The proposed model corrects these deficiencies and is shown to provide reasonably accurate predictions for both concrete in CFFTs and concrete confined with an FRP wrap and for both normal strength concrete (NSC) and high strength concrete (HSC).
The CLM-APSIM model corrects a serious deficiency in CLM4.5-related to CLM4.5's underestimation of aboveground biomass (i.e. overestimation of belowground biomass) and overestimation of Harvest Index, which lead to a reasonable yield estimation with wrong mechanisms.
The underlying model corrects for base composition.
The Heckman sample selection model corrects for the possibility that HIV prevalence is different in respondents who refuse testing.
A random intercept model corrects for the problem of correlated observations in a cluster by introducing a random effect at each cluster.
The model corrects the recall of remote events more than it corrects the recall of recent events, because the predicted values of remote events would be lower.
