36 resultados para Network (Re) Organization
Resumo:
Trabalho de Projeto submetido à Escola Superior de Teatro e Cinema para cumprimento dos requisitos necessários à obtenção do grau de Mestre em Teatro - especialização em Teatro e Comunidade.
Resumo:
Session 7: Playing with Roles, images and improvising New States of Awareness, 3rd Global Conference, 1st November – 3rd November, 2014, Prague, Czech Republic.
Resumo:
We model the cytoskeleton as a fractal network by identifying each segment with a simple Kelvin-Voigt element with a well defined equilibrium length. The final structure retains the elastic characteristics of a solid or a gel, which may support stress, without relaxing. By considering a very simple regular self-similar structure of segments in series and in parallel, in one, two, or three dimensions, we are able to express the viscoelasticity of the network as an effective generalized Kelvin-Voigt model with a power law spectrum of retardation times L similar to tau(alpha). We relate the parameter alpha with the fractal dimension of the gel. In some regimes ( 0 < alpha < 1), we recover the weak power law behaviors of the elastic and viscous moduli with the angular frequencies G' similar to G" similar to w(alpha) that occur in a variety of soft materials, including living cells. In other regimes, we find different power laws for G' and G".
Resumo:
Trabalho final de Mestrado para obtenção do grau de Mestre em Engenharia de Electrónica e Telecomunicações
Resumo:
Trabalho de Projecto de Natureza Científica para obtenção do grau de Mestre em Engenharia Civil
Resumo:
The main result of this work is a new criterion for the formation of good clusters in a graph. This criterion uses a new dynamical invariant, the performance of a clustering, that characterizes the quality of the formation of clusters. We prove that the growth of the dynamical invariant, the network topological entropy, has the effect of worsening the quality of a clustering, in a process of cluster formation by the successive removal of edges. Several examples of clustering on the same network are presented to compare the behavior of other parameters such as network topological entropy, conductance, coefficient of clustering and performance of a clustering with the number of edges in a process of clustering by successive removal.