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2015 IEEE International Conference on Progress in Informatics and Computing(PIC 2015)

作者： Tianming Zhan Yang Xu Zebin Wu School of Computer Science and Communication Engineering Jiangsu University Jiangsu Key Laboratory of Meteorological Observation and Information Processing Nanjing University of Information Science and Technology School of Computer Science and Engineering Nanjing University of Science and Technology

Spectral-spatial classification is very important in the field of remotely sensed hyperspectral imaging. The Markov Random Field(MRF) is usually used to provide the spatial constraint. However, the traditional construction of MRF uses a neighborhood and gives the same weight for all the pixels in the same neighborhood. Without the structure information in HSI, the performance of classification is not good enough. In this paper, we propose two improvements on MRF: the adaptive MRF is constructed according to spectral similarity of the spatial patch to reflect the structure information in HSI;a regularized method with a high confidence index(HCI) rule is presented to determine the refined probabilities of each pixel that promotes spatial continuity within each class. The effect of HCI rule is utilized to treat the probabilities discriminately, where the vectors with HCI are supposed to be well labeled. And the original probabilities of the pixels belong to each class are obtained by the spectral information using nearest regularized subspace(NRS) method in the first step. Experimental results on real hyperspectral data set demonstrate that the proposed method outperforms many existing methods in terms of the overall accuracy, average accuracy and kappa statistic.

关键词： Hyperspectral image classification Nearest regularized subspace Adaptive MRF High confidence index

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An endocrine cooperative particle swarm optimization algorithm for routing recovery problem of wireless sensor networks with multiple mobile sinks

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information Sciences 2015年第1期300卷 100-113页

作者： Hu, Yi-Fan Ding, Yong-Sheng Ren, Li-Hong Hao, Kuang-Rong Han, Hua Engineering Research Center of Digitized Textile and Fashion Technology Ministry of Education Donghua University Shanghai 201620 China Shandong Computer Science Center (National Supercomputer Center in Jinan) Jinan 250014 China College of Information Sciences and Technology Donghua University Shanghai 201620 China Shandong Provincial Key Laboratory of Computer Network Jinan 250014 China College of Electronic and Electrical Engineering Shanghai University of Engineering Science Shanghai 201620 China

In the wireless sensor networks with multiple mobile sinks, the movement of sinks or failure of sensor nodes may lead to the breakage of the existing routes. In most routing protocols, the query packets are broadcasted to repair a broken path from source node to sink, which cause significant communication overhead in terms of both energy and delay. In order to repair broken path with lower communication overhead, we propose an efficient routing recovery protocol with endocrine cooperative particle swarm optimization algorithm (ECPSOA) to establish and optimize the alternative path. In the ECPSOA, mutation direction of the particle is determined by multi-swarm evolution equation, and its diversity is enriched by the endocrine mechanism, which can enhance the capacity of global search and improve the speed of convergence and accuracy of the algorithm. By using this method, the alternative path from source nodes to the sink with the optimal QoS parameters can be selected. Simulation results show that our routing protocol significantly improves the robustness and adapts to rapid topological changes with multiple mobile sinks, while efficiently reducing the communication overhead and the energy consumption. © 2014 Elsevier Inc. All rights reserved.

关键词： Endocrine cooperative mechanism Multiple mobile sinks PSO algorithm Routing recovery Wireless sensor networks

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Context-aware computing for smart home environment

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Journal of Computational information Systems 2015年第15期11卷 5453-5460页

作者： Liu, Li Fu, Xiaodong Liu, Lijun Huang, Qingsong Yunnan Provincial Key Laboratory of Computer Technology Application Faculty of Information Engineering and Automation Kunming University of Science and Technology Kunming China State-Province Joint Laboratory of Digital Home Interactive Applications School of Information Science & Technology Sun Yat-sen University Guangzhou China

Context-aware computing has proven to be successful in collecting and understanding various sensor data. However, providing an intelligent service by exploiting the collected context data from heterogeneous sensors is difficult on smart home because it is a complex environment with various devices and appliances. In this paper, we propose a context-aware computing approach for heterogeneous smart home environments. The key idea in this work is to integrate large-scale home context information from multiple heterogeneous sensors. We first define a semantic decision by context-aware inference including rule, inference and pattern driven. Then, a designed architecture that manages home environment is developed between large numbers of heterogeneous information entities and enhances intelligence abilities. Using the established rules and inferences, the proposed method is applicable for intelligent home to further discover more useful representative activities and personalized services with inhabitant needs. Experimental results show the effectiveness of our proposed method. Copyright © 2015 Binary information Press.

关键词： Semantics

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ECNU at 2015 eHealth task 2: User-centred health information retrieval 16

ECNU at 2015 eHealth task 2: User-centred health information...

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16th Conference and Labs of the Evaluation Forum, CLEF 2015

作者： Song, Yang He, Yun Hu, Qinmin He, Liang Haacke, E. Mark Shanghai Key Laboratory of Multidimensional Information Processing East China Normal University Shanghai200241 China Department of Computer Science and Technology East China Normal University Shanghai200241 China MR Research Facility Department of Radiology Wayne State University DetroitMI48201 United States

This paper presents our work on the 2015 CLEF eHealth Task 2. In particular, we propose a Web-based query expansion model and a learning-to-rank algorithm to better understand and satisfy the task.

关键词： Websites

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Completion time-a ware flow scheduling in heterogenous networks 1

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15th International Conference on Algorithms and Architectures for Parallel processing, ICA3PP 2015

作者： He, Shiming Xie, Kun Zhang, Dafang Hunan Provincial Key Laboratory of Intelligent Processing of Big Data on Transportation School of Computer and Communication Engineering Hunan Province Engineering Research Center of Electric Transportation and Smart Distributed Network Changsha University of Science and Technology Changsha410114 China College of Computer Science and Electronics Engineering Hunan University Changsha410082 China Department of Electrical and Computer Engineering State University of New York at Stony Brook NY United States

ISBN: (数字)9783319271194

ISBN: (纸本)9783319271187

In China, the expressway isn’t free. When a vehicle exits, the exit toll station needs to calculate the toll according to the vehicle trajectory obtained by sending a trajectory query task to the trajectory center remotely. For the accurate of toll and keep the exit smoothly, transmitting the trajectory result reliably and in time is a key issue. There are three heterogenous networks in expressway, Fibernet, Telecommunications Network and 3G. We concurrently exploit three heterogenous networks by allocating the trajectory result into three sub-flows where each sub-flow is transmitted in one kind of networks. But existing multipath transfer solution(FMTCP) doesn’t consider the difference of completed time among all sub-flows and can’t make sure the completed time in time. Therefore, we formulate the sub-flows schedule as a integer programming problem, which is proved to be NP-hard problem, and propose a Completion time-aware Flow Scheduling scheme (CaFS) which calculates the size of sub-flows. For the reliably, it exploits generation-based network coding. For the transmission in time, CaFS allocates the size of sub-flow into suitable generation and scheduling the generations. The simulation results demonstrate that, comparing with the FMTCP, CaFS improves 31. 9% in completion time and 30% in task finished rate. © Springer International Publishing Switzerland 2015.

关键词： Network coding

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An IABC Based Route Maintaining Protocol in Mobile Wireless Sensor Networks

An IABC Based Route Maintaining Protocol in Mobile Wireless ...

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2015 IEEE 16th International Conference on Communication technology(ICCT 2015)

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

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： Wireless sensor networks Mobile sink Route maintaining Artificial bee colony algorithm Concentric ring

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A Classification and Pareto Domination based Multiobjective Evolutionary Algorithm

A Classification and Pareto Domination based Multiobjective ...

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IEEE Congress on Evolutionary Computation

作者： Jinyuan Zhang Aimin Zhou Guixu Zhang Shanghai Key Laboratory of Multidimensional Information Processing Department of Computer Science and Technology East China Normal University 500 Dongchuan Road Shanghai China

ISBN: (纸本)9781479974931

In multiobjective evolutionary algorithms, most selection operators are based on the objective values or the approximated objective values. It is arguable that the selection in evolutionary algorithms is a classification problem in nature, i.e., selection equals to classifying the selected solutions into one class and the unselected ones into another class. Following this idea, we propose a classification based preselection for multiobjective evolutionary algorithms. This approach maintains two external populations: one is a positive data set which contains a set of 'good' solutions, and the other is a negative data set contains a set of 'bad' solutions. In each generation, the two external populations are used to train a classifier firstly, then the classifier is applied to filter the newly generated candidate solutions and only the ones labeled as positive are kept as the offspring solutions. The proposed preselection is integrated into the Pareto domination based algorithm framework in this paper. A systematic empirical study on the influence of different classifiers and different reproduction operators has been done. The experimental results indicate that the classification based preselection can improve the performance of Pareto domination based multiobjective evolutionary algorithms.

关键词： Evolutionary algorithm multiobjective optimization classification preselection

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computer-aided design bitmap retrieval methods based on shape features

Computer-aided design bitmap retrieval methods based on shap...

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International Conference on Fuzzy Systems and Knowledge Discovery (FSKD)

作者： Yuan Yin Shengxiang Gao Zhengtao Yu Yunshan Zhang Key Laboratory of Intelligent Information Processing Kunming University of Science and Technology Kunming China Yunnan Administration College Computer Network Center Kunming China

ISBN: (纸本)9781467376839

This paper presents a computer-aided design (CAD) bitmap retrieval method based the on shape characteristics of CAD bitmaps. First, using the Canny edge detection algorithm to extract edge shapes of the CAD bitmaps, the edge direction histogram of CAD bitmaps are constructed according to the edge shapes. Next, using Euclidean distance and cosine value to calculate the distances between edge histograms, the similarities between CAD bitmaps are obtained according to the distances between histograms. Finally, sorting series of CAD bitmaps are obtained according to similarity values. The experimental results show that using shape features results in better effects than using color or texture features for CAD bitmap retrieval.

关键词： Design automation Image edge detection Shape Histograms Feature extraction Euclidean distance Color

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Vector Localization Algorithm Based on Signal Strength in Wireless Sensor Network

Vector Localization Algorithm Based on Signal Strength in Wi...

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International Symposium on Parallel Architectures, Algorithms and Programming (PAAP)

作者： Jun Xu Min Wu Chao Sha Tianyu Lu Ruchuan Wang Computer and Software College of Nanjing University of Posts and Telecommunications NanJing Provincial Kev Laboratory for Computer Information Processing Technology Soochow University SuZhou School of Engineering and Computation New York Institute of Technology New York NY USA

To deal with the inaccuracy and the uniform distribution of the DV-Hop algorithm, it is necessary to put forward a new optimization algorithm based on DV-Hop and RSSI for the two-dimensional planar node location called RSDV-Hop. The algorithm is based on the shortest hop distance with RSSI algorithm and gets the position between the nodes and the anchors according to the difference of signal strength. Moreover, it estimate the distance between the nodes and the anchors on the basis of the difference of signal strength. Therefore it can reduce the influence of the error of signal strength and the distance as far as possible by choosing different localization algorithm based on the different relationship of the nodes and the anchors. Experimental results show that the proposed algorithm performance well on the positioning accuracy and have better success rate than the DV-Hop and WPDV-Hop.

关键词： Attenuation Algorithm design and analysis Classification algorithms Fitting Distance measurement Software algorithms Wireless sensor networks

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Detection Level of Apple Based on BP Neural Network

Detection Level of Apple Based on BP Neural Network

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International Conference on information Sciences,Machinery,Materials and Energy（ICISMME 2015）

作者： Xiaoling LI Jimin YUAN School of Computer Science and Technology Chengdu University University Key Laboratory of Pattern Recognition and Intelligent information Processing The Department Computer Engineering Chengdu Aeronautic Vocational and Technical College

In view of the draw backs of apple grade identification in China,which still relies on photoelectric sorting and manual separation,this paper presents a processing method on the basis of the technology of computer vision and digital *** image processing technology,the researcher calculated the length of the long-short-axis,marked the location of it and calculated the 4 parameters,color,mean square,shape,size,as the key characteristics of the BP input of network to build a network and identify the level of apple through analysis of the external characteristics of *** optimum structure parameters of the BP neural network which had 9 hidden layer neurons were determined by RP training *** showed that average accuracy for fruit classification can reach 92.5% by using this model,and the executing time of microcomputer for grading of one apple is 9.3 *** method has the characteristics of high accuracy and good real-time performance.

关键词： characteristic parameter BP neural network apple detect level

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