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Despite ongoing progress, the mining methods currently manufactured for exploring such data still stumble over their very characteristic features and in particular their considerable complexity and diversity.
Exploring such data can benefit substantially from interactive visualization tools that bring the problem of data mining and analysis closer to the individual researcher in the field, by allowing real-time visual data manipulation.
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Researchers explore such data to discover topics of interest, find related research groups, and estimate the impact of authors and publications [1 6].
Consequently, considerable efforts have been devoted to exploring such massive data in order to gain the maximum benefit from this treasure.
Moreover, more possibilities of HLS designs are explored such as data organization, aggressive pipeline insertion and the implementation of the algorithm in a soft processor like the Microblaze from Xilinx.
Preclinical studies exploring such combinations are now being performed, and some promising data have been presented.
It is well recognized that exploring such interactions requires large study populations with well-defined exposure data.
California has been exploring such an approach.
The relationship of palm oil consumption and health in these settings is of great interest and should be explored when such data become available.
Forthcoming SEPEA and PsyMaptic data will explore such possibilities.
Unfortunately we had no data to explore such an association.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com