In the production step, data from step 1, together with other inputs, is used to run crop models (DSSAT, HERMES, MONICA, STICS, EPIC or AquaCrop) that analyse the impact on sunflower yields.
In the first step, data from a binary source is arranged in K subcarriers carrying M subsymbols each, which result in a total of MK parallel substreams.
In the last step, data from different EC stations around a route were converted into a single dataset by taking their arithmetic mean.
In the first step, data from the data sources are retrieved, potentially merged, filtered, and finally aggregated, in order to provide datasets that highlight one particular aspect of the OSM project.
In the second step, data from the html files were saved as a single file in Microsoft word.
As a first step, data from previously sequenced BACs that span genes MELO3C004258 (partially) to MELO3C004290 (partially) was analyzed to close unresolved gaps.
In this step, data from a longitudinal quantitative study and a qualitative multiple case study involving 40 family physicians were analyzed.
To predict the stability of the sequence, we used the base step data from Santalucia et al. and the formula described in their study [ 41].
In a first step, data from simulations with the same number of subjects on active drug and on placebo was used and 6, 9, 12, 15, and 18 subjects per group were selected.
Data processing for Smart Cities become more challenging, facing with different handling steps: data collection from different heterogeneous sources, processing sometimes in real-time and then delivered to high level services or applications used in Smart Cities.
