The dynamics of CO2 emissions and economic growth: A comparative analysis using symbolic time series

The aim of this paper is to analyze the dynamic relationship between economic growth and CO2 emissions for a set of 98 countries over the lengthy period from 1951 to 2014. We describe the topology and hierarchy of countries and introduce a different concept of economic performance based on the idea of dynamic regimes. These regimes are defined by the average levels of per-capita CO2 emissions and the growth rates of per-capita GDP. By presenting a nonparametric clustering technique, the paper identifies two main groups. One cluster can be identified as the group of developed countries, which presents a homogeneous structure and tends toward more similar dynamics over time. The other cluster, associated with developing countries, is homogeneous but the dynamics of the countries do not show convergence. The study also finds some, though little, mobility between the groups.

Experimental evaluation of nonparametric clustering algorithms for image segmentation

Experimental evaluation of 12 nonparametric clustering algorithms for image segmentation was made. Algorithms developed in FRC ICT are compared to ones from ENVI, ELKI and Smile software packages. Seven model datasets were generated to estimate clustering accuracy. The computational efficiency was evaluated using digital photographs and fragments of multispectral images obtained from WorldView-2 satellite.