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The detailed extraction strategy is elaborated as a set of logic rules designed for our approach.
The feature extraction strategy is schematically depicted in Figure 2. As already mentioned, no segmentation/classification of the training audio-visual data is required in the proposed approach.
The goal of our feature extraction strategy is to reduce the adverse effects of the degradations to a minimum through extracting texture information minimally affected by the noise factors.
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A batch extraction strategy was compared with a continuous extraction in a perforated rotating disc contactor (PRDC).
The data extraction strategy was discussed and designed by two authors (CW and CC).
They were advised to stop only when further traction would be considered harmful to the patient or when based on their experience a change in the extraction strategy was indicated.
They were advised to stop traction only when further traction would be considered as harmful to the patient or when based on their experience a change in the extraction strategy was indicated.
Finally, the in-plane and transverse extraction strategies were compared for large parts.
In addition, two extraction strategies were tested: RNA was either purified on columns or simply prepared from crude lysates in the presence of a chaotropic buffer.
The comparative study of the unbuffered and buffered QuEChERS extraction strategies was explored.
Different extraction strategies were also evaluated to see if they could enhance the accuracy of established methods when a more heterogeneous feedstock such as bark or hog fuel was used as the biomass feedstock.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com