The phrase "advance data" is not commonly used in written English and may cause confusion.
It could be used in contexts related to data that is ahead of a certain point in time or data that is prepared in advance for analysis or reporting.
Example: "We need to analyze the advance data collected from the previous quarter to forecast future trends."
Alternatives: "preliminary data" or "pre-processed data".
Orders for durable goods, those intended to last at least three years, rose 2.9percentt in January, a smaller gain than the 3.3percentt increase reported in advance data on durable goods released last week.
Advance data released by the government's Central Statistical Organization said growth would be helped by the farm sector, which was expected to grow by 9.1percentt, compared with a drop of 5.2percentt a year ago.
The latest effort to use artificial intelligence to fight illegal fishing is coming from Virginia-based The Nature Conservancy (TNC), which launched a contest on Kaggle – a crowdsourcing site based in San Francisco that uses competitions to advance data science –earlier this week.
In order to store the macroblock's references, the proposed encoder is implemented with advance data structures, which eliminates the need for the extra picture buffer.
To support the new types of interaction, we must advance data modeling, information organization, and knowledge representation for an integrated discovery and leaning system to ensure the rigor and relevance of data curation.
In this concluding article of the NextGen Special Issue we synthesize insights and formulate a strategy to advance data, models, and knowledge products that are consistent with this vision.
In the race to advance data-driven electioneering strategies pioneered by successive Obama campaigns, Cruz has turned to Cambridge Analytica for its unparalleled offering of psychological data based on a treasure trove of Facebook "likes", allowing it to match individuals' traits with existing voter datasets, such as who owned a gun.
The purpose of the network is to support CDOs in collaborative efforts to improve and share their work to advance data-driven government.
The objective of this research was to advance data-driven digital soil mapping techniques for the prediction of soil physical properties at high spatial resolution using auxiliary data in a semiarid ecosystem in southeastern Arizona, USA.
The goal of this research was to advance data-driven digital soil mapping techniques by developing an approach that can integrate multi-scale digital surface topography and reflectance-derived remote sensing products, and characterize multi-scale soil-landscape relations of Quaternary alluvial and eolian deposits.
With the advancement of high throughput sequencing technology, advanced data mining techniques have been developed for high throughput DNA sequencing data [ 1, 2].
