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The advantage of parallel computing when using meta-heuristic techniques for optimizing multi-scale models was clear: for example, the CPU time reduced by up to 50% when twice the number of cores was utilised to simulate the multi-scale model in gPROMS.
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In this work, EFG is utilised to simulate the orthogonal cutting process of unidirectional composites.
Thus, three dynamic loading models were utilised to simulate human rhythmic activities such as jumping and aerobics.
The Gaussian pyramid model is utilised to simulate a multi-scale structure that often comprises nine images with different spatial resolutions.
Published experimental data was utilised to validate the developed model.
Peel-ply was utilised to achieve the characteristic surface texture.
The Kolmogorov-Smirnov test was utilised to determine Gaussian distribution.
NVivo10 was utilised to aid in data management and coding.
Bootstrap method was utilised to calculate the CIs for AUC.
A topic guide was utilised to guide qualitative data collection.
The software package SPSS 15.0 was utilised to analyse data.
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