 2015年第4期11卷 1497-1504页

作者： Zheng, Xiyuan Zhang, Huaxiang Fang, Xiaonan Meng, Lili School of Information Science and Engineering Shandong Normal University Jinan China Shandong Provincial Key Laboratory for Novel Distributed Computer Software Technology Jinan China Jinan China

In recent years, multi-label learning is becoming a new research hot spot. In this paper, we proposed a multi-label learning method called LTFML based on the idea of trying to determine the typical features for each class label. First, LTFML choose those samples with some specific class label from the multilabel data set and cluster these selected samples. We use these clustering centers gained by above step as typical features which can represent effectively this class label. Then the distances between each sample and these clustering centers are used to represent each sample and weighted according to the standard deviations of each clustering cluster. Finally, a set of SVM classifiers are used to estimate the class label vector of unseen instance. Experimental results show that LTFML can have a very good performance over the well-known multi-label learning algorithms. 1553-9105/Copyright © 2015 Binary Information Press

关键词： Learning algorithms

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Spider: A Non-blocking Optical Router for Multicasting Communication in ONoC

Spider: A Non-blocking Optical Router for Multicasting Commu...

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International Conference on computer science and Network technology

作者： Lei Huang Huaxi Gu Bowen Zhang Xuesong Wang Kun Wang State Key Laboratory of Integrated Services Networks Xidian University Xi'an China School of Computer Science and Technology Xidian University Xi'an China

ISBN: (纸本)9781467381741

Optical Network-on-Chip (ONoC) architectures have attracted increasing attention as an optimized solution for intra-core communication. Due to the explosive growth in communication traffic, more multicast demands have been brought. Nevertheless, as a key role in an on-chip photonic interconnection network, the most existing routers cannot satisfy multicasting need. In this paper, we propose a kind of non-blocking optical router of 4x4 and 5x5 architectures named Spider for multicasting communication in optical network-onchip. Spideremploys fewer microring resonators, lower insertion loss, and reduces power consumption when compared with previous ONoC router designs.

关键词： Optical routers Multicasting communication Nonblocking multicast communication Spiders telecommunication traffic Interconnection networks

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Digital circuit optimization design algorithm based on cultural evolution

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Metallurgical and Mining Industry 2015年第9期7卷 877-885页

作者： Yan, Xuesong Wu, Qinghua Liu, Hanmin School of Computer Science China University of Geosciences Wuhan Hubei China Hubei Provincial Key Laboratory of Intelligent Robot Wuhan Institute of Technology Wuhan Hubei China School of Computer Science and Engineering Wuhan Institute of Technology Wuhan Hubei China Wuhan Institute of Ship Building Technology Wuhan Hubei China

Cultural Algorithms (CA) are a class of computational models derived from observing the cultural evolution process in nature. The Cultural Algorithm is a dual inheritance system that characterizes evolution in human culture at both the macro-evolutionary level, which takes place within the belief space, and at the micro-evolutionary level, which occurs at the population space. Cultural algorithm is used to solve complex calculations of the new global optimization search algorithms, cultural algorithms in the optimization of the complex functions of its superior performance. In this paper, we use the this algorithm for combinational digital circuit optimization design, from the experiment results shown our algorithm are effective for this problem.

关键词： Global optimization

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A Study of a Virtual Network Embedding Algorithm

A Study of a Virtual Network Embedding Algorithm

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IEEE International Conference on Ubiquitous Computing and Communications

作者： Zhen-hua Chen Xiang-wei Zheng Dian-jie Lu School of Information Science and Engineering Shandong Normal University Jinan China Shandong Provincial Key Laboratory for Distributed Computer Software Novel Technology Jinan China

ISBN: (纸本)9781509001552

Currently, energy cost has become an important burden of infrastructure providers in network virtual environment. Therefore, consolidating nodes and links to save energy is an effective method when virtual networks are embedded on substrate network. The traditional embedding method usually considers cost minimization or revenue maximization as its goal. This paper studies the problem of energy consumption, cost and revenue simultaneously and a virtual network embedding model saving energy is proposed. Then, a heuristic algorithm base on group search optimizer is developed. The simulation experiments show that the proposal can effectively reduce energy consumption when a large quantity of virtual networks arrives.

关键词： Substrate network Virtual network style Virtual network embedding Energy consumption Group Search Optimizer

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Microblog Orientation Analysis Based on Connnectives

Microblog Orientation Analysis Based on Connnectives

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International Conference on Broadband, Wireless Computing, Communication and Applications (BWCCA)

作者： Jun Zhao Hong Wang School of Information Science and Engineering Shandong Normal University Jinan China Shandong Provincial Key Laboratory for Distributed Computer Software Novel Technology Jinan China

ISBN: (纸本)9781467383165

At present, a larger number of researchers analyzed Micro-blog orientation and they concentrated their energy on emotional words, adverb and negative words without considering the impact of other emotional factors, such as the coordinative relation, progressive relation and adversative relation. So a method studying the sentiment polarity of associated words was proposed. The structure characteristics of associated words were analyzed sufficiently, and a turning words dictionary, a Chinese emotion dictionary and a negative words dictionary were founded based on the existing dictionary. This paper considers the combination laws of negative words, adversative words and conjunctions into Micro-blog. In the experiments, we verify this method can analyze the sentiment polarity of transition sentences efficiently and also has higher classification accuracy.

关键词： Dictionaries Support vector machines Blogs Turning Feature extraction Mutual information Software

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