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SWPDPM and SWMEM had computational times that were the same order of magnitude as that of the IECM, although these methods provided better results than the method recommended by the IEC standards.
It was found that all the methods provided better results when using data from the newer instrument; the parameters required for a high percentage of correct detections were less sensitive, which resulted in fewer false triggers (reduced by a factor of 2 7) when using the methods alone without stormy conditions.
Furthermore, LiCl and guanidinium methods provided better yields in the MCF-7 samples compared to the column method (p < 0.01).
As shown in Table 1, all POCRE and POCRE0 methods provided better estimates of breeding values for generations 1001 and 1002 than BayesB.
Similar(56)
As discussed in the previous section, our AMA representation methods provide better quality than ED scheme.
Results are presented in Figure 8. From the figure, we can see that the HT and HC methods provide better performance than other methods.
Through experiments on standard datasets it is shown that the proposed methods provide better recall performance than most of the existing methods.
These methods provide better or comparable power performance than some of the robust tests such as MAX3.
It is apparent from this table that the context similarity-based feature selection methods provide better performance than the frequency-based methods.
However, the proposed method provided better objective and subjective performance than the other methods.
Compared to the Empirical Area Reduction method, the Area Increment method provided better prediction.
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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