62 research outputs found
The worldwide air transportation network: Anomalous centrality, community structure, and cities' global roles
We analyze the global structure of the world-wide air transportation network,
a critical infrastructure with an enormous impact on local, national, and
international economies. We find that the world-wide air transportation network
is a scale-free small-world network. In contrast to the prediction of
scale-free network models, however, we find that the most connected cities are
not necessarily the most central, resulting in anomalous values of the
centrality. We demonstrate that these anomalies arise because of the
multi-community structure of the network. We identify the communities in the
air transportation network and show that the community structure cannot be
explained solely based on geographical constraints, and that geo-political
considerations have to be taken into account. We identify each city's global
role based on its pattern of inter- and intra-community connections, which
enables us to obtain scale-specific representations of the network.Comment: Revised versio
Maps of random walks on complex networks reveal community structure
To comprehend the multipartite organization of large-scale biological and
social systems, we introduce a new information theoretic approach that reveals
community structure in weighted and directed networks. The method decomposes a
network into modules by optimally compressing a description of information
flows on the network. The result is a map that both simplifies and highlights
the regularities in the structure and their relationships. We illustrate the
method by making a map of scientific communication as captured in the citation
patterns of more than 6000 journals. We discover a multicentric organization
with fields that vary dramatically in size and degree of integration into the
network of science. Along the backbone of the network -- including physics,
chemistry, molecular biology, and medicine -- information flows
bidirectionally, but the map reveals a directional pattern of citation from the
applied fields to the basic sciences.Comment: 7 pages and 4 figures plus supporting material. For associated source
code, see http://www.tp.umu.se/~rosvall
Modularity and community structure in networks
Many networks of interest in the sciences, including a variety of social and
biological networks, are found to divide naturally into communities or modules.
The problem of detecting and characterizing this community structure has
attracted considerable recent attention. One of the most sensitive detection
methods is optimization of the quality function known as "modularity" over the
possible divisions of a network, but direct application of this method using,
for instance, simulated annealing is computationally costly. Here we show that
the modularity can be reformulated in terms of the eigenvectors of a new
characteristic matrix for the network, which we call the modularity matrix, and
that this reformulation leads to a spectral algorithm for community detection
that returns results of better quality than competing methods in noticeably
shorter running times. We demonstrate the algorithm with applications to
several network data sets.Comment: 7 pages, 3 figure
Resolution limit in community detection
Detecting community structure is fundamental to clarify the link between
structure and function in complex networks and is used for practical
applications in many disciplines. A successful method relies on the
optimization of a quantity called modularity [Newman and Girvan, Phys. Rev. E
69, 026113 (2004)], which is a quality index of a partition of a network into
communities. We find that modularity optimization may fail to identify modules
smaller than a scale which depends on the total number L of links of the
network and on the degree of interconnectedness of the modules, even in cases
where modules are unambiguously defined. The probability that a module conceals
well-defined substructures is the highest if the number of links internal to
the module is of the order of \sqrt{2L} or smaller. We discuss the practical
consequences of this result by analyzing partitions obtained through modularity
optimization in artificial and real networks.Comment: 8 pages, 3 figures. Clarification of definition of community in
Section II + minor revision
Influencia de un sistema informático de gestión documental en la Compañía de Bomberos Los Olivos Nº 161
La presente investigación comprendió el desarrollo, implementación y evaluación de un
sistema de gestión documental en el área de Administración de la Compañía de Bomberos
Voluntarios “Los Olivos N° 161”, basada en partes de la administración de los documentos
como los formularios de emergencia, ficha de paciente, ficha de emergencia, ficha de
ocurrencia y reportes, con la finalidad de determinar la influencia de un sistema
informático en a gestión documental del área, específicamente en las características
principales de este proceso como son la disponibilidad de datos y la generación de
reportes, la cual se orientó a evaluar el tiempo promedio de registro de partes generales de
emergencia, tiempo promedio de búsqueda de partes generales de emergencia del personal
y el tiempo promedio en la generación de reporte respectivamente.
El sistema informático se desarrolló con la metodología RUP que está establecida y
desarrollada en la investigación, como un estándar normal para el análisis y desarrollo de
software, así como el uso de la herramienta de desarrollo Sencha Extjs JavaScript y el
gestor de base de datos SQL Server R2.
La metodología que se usó para la investigación fue cuantitativa deductiva y como tipo de
estudio se utilizó el tipo experimental, con un diseño de investigación cuasi - experimental
que consta de un grupo control y un grupo experimental; para ello se estableció una
población de 224 partes generales de emergencia, el grupo de control fue evaluado del 01
al 30 de Septiembre de 2012 y el grupo experimental fue del 01 al 30 de Septiembre de
2012. Para la prueba de hipótesis se utilizó la prueba T - Student debido a que la población
era pequeña con presencia de una distribución normal.
Finalmente, en la investigación se obtuvo como resultado el uso del sistema de gestión
documentaría en el área de Administración de la Compañía de Bomberos Voluntarios “Los
Olivos N° 161”, que logró disminuir el tiempo promedio de registro en un 65,50%,
equivalente a una reducción de 246 segundos menos en promedio al planteado
inicialmente, también se logro disminuir el tiempo promedio de búsqueda en un 88.27%,
equivalente a una reducción de 117 segundos menos en promedio a lo planteado
inicialmente, asimismo se logró disminuir el tiempo de generación de reportes en un
99.77%, que equivalen a una reducción de 11397segundos en promedio.
Se concluyó que el uso de un sistema informático de gestión documental mejoró los
procesos de agestión de documentos en el área de Administración de la Compañía de
Bomberos Los Olivos N° 161
Networks of strong ties
Social networks transmitting covert or sensitive information cannot use all
ties for this purpose. Rather, they can only use a subset of ties that are
strong enough to be ``trusted''. In this paper we consider transitivity as
evidence of strong ties, requiring that each tie can only be used if the
individuals on either end also share at least one other contact in common. We
examine the effect of removing all non-transitive ties in two real social
network data sets. We observe that although some individuals become
disconnected, a giant connected component remains, with an average shortest
path only slightly longer than that of the original network. We also evaluate
the cost of forming transitive ties by deriving the conditions for the
emergence and the size of the giant component in a random graph composed
entirely of closed triads and the equivalent Erdos-Renyi random graph.Comment: 10 pages, 7 figure
Extracting the hierarchical organization of complex systems
Extracting understanding from the growing ``sea'' of biological and
socio-economic data is one of the most pressing scientific challenges facing
us. Here, we introduce and validate an unsupervised method that is able to
accurately extract the hierarchical organization of complex biological, social,
and technological networks. We define an ensemble of hierarchically nested
random graphs, which we use to validate the method. We then apply our method to
real-world networks, including the air-transportation network, an electronic
circuit, an email exchange network, and metabolic networks. We find that our
method enables us to obtain an accurate multi-scale descriptions of a complex
system.Comment: Figures in screen resolution. Version with full resolution figures
available at
http://amaral.chem-eng.northwestern.edu/Publications/Papers/sales-pardo-2007.pd
Modularity map of the network of human cell differentiation
Cell differentiation in multicellular organisms is a complex process whose
mechanism can be understood by a reductionist approach, in which the individual
processes that control the generation of different cell types are identified.
Alternatively, a large scale approach in search of different organizational
features of the growth stages promises to reveal its modular global structure
with the goal of discovering previously unknown relations between cell types.
Here we sort and analyze a large set of scattered data to construct the network
of human cell differentiation (NHCD) based on cell types (nodes) and
differentiation steps (links) from the fertilized egg to a crying baby. We
discover a dynamical law of critical branching, which reveals a fractal
regularity in the modular organization of the network, and allows us to observe
the network at different scales. The emerging picture clearly identifies
clusters of cell types following a hierarchical organization, ranging from
sub-modules to super-modules of specialized tissues and organs on varying
scales. This discovery will allow one to treat the development of a particular
cell function in the context of the complex network of human development as a
whole. Our results point to an integrated large-scale view of the network of
cell types systematically revealing ties between previously unrelated domains
in organ functions.Comment: 32 pages, 7 figure
Traffic-driven Epidemic Spreading in Finite-size Scale-Free Networks
The study of complex networks sheds light on the relation between the
structure and function of complex systems. One remarkable result is the absence
of an epidemic threshold in infinite-size scale-free networks, which implies
that any infection will perpetually propagate regardless of the spreading rate.
The vast majority of current theoretical approaches assumes that infections are
transmitted as a reaction process from nodes to all neighbors. Here we adopt a
different perspective and show that the epidemic incidence is shaped by traffic
flow conditions. Specifically, we consider the scenario in which epidemic
pathways are defined and driven by flows. Through extensive numerical
simulations and theoretical predictions, it is shown that the value of the
epidemic threshold in scale-free networks depends directly on flow conditions,
in particular on the first and second moments of the betweenness distribution
given a routing protocol. We consider the scenarios in which the delivery
capability of the nodes is bounded or unbounded. In both cases, the threshold
values depend on the traffic and decrease as flow increases. Bounded delivery
provokes the emergence of congestion, slowing down the spreading of the disease
and setting a limit for the epidemic incidence. Our results provide a general
conceptual framework to understand spreading processes on complex networks.Comment: Final version to be published in Proceedings of the National Academy
of Sciences US
Scaling and correlations in three bus-transport networks of China
We report the statistical properties of three bus-transport networks (BTN) in
three different cities of China. These networks are composed of a set of bus
lines and stations serviced by these. Network properties, including the degree
distribution, clustering and average path length are studied in different
definitions of network topology. We explore scaling laws and correlations that
may govern intrinsic features of such networks. Besides, we create a weighted
network representation for BTN with lines mapped to nodes and number of common
stations to weights between lines. In such a representation, the distributions
of degree, strength and weight are investigated. A linear behavior between
strength and degree s(k) ~ k is also observed.Comment: 9 pages, 6 figures and 2 tables. Slight difference from the published
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