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In this paper, with the findings from the computer support cooperative work (CSCW /computer support collaborative learning (CSCL) and advantages provided by grid, we propose to build grid-enabled large-scale collaboration environment (GLCE).
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In the context of the 2D unstructured grids, we propose a limitation procedure on the gradient reconstruction to enforce several stability properties.
In order to avoid the stringent time step restriction imposed by very fine grids, we propose strategies that allow for a fluid velocity CFL number larger than 1.
Under the smart grid environment, we propose a coordinated scheduling model of power system with ADNs based on multi-agent system.
For the linear sub-grid reconstruction, we propose two possible candidates for consistent gradient discretization over general grids.
To achieve this goal, Spatial subdivision algorithm is firstly proposed to partition space into a uniform grid, we also propose parallel radix sort algorithm and then sort the particles based on their hash values.
In the grid coding scheme that we propose there is a hierarchy of grid periods governed by a geometric progression.
In this paper, we propose Grid Sampling DMR (GS-DMR), a low-overhead soft error detection scheme for stencil-based computation.
To circumvent problems associated with completely arbitrary grids and complex geometries we propose to use a multi-domain formulation in which to solve the partial differential equation, with the ability to adapt the grid as well as the order of the scheme within each subdomain.
To reduce the computational burden, we propose a grid search procedure with a simplified calculation of the objective function.
We propose a grid model for the vegetation in bands, with special emphasis on those comprising the tiger bush in the Sahel.
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CEO of Professional Science Editing for Scientists @ prosciediting.com