12,651 research outputs found
Comparison and validation of community structures in complex networks
The issue of partitioning a network into communities has attracted a great
deal of attention recently. Most authors seem to equate this issue with the one
of finding the maximum value of the modularity, as defined by Newman. Since the
problem formulated this way is NP-hard, most effort has gone into the
construction of search algorithms, and less to the question of other measures
of community structures, similarities between various partitionings and the
validation with respect to external information. Here we concentrate on a class
of computer generated networks and on three well-studied real networks which
constitute a bench-mark for network studies; the karate club, the US college
football teams and a gene network of yeast. We utilize some standard ways of
clustering data (originally not designed for finding community structures in
networks) and show that these classical methods sometimes outperform the newer
ones. We discuss various measures of the strength of the modular structure, and
show by examples features and drawbacks. Further, we compare different
partitions by applying some graph-theoretic concepts of distance, which
indicate that one of the quality measures of the degree of modularity
corresponds quite well with the distance from the true partition. Finally, we
introduce a way to validate the partitionings with respect to external data
when the nodes are classified but the network structure is unknown. This is
here possible since we know everything of the computer generated networks, as
well as the historical answer to how the karate club and the football teams are
partitioned in reality. The partitioning of the gene network is validated by
use of the Gene Ontology database, where we show that a community in general
corresponds to a biological process.Comment: To appear in Physica A; 25 page
Mining Telecommunication Circles via the Call Record and Short Messages
Telecommunication circles are groups of similar customers in telecommunication networks. Mining such circles provides with telecommunication operators great value in developing prospective customers while retaining old ones. However, most of the existing community detecting algorithms utilize mainly the structure of the complex network and ignore the strength of relationship. This paper improves the classic CPM (Clique Percolation Method) algorithm by taking into account both the call record and short messages, and proposes a new algorithms called SR_CPM (Strengthened Relationship CPM). The new algorithm is applied to telecommunication networks and demonstrates superior effectiveness over CPM
Line graphs as social networks
The line graphs are clustered and assortative. They share these topological
features with some social networks. We argue that this similarity reveals the
cliquey character of the social networks. In the model proposed here, a social
network is the line graph of an initial network of families, communities,
interest groups, school classes and small companies. These groups play the role
of nodes, and individuals are represented by links between these nodes. The
picture is supported by the data on the LiveJournal network of about 8 x 10^6
people. In particular, sharp maxima of the observed data of the degree
dependence of the clustering coefficient C(k) are associated with cliques in
the social network.Comment: 11 pages, 4 figure
Visual stress, its treatment with spectral filters, and its relationship to visually induced motion sickness
We review the concept of visual stress and its relation to neurological disease. Visual stress can occur from the observation of images with unnatural spatial structure and an excess of contrast energy at spatial frequencies to which the visual system is generally most sensitive. Visual stress can often be reduced using spectral filters, provided the colour is selected with precision to suit each individual. The use of such filters and their effects on reading speed are reviewed. The filters have been shown to benefit patients with a variety of neurological conditions other than reading difficulty, all associated with an increased risk of seizures. © 2009 Elsevier Ltd
Generation of scale-free networks using a simple preferential rewiring dynamics
We propose a simple dynamical model that generates networks with power-law
degree distributions with the exponent 2 through rewiring only. At each time
step, two nodes, i and j, are randomly selected, and one incoming link to i is
redirected to j with the rewiring probability R, determined only by degrees of
two nodes, k_i and k_j, while giving preference to high-degree nodes. To take
the structure of networks into account, we also consider what types of networks
are of interest, whether links are directed or not, and how we choose a
rewiring link out of all incoming links to i, as a result, specifying 24
different cases of the model. We then observe numerically that networks will
evolve to steady states with power-law degree distributions when parameters of
the model satisfy certain conditions.Comment: 10 pages, 4 figure
Migrating to Cloud-Native Architectures Using Microservices: An Experience Report
Migration to the cloud has been a popular topic in industry and academia in
recent years. Despite many benefits that the cloud presents, such as high
availability and scalability, most of the on-premise application architectures
are not ready to fully exploit the benefits of this environment, and adapting
them to this environment is a non-trivial task. Microservices have appeared
recently as novel architectural styles that are native to the cloud. These
cloud-native architectures can facilitate migrating on-premise architectures to
fully benefit from the cloud environments because non-functional attributes,
like scalability, are inherent in this style. The existing approaches on cloud
migration does not mostly consider cloud-native architectures as their
first-class citizens. As a result, the final product may not meet its primary
drivers for migration. In this paper, we intend to report our experience and
lessons learned in an ongoing project on migrating a monolithic on-premise
software architecture to microservices. We concluded that microservices is not
a one-fit-all solution as it introduces new complexities to the system, and
many factors, such as distribution complexities, should be considered before
adopting this style. However, if adopted in a context that needs high
flexibility in terms of scalability and availability, it can deliver its
promised benefits
Size, shape and flow of powders for use in Selective Laser Sintering (SLS)
6th International Conference on Advanced Research in Virtual and Rapid Prototyping, Leiria, Portugal, 1-5 October 2013This paper investigates the effects of particles size and morphology on flowability of a range of polymeric powders (SLS and non-SLS grades). The effect of additives incorporation, as well as drying or sieving,
on the flowability characteristics of the powders is also analyzed. The results show that the particle morphology has a stronger influence on the flowability than the particle size distribution. Moreover, the incorporation of additives has to be carefully considered in order to have positive effects on the powder flowability
Flow graphs: interweaving dynamics and structure
The behavior of complex systems is determined not only by the topological
organization of their interconnections but also by the dynamical processes
taking place among their constituents. A faithful modeling of the dynamics is
essential because different dynamical processes may be affected very
differently by network topology. A full characterization of such systems thus
requires a formalization that encompasses both aspects simultaneously, rather
than relying only on the topological adjacency matrix. To achieve this, we
introduce the concept of flow graphs, namely weighted networks where dynamical
flows are embedded into the link weights. Flow graphs provide an integrated
representation of the structure and dynamics of the system, which can then be
analyzed with standard tools from network theory. Conversely, a structural
network feature of our choice can also be used as the basis for the
construction of a flow graph that will then encompass a dynamics biased by such
a feature. We illustrate the ideas by focusing on the mathematical properties
of generic linear processes on complex networks that can be represented as
biased random walks and also explore their dual consensus dynamics.Comment: 4 pages, 1 figur
Scale-free networks without growth
In this letter, we proposed an ungrowing scale-free network model, wherein
the total number of nodes is fixed and the evolution of network structure is
driven by a rewiring process only. In spite of the idiographic form of , by
using a two-order master equation, we obtain the analytic solution of degree
distribution in stable state of the network evolution under the condition that
the selection probability in rewiring process only depends on nodes'
degrees. A particular kind of the present networks with linearly correlated
with degree is studied in detail. The analysis and simulations show that the
degree distributions of these networks can varying from the Possion form to the
power-law form with the decrease of a free parameter , indicating the
growth may not be a necessary condition of the self-organizaton of a network in
a scale-free structure.Comment: 4 pages and 3 figure
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