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In general, two types of implementing methods are widely used in the literature, and in the demonstration projects that will be introduced in Sections 3 and 4. The implementing method is defined as a way to find the equilibrium among the actors, and thus complete the transactions.
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The success of implementing methods is dependent on contextual factors that influence the intervention's outcome(s) and sustainability.
Moreover, the implemented method is highly parallel and therefore suitable for High Performance Computing.
The most widely implemented method is patterning the graphene into a narrow ribbon called graphene nanoribbon (GNR) [4].
The first implemented method is a numerical-multiphysics method which couples computational fluid dynamics and heat-transfer equations.
The experimental validation of the implemented method showed that the implemented method is able to assess quantitatively the linearity of the system.
The principle of the implemented method is to refine an initial solution of the local tomography problem, knowing that middle and high-frequency features are usually well recovered.
Therefore, the implemented method is suitable for real-time posture estimation without using high-performance hardware.
However, we observed, as also noted by Hu [ 38] in their own model, that the implemented method is sensitive to outliers.
His implemented method was a fuzzy regression nearest neighbor ANN model.
The implemented method was tested comparing the wind map with both literature and the available experimental data.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com