A designing philosophy utilizing the similarity between hardware, software and the problems to be solved is embodied, based on the multi-scale method and discrete simulation approaches developed at Institute of Process Engineering IPEE) and implemented in a graphic processing unit (GPU -based hybrid computinGPU -based
The results of the present study seem to indicate however that these traditional strategies perform worse than the simulation-based approach developed in the present study, and that in reality, it is a combination of highly mutable mtSNPs and haplogroup diagnostic sites that optimized the ability of a given mtSNP panels to account for the highest levels of diversity.
In this study, a multi-physics based EIS simulation approach is developed to study the cycling effect on the battery impedance responses.
In this study, a microstructure-based finite element simulation approach was developed to predict the elastic mechanical behaviors of hollow spheres filled syntactic foams.
In an attempt to overcome these difficulties, in the present paper we adopt a Monte Carlo simulation approach, previously developed on the basis of the Kolmogorov Dmitriev theory of branching stochastic processes.
So in this paper, based on routine bridge weight-in-motion (B-WIM) results, a simulation approach is developed and proposed to predict bridge safety and integrity if heavy trucks experience emergency braking on the bridge.
We show a realization of these concepts as part of ML-Rules, a modeling and simulation approach we developed.
A simulation approach is developed based on the sufficient cause model to test the likelihood of significant associations observed between a noncausally related exposure and the outcome.
To describe the healthcare team training in obstetric emergencies using clinical simulation with an interdisciplinary approach, developed at the Hospital virtual Valdecilla.
We analyse three VaR calculation methods: the historical simulation standard approach, the historical simulation with ARMA forecasts (HSAF) approach, developed in this paper, and the variance covariance method based on autoregressive conditional heteroskedasticity models forecasts.
