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A stepwise regression, with backward method, was run in SPSS.
To do so, each method was run ten time and three validation techniques was used to estimate the accuracy statistics consist of cross validation, independent validation and validation with total of train data.
A SEM with a maximum likelihood estimation method was run.
When such an event was detected, a ML method was run.
Next, the regression method was run 10 times, each time using a different fold as the validation set and the other 9 folds as the training set.
The number of FFs in all these methods was 300,000, and each method was run 25 times on each test function.
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The method was running isocratic for 20 min with 95% A. For both procedures, the MS was set to scan from 95 to 1,500 m/z ions in both positive and negative mode.
# confidence estimation method is run.
For this purpose, tests introducing two electromagnetic methods (GPR and the capacitive technique), as well as the impact-echo method, were run on six different concrete mixes containing various porosities, with five water content values and three chloride concentrations.
The results indicate that the three parallel approaches, when the method is run using 64 processors on a SGI Origin 3800, are between 25 and 75 times faster than the sequential one.
All design method are run in a single cycle of design without any effort to improve the performance level to experience the effectiveness of the each metod in predicting seismic demand.
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