181 research outputs found
Self-generated Self-similar Traffic
Self-similarity in the network traffic has been studied from several aspects:
both at the user side and at the network side there are many sources of the
long range dependence. Recently some dynamical origins are also identified: the
TCP adaptive congestion avoidance algorithm itself can produce chaotic and long
range dependent throughput behavior, if the loss rate is very high. In this
paper we show that there is a close connection between the static and dynamic
origins of self-similarity: parallel TCPs can generate the self-similarity
themselves, they can introduce heavily fluctuations into the background traffic
and produce high effective loss rate causing a long range dependent TCP flow,
however, the dropped packet ratio is low.Comment: 8 pages, 12 Postscript figures, accepted in Nonlinear Phenomena in
Complex System
Directed network modules
A search technique locating network modules, i.e., internally densely
connected groups of nodes in directed networks is introduced by extending the
Clique Percolation Method originally proposed for undirected networks. After
giving a suitable definition for directed modules we investigate their
percolation transition in the Erdos-Renyi graph both analytically and
numerically. We also analyse four real-world directed networks, including
Google's own webpages, an email network, a word association graph and the
transcriptional regulatory network of the yeast Saccharomyces cerevisiae. The
obtained directed modules are validated by additional information available for
the nodes. We find that directed modules of real-world graphs inherently
overlap and the investigated networks can be classified into two major groups
in terms of the overlaps between the modules. Accordingly, in the
word-association network and among Google's webpages the overlaps are likely to
contain in-hubs, whereas the modules in the email and transcriptional
regulatory networks tend to overlap via out-hubs.Comment: 21 pages, 10 figures, version 2: added two paragaph
Universal hierarchical behavior of citation networks
Many of the essential features of the evolution of scientific research are imprinted in the structure of citation networks. Connections in these networks imply information about the transfer of knowledge among papers, or, in other words, edges describe the impact of papers on other publications. This inherent meaning of the edges implies that citation networks can exhibit hierarchical features that are typical of networks based on decision making. In this paper, we investigate the hierarchical structure of citation networks consisting of papers in the same field. We find that the majority of the networks follow a universal trend towards a highly hierarchical state, and the various fields display differences only concerning (i)their phase in life (distance from the 'birth' of a field) or (ii)the characteristic time according to which they are approaching the stationary state. We also show by a simple argument that the alterations in the behavior are related to and can be understood by the degree of specialization corresponding to the fields. Our results suggest that during the accumulation of knowledge in a given field, some papers are gradually becoming relatively more influential than most other papers. © 2014 IOP Publishing Ltd and SISSA Medialab srl
Anomalous diffusion in the citation time series of scientific publications
We analyze the citation time-series of manuscripts in three different fields of science; physics, social science and technology. The evolution of the time-series of the yearly number of citations, namely the citation trajectories, diffuse anomalously, their variance scales with time proportional to t (2H ), where H not equal 1/2. We provide detailed analysis of the various factors that lead to the anomalous behavior: non-stationarity, long-ranged correlations and a fat-tailed increment distribution. The papers exhibit a high degree of heterogeneity across the various fields, as the statistics of the highest cited papers is fundamentally different from that of the lower ones. The citation data is shown to be highly correlated and non-stationary; as all the papers except the small percentage of them with high number of citations, die out in time
Preferential attachment of communities: the same principle, but a higher level
The graph of communities is a network emerging above the level of individual
nodes in the hierarchical organisation of a complex system. In this graph the
nodes correspond to communities (highly interconnected subgraphs, also called
modules or clusters), and the links refer to members shared by two communities.
Our analysis indicates that the development of this modular structure is driven
by preferential attachment, in complete analogy with the growth of the
underlying network of nodes. We study how the links between communities are
born in a growing co-authorship network, and introduce a simple model for the
dynamics of overlapping communities.Comment: 7 pages, 3 figure
A New Method for Computing Topological Pressure
The topological pressure introduced by Ruelle and similar quantities describe
dynamical multifractal properties of dynamical systems. These are important
characteristics of mesoscopic systems in the classical regime. Original
definition of these quantities are based on the symbolic description of the
dynamics. It is hard or impossible to find symbolic description and generating
partition to a general dynamical system, therefore these quantities are often
not accessible for further studies. Here we present a new method by which the
symbolic description can be omitted. We apply the method for a mixing and an
intermittent system.Comment: 8 pages LaTeX with revtex.sty, the 4 postscript figures are included
using psfig.tex to appear in PR
Evaluation of vaccine-induced maternal immunity against classical swine fever
The vaccine-induced maternal immunity against classical swine fever (CSF) was investigated in this study. Eight sows were vaccinated with the Chinese strain of classical swine fever virus (CSFV). The length of time between vaccination and farrowing was 167-217 days. Milk samples from the front, middle and back udder sections and blood samples were taken from the sows on days 3 and 14 after farrowing. Blood samples were obtained from the piglets at the age of 3, 6 and 10 weeks. The antibody level of the milk was examined by ELISA, and that of blood samples by the virus neutralization (VN) test as well. In all 3-week-old piglets and in 80% of the 6-week-old animals the neutralizing antibody level reached the titre of 1:40. In none of the 10-week-old piglets did the titre exceed the value of 1:20, but in about 25% of the piglets it reached 1:20; the half of these piglets came from two litters. In none of the piglets did the antibody level reach the negative threshold in the ELISA test during the study. No significant differences were found between the udder sections in milk antibody level by ELISA
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