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In this paper, we present knowledge engineering methods for the extraction and modeling of findings from market surveys and data analytics in the form of reusable and sharable knowledge.
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Feature extraction and modeling of local location data.
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Secondary thematic analysis of the model or models was then undertaken as a means of creating the a priori framework as the basis for the extraction and synthesis.
In this paper, PEME is conducted for the extraction of model analytes from biological fluids.
It is a general computational model for the extraction of symmetry features of Islamic Geometrical Patterns (IGP) images.
It is designed for the extraction of alternative and equivalent classification models through iterative deletion of selected features.
The predicted model obtained for the extraction yield of quercetin (Y3) was as follows: Analysis of variance for predicted models implied that the model was highly significant (F-value 21.48, P < 0.0001) with a good coefficient of determination (R = 0.99).
Well-fitting models for the extraction of CSA and PI were successfully established.
Well-fitting models for the extraction of baicalin, wogonoside, baicalein and wogonin were successfully established and verified.
The MeOH extraction method was employed for the extraction of a few pieces of fiber.
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