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Subset designs are studied for their robustness to missing observations in different experimental regions.
Critical process parameters were screened using the one-factor-at-a-time (OFAT) approach to select optimum experimental regions.
These responses have been represented and studied in all experimental regions of activation time and activation temperature, the most influential factors in activated carbon preparation.
The applied function highlighted the influence of investigated factors on entire mixture and enabled identification of experimental regions where the chromatographic behavior was satisfactory.
The proposed algorithm is capable of constructing optimal U-type designs under various flexible experimental regions in two or more dimensions.
This limits the operational flexibility, in particular in the case of changes of optics and orbit configuration in the experimental regions.
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The experimental region was explored using a Box Behnken design for three factors, extended to experimentally include all eight possible combinations of presence/absence of the factors studied.
The experimental region is a hypercube or a hypersphere.
An equation was proposed to model the mean roughness in the studied experimental region.
For four years in the experimental region, the researchers asked clinicians to assess their patients' risk of falls and to consider medication reduction and other prevention measures like strength training, vision adjustment and blood pressure treatment.
In some experimental region, well-defined dots cannot be produced due to unstable plasmas.
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