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| Grant number: | 15/18942-8 |
| Support Opportunities: | Scholarships in Brazil - Post-Doctoral |
| Start date: | May 01, 2016 |
| End date: | May 31, 2017 |
| Field of knowledge: | Physical Sciences and Mathematics - Physics |
| Principal Investigator: | Luciano da Fontoura Costa |
| Grantee: | Cesar Henrique Comin |
| Host Institution: | Instituto de Física de São Carlos (IFSC). Universidade de São Paulo (USP). São Carlos , SP, Brazil |
| Associated research grant: | 11/50761-2 - Models and methods of e-Science for life and agricultural sciences, AP.TEM |
Abstract There has been an increasing interest in applying complex networks to model systems composed by many elements, specially in cases where such elements interact in a non-trivial manner. Many studies developed in the area aim at defining a model to explain certain properties of the connectivity, such as the degree distribution and community structure, and dynamics, such as phase transitions and vulnerability, of the system under study. Such models are usually based on singular principles acting on the connectivity of all elements of the system. Well-known examples of such principles are the preferential attachment and the small-world property. We aim at establishing a distinct approach to complex systems modeling by assuming the existence of a set of features related to the system, which can be as large as necessary in order to explain the system topology. In this context, the network evolution is seen as a recurring relationship between the influence of node features on the network topology and the subsequent acting of the topology to modify such features. Therefore, the network can be considered as being embedded in an effective feature space, in which the nodes adjust their positions and connectivity along time. Our goal is to develop a methodology to uncover such space, and show that features belonging to this space, which oftentimes cannot be properly observed, directly act on the system connectivity. The methodology will be applied to a number of network models, as well as networks representing the topology of real-world systems such as street crossings, blood vessel bifurcations and airlines between airports. | |
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