The need for careful interpretation of initial failure predictions is emphasized, as is the need to allow for multiple sources of nonlinearity, (including progressive damage) where accuracy is sought for certain classes of large deformation and final failure strength predictions.
The need for careful interpretation of initial failure predictions is emphasised, as is the need to allow for multiple sources of non-linearity (including progressive damage) where accuracy is sought for certain classes of large deformation and final failure strength predictions.
The examples shown here illustrate that there can be a substantial decreases in accuracy of mapping for certain types of variants, such as small indels, or higher numbers of mismatches, which may be biologically important.
We would like to hypothesise that with modern technology it is possible to make such predictions in real-time with sufficiently high reliability and accuracy (at least for certain activities such as automated laboratory analyses).
However, the accuracy of certain types of ball tracking ballistic shots, for example—becomes easier on shorter sequences since there is less unpredictability.
The incorporation of a digital elevation model (DEM) layer and associated class rules into the object-based classification produced slightly higher accuracies overall and for certain classes; however this was not statistically significant over the object-based using spectral information solely.
This is demonstrated later by simulations using several measures to determine the minimum sequence length required for certain accuracy.
The wide range of different chemical structures present among pesticides can compromise the accuracy of the MRM for certain analytes.
Currently, some traditional techniques cannot meet the strict requirement of the accuracy of relative orbit determination for certain space missions.
