Titlebook: Big Data in Engineering Applications; Sanjiban Sekhar Roy,Pijush Samui,Stavros Ntalampir Book 2018 Springer Nature Singapore Pte Ltd. 2018

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2197-6503 achine learning techniques in Big Data environment.Treats bo.This book presents the current trends, technologies, and challenges in Big Data in the diversified field of engineering and sciences. It covers the applications of Big Data ranging from conventional fields of mechanical engineering, civil

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1D Computational Spherical Geometryer the requirement. This type of design provide a more powerful and scalable approach for the data handling. This chapter explains about the how efficient HBase architecture and its command, operations are different from traditional systems.

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Coordinate-Free Geometric Computingh data in the health area, all of them as a basis to carry out data analysis, to support decision-making and to serve as a basis for the creation of Institutional health programs. It concludes with evidence of the significant contribution that a big data model can give to the health sector in Mexico.

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減弱不好

Applying Big Data Concepts to Improve Flat Steel Production Processes,t is operationally applicable. In the first application, we realized an instant interactive data visualisation enabling the in-coil aggregation of millions of quality and process measures within seconds. In the second application, we used the simple and fast HR data access to realize a refined cause-and-effect analysis.

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