Sentence examples for data a recognition from inspiring English sources

This paper is a contribution to the research needed towards a possible improvement of design recommendations, based on the following rational data: (a) Recognition of all failure modes, and (b) Specific contribution of force transfer mechanisms, such as tensile strength and compression strength of masonry, masonry to masonry friction, pullout force of steel bars and dowel action.

Collecting racial data is a recognition that although race is not a valid biological concept, it remains a potent cultural and political one.

Our results are partially consistent with those of White et al. (2010b), who applied the drift diffusion model to data from a recognition memory task and found that participants with high trait anxiety responded more carefully after making an error (i.e., increased boundary separation a following an error).

The proposed virtual human-based video conference framework consists of a definition stage that predefines the data for video conferencing, a recognition stage that extracts pose data from the images, and a reconstruction stage that reconstructs the virtual conference (Figure 1).

From these data, a unified target recognition mechanism can be concluded for the RNPs Cascade and Cas9 from types I and II CRISPR Cas systems.

Vehicle characteristic data were processed by a recognition algorithm to supply vehicular classification.

This is significant data, because recognition of faces is an important part of interpersonal interaction and successful functioning within a social group.

We encourage scientists to acknowledge the effort of those scientists and data infrastructures that support high-quality data (Table 2), but we are aware that a full system recognition of data work recognition is still to be developed.

With labeled data and recognition models designed for particular classes, an accuracy of 89% was achieved in classifying the motion of participants left out of the modeling process.

In cases where no city plans or field survey data are available, a viable option is to use remotely-sensed data for recognition of urban features.

By applying this to natural gas pipelines, a large amount of location data was collected for data feature recognition and model analysis.