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However LP-MVDR and spectral flatness methods still perform reasonably well.

Although the use of parallel MRI is increasingly common, most of the correction methods still perform Rician noise removal, yielding an erroneous result due to an incorrect noise model.

These methods still perform poorly as they attempt to interpret free text extracted from scientific literature, where the same concept may be described in different ways, whereas in GO each concept is unequivocally coded.

However, as evident in the ROC curve in Figure 6, when all genes are considered, the statistical adjustment methods still perform better than existing methods.

For model 2, IG, LRIT and FIM have very good performance (power = 1); MECPM also performs well (power = 0.96); while the other methods still perform poorly.

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However, the new method still performs closely to MUSIC with M 1=4.

Even when hologram is degraded by destructive interference, our method still performs well.

As indicated in Table3, the radial symmetry method still performs better in all noise factor combinations than the correlation method.

On the WTSN, the PageRank-based method still performs a little better than the degree centrality-based method.

For the third scenario, our method still performs very well for both normal data and skewed data.

The populations do not have to be ideal; the method still performs well with highly skewed sex ratios and overdispersed variance in reproductive success (Waples 2006).

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