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The multivariate analysis of variance (MANOVA) was employed to optimize the data matrix.
Current communication systems employ adaptive modulation and coding schemes to optimize the data throughput.
It has built a cloud based service designed to helps companies optimize the data being sent to their mobile apps.
Therefore an interface tool to optimize the data preparation has been developed.
The PyGrav code we developed to optimize the data processing and to reduce the data uncertainties is also presented.
Unlike ID, FSD, and some other detection methods, IC aims to optimize the data before the DFT operation.
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As a result, although such considerations can effectively simplify the algorithm design, it is not often the optimal solutions for improving the network performances e.g., maximizing the network lifetimes or optimizing the data rate on each link.
We outline and discuss the diverse available options in optimizing the data representations used.
It mainly focuses on improving migration performance through optimizing the data deduplication technique.
In other words, before the fuzzy-based rules are implemented, it makes some preprocesses for optimizing the data.
The relay node is a service provider who should take responsibilities of configuring and optimizing the data transferring procedure.
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