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    15 November 2018, Volume 4 Issue 6
    FOCUS
    Big data driven 5G network and service optimization
    Hequan WU
    2018, 4(6):  1-8.  doi:10.11959/j.issn.2096-0271.2018055
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    The advent of 5G era will further accelerate the development of mobile data.The source of mobile big data was introduced,and the application direction of big data analysis in 5G network optimization was analyzed.According to the new characteristics of 5G network,the potential applications of big data in 5G networks,such as large-scale antenna and distributed antenna,wireless access network resource management,heterogeneous access network,cloud network,mobile edge computing,terminal and cloud intelligence,SDN and NFV,network slicing,cross-layer joint optimization,source routing optimization,etc.,were systematically expounded.Combined with the characteristics of 5G data,the applications of 5G big data in smart city,smart medicine,smart transportation,industrial Internet were analyzed.

    TOPIC:BIG DATA TALENT CULTIVATION AND CURRICULUM DESIGN UNDER THE BACKGROUND OF EMERGING ENGINEERING EDUCATION
    Construction of big data teaching system under the background of emerging engineering education
    Yuanzhuo WANG, Jianye YU
    2018, 4(6):  11-18.  doi:10.11959/j.issn.2096-0271.2018056
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    The rapid development of big data industry has posed a big challenge to cultivate big data talents.How to effectively integrate interdisciplinary and cross-disciplinary knowledge and build a teaching system for big data education is a problem facing the current major construction of big data majors in universities.From the perspective of emerging engineering education,the cultivating requirements of big data talents,curriculum system,teaching material system and practical educating system were discussed.Then some cases of integration of industry,government and university were introduced.Finally,some key points of major construction of big data were discussed.

    Toward construction of “data science” course group and “introduction to data science” course
    Xiongpai QIN, Yueguo CHEN, Cuiping LI, Yunpeng CHAI, Jun XU, Jirong WEN, Xiaoyong DU
    2018, 4(6):  19-28.  doi:10.11959/j.issn.2096-0271.2018057
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    To adapt to data science and big data talent cultivation requirements of the new era,School of Information,Renmin University of China has reformed its course system in recent years.Three course groups as problem solving,computer system,and data science has been designed.Firstly,the behind idea of the three course groups was presented,then the focus was shifted to the introduction of the first course among the data science course group,i.e.“introduction to data science”,including objective and positioning of the course,course contents,teaching program,access method,and project design.

    Course construction experience sharing of the principles and applications of big data technology
    Ziyu LIN
    2018, 4(6):  29-37.  doi:10.11959/j.issn.2096-0271.2018058
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    The training of big data professionals is the foundation of a new round of scientific and technological contest in the world.Colleges and universities assume the responsibility of training big data talents.As a typical “new engineering” major,the major of big data is still in the exploratory stage in the construction of curriculum system.Firstly,the difficulties in the construction of big data courses were analyzed,and then the big data course system built by Xiamen University was introduced,including introductory courses,advanced courses and training courses.Also the experience and methods of the course construction of the principles and applications of big data technology were introduced,which includes course orientation,training objectives,preparatory knowledge,knowledge partitioning between big data and cloud computing courses,course content and arrangement,teaching material,experimental environment construction,matching resources construction,online service platform,offline training and communication,and so on.

    Reform and exploration for introduction course of big data professional under the background of emerging engineering education
    Zuping ZHANG
    2018, 4(6):  38-45.  doi:10.11959/j.issn.2096-0271.2018059
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    In the upsurge of declaration and construction about data science and big data technology professional,the professional training system and related curriculum syllabus have always been the characteristics of various colleges and universities.Aiming at the training objective of introduction to specialty course and the requirements of emerging engineering education,the teaching materials,course orientation and specific teaching contents of introduction to specialty were discussed.By introducing practical teaching into introduction to specialty,it reflects the training objective of professional ability system.Its aim is to form students a good sense of practice at the early stage and have a personal experience with typical technology.The knowledge level and ability requirement of big data professional will be achieved easily after introducing practical teaching into introduction to specialty.

    Discussion on training program of computer majors under the background of emerging engineering education
    Li MA, Yongmei ZHANG
    2018, 4(6):  46-53.  doi:10.11959/j.issn.2096-0271.2018060
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    The emerging engineering education conforms to the emergence of social and technological development,and presents new challenges to talent training.From the point of view of construction the training of computer majors,the construction of theoretical and practical teaching systems were discussed,and a reference for the training of information professionals under the new subject environment was provided,from the expansion of curriculum content to the practice and training link,and then to the platform of joint training of talents between universities and enterprises.

    STUDY
    Air quality estimation based on active learning and Kriging interpolation
    Huijuan CHANG, Zhiwen YU, Zhiyong YU, Qi AN, Bin GUO
    2018, 4(6):  54-64.  doi:10.11959/j.issn.2096-0271.2018061
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    For the air quality monitoring station,it can only be deployed in a few locations and cannot obtain the air quality information of each location in the city.An air quality estimation algorithm based on active learning and Kriging interpolation was proposed.Firstly,Kriging interpolation was used as the basic air quality estimation algorithm.Secondly,combined with the idea of active learning,the position-first sampling with the highest confidence of the model was searched.Finally,an interpolation model based on active learning was established to select the least position-to-air quality.Sampling was performed to maximize the accuracy of air quality at other locations.The results show that the proposed algorithm can effectively improve the accuracy of air quality estimation,reduce the number of sampling stations and reduce the deployment cost.

    FORUM
    Defining data assets based on the attributes of data
    Yangyong ZHU, Yazhen YE
    2018, 4(6):  65-76.  doi:10.11959/j.issn.2096-0271.2018062
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    In the background of big data now,it has been widely recognized that data is the key factor of digital economy.Therefore,it is necessary to understand the meaning behind of the definitions of information assets,digital assets and data assets.A survey of information assets,digital assets,and data assets was given.The physical attributes,existence attributes and information attributes of data and data assets were discussed.Based on these attributes,information assets,digital assets and data assets were merged into data assets.Data assets were defined as valuable,measurable and accessible data resources in cyberspace owned by an accounting subject.According to the definition and attributes of data assets,data assets have the characteristics of both tangible assets and intangible assets,current assets and long-term assets.Therefore,data assets should be considered as a new category of assets.

    COLUMN:NATIONAL ENGINEERING LABORATORY FOR BIG DATA
    Innovation platform of integrated transportation big data application technology
    Xiaobo LIU, Yangsheng JIANG, Youhua TANG
    2018, 4(6):  78-84.  doi:10.11959/j.issn.2096-0271.2018063
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    The integrated transportation systems in China are posing key issues such as insufficient service capability for trans-industrial and trans-regional transportation management.To deal with these issues,the construction goal of an innovative“Internet + Environment” platform that uses big data and artificial intelligent technologies to improve the system performance was proposed.The overall technological framework,research and development system,and the construction progress of the platform were introduced.

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