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(a) 4PAM and (b) QPSK. Figure 2 shows the estimation performance under different sample sizes.
A mathematic example is first adopted for illustrating how the proposed approach works under different sample sizes and sample noises.
The properties of these two designs are evaluated based on treatment imbalance and allocation predictability under different sample sizes and unequal allocation ratios.
This equation is useful in forensic cases in which original concentration of ethanol has to be estimated under different sample storage conditions.
Perusal of the data from Table 3 indicates that there is no significant change in power losses under different sample weight and different radiation conditions.
The mean and the true values of the C p, C pk and S pk indices for different cases under different sample sizes are shown in Tables 1, 2 and 3, respectively.
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This dual nature of motifs – they are local objects but their significance is assessed against a globally randomized network ensemble – explains the qualitative differences in their behaviour under different sampling regimes.
Results show that the proposed formula performs well under different sampling frequencies and wind tunnel data.
We also examine signal identification performance under different sampling rates and noise levels.
Figure 9 shows performance results for different sampling methods under different sampling conditions, on the four selected datasets, with (L=100).
Figure 15 shows the comparison between the localization failures of OC and CC under different sampling rates.
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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