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I suspect that a problem that used to dog Western sites that the businesses were run by a generation that just didn't "get" the Web persists in Japan.
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This paper describes a multi-objective power dispatching problem that uses Plug-in Electric Vehicle (PEV) as storage units.
We approach the localization problem by formulating an alternative problem that uses distance estimates locally computed at each node.
We therefore developed a novel regularization scheme for the inversion problem that uses discontinuity, sparsity, and smoothness constraints.
The schemes are based on the solution to a local Riemann-type problem that uses d'Alembert's exact solution.
In this paper we propose a metamodel-independent solution to this problem that uses ATL (Atlas Transformation Language).
In this paper, a multi-objective power dispatching problem that uses Plug-in Electric Vehicle (PEV) as storage units is considered.
We describe the theoretical solution of an approximation problem that uses a finite weighted sum of complex exponential functions.
This instantaneous linear model comes from the mathematical formulation of the EEG/MEG forward problem that uses the quasi-static formulation of Maxwell's equations.
The first space is based on a local eigenvalue problem that uses an interior weighted L2-norm and a boundary weighted L2-norm for computing the "mass" matrix.
Next, we attempt to minimize fixed and operating costs by introducing an optimal sizing problem that uses as constraints the requirements on vehicle performance.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com