T2 maps were aligned to the reference brain's T1 data by finding the linear spatial transformation that maximized the normalized mutual information between the two data sets.
With the pairwise similarities between SPNs, the graph is bipartitioned recursively by finding the splitting point that minimizes the corresponding normalized cut.
Data that showed significant seasonality were normalized as anomalies (Supplemental Figures 1 and 2)—for example, rainfall anomalies were calculated by finding the mean rainfall and monthly anomalies represented standard deviations from this mean.
Start by finding the present moment.
Start out by finding the nearest tree.
The described approach includes an exhaustive search procedure to find the group cluster parameters that resulted in an optimal clustering of the group data, by finding a clustering solution with a minimal normalized cut cost [20].
The hierarchical clustering uses the normalized BoWR of the On cycles for finding the various operational patterns of the chiller.
All output variables were first normalized before proceeding to the next step of finding the optimal number of clusters (k).
The percent relative expression was calculated by dividing each normalized value by the normalized value of wild type, which was set at 100%.
