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To minimize the rates of false positive target prediction, MtiBase integrated a great quantity of data in each procedure.
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We then fit the data acquired in each fractile procedure using local data interpolation (i.e., splines, MATLAB SLM tool).
Simple copula models are sufficient to incorporate the dependence structure of the data in the procedure.
It can be seen that the affinity measurement for training data and testing data in this procedure are inconsistent thus they are heterogeneous.
Errors of alignment of the gear drive due to shaft deflections are considered as input data in the analytical procedure.
The means of also differed between the four approaches of handling imputed data in the resampling procedure.
We thus use the training data in an optimization procedure to find the correct values for w.
The estimate of optimism was sensitive to the choice of handling imputed data in the bootstrap procedure.
The literature reflects the need for efforts to incorporate production and manufacturing flexibility-related data (realistic data) in CF procedures in a simple manner.
Eq. 9 is applied pixel by pixel in the projection data in the scatter correction procedure.
Remedying these shortcomings, Eiken Foundation of Japan (2015) analyzed the data in a more robust procedure.
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