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Unlike existing objective metrics, the proposed no-reference metric is able to predict the relative amount of noise perceived in images with different content, without a reference.
The results show that the proposed metric is able to calculate the confidence level of solutions effectively during the optimisation process.
We show that the proposed metric is able to adapt to changes in interfering traffic better than existing link metrics such as ETT, WCETT and MIC.
As can be noticed, the proposed metric is able to predict the subjective judgment.
The AccLQ metric is able to find the paths formed by the links with PER =1×10−7.
In this case, the proposed metric is able to cope with the masking effect of textures and with the perceived impact of silhouette definition and text readability.
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Although the metric was able to successfully classify roughly two-thirds of both CFS and healthy samples correctly, the level of misclassification was high.
These findings strongly indicate that our metric was able to suggest excellent NSHL candidates to be screened in patients and controls for causative mutations.
Tests on the simulation datasets revealed that only the informativeness metric was able to correctly uncover the true clustering structure of the data in every situation.
By screening for individual amino acid mutations in HIV protease that displayed positive selection, this metric was able to correctly predict 19 out of 23 known drug resistance mutation sites in HIV protease [ 10].
It is pointed out that a qualified reliability metric that is able to consider the effect of epistemic uncertainty needs to (1) compensate the conservatism in the estimations of the component-level reliability metrics caused by epistemic uncertainty, and (2) satisfy the duality axiom, otherwise it might lead to paradoxical and confusing results in engineering applications.
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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