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Two groups of numerical experiments are demonstrated in this section.
These issues and challenges will be demonstrated in this section.
The experimental validation of the formulated model is demonstrated in this section.
The application of the proposed approach is demonstrated in this section using a numerical example.
The desirability model is demonstrated in this section to analyse the mechanistic coreflooding experiments published in the literature.
The approach for classifying discriminative language characterization score vectors in LID system is demonstrated in this section.
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To make things more concrete, we demonstrate in this section how the manifold lifting viewpoint can inform the design of reconstruction algorithms in the context of two generic multi-view scenarios: far-field and near-field imaging.
This is demonstrated in the section of a tomogram shown in Fig. 5.
As demonstrated earlier in this section, this variance-covariance matrix is independent of allele coding.
In the case of a rapidly varying background rate function, as demonstrated in the following section, this adaptive procedure provides estimates of background rate that are much better than those obtained using a global smoothness parameter.
As demonstrated in the next section, this correlation can be quantified and is statistically significant across these and several other languages and corpora.
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proven in this section
determined in this section
validated in this section
revealed in this section
delineated in this section
highlighted in this section
demonstrated in this model
demonstrated in this series
demonstrated in this image
demonstrated in this phase
demonstrated in this survey
demonstrated in this study
demonstrated in this program
demonstrated in this figure
demonstrated in this work
demonstrated in this plant
demonstrated in this patient
demonstrated in this chapter
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com