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Big Data is driving radical changes in traditional data analysis platforms.
Convolutional neural networks (CNN) have been successfully used in traditional data mining environments [59].
Thousands of applications are running in traditional data centers along mixed hardware tool.
Crisp input and output data are fundamentally indispensable in traditional data envelopment analysis (DEA).
These can be seen as volatile fields in traditional data model entities.
Quan et al. proposed a way of saving energy in traditional data centers considering all the above features [18].
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Nicholson also notes interest from medium-size companies in traditional data-rich sectors like financial services and e-commerce.
Criteria for choosing the initial chemicals for prototype development were human exposures in which common, underlying mechanisms are generally understood, and both in vitro molecular biology data and in vivo traditional data are available for the chemical.
Fig. 2 The periodical beaconing process in the traditional data dissemination strategy Fig. 3 The beaconing process in our new energy-efficient data dissemination strategy.
The intent is to use in vivo traditional data to explore further the predictive potential of both in vivo and in vitro "omic" data.
In a traditional data center, most of the cost is consumed by infrastructure for maintenance.
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