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We keep our implementation close to the structure published by Kasap et al. [3,4] and include ideas from Sotiriades et al. [5] such that all parts of the algorithm are organized in components of a long pipeline.
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In general terms, these recommendations would aim to bring the tool and its implementation closer to the needs and values of its final users, since, as asserted by Logan et al., the closer to the final user, the more likely that the implementation strategies will be effective [ 13].
The use of decentralized control leads to performance deterioration as compared to centralized control, but brings other advantages: on one hand, it allows for a local implementation close to each actuator, on the other, sensor or actuator failures create only local disturbances.
Its extension to the case of heterogeneous and/or anisotropic cases is exploited here, keeping an implementation cost close to the popular Raviart Thomas mixed finite element of the lowest order, known as RT0.
Because we tested three 2D-lattice parameter extraction computer programs on calculated images that do not contain systematic errors by themselves, essentially only random errors should have propagated to the extraction results if the corresponding algorithm implementations were close to the ideal algorithm implementation of the preceding paragraph.
This detector is considered for comparison for several reasons, first its implementation is very close to the successful work of Viola and Jones detector.
They show that the relaxed implementations are reasonably close to the optimal solution, and provide vast gains compared to the traditional overlay topologies that peer-to-peer applications build.
With our implementation we are very close to the theoretical bound of the cheap gradient principle.
Thus, based on this typology, MAR implementation through controlled infiltration close to the estuarial area seems to be more appropriated, whereas the direct deep injection appears to be more relevant in more distant zones.
This can prevent writing formal specifications close to the actual implementation, and can thus hamper a refinement-based stepwise development.
The aim of this paper is to find a quantization technique that has low implementation complexity and asymptotic performance arbitrarily close to the optimum.
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