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The performance of these kernel reconstruction methods is then assessed in light of previous temperature interpolation methods by testing them upon isotope 238U.
In order to show the feasibility of the proposed method, firstly, we will compare our approach with OTSU and K-means methods by testing and applying them on synthetic images.
We validated the proposed method on a gathered ground truth set and also demonstrated the superior biological significance of our method to three previous methods by testing the results on functional enrichment, the prevalence of protein-protein interaction and target gene co-expression.
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We validated our method by testing agarose samples with indentation moduli ranging over three orders of magnitude via AFM and compared these results with bulk compression tests.
We propose a nonlinear elastic impedance inversion method based on a fast Markov chain Monte Carlo (MCMC) method, and validate the feasibility and robustness of the method by testing the noise immunity of well data.
We then interrogate the method by testing its ability to track interfaces through large, controlled topology changes, whereby an initially simple interface configuration is subjected to vortical flows.
In addition, a practical experimental method by testing the viscosity of deposit-in-oil slurry ahead of the pig was specially designed to measure the volume of deposit during pigging in actual field.
We begin the investigation of the accuracy of our method by testing on a simulation case.
We chose to next validate use of our method by testing its ability to identify the key biomarkers used to define breast cancer subtypes.
The sensitivity of detection of Th or U3 RNA by the qPCR method was compared with that of the standard urea-PAGE-silver staining method by testing the same amount of serially diluted Th RNA or U3 RNA (not shown).
At last, these methods are verified by testing.
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