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检索条件"任意字段=2014 IEEE International Conference on Progress in Informatics and Computing"

共 1844 条记录，以下是111-120 订阅

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An English Subordinate Clause Connective Correction Model Based on Genetic Algorithm and K-Nearest Neighbor Algorithm 5

An English Subordinate Clause Connective Correction Model Ba...

引用

2017 international conference on progress in informatics and computing(PIC)

作者： Guimin Huang Chuang Wu Sirui Huang Hongtao Zhu Ruyu Mo Ya Zhou Guilin University of Electronic Technology Xi'an Jiaotong-Liverpool University

ISBN: (纸本)9781538619797;9781538619780

In English writing, English learners will inevitably make a variety of grammatical mistakes, especially in English subordinate clause connective. To alleviate high error rate of connective in subordinate clauses of Chinese students' English writing, an automatic error correction model for English subordinate clause connective is studied and implemented from the perspective of machine learning genetic algorithm(GA) and k-nearest neighbor(KNN) algorithm combination model. Firstly, an automatic feature selection algorithm based on GA is adopted to reduce time consuming and space cost, and to improve the accuracy of connective error correction. Secondly, through comparing the Naive Bayes, decision tree, maximum entropy and KNN algorithm, KNN algorithm is found better while classifying the connectives. Finally, we compared the performance of several hybrid models, which combine different machine learning algorithms with GA. This proves that the combination of GA and KNN algorithm is optimal.

关键词： machine learning genetic algorithm connective correction feature selection

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Cloud computing in Electric Vehicles Charging Control and Dispatch Optimization 2

Cloud Computing in Electric Vehicles Charging Control and Di...

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2nd ieee international conference on progress in informatics and computing (PIC)

作者： Wu, Dan Liu, Bo Chen, Zhijian Xie, Wenyan Huang, Xiang Pei, Shuwei Sheng, Bin Feng, Donghan China Southern Power Grid Co Ltd Informat Ctr Guangzhou Guangdong Peoples R China Chinese Acad Sci Inst Software State Key Lab Comp Sci Beijing Peoples R China Guangdong Elect Power Design Inst Network & Informat Branch Guangzhou Guangdong Peoples R China Shanghai Jiao Tong Univ Dept Comp Sci & Engn Shanghai 200030 Peoples R China Shanghai Jiao Tong Univ Dept Elect Engn Shanghai 200030 Peoples R China

ISBN: (纸本)9781479920303

Charging of large-scale electric vehicles will have a significant impact on the grid so that their charging schedule needs to be optimized. The traditional centralized scheduling method requires high performance in information exchange and computing. Based on the analysis of the features of electric vehicle charging load and the research of cloud computing, we propose a cloud computing based schedule platform for optimal charging of electric vehicles. In addition, the function and implementation of the three basic modules of the platform ( the data collection module, the cloud computing center and the control center) are exposed. The platform performs well in optimal scheduling for electric vehicles. In addition, the platform can also make full use of the computing resource and reduce the communication congestion.

关键词： cloud computing electric vehicle optimal charging service platform

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3D Model Reconstruction based on Plantar Image's Feature Segmentation 5

3D Model Reconstruction based on Plantar Image's Feature Seg...

引用

2017 international conference on progress in informatics and computing(PIC)

作者： Maqiu Zhang Zhenning Zhang Weiqing Li School of Computer Science and Engineering Nanjing University of Science and Technology

ISBN: (纸本)9781538619797;9781538619780

The 3D reconstruction of sole based on laser scanning is costly and time-consuming, the 3D reconstruction based on structured light is susceptible to ambient light. A 3D reconstruction method of sole based on the plantar image's feature segmentation is proposed. The sole is segmented into two regions by the morphological features in the image. One is the arch part touching the glass, another is the un-touching camber part. And an experiment is designed to summarize the law between the plantar height and gray value in each region. Then we reconstruct the two regions' shapes separately on the basis of the regulation. Finally, we implement the plantar reconstruction by merging the two point cloud models. Experimental evaluation demonstrates that the system can do the classification and reconstruction effectively.

关键词： Image segmentation Arch type Feature Segmentation 3D reconstruction

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A fast seismic data processing approach based on parallel wavelet transform

A fast seismic data processing approach based on parallel wa...

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ieee international conference on progress in informatics and computing (PIC)

作者： Zhang, Xiaolai Lu, Yongquan Li, Jinsong Wang, Jintao High Performance Computing Center Communication University of China Beijing 100024 China Information Engineering School Communication University of China Beijing 100024 China

ISBN: (纸本)9781424467860

A new implementation of seismic data processing approach based on parallel wavelet transform is presented in this paper. Firstly, the feasibility and necessity of the parallel processing method for seismic data are elaborated from three primary aspects. Based on the analysis, the parallel wavelet transform is implemented by using MATLAB on a distributed cluster. Finally, both sequential and parallel implements are employed to test and compare the performance of our implementation. A series of experiments have demonstrated that parallel wavelet transform can significantly reduce the running time and improve the speedup greatly. ©2010 ieee.

关键词： Wavelet transforms

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Congestion Integrated Control in Virtualized Clouds 2

Congestion Integrated Control in Virtualized Clouds

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2nd ieee international conference on progress in informatics and computing (PIC)

作者： Zhang, Yumeng Ren, Fengyuan Cheng, Peng Miao, Mao Lin, Chuang Tsinghua Univ Dept Comp Sci & Technol Tsinghua Natl Lab Informat Sci & Technol Beijing 100084 Peoples R China

ISBN: (纸本)9781479920303

Many cloud computing platforms adopt virtualization technology to provide cloud services. To achieve high computing performance, many data parallel frameworks are adopted to run the jobs. The job is broken into pieces and farmed out to virtual machines (VMs) to process in parallel. The responses from these VMs are aggregated to produce the final result with concurrent flows. However, the concurrent flows adjust congestion window in an isolated manner, there will be large variance among the transmission time of each flow. It will have negative impact on the cloud application performance since the slowest flow determines the total completion time of concurrent flows. To facilitate resource utilization and VM management, these VMs usually reside in the same physical host which offers the native infrastructure for concurrent flows' integrated management. Therefore, we propose a Congestion Integrated Control (CIC) scheme which offloads each flow's independent congestion control module and sets up an integrated control platform to perform the congestion control for concurrent flows in a unified manner. The CIC scheme is implemented on the Xen platform. The performance evaluation indicates that the large variance among transmission time of each flow is substantially reduced and total completion time of concurrent flows is decreased correspondingly.

关键词： cloud computing virtualization congestion control xen

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A Novel Mutual Information based Ant Colony Classifier 5

A Novel Mutual Information based Ant Colony Classifier

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2017 international conference on progress in informatics and computing(PIC)

作者： Hang Yu Xiaoxiao Qian Yang Yu Jiujun Cheng Ying Yu Shangce Gao College of Computer Science and Technology Taizhou University Faculty of Engineering University of Toyama Key Laboratory of Embedded System and Service Computing Ministry of EducationTongji University

ISBN: (纸本)9781538619797;9781538619780

By constructing a list of IF-THEN rules, the traditional ant colony optimization(ACO) has been successfully applied on data classification with not only a promising accuracy but also a user comprehensibility. However, as the collected data to be classified usually contain large volumes and redundant features, it is challenging to further improve the classification accuracy and meanwhile reduce the computational time for *** paper proposes a novel hybrid mutual information based ant colony algorithm(mrAM+) for classification. First, a maximum relevance minimum redundancy feature selection method is used to select the most informative and discriminative attributes in a dataset. Then, we use the enhanced ACO classifier(i.e., AM+)to perform the classification. Experimental results show that the proposed mrAM+ outperforms other seven state-of-art related classification algorithms in terms of accuracy and the size of model.

关键词： ant colony optimization mutual information classification data mining feature selection

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Brain Storm Optimization with Adaptive Search Radius for Optimization 5

Brain Storm Optimization with Adaptive Search Radius for Opt...

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2017 international conference on progress in informatics and computing(PIC)

作者： Yang Yu Lei Wu Hang Yu Sheng Li Shi Wang Shangce Gao Faculty of Engineering University of Toyama Hefei Power Supply Co. Ltd.State Grid Corporation of China College of Computer Science and Technology Taizhou University

ISBN: (纸本)9781538619797;9781538619780

Brain storm optimization algorithm is a newly proposed algorithm which is based on the social behaviors of human beings. It gets inspiration from the procedure of brain storming to generate new individuals. The properties of brain storming highly ensure the diversity of the whole population and can efficiently eliminate premature convergence. In this paper, an adaptive search radius method has been proposed to help brain storm optimization to enhance its search ability. The proposed algorithm equipped with adaptive search strategies introduces a success and failure memory to choose the best suitable search strategy to improve the individual quality in each iteration. Three strategies can be chosen in the duration of convergence adaptively and guarantee better solutions compared with traditional brain storm optimization.

关键词： brain storm optimization adaptive search radius memory-based selection meta-heuristic algorithm

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The Realization of Identification Method for DataMatrix Code 5

The Realization of Identification Method for DataMatrix Code

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2017 international conference on progress in informatics and computing(PIC)

作者： YanGe Dai Lizhen Liu Wei Song Chao Du Xinlei Zhao Information and Engineering College Capital Normal University College of Foreign Languages Capital Normal University

ISBN: (纸本)9781538619797;9781538619780

The minimum size of the DataMatrix code is 0.0002 square inches and this size is the smallest of the current onedimensional and two-dimensional codes. So it is particularly suitable for printing on metal parts of circuit boards. However, compared with the general two-dimensional code, there are still many technical difficulties on metal surface DataMatrix code identification technology. The reflection on metal surface is not conducive to the DataMatrix binarization. The large spacing between the codes is not conducive to positioning and identification. There is a distorted or incomplete DataMatrix code on metal surface. In this paper, a DataMatrix code recognition method is proposed by digital image processing technology. Firstly, Binarization is achieved by improving the traditional Otsu algorithm. The binarized image is dilated to solve the problem of large code interval. Secondly, the DataMatrix code region is located. The Hough transform is used to detect the four vertices of the DataMatrix code. The vertex is used to correct the twisty DataMatrix code. Finally, according to the structural characteristics of the DataMatrix code, the incomplete code is completed. According to the encoding rules, the DataMatrix code is decoded. After the above series of steps, we can achieve the purpose of identifying DataMatrix code.

关键词： DataMatrix image processing binarization

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A Preference-based Multi-objective Evolutionary Strategy for Ab Initio Prediction of Proteins 5

A Preference-based Multi-objective Evolutionary Strategy for...

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2017 international conference on progress in informatics and computing(PIC)

作者： Zhenyu Song Yajiao Tang Xingqian Chen Shuangbao Song Shuangyu Song Shangce Gao Faculty of Engineering University of Toyama

ISBN: (纸本)9781538619797;9781538619780

Predicting the three-dimensional structure of a protein from its amino acid sequence is an important issue in the field of computational biology and bioinformatics. It remains as an unsolved problem and attract enormous researchers' interests. Different from most conventional methods, we model the protein structure prediction(PSP) problem as a multiobjective optimization problem. A three-objective energy function based on three physical terms is designed to evaluate a protein conformation. A multi-objective evolutionary strategy algorithm coupled with preference information is proposed in this study. The preference information is used in the survival criteria, focusing on the exploration of search process. The experimental results based on five proteins in PDB library demonstrate the effectiveness of proposed method. The analysis of Pareto fronts indicates that the preference information can make solutions diverse in genotypic space. Thus, the proposed method gives a new perspective for solving PSP problems.

关键词： Protein structure prediction multi-objective optimization multi-objective evolutionary algorithm preference information utility function

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Infrared Remote Sensing Imaging via Asymmetric Compressed Sensing 5

Infrared Remote Sensing Imaging via Asymmetric Compressed Se...

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2017 international conference on progress in informatics and computing(PIC)

作者： Zhao-yun Fan Quan-sen Sun Ji-xin Liu School of Computer Science and Engineering Nanjing University of Science and Technology Engineering Research Center of Wideband Wireless Communication Technology Ministry of Education Nanjing University of Posts and Telecommunications

ISBN: (纸本)9781538619797;9781538619780

Compressed sensing（CS） theory provides a new acquisition idea for sparse signals and sparsely-expressed signals. CS-based hardware design has been widely concerned. And related products have been tentatively tried in many fields. The design of remote sensing imaging based on CS mainly includes single pixel multiple exposure imaging and block focal plane coding multi-pixel single exposure imaging. In this paper, a CS asymmetric processing model, which is different from traditional image reconstruction, is proposed. And it is applied to CS hardware design for infrared（IR） remote sensing imaging. This model fully considers the global information of the image, which combines the multiple neighborhood values of the observed results in the CS process, and also combines the multiple measurement matrix blocks to form a new measurement matrix. At the same time, a sparse dictionary construction method suitable for asymmetric patterns is proposed, which can effectively compensate for the local differences caused by image *** experimental results show that the proposed method is superior to the conventional block focal plane coding compression reconstruction both in reconstruction time and in reconstruction quality.

关键词： Compressed Sensing Image Reconstruction Asymmetric Mode Measurement Matrix

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