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We implement this method in two and three space dimensions for a model of linear or nonlinear elasticity.
We implement this method for Staphylococcus aureus and Mycobacterium tuberculosis in a software package ('Mykrobe predictor') that takes raw sequence data as input, and generates a clinician-friendly report within 3 minutes on a laptop.
We implement this method in the two-dimensional case, and test it by verifying the von Neumann relation, which governs the coarsening of a two-dimensional dry foam.
We implement this method in the context of the kernel density estimator, where one needs to select the bandwidth parameter so as to minimize L2 risk.
We implement this method in the three-dimensional framework, and test it by verifying the 3D generalization of the von Neumann relation, which governs the coarsening of a three-dimensional dry foam.
We implement this method in a real environment using the optimal compensation parameters estimated from an artificial environment.
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We implemented this method on the FEniCS C++ platform and show time and spatial convergence results.
We implemented this method in a web-based authoring tool called Virtual People Factory.
In this paper, we implemented this method to one-dimensional two-group problems and proved its validity for these problems.
We implemented this method along with other two master-worker schemes (a previously existing one and a recently modified one) for three different scientific computational kernels.
We implemented this method and present it in section 3.1.1.
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