Sentence examples for modeling these variations from inspiring English sources

However, observations from two 10-day intervals for modeling these variations are rare.

This contribution proposes a methodology to model these variations from empirical models.

As suggested by our model calculations, these variations are likely correlated with the in situ CH4 concentrations in the S. crosnieri colonies.

BRDFs naturally vary with position on a surface, and it is important to model this variation.

So-called indicators (i.e. representative model data) are selected to study model sensitivity to these variations.

Commonly automatic emotion recognition systems capture spectral information with frame-based information and temporal information by either computing a range of functionals over all the frame-level features in an utterance or by using a suitable back-end to model temporal variations of these frame-level features.

A landscape evolution model shows that these variations produce internal structure in scalloped depressions, commonly in the form of arcuate ridges, which emerge as depressions resume growth after pausing or slowing.

Novel data are provided for droplets in a Wenzel state, a Cassie Baxter state, and combined state on micro-grooved surfaces, and the ability of the empirical model to handle these variations is explored.

More sophisticated models to explain these variations are needed.

Exposure to stressful life events varies by SEP and race or ethnicity (Bosma et al. 1997; Marmot et al. 1997; Schulz et al. 2001; Williams et al. 1997), and the HEP conceptual model suggests that these variations are, at least in part, shaped by aspects of the social and physical environment.

Importantly, modeling rate variation seemed to be an important component.