Estimating the clustering coefficient in scale-free networks on lattices with local spatial correlation structure

2008 ◽  
Vol 387 (21) ◽  
pp. 5287-5294 ◽  
Author(s):  
Anastasios A. Tsonis ◽  
Kyle L. Swanson ◽  
Geli Wang
Keyword(s):  
Spatial Correlation ◽  
Clustering Coefficient ◽  
Correlation Structure ◽  
Scale Free ◽  
Spatial Correlation Structure ◽  
Scale Free Networks

Sky-Cover Correlation within a Sky Dome

1991 ◽  
Vol 30 (7) ◽  
pp. 1037-1039 ◽  
Author(s):  
James H. Willand ◽  
Julia Steeves
Keyword(s):  
Spatial Correlation ◽  
Cloud Cover ◽  
Correlation Structure ◽  
National Weather Service ◽  
Structural Pattern ◽  
The Earth ◽  
Spatial Correlation Structure ◽  
Sky Conditions ◽  
Very High ◽  
Weather Service

Abstract A new utility for the use of whole-sky photographs has been developed through an effort to discern the structural pattern of correlations of cloud cover within an observer's sky dome. The photographs were taken from the National Weather Service observing site at Columbia, Missouri, and were originally assembled for the purpose of estimating probabilities of cloud-free lines of sight from the earth through the atmosphere. The procedure for determining the spatial correlation structure of sky cover within the sky dome starts with the defining and tabulating of a dichotomous sky-cover condition over small sectors of the sky dome, and then calculating the correlation associated with the tabulated sky conditions in each sector. This note shows that correlation of sky-cover conditions over a sky dome are very high, and that they are less degrading in the winter than in the summer. The results of this study can be applied to the estimation of cloud-free lines of sight to multiple satellites.

scholarly journals Scale-Free Networks with the Same Degree Distribution: Different Structural Properties

2013 ◽  
Vol 2013 ◽  
pp. 1-9 ◽  
Author(s):  
José H. H. Grisi-Filho ◽  
Raul Ossada ◽  
Fernando Ferreira ◽  
Marcos Amaku
Keyword(s):  
Structural Properties ◽  
Degree Distribution ◽  
Pearson Correlation ◽  
Clustering Coefficient ◽  
The Other ◽  
Scale Free ◽  
Component Size ◽  
Global Efficiency ◽  
Nearest Neighbours ◽  
Scale Free Networks

We have analysed some structural properties of scale-free networks with the same degree distribution. Departing from a degree distribution obtained from the Barabási-Albert (BA) algorithm, networks were generated using four additional different algorithms (Molloy-Reed, Kalisky, and two new models named A and B) besides the BA algorithm itself. For each network, we have calculated the following structural measures: average degree of the nearest neighbours, central point dominance, clustering coefficient, the Pearson correlation coefficient, and global efficiency. We found that different networks with the same degree distribution may have distinct structural properties. In particular, model B generates decentralized networks with a larger number of components, a smaller giant component size, and a low global efficiency when compared to the other algorithms, especially compared to the centralized BA networks that have all vertices in a single component, with a medium to high global efficiency. The other three models generate networks with intermediate characteristics between B and BA models. A consequence of this finding is that the dynamics of different phenomena on these networks may differ considerably.

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