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11th International Conference on Intelligent Computing, ICIC 2015

作者： Mu, Nan Xu, Xin Li, Ziheng School of Computer Science and Technology Wuhan University of Science and Technology Wuhan430081 China Hubei Province Key Laboratory of Intelligent Information Processing and Real-Time Industrial System Wuhan University of Science and Technology Wuhan430081 China

ISBN: (纸本)9783319221854

Salient object detection has drawn much attention recently. The extracted salient objects can be used for tasks including recognition, segmentation and retrieval. Most existing models for saliency detection can only be applied to the high contrast and normal contrast scenes. They are not robust enough to handle objects in low contrast images. Due to low lightness, low Signal to Noise Ratio (SNR) and low appearance information, saliency detection in low contrast scenes remains a challenge. To solve this problem, this paper proposes a saliency detection model based on the feature extraction, in which optimal features have been learned in different contrast environment to improve the effectiveness of salient object detection. Compared with other existing saliency models, the proposed method has strong adaptability for different scenes, and gives superior performance in detecting the salient object especially in low contrast images. © Springer International Publishing Switzerland 2015.

关键词： Feature extraction

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Optimizing multiple ontology alignments through hybrid evolutionary algorithm based on a new elitist strategy

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ICIC Express Letters, Part B: Applications 2016年第6期7卷 1241-1248页

作者： Jiang, Li Tsai, Pei-Wei Xue, Xingsi Computer Department Fuzhou Polytechnic No. 8 Lianrong Road University Town Minhou Fuzhou350108 China College of Information Science and Engineering Fujian University of Technology No. 3 Xueyuan Road University Town Minhou Fuzhou350118 China Fujian Provincial Key Laboratory of Big Data Mining and Applications Fujian University of Technology No. 3 Xueyuan Road University Town Minhou Fuzhou350118 China

In this paper, we propose a hybrid evolutionary algorithm based on a new elitist strategy to address the problem of optimizing the multiple ontology alignments simultaneously. Comparing with the conventional approach, our method is able to deal with multiple pair of ontologies at a time, and through a new elitist strategy, avoid the bias improvement caused by f-measure. Experimental results show that our approach is effective. © 2016 ICIC International.

关键词： Ontology

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Cluster based hybrid key management scheme for ad hoc networks

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ICIC Express Letters, Part B: Applications 2016年第6期7卷 1329-1334页

作者： Zhang, Jing Xu, Li Tang, Rongmei Zhang, Shunmiao School of Information Science and Engineering Fujian University of Technology No. 3 Xueyuan Road University Town Minhou Fuzhou350118 China Fujian Provincial Key Laboratory of Big Data Mining and Applications Fujian University of Technology No. 3 Xueyuan Road University Town Minhou Fuzhou350118 China School of Mathematics and Computer Science Fujian Normal University Fuzhou University Town Minhou Fuzhou350118 China

Secure communication is part of the most important aspects for ad hoc networks. One cluster based Hybrid key Management Scheme is proposed in this paper for ad hoc networks. The clusters are constructed by the R-hop connected dominating sets based Partition Algorithm, which is only with the knowledge of local connectivity information. Furthermore, Hybrid key Management Scheme can be seen as an integration of both the asymmetric key and symmetric key cryptography. The asymmetric one is based on the elliptic curve cryptosystem, which is an asymmetric one. However, inter cluster key management is based on symmetric key encryption. Experimental results show this scheme is reliable and it is able to achieve higher success of landing ratio than other comparable algorithms. © 2016 ICIC International.

关键词： Ad hoc networks

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Fixed-point simulation technology for SAR real-time imaging system

Fixed-point simulation technology for SAR real-time imaging ...

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IET International Radar Conference 2015

作者： Zhou, Xin Xie, Yi-Zhuang Yang, Chen Du, Qing Deng, Yi Beijing Key Laboratory of Embedded Real-Time Information Processing Technology Beijing Institute of Technology Beijing100081 China Department of Electrical and Computer Engineering Virginia Polytechnic Institute State University ArlingtonVA United States

ISBN: (纸本)9781849199940

In this paper, a fast fixed-point simulation technology is proposed for a multi-channel synthetic aperture radar (SAR) imaging system. The overall computations in the SAR imaging algorithm is explicitly analysed. FFT operations account for most memory consumption in the imaging flow. Accordingly, a fixed-point FFT algorithm is adopted due to the trade-off between precision and memory occupation of the FPGA implementation. Furthermore, this paper describes an optimized word-length configuration method based on theoretical analysis of architecture of Radix-22 FFT. This methodology is verified in a SystemC development environment due to its superiority of fast and bit-accurate system-level simulation capability. Finally, the proposed SystemC based fixed-point imaging algorithm and the Matlab based floating-point imaging algorithm are both conducted to process point array target raw data. Peak side-lobe ratio (PSLR) and integrated side-lobe ratio (ISLR) is evaluated. Experimental results indicate that profiles in the two cases do not differ greatly, which validates that the proposed fixedpoint algorithm with less resources occupation has comparable accuracy and can meet system requirements.

关键词： Fast Fourier transforms

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Improved protein residue-residue contacts prediction using learning-to-rank

Improved protein residue-residue contacts prediction using l...

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IEEE International Conference on Bioinformatics and Biomedicine (BIBM)

作者： Xiaoyang Jing Qiwen Dong School of Computer Science Fudan University Shanghai People's Republic of China Shanghai Key Laboratory of Intelligent Information Processing Shanghai People's Republic of China Key Laboratory of Network Oriented Intelligent Computation Harbin Institute of Technology Shenzhen Graduate School Shenzhen Guangdong People's Republic of China Institute for Data Science and Engineering East China Normal University Shanghai People's Republic of China

ISBN: (纸本)9781509016129

Protein residue-residue contacts dictate the topology of protein structure and play an important role in structural biology, especially in de novo protein structure prediction. Accurate prediction of residue contacts could improve the performance of de novo protein structure prediction methods. In this study, a novel method based on learning-to-rank (RRCRank) has been presented to predict protein residue-residue contacts. The proposed method formulates the contacts prediction problem as a ranking problem. Firstly, the contact probabilities of residue pairs are predicted by ensemble machine-learning classifiers and correlated mutations approaches. And then, the proposed method integrates the complementary outputs of machine-learning and correlated mutations approaches and uses the learning-to-rank algorithm to rank residue pairs based on their probabilities to be contacts. Benchmarked on the CASP11 dataset, the proposed method achieves an improved performance for all three categories of contacts (short-range, medium-range and long-range contacts), which shows the proposed method based on learning-to-rank could take advantage of machine-learning and correlated mutations approaches and could provide the state-of-the-art performance.

关键词： Proteins Protein engineering Training Predictive models Feature extraction Classification algorithms Prediction algorithms

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An efficient topology-based algorithm for transient analysis of power grid 11th

An efficient topology-based algorithm for transient analysis...

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11th International Conference on Intelligent Computing, ICIC 2015

作者： Yang, Lan Wang, Jingbin Azevedo, Lorenzo Wang, Jim Jing-Yan School of Computer Science and Information Engineering Chongqing Technology and Business University Chongqing400067 China Tianjin Key Laboratory of Cognitive Computing and Application Tianjin University Tianjin300072 China National Time Service Center Chinese Academy of Sciences Xi’an710600 China Provincial Key Laboratory for Computer Information Processing Technology Soochow University Suzhou215006 China Computer Science Department University of Säo Paulo Säo Paulo SP05508-070 Brazil Thuwal23955-6900 Saudi Arabia

ISBN: (纸本)9783319221793

In the design flow of integrated circuits, chip-level verification is an important step that sanity checks the performance is as expected. Power grid verification is one of the most expensive and time-consuming steps of chip-level verification, due to its extremely large size. Efficient power grid analysis technology is highly demanded as it saves computing resources and enables faster iteration. In this paper, a topology-base power grid transient analysis algorithm is proposed. Nodal analysis is adopted to analyze the topology which is mathematically equivalent to iteratively solving a positive semi-definite linear equation. The convergence of the method is proved. © Springer International Publishing Switzerland 2015.

关键词： Topology

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A novel naive bayes classifier model based on differential evolution 11th

A novel naive bayes classifier model based on differential e...

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11th International Conference on Intelligent Computing, ICIC 2015

作者： Li, Jun Fang, Guokang Li, Bo Wang, Chong College of Computer Science and Technology Wuhan University of Science and Technology WUST Wuhan430065 China Hubei Province Key Laboratory of Intelligent Information Processing and Real-time Industrial System WUST Wuhan430065 China State Key Laboratory of Software Engineering Wuhan University Wuhan430072 China

ISBN: (纸本)9783319221793

Naive Bayes (NB) classifier is a simple and efficient classifier, but the independent assumption of its attribute limits the application of the actual data. This paper presents an approach called Differential Evolution-Naive Bayes (DE-NB) which takes advantage of combining differential evolution with naive Bayes for attribute selection to improve naive Bayes classifier. This method applies DE firstly to search out an optimal subset of attributes reduction in the original attribute space, and then constructs a naive Bayes classifier on the gotten subset of the attributes reduction. Nineteen experimental results on UCI datasets distinctly show that compared with Cfs-BestFirst algorithm, NB algorithm, Support Vector Machine (SVM) algorithm, Decision Tree (C4.5) algorithm, K-neighbor (KNN) algorithm, the proposed algorithm has higher classification accuracy. © Springer International Publishing Switzerland 2015.

关键词： Feature Selection

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A Novel Quantum-behaved Particle Swarm Optimization Algorithm

A Novel Quantum-behaved Particle Swarm Optimization Algorith...

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The 14th International Symposium on Distributed Computing and Applications to Business,Engineering and Science(DCABES 2015)(第十四届分布式计算及其应用国际学术研讨会)

作者： Jing Zhao Hong Liu School of Information Qilu University of Technology Shandong Provincial Key Laboratory for Distribut Shandong Provincial Key Laboratory for Distributed Computer Software Novel Technology College of Inf

ISBN: (纸本)9781467365949

A novel Quantum-behaved Particle Swarm Optimization algorithm with probability(P-QPSO)is introduced to improve the global convergence property of *** the proposed algorithm,all the particles keep the original evolution with large probability,and do not update the position of particles with small probability,and re-initialize the position of particles with small *** benchmark functions are used to test the performance of *** results of experiment show that the proposed technique can increase diversity of population and converge more rapidly than other evolutionary computation methods.

关键词： particle swarm optimization algorithm quantum-behaved probability benchmark function

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A community evolution model based on visibility graph 34

A community evolution model based on visibility graph

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34th Chinese Control Conference, CCC 2015

作者： Hong, Wang Yan-Shen, Sun School of Information Science and Engineering Shandong Normal University Jinan China Shandong Provincial Key Laboratory for Distributed Computer Software Novel Technology Jinan China Department of Earth Sciences Zhejiang University Hangzhou China

ISBN: (纸本)9789881563897

One of the most important work to analyze networks is community detection. We present a dynamic community discovery method based on Visibility Graph. Firstly, we put forward related definitions of Visibility Graph for multi-dimensional time series. Then, we present algorithms to describe how to use Visibility Graph in finding communities in complex networks. Finally, we present algorithms to find dynamic multi-relational communities. We apply our method in some real data sets. Experimental results show that our methods do better for finding dynamic communities in complex networks. © 2015 Technical Committee on Control Theory, Chinese Association of Automation.

关键词： community discovery community evolution complex network visibility graph

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On lifetime enhancement of dynamic wireless sensor networks with energy-harvesting sensors

On lifetime enhancement of dynamic wireless sensor networks ...

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IEEE International Conference on Communications in China (ICCC)

作者： Chun-Cheng Lin Der-Jiunn Deng Lei Shu Kun Wang Shang-Bin Wang I-Hsin Tsai Department of Industrial Engineering and Management National Chiao Tung University Hsinchu Taiwan Department of Computer Science and Information Engineering National Changhua University of Education Changhua Taiwan Guangdong Provincial Key Laboratory of Petrochemical Equipment Fault Diagnosis Guangdong University of Petrochemical Technology Maoming China School of Internet of Things Nanjing University of Posts and Telecommunications Nanjing China

This work investigates the problem of extending the lifetime of dynamic WSNs with energy-harvesting (EH) sensors to enhancing the total WSN lifetime. This problem is modeled as finding the maximal number of covers each of which can cover all targets to be monitored. Since the concerned problem is also NP-complete, this work proposes a novel harmony search algorithm. By simulation, the proposed algorithm is shown to be promising.

关键词： Sensors Wireless sensor networks Heuristic algorithms Monitoring Sociology Statistics Electronic mail Wireless sensor networks electronic mail Sociology Heuristic algorithms Sensors energy harvesting

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