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We perform Monte Carlo simulations with Matlab®; using the parameters presented in Table 1.
Monte Carlo simulation, also known as multivariate sensitivity simulation (MVSS), was used on the LCD option scenario in understanding the behavioral boundaries of its maximum and minimum values respectively using the parameters presented in Table 8.
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For the analysis we used the parameters presented in Table 4, to compare a hypothetical pure Electric Vehicle (EV), an Extended Range Electric Vehicle EREVV), a Hybrid Electric Vehicle (HEV) and a conventional gasoline ICE vehicle (CV) [19].
Using the parameter values presented in Table 1, we predict that a phage unable to express psbA would produce 2.81% fewer genomes after 8 h of infection.
Further, using the spectroscopic parameters presented in Table 1 which are taken from Ref. [8], we computed rotational-vibrational energy spectrum of some diatomic molecules in 2,3,4,5-dimensions.
Summarizing, the equation to generate the time-to-event data was: The Weibull density equation and curves for time-to-event using the parameters above are presented in Figure 1.
Instead of this stepwise modelling, the plastic work hardening of the materials was modelled with the Hollomon hardening law using the material parameter presented in Table 1.
So we presented the sROC curves obtained by using the parameters of the hierarchical model to present overall summary of GP73 and AFP.
We used population parameters presented in the M true column (Table 2 ) for data simulation.
This goal has been reached using the presented parameters and we are convinced that the process can be tailored to various applications.
In this article, we use NS2 [20] as the simulation tool and use the network environment parameters presented in Table 1 as simulation parameters.
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