Sentence examples for features of the cluster from inspiring English sources

In fully dynamic clustering, all features of the cluster such as the size and/or shape of the clusters and the set of BSs forming a cluster can be changed as often as every scheduling interval [16 18, 21, 23 30].

Assemblies were performed for each isolate individually and also as a combined assembly including all sequence data for a deeper coverage of the common features of the cluster SMI-049 isolates.

Peptide models of different Fe S clusters have demonstrated the impact of solvent composition in ET features of the cluster.

Key features of the Cluster, as encapsulated by this framework, included a common set of values that attracted people into the network (forming), provided a common identity for the network (norming), facilitated successful relationships and encouraged effective sharing of ideas and resources within the Cluster (performing).

Comparison of the results with those obtained using the widely employed k-means clustering method (which results in five clusters, with the loss of some information about the features of the clusters) suggests the superiority of the cross-entropy clustering method.

The temporal observations are used as features of the clustering.

Data were preprocessed using data encoding for leveling of qualitative attributes (indicated in Table 1) before the cluster formation and further imputed the missing value with centroid value of the features of the clusters.

We could not find any common features of the clustered changed-tissues jiDE genes.

Our data also show some interesting epidemiological features of the clustered isolates.

Bolstering the hypothesis that the processing performed by the FP regions is particularly critical to the attentional control of reading is the set of general observations about the features of the clusters' BOLD responses.

But, as a high percentage of the clusters in ProtoNet contain at least one of the 10 337 Pfam family annotations (50% of proteins have at least one such annotation), it would be desirable to characterize a set of clusters, in terms of their 'expected correlation' to an annotation source such as Pfam, by learning the intrinsic features of the clustering procedure.