Sentence examples for models should use from inspiring English sources

First, the markets for this stuff, mainly newspaper and now news sites, have to return to the old ways of good reporting, second, criminal penalties should remain tough, as they are, for convicted hackers and third, the phone industry that keeps inundating us with new more advanced and expensive models, should use its technology to develop hack-proof phones.

As a precautionary principle, odour emission rates utilised in atmospheric dispersion models should use the maximum values for broilers and turkeys (1.22 and 10.5 ouE s−1 birespectivelyively) and the mean value for the layers depending on the manure handling system used (0.47 or 1.35 ouE s−1 bird−1).

Our approach is parsimonious in that, within the research theme of investigating the extent to which human perception is Bayesian optimal [23], [24], models should use the same generative process as the perceptual experiment.

7 Furthermore, to be of practical use, these models should use clearly defined easily obtainable data, have good predictive power, be tested in a large sample representative of the target population, and have high reliability and face validity.

More specifically, to be useful in routine clinical practice, a good predictive model should use clinical data, make prediction at a time suitable for making clinical impact, have high accuracy, and use an appropriate definition of asthma.

Finally, we suggest the revised version of MSIS series of model should use the Fourier representation to express the intra-annual variations.

A main result of control oriented identification is that, to minimize the closed-loop error that will ultimately result from a model-based controller, the identification of the model should use closed-loop data produced with the very same controller.

Fifthly, the costing model should use the costs and production as registered in a given period.

Following the parsimonious rule, the best prediction model should use the smallest possible flanking region and the fewest possible SNPs to generate the most accurate predictions.

Instead of the South African model, we should use a two-pronged approach.

They are grounded in real things, and they don't obsess over which regression model they should use".