On the universality of the scaling of fluctuations in traffic on complex networks

We study the scaling of fluctuations with the mean of traffic in complex networks using a model where the arrival and departure of "packets" follow exponential distributions, and the processing capability of nodes is either unlimited or finite. The model presents a wide variety of exponents between 1/2 and 1 for this scaling, revealing their dependence on the few parameters considered, and questioning the existence of universality classes. We also report the experimental scaling of the fluctuations in the Internet for the Abilene backbone network. We found scaling exponents between 0.71 and 0.86 that do not fit with the exponent 1/2 reported in the literature.Comment: 4 pages, 4 figure

Transforming Sustainable Value in the Construction Industry – The role of Social Movements

Projects pursuing the balance of economic, ecological, and social aspects are being increasingly implemented by the construction industry. This shift represents a paradigm change and evidences new values being acknowledged within the sector. Concurrently, construction scholars tend to emphasize the creation, retention and addition of value, focusing mostly on costs and client deliverables. However, less attention is paid to the process of value change, specifically one that focuses on alternative stakeholders, such as Social Movements. We employ Social Movement theory to comprehend how these organizations affect the notion of value and value change in this industry. Their role is accentuated as a source for a value paradigm change in the form of institutional pressures that shape the values of other stakeholders of the construction industry. These pressures elicit a response in the form of a broader incorporation of sustainable practices amongst construction projects, which effectively alters the industry’s notion of value. Additionally, we showcase a theoretical model that describes the pressure channels originated by Social Movements and their process mechanism affecting the construction industry

Commensurate and Non-Commensurate Fractional-Order Discrete Models of an Electric Individual-Wheel Drive on an Autonomous Platform

This paper presents integer and linear time-invariant fractional order (FO) models of a closed-loop electric individual-wheel drive implemented on an autonomous platform. Two discrete-time FO models are tested: non-commensurate and commensurate. A classical model described by the second-order linear difference equation is used as the reference. According to the sum of the squared error criterion (SSE), we compare a two-parameter integer order model with four-parameter non-commensurate and three-parameter commensurate FO descriptions. The computer simulation results are compared with the measured velocity of a real autonomous platform powered by a closed-loop electric individual-wheel drivehe research was supported by the Polish National Science Center in 2013-2015 as a research project (DEC-2012/05/B/ST 6/03647).info:eu-repo/semantics/publishedVersio

Size reduction of complex networks preserving modularity

The ubiquity of modular structure in real-world complex networks is being the focus of attention in many trials to understand the interplay between network topology and functionality. The best approaches to the identification of modular structure are based on the optimization of a quality function known as modularity. However this optimization is a hard task provided that the computational complexity of the problem is in the NP-hard class. Here we propose an exact method for reducing the size of weighted (directed and undirected) complex networks while maintaining invariant its modularity. This size reduction allows the heuristic algorithms that optimize modularity for a better exploration of the modularity landscape. We compare the modularity obtained in several real complex-networks by using the Extremal Optimization algorithm, before and after the size reduction, showing the improvement obtained. We speculate that the proposed analytical size reduction could be extended to an exact coarse graining of the network in the scope of real-space renormalization.Comment: 14 pages, 2 figure

Enhance the Efficiency of Heuristic Algorithm for Maximizing Modularity Q

Modularity Q is an important function for identifying community structure in complex networks. In this paper, we prove that the modularity maximization problem is equivalent to a nonconvex quadratic programming problem. This result provide us a simple way to improve the efficiency of heuristic algorithms for maximizing modularity Q. Many numerical results demonstrate that it is very effective.Comment: 9 pages, 3 figure