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2017 3rd international conference on Humanity and Social science（ICHSS 2017)

作者： Yu HONG Shan-shan REN Zheng-mei YIN Xiao-wei MU Jilin University of Finance and Economics College of Humanities & Sciences Northeast Normal University

Using annual trade data from 1987 to 2016, this study focuses on the Chinese import trade patterns in garment, textile and footwear. We employ the indicators of net exports and revealed symmetric comparative advantage to generate H index to assess the divergence of the import policy. Our findings imply that 1) China has been comparative dis-advantageous in the imports of the low-technology garment, textile and footwear, and 2) the Chinese trade policy has been persistently restrictive towards the imports of the products. We document that the Chinese government may restrict the imports to improve the domestic employment.

关键词： China Trade policy Import restriction Textile Comparative advantage

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Research on Parallel Processing Framework of Power Big data

Research on Parallel Processing Framework of Power Big Data

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2017 3rd international conference on Computational Systems and Communications(ICCSC 2017)

作者： HU Bin LUO Li-ming YANG Pei HUANG Tai-gui ZHANG Li-ping Global Energy Interconnection Research Institute State Grid Anhui Electric Power Company Nanjing University Post & Telecommunication

With the application of the power of big data landing and deepening, which put forward higher requirements on the performance analysis, and based on multi node parallel processing technology will become one of the core support technology and the rapid development of the application of power analysis of big data. This paper briefly analyzes the application requirements of large power parallel data processing, this paper presents a parallel processing framework for the power of big data and the realization method of management services and computing services in detail the design, research and development of parallel processing platform for the power of big data, and based on the national power quality monitoring data, comparison test Hive and 1.1.0. Compared with the experimental results, the results show that, when the node size is relatively small, the power big data parallel processing platform is less obvious than Hive 1.1.0. However, with the increasing size of the nodes, the advantages of the large data parallel processing platform of power are larger than that of Hive 1.1.0.

关键词： Power big data Parallel Processing Power quality Hive

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The distribution of scientific index weight based on information entropy and correlation coefficient

The distribution of scientific index weight based on informa...

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2016 3rd international conference on Modern Economic Technology and Management(ICMETM 2016)

作者： Rui Chi Xiang Su Nianxin Wang School of Economics and Management Jiangsu University of Science and Technology

The weights of scientific research indexes affect the accuracy of *** entropy reflects the amount of index information;correlation coefficients reflect the correlation between the indexes and assessment *** this paper,it takes the normalized products of information entropy and correlation coefficients as the weights of scientific assessment *** result of empirical analysis shows the reason why "The Core Journals"(native) and foreign journals being assigned with the largest weight coefficient is because both of its entropy and correlation coefficients are *** some important index weights of the national projects and "A Journal Papers" are smaller because only a few people have the index data,and this will result in small index information ***'s last verified by the sample distribution that the product of the scientific index and the weight coefficient is conducive to grading the assessment of the teachers.

关键词： scientific assessment weight coefficient amount of index information sample distribution index system assessment result

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Targeted Poverty Alleviation in Big data Era: What Should Be Done and How Could It Be Possible

Targeted Poverty Alleviation in Big Data Era: What Should Be...

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2017 3rd international conference on Management science and Innovative Education(MSIE 2017)

作者： ZHAOPAN DING YONGZHU JIN School of Public Administration Guizhou University

Big data is a new technological revolution, following Internet, Internet of Things and Cloud computing. In Big data Era, as a kind of strategic resource, Big data's precise and effective technical concept happen to be the same with targeted poverty alleviation in development direction. On account of this, Big data enables"recognizing the real poverty", "supporting real impoverished people" and "taking practical actions on poverty alleviation" to be possible in targeted poverty ***, Big data enables us to screen effective information so as to achieve precise recognition, to mix all the information from different fields and different categories so as to achieve precise management, and to further analyze information about poverty so as to find suitable measures for poverty alleviation. Therefore,targeted poverty alleviation in Big data era should be promoted by making full use of Big data technology to establish Big data network and to provide precise information on poverty alleviation. E-commerce should be developed to promote the development of poverty alleviation industries. And evaluation system for poverty alleviation should be reformed to promote fairness and transparency of the process of poverty *** doing so, we will truly put the targeted recognition to poor villages and poor residents into effect, and promote targeted poverty alleviation and targeted management to construct the development pattern led by Big data.

关键词： Targeted Poverty Alleviation in Big data Era What Should Be Done and How Could It Be Possible

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A fast, stable dissemination protocol based on similarity of congestion level in urban vehicular networks

A fast, stable dissemination protocol based on similarity of...

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2017 3rd international conference on Computational Systems and Communications(ICCSC 2017)

作者： Haitao Xu Zhibei Qi Urban Computing and Big Data Laboratory Hangzhou Dianzi University

Aiming at the phenomenon that the current traffic congestion detection scheme has a long cycle and low efficiency of the information transmission in the city, this paper proposes a traffic congestion detection and congestion information forwarding scheme based on Vehicular Ad-hoc NETwork(VANET) technology. Based on vehicle-to-vehicle communication mode, the scheme first determine the occurrence of traffic congestion, through the congestion similarity theory combined with the communication link quality factors, select the appropriate congestion information forwarding nodes, achieve real-time rapid dissemination of information, reduce the amount of redundant information congestion purposes. Finally, the simulation results show that the proposed scheme has significant advantages in terms of information loss rate, propagation delay and forwarding rate and effectively improve the efficiency of traffic congestion information dissemination.

关键词： VANET Vehicle density Congestion similarity Link quality Forwarding node

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How Extenics Promote Innovation and Entrepreneurship in Colleges on the Background of the Mobile Internet

How Extenics Promote Innovation and Entrepreneurship in Coll...

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2017 3rd international conference on Creative Education (ICCE 2017)

作者： Xingsen Li Wei Liu Yingying Zhou Research Center on Intelligent Computing and Data Management Ningbo Institute of Technology Zhejiang University School of Foreign Languages Beijing Forestry University Ningbo Dahongying University

Entrepreneurship and innovation by college students is a systematic project requiring suitable guide. The paper presents a model of how the Chinese original discipline, Extenics, promotes both innovation and entrepreneurship in Ningbo, China, which is relatively well-developed in the environment of entrepreneurship. We designed a teaching model of multi-collaborative innovation and entrepreneurship practice under the Mobile internet environment based on the scientific methodology--Extentics. By information collection on the mobile internet and intelligent processing into basic element base, our systematic extending model was conducted to prompt the methodology mechanism of both innovation and entrepreneurship, and in turn improve the collaboration of governments, colleges and enterprises to facilitate the advancement of innovation and entrepreneurship. Applications showed that this methodological system could effectively increase the success rate of innovation and entrepreneurship by college students.

关键词： Entrepreneurship Innovation education Extenics Methodology College students

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Development of a New Platform Through Distributed Storage System for the Bioinformatics Analysis

Development of a New Platform Through Distributed Storage Sy...

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2017 3rd international conference on Artificial Intelligence and Industrial Engineering (AIIE2017)

作者： Ali Osman CIBIKDIKEN Mucahit BUYUKYILMAZ Mehmet Akif NACAR Ahmet Ercan TOPCU Yusuf TAMBAG Abdullah KARADAG Necmettin Erbakan University Department of Computer Engineering Necmettin Erbakan University ACDAL Harran University Department of Computer Engineering Yildirim Beyazit University Department of Computer Engineering

data security has become a major issue in recent years. It becomes a requirement to store the sensitive data with at least two backup systems in geographically distributed data centers in order to provide the security. In addition, there is a huge need for the computational power to analyze the big data generated through various high-throughput multiomics applications such as next-generation sequencing and mass spectrometry platforms. In this study, a geographically distributed asynchronous replication application and architecture, called LUNGBASE, based on the OpenStack Swift has been introduced. This study enables to replicate the data generated through the LUNGMARK project, a lung cancer molecular profiling study through bioinformatics-supported integrative multiomics analysis, carried out at the Molecular Oncology Laboratory of the TUBITAK-Marmara Research Center(MRC), Genetic Engineering and Biotechnology Institute(GEBI), in different geographical regions. In this paper, we proposed an architecture and application model that can perform an effective file transfer operations and smart and automated data movement on distributed environment.

关键词： Object storage data replication Cloud computing Bio informatics

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A spectral clustering method of taking the space topology relationship and the voltage data dependency of the power network into consideration

A spectral clustering method of taking the space topology re...

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2017 3rd international conference on Intelligent Energy and Power Systems(IEPS 2017)

作者： Mei Dong Tang Zhaohui Chen Jingting Modern Energy Systems and Power Electronics China Central South University School of Information Science and Engineering Central South University

The voltage is one of the important criteria for the evaluation of the electric energy quality,as well as the sign of reflecting the reactive power balance and reasonable distribution electric power system. Distributed voltage control is a kind of fast and effective controlling method. To deal with the complicated conditions of the divided boundary,this article leads into the concept of the temporal and spatial boundary constraint set,putting forward the method of spectral clustering partition of the boundary constraint set. Firstly,the way of obtaining the distributed numbers is given specific to the electric power net. Then,the voltage time series analysis is carried on the base of the space relationship. Betweenness,degree and other complex internet and intranet concept have been brought in to evaluate the importance of node,the definition of the partition degree has been made through the data visualization. Dividing the boundary node into whirlpool node and isolated node,dealing with them separately. When the voltage fluctuation takes place,the reason can be made clear,the prediction about chain fluctuation spreading tendency will be made and the regulation and control scheme will be given. Application in some province's electric power net system has saved the computing time and improved the response speed.

关键词： Spectral clustering Graph theory Spatiotemporal Association Border Set

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data fusion approach for enhanced anomaly detection 3rd

Data fusion approach for enhanced anomaly detection

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3rd international conference on Innovations in Computer science and Engineering, ICICSE 2015

作者： Ravinder Reddy, R. Ramadevi, Y. Sunitha, K.V.N. Department of Computer Science and Engineering Chaitanya Bharathi Institute of Technology Hyderabad500075 India B.V. Raju Institute of Technology for Women Bachupally Hyderabad Telangana500090 India

ISBN: (纸本)9789811004179

Anomaly detection is very sensitive for the data because, the feature vector selection is a very influential aspect in the anomaly detection rate and performance of the system. In this paper, we are trying to revise the dataset based on the rough genetic approach. This method improves the quality of the dataset based on the selection of valid input records to enhance the anomaly detection rate. We used rough sets for pre-processing the data and dimensionality reductions. Genetic algorithm is used to select proper feature vectors based on the fitness. The fusion of the soft computing techniques improves the data quality and reduces dimensionality. Empirical results prove that it improves detection rate as well as detection speed. © Springer science+Business Media Singapore 2016.

关键词： Rough set theory

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Multi-scale visual analysis of time-varying electrocorticography data via clustering of brain regions

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BMC BIOINFORMATICS 2017年第Sup6期18卷 236-236页

作者： Murugesan, Sugeerth Bouchard, Kristofer Chang, Edward Dougherty, Max Hamann, Bernd Weber, Gunther H. Lawrence Berkeley Natl Lab Computat Res Div One Cyclotron Rd Berkeley CA 94720 USA UCSF Dept Neurol Surg 505 Parnassus Ave San Francisco CA 94143 USA Univ Calif Davis Dept Comp Sci One Shields Ave Davis CA 95616 USA

Background: There exists a need for effective and easy-to-use software tools supporting the analysis of complex Electrocorticography (ECoG) data. Understanding how epileptic seizures develop or identifying diagnostic indicators for neurological diseases require the in-depth analysis of neural activity data from ECoG. Such data is multi-scale and is of high spatio-temporal resolution. Comprehensive analysis of this data should be supported by interactive visual analysis methods that allow a scientist to understand functional patterns at varying levels of granularity and comprehend its time-varying behavior. Results: We introduce a novel multi-scale visual analysis system, ECoG ClusterFlow, for the detailed exploration of ECoG data. Our system detects and visualizes dynamic high-level structures, such as communities, derived from the time-varying connectivity network. The system supports two major views: 1) an overview summarizing the evolution of clusters over time and 2) an electrode view using hierarchical glyph-based design to visualize the propagation of clusters in their spatial, anatomical context. We present case studies that were performed in collaboration with neuroscientists and neurosurgeons using simulated and recorded epileptic seizure data to demonstrate our system's effectiveness. Conclusion: ECoG ClusterFlow supports the comparison of spatio-temporal patterns for specific time intervals and allows a user to utilize various clustering algorithms. Neuroscientists can identify the site of seizure genesis and its spatial progression during various the stages of a seizure. Our system serves as a fast and powerful means for the generation of preliminary hypotheses that can be used as a basis for subsequent application of rigorous statistical methods, with the ultimate goal being the clinical treatment of epileptogenic zones.

关键词： Electrocorticography Clustering Spatio-temporal graphs Unsupervised learning Neuroinformatics Epilepsy Visual analysis Brain imaging Graph visualization Mutli-scale analysis

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