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Using the discriminant feature selection method, this cluster was selected as the discriminant pattern in signal y2: Dy 2. The same method identified the discriminant pattern in y1signal: Dy 1.
The total number of households per cluster was selected using the systematic random-sampling method, followed by the selection of only one eligible respondent per household using the Kish Grid technique (9), which allows selection of one person to interview from all eligible household residents.
Every fifth tree in the cluster was selected as a sample tree and measured for height using Suunto hypsometer.
The fragment that was the closest to the center of its cluster was selected as the representative for the group.
The middle cluster was selected as the discriminant features, and the remaining feature points were identified as the commonality features between the two signals.
Subsequently, each cluster was selected as a validation set and molecular fragments from the remaining clusters were used by eSynth to build new molecules.
The centroid of each cluster was selected as the representative conformer of that cluster to construct a smaller conformer model with 500 conformers or less.
First, each activity locus (single sphere or cluster) was selected on random, from the biopsy-unique microsphere distribution, and then pre-positioned on random in a 160 × 160 × 1 matrix, with spatial resolution 452 μm (resolution adapted to dose point kernel, as described in the next paragraph).
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RMSD is used as the distance metric and the largest cluster is selected as the final FRAGFOLD-IDP ensemble.
Since the cluster is selected randomly, its expected size is N/k.
The features outside this cluster were selected as the commonality structure between the two signals.
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