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 $G$, 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 $G$ in rewiring process only depends on nodes' degrees. A particular kind of the present networks with $G$ 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 $\alpha$, 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