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In this thesis we show that by adopting this algorithm, we can provide a reliable connection to the end-user even as gateways presence or capacity varies.
Sample cases focusing the water impingement computation for aircraft icing were solved by adopting this algorithm assisted by the Lagrangian particle dynamics model, and the computational results were verified by the experiments.
However, the implications of adopting this algorithm into clinical practice are unclear.
Adopting this algorithm would mean that 50% of the SSTs on patients taking inhaled GCs need not have been performed.
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We also adopt this algorithm to solve the problem.
We adopt this algorithm to explore contextual information for pitch accent and boundary detection.
We have adopted this algorithm to generate partial alignments between the query and the target sequence.
However, the opposite prediction for the 2∶1 and 5∶0 conditions based on self-terminating search stands as evidence against the possibility that subjects adopted this algorithm.
We chose to adopt this algorithm as it allowed better comparability for our work with other studies; in addition, as we hope to perform follow-up scans on this group, it allowed consistency in our approach (to use the peelmode function of the instrument may lead to difficulties with identification of the threshold value).
Moreover, a scale factor η is designed for reducing model complexity in CA-CSMWPLS fitness function and a peculiar coding and a decoding rule are adopted in this algorithm.
The profile optimization strategy adopted in this algorithm is also novel, based on a sequential Monte Carlo Expectation Maximization approach.
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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