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Random Networks (random + network)

Distribution by Scientific Domains

Engineering	42%

Selected Abstracts

Complex networks: two ways to be robust?

ECOLOGY LETTERS, Issue 6 2002
Carlos J. Melián
Abstract Recent studies of biological networks have focused on the distribution of the number of links per node. However, the connectivity distribution does not uncover all the complexity of their topology. Here, we analyse the relation between the connectivity of a species and the average connectivity of its nearest neighbours in three of the most resolved community food webs. We compare the pattern arising with the one recently reported for protein networks and for a simple null model of a random network. Whereas two highly connected nodes are unlikely to be connected between each other in protein networks, the reverse happens in food webs. We discuss this difference in organization in relation to the robustness of biological networks to different types of perturbation. [source]

Carbon Nanotube/Hexa- peri -hexabenzocoronene Bilayers for Discrimination Between Nonpolar Volatile Organic Compounds of Cancer and Humid Atmospheres

ADVANCED MATERIALS, Issue 38 2010
Yael Zilberman
Cancer detection: The development of a cost-effective, portable and non-invasive diagnostic tool for detecting cancer from exhaled breath requires sensors that discriminate well between polar and nonpolar volatile organic compounds in highly humid atmospheres. Here we show that a chemiresistive bilayer comprised of a dense cap layer of discotic hexa-dodecyl-hexa-peri-hexabenzocoronene derivatives (hereby, HBC-C12) and a random network of carbon nanotubes (RN-CNT) as underlayer layer could fulfill these requirements. [source]

Ab-initio modeling of a-Si and a-Si:H

PHYSICA STATUS SOLIDI (C) - CURRENT TOPICS IN SOLID STATE PHYSICS, Issue 5 2010
Ricardo M. Ribeiro
Abstract The simulation of a-Si is complicated because there is no direct experimental data, as there are for crystals. Our approach to simulate a-Si is to build several relatively small amorphous samples and, later, the properties we wish to calculate are averaged over all samples. We applied the Wooten, Winer and Weaire bond switch to 64 atom cubic supercell of crystalline silicon. This mechanism was used to create 15 samples of continuous random network of silicon. For each supercell, the volume and atomic relaxation were allowed in order to minimize the total energy, using a density functional-pseudopotential code. The radial and angular distributions, the electronic and vibrational density of states, and the Raman spectra were calculated. The radial distribution agrees very well with experimental data. The angular distribution has its maximum at 109.4 degree. The experimental positions and relative intensities of the Transverse Optical (TO) and Transverse Acoustic vibrational modes are well reproduced, with 14 and 25 cm -1 peak deviations, respectively. The shape of the calculated Raman spectra agrees well with experimental data, being the intense TO peak shifted by 50 cm -1. The TO width at half-weight is very well reproduced. Introducing hydrogen in the a-Si samples, decorating all the undercoordinated Si atoms and at bond centres of floating bonds, the hydrogen vibrational frequencies of the relaxed structures agree very well with experimental data. (© 2010 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim) [source]

A Massively Parallel Time-Dependent Least-Time-Path Algorithm for Intelligent Transportation Systems Applications

COMPUTER-AIDED CIVIL AND INFRASTRUCTURE ENGINEERING, Issue 5 2001
Athanasios Ziliaskopoulos
This article is concerned with the problem of computing in parallel time-dependent least-time paths that can be used in real-time intelligent transportation systems applications. A message-passing scheme is presented, and its correctness is proved. The algorithm's computational complexity is shown to be O(|T|2|V|2), an improvement by |V| over the best-known sequential algorithm. The algorithm is implemented, coded, and computationally tested on actual and random networks with promising results. The algorithm is implemented on a CRAY-T3D supercomputer using a Parallel Virtual Machine environment that allows portability to lower-end multiprocessor machines. [source]

An analytic model for the behavior of arbitrary peer-to-peer networks

EUROPEAN TRANSACTIONS ON TELECOMMUNICATIONS, Issue 6 2004
Rüdiger Schollmeier
We present an analytic approach to better understand and design peer-to-peer (P2P) networks, which are becoming increasingly important, as they contribute an amount of traffic often dominating the total traffic in the internet even today. We start from a graph theoretical approach for infinite random networks and enhance that to include the effects of a finite network. Our approach is valid for an arbitrary degree distribution in the network and thus avoids the need for extensive simulation, which would otherwise be required to evaluate the performance of a specific P2P protocol. Our analytic approach can thus be used for improved tailoring of P2P communication as well as to minimize the often excessive signaling traffic. Copyright © 2004 AEI [source]

Disordered lattice networks: general theory and simulations

INTERNATIONAL JOURNAL OF CIRCUIT THEORY AND APPLICATIONS, Issue 6 2005
Stefano GiordanoArticle first published online: 16 NOV 200
Abstract In this work we develop a theory for describing random networks of resistors of the most general topology. This approach generalizes and unifies several statistical theories available in literature. We consider an n-dimensional anisotropic random lattice where each node of the network is connected to a reference node through a given random resistor. This topology includes many structures of great interest both for theoretical and practical applications. For example, the one-dimensional systems correspond to random ladder networks, two-dimensional structures model films deposited on substrates and three-dimensional lattices describe random heterogeneous materials. Moreover, the theory is able to take into account the anisotropic percolation problem for two- and three-dimensional structures. The analytical results allow us to obtain the average behaviour of such networks, i.e. the electrical characterization of the corresponding physical systems. This effective medium theory is developed starting from the properties of the lattice Green's function of the network and from an ad hoc mean field procedure. An accurate analytical study of the related lattice Green's functions has been conducted obtaining many closed form results expressed in terms of elliptic integrals. All the theoretical results have been verified by means of numerical Monte-Carlo simulations obtaining a remarkably good agreement between numerical and theoretical values. Copyright © 2005 John Wiley & Sons, Ltd. [source]

Unified QSAR & network-based computational chemistry approach to antimicrobials.

JOURNAL OF COMPUTATIONAL CHEMISTRY, Issue 1 2010

Abstract In the previous work, we reported a multitarget Quantitative Structure-Activity Relationship (mt-QSAR) model to predict drug activity against different fungal species. This mt-QSAR allowed us to construct a drug,drug multispecies Complex Network (msCN) to investigate drug,drug similarity (González-Díaz and Prado-Prado, J Comput Chem 2008, 29, 656). However, important methodological points remained unclear, such as follows: (1) the accuracy of the methods when applied to other problems; (2) the effect of the distance type used to construct the msCN; (3) how to perform the inverse procedure to study species,species similarity with multidrug resistance CNs (mdrCN); and (4) the implications and necessary steps to perform a substructural Triadic Census Analysis (TCA) of the msCN. To continue the present series with other important problem, we developed here a mt-QSAR model for more than 700 drugs tested in the literature against different parasites (predicting antiparasitic drugs). The data were processed by Linear Discriminate Analysis (LDA) and the model classifies correctly 93.62% (1160 out of 1239 cases) in training. The model validation was carried out by means of external predicting series; the model classified 573 out of 607, that is, 94.4% of cases. Next, we carried out the first comparative study of the topology of six different drug,drug msCNs based on six different distances such as Euclidean, Chebychev, Manhattan, etc. Furthermore, we compared the selected drug,drug msCN and species,species mdsCN with random networks. We also introduced here the inverse methodology to construct species,species msCN based on a mt-QSAR model. Last, we reported the first substructural analysis of drug,drug msCN using Triadic Census Analysis (TCA) algorithm. © 2009 Wiley Periodicals, Inc. J Comput Chem 2010 [source]