The knowledge-based framework can be adapted to provide a harmonised and standardised dataset for any riverine study area.
The paper shows how a shared ontology-based framework can be used to generate consistent 3D virtual environments and discrete event simulation models, demonstrating this way how the proposed solution can provide an interoperable backbone for heterogeneous software tools.
The implementation of health policy through a consumer-oriented intervention, set within a contemporary pain management evidence-based framework, can be successfully delivered within primary care.
Solution: reaction probability in the interaction volume: Both concepts, the flux/surface-based description and the macroscopic, volume-based framework can be brought into agreement in the following way: 1.
The article proposes that a life cycle based ecodesign framework can be a driver for sustainable innovations in components, product systems, technologies and business models.
It is found that the proposed genetic algorithm based multi-objective framework can be implemented to multi-dimensional engineering problems to obtain the Pareto-optimal set.
It is well-known that the solutions based on LS framework can be easily distorted by a single outlier.
The study plan based on a theoretical framework can be an essential first step for establishing effective intervention programs for obesity among professional and voluntary firefighters.
If essential structural properties are shared, hard- and soft-linking of applications based on the same framework can be performed even with different modelling approaches or with models using different regional and temporal resolutions.
The results show that the parallel method based on the MapReduce framework can be successfully used to gather networks with desired behaviors and the computation time can be reduced.
The building and testing of comparison model based on the classification model framework can be accomplished using the following steps: 1) Sample positive and negative target genes data as a training model of the data set, from positive target genes (788 groups) and negative target genes (4000 groups) randomly, with total of 4788 target genes.
