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We then estimate the number of DNA molecules required to solve the satisfiability problem with a given error probability.
The number of retransmissions reduces significantly while the number of iterations increases to achieve a given error level [7].
The coefficients must be chosen to minimize a given error metric for each angular interval delimited by the angles and.
For a given error bound δ, P r(S t ≥δ) is higher when t is larger.
In our context, we can interpret (mathbb {P}) as the sensitivity of the steering institutions' response to a given error.
It is shown that the methods can significantly reduce the number of unknowns and computational time required to obtain a given error.
The number of floating point operations at a given error level associated with these two kinds of schemes are then compared.
There are also different methods that have been proposed to fit a two-sided design for a given error spending function.
For a given error level, the suggested approach reduces the number of instantiations of the fields-level model compared to state-of-the-art methods.
This task has been carried out by taking into account the program parameters and the material model, in order to minimize a given error function.
Furthermore, we show how to find an optimal sequence of simplification rules, such that their application yields a minimal model under a given error budget for performance estimation.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com