An improved method for discovering link criticality in transport networks

Quantitatively assessing the importance or criticality of each link in a network is of practical value to operators, as that can help them to increase the network's resilience, provide more efficient services, or improve some other aspect of the service. Betweenness is a graph-theoretical measure of centrality that can be applied to communication networks to evaluate link importance. However, as we illustrate in this paper, the basic definition of betweenness centrality produces inaccurate estimations as it does not take into account some aspects relevant to networking, such as the heterogeneity in link capacity or the difference between node-pairs in their contribution to the total traffic. A new algorithm for discovering link centrality in transport networks is proposed in this paper. It requires only static or semi-static network and topology attributes, and yet produces estimations of good accuracy, as verified through extensive simulations. Its potential value is demonstrated by an example application. In the example, the simple shortest-path routing algorithm is improved in such a way that it outperforms other more advanced algorithms in terms of blocking ratio

"Mad dogs and transnational migrants?" Bajan-Brit second-generation migrants and accusations of madness

Second-generation British-Barbadians ("Bajan-Brits'') returning to the land of their parents are frequently accused by indigenous Barbadian nationals of being mad. Narratives of the migrants reflect four major sets of factors: (1) madness as perceived behavioral and cultural differences; (2) explanations that relate to the historical-clinical circumstances surrounding the incidence of mental ill health among first-generation West Indian migrants to the United Kingdom; (3) madness as a pathology of alienation that is attendant on living in Barbados; and (4) madness as "othering,'' "outing,'' and "fixity.'' British second-generation "returning nationals'' to the Caribbean, living as they do in the plural world of the land of their parents' birth, after having been raised in the colonial "Mother Country,'' exhibit hybridity and in-betweenness. Accusations of madness serve to fix the position of these young migrants outside the mainstream of indigenous Barbadian society. Our analysis invokes recent postcolonial writings dealing with "strange encounters'' to theorize that the madness accusation serves to "other'' the young Bajan-Brit migrants in a strongly postcolonial context.

Comparison of the interactomic networks of different species in terms of accessibility

Protein-protein interaction networks were investigated in terms of outward accessibility, which quantifies the effectiveness of each protein in accessing other proteins and is related to the internality of nodes. By comparing the accessibility between 144 ortholog proteins in yeast and the fruit fly, we found that the accessibility tends to be higher among proteins in the fly than in yeast. In addition, z-scores of the accessibility calculated for different species revealed that the protein networks of less evolved species tend to be more random than those of more evolved species. The accessibility was also used to identify the border of the yeast protein interaction network, which was found to be mainly composed of viable proteins.

Investigating relationships within and between category networks in Wikipedia

This work maps and analyses cross-citations in the areas of Biology, Mathematics, Physics and Medicine in the English version of Wikipedia, which are represented as an undirected complex network where the entries correspond to nodes and the citations among the entries are mapped as edges. We found a high value of clustering coefficient for the areas of Biology and Medicine, and a small value for Mathematics and Physics. The topological organization is also different for each network, including a modular structure for Biology and Medicine, a sparse structure for Mathematics and a dense core for Physics. The networks have degree distributions that can be approximated by a power-law with a cut-off. The assortativity of the isolated networks has also been investigated and the results indicate distinct patterns for each subject. We estimated the betweenness centrality of each node considering the full Wikipedia network, which contains the nodes of the four subjects and the edges between them. In addition, the average shortest path length between the subjects revealed a close relationship between the subjects of Biology and Physics, and also between Medicine and Physics. Our results indicate that the analysis of the full Wikipedia network cannot predict the behavior of the isolated categories since their properties can be very different from those observed in the full network. (C) 2011 Elsevier Ltd. All rights reserved.

On the efficiency of data representation on the modeling and characterization of complex networks

Specific choices about how to represent complex networks can have a substantial impact on the execution time required for the respective construction and analysis of those structures. In this work we report a comparison of the effects of representing complex networks statically by adjacency matrices or dynamically by adjacency lists. Three theoretical models of complex networks are considered: two types of Erdos-Renyi as well as the Barabasi-Albert model. We investigated the effect of the different representations with respect to the construction and measurement of several topological properties (i.e. degree, clustering coefficient, shortest path length, and betweenness centrality). We found that different forms of representation generally have a substantial effect on the execution time, with the sparse representation frequently resulting in remarkably superior performance. (C) 2011 Elsevier B.V. All rights reserved.

Análise bibliométrica da revista Scire: Um estudo de colaboração científica institucional

The aim of this research is to make a bibliometric analysis of the journal Scire: Representación y Organización del Conocimiento, edited in Spain, in order to evidence the most productive institutions and countries, as well as to build a cooperation network and calculate the density indicators, centrality degree and betweenness. The 292 articles of the period 1996 to 2010 were analyzed. It was found out that, of the institutions participating in the articles, 25 institutions have been clearly the most productive. Almost all of them are Spanish, except four Brazilian ones and three more from three different countries. The institutional network showed a low density, but several cooperative sub-networks were identified, which suggest the existence of an international dialogue among researchers on the discipline.

Aportes bibliométricos à produção científica nos principais periódicos da área de Ciência da Informação no Brasil, no período de 2006-2010

Pós-graduação em Ciência da Informação - FFC

Mitos hispânicos no romance histórico brasileiro: uma leitura de O Chalaça (1994) e de O feitiço da ilha do Pavão (1997)

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Investigadores de mayor visibilidad en Organización y Representación del Conocimiento: un estudio desde el análisis de cocitaciones

The most visible researchers in Knowledge Organization and Representation were identified, from the perspective of Brazilian researchers, based on cocitations from the papers presented in the last five meetings of the Encontros Nacionais de Pesquisa of the Associação Nacional de Pesquisa e Pós- Graduação em Ciência da Informação (ENANCIBs) from 2003 to 2008. First, the total number of references was identified, a total of 134 articles. Second, a citation analysis was conducted, being considered the most cited authors those who received 12 citations or more, which resulted in 31 most cited authors. Third, the Pajek software was used for the construction of the co-citation network and, thereafter, some indicators were calculated with the Ucinet software, which describe the structure and cohesion of the generated network, and, particularly, its density, and its degree of centrality, betweenness and proximity. The high cohesion of the network and the compliance between the most co-cited authors and the calculated indicators were verified.

Análise bibliométrica da revista Scire: um estudo de colaboração científica institucional

The aim of this research is to make a bibliometric analysis of the journal Scire: Representación y Organización del Conocimiento, edited in Spain, in order to evidence the most productive institutions and countries, as well as to build a cooperation network and calculate the density indicators, centrality degree and betweenness. The 292 articles of the period 1996 to 2010 were analyzed. It was found out that, of the institutions participating in the articles, 25 institutions have been clearly the most productive. Almost all of them are Spanish, except four Brazilian ones and three more from three different countries. The institutional network showed a low density, but several cooperative sub-networks were identified, which suggest the existence of an international dialogue among researchers on the discipline.

Produção e comunicação da informação em ct&i gt7 da ancib: análise bibliométrica no período 2003/2009

The aim of the present research is to analyse Ancib’s scientific production in the workgroup GT7 named Production and Communication of Information in ST&I, between the years of 2003 and 2009, through bibliometric indicators, from which it is possible to indicate what is more important or significant within a scientific field or context, so as to therefore analyse trends, existing relations or processes. The bibliometric studies are an approach method for the analysis of science behaviour in a given field. More specifically, by means of production and connection indicators, it aims at revealing and portraying the most productive authors, the kind of authorship present in this group, the most recurrent themes, most productive institutions, and the collaborative network determined by the institutional coauthorships and their indicators, so as to map and visualize the main researchers and institutions of the present GT, within the period of time in question. The research procedure derived from studying the 94 research project results presented in the period, where the paper reference, summary and corresponding key words can be found. Analysis concerning the most productive authors, most recurrent themes, kinds of authorship and most productive institutions have been carried out from the variables under review. The collaborative network between the institutions was built using the Pajek software, and, with the help of the Ucinet software, indicators of degree centrality, betweeness centrality, and closeness centrality have been reached, besides the calculation of density. The results point to 11 researchers and 9 institutions as the most productive ones. The collaborative institutional network was shown to be fragile, presenting low density, and in general the participating institutions have presented low centrality indexes. As a conclusion, it has been observed that the themes focus, in general, on bibliometric analysis and their indicators, using regional and national data as their universe.

Rede de coautoria institucional em Ciência da Informação: uma comparação entre indicadores de rede e os conceitos CAPES

The objective of this is study is to point inter-institutional partnerships in Information Science formed through co-authorship network. More specifically, we calculate indicators of centrality degree, betweenness centrality and closeness centrality, and analyze the relationships between the grades attributed by CAPES - Coordination for the Improvement of Higher Education Personnel - to the institutions and the indicators on the network, checking whether there is proximity and similarity between network indicators and CAPES's grades. Our corpus consisted of all articles published in the four journals in the field of Information Science in Brazil, with regular publications, based in SciVerse Scopus, for the 2010- 2012 period. We retrieved 237 articles, 58 co-authored, with 117 participant institutions. We conducted the analysis of relations between institutions with greater grades by CAPES and the network through centrality indicators. It was concluded that these network indicators and CAPES concepts are articulated, harmonizing these two categories of indicators.

Análise de propriedades topológicas das redes biológicas integradas da Escherichia coli e da Saccharomyces cerevisiae

Biological processes are complex and possess emergent properties that can not be explained or predict by reductionism methods. To overcome the limitations of reductionism, researchers have been used a group of methods known as systems biology, a new interdisciplinary eld of study aiming to understand the non-linear interactions among components embedded in biological processes. These interactions can be represented by a mathematical object called graph or network, where the elements are represented by nodes and the interactions by edges that link pair of nodes. The networks can be classi- ed according to their topologies: if node degrees follow a Poisson distribution in a given network, i.e. most nodes have approximately the same number of links, this is a random network; if node degrees follow a power-law distribution in a given network, i.e. small number of high-degree nodes and high number of low-degree nodes, this is a scale-free network. Moreover, networks can be classi ed as hierarchical or non-hierarchical. In this study, we analised Escherichia coli and Saccharomyces cerevisiae integrated molecular networks, which have protein-protein interaction, metabolic and transcriptional regulation interactions. By using computational methods, such as MathematicaR , and data collected from public databases, we calculated four topological parameters: the degree distribution P(k), the clustering coe cient C(k), the closeness centrality CC(k) and the betweenness centrality CB(k). P(k) is a function that calculates the total number of nodes with k degree connection and is used to classify the network as random or scale-free. C(k) shows if a network is hierarchical, i.e. if the clusterization coe cient depends on node degree. CC(k) is an indicator of how much a node it is in the lesse way among others some nodes of the network and the CB(k) is a pointer of how a particular node is among several ...(Complete abstract click electronic access below)

Aspectos da geometria neutra

Pós-graduação em Matemática em Rede Nacional - IBILCE

Predicting epidemic outbreak from individual features of the spreaders

Knowing which individuals can be more efficient in spreading a pathogen throughout a determinate environment is a fundamental question in disease control. Indeed, over recent years the spread of epidemic diseases and its relationship with the topology of the involved system have been a recurrent topic in complex network theory, taking into account both network models and real-world data. In this paper we explore possible correlations between the heterogeneous spread of an epidemic disease governed by the susceptible-infected-recovered (SIR) model, and several attributes of the originating vertices, considering Erdos-Renyi (ER), Barabasi-Albert (BA) and random geometric graphs (RGG), as well as a real case study, the US air transportation network, which comprises the 500 busiest airports in the US along with inter-connections. Initially, the heterogeneity of the spreading is achieved by considering the RGG networks, in which we analytically derive an expression for the distribution of the spreading rates among the established contacts, by assuming that such rates decay exponentially with the distance that separates the individuals. Such a distribution is also considered for the ER and BA models, where we observe topological effects on the correlations. In the case of the airport network, the spreading rates are empirically defined, assumed to be directly proportional to the seat availability. Among both the theoretical and real networks considered, we observe a high correlation between the total epidemic prevalence and the degree, as well as the strength and the accessibility of the epidemic sources. For attributes such as the betweenness centrality and the k-shell index, however, the correlation depends on the topology considered.