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In order for model-driven engineering to succeed, automated code generation from models through model transformations has to guarantee that extra-functional properties specified at design level are preserved at code level.
Furthermore, in order for model-fitting and model-selection analysis of palaeoecological data to yield sufficient information to be useful for predictive modelling, this approach needs to be used to analyze a greater variety of transitions in dominant plant functional types.
In order for models in PathText to be freely accessed by a wider community, we need to include a proper authentication method for accessing full papers.
However, in order for modelling to gain strength as a tool for health policy, it is critical that key model factors are made transparent so that users of models have a clear understanding of the model and its limitations.
Candidate models D and G further show clear deviations at larger SH degrees such as for SH degree n=5 and order m=0 for model D and n=3 and order m=0 for model G.
Such models often have unvalidated parameters that must be introduced by the modeler in order for the model to be fully functional.
In order for a model to be useful, trialists need to take into account local factors which influence a model's parameters.
In order for their model not to implode they will need to deliver value to their supplier customers in China.
This is required in order for the model estimation results to be interpretable.
Some assumptions must be made in order for this model to be valid.
In order for this model to be accurate, the clutter reflectivities in the ROI must be small enough.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com