Sentence examples for heterogeneous contexts from inspiring English sources

The aim of this paper is to present an information granulation of the linguistic information used in group decision making problems defined in heterogeneous contexts, i.e., where the experts have associated importance degrees reflecting their ability to handle the problem.

In e-marketplace, semantic document exchange is a methodology of providing exchangeable semantic documents, which ensures document writer, writer's computer, reader's computer and document reader to share a same understanding in meaning on any exchanged document, that is, a semantic document is exchangeable across any heterogeneous contexts.

Population studies operate in heterogeneous contexts.

Several factors indicate the robustness of the findings: the themes identified were repeated across a large proportion of the studies, despite the heterogeneous contexts and populations; the themes did not vary substantially across different countries; and the sensitivity analysis revealed that removing studies rated as 'low' did not alter the findings of the review.

While the Stages of Change model we detailed here emphasizes early recognition and acceptance of enucleation (a survival priority) that may best apply to late presenting retinoblastoma in resource-limited settings, components and applications of this model may be adapted for other heterogeneous contexts.

Finally, we investigate different clustering approaches for the hybrid data fusion in the heterogeneous context.

In the following, we describe the genetics-based algorithm applied in the heterogeneous context for positioning purposes.

This study contributes to this heterogeneous context by investigating public participation in GIS within the field of mobile-based applications.

These are heterogeneous context perception and integration at the semantic level, and context-aware content discovery and adaptation at run-time.

Organizations are constantly facing accelerating macro- and micro-level environmental changes, challenging to become dynamic and adapt to the unstable and heterogeneous context.

Other challenges that need to be addressed to develop robust mobile learning recommenders are those related to (i) the limited-resource mobile technology; (ii) low-bandwidth and unsecured wireless communication; (iii) heterogeneous context management and (iv) personalized content retrieval.