This method builds a knowledge-data-integrated sparse (KDIS) monitoring model by integrating process data with fundamental process knowledge.
The designer should then be able to select and extract the required information from a predefined knowledge data base, enabling him to take decisions at the architectural stage and thus solve design problems.
Briefly, steps 1 3 involve qualitative methods and data, step 4 transforms these data into figures and quantities, while step 5 represents a more hybrid knowledge data formation stage, usually creating both narratives and numbers, though with a prominence to the quantified output.
Concerning bioenergy and biomass, there is a large list of available knowledge, data and models from heterogeneous sources.
To our knowledge, data set A is actually unique for the number of technical replicates of clinical DNA samples profiled on Illumina 450K arrays.
To the best of our knowledge, data on a specific dimension of optimism, that is, confidence in the future, as well as information on the extent to which socioeconomic factors and psychological distress explain the association, are lacking.
Most profoundly, we lacked a governmentwide capability to integrate foreign and domestic knowledge, data operations and analysis.
It takes people, it takes skills, it takes tools to become knowledge, data and change.
This fact showed the pharmacological dependency of some knowledge data.
To our knowledge, data on pulmonary effects are limited.
To correct this deficiency, a novel knowledge-data-integrated sparse modeling method is proposed for batch process monitoring.
