Sentence examples for measures of degree from inspiring English sources

Exact(13)

In a directed network, there are two separate measures of Degree centrality, namely in-degree and out-degree.

The proposed approach relies on certain quantitative measures of degree of controllability and observability based on the controllability and observability gramians.

Thus, they explore whether a predictive model of sentencing outcome can be constructed from measures of degree centrality, betweenness centrality, and closeness centrality together with graph density and centralization metrics.

With respect to two measures of degree of interaction, four families have a high degree of documented interaction: Gaviidae (loons or divers), Podicipedidae (grebes), Diomedeidae (albatrosses) and Sulidae (boobies and gannets).

These results underline an issue that seems to be relevant for the Spanish case, namely, that the measures of degree of underreporting by self-employed workers are in relation to a given level of underreporting by salary workers, which is difficult to be assumed that is null.

SNA measures of degree centrality (i.e. the activity of an actor or actor popularity), betweenness centrality (i.e. the capacity to control the flow of information in a network), closeness centrality (i.e. reachable to other nodes) and reciprocity (i.e. tendency to make reciprocal links) are considered to explore this longitudinal network.

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Similar(45)

Cross-correlation between marker traces was determined to obtain measures of degrees of coupling between body segments.

Other interpretations are "subjectivist," taking probabilities to be measures of "degrees of belief," perhaps evidenced in behavior in situations of risk by choices of available lotteries over outcomes.

ORP is a measure of degree to which a substance is capable of oxidizing or reducing another substance.

Clustering coefficient: it is a measure of degree to which hubs in a chart tend to bunch together.

Clustering coefficient is the measure of degree to which nodes in a graph tends to cluster together.

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