The stability criteria presented here may be used not only to obtain flutter and divergence boundaries, but also to identify various instability zones in a parameter space.
However, the calculation procedure and design criteria presented here are applicable to any oxygen carrier to be used in the process.
For all the criteria presented here, more transmission power is allocated to the channels which have larger gain of H r [k] and suffer less interference power provided by the cellular communication systems.
The criteria presented here can, therefore, be considered a foundation upon which to build future consensus criteria.
In all three settings (σ = 0.5, 0.1, 0.01), the proposed MCMC-Mallows algorithm was better able to estimate the causal effects than either Pinna or IDA, as shown by the different criteria presented here.
The criteria presented here follow the same principles of science as applied by wet-laboratory scientists, where data are confirmed by repetitions on the one hand, and by additional experimental strategies to exclude alternative explanations on the other.
Since the criteria presented here rely on a mixture of intrinsic features of health states, and frequency statistics obtained from empirical sources, the alternative sampling scheme described is not necessarily generalisable to all national contexts.
Then a clustering approach implemented in the QTLClust module and based on a Gaussian mixture model, determines the optimal number, K, of clusters by means of 4 different information-based criteria, including the Akaike Information Criterion (AIC) that is the only criteria presented here.
Unlike reported studies where the superiority of this criterion was only demonstrated through off-line simulation, both the theoretical modeling and practical implementation of this criterion is presented here using the one machine infinite bus system.
