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Building a new anthropometric database is a difficult and costly job that requires considerable manpower and time.
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Large scale detection and correction of spelling mistakes in public databases is a difficult task, and so there is a reliance on the submitter to correct these.
This is why ad hoc discovery of complex periodic patterns in a database workload is a difficult and time-consuming task.
Discovering the complex periodic patterns in the database audit trails is a difficult and time-consuming task.
Not only that keeping these databases up-to-date is a difficult task, but retrosynthetic methods are also, due to their high computational demands, not suitable for large-scale predictions.
Sometimes, the storage and maintenance of the historical databases could be a difficult task.
This latest database is more difficult to process, since the background can be different and the faces present various positions, expressions and aspects.
In this sense, the Caltech-256 database has been considered to be a difficult challenge to object recognition systems.
The industry could perhaps argue that the international IMEI Database is difficult to use, which seems an untenable argument from such a technically sophisticated industry, particularly due to its existing use elsewhere.
Evaluation of a candidate gene database is difficult.
The new federal rule seeks to integrate the state and federal reporting efforts, although environmental and citizen groups say the state database is difficult to use.
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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