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Experimental results on the dataset demonstrate that the proposed framework can achieve superior detection performance to the state-of-the-art approaches.
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An initial look at the dataset demonstrates the localisation of the individual types of equipment in the particular self-governing regions in Fig.1.
To reduce the confounding effect of background signal variation on the analysis, only the half of the dataset demonstrating the most variation across samples was used to perform unsupervised hierarchical cluster analysis using Cluster software [ 34].
Also, since total RNA samples containing a wide range of transcript abundance levels were used in this experiment, the dataset demonstrates that the accuracy of the assay is maintained over all mRNA expression levels.
Our empirical results on the datasets demonstrate that our measure stands out as a useful measure to define the attractors comparing to the other influence measures.
The remarkably fair accuracies of the three classifiers for both the datasets demonstrate its efficiency and justify its use for practical application.
We believed the outperformance of our CRCNN approach on all the datasets demonstrated its effectiveness for practical applications.
The obtained distance distribution histograms (DDHs) on these two datasets are shown in Figures 1 and 2. The enormous difference in the performance of the datasets demonstrates that no universally applicable Gabor filters exist for all the datasets.
Comparisons with other approaches and the related works on the same dataset demonstrate the superiority of the proposed method.
The results carried out on the CHEN11 dataset demonstrate that the improvement of PRANK is basically independent on the utilized threshold (see Figure 3).
Previous studies on the ELEA dataset demonstrate that incorporating knowledge from other domains were beneficial for predicting the extraversion trait [39].
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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