Sentence examples for in which centrality from inspiring English sources

In fact, centrality has been mentioned sporadically in transportation-related journals in which centrality measures were used to locate the most accessible route in a network [19, 20], the shortest path of a network [21], and design the best shape for a crossdock [22].

Finally, we mapped the brain regions in which centrality graph-derived measures showed the greatest contribution to classification.

Figure 3 depicts the regions in which centrality measures contributed to the classification of the ADHD types in the OHSU sample.

Many papers have been written to show co-relations among various centrality measures and to date, research has been carried out to answers these questions: which centrality measure is best for obtaining the top-K influential nodes in a given network, which centrality measure is the best fit for a given type of data etc.

The brain regions in which degree centrality contributed mostly to classification of ADHD types are also depicted in Figure 3.

The regions in which betweenness centrality (binary) showed significant associations with memory in the microbleed group failed to show significant associations in the non-microbleed group.

Similar results were observed for the subgroup of patients without contusions, in which betweenness centrality (binary) in isolation had the lowest mean squared error in predicting associative memory (P < 0.01, R = 0.54).

Results were qualitatively similar for the subgroup of patients without contusions, in which eigenvector centrality (binary) was the most influential metric (regression coefficient lying > 2 SD above that of the next highest metric) in the combination with the lowest mean squared error (P < 0.01, R = 0.83).

Results were qualitatively similar for the subgroup of patients without contusions, in which eigenvector centrality (binary) was the most influential metric (regression coefficient lying 2 SD above that of the next highest metric) out of the combination with the lowest mean squared error (P = 0.02, R = 0.73).

So, we developed a hybrid presentation in which the node centrality information is superimposed on the evaluated MST.

Local connectivity of a protein is defined as the number of human PPIs in which it participates; centrality is the fraction of shortest paths in human PPI network between all protein pairs that pass through the given protein.