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Clearly, a small amount of experimental data, about the stall angles and the relative lift coefficients, were needed to appropriately calculate the error in the μGA.
The non-probabilistic set-theoretic models, compared with the probabilistic approach, only require a small amount of experimental samples to process the study of uncertainties.
Results show that the proposed model can get the CAAHXs' characteristics in full working conditions by using only a small amount of experimental data, which can greatly improve the efficiency of the system design and optimization.
Since experiments are very time consuming, a model which allows for solubility predictions in pure solvents and solvent mixtures based only on a small amount of experimental data is required.
This study presents the very fast (300 iteration steps) and very accurate (relative error of 0.88%) retention model, obtained by using a small amount of experimental data (16 experimental data points in training set).
It is an artificial intelligence having a multi-valued logic structure and the implementation is easier than other models due to its ability to perform with a small amount of experimental data in non-linear, trial error, ill-defined and complex textile domain.
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Thus, it is easy to fast build a genetic map with a good coverage of the pine genome with only a relatively small amount of experimental effort.
By using a relatively small amount of experimental data (25 experimental data points in the training set), a very accurate prediction of the retention (percentage normalized differences between the predicted and the experimental data less than 0.6%) was obtained.
Due to the difficulty in accurately assaying protein DNA interactions on a large scale, we have only a small amount of high-quality experimental data regarding the location of these binding sites.
However, since only a small amount of data with limited experimental designs has so far been reported, more data obtained from a variety of experimental settings needs to be accumulated.
Though suggestive, the small amount of experimental evidence evaluating the impact of TPs on clinical outcomes does not clearly demonstrate the superiority of the intervention compared to standard controls.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com