Sentence examples for generated relationships from inspiring English sources
Subsequently, the family of model generated relationships, each a function of soil background and canopy characteristics, was employed for a fast pixel-wise mapping of Cab and LAI.
Solid lines indicate the generated relationships are proofed by Chem2Bio2RDF (i.e. there is a relationship in one of the Chem2Bio2RDF datasets that confirms the literature relationship).
The dashed lines indicates the generated relationships have not been found in Chem2Bio2Rdf, perhaps indicating very recent findings which are not yet encoded in databases, or associations which are not direct enough to be in a dataset.
Pathway studio then generated relationships between gene products using a literature search of curated genes and displayed the interactions in the form of pathways that can also include other genes/proteins, small molecules, cellular processes, and relevant transcription factors.
"But if you can generate relationships that are more inspired and personal, it will only encourage everyone to keep giving in the future".
They say it is a way for students to fund their way through university, do something for the social good and generate relationships between two of the most ignored groups of our society – students and the elderly.
The following algorithm shown in the Figure 3 refines the preliminary RDF diagram using extracted term set: Figure 3 Algorithm to generate relationships among content resources.
The proposed methodology enables Web-based system developers to generate relationships between resources, and to improve software quality by adopting software engineering techniques in XML development.
The soil-vegetation-atmosphere transfer (SVAT) model WAVES was used to generate relationships between net recharge (diffuse recharge minus evapotranspiration from groundwater) and depth to water table for different combinations of climate, soil and land cover types.
Literature mining has been extensively used to generate relationships between entities (keywords, genes, concepts, diseases, etc) that co-occur in publications [12] [15].
We also present an algorithm to generate relationships between these homology groups.
