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Spelling errors can be identified by using a lexicon of Arabic words.
The angular errors and displacement errors can be identified separately when choosing the appropriate setup position and direction of ball bar.
This ensures that there is group learning from error, and repeated errors can be identified to increase general awareness of pitfalls in interpretation.
It is shown that models that minimize the multistep prediction errors can be identified or verified by filtering the data using certain data prefilters and then applying the prediction error method to the filtered data.
However, if analysis of the formal specification is done through rigorous computer tools then potential errors can be identified at earlier stages of development which increases a confidence of correctness.
Errors can be identified, filtered or corrected by using consensus from sequences within clusters.
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This suggests that using proper QC/I methods, operator error can be identified and reduced.
At least four types of positional error can be identified: 1. Positional error in street reference data.
For example, errors in data sources are caught by the in-build test that halts the build until the error can be identified and fixed.
Apart from the errors that can be identified and quantified by EM simulation, practical devices are also plagued by the infamous problem of standing waves.
Thus, detailed error models can be identified with the new algorithm by means of the usual parameter-linear model formulation.
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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