Semantic-based & Customizable Data Extraction and Dynamic Data Loading
The paper presentes a method of semantic-based customizable data extraction and dynamic data loading.It provides the description of semantic-based metadata on source database and generates the general tactic mode according as data requirement for different user and semantic-related data.Based on strategy the corresponding data extraction approach was proposed and implemented.In the end,the methods of fault-tolerant and dynamic data loading are adopt to realize bulk data migration among different structure database on a certain extent.
Background ::: Anthropometric models remain appropriate alternatives to estimate body composition of peripubertal populations. However, these traditional models do not consider other body components that undergo major changes during peripubertal growth spurt, with restrictions to a multicompartimental approach as a quantitative growth. DXA has great potential to determine pediatric body composition in more than one component (3-C), but has limited use in field settings. Thus, the aim of this study was to propose and validate an anthropometric model for simultaneous estimation of lean soft tissue (LST), bone mineral content (BMC) and fat mass (FM) in healthy girls, from a multivariate approach of densitometric technique, as the criterion method.