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2016 IEEE International Conference on Progress in Informatics and computing

作者： Shui-Hua Wang Hui-Min Lu Yu-Jie Li Yang Wang Zhi-Min Chen Yu-Min Wei Wen-Juan Jia Fang-Yuan Liu Yu-Dong Zhang School of Computer Science and Technology Nanjing Normal University Hunan Provincial Key Laboratory of Network Investigational Technology Hunan Policy Academy Department of Electrical Engineering The city college of New YorkCUNY Department of Mechanical and Control Engineering Kyushu Institute of Technology School of Information Engineering Yangzhou University School of Physics and Electronic Engineering Taizhou University School of Electronic Information Shanghai Dianji University School of Energy and Mechanical Engineering Nanjing Normal University Key Laboratory of Intelligent Computing and Information Processing in Fujian Provincial University Quanzhou Normal University

Cluster analysis is important in scientific and industrial fields. In this study, we proposed a novel chaotic biogeography-based optimization(CBBO) method, and applied it in centroid-based clustering methods. The results over three types of simulation data showed that this proposed CBBO method gave better performance than chaotic particle swarm optimization, genetic algorithm, firefly algorithm, and quantum-behaved particle swarm optimization. In all, our CBBO method is effective in centroid-based clustering.

关键词： chaotic biogeography-based optimization cluster analysis centroid-based clustering simulation particle swarm optimization

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A new logistic map based chaotic biogeography-based optimization approach for cluster analysis

A new logistic map based chaotic biogeography-based optimiza...

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IEEE International Conference on Progress in Informatics and computing (PIC)

作者： Shui-Hua Wang Hui-Min Lu Yu-Jie Li Yang Wang Zhi-Min Chen Yu-Min Wei Wen-Juan Jia Fang-Yuan Liu Yu-Dong Zhang Hunan Provincial Key Laboratory of Network Investigational Technology Hunan Policy Academy Changsha Hunan China School of Computer Science and Technology Nanjing Normal University Nanjing Jiangsu China Department of Electrical Engineering CUNY New York NY USA Department of Mechanical and Control Engineering Kyushu Institute of Technology Fukuoka Prefecture Japan School of Information Engineering Yangzhou University Yangzhou Jiangsu China School of Physics and Electronic Engineering Taizhou University Taizhou Zhejiang China School of Electronic Information Shanghai Dianji University Shanghai China School of Energy and Mechanical Engineering Nanjing Normal University Nanjing Jiangsu China Key Laboratory of Intelligent Computing and Information Processing in Fujian Provincial University Quanzhou Normal University Quanzhou Fujian China

ISBN: (纸本)9781509034857

Cluster analysis is important in scientific and industrial fields. In this study, we proposed a novel chaotic biogeography-based optimization (CBBO) method, and applied it in centroid-based clustering methods. The results over three types of simulation data showed that this proposed CBBO method gave better performance than chaotic particle swarm optimization, genetic algorithm, firefly algorithm, and quantum-behaved particle swarm optimization. In all, our CBBO method is effective in centroid-based clustering.

关键词： Genetic algorithms Optimization Clustering algorithms Particle swarm optimization Algorithm design and analysis Logistics Mathematical model

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The Recognition of Maize seeds Based on Multi-scale Feature Fusion and Extreme Learning Machine

The Recognition of Maize seeds Based on Multi-scale Feature ...

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2015 3rd International Conference on Mechanical Engineering and intelligent Systems(ICMEIS 2015)

作者： Mingzhi Du Xiao Ke Mingke Zhou College of Mathematics and Computer Science Fuzhou University Fujian Provincial Key Laboratory of Networking Computing and Intelligent Information Processing (Fuzhou University)

In recognizing traditional crops seeds like maize seeds, we usually use electrophoresis assay method, fluorescence scanning method and chemical assay method. These methods are destructive methods. They take a long time to detect and are demanding of professional background knowledge and hardware conditions etc. What's more, these methods, based on BP neural network and support vector machine(SVM)while taking a long time to detect are less accurate in process of classification. In this paper, based on the computer vision technology, we proposed a new method for the classification of maize seeds, a method based on multi-scale feature fusion and extreme learning machine. First, we extract the multi-scale fusion feature of maize seeds. Second, based on extreme learning machine, we construct the classifier model of maize seed. Third, because of the window of image in the case of multi-scale detection has the problem of capturing the same object seed with many overlapping windows, we put forward a kind of window fusion algorithm to solve it. The simulation results show that: The method is able to identify the maize seeds accurately. Using this method the accuracy of classification of maize seeds can reached 97.66% and the error rate is less than 0.1%. Compared with the traditional methods, the method we proposed can improve the speed of detection and the accuracy of classification, and has no strict hardware requirements.

关键词： extreme learning machine feature fusion object recognition

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XGRouter: high-quality global router in X-architecture with particle swarm optimization

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Frontiers of Computer Science 2015年

作者： Liu, Genggeng Guo, Wenzhong Li, Rongrong Niu, Yuzhen Chen, Guolong College of Mathematics and Computer Science Fuzhou University Fuzhou350116 China Fujian Provincial Key Laboratory of Network Computing and Intelligent Information Processing Fuzhou University Fuzhou350116 China

This paper presents a high-quality very large scale integration (VLSI) global router in X-architecture, called XGRouter, that heavily relies on integer linear programming (ILP) techniques, partition strategy and particle swarm optimization (PSO). A new ILP formulation, which can achieve more uniform routing solution than other formulations and can be effectively solved by the proposed PSO is proposed. To effectively use the new ILP formulation, a partition strategy that decomposes a large-sized problem into some small-sized sub-problems is adopted and the routing region is extended progressively from the most congested region. In the post-processing stage of XGRouter, maze routing based on new routing edge cost is designed to further optimize the total wire length and mantain the congestion uniformity. To our best knowledge, XGRouter is the first work to use a concurrent algorithm to solve the global routing problem in X-architecture. Experimental results show that XGRouter can produce solutions of higher quality than other global routers. And, like several state-of-the-art global routers, XGRouter has no overflow. © 2015 Higher Education Press and Springer-Verlag Berlin Heidelberg

关键词： VLSI circuits

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Cost-Driven Scheduling for Deadline-Constrained Workflow on Multi-clouds

Cost-Driven Scheduling for Deadline-Constrained Workflow on ...

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IEEE International Symposium on Parallel and Distributed processing Workshops and Phd Forum (IPDPSW)

作者： Bing Lin Wenzhong Guo Guolong Chen Naixue Xiong Rongrong Li College of Mathematics and Computer Sciences Fuzhou University Fuzhou PR China Fujian Provincial Key Laboratory of Network Computing and Intelligent Information Proccssing Fuzhou PR China School of Computer Science Colorado Technical University Colorado Springs CO USA

ISBN: (纸本)9781467376853

The tremendous parallel computing ability of Cloud computing as a new service provisioning paradigm encourages investigators to research its drawbacks and advantages on processing large-scale scientific applications such as workflows. The current Cloud market is composed of numerous diverse Cloud providers and workflow scheduling is one of the biggest challenges on Multi-Clouds. However, the existing works fail to either satisfy the Quality of Service (QoS) requirements of end users or involve some fundamental principles of Cloud computing such as pay-as-you-go pricing model and heterogeneous computing resources. In this paper, we adapt the Partial Critical Paths algorithm (PCPA) for the multi-cloud environment and propose a scheduling strategy for scientific workflow, called Multi-Cloud Partial Critical Paths (MCPCP), which aims to minimize the execution cost of workflow while satisfying the defined deadline constrain. Our approach takes into account the essential characteristics on Multi-Clouds such as charge per time interval, various instance types from different Cloud providers as well as homogeneous intra-bandwidth vs. Heterogeneous inter-bandwidth. Various well-know workflows are used for evaluating our strategy and the experimental results show that the proposed approach has a good performance on Multi-Clouds.

关键词： Scheduling Schedules Cloud computing Processor scheduling Data transfer Quality of service Bandwidth

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A forensics tool of Foxmail client

A forensics tool of Foxmail client

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International Conference on Systems and Informatics (ICSAI)

作者： Lili Xie Guolong Chen College of Mathematics and Computer Science Fujian Provincial Key Laboratory of Network Computing and Intelligent Information Processing Fuzhou Fujian China

ISBN: (纸本)9781479954599

Computer forensics is an important part of the computer crime investigation. So a Forensics system aimed to Foxmail data analysis and investigation is proposed in this paper. The system can index the email data based on Lucene technology and the MMSeg participle algorithm, and provides the full text retrieval of the email content function. Subsequently, a visual communication graph would be generated according to the retrieval results. Based on the communication graph, an algorithm on graphic structure analysis is proposed, and by means of centrality and minimum traffic filtering method, multilevel analysis is carried out on the graph, which can detect the possible suspicious personnel and their relationships and provide strong support for the computer crime investigation.

关键词： Electronic mail Forensics Postal services Indexes Filtering Personnel Algorithm design and analysis

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A weighted lexicon-based generative model for opinion retrieval

A weighted lexicon-based generative model for opinion retrie...

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International Conference on Machine Learning and Cybernetics (ICMLC)

作者： Xiang-Wen Liao Hu Chen Jing-Jing Wei Zhi-Yong Yu Guo-Long Chen Fujian Provincial Key Laboratory of Network Computing and Intelligent Information Processing Fuzhou University Fuzhou China

ISBN: (纸本)9781479942145

In recent years, opinion retrieval attracted a growing research interest as online users' opinions become more and more valuable for market survey, political polls, etc. The goal of opinion retrieval is to find relevant and opinionate documents according to a user's query. Compared with previous lexicon-based generative model for opinion retrieval considering that the sentiment words are equal for a query, which cannot reflect different sentiment words' relevant opinion strength, we propose a graph-based approach by using HITS model to capture the sentiment words' relevant opinion strength. Then the weights are incorporated into the weighted lexicon-based generative model for opinion retrieval. Experimental results on two datasets show the effectiveness of the proposed generative model. Compared with the baseline approach, improvements of 4% and 11% have been obtained on two real datasets.

关键词： Computational modeling Twitter Analytical models Abstracts

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A heterogeneous graph model for social opinion detection 13

A heterogeneous graph model for social opinion detection

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13th International Conference on Machine Learning and Cybernetics, ICMLC 2014

作者： Liao, Xiangwen Huang, Yichao Wei, Jingjing Yu, Zhiyong Chen, Guolong College of Mathematics and Computer Science Fuzhou University Fuzhou350116 China College of Physics and Information Engineering Fuzhou University Fuzhou350116 China Fujian Provincial Key Laboratory of Network Computing and Intelligent Information Processing Fuzhou University Fuzhou350116 China

ISBN: (纸本)9783662456514

Microblogging services, such as Twitter, have become popular for people to share their opinions towards a broad range of topics. It is a great challenge to get an overview of some important topics by reading all tweets every day. Previous researches such as opinion detection and opinion summarization have been studied for this problem. However, these works mainly focus on the content of text without taking the quality of short text and features of social media into consideration. In this paper, we propose a heterogeneous graph model for users’ opinion detection on microblog. We first extract keywords of topics. Then, a three-level microblog graph is constructed by combining user influence, word importance, post significance, and topic periodicity. Microblog posts are ranked from different topics by using the random walk algorithm. Experimental results on real a dataset validate the effectiveness of our approach. In comparison with baseline approaches, the proposed method achieves 8% improvement. © Springer-Verlag Berlin Heidelberg 2014.

关键词： Random processes

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A forensics method of web browsing behavior based on association rule mining

A forensics method of web browsing behavior based on associa...

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International Conference on Systems and Informatics (ICSAI)

作者： Yiyun Zhang Guolong Chen College of Mathematics and Computer Science Fuzhou University Fujian Provincial Key Laboratory of Network Computing and Intelligent Information Processing Fuzhou Fujian China

ISBN: (纸本)9781479954599

With the development of network, web forensics is becoming more and more important due to the rampant cybercrime. In this paper, a forensics method of web browsing behavior based on association rule mining is presented. The method aims at providing the necessary data support to build the behavior pattern library for investigation. The records of the user's browsing history are collected to be analyzed. The obtained original data are pretreated to transactional data which are suitable for association rule mining. Frequent browsing time and frequent web browsing sequences are obtained from the transactional data by Apriori algorithm. The mining results are helpful for identification and recognition of anonymous or suspicious web browsing behavior patterns.

关键词： History Browsers Forensics Association rules Libraries Uniform resource locators

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Data Replication Placement Strategy Based On Bidding Mode for Cloud Storage Cluster

Data Replication Placement Strategy Based On Bidding Mode fo...

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2014 11th Web information System and Application Conference(第十一届全国web信息系统及其应用学术会议)

作者： Hong Zhang Bing Lin Zhanghui Liu Wenzhong Guo College of Mathematics and Computer Science Fujian Provincial Key Laboratory of Network Computing and Intelligent Information Processing Fuzhou University Fuzhou 350116 China

ISBN: (纸本)9781479957286

The data availability in large-scale cloud storage has been increasing by means of data *** provide cost-effective availability, minimize the response time of applications and make load balancing for cloud storage, a new replica placement policy with bidding thought is *** policy combines the own characteristics of replica and factors of bidding mode(e.g, bidding time, bidding standard, bidding price etc.) and starts replica bidding activity when the file data availability cannot meet the given *** placement is based on capacity and accessing probability of data *** experimental results show that our policy has a better performance in both load balance and response time comparing to the static replica policy and CDRM scheme.

关键词： Data Replica Bidding Mode Cloud Storage Load Balance

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