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This method attained high similarity indices.
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This method attains a speed of more than 20,000 comparisons per second, which makes screenings across large datasets and even entire databases easily feasible.
This method attains the best quality nanofluids; however, there are substantial limitations on the flexibility to create customised nanoparticle volumetric concentrations and basefluid type samples.
With the semiautomatic segmentation by the experienced neurologist for comparison, this automatic method attained high similarity indices.
The overall results showed that their proposed method attained a substantially higher degree of efficacy.
As a result the proposed method attained a maximum recognition accuracy of 98.89%.
As a results, the object-driven method attained better results in evaluation on MOS scores than on precision-recall scores.
The MOS results also show that the proposed method attained better scores than the other ones, as the precision-recall results do.
The proposed method attained an analytical frequency of 36 determinations per hour with a relative standard deviation of 1.47% for 10 measurements of 1.0 × 10−5 mol L−1 CO.
The KLD summarization method attained 70% precision, and the RlogF method achieved 72% precision.
The RF-based method attained 80.47% prediction accuracy with the AUC being 0.834.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com