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Similarly, the digital information with different structures, such as natural text, PDF, HTML and embedded systems data, is not simple enough to capture as entities and relationships [8].
However, interpretation of obtained data is not simple.
The importance of optimality criterion was previously also noted by Dowton et al. [ 6] and suggests that the extraction of phylogenetic signal from hymenopteran mitogenomic data is not simple.
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Despite the fact that the main information to obtain such model is usually available from three dimensional medical examination data, it is not simple to use these data and even more difficult to hold all the information together inside an engineering useful model.
Even with the transformation process, the resolution of data impedance is not simple.
The statistical analysis of hand data is not a simple task and there exist plenty of possibilities.
However, the construction of the expanded funds transaction table subdivided into a hundred industries for each year of the FOF data is not a simple task.
An absolute goodness-of-fit measure for multivariate data is not a simple matter, particularly when the actual data histogram is not known, and the sample sizes relatively small.
Collecting and analyzing that data is not as simple as throwing up a few sensors, and Industrious is committed to building out an infrastructure that supports data analysis in the long term.
As the discussion above suggests, analysis of EST data is not a simple task.
However, creating a roadmap of the disease from mouse data is not a simple task.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com