In contrast, the IHC results were not significantly correlated to the results from with the other methodologies we applied.
As an illustration of the power of this methodology, we apply it to biomineralized shells, avian beaks and feathers, and fish scales.
In order to illustrate the methodology we apply the model to a panel of 48 countries (Asia, Latin America, Africa) and four periods between 1970 and 2005.
To illustrate this new methodology, we apply it to determine the regularity regions of a non-linear example whose firing maps undergo bifurcations that were unknown for the previously studied linear systems.
Thus, in our methodology, we apply the MCMC sampler of Friedman and Koller (2003) to infer Bayesian Network structures for each hidden state of the HDP-HMM by sampling over total orderings of the nodes, given the data points corresponding to the state in question.
In addition, the methodology we apply also helps assess the importance of individual determinants – e.g., what proportion of rural-urban HAZ score differentials may be explained by differential wealth or maternal education levels, and how does this proportion vary across the HAZ distribution?
In order to test the strength of the proposed methodology we applied it to a case study in the above-tree-line glacial cirque of Mount Prado (Northern Apennines, N Italy).
In addition to this section, this paper has the following sections: Section 2 describes the case description with: the description of the methodology we applied in this research, and the description of the theoretical basis of the techniques and notation used in the analysis and design phases.
In order to test the performance of the proposed methodology, we applied it to the South American region with data obtained by RAPEAS (Red Argentina para el Estudio de la Atmósfera Superior, i.e. Argentine Network for the Study of the Upper Atmosphere) during the years 1958 2009.
In order to determine whether the disease signal could be validated using an alternative methodology, we applied the method of Cheadle et al [32] to validate across chip platforms.
In order to ascertain the sensitivity of the methodology, we applied the system to various simulated, artificial increases in the number of disease presentations or 'hotspots'hotspots
