Sentence examples for data automating from inspiring English sources

Additionally, given the inherently large aspect of music data, automating this task becomes a necessity rather than a luxury.

Overall, an effective cloud computing strategy makes storing data, automating backups, and increasing access much easier, saving a lot of time and resources that can benefit all businesses.

This new set of tools, called CAMERA, allows rapid high-throughput analysis of liquid chromatography mass spectrometry (LC-MS) data, automating many feature-grouping and annotation tasks that until recently required manual inspection.

Microsoft approach to data mining is based on a number of principles: ensuring that data mining approaches scale with increases in data, automating pattern search, and developing understandable and interesting models.

EU research is promoting the development of a range of technologies that could engender systematic violations of its subjects fundamental rights, including militarised border controls, surveillance and profiling technologies, the widespread collection and analysis of personal data, automated targeting systems, satellite and space-based surveillance, and crisis management tools.

To compare three methods for assessing wear time from accelerometer data: automated, log-books and a combination of the two.

Nevertheless, we will demonstrate that, even for such heavily curated data, automated techniques are needed to extract unbiased and hypothesis-free trends and to check for internal consistency.

Together with these gene expression and flow data, automated imaging analysis identified chemokine-driven proinflammatory neutrophils, which might be activated by lethal viral loads.

As high-throughput biology generates increasing amounts of genomic and metabolic data, automated in silico approaches will become increasingly useful for making biologically useful predictions.

This strategy was applied during the process of checking the data, automated through a VBA program.

Strengths of this study include the following characteristics: clinical diagnosis of diabetes from chart data, automated data-derived indexes of medical comorbidity and complications, automated laboratory data, and automated collection of death data based on state records.