3 resultados para Sarah network of hospitals

em Universidad de Alicante


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Urban researchers and planners are often interested in understanding how economic activities are distributed in urban regions, what forces influence their special pattern and how urban structure and functions are mutually dependent. In this paper, we want to show how an algorithm for ranking the nodes in a network can be used to understand and visualize certain commercial activities of a city. The first part of the method consists of collecting real information about different types of commercial activities at each location in the urban network of the city of Murcia, Spain. Four clearly differentiated commercial activities are studied, such as restaurants and bars, shops, banks and supermarkets or department stores, but obviously we can study other. The information collected is then quantified by means of a data matrix, which is used as the basis for the implementation of a PageRank algorithm which produces a ranking of all the nodes in the network, according to their significance within it. Finally, we visualize the resulting classification using a colour scale that helps us to represent the business network.

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Results of the monitoring network of the Posidonia oceanica meadows in the Valencia region in Spain are analysed. For spatial comparison the whole data set has been analysed, however, for temporal trends we only selected stations that have been monitored at least 6 years in the period of 2002–2011 (26 stations in 13 localities). At the south of the studied area, meadows are larger, and they have higher density and covering than that in the Valencia Gulf, excluding Oropesa meadow. Monitoring of P. oceanica meadows in the Valencia region in Spain indicates that most of them are stationary or they are increasing their density and covering while no decline was observed in the studied meadows. These results indicate that there is not a general decline of P. oceanica meadows and that the decline of P. oceanica, when it has been observed in other studies, is produced by local causes that may be managed at the local level. This study also reflects the importance of long series of direct data to analyse trends in the population dynamics for slow-growing species.

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his paper discusses a process to graphically view and analyze information obtained from a network of urban streets, using an algorithm that establishes a ranking of importance of the nodes of the network itself. The basis of this process is to quantify the network information obtained by assigning numerical values to each node, representing numerically the information. These values are used to construct a data matrix that allows us to apply a classification algorithm of nodes in a network in order of importance. From this numerical ranking of the nodes, the process finish with the graphical visualization of the network. An example is shown to illustrate the whole process.