Sentence examples for be employed in generating from inspiring English sources

In the paper, we illustrate how the QTRIG relationships can be employed in generating qualitative spatial descriptions in two-dimensional Euclidean geometric problems, and furthermore, how the derived qualitative spatial descriptions can be used to guide a simulated-annealing-based exact quantitative value assignment.

More generally, we suggest that a combination of different statistical methods should be employed in generating alarms for infectious disease outbreaks.

Complete two-level factorial design was employed in generating the experiments from models with five- and eight-level systems.

One problem in building an overall picture of the pathophysiology of sepsis/SIRS is the variety of methods that are employed in generating the sepsis-like response in laboratory models.

Two forms of coding were employed: in-vivo coding, which generated analytical categories based on the actual words used by research participants, and open coding, were codes were generated by the researcher based on a close reading of the textual data.

Reverse genetics may be employed in the future to rapidly generate PR-8 based PR-8 basedt vireassortant

If a particular gene is found to be elevated by multiple stresses with prolonged duration of stress exposure, it can be well presumed that the gene can be employed in genetic engineering program to generate crop plants showing broad spectrum resistance, rather than resistance to a particular stress only.

It can be employed in image and video composition to generate artistic atmospheric effects over real scenes.

Because of the opportunity cost of forcing utilities to replace coal-fired power plants early; this, they say, takes up capital that otherwise would have been employed in ways that generate more economic activity.

Another fuzzy-based hierarchy method is employed in [17] to generate features characterized in terms of information quality and source credibility.

Next, the background modelling module is employed in order to generate a high-quality adaptive background model using a unique two-stage training procedure and a mechanism for recognizing changes in illumination.