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It generates a data deficit of 4 units, each couple counting as a symbol in the source alphabet.
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The thing about IoT is that it generates a ton of data and the question becomes how do you make sense of it all.
Combining the new phase information with the original intensity data, it generates a new picture--and so on.
Through the data it generates, a product can tell companies a lot about the customer experience: about product use and performance, customer preferences, and customer satisfaction.
This is due to the manner in which Nagios performs data collection: it generates a schedule and linearly iterates through that schedule until all polling has been completed for that time period.
It generates an 'extraction', a histogram of the data binned on any one column in the table.
The research process provided the opportunity for the whole team to observe and interact with users first-hand, and it generated a lot of useful data in the form of verbatims and narratives, user stories, and ideas co-created with participants.
It is comparably easy to generate a data set of several chloroplast markers, but those results need to be complemented and compared to unlinked nuclear markers.
Down the road, it also has its eye on generating a data-based revenue stream via paid-tier trip analytics.
The internet was not set up for that purpose, yet it constantly generates a massive data stream that is just waiting to be analyzed - and even more so, to be understood regarding what it means to be "human" in the age of pervasive communication.
A source node sends data to a sink node through PBUR when it generates data for a certain sensor node. 2.
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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