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Maximizing the fractal modularity is also important in the box-covering method, which can be divided into two objectives: maximization of ratio association and minimization of ratio cut.
This task can be divided into two objectives: finding and quantifying expressed genomic regions giving rise to small RNA reads, and scoring these regions as potential new miRNAs.
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The metrics are divided into three "objectives".
However, the composite network W optimized from the target network K is not necessarily optimal for the classifier, since the optimization of the composite network and of the classifier is divided into two separate objectives.
In order to provide quantitative guidelines relevant to managerial decision, the main objective of the study was further divided into two complementary outcomes: Objective ex-ante: the determination of the most efficient allocation of resources between the screening and the multicohort quadrivalent immunisation programme, given the constraints discussed above.
Generally, optimization in terms of the number of objective functions and optimization criteria is divided into two categories of single-objective optimization problems and multi-objective optimization problems.
In other words, each 'parent' group is divided into two 'child' groups, with the objective of creating increasingly homogeneous subgroups.
This overall goal was divided into five separate performance objectives and translated into change objectives based on the needs assessment, literature search, survey and interviews with HHC workers and experts in the field (see Table 2).
In this method the objectives are divided into two levels.
Lastly, the remaining objectives are divided into two conflicting groups based on their Spearman's rank correlation coefficients.
Divided into two groups, they headed for their objectives.
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