Though introduced recently, complex networks research has grown steadily because of its potential to represent, characterize and model a wide range of intricate natural systems and phenomena. Because of the intrinsic ...

When the resilience of a network is analyzed it is often studied alone, but in the real world networks usually interact with other networks establishing dependencies. The Internet at a BGP level is an example of this kind ...

While the inventor is often the driver of an invention in the early stages, he/she needs to move between different social networks for knowledge in order to create and capture value. The main objective of this research is ...

Neural networks are dynamic systems consisting of highly interconnected and parallel nonlinear processing elements that are shown to be extremely effective in computation. This paper presents an architecture of recurrent ...

Combining social network analysis (SNA) and data envelopment analysis (DEA) techniques is a recent and relevant trend in the literature. However, although other works have integrated these techniques, none have done so in ...

The patterns of scientific collaboration have been frequently investigated in terms of complex networks without reference to time evolution. In the present work, we derive collaborative networks (from the arXiv repository) ...

Species establish different interactions (e.g. antagonistic, mutualistic) with multiple species, forming multilayer ecological networks. Disentangling network co-structure in multilayer networks is crucial to predict how ...

Innovation is widely recognized as important. In addition, in this context, innovation networks have gained importance in academic studies, since an organization alone, does not always have access to all necessary resources. ...