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This work presents a molecular dynamics simulation method designed to describe the processes of electron and lattice relaxation taking place in the typical cascade volumes formed by high-energy implants.
Particle filtering is a Monte Carlo simulation method designed to approximate non-linear filters that estimate and track the state of a dynamic system.
A parallel molecular dynamics simulation method, designed for large-scale problems, employing dynamic spatial domain decomposition for short-ranged molecular interactions is proposed.
The chapter reviews the results of a multiscale simulation method designed to understand the surfactant-mediated synthesis of cobalt nanodots and their assembly into two-dimensional hexatic arrays in a unified manner.
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In Section 3, the DGs mathematical modeling are introduced, and the Monte Carlo simulation methods designed for energy without the high penetration case are proposed in detail.
This paper focuses on the design of 3D woven-fiber composite products and proposes a flattening simulation method for designed 3D models with constant thickness.
Next, a memetic algorithm (MA) with a fuzzy simulation method is designed to solve the problem.
A numerical simulation method was designed to generate the following car's trajectories by using the field trajectories as the input.
Our simulation method is designed for high-porosity insulation media with air as the interstitial fluid where conduction through the solid structure is minimal.
Whereas anticipated discrete faults can be properly addressed by fault dictionary methods based on simulation, a consistency based method designed for hybrid systems is proposed to address parametric faults and non-anticipated faults.
We evaluate our programs using high-quality sequence data for a set of gene clusters (including the well-studied β-globin and α-globin clusters) as well as simulation data produced using the method designed in our study evaluating conversion detectors (Song, Hsu, Riemer, and Miller 2011).
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