Exact(36)
Next, the data regarding nicotine consumption prior to surgery were recorded.
Next, the data based on the gestalt-evaluation time series is classified by LDA learning for risk evaluation.
Next, the data is further partitioned into clusters, that is, periods where the observed frequency of separating events is high and periods when it is low.
Next, the data was categorised into three clusters representing the three MLP levels of landscape (macro level), regime (meso level) and niche (micro level).
Next, the data was multiplied by the multi-exponential function that best fitted the plasma-to-whole blood ratios, again derived from the manual samples, to generate a plasma TAC.
This choice is not without cost, as it does not guarantee that from one scan to the next the data at a particular frequency is always from the same BTS.
Similar(24)
In the next section the data and the empirical strategy are illustrated.
After the static classification, we present in the next section the data collecting and prediction mechanism.
The next decade the data policies set could determine the basis of digital rights for the foreseeable future.
In the next section, the data needed for the calculations is presented, with an application to the port of Antwerp.
In the next step, the data analyst selects a time series training set and starts the training algorithm.
Write better and faster with AI suggestions while staying true to your unique style.
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