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The first, "static" strategy involves modifying a surface with an amphiphilic comb polymer that presents short oligoethylene glycol side-chains.
According to the optimal static strategy designed in this research, the effect of the bypass valve on SOFC system performance has been analyzed.
The main idea of the proposed method is a combination of an off-line static strategy using time series prediction and an on-line dynamic adjustment using reinforcement learning.
It accepts considerably more users than both variants of the static strategy.
The second variant of the static strategy randomly distributes the 256 processes among the RAs.
When link gains are time varying, our result reveals that a static strategy can only be suboptimal.
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We theoretically prove that the MD policy behaves better than static strategies.
However, the static strategies become less and less adequate for today's highly competitive industrial society because of their low efficiency to detect slight process changes promptly.
With these features, it is difficult to store and process data streams with simple and static strategies.
The results show that the proposed strategy ensures remarkable amount of reduction in energy usage when compared to the static strategies.
As observed above, the two static strategies are not capable of significantly affecting the fraction of contained followers, with the exception of Strategy 1 for specific values of the parameters in the extremist society.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com