Sentence examples for small models that from inspiring English sources

One, Rolling Orange in Cobble Hill, Brooklyn, sells a dozen styles, from small models that can carry an apple box-worth of gear to behemoths that can move 100 to 200 pounds, according to Christine Brinkhorst, the shop manager.

Several small models that address specific areas of interest, while making assumptions on other details, are thus (or seems to be) the only currently meaningful approach to developing useful research models on the subject matter.

Daimler cannot sell more big-margin vehicles such as the E-class, AMG E or the S-Class and SUV's in Europe unless it sells more small models that will allow the company to fall in line with E.U. emission requirements.

Teaching AI how to partition data to create small models that can be added together to create larger models has proven to be remarkably challenging for machine learning researchers.

Thus it is only advisable to break the conceptual model into a set of small models that describe only a part of the phenomenon, and after that connecting their outcomes [ 5].

These false positive matchings typically arise with small models that formally appear as reductions of large models without any biological meaning, for the same reasons as in the cases discussed above within a same class.

Experimental tests were performed using small-scale models that are representative of the bottom panels, and the results are correlated with those from numerical simulations to define a proper mesh refinement to reproduce the buckling phenomenon.

The answer is that you can't, although Renault has now introduced a new small model that carries the same name; this one has made it to the UK and it's the car that our readers put through its paces this week.

It utilizes phonological features, automatic speech alignment based on acoustic models that were trained on normal speech, context-dependent speaker feature extraction, and intelligibility prediction based on a small model that can be trained on pathological speech samples.

This paper presents a methodology that uses phonological features, automatic speech alignment (based on acoustic models trained with normal speech), context-dependent speaker feature extraction, and intelligibility prediction based on a small model that can be trained on pathological speech samples.

However, these different sources are difficult to unify and to integrate into a small model that is easy to understand.