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We also demonstrate through smooth test problems that the proposed third order MPP/PP WENO schemes coupled with a third order Runge Kutta (RK) method attain the desired order of accuracy.
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As a result the proposed method attained a maximum recognition accuracy of 98.89%.
The outcome of the proposed method attains 99.17% accuracy for Berlin database and 97.74% for Telugu database.
The simulation results show that the proposed method attains 100% success rates for all of the numerical benchmarks with an exploitative mutation strategy.
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 method attains a better trade-off between privacy and utility.
The overall results showed that their proposed method attained a substantially higher degree of efficacy.
As a results, the object-driven method attained better results in evaluation on MOS scores than on precision-recall scores.
Their method attains the improvement of around 28% relative to the Soubra's (2000) solution for the case of a vertical wall and for ϕ = δ = i = 45°.
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.
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CEO of Professional Science Editing for Scientists @ prosciediting.com