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In the second MapReduce job, every map gets a data block of the Boundary set and it computed for each sample in its partition the k nearest neighbors.
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Additionally, it computes for each local structure its free energy as well as the starting position in the sequence.
Then it computes, for each extracted frequent motif, its support and weighted support (π w ) in the shuffled set.
A mapping of the state space is then designed offline: it computes for each state of the state space the maximum allowable sampling interval, which makes it possible to reduce the number of actuations during the real-time control of the system.
As expected, the 1st order sample cross-correlation, (r_{12}(1)), presents several sharp drops and rises when it is computed for the original returns (top panel) and it is quite different from its robust counterpart.
Furthermore, it is computed for a tracking problem by minimizing its magnitude among feasible sets of controller gains satisfying a quadratic tracking condition in the sense that tracking errors are norm-bounded.
Instead, it is computed for one's immediate needs (such as hunting a prey or escaping from danger).
It was computed for 18,730 geo-referenced topsoil samples (from the Land Use/Land Cover Area frame statistical Survey (LUCAS) dataset).
The block correlation is the correlation between the block kriging prediction of a variable and the true spatial mean which it estimates, computed for a particular sampling configuration and block size over the stochastic model which underlies the kriging prediction.
It is computed for LSOAs by weighting seven different domains: income deprivation, employment deprivation, health deprivation, education deprivation, barriers to housing and services, crime levels, and living environment deprivation.
It was computed for all voxels that proved to be significant with respect to a voxel-wise (uncorrected) error probability of p = 0.005.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com