Multifractal analysis of complex networks
International Nuclear Information System (INIS)
Wang Dan-Ling; Yu Zu-Guo; Anh V
2012-01-01
Complex networks have recently attracted much attention in diverse areas of science and technology. Many networks such as the WWW and biological networks are known to display spatial heterogeneity which can be characterized by their fractal dimensions. Multifractal analysis is a useful way to systematically describe the spatial heterogeneity of both theoretical and experimental fractal patterns. In this paper, we introduce a new box-covering algorithm for multifractal analysis of complex networks. This algorithm is used to calculate the generalized fractal dimensions D q of some theoretical networks, namely scale-free networks, small world networks, and random networks, and one kind of real network, namely protein—protein interaction networks of different species. Our numerical results indicate the existence of multifractality in scale-free networks and protein—protein interaction networks, while the multifractal behavior is not clear-cut for small world networks and random networks. The possible variation of D q due to changes in the parameters of the theoretical network models is also discussed. (general)
Fractal and multifractal analyses of bipartite networks
Liu, Jin-Long; Wang, Jian; Yu, Zu-Guo; Xie, Xian-Hua
2017-03-01
Bipartite networks have attracted considerable interest in various fields. Fractality and multifractality of unipartite (classical) networks have been studied in recent years, but there is no work to study these properties of bipartite networks. In this paper, we try to unfold the self-similarity structure of bipartite networks by performing the fractal and multifractal analyses for a variety of real-world bipartite network data sets and models. First, we find the fractality in some bipartite networks, including the CiteULike, Netflix, MovieLens (ml-20m), Delicious data sets and (u, v)-flower model. Meanwhile, we observe the shifted power-law or exponential behavior in other several networks. We then focus on the multifractal properties of bipartite networks. Our results indicate that the multifractality exists in those bipartite networks possessing fractality. To capture the inherent attribute of bipartite network with two types different nodes, we give the different weights for the nodes of different classes, and show the existence of multifractality in these node-weighted bipartite networks. In addition, for the data sets with ratings, we modify the two existing algorithms for fractal and multifractal analyses of edge-weighted unipartite networks to study the self-similarity of the corresponding edge-weighted bipartite networks. The results show that our modified algorithms are feasible and can effectively uncover the self-similarity structure of these edge-weighted bipartite networks and their corresponding node-weighted versions.
International Nuclear Information System (INIS)
Amritkar, R.E.; Gupte, N.
1988-09-01
We review the framework set up for the multifractal analysis of self-similar sets. This framework provides a way of extracting the singular structure of the sets analysed and has proven to be useful in a wide variety of physical contexts. We discuss some of the diverse applications of the framework. The framework has also provided the basis for significant advances in the analysis of dynamical systems. We review various developments based on the multifractal framework. These include the thermodynamic formalism, the inverse problem and the framework required for partially self-similar sets. We discuss the consequences of these developments for the analysis of attractors of systems on the border-line of chaos and give an outline of the developing field of the analysis of chaotic attractors. A brief account of other developments like the effect of fluctuations and the renormalization group analysis of multifractals is also provided. (author). 111 refs, 9 figs, 2 tabs
Variability of multifractal parameters in an urban precipitation monitoring network
Licznar, Paweł; De Michele, Carlo; Dżugaj, Dagmara; Niesobska, Maria
2014-05-01
Precipitation especially over urban areas is considered a highly non-linear process, with wide variability over a broad range of temporal and spatial scales. Despite obvious limitations of rainfall gauges location at urban sites, rainfall monitoring by gauge networks is a standard solution of urban hydrology. Often urban precipitation gauge networks are formed by modern electronic gauges and connected to control units of centralized urban drainage systems. Precipitation data, recorded online through these gauge networks, are used in so called Real-Time-Control (RTC) systems for the development of optimal strategies of urban drainage outflows management. As a matter of fact, the operation of RTC systems is motivated mainly by the urge of reducing the severity of urban floods and combined sewerage overflows, but at the same time, it creates new valuable precipitation data sources. The variability of precipitation process could be achieved by investigating multifractal behavior displayed by the temporal structure of precipitation data. There are multiply scientific communications concerning multifractal properties of point-rainfall data from different worldwide locations. However, very little is known about the close variability of multifractal parameters among closely located gauges, at the distances of single kilometers. Having this in mind, here we assess the variability of multifractal parameters among gauges of the urban precipitation monitoring network in Warsaw, Poland. We base our analysis on the set of 1-minute rainfall time series recorded in the period 2008-2011 by 25 electronic weighing type gauges deployed around the city by the Municipal Water Supply and Sewerage Company in Warsaw as a part of local RTC system. The presence of scale invariance and multifractal properties in the precipitation process was investigated with spectral analysis, functional box counting method and studying the probability distributions and statistical moments of the rainfall
High values of disorder-generated multifractals and logarithmically correlated processes
International Nuclear Information System (INIS)
Fyodorov, Yan V.; Giraud, Olivier
2015-01-01
In the introductory section of the article we give a brief account of recent insights into statistics of high and extreme values of disorder-generated multifractals following a recent work by the first author with P. Le Doussal and A. Rosso (FLR) employing a close relation between multifractality and logarithmically correlated random fields. We then substantiate some aspects of the FLR approach analytically for multifractal eigenvectors in the Ruijsenaars–Schneider ensemble (RSE) of random matrices introduced by E. Bogomolny and the second author by providing an ab initio calculation that reveals hidden logarithmic correlations at the background of the disorder-generated multifractality. In the rest we investigate numerically a few representative models of that class, including the study of the highest component of multifractal eigenvectors in the Ruijsenaars–Schneider ensemble
Directory of Open Access Journals (Sweden)
Guillaume Attuel
2018-03-01
Full Text Available Atrial fibrillation (AF is a cardiac arrhythmia characterized by rapid and irregular atrial electrical activity with a high clinical impact on stroke incidence. Best available therapeutic strategies combine pharmacological and surgical means. But when successful, they do not always prevent long-term relapses. Initial success becomes all the more tricky to achieve as the arrhythmia maintains itself and the pathology evolves into sustained or chronic AF. This raises the open crucial issue of deciphering the mechanisms that govern the onset of AF as well as its perpetuation. In this study, we develop a wavelet-based multi-scale strategy to analyze the electrical activity of human hearts recorded by catheter electrodes, positioned in the coronary sinus (CS, during episodes of AF. We compute the so-called multifractal spectra using two variants of the wavelet transform modulus maxima method, the moment (partition function method and the magnitude cumulant method. Application of these methods to long time series recorded in a patient with chronic AF provides quantitative evidence of the multifractal intermittent nature of the electric energy of passing cardiac impulses at low frequencies, i.e., for times (≳0.5 s longer than the mean interbeat (≃ 10−1 s. We also report the results of a two-point magnitude correlation analysis which infers the absence of a multiplicative time-scale structure underlying multifractal scaling. The electric energy dynamics looks like a “multifractal white noise” with quadratic (log-normal multifractal spectra. These observations challenge concepts of functional reentrant circuits in mechanistic theories of AF, still leaving open the role of the autonomic nervous system (ANS. A transition is indeed observed in the computed multifractal spectra which group according to two distinct areas, consistently with the anatomical substrate binding to the CS, namely the left atrial posterior wall, and the ligament of Marshall
Attuel, Guillaume; Gerasimova-Chechkina, Evgeniya; Argoul, Francoise; Yahia, Hussein; Arneodo, Alain
2018-01-01
Atrial fibrillation (AF) is a cardiac arrhythmia characterized by rapid and irregular atrial electrical activity with a high clinical impact on stroke incidence. Best available therapeutic strategies combine pharmacological and surgical means. But when successful, they do not always prevent long-term relapses. Initial success becomes all the more tricky to achieve as the arrhythmia maintains itself and the pathology evolves into sustained or chronic AF. This raises the open crucial issue of deciphering the mechanisms that govern the onset of AF as well as its perpetuation. In this study, we develop a wavelet-based multi-scale strategy to analyze the electrical activity of human hearts recorded by catheter electrodes, positioned in the coronary sinus (CS), during episodes of AF. We compute the so-called multifractal spectra using two variants of the wavelet transform modulus maxima method, the moment (partition function) method and the magnitude cumulant method. Application of these methods to long time series recorded in a patient with chronic AF provides quantitative evidence of the multifractal intermittent nature of the electric energy of passing cardiac impulses at low frequencies, i.e., for times (≳0.5 s) longer than the mean interbeat (≃ 10−1 s). We also report the results of a two-point magnitude correlation analysis which infers the absence of a multiplicative time-scale structure underlying multifractal scaling. The electric energy dynamics looks like a “multifractal white noise” with quadratic (log-normal) multifractal spectra. These observations challenge concepts of functional reentrant circuits in mechanistic theories of AF, still leaving open the role of the autonomic nervous system (ANS). A transition is indeed observed in the computed multifractal spectra which group according to two distinct areas, consistently with the anatomical substrate binding to the CS, namely the left atrial posterior wall, and the ligament of Marshall which is
Zou, Hai-Long; Yu, Zu-Guo; Anh, Vo; Ma, Yuan-Lin
2018-05-01
In recent years, researchers have proposed several methods to transform time series (such as those of fractional Brownian motion) into complex networks. In this paper, we construct horizontal visibility networks (HVNs) based on the -stable Lévy motion. We aim to study the relations of multifractal and Laplacian spectrum of transformed networks on the parameters and of the -stable Lévy motion. First, we employ the sandbox algorithm to compute the mass exponents and multifractal spectrum to investigate the multifractality of these HVNs. Then we perform least squares fits to find possible relations of the average fractal dimension , the average information dimension and the average correlation dimension against using several methods of model selection. We also investigate possible dependence relations of eigenvalues and energy on , calculated from the Laplacian and normalized Laplacian operators of the constructed HVNs. All of these constructions and estimates will help us to evaluate the validity and usefulness of the mappings between time series and networks, especially between time series of -stable Lévy motions and HVNs.
Schertzer, D. J. M.; Tchiguirinskaia, I.
2016-12-01
Multifractal fields, whose definition is rather independent of their domain dimension, have opened a new approach of geophysics enabling to explore its spatial extension that is of prime importance as underlined by the expression "spatial chaos". However multifractals have been until recently restricted to be scalar valued, i.e. to one-dimensional codomains. This has prevented to deal with the key question of complex component interactions and their non trivial symmetries. We first emphasize that the Lie algebra of stochastic generators of cascade processes enables us to generalize multifractals to arbitrarily large codomains, e.g. flows of vector fields on large dimensional manifolds. In particular, we have recently investigated the neat example of stable Levy generators on Clifford algebra that have a number of seductive properties, e.g. universal statistical and robust algebra properties, both defining the basic symmetries of the corresponding fields (Schertzer and Tchiguirinskaia, 2015). These properties provide a convenient multifractal framework to study both the symmetries of the fields and how they stochastically break the symmetries of the underlying equations due to boundary conditions, large scale rotations and forcings. These developments should help us to answer to challenging questions such as the climatology of (exo-) planets based on first principles (Pierrehumbert, 2013), to fully address the question of the limitations of quasi- geostrophic turbulence (Schertzer et al., 2012) and to explore the peculiar phenomenology of turbulent dynamics of the atmosphere or oceans that is neither two- or three-dimensional. Pierrehumbert, R.T., 2013. Strange news from other stars. Nature Geoscience, 6(2), pp.8183. Schertzer, D. et al., 2012. Quasi-geostrophic turbulence and generalized scale invariance, a theoretical reply. Atmos. Chem. Phys., 12, pp.327336. Schertzer, D. & Tchiguirinskaia, I., 2015. Multifractal vector fields and stochastic Clifford algebra
Next Generation Social Networks
DEFF Research Database (Denmark)
Sørensen, Lene Tolstrup; Skouby, Knud Erik
2008-01-01
different online networks for communities of people who share interests or individuals who presents themselves through user produced content is what makes up the social networking of today. The purpose of this paper is to discuss perceived user requirements to the next generation social networks. The paper...
NEW SUNS IN THE COSMOS. III. MULTIFRACTAL SIGNATURE ANALYSIS
Energy Technology Data Exchange (ETDEWEB)
Freitas, D. B. de; Nepomuceno, M. M. F.; Junior, P. R. V. de Moraes; Chagas, M. L. Das; Bravo, J. P.; Costa, A. D.; Martins, B. L. Canto; Medeiros, J. R. De [Departamento de Física, Universidade Federal do Rio Grande do Norte, 59072-970 Natal, RN (Brazil); Lopes, C. E. F. [SUPA Wide-Field Astronomy Unit, Institute for Astronomy, School of Physics and Astronomy, University of Edinburgh, Royal Observatory, Blackford Hill, Edinburgh EH9 3HJ (United Kingdom); Leão, I. C. [European Southern Observatory, Karl-Schwarzschild-Str. 2, D-85748 Garching (Germany)
2016-11-01
In the present paper, we investigate the multifractality signatures in hourly time series extracted from the CoRoT spacecraft database. Our analysis is intended to highlight the possibility that astrophysical time series can be members of a particular class of complex and dynamic processes, which require several photometric variability diagnostics to characterize their structural and topological properties. To achieve this goal, we search for contributions due to a nonlinear temporal correlation and effects caused by heavier tails than the Gaussian distribution, using a detrending moving average algorithm for one-dimensional multifractal signals (MFDMA). We observe that the correlation structure is the main source of multifractality, while heavy-tailed distribution plays a minor role in generating the multifractal effects. Our work also reveals that the rotation period of stars is inherently scaled by the degree of multifractality. As a result, analyzing the multifractal degree of the referred series, we uncover an evolution of multifractality from shorter to larger periods.
Multifractal Cross Wavelet Analysis
Jiang, Zhi-Qiang; Gao, Xing-Lu; Zhou, Wei-Xing; Stanley, H. Eugene
Complex systems are composed of mutually interacting components and the output values of these components usually exhibit long-range cross-correlations. Using wavelet analysis, we propose a method of characterizing the joint multifractal nature of these long-range cross correlations, a method we call multifractal cross wavelet analysis (MFXWT). We assess the performance of the MFXWT method by performing extensive numerical experiments on the dual binomial measures with multifractal cross correlations and the bivariate fractional Brownian motions (bFBMs) with monofractal cross correlations. For binomial multifractal measures, we find the empirical joint multifractality of MFXWT to be in approximate agreement with the theoretical formula. For bFBMs, MFXWT may provide spurious multifractality because of the wide spanning range of the multifractal spectrum. We also apply the MFXWT method to stock market indices, and in pairs of index returns and volatilities we find an intriguing joint multifractal behavior. The tests on surrogate series also reveal that the cross correlation behavior, particularly the cross correlation with zero lag, is the main origin of cross multifractality.
Determination of key parameters of vector multifractal vector fields
Schertzer, D. J. M.; Tchiguirinskaia, I.
2017-12-01
For too long time, multifractal analyses and simulations have been restricted to scalar-valued fields (Schertzer and Tchiguirinskaia, 2017a,b). For instance, the wind velocity multifractality has been mostly analysed in terms of scalar structure functions and with the scalar energy flux. This restriction has had the unfortunate consequences that multifractals were applicable to their full extent in geophysics, whereas it has inspired them. Indeed a key question in geophysics is the complexity of the interactions between various fields or they components. Nevertheless, sophisticated methods have been developed to determine the key parameters of scalar valued fields. In this communication, we first present the vector extensions of the universal multifractal analysis techniques to multifractals whose generator belong to a Levy-Clifford algebra (Schertzer and Tchiguirinskaia, 2015). We point out further extensions noting the increased complexity. For instance, the (scalar) index of multifractality becomes a matrice. Schertzer, D. and Tchiguirinskaia, I. (2015) `Multifractal vector fields and stochastic Clifford algebra', Chaos: An Interdisciplinary Journal of Nonlinear Science, 25(12), p. 123127. doi: 10.1063/1.4937364. Schertzer, D. and Tchiguirinskaia, I. (2017) `An Introduction to Multifractals and Scale Symmetry Groups', in Ghanbarian, B. and Hunt, A. (eds) Fractals: Concepts and Applications in Geosciences. CRC Press, p. (in press). Schertzer, D. and Tchiguirinskaia, I. (2017b) `Pandora Box of Multifractals: Barely Open ?', in Tsonis, A. A. (ed.) 30 Years of Nonlinear Dynamics in Geophysics. Berlin: Springer, p. (in press).
Study on multi-fractal fault diagnosis based on EMD fusion in hydraulic engineering
International Nuclear Information System (INIS)
Lu, Shibao; Wang, Jianhua; Xue, Yangang
2016-01-01
Highlights: • The measured shafting vibration data signal of the hydroelectric generating set is acquired through EMD. • The vibration signal waveform is identified and purified with EMD to obtain approximation coefficient of various fault signals. • The multi-fractal spectrum provides the distributed geometrical or probabilistic information of point. • EMD provides the real information for the next subsequent analysis and recognition. - Abstract: The vibration signal analysis of the hydraulic turbine unit aims at extracting the characteristic information of the unit vibration. The effective signal processing and information extraction are the key to state monitoring and fault diagnosis of the hydraulic turbine unit. In this paper, the vibration fault diagnosis model is established, which combines EMD, multi-fractal spectrum and modified BP neural network; the vibration signal waveform is identified and purified with EMD to obtain approximation coefficient of various fault signals; the characteristic vector of the vibration fault is acquired with the multi-fractal spectrum algorithm, which is classified and identified as input vector of BP neural network. The signal characteristics are extracted through the waveform, the diagnosis and identification are carried out in combination of the multi-fractal spectrum to provide a new method for fault diagnosis of the hydraulic turbine unit. After the application test, the results show that the method can improve the intelligence and humanization of diagnosis, enhance the man–machine interaction, and produce satisfactory identification result.
Multifractal Conceptualisation of Hydro-Meteorological Extremes
Tchiguirinskaia, I.; Schertzer, D.; Lovejoy, S.
2009-04-01
Hydrology and more generally sciences involved in water resources management, technological or operational developments face a fundamental difficulty: the extreme variability of hydro-meteorological fields. It clearly appears today that this variability is a function of the observation scale and yield hydro-meteorological hazards. Throughout the world, the development of multifractal theory offers new techniques for handling such non-classical variability over wide ranges of time and space scales. The resulting stochastic simulations with a very limited number of parameters well reproduce the long range dependencies and the clustering of rainfall extremes often yielding fat tailed (i.e., an algebraic type) probability distributions. The goal of this work was to investigate the ability of using very short or incomplete data records for reliable statistical predictions of the extremes. In particular we discuss how to evaluate the uncertainty in the empirical or semi-analytical multifractal outcomes. We consider three main aspects of the evaluation, such as the scaling adequacy, the multifractal parameter estimation error and the quantile estimation error. We first use the multiplicative cascade model to generate long series of multifractal data. The simulated samples had to cover the range of the universal multifractal parameters widely available in the scientific literature for the rainfall and river discharges. Using these long multifractal series and their sub-samples, we defined a metric for parameter estimation error. Then using the sets of estimated parameters, we obtained the quantile values for a range of excedance probabilities from 5% to 0.01%. Plotting the error bars on a quantile plot enable an approximation of confidence intervals that would be particularly important for the predictions of multifractal extremes. We finally illustrate the efficiency of such concept on its application to a large database (more than 16000 selected stations over USA and
Multifractal properties of resistor diode percolation.
Stenull, Olaf; Janssen, Hans-Karl
2002-03-01
Focusing on multifractal properties we investigate electric transport on random resistor diode networks at the phase transition between the nonpercolating and the directed percolating phase. Building on first principles such as symmetries and relevance we derive a field theoretic Hamiltonian. Based on this Hamiltonian we determine the multifractal moments of the current distribution that are governed by a family of critical exponents [psi(l)]. We calculate the family [psi(l)] to two-loop order in a diagrammatic perturbation calculation augmented by renormalization group methods.
Multifractals theory and applications
Harte, David
2001-01-01
Although multifractals are rooted in probability, much of the related literature comes from the physics and mathematics arena. Multifractals: Theory and Applications pulls together ideas from both these areas using a language that makes them accessible and useful to statistical scientists. It provides a framework, in particular, for the evaluation of statistical properties of estimates of the Renyi fractal dimensions.The first section provides introductory material and different definitions of a multifractal measure. The author then examines some of the various constructions for describing multifractal measures. Building from the theory of large deviations, he focuses on constructions based on lattice coverings, covering by point-centered spheres, and cascades processes. The final section presents estimators of Renyi dimensions of integer order two and greater and discusses their properties. It also explores various applications of dimension estimation and provides a detailed case study of spatial point patte...
Multifractal regime transition in a modified minority game model
International Nuclear Information System (INIS)
Crepaldi, Antonio F.; Rodrigues Neto, Camilo; Ferreira, Fernando F.; Francisco, Gerson
2009-01-01
The search for more realistic modeling of financial time series reveals several stylized facts of real markets. In this work we focus on the multifractal properties found in price and index signals. Although the usual minority game (MG) models do not exhibit multifractality, we study here one of its variants that does. We show that the nonsynchronous MG models in the nonergodic phase is multifractal and in this sense, together with other stylized facts, constitute a better modeling tool. Using the structure function (SF) approach we detected the stationary and the scaling range of the time series generated by the MG model and, from the linear (non-linear) behavior of the SF we identified the fractal (multifractal) regimes. Finally, using the wavelet transform modulus maxima (WTMM) technique we obtained its multifractal spectrum width for different dynamical regimes.
Alternative measure of multifractal content and its application in finance
International Nuclear Information System (INIS)
Grech, Dariusz
2016-01-01
An alternative method for analysis of multifractal properties of time series is provided. We propose a new kind of measure of multifractality strength which takes into account the behavior of multifractal profile of the generalized Hurst exponent h(q) for all moment orders q and is not limited only to the edge values of moment orders describing the scaling properties of smallest and largest fluctuations of a given signal in multifractal detrended fluctuation analysis (MFDFA). The meaning of this new measure is clarified and its performance is investigated for synthetic multifractal data and also for examples of real signals originating from stock markets. We provide also the interpretation of the alternative method following the scaling law that links together the geometric mean value of properly normalized standard q-fluctuation function F"2(q; τ) in MFDFA and the window length τ in which detrending of a signal is performed. We discuss in this context the influence of multifractal bias on the new measure, i.e., the influence of effects which give similar observed features as multiscaling properties however, are not generated by temporal multiscaling autocorrelation in data. It is shown that the proposed alternative measure is robust in some extend to nonstationarity in data. As a result one may avoid problems with interpretation of multifractal profile h(q) encountered in many real nonstationary signals investigated in the standard way.
Regularities of Multifractal Measures
Indian Academy of Sciences (India)
First, we prove the decomposition theorem for the regularities of multifractal Hausdorff measure and packing measure in R R d . This decomposition theorem enables us to split a set into regular and irregular parts, so that we can analyze each separately, and recombine them without affecting density properties. Next, we ...
Multifractal vector fields and stochastic Clifford algebra.
Schertzer, Daniel; Tchiguirinskaia, Ioulia
2015-12-01
In the mid 1980s, the development of multifractal concepts and techniques was an important breakthrough for complex system analysis and simulation, in particular, in turbulence and hydrology. Multifractals indeed aimed to track and simulate the scaling singularities of the underlying equations instead of relying on numerical, scale truncated simulations or on simplified conceptual models. However, this development has been rather limited to deal with scalar fields, whereas most of the fields of interest are vector-valued or even manifold-valued. We show in this paper that the combination of stable Lévy processes with Clifford algebra is a good candidate to bridge up the present gap between theory and applications. We show that it indeed defines a convenient framework to generate multifractal vector fields, possibly multifractal manifold-valued fields, based on a few fundamental and complementary properties of Lévy processes and Clifford algebra. In particular, the vector structure of these algebra is much more tractable than the manifold structure of symmetry groups while the Lévy stability grants a given statistical universality.
Multifractal vector fields and stochastic Clifford algebra
Energy Technology Data Exchange (ETDEWEB)
Schertzer, Daniel, E-mail: Daniel.Schertzer@enpc.fr; Tchiguirinskaia, Ioulia, E-mail: Ioulia.Tchiguirinskaia@enpc.fr [University Paris-Est, Ecole des Ponts ParisTech, Hydrology Meteorology and Complexity HM& Co, Marne-la-Vallée (France)
2015-12-15
In the mid 1980s, the development of multifractal concepts and techniques was an important breakthrough for complex system analysis and simulation, in particular, in turbulence and hydrology. Multifractals indeed aimed to track and simulate the scaling singularities of the underlying equations instead of relying on numerical, scale truncated simulations or on simplified conceptual models. However, this development has been rather limited to deal with scalar fields, whereas most of the fields of interest are vector-valued or even manifold-valued. We show in this paper that the combination of stable Lévy processes with Clifford algebra is a good candidate to bridge up the present gap between theory and applications. We show that it indeed defines a convenient framework to generate multifractal vector fields, possibly multifractal manifold-valued fields, based on a few fundamental and complementary properties of Lévy processes and Clifford algebra. In particular, the vector structure of these algebra is much more tractable than the manifold structure of symmetry groups while the Lévy stability grants a given statistical universality.
Generative Adversarial Networks: An Overview
Creswell, Antonia; White, Tom; Dumoulin, Vincent; Arulkumaran, Kai; Sengupta, Biswa; Bharath, Anil A.
2018-01-01
Generative adversarial networks (GANs) provide a way to learn deep representations without extensively annotated training data. They achieve this through deriving backpropagation signals through a competitive process involving a pair of networks. The representations that can be learned by GANs may be used in a variety of applications, including image synthesis, semantic image editing, style transfer, image super-resolution and classification. The aim of this review paper is to provide an overview of GANs for the signal processing community, drawing on familiar analogies and concepts where possible. In addition to identifying different methods for training and constructing GANs, we also point to remaining challenges in their theory and application.
Generating random networks and graphs
Coolen, Ton; Roberts, Ekaterina
2017-01-01
This book supports researchers who need to generate random networks, or who are interested in the theoretical study of random graphs. The coverage includes exponential random graphs (where the targeted probability of each network appearing in the ensemble is specified), growth algorithms (i.e. preferential attachment and the stub-joining configuration model), special constructions (e.g. geometric graphs and Watts Strogatz models) and graphs on structured spaces (e.g. multiplex networks). The presentation aims to be a complete starting point, including details of both theory and implementation, as well as discussions of the main strengths and weaknesses of each approach. It includes extensive references for readers wishing to go further. The material is carefully structured to be accessible to researchers from all disciplines while also containing rigorous mathematical analysis (largely based on the techniques of statistical mechanics) to support those wishing to further develop or implement the theory of rand...
International Nuclear Information System (INIS)
Zhang Ang-Hui; Li Xiao-Wen; Su Gui-Feng; Zhang Yi
2015-01-01
We present a multifractal detrended fluctuation analysis (MFDFA) of the time series of return generated by our recently-proposed Ising financial market model with underlying small world topology. The result of the MFDFA shows that there exists obvious multifractal scaling behavior in produced time series. We compare the MFDFA results for original time series with those for shuffled series, and find that its multifractal nature is due to two factors: broadness of probability density function of the series and different correlations in small- and large-scale fluctuations. This may provide new insight to the problem of the origin of multifractality in financial time series. (paper)
Multifractality in Cardiac Dynamics
Ivanov, Plamen Ch.; Rosenblum, Misha; Stanley, H. Eugene; Havlin, Shlomo; Goldberger, Ary
1997-03-01
Wavelet decomposition is used to analyze the fractal scaling properties of heart beat time series. The singularity spectrum D(h) of the variations in the beat-to-beat intervals is obtained from the wavelet transform modulus maxima which contain information on the hierarchical distribution of the singularities in the signal. Multifractal behavior is observed for healthy cardiac dynamics while pathologies are associated with loss of support in the singularity spectrum.
Multifractal modelling and 3D lacunarity analysis
International Nuclear Information System (INIS)
Hanen, Akkari; Imen, Bhouri; Asma, Ben Abdallah; Patrick, Dubois; Hedi, Bedoui Mohamed
2009-01-01
This study presents a comparative evaluation of lacunarity of 3D grey level models with different types of inhomogeneity. A new method based on the 'Relative Differential Box Counting' was developed to estimate the lacunarity features of grey level volumes. To validate our method, we generated a set of 3D grey level multifractal models with random, anisotropic and hierarchical properties. Our method gives a lacunarity measurement correlated with the theoretical one and allows a better model classification compared with a classical approach.
Conception of Next Generation Networks
Directory of Open Access Journals (Sweden)
Slavko Šarić
2004-11-01
tool for the realization ofadditional se1vices and for enabling the control in NGN. Theproblem of JP routers for NGN has also been mentioned, aswell as the importance of the new core generation of optical networks.The conceptual framework of NGN is based today onIP/ATM transport technology, which is at this level of developmentgenerally accepted as the optimal transp011 solution. The problem of addressing caused by the insufficient address spaceof Ipv4 has been stressed and the solution of that problem hasbeen anticipated with the introduction of lpv6 technology,which, due to its complexity and high costs, would be graduallyintroduced by a dual approach into the system.The differentiating elements of NGN in relation to the existingnetworks have been specially pointed out. The modulm;that is, plane nature of the NGN conception in relation to thevertical and hierarchical conception of PSTN has beenstressed, as well as the pdvileges that this open conception offerswhen choosing the equipment of the highest quality by differentmanufacturers. Both existing, voice (TDM and data(NGN (ATM/IP, networks will act parallel in the next yearsuntil new solutions to NGN will have been introduced.
Multifractals embedded in short time series: An unbiased estimation of probability moment
Qiu, Lu; Yang, Tianguang; Yin, Yanhua; Gu, Changgui; Yang, Huijie
2016-12-01
An exact estimation of probability moments is the base for several essential concepts, such as the multifractals, the Tsallis entropy, and the transfer entropy. By means of approximation theory we propose a new method called factorial-moment-based estimation of probability moments. Theoretical prediction and computational results show that it can provide us an unbiased estimation of the probability moments of continuous order. Calculations on probability redistribution model verify that it can extract exactly multifractal behaviors from several hundred recordings. Its powerfulness in monitoring evolution of scaling behaviors is exemplified by two empirical cases, i.e., the gait time series for fast, normal, and slow trials of a healthy volunteer, and the closing price series for Shanghai stock market. By using short time series with several hundred lengths, a comparison with the well-established tools displays significant advantages of its performance over the other methods. The factorial-moment-based estimation can evaluate correctly the scaling behaviors in a scale range about three generations wider than the multifractal detrended fluctuation analysis and the basic estimation. The estimation of partition function given by the wavelet transform modulus maxima has unacceptable fluctuations. Besides the scaling invariance focused in the present paper, the proposed factorial moment of continuous order can find its various uses, such as finding nonextensive behaviors of a complex system and reconstructing the causality relationship network between elements of a complex system.
Next generation satellite communications networks
Garland, P. J.; Osborne, F. J.; Streibl, I.
The paper introduces two potential uses for new space hardware to permit enhanced levels of signal handling and switching in satellite communication service for Canada. One application involves increased private-sector services in the Ku band; the second supports new personal/mobile services by employing higher levels of handling and switching in the Ka band. First-generation satellite regeneration and switching experiments involving the NASA/ACTS spacecraft are described, where the Ka band and switching satellite network problems are emphasized. Second-generation satellite development is outlined based on demand trends for more packet-based switching, low-cost earth stations, and closed user groups. A demonstration mission for new Ka- and Ku-band technologies is proposed, including the payload configuration. The half ANIK E payload is shown to meet the demonstration objectives, and projected to maintain a fully operational payload for at least 10 years.
Multifractal Scaling of Grayscale Patterns: Lacunarity and Correlation Dimension
Roy, A.; Perfect, E.
2012-12-01
While fractal models can characterize self-similarity in binary fields, comprised solely of 0's and 1's, the concept of multifractals is needed to quantify scaling behavior in non-binary grayscale fields made up of fractional values. Multifractals are characterized by a spectrum of non-integer dimensions, Dq (-∞ < q < +∞) instead of a single fractal dimension. The gliding-box algorithm is sometimes employed to estimate these different dimensions. This algorithm is also commonly used for computing another parameter, lacunarity, L, which characterizes the distribution of gaps or spaces in patterns, fractals, multifractals or otherwise, as a function of scale (or box-size, x). In the case of 2-dimensional multifractal fields, L has been shown to be theoretically related to the correlation dimension, D2, by dlog(L)/dlog(x) = D2 - 2. Therefore, it is hypothesized that lacunarity analysis can help in delineating multifractal behavior in grayscale patterns. In testing this hypothesis, a set of 2-dimensional multifractal grayscale patterns was generated with known D2 values, and then analyzed for lacunarity by employing the gliding-box algorithm. The D2 values computed using this analysis gave a 1:1 relationship with the known D2 values, thus empirically validating the theoretical relationship between L and D2. Lacunarity analysis was further used to evaluate the multifractal nature of natural grayscale images in the form of soil thin sections that had been previously classified as multifractals based on the standard box counting method. The results indicated that lacunarity analysis is a more sensitive indicator of multifractal behavior in natural grayscale patterns than the box counting approach. A weighted mean of the log-transformed lacunarity values at different scales was employed for differentiating between grayscale patterns with various degrees of scale dependent clustering attributes. This new measure, which expresses lacunarity as a single number, should
Multifractal resilience and viability
Tchiguirinskaia, I.; Schertzer, D. J. M.
2017-12-01
The term resilience has become extremely fashionable and there had been many attempts to provide operational definition and in fact metrics going beyond a set of more or less ad-hoc indicators. The viability theory (Aubin and Saint-Pierre, 2011) have been used to give a rather precise mathematical definition of resilience (Deffuant and Gilbert, 2011). However, it does not grasp the multiscale nature of resilience that is rather fundamental as particularly stressed by Folke et al (2010). In this communication, we first recall a preliminary attempt (Tchiguirinskaia et al., 2014) to define multifractal resilience with the help of the maximal probable singularity. Then we extend this multifractal approach to the capture basin of the viability, therefore the resilient basin. Aubin, J P, A. Bayen, and P Saint-Pierre (2011). Viability Theory. New Directions. Springer, Berlin,. Deffuant, G. and Gilbert, N. (eds) (2011) Viability and Resilience of Complex Systems. Springer Berlin.Folke, C., S R Carpenter, B Walker, M Sheffer, T Chapin, and J Rockstroem (2010). Resilience thinking: integrating re- silience, adaptability and transformability. Ecology and So- ciety, 14(4):20, Tchiguirinskaia,I., D. Schertzer, , A. Giangola-Murzyn and T. C. Hoang (2014). Multiscale resilience metrics to assess flood. Proceedings of ICCSA 2014, Normandie University, Le Havre, France -.
Measuring efficiency of international crude oil markets: A multifractality approach
Niere, H. M.
2015-01-01
The three major international crude oil markets are treated as complex systems and their multifractal properties are explored. The study covers daily prices of Brent crude, OPEC reference basket and West Texas Intermediate (WTI) crude from January 2, 2003 to January 2, 2014. A multifractal detrended fluctuation analysis (MFDFA) is employed to extract the generalized Hurst exponents in each of the time series. The generalized Hurst exponent is used to measure the degree of multifractality which in turn is used to quantify the efficiency of the three international crude oil markets. To identify whether the source of multifractality is long-range correlations or broad fat-tail distributions, shuffled data and surrogated data corresponding to each of the time series are generated. Shuffled data are obtained by randomizing the order of the price returns data. This will destroy any long-range correlation of the time series. Surrogated data is produced using the Fourier-Detrended Fluctuation Analysis (F-DFA). This is done by randomizing the phases of the price returns data in Fourier space. This will normalize the distribution of the time series. The study found that for the three crude oil markets, there is a strong dependence of the generalized Hurst exponents with respect to the order of fluctuations. This shows that the daily price time series of the markets under study have signs of multifractality. Using the degree of multifractality as a measure of efficiency, the results show that WTI is the most efficient while OPEC is the least efficient market. This implies that OPEC has the highest likelihood to be manipulated among the three markets. This reflects the fact that Brent and WTI is a very competitive market hence, it has a higher level of complexity compared against OPEC, which has a large monopoly power. Comparing with shuffled data and surrogated data, the findings suggest that for all the three crude oil markets, the multifractality is mainly due to long
Multifractal spectra in shear flows
Keefe, L. R.; Deane, Anil E.
1989-01-01
Numerical simulations of three-dimensional homogeneous shear flow and fully developed channel flow, are used to calculate the associated multifractal spectra of the energy dissipation field. Only weak parameterization of the results with the nondimensional shear is found, and this only if the flow has reached its asymptotic development state. Multifractal spectra of these flows coincide with those from experiments only at the range alpha less than 1.
MULTIFRACTAL STRUCTURE OF CENTRAL AND EASTERN EUROPEAN FOREIGN EXCHANGE MARKETS
Directory of Open Access Journals (Sweden)
Cn#259;pun#351;an Rn#259;zvan
2012-07-01
Full Text Available It is well known that empirical data coming from financial markets, like stock market indices, commodities, interest rates, traded volumes and foreign exchange rates have a multifractal structure. Multifractals were introduced in the field of economics to surpass the shortcomings of classical models like the fractional Brownian motion or GARCH processes. In this paper we investigate the multifractal behavior of Central and Eastern European foreign exchange rates, namely the Czech koruna, Croatian kuna, Hungarian forint, Polish zlot, Romanian leu and Russian rouble with respect to euro from January 13, 2000 to February 29, 2012. The dynamics of exchange rates is of interest for investors and traders, monetary and fiscal authorities, economic agents or policy makers. The exchange rate movements affect the international balance of payments, trade flows, and allocation of the resources in national and international economy. The empirical results from the multifractal detrending fluctuation analysis algorithm show that the six exchange rate series analysed display significant multifractality. Moreover, generating shuffled and surrogate time series, we analyze the sources of multifractality, long-range correlations and heavy-tailed distributions, and we find that this multifractal behavior can be mainly attributed to the latter. Finally, we propose a foreign exchange market inefficiency ranking by considering the multifractality degree as a measure of inefficiency. The regulators, through policy instruments, aim to improve the informational inefficiency of the markets, to reduce the associated risks and to ensure economic stabilization. Evaluation of the degree of information efficiency of foreign exchange markets, for Central and Eastern Europe countries, is important to assess to what extent these countries are prepared for the transition towards fully monetary integration. The weak form efficiency implies that the past exchange rates cannot help to
Introduction to the Multifractal Analysis of Images
Lévy Véhel , Jacques
1998-01-01
International audience; After a brief review of some classical approaches in image segmentation, the basics of multifractal theory and its application to image analysis are presented. Practical methods for multifractal spectrum estimation are discussed and some experimental results are given.
Network Restoration for Next-Generation Communication and Computing Networks
Directory of Open Access Journals (Sweden)
B. S. Awoyemi
2018-01-01
Full Text Available Network failures are undesirable but inevitable occurrences for most modern communication and computing networks. A good network design must be robust enough to handle sudden failures, maintain traffic flow, and restore failed parts of the network within a permissible time frame, at the lowest cost achievable and with as little extra complexity in the network as possible. Emerging next-generation (xG communication and computing networks such as fifth-generation networks, software-defined networks, and internet-of-things networks have promises of fast speeds, impressive data rates, and remarkable reliability. To achieve these promises, these complex and dynamic xG networks must be built with low failure possibilities, high network restoration capacity, and quick failure recovery capabilities. Hence, improved network restoration models have to be developed and incorporated in their design. In this paper, a comprehensive study on network restoration mechanisms that are being developed for addressing network failures in current and emerging xG networks is carried out. Open-ended problems are identified, while invaluable ideas for better adaptation of network restoration to evolving xG communication and computing paradigms are discussed.
Clustering Multiple Sclerosis Subgroups with Multifractal Methods and Self-Organizing Map Algorithm
Karaca, Yeliz; Cattani, Carlo
Magnetic resonance imaging (MRI) is the most sensitive method to detect chronic nervous system diseases such as multiple sclerosis (MS). In this paper, Brownian motion Hölder regularity functions (polynomial, periodic (sine), exponential) for 2D image, such as multifractal methods were applied to MR brain images, aiming to easily identify distressed regions, in MS patients. With these regions, we have proposed an MS classification based on the multifractal method by using the Self-Organizing Map (SOM) algorithm. Thus, we obtained a cluster analysis by identifying pixels from distressed regions in MR images through multifractal methods and by diagnosing subgroups of MS patients through artificial neural networks.
Editorial: Next Generation Access Networks
Ruffini, Marco; Cincotti, Gabriella; Pizzinat, Anna; Vetter, Peter
2015-12-01
Over the past decade we have seen an increasing number of operators deploying Fibre-to-the-home (FTTH) solutions in access networks, in order to provide home users with a much needed network access upgrade, to support higher peak rates, higher sustained rates and a better and more uniform broadband coverage of the territory.
Optical Subsystems for Next Generation Access Networks
DEFF Research Database (Denmark)
Lazaro, J.A; Polo, V.; Schrenk, B.
2011-01-01
Recent optical technologies are providing higher flexibility to next generation access networks: on the one hand, providing progressive FTTx and specifically FTTH deployment, progressively shortening the copper access network; on the other hand, also opening fixed-mobile convergence solutions...... in next generation PON architectures. It is provided an overview of the optical subsystems developed for the implementation of the proposed NG-Access Networks....
Generative adversarial networks for brain lesion detection
Alex, Varghese; Safwan, K. P. Mohammed; Chennamsetty, Sai Saketh; Krishnamurthi, Ganapathy
2017-02-01
Manual segmentation of brain lesions from Magnetic Resonance Images (MRI) is cumbersome and introduces errors due to inter-rater variability. This paper introduces a semi-supervised technique for detection of brain lesion from MRI using Generative Adversarial Networks (GANs). GANs comprises of a Generator network and a Discriminator network which are trained simultaneously with the objective of one bettering the other. The networks were trained using non lesion patches (n=13,000) from 4 different MR sequences. The network was trained on BraTS dataset and patches were extracted from regions excluding tumor region. The Generator network generates data by modeling the underlying probability distribution of the training data, (PData). The Discriminator learns the posterior probability P (Label Data) by classifying training data and generated data as "Real" or "Fake" respectively. The Generator upon learning the joint distribution, produces images/patches such that the performance of the Discriminator on them are random, i.e. P (Label Data = GeneratedData) = 0.5. During testing, the Discriminator assigns posterior probability values close to 0.5 for patches from non lesion regions, while patches centered on lesion arise from a different distribution (PLesion) and hence are assigned lower posterior probability value by the Discriminator. On the test set (n=14), the proposed technique achieves whole tumor dice score of 0.69, sensitivity of 91% and specificity of 59%. Additionally the generator network was capable of generating non lesion patches from various MR sequences.
Multifractal modelling and 3D lacunarity analysis
Energy Technology Data Exchange (ETDEWEB)
Hanen, Akkari, E-mail: bettaieb.hanen@topnet.t [Laboratoire de biophysique, TIM, Faculte de Medecine (Tunisia); Imen, Bhouri, E-mail: bhouri_imen@yahoo.f [Unite de recherche ondelettes et multifractals, Faculte des sciences (Tunisia); Asma, Ben Abdallah, E-mail: asma.babdallah@cristal.rnu.t [Laboratoire de biophysique, TIM, Faculte de Medecine (Tunisia); Patrick, Dubois, E-mail: pdubois@chru-lille.f [INSERM, U 703, Lille (France); Hedi, Bedoui Mohamed, E-mail: medhedi.bedoui@fmm.rnu.t [Laboratoire de biophysique, TIM, Faculte de Medecine (Tunisia)
2009-09-28
This study presents a comparative evaluation of lacunarity of 3D grey level models with different types of inhomogeneity. A new method based on the 'Relative Differential Box Counting' was developed to estimate the lacunarity features of grey level volumes. To validate our method, we generated a set of 3D grey level multifractal models with random, anisotropic and hierarchical properties. Our method gives a lacunarity measurement correlated with the theoretical one and allows a better model classification compared with a classical approach.
Multifractional theories: an unconventional review
Energy Technology Data Exchange (ETDEWEB)
Calcagni, Gianluca [Instituto de Estructura de la Materia, CSIC,Serrano 121, 28006 Madrid (Spain)
2017-03-27
We answer to 72 frequently asked questions about theories of multifractional spacetimes. Apart from reviewing and reorganizing what we already know about such theories, we discuss the physical meaning and consequences of the very recent flow-equation theorem on dimensional flow in quantum gravity, in particular its enormous impact on the multifractional paradigm. We will also get new theoretical results about the construction of multifractional derivatives and the symmetries in the yet-unexplored theory T{sub γ}, the resolution of ambiguities in the calculation of the spectral dimension, the relation between the theory T{sub q} with q-derivatives and the theory T{sub γ} with fractional derivatives, the interpretation of complex dimensions in quantum gravity, the frame choice at the quantum level, the physical interpretation of the propagator in T{sub γ} as an infinite superposition of quasiparticle modes, the relation between multifractional theories and quantum gravity, and the issue of renormalization, arguing that power-counting arguments do not capture the exotic properties of extreme UV regimes of multifractional geometry, where T{sub γ} may indeed be renormalizable. A careful discussion of experimental bounds and new constraints are also presented.
Generating Seismograms with Deep Neural Networks
Krischer, L.; Fichtner, A.
2017-12-01
The recent surge of successful uses of deep neural networks in computer vision, speech recognition, and natural language processing, mainly enabled by the availability of fast GPUs and extremely large data sets, is starting to see many applications across all natural sciences. In seismology these are largely confined to classification and discrimination tasks. In this contribution we explore the use of deep neural networks for another class of problems: so called generative models.Generative modelling is a branch of statistics concerned with generating new observed data samples, usually by drawing from some underlying probability distribution. Samples with specific attributes can be generated by conditioning on input variables. In this work we condition on seismic source (mechanism and location) and receiver (location) parameters to generate multi-component seismograms.The deep neural networks are trained on synthetic data calculated with Instaseis (http://instaseis.net, van Driel et al. (2015)) and waveforms from the global ShakeMovie project (http://global.shakemovie.princeton.edu, Tromp et al. (2010)). The underlying radially symmetric or smoothly three dimensional Earth structures result in comparatively small waveform differences from similar events or at close receivers and the networks learn to interpolate between training data samples.Of particular importance is the chosen misfit functional. Generative adversarial networks (Goodfellow et al. (2014)) implement a system in which two networks compete: the generator network creates samples and the discriminator network distinguishes these from the true training examples. Both are trained in an adversarial fashion until the discriminator can no longer distinguish between generated and real samples. We show how this can be applied to seismograms and in particular how it compares to networks trained with more conventional misfit metrics. Last but not least we attempt to shed some light on the black-box nature of
Weyl and Riemann-Liouville multifractional Ornstein-Uhlenbeck processes
International Nuclear Information System (INIS)
Lim, S C; Teo, L P
2007-01-01
This paper considers two new multifractional stochastic processes, namely the Weyl multifractional Ornstein-Uhlenbeck process and the Riemann-Liouville multifractional Ornstein-Uhlenbeck process. Basic properties of these processes such as locally self-similar property and Hausdorff dimension are studied. The relationship between the multifractional Ornstein-Uhlenbeck processes and the corresponding multifractional Brownian motions is established
Network information provision to potential generators: Appendices
Energy Technology Data Exchange (ETDEWEB)
NONE
2001-07-01
This Code of Practice (CoP) has been prepared to outline the standard of information that Distribution Network Operators (DNOs) should be required to produce in relation to the provision of network maps, schematic diagrams and specific network data. Network information from DNOs may be required by generators (and other customers) in order to assess the potential opportunities available for the connection of new generation plant. Seven Year Statements are published annually by the Transmission Licensees operating in Great Britain, i.e. The National Grid Company, Scottish Power and Scottish Hydro Electric, and contain all the network information relating to each transmission system, e.g. Generation Capacities, System Parameters and Plant Fault Levels. A similar arrangement for DNOs has been outlined in the Electricity Distribution Licence published by Ofgem. Under Condition 25 of the licence, 'The Long Term Development Statement', distribution licence holders are required to make available historic and planned network data. By providing sufficient network information, competition in generation will be improved. At the time of writing, any party interested in assessing distribution network information needs to make contact with the appropriate DNO, identifying the correct department and person. Written applications are then sent to that person, describing the type of network information that is required. Information required from embedded generators by DNOs is specified in detail in both of The Distribution Codes of England and Wales, and Scotland. However, there are no guidelines or details of network information to be provided by DNOs. This Code of Practise is designed to balance this situation and help DNOs, prospective generators and other applicants for information to achieve satisfaction by clarifying expectations. (Author)
Next Generation Reliable Transport Networks
DEFF Research Database (Denmark)
Zhang, Jiang
the wavelength and fiber assignment problem is proposed and implemented for avionic optical transport networks. Simulation results give out resource consumptions and prove the efficiency of the proposed mechanisms. Finally, a Home Environment Service Knowledge Management system is proposed. Through ontology...... technologies, a knowledge base is constructed to represent the whole information of a home environment. By applying the reasoner tool, the proposed system manages to keep the consistency in a home environment and helps all software configure and update procedures across multiple vendors....... of criticality and security, there are certain physical or logical segregation requirements between the avionic systems. Such segregations can be implemented on the proposed avionic networks with different hierarchies. In order to fulfill the segregation requirements, a tailored heuristic approach for solving...
Modeling documents with Generative Adversarial Networks
Glover, John
2016-01-01
This paper describes a method for using Generative Adversarial Networks to learn distributed representations of natural language documents. We propose a model that is based on the recently proposed Energy-Based GAN, but instead uses a Denoising Autoencoder as the discriminator network. Document representations are extracted from the hidden layer of the discriminator and evaluated both quantitatively and qualitatively.
Optimizing the next generation optical access networks
DEFF Research Database (Denmark)
Amaya Fernández, Ferney Orlando; Soto, Ana Cardenas; Tafur Monroy, Idelfonso
2009-01-01
Several issues in the design and optimization of the next generation optical access network (NG-OAN) are presented. The noise, the distortion and the fiber optic nonlinearities are considered to optimize the video distribution link in a passive optical network (PON). A discussion of the effect...
Achieving universal access to next generation networks
DEFF Research Database (Denmark)
Falch, Morten; Henten, Anders
The paper examines investment dimensions of next generation networks in a universal service perspective in a European context. The question is how new network infrastructures for getting access to communication, information and entertainment services in the present and future information society...
Network information provision to potential generators
Energy Technology Data Exchange (ETDEWEB)
Nicholson, G.
2001-07-01
At the time of finalising this report, an Ofgem consultation is underway on the form of Distribution Licence Condition 25, which will state the requirements for Distribution Network Operators to provide and publish data. This report is also relevant to the DTI Ofgem Embedded Generation Working Group (EGWG), which has recently completed its report and recommendations. It is hoped that this document will provide an overview of the status, importance, role and benefits of network information, which can be utilised by Generators, Network Operators and other industry players in framing their responses to this and future consultations. (Authors)
Fractals and multifractals in physics
International Nuclear Information System (INIS)
Arcangelis, L. de.
1987-01-01
We present a general introduction to the world of fractals. The attention is mainly devoted to stress how fractals do indeed appear in the real world and to find quantitative methods for characterizing their properties. The idea of multifractality is also introduced and it is presented in more details within the framework of the percolation problem
Young generation network: facing the future
International Nuclear Information System (INIS)
Berk, R.
1997-01-01
The future of the nuclear industry lies with the young generation. That's why in 1995, ENS supported the creation of the Young Generation Network (YGN). The YGN aims to fulfill the needs and interests of young people working in the nuclear business by organizing special programs with interesting opportunities and activities. (author)
Modeling urbanization patterns with generative adversarial networks
Albert, Adrian; Strano, Emanuele; Kaur, Jasleen; Gonzalez, Marta
2018-01-01
In this study we propose a new method to simulate hyper-realistic urban patterns using Generative Adversarial Networks trained with a global urban land-use inventory. We generated a synthetic urban "universe" that qualitatively reproduces the complex spatial organization observed in global urban patterns, while being able to quantitatively recover certain key high-level urban spatial metrics.
Traffic Management for Next Generation Transport Networks
DEFF Research Database (Denmark)
Yu, Hao
required by the next generation transport network to provide Quality-of-Service (QoS) guaranteed video services. Augmenting network capacity and upgrading network nodes indicate long deployment period, replacement of equipment and thus significant cost to the network service providers. This challenge may...... slacken the steps of some network operators towards providing IPTV services. In this dissertation, the topology-based hierarchical scheduling scheme is proposed to tackle the problem addressed. The scheme simplifies the deployment process by placing an intelligent switch with centralized traffic...... management functions at the edge of the network, scheduling traffic on behalf of the other nodes. The topology-based hierarchical scheduling scheme is able to provide outstanding flow isolation due to its centralized scheduling ability, which is essential for providing IPTV services. In order to reduce...
Fiber to the home: next generation network
Yang, Chengxin; Guo, Baoping
2006-07-01
Next generation networks capable of carrying converged telephone, television (TV), very high-speed internet, and very high-speed bi-directional data services (like video-on-demand (VOD), Game etc.) strategy for Fiber To The Home (FTTH) is presented. The potential market is analyzed. The barriers and some proper strategy are also discussed. Several technical problems like various powering methods, optical fiber cables, and different network architecture are discussed too.
Design Guidelines for New Generation Network Architecture
Harai, Hiroaki; Fujikawa, Kenji; Kafle, Ved P.; Miyazawa, Takaya; Murata, Masayuki; Ohnishi, Masaaki; Ohta, Masataka; Umezawa, Takeshi
Limitations are found in the recent Internet because a lot of functions and protocols are patched to the original suite of layered protocols without considering global optimization. This reveals that end-to-end argument in the original Internet was neither sufficient for the current societal network and nor for a sustainable network of the future. In this position paper, we present design guidelines for a future network, which we call the New Generation Network, which provides the inclusion of diverse human requirements, reliable connection between the real-world and virtual network space, and promotion of social potentiality for human emergence. The guidelines consist of the crystal synthesis, the reality connection, and the sustainable & evolutional guidelines.
Lorentz violations in multifractal spacetimes
Energy Technology Data Exchange (ETDEWEB)
Calcagni, Gianluca [Instituto de Estructura de la Materia, CSIC, Madrid (Spain)
2017-05-15
Using the recent observation of gravitational waves (GW) produced by a black-hole merger, we place a lower bound on the energy above which a multifractal spacetime would display an anomalous geometry and, in particular, violations of Lorentz invariance. In the so-called multifractional theory with q-derivatives, we show that the deformation of dispersion relations is much stronger than in generic quantum-gravity approaches (including loop quantum gravity) and, contrary to the latter, present observations on GWs can place very strong bounds on the characteristic scales at which spacetime deviates from standard Minkowski. The energy at which multifractal effects should become apparent is E{sub *} > 10{sup 14} GeV (thus improving previous bounds by 12 orders of magnitude) when the exponents in the measure are fixed to their central value 1 / 2. We also estimate, for the first time, the effect of logarithmic oscillations in the measure (corresponding to a discrete spacetime structure) and find that they do not change much the bounds obtained in their absence, unless the amplitude of the oscillations is fine tuned. This feature, unavailable in known quantum-gravity scenarios, may help the theory to avoid being ruled out by gamma-ray burst (GRB) observations, for which E{sub *} > 10{sup 17} GeV or greater. (orig.)
Li, Xiaohui; Li, Xiangling; Yuan, Feng; Jowitt, Simon M.; Zhou, Taofa; Yang, Kui; Zhou, Jie; Hu, Xunyu; Li, Yang
2016-09-01
Industrial and agricultural activities can generate heavy metal pollution that can cause a number of negative environmental and health impacts. This means that evaluating heavy metal pollution and identifying the sources of these pollutants, especially in urban or developed areas, is an important first step in mitigating the effects of these contaminating but necessary economic activities. Here, we present the results of a heavy metal (Cu, Pb, Zn, Cd, As, and Hg) soil geochemical survey in Hefei city. We used a multifractal spectral technique to identify and compare the multifractality of heavy metal concentrations of soils within the industrial Daxing and agricultural Yicheng areas. This paper uses three multifractal parameters (Δα, Δf(α), and τ''(1)) to indicate the overall amount of multifractality within the soil geochemical data. The results show all of the elements barring Hg have larger Δα, Δf(α), and τ''(1) values in the Daxing area compared to the Yicheng area. The degree of multifractality suggests that the differing economic activities in Daxing and Yicheng generate very different heavy metal pollution loads. In addition, the industrial Daxing area contains significant Pb and Cd soil contamination, whereas Hg is the main heavy metal present in soils within the Yicheng area, indicating that differing clean-up procedures and approaches to remediating these polluted areas are needed. The results also indicate that multifractal modelling and the associated generation of multifractal parameters can be a useful approach in the evaluation of heavy metal pollution in soils.
BGen: A UML Behavior Network Generator Tool
Huntsberger, Terry; Reder, Leonard J.; Balian, Harry
2010-01-01
BGen software was designed for autogeneration of code based on a graphical representation of a behavior network used for controlling automatic vehicles. A common format used for describing a behavior network, such as that used in the JPL-developed behavior-based control system, CARACaS ["Control Architecture for Robotic Agent Command and Sensing" (NPO-43635), NASA Tech Briefs, Vol. 32, No. 10 (October 2008), page 40] includes a graph with sensory inputs flowing through the behaviors in order to generate the signals for the actuators that drive and steer the vehicle. A computer program to translate Unified Modeling Language (UML) Freeform Implementation Diagrams into a legacy C implementation of Behavior Network has been developed in order to simplify the development of C-code for behavior-based control systems. UML is a popular standard developed by the Object Management Group (OMG) to model software architectures graphically. The C implementation of a Behavior Network is functioning as a decision tree.
NASA's Next Generation Space Geodesy Network
Desai, S. D.; Gross, R. S.; Hilliard, L.; Lemoine, F. G.; Long, J. L.; Ma, C.; McGarry, J. F.; Merkowitz, S. M.; Murphy, D.; Noll, C. E.;
2012-01-01
NASA's Space Geodesy Project (SGP) is developing a prototype core site for a next generation Space Geodetic Network (SGN). Each of the sites in this planned network co-locate current state-of-the-art stations from all four space geodetic observing systems, GNSS, SLR, VLBI, and DORIS, with the goal of achieving modern requirements for the International Terrestrial Reference Frame (ITRF). In particular, the driving ITRF requirements for this network are 1.0 mm in accuracy and 0.1 mm/yr in stability, a factor of 10-20 beyond current capabilities. Development of the prototype core site, located at NASA's Geophysical and Astronomical Observatory at the Goddard Space Flight Center, started in 2011 and will be completed by the end of 2013. In January 2012, two operational GNSS stations, GODS and GOON, were established at the prototype site within 100 m of each other. Both stations are being proposed for inclusion into the IGS network. In addition, work is underway for the inclusion of next generation SLR and VLBI stations along with a modern DORIS station. An automated survey system is being developed to measure inter-technique vectorties, and network design studies are being performed to define the appropriate number and distribution of these next generation space geodetic core sites that are required to achieve the driving ITRF requirements. We present the status of this prototype next generation space geodetic core site, results from the analysis of data from the established geodetic stations, and results from the ongoing network design studies.
Micro-generation network connection (renewables)
Energy Technology Data Exchange (ETDEWEB)
Thornycroft, J.; Russell, T.; Curran, J.
2003-07-01
The drive to reduce emissions of carbon dioxide will result in an increase in the number of small generation units seeking connection to the electric power distribution network. The objectives of this study were to consider connection issues relating to micro-generation from renewables and their integration into the UK distribution network. The document is divided into two sections. The first section describes the present system which includes input from micro-generation, the technical impacts and the financial considerations. The second part discusses technical, financial and governance options for the future. A summary of preferred options and recommendations is given. The study was carried out by the Halcrow Group Ltd under contract to the DTI.
Multifractal Analysis for the Teichmueller Flow
Energy Technology Data Exchange (ETDEWEB)
Meson, Alejandro M., E-mail: meson@iflysib.unlp.edu.ar; Vericat, Fernando, E-mail: vericat@iflysib.unlp.edu.ar [Instituto de Fisica de Liquidos y Sistemas Biologicos (IFLYSIB) CCT-CONICET, La Plata-UNLP and Grupo de Aplicaciones Matematicas y Estadisticas de la Facultad de Ingenieria (GAMEFI) UNLP (Argentina)
2012-03-15
We present a multifractal description for Teichmueller flows. A key ingredient to do this is the Rauzy-Veech-Zorich reduction theory, which allows to treat the problem in the setting of suspension flows over subshifts. To perform the multifractal analysis we implement a thermodynamic formalism for suspension flows over countable alphabet subshifts a bit different from that developed by Barreira and Iommi.
Diffusion and scattering in multifractal clouds
Energy Technology Data Exchange (ETDEWEB)
Lovejoy, S. [McGill Univ., Montreal, Quebec (Canada); Schertzer, D. [Universite Pierre et Marie Curie, Paris (France); Waston, B. [St. Lawrence Univ., Canton, NY (United States)] [and others
1996-04-01
This paper describes investigations of radiative properties of multifractal clouds using two different approaches. In the first, diffusion is considered by examining the scaling properties of one dimensional random walks on media with multifractal diffusivities. The second approach considers the scattering statistics associated with radiative transport.
MULTIFRACTAL ANALYSIS OFTHE DYNAMICS OF TURKISHEXCHANGE RATE
Directory of Open Access Journals (Sweden)
Ezgi Gülbaş
2013-01-01
Full Text Available We perform a comparative study of applicability of the Multifractal DetrendedFluctuation Analysis (MFDFA and the Wavelet Transform Modulus Maxima(WTMM method in properly detecting ofmono- and multifractal character ofdata. After summarizing the theory behind both methods, we apply both methodson USD/TRY currency. The results show thatour data has multifractal nature butnot at high level and multifractality ispoorer if WTMM method is used. We alsoinvestigated whether other Eastern European country currencies, such as RussianRubble and Hungarian Forint have multifractal characters by using MFDFAmethod. Therefore, forecasters have often encountered in trying to predict theseexchange rates with models that do notincorporate any notion of inhomogeneitywill have little predictive power.
Multifractal structures for the Russian stock market
Ikeda, Taro
2018-02-01
In this paper, we apply the multifractal detrended fluctuation analysis (MFDFA) to the Russian stock price returns. To the best of our knowledge, this paper is the first to reveal the multifractal structures for the Russian stock market by financial crises. The contributions of the paper are twofold. (i) Finding the multifractal structures for the Russian stock market. The generalized Hurst exponents estimated become highly-nonlinear to the order of the fluctuation functions. (ii) Computing the multifractality degree according to Zunino et al. (2008). We find that the multifractality degree of the Russian stock market can be categorized within emerging markets, however, the Russian 1998 crisis and the global financial crisis dampen the degree when we consider the order of the polynomial trends in the MFDFA.
Neural network application to diesel generator diagnostics
International Nuclear Information System (INIS)
Logan, K.P.
1990-01-01
Diagnostic problems typically begin with the observation of some system behavior which is recognized as a deviation from the expected. The fundamental underlying process is one involving pattern matching cf observed symptoms to a set of compiled symptoms belonging to a fault-symptom mapping. Pattern recognition is often relied upon for initial fault detection and diagnosis. Parallel distributed processing (PDP) models employing neural network paradigms are known to be good pattern recognition devices. This paper describes the application of neural network processing techniques to the malfunction diagnosis of subsystems within a typical diesel generator configuration. Neural network models employing backpropagation learning were developed to correctly recognize fault conditions from the input diagnostic symptom patterns pertaining to various engine subsystems. The resulting network models proved to be excellent pattern recognizers for malfunction examples within the training set. The motivation for employing network models in lieu of a rule-based expert system, however, is related to the network's potential for generalizing malfunctions outside of the training set, as in the case of noisy or partial symptom patterns
Wavelet network controller for nuclear steam generators
International Nuclear Information System (INIS)
Habibiyan, H; Sayadian, A; Ghafoori-Fard, H
2005-01-01
Poor control of steam generator water level is the main cause of unexpected shutdowns in nuclear power plants. Particularly at low powers, it is a difficult task due to shrink and swell phenomena and flow measurement errors. In addition, the steam generator is a highly complex, nonlinear and time-varying system and its parameters vary with operating conditions. Therefore, it seems that design of a suitable controller is a necessary step to enhance plant availability factor. The purpose of this paper is to design, analyze and evaluate a water level controller for U-tube steam generators using wavelet neural networks. Computer simulations show that the proposed controller improves transient response of steam generator water level and demonstrate its superiority to existing controllers
Embedded generation and network management issues
Energy Technology Data Exchange (ETDEWEB)
NONE
2000-07-01
This report focuses on the characteristics of power generators that are important to accommodation in a distribution system. Part 1 examines the differences between transmission and distribution systems, and issues such as randomness, diversity, predictability, and controllability associated with accommodation in a distribution system. Part 2 concentrates on technical and operational issues relating to embedded generation, and the possible impact of the New Electricity Trading Arrangements. Commercial issues, contractual relationships for network charging and provision of services, and possible ways forward are examined in the last three parts of the report.
Generative Adversarial Networks for Improving Face Classification
Natten, Jonas
2017-01-01
Master's thesis Information- and communication technology IKT590 - University of Agder 2017 Facial recognition can be applied in a wide variety of cases, including entertainment purposes and biometric security. In this thesis we take a look at improving the results of an existing facial recognition approach by utilizing generative adversarial networks to improve the existing dataset. The training data was taken from the LFW dataset[4] and was preprocessed using OpenCV[2] for...
Biology Question Generation from a Semantic Network
Zhang, Lishan
Science instructors need questions for use in exams, homework assignments, class discussions, reviews, and other instructional activities. Textbooks never have enough questions, so instructors must find them from other sources or generate their own questions. In order to supply instructors with biology questions, a semantic network approach was developed for generating open response biology questions. The generated questions were compared to professional authorized questions. To boost students' learning experience, adaptive selection was built on the generated questions. Bayesian Knowledge Tracing was used as embedded assessment of the student's current competence so that a suitable question could be selected based on the student's previous performance. A between-subjects experiment with 42 participants was performed, where half of the participants studied with adaptive selected questions and the rest studied with mal-adaptive order of questions. Both groups significantly improved their test scores, and the participants in adaptive group registered larger learning gains than participants in the control group. To explore the possibility of generating rich instructional feedback for machine-generated questions, a question-paragraph mapping task was identified. Given a set of questions and a list of paragraphs for a textbook, the goal of the task was to map the related paragraphs to each question. An algorithm was developed whose performance was comparable to human annotators. A multiple-choice question with high quality distractors (incorrect answers) can be pedagogically valuable as well as being much easier to grade than open-response questions. Thus, an algorithm was developed to generate good distractors for multiple-choice questions. The machine-generated multiple-choice questions were compared to human-generated questions in terms of three measures: question difficulty, question discrimination and distractor usefulness. By recruiting 200 participants from
Multifractal scaling analysis of autopoisoning reactions over a rough surface
International Nuclear Information System (INIS)
Chaudhari, Ajay; Yan, Ching-Cher Sanders; Lee, S.-L.
2003-01-01
Decay type diffusion-limited reactions (DLR) over a rough surface generated by a random deposition model were performed. To study the effect of the decay profile on the reaction probability distribution (RPD), multifractal scaling analysis has been carried out. The dynamics of these autopoisoning reactions are controlled by the two parameters in the decay function, namely, the initial sticking probability (P ini ) of every site and the decay rate (m). The smaller the decay rate, the narrower is the range of α values in the α-f(α) multifractal spectrum. The results are compared with the earlier work of DLR over a surface of diffusion-limited aggregation (DLA). We also considered here the autopoisoning reactions over a smooth surface for comparing our results, which show clearly how the roughness affects the chemical reactions. The q-τ(q) multifractal curves for the smooth surface are linear whereas those for the rough surface are nonlinear. The range of α values in the case of a rough surface is wider than that of the smooth surface
Multifractal diffusion entropy analysis: Optimal bin width of probability histograms
Jizba, Petr; Korbel, Jan
2014-11-01
In the framework of Multifractal Diffusion Entropy Analysis we propose a method for choosing an optimal bin-width in histograms generated from underlying probability distributions of interest. The method presented uses techniques of Rényi’s entropy and the mean squared error analysis to discuss the conditions under which the error in the multifractal spectrum estimation is minimal. We illustrate the utility of our approach by focusing on a scaling behavior of financial time series. In particular, we analyze the S&P500 stock index as sampled at a daily rate in the time period 1950-2013. In order to demonstrate a strength of the method proposed we compare the multifractal δ-spectrum for various bin-widths and show the robustness of the method, especially for large values of q. For such values, other methods in use, e.g., those based on moment estimation, tend to fail for heavy-tailed data or data with long correlations. Connection between the δ-spectrum and Rényi’s q parameter is also discussed and elucidated on a simple example of multiscale time series.
Saliency detection by conditional generative adversarial network
Cai, Xiaoxu; Yu, Hui
2018-04-01
Detecting salient objects in images has been a fundamental problem in computer vision. In recent years, deep learning has shown its impressive performance in dealing with many kinds of vision tasks. In this paper, we propose a new method to detect salient objects by using Conditional Generative Adversarial Network (GAN). This type of network not only learns the mapping from RGB images to salient regions, but also learns a loss function for training the mapping. To the best of our knowledge, this is the first time that Conditional GAN has been used in salient object detection. We evaluate our saliency detection method on 2 large publicly available datasets with pixel accurate annotations. The experimental results have shown the significant and consistent improvements over the state-of-the-art method on a challenging dataset, and the testing speed is much faster.
Automatic Generation of Network Protocol Gateways
DEFF Research Database (Denmark)
Bromberg, Yérom-David; Réveillère, Laurent; Lawall, Julia
2009-01-01
for describing protocol behaviors, message structures, and the gateway logic. Z2z includes a compiler that checks essential correctness properties and produces efficient code. We have used z2z to develop a number of gateways, including SIP to RTSP, SLP to UPnP, and SMTP to SMTP via HTTP, involving a range......The emergence of networked devices in the home has made it possible to develop applications that control a variety of household functions. However, current devices communicate via a multitude of incompatible protocols, and thus gateways are needed to translate between them. Gateway construction......, however, requires an intimate knowledge of the relevant protocols and a substantial understanding of low-level network programming, which can be a challenge for many application programmers. This paper presents a generative approach to gateway construction, z2z, based on a domain-specific language...
Multifractal cross-correlations between crude oil and tanker freight rate
Chen, Feier; Miao, Yuqi; Tian, Kang; Ding, Xiaoxu; Li, Tingyi
2017-05-01
Analysis of crude oil price and tanker freight rate volatility attract more attention as the mechanism is not only the basis of industrialization but also a vital role in economics, especially after the year 2008 when financial crisis notably blew the maritime transportation. In this paper, we studied the cross-correlations between the West Texas International crude oil (WTI) and Baltic Exchange Dirty Tanker Index (BDTI) employing the Multifractal Detrended Cross-Correlation Analysis (MF-DCCA). Empirical results show that the degree of short-term cross-correlation is higher than that in the long term and that the strength of multifractality after financial crisis is larger than that before. Moreover, the components of multifractal spectrum are quantified with the finite-size effect taken into consideration and an improved method in terms of constructing the surrogated time series provided. Numerical results show that the multifractality is generated mostly from the nonlinear and the fat-tailed probability distribution (PDF) part. Also, it is apparent that the PDF part changes a lot after the financial crisis. The research is contributory to risk management by providing various instructions for participants in shipping markets. Our main contribution is that we investigated both the multifractal features and the origin of multifractality and provided confirming evidence of multifractality through numerical results while applying quantitative analysis based on MF-DCCA; furthermore, the research is contributory to risk management since it provides instructions in both economic market and stock market simultaneously. However, constructing the surrogated series in order to obtain consistence seems less convincing which requires further discussion and attempts.
Multifractal analysis of visibility graph-based Ito-related connectivity time series.
Czechowski, Zbigniew; Lovallo, Michele; Telesca, Luciano
2016-02-01
In this study, we investigate multifractal properties of connectivity time series resulting from the visibility graph applied to normally distributed time series generated by the Ito equations with multiplicative power-law noise. We show that multifractality of the connectivity time series (i.e., the series of numbers of links outgoing any node) increases with the exponent of the power-law noise. The multifractality of the connectivity time series could be due to the width of connectivity degree distribution that can be related to the exit time of the associated Ito time series. Furthermore, the connectivity time series are characterized by persistence, although the original Ito time series are random; this is due to the procedure of visibility graph that, connecting the values of the time series, generates persistence but destroys most of the nonlinear correlations. Moreover, the visibility graph is sensitive for detecting wide "depressions" in input time series.
Multifractal structure in Latin-American market indices
International Nuclear Information System (INIS)
Zunino, Luciano; Figliola, Alejandra; Tabak, Benjamin M.; Perez, Dario G.; Garavaglia, Mario; Rosso, Osvaldo A.
2009-01-01
We study the multifractal nature of daily price and volatility returns of Latin-American stock markets employing the multifractal detrended fluctuation analysis. Comparing with the results obtained for a developed country (US) we conclude that the multifractality degree is higher for emerging markets. Moreover, we propose a stock market inefficiency ranking by considering the multifractality degree as a measure of inefficiency. Finally, we analyze the sources of multifractality quantifying the contributions of two factors, the long-range correlations of the time series and the broad fat-tail distributions. We find that the multifractal structure of Latin-American market indices can be mainly attributed to the latter.
Unified Model for Generation Complex Networks with Utility Preferential Attachment
International Nuclear Information System (INIS)
Wu Jianjun; Gao Ziyou; Sun Huijun
2006-01-01
In this paper, based on the utility preferential attachment, we propose a new unified model to generate different network topologies such as scale-free, small-world and random networks. Moreover, a new network structure named super scale network is found, which has monopoly characteristic in our simulation experiments. Finally, the characteristics of this new network are given.
Network integration of distributed power generation
Dondi, Peter; Bayoumi, Deia; Haederli, Christoph; Julian, Danny; Suter, Marco
The world-wide move to deregulation of the electricity and other energy markets, concerns about the environment, and advances in renewable and high efficiency technologies has led to major emphasis being placed on the use of small power generation units in a variety of forms. The paper reviews the position of distributed generation (DG, as these small units are called in comparison with central power plants) with respect to the installation and interconnection of such units with the classical grid infrastructure. In particular, the status of technical standards both in Europe and USA, possible ways to improve the interconnection situation, and also the need for decisions that provide a satisfactory position for the network operator (who remains responsible for the grid, its operation, maintenance and investment plans) are addressed.
Joint multifractal analysis based on wavelet leaders
Jiang, Zhi-Qiang; Yang, Yan-Hong; Wang, Gang-Jin; Zhou, Wei-Xing
2017-12-01
Mutually interacting components form complex systems and these components usually have long-range cross-correlated outputs. Using wavelet leaders, we propose a method for characterizing the joint multifractal nature of these long-range cross correlations; we call this method joint multifractal analysis based on wavelet leaders (MF-X-WL). We test the validity of the MF-X-WL method by performing extensive numerical experiments on dual binomial measures with multifractal cross correlations and bivariate fractional Brownian motions (bFBMs) with monofractal cross correlations. Both experiments indicate that MF-X-WL is capable of detecting cross correlations in synthetic data with acceptable estimating errors. We also apply the MF-X-WL method to pairs of series from financial markets (returns and volatilities) and online worlds (online numbers of different genders and different societies) and determine intriguing joint multifractal behavior.
Testing for multifractality of Islamic stock markets
Saâdaoui, Foued
2018-04-01
Studying the power-law scaling of financial time series is a promising area of econophysics, which has often contributed to the understanding of the intricate features of the global markets. In this article, we examine the multifractality of some financial processes and the underlying formation mechanisms in the context of Islamic equity markets. The well-known Multifractal Detrended Fluctuation Analysis (MF-DFA) is used to investigate the self-similar properties of two Dow Jones Islamic Market Indexes (DJIM). The results prove that both indexes exhibit multifractal properties. By discussing the sources of multifractality, we find that they are related to the occurrence of extreme events, long-range dependency of autocorrelations and fat-tailed distribution of returns. These results have several important implications for analysts and decision makers in modeling the dynamics of Islamic markets, thus recommending efficient asset allocation plans to investors dealing with Islamic equity markets.
Cascading Generative Adversarial Networks for Targeted
Hamdi, Abdullah
2018-01-01
Abundance of labelled data played a crucial role in the recent developments in computer vision, but that faces problems like scalability and transferability to the wild. One alternative approach is to utilize the data without labels, i.e. unsupervised learning, in learning valuable information and put it in use to tackle vision problems. Generative Adversarial Networks (GANs) have gained momentum for their ability to model image distributions in unsupervised manner. They learn to emulate the training set and that enables sampling from that domain and using the knowledge learned for useful applications. Several methods proposed enhancing GANs, including regularizing the loss with some feature matching. We seek to push GANs beyond the data in the training and try to explore unseen territory in the image manifold. We first propose a new regularizer for GAN based on K-Nearest Neighbor (K-NN) selective feature matching to a target set Y in high-level feature space, during the adversarial training of GAN on the base set X, and we call this novel model K-GAN. We show that minimizing the added term follows from cross-entropy minimization between the distributions of GAN and set Y. Then, we introduce a cascaded framework for GANs that try to address the task of imagining a new distribution that combines the base set X and target set Y by cascading sampling GANs with translation GANs, and we dub the cascade of such GANs as the Imaginative Adversarial Network (IAN). Several cascades are trained on a collected dataset Zoo-Faces and generated innovative samples are shown, including from K-GAN cascade. We conduct an objective and subjective evaluation for different IAN setups in the addressed task of generating innovative samples and we show the effect of regularizing GAN on different scores. We conclude with some useful applications for these IANs, like multi-domain manifold traversing.
Cascading Generative Adversarial Networks for Targeted
Hamdi, Abdullah
2018-04-09
Abundance of labelled data played a crucial role in the recent developments in computer vision, but that faces problems like scalability and transferability to the wild. One alternative approach is to utilize the data without labels, i.e. unsupervised learning, in learning valuable information and put it in use to tackle vision problems. Generative Adversarial Networks (GANs) have gained momentum for their ability to model image distributions in unsupervised manner. They learn to emulate the training set and that enables sampling from that domain and using the knowledge learned for useful applications. Several methods proposed enhancing GANs, including regularizing the loss with some feature matching. We seek to push GANs beyond the data in the training and try to explore unseen territory in the image manifold. We first propose a new regularizer for GAN based on K-Nearest Neighbor (K-NN) selective feature matching to a target set Y in high-level feature space, during the adversarial training of GAN on the base set X, and we call this novel model K-GAN. We show that minimizing the added term follows from cross-entropy minimization between the distributions of GAN and set Y. Then, we introduce a cascaded framework for GANs that try to address the task of imagining a new distribution that combines the base set X and target set Y by cascading sampling GANs with translation GANs, and we dub the cascade of such GANs as the Imaginative Adversarial Network (IAN). Several cascades are trained on a collected dataset Zoo-Faces and generated innovative samples are shown, including from K-GAN cascade. We conduct an objective and subjective evaluation for different IAN setups in the addressed task of generating innovative samples and we show the effect of regularizing GAN on different scores. We conclude with some useful applications for these IANs, like multi-domain manifold traversing.
Universal multifractality in multiparticle production
International Nuclear Information System (INIS)
Florkowski, W.; Hwa, R.C.
1991-01-01
The G moments for the multifractal analysis of multiparticle production are investigated in a model-independent way. By successive bin splitting and assuming the existence of a multiplicity splitting function that depends on multiplicity, but applicable at all steps of the splittings, we study the ergodicity of horizontal and vertical averaging, and derive a universality relation for the G moments. It relates the G moments for different initial multiplicities to a common scaling function Γ q (ξ). The experimental verification of this scaling property would, on the one hand, signify self-similarity in the data, and, on the other, provide a convenient function for comparison not only among different experiments, but also between theory and experiment
Multifractal Modeling of Turbulent Mixing
Samiee, Mehdi; Zayernouri, Mohsen; Meerschaert, Mark M.
2017-11-01
Stochastic processes in random media are emerging as interesting tools for modeling anomalous transport phenomena. Applications include intermittent passive scalar transport with background noise in turbulent flows, which are observed in atmospheric boundary layers, turbulent mixing in reactive flows, and long-range dependent flow fields in disordered/fractal environments. In this work, we propose a nonlocal scalar transport equation involving the fractional Laplacian, where the corresponding fractional index is linked to the multifractal structure of the nonlinear passive scalar power spectrum. This work was supported by the AFOSR Young Investigator Program (YIP) award (FA9550-17-1-0150) and partially by MURI/ARO (W911NF-15-1-0562).
(Multi)fractality of Earthquakes by use of Wavelet Analysis
Enescu, B.; Ito, K.; Struzik, Z. R.
2002-12-01
The fractal character of earthquakes' occurrence, in time, space or energy, has by now been established beyond doubt and is in agreement with modern models of seismicity. Moreover, the cascade-like generation process of earthquakes -with one "main" shock followed by many aftershocks, having their own aftershocks- may well be described through multifractal analysis, well suited for dealing with such multiplicative processes. The (multi)fractal character of seismicity has been analysed so far by using traditional techniques, like the box-counting and correlation function algorithms. This work introduces a new approach for characterising the multifractal patterns of seismicity. The use of wavelet analysis, in particular of the wavelet transform modulus maxima, to multifractal analysis was pioneered by Arneodo et al. (1991, 1995) and applied successfully in diverse fields, such as the study of turbulence, the DNA sequences or the heart rate dynamics. The wavelets act like a microscope, revealing details about the analysed data at different times and scales. We introduce and perform such an analysis on the occurrence time of earthquakes and show its advantages. In particular, we analyse shallow seismicity, characterised by a high aftershock "productivity", as well as intermediate and deep seismic activity, known for its scarcity of aftershocks. We examine as well declustered (aftershocks removed) versions of seismic catalogues. Our preliminary results show some degree of multifractality for the undeclustered, shallow seismicity. On the other hand, at large scales, we detect a monofractal scaling behaviour, clearly put in evidence for the declustered, shallow seismic activity. Moreover, some of the declustered sequences show a long-range dependent (LRD) behaviour, characterised by a Hurst exponent, H > 0.5, in contrast with the memory-less, Poissonian model. We demonstrate that the LRD is a genuine characteristic and is not an effect of the time series probability
Directory of Open Access Journals (Sweden)
D. Schertzer
1994-01-01
Full Text Available 1. The conference The third conference on "Nonlinear VAriability in Geophysics: scaling and multifractal processes" (NVAG 3 was held in Cargese, Corsica, Sept. 10-17, 1993. NVAG3 was joint American Geophysical Union Chapman and European Geophysical Society Richardson Memorial conference, the first specialist conference jointly sponsored by the two organizations. It followed NVAG1 (Montreal, Aug. 1986, NVAG2 (Paris, June 1988; Schertzer and Lovejoy, 1991, five consecutive annual sessions at EGS general assemblies and two consecutive spring AGU meeting sessions. As with the other conferences and workshops mentioned above, the aim was to develop confrontation between theories and experiments on scaling/multifractal behaviour of geophysical fields. Subjects covered included climate, clouds, earthquakes, atmospheric and ocean dynamics, tectonics, precipitation, hydrology, the solar cycle and volcanoes. Areas of focus included new methods of data analysis (especially those used for the reliable estimation of multifractal and scaling exponents, as well as their application to rapidly growing data bases from in situ networks and remote sensing. The corresponding modelling, prediction and estimation techniques were also emphasized as were the current debates about stochastic and deterministic dynamics, fractal geometry and multifractals, self-organized criticality and multifractal fields, each of which was the subject of a specific general discussion. The conference started with a one day short course of multifractals featuring four lectures on a Fundamentals of multifractals: dimension, codimensions, codimension formalism, b Multifractal estimation techniques: (PDMS, DTM, c Numerical simulations, Generalized Scale Invariance analysis, d Advanced multifractals, singular statistics, phase transitions, self-organized criticality and Lie cascades (given by D. Schertzer and S. Lovejoy, detailed course notes were sent to participants shortly after the
Schertzer, D.; Lovejoy, S.
1. The conference The third conference on "Nonlinear VAriability in Geophysics: scaling and multifractal processes" (NVAG 3) was held in Cargese, Corsica, Sept. 10-17, 1993. NVAG3 was joint American Geophysical Union Chapman and European Geophysical Society Richardson Memorial conference, the first specialist conference jointly sponsored by the two organizations. It followed NVAG1 (Montreal, Aug. 1986), NVAG2 (Paris, June 1988; Schertzer and Lovejoy, 1991), five consecutive annual sessions at EGS general assemblies and two consecutive spring AGU meeting sessions. As with the other conferences and workshops mentioned above, the aim was to develop confrontation between theories and experiments on scaling/multifractal behaviour of geophysical fields. Subjects covered included climate, clouds, earthquakes, atmospheric and ocean dynamics, tectonics, precipitation, hydrology, the solar cycle and volcanoes. Areas of focus included new methods of data analysis (especially those used for the reliable estimation of multifractal and scaling exponents), as well as their application to rapidly growing data bases from in situ networks and remote sensing. The corresponding modelling, prediction and estimation techniques were also emphasized as were the current debates about stochastic and deterministic dynamics, fractal geometry and multifractals, self-organized criticality and multifractal fields, each of which was the subject of a specific general discussion. The conference started with a one day short course of multifractals featuring four lectures on a) Fundamentals of multifractals: dimension, codimensions, codimension formalism, b) Multifractal estimation techniques: (PDMS, DTM), c) Numerical simulations, Generalized Scale Invariance analysis, d) Advanced multifractals, singular statistics, phase transitions, self-organized criticality and Lie cascades (given by D. Schertzer and S. Lovejoy, detailed course notes were sent to participants shortly after the conference). This
Multifractals Properties on the Near Infrared Spectroscopy of Human Brain Hemodynamic
Directory of Open Access Journals (Sweden)
Truong Quang Dang Khoa
2012-01-01
Full Text Available Nonlinear physics presents us with a perplexing variety of complicated fractal objects and strange sets. Naturally one wishes to characterize the objects and describe the events occurring on them. Moreover, most time series found in “real-life” applications appear quite noisy. Therefore, at almost every point in time, they cannot be approximated either by the Taylor series or by the Fourier series of just a few terms. Many experimental time series have fractal features and display singular behavior, the so-called singularities. The multifractal spectrum quantifies the degree of fractals in the processes generating the time series. A novel definition is proposed called full-width Hölder exponents that indicate maximum expansion of multifractal spectrum. The obtained results have demonstrated the multifractal structure of near-infrared spectroscopy time series and the evidence for brain imagery activities.
Heterogeneous flow in multi-layer joint networks and its influence on incipient karst generation
Wang, X.; Jourde, H.
2017-12-01
Various dissolution types (e.g. pipe, stripe and sheet karstic features) have been observed in fractured layered limestones. Yet, due to a large range of structural and hydraulic parameters play a role in the karstification process, the dissolution mechanism, occurring either along fractures or bedding planes, is difficult to quantify. In this study, we use numerical models to investigate the influence of these parameters on the generation of different types of incipient karst. Specifically, we focus on two parameters: the fracture intensity contrast between adjacent layers and the aperture ratio between bedding planes and joints (abed/ajoint). The DFN models were generated using a pseudo-genetic code that considers the stress shadow zone. Flow simulations were performed using a combined finite-volume finite-element simulator under practical boundary conditions. The flow channeling within the fracture networks was characterized by applying a multi-fractal technique. The rock block equivalent permeability (keff) was also calculated to quantify the change in bulk hydraulic properties when changing the selected structural and hydraulic parameters. The flow simulation results show that the abed/ajoint ratio has a first-order control on the heterogeneous distribution of flow in the multi-layer system and on the magnitude of equivalent permeability. When abed/ajoint 0.1, the bedding plane has more control and flow becomes more pervasive and uniform, and the keff is accordingly high. A simple model, accounting for the calculation of the heterogeneous distributions of Damköhler number associated with different aperture ratios, is proposed to predict what type of incipient karst tends to develop under the studied flow conditions.
The guitar chord-generating algorithm based on complex network
Ren, Tao; Wang, Yi-fan; Du, Dan; Liu, Miao-miao; Siddiqi, Awais
2016-02-01
This paper aims to generate chords for popular songs automatically based on complex network. Firstly, according to the characteristics of guitar tablature, six chord networks of popular songs by six pop singers are constructed and the properties of all networks are concluded. By analyzing the diverse chord networks, the accompaniment regulations and features are shown, with which the chords can be generated automatically. Secondly, in terms of the characteristics of popular songs, a two-tiered network containing a verse network and a chorus network is constructed. With this network, the verse and chorus can be composed respectively with the random walk algorithm. Thirdly, the musical motif is considered for generating chords, with which the bad chord progressions can be revised. This method can make the accompaniments sound more melodious. Finally, a popular song is chosen for generating chords and the new generated accompaniment sounds better than those done by the composers.
Application of genetic neural network in steam generator fault diagnosing
International Nuclear Information System (INIS)
Lin Xiaogong; Jiang Xingwei; Liu Tao; Shi Xiaocheng
2005-01-01
In the paper, a new algorithm which neural network and genetic algorithm are mixed is adopted, aiming at the problems of slow convergence rate and easily falling into part minimums in network studying of traditional BP neural network, and used in the fault diagnosis of steam generator. The result shows that this algorithm can solve the convergence problem in the network trains effectively. (author)
Multifractal analysis of heartbeat dynamics during meditation training
Song, Renliang; Bian, Chunhua; Ma, Qianli D. Y.
2013-04-01
We investigate the multifractality of heartbeat dynamics during Chinese CHI meditation in healthy young adults. The results show that the range of multifractal singularity spectrum of heartbeat interval time series during meditation is significantly narrower than those in the pre-meditation state of the same subject, which indicates that during meditation the heartbeat becomes regular and the degree of multifractality decreases.
Network reconfiguration and neuronal plasticity in rhythm-generating networks.
Koch, Henner; Garcia, Alfredo J; Ramirez, Jan-Marino
2011-12-01
Neuronal networks are highly plastic and reconfigure in a state-dependent manner. The plasticity at the network level emerges through multiple intrinsic and synaptic membrane properties that imbue neurons and their interactions with numerous nonlinear properties. These properties are continuously regulated by neuromodulators and homeostatic mechanisms that are critical to maintain not only network stability and also adapt networks in a short- and long-term manner to changes in behavioral, developmental, metabolic, and environmental conditions. This review provides concrete examples from neuronal networks in invertebrates and vertebrates, and illustrates that the concepts and rules that govern neuronal networks and behaviors are universal.
Wireless Integrated Network Sensors Next Generation
National Research Council Canada - National Science Library
Merrill, William
2004-01-01
..., autonomous networking, and distributed operations for wireless networked sensor systems. Multiple types of sensor systems were developed and provided including capabilities for acoustic, seismic, passive infrared detection, and visual imaging...
A multifractal analysis of Asian foreign exchange markets
Oh, G.; Eom, C.; Havlin, S.; Jung, W.-S.; Wang, F.; Stanley, H. E.; Kim, S.
2012-06-01
We analyze the multifractal spectra of daily foreign exchange rates for Japan, Hong-Kong, Korea, and Thailand with respect to the United States in the period from 1991 until 2005. We find that the return time series show multifractal spectrum features for all four cases. To observe the effect of the Asian currency crisis, we also estimate the multifractal spectra of limited series before and after the crisis. We find that the Korean and Thai foreign exchange markets experienced a significant increase in multifractality compared to Hong-Kong and Japan. We also show that the multifractality is stronger related to the presence of high values of returns in the series.
Multifractal Analysis of Asian Foreign Exchange Markets and Financial Crisis
Oh, Gabjin; Kwon, Okyu; Jung, Woo-Sung
2012-02-01
We analyze the multifractal spectra of daily foreign exchange rates for Japan, Hong-Kong, Korea, and Thailand with respect to the United States Dollar from 1991 to 2005. We find that the return time series show multifractal spectrum features for all four cases. To observe the effect of the Asian currency crisis, we also estimate the multifractal spectra of limited series before and after the crisis. We find that the Korean and Thai foreign exchange markets experienced a significant increase in multifractality compared to Hong-Kong and Japan. We also show that the multifractality is stronge related to the presence of high values of returns in the series.
Submicron scale tissue multifractal anisotropy in polarized laser light scattering
Das, Nandan Kumar; Dey, Rajib; Chakraborty, Semanti; Panigrahi, Prasanta K.; Meglinski, Igor; Ghosh, Nirmalya
2018-03-01
The spatial fluctuations of the refractive index within biological tissues exhibit multifractal anisotropy, leaving its signature as a spectral linear diattenuation of scattered polarized light. The multifractal anisotropy has been quantitatively assessed by the processing of relevant Mueller matrix elements in the Fourier domain, utilizing the Born approximation and subsequent multifractal analysis. The differential scaling exponent and width of the singularity spectrum appear to be highly sensitive to the structural multifractal anisotropy at the micron/sub-micron length scales. An immediate practical use of these multifractal anisotropy parameters was explored for non-invasive screening of cervical precancerous alterations ex vivo, with the indication of a strong potential for clinical diagnostic purposes.
Mobility Models for Next Generation Wireless Networks Ad Hoc, Vehicular and Mesh Networks
Santi, Paolo
2012-01-01
Mobility Models for Next Generation Wireless Networks: Ad Hoc, Vehicular and Mesh Networks provides the reader with an overview of mobility modelling, encompassing both theoretical and practical aspects related to the challenging mobility modelling task. It also: Provides up-to-date coverage of mobility models for next generation wireless networksOffers an in-depth discussion of the most representative mobility models for major next generation wireless network application scenarios, including WLAN/mesh networks, vehicular networks, wireless sensor networks, and
Multifractals of investor behavior in stock market
Oh, Gabjin
2017-07-01
In this paper, we analyze the nonlinear properties of investor activity using the multifractal detrended fluctuation analysis (MF-DFA) method. Using the aggregated trading volumes of buying, selling, and normalized net investor trading (NIT) to quantify the characteristics of trader behavior in the KOSPI market, we find that the cumulative distribution functions of all NIT time series, except for individual traders, follow a power-law distribution with an exponent in the range of 2.92 ≤ γ ≤ 3.87. To observe the nonlinear features of investor activity, we also calculate the multifractal spectra for the buyer, seller, and NIT data sets and find that a multifractal structure exists in all of the data, regardless of the investor type studied.
Correlation and multifractality in climatological time series
International Nuclear Information System (INIS)
Pedron, I T
2010-01-01
Climate can be described by statistical analysis of mean values of atmospheric variables over a period. It is possible to detect correlations in climatological time series and to classify its behavior. In this work the Hurst exponent, which can characterize correlation and persistence in time series, is obtained by using the Detrended Fluctuation Analysis (DFA) method. Data series of temperature, precipitation, humidity, solar radiation, wind speed, maximum squall, atmospheric pressure and randomic series are studied. Furthermore, the multifractality of such series is analyzed applying the Multifractal Detrended Fluctuation Analysis (MF-DFA) method. The results indicate presence of correlation (persistent character) in all climatological series and multifractality as well. A larger set of data, and longer, could provide better results indicating the universality of the exponents.
The weather and climate: emergent laws and multifractal cascades
Lovejoy, Shaun; Schertzer, Daniel
2013-04-01
Science in general and physics and geophysics in particular are hierarchies of interlocking theories and models with low level, fundamental laws such as quantum mechanics and statistical mechanics providing the underpinnings for the emergence of the qualitatively new, higher level laws of thermodynamics and continuum mechanics that provide the current bases for modelling the weather and climate. Yest it was the belief of generations of turbulence pioneers (notably Richardson, Kolmogorov, Obhukhov, Corrsin, Bolgiano) that at sufficiently high levels of nonlinearity (quantified by the Reynold's number, of the order 10**12 in the atmosphere) that new even higher level laws would emerge describing "fully developed turbulence". However for atmospheric applications, the pioneers' eponymous laws suffered from two basic restrictions - isotropy and homogeneity - that prevented them from being valid over wide ranges of scale. Over the last thirty years both of these restrictions have been overcome - the former with the generalization from isotropic to strongly anisotropic notions of scale (to account notably for stratification), and from homogeneity to strong heterogeneity (intermittency) via multifractal cascades. In this presentation we give an overview of recent developments and analyses covering huge ranges of space-time scales (including weather, macroweather and climate time scales). We show how the combination of strong anisotropy and strong intermittency commonly leads to the "phenomenological fallacy" in which morphology is confounded with mechanism. With the help of stochastic models, we show how processes with vastly different large and small scale morphologies can arise from a unique multifractal dynamical mechanisms [Lovejoy and Schertzer, 2013]. References: Lovejoy, S., and D. Schertzer (2013), The Weather and Climate: Emergent Laws and Multifractal Cascades, 480 pp., Cambridge University Press, Cambridge.
Serletis, Demitre; Bardakjian, Berj L.; Valiante, Taufik A.; Carlen, Peter L.
2012-10-01
Fractal methods offer an invaluable means of investigating turbulent nonlinearity in non-stationary biomedical recordings from the brain. Here, we investigate properties of complexity (i.e. the correlation dimension, maximum Lyapunov exponent, 1/fγ noise and approximate entropy) and multifractality in background neuronal noise-like activity underlying epileptiform transitions recorded at the intracellular and local network scales from two in vitro models: the whole-intact mouse hippocampus and lesional human hippocampal slices. Our results show evidence for reduced dynamical complexity and multifractal signal features following transition to the ictal epileptiform state. These findings suggest that pathological breakdown in multifractal complexity coincides with loss of signal variability or heterogeneity, consistent with an unhealthy ictal state that is far from the equilibrium of turbulent yet healthy fractal dynamics in the brain. Thus, it appears that background noise-like activity successfully captures complex and multifractal signal features that may, at least in part, be used to classify and identify brain state transitions in the healthy and epileptic brain, offering potential promise for therapeutic neuromodulatory strategies for afflicted patients suffering from epilepsy and other related neurological disorders. This paper is based on chapter 5 of Serletis (2010 PhD Dissertation Department of Physiology, Institute of Biomaterials and Biomedical Engineering, University of Toronto).
METHODOLOGY FOR GENERATION OF CORPORATE NETWORK HOSTNAME
Garrigós, Allan Mac Quinn; Sassi, Renato José
2011-01-01
The general concept of corporate network is made up of two or more interconnected computers sharing information, for the right functionality of the sharing. the nomenclature of these computers within the network is extremely important for proper organization of the names on Active Directory (AD -Domain Controller) and removing the duplicated names improperly created equal, removing the arrest of communications between machines with the same name on the network. The aim of this study was to de...
Spatial Characterization of Landscapes through Multifractal Analysis of DEM
Directory of Open Access Journals (Sweden)
P. L. Aguado
2014-01-01
Full Text Available Landscape evolution is driven by abiotic, biotic, and anthropic factors. The interactions among these factors and their influence at different scales create a complex dynamic. Landscapes have been shown to exhibit numerous scaling laws, from Horton’s laws to more sophisticated scaling of heights in topography and river network topology. This scaling and multiscaling analysis has the potential to characterise the landscape in terms of the statistical signature of the measure selected. The study zone is a matrix obtained from a digital elevation model (DEM (map 10 × 10 m, and height 1 m that corresponds to homogeneous region with respect to soil characteristics and climatology known as “Monte El Pardo” although the water level of a reservoir and the topography play a main role on its organization and evolution. We have investigated whether the multifractal analysis of a DEM shows common features that can be used to reveal the underlying patterns and information associated with the landscape of the DEM mapping and studied the influence of the water level of the reservoir on the applied analysis. The results show that the use of the multifractal approach with mean absolute gradient data is a useful tool for analysing the topography represented by the DEM.
Building next-generation converged networks theory and practice
Pathan, Al-Sakib Khan
2013-01-01
Supplying a comprehensive introduction to next-generation networks, Building Next-Generation Converged Networks: Theory and Practice strikes a balance between how and why things work and how to make them work. It compiles recent advancements along with basic issues from the wide range of fields related to next generation networks. Containing the contributions of 56 industry experts and researchers from 16 different countries, the book presents relevant theoretical frameworks and the latest research. It investigates new technologies such as IPv6 over Low Power Wireless Personal Area Network (6L
Transient stability analysis of a distribution network with distributed generators
Xyngi, I.; Ishchenko, A.; Popov, M.; Sluis, van der L.
2009-01-01
This letter describes the transient stability analysis of a 10-kV distribution network with wind generators, microturbines, and CHP plants. The network being modeled in Matlab/Simulink takes into account detailed dynamic models of the generators. Fault simulations at various locations are
The New Generation Russian VLBI Network
Finkelstein, Andrey; Ipatov, Alexander; Smolentsev, Sergey; Mardyshkin, Vyacheslav; Fedotov, Leonid; Surkis, Igor; Ivanov, Dmitrij; Gayazov, Iskander
2010-01-01
This paper deals with a new project of the Russian VLBI Network dedicated for Universal Time determinations in quasi on-line mode. The basic principles of the network design and location of antennas are explained. Variants of constructing receiving devices, digital data acquisition system, and phase calibration system are specially considered. The frequency ranges and expected values of noise temperature are given.
CO-GENERATION AND OPERATING NETWORK CELLS
DEFF Research Database (Denmark)
Nielsen, John Eli
2008-01-01
In Denmark several thousands of generators are connected to the distribution system (10 kV and 0.4 kV). The production from these generators many times exceeds the load. The generators can be divided into two types, Wind turbines and CHP generators. These generators have one thing in common......, the power system they are connected to, has never been designed to accommodate so many generators. In Denmark we now expect a third type of generators: the microgenerators. This time we want to be prepared. Denmark therefore now participates in a lot of research and full scale demonstration projects. A key...
Speech-Driven Facial Reenactment Using Conditional Generative Adversarial Networks
Jalalifar, Seyed Ali; Hasani, Hosein; Aghajan, Hamid
2018-01-01
We present a novel approach to generating photo-realistic images of a face with accurate lip sync, given an audio input. By using a recurrent neural network, we achieved mouth landmarks based on audio features. We exploited the power of conditional generative adversarial networks to produce highly-realistic face conditioned on a set of landmarks. These two networks together are capable of producing a sequence of natural faces in sync with an input audio track.
Centralized Networks to Generate Human Body Motions.
Vakulenko, Sergei; Radulescu, Ovidiu; Morozov, Ivan; Weber, Andres
2017-12-14
We consider continuous-time recurrent neural networks as dynamical models for the simulation of human body motions. These networks consist of a few centers and many satellites connected to them. The centers evolve in time as periodical oscillators with different frequencies. The center states define the satellite neurons' states by a radial basis function (RBF) network. To simulate different motions, we adjust the parameters of the RBF networks. Our network includes a switching module that allows for turning from one motion to another. Simulations show that this model allows us to simulate complicated motions consisting of many different dynamical primitives. We also use the model for learning human body motion from markers' trajectories. We find that center frequencies can be learned from a small number of markers and can be transferred to other markers, such that our technique seems to be capable of correcting for missing information resulting from sparse control marker settings.
Next Generation Campus Network Deployment Project Based on Softswitch
HU Feng; LIU Ziyan
2011-01-01
After analyzing the current networks of Guizhou University，we brought forward a scheme of next generation campus networks based on softswitch technology by choosing SoftX3000 switching system of HuaWei and provided the specific solution of accessing campus networks in this paper. It is proved that this scheme is feasible by using OPNET, which not only accomplished the integration of the PSTN and IP networks but also achieved the combining of voice services and data services.
Anti-correlation and multifractal features of Spain electricity spot market
Norouzzadeh, Payam; Dullaert, W.; Rahmani, Bahareh
2007-01-01
We use multifractal detrended fluctuation analysis (MF-DFA) to numerically investigate correlation, persistence, multifractal properties and scaling behavior of the hourly spot prices for the Spain electricity exchange-Compania O Peradora del Mercado de Electricidad (OMEL). Through multifractal
Multifractal and higher-dimensional zeta functions
International Nuclear Information System (INIS)
Véhel, Jacques Lévy; Mendivil, Franklin
2011-01-01
In this paper, we generalize the zeta function for a fractal string (as in Lapidus and Frankenhuijsen 2006 Fractal Geometry, Complex Dimensions and Zeta Functions: Geometry and Spectra of Fractal Strings (New York: Springer)) in several directions. We first modify the zeta function to be associated with a sequence of covers instead of the usual definition involving gap lengths. This modified zeta function allows us to define both a multifractal zeta function and a zeta function for higher-dimensional fractal sets. In the multifractal case, the critical exponents of the zeta function ζ(q, s) yield the usual multifractal spectrum of the measure. The presence of complex poles for ζ(q, s) indicates oscillations in the continuous partition function of the measure, and thus gives more refined information about the multifractal spectrum of a measure. In the case of a self-similar set in R n , the modified zeta function yields asymptotic information about both the 'box' counting function of the set and the n-dimensional volume of the ε-dilation of the set
Phoebus: Network Middleware for Next-Generation Network Computing
Energy Technology Data Exchange (ETDEWEB)
Martin Swany
2012-06-16
The Phoebus project investigated algorithms, protocols, and middleware infrastructure to improve end-to-end performance in high speed, dynamic networks. The Phoebus system essentially serves as an adaptation point for networks with disparate capabilities or provisioning. This adaptation can take a variety of forms including acting as a provisioning agent across multiple signaling domains, providing transport protocol adaptation points, and mapping between distributed resource reservation paradigms and the optical network control plane. We have successfully developed the system and demonstrated benefits. The Phoebus system was deployed in Internet2 and in ESnet, as well as in GEANT2, RNP in Brazil and over international links to Korea and Japan. Phoebus is a system that implements a new protocol and associated forwarding infrastructure for improving throughput in high-speed dynamic networks. It was developed to serve the needs of large DOE applications on high-performance networks. The idea underlying the Phoebus model is to embed Phoebus Gateways (PGs) in the network as on-ramps to dynamic circuit networks. The gateways act as protocol translators that allow legacy applications to use dedicated paths with high performance.
Next Generation Network Routing and Control Plane
DEFF Research Database (Denmark)
Fu, Rong
proved, the dominating Border Gateway Protocol (BGP) cannot address all the issues that in inter-domain QoS routing. Thus a new protocol or network architecture has to be developed to be able to carry the inter-domain traffic with the QoS and TE consideration. Moreover, the current network control also...... lacks the ability to cooperate between different domains and operators. The emergence of label switching transport technology such as of Multi-Protocol Label Switching (MPLS) or Generalized MPLS (GMPLS) supports the traffic transport in a finer granularity and more dedicated end-to-end Quality...... (RACF) provides the platform that enables cooperation and ubiquitous integration between networks. In this paper, we investigate in the network architecture, protocols and algorithms for inter-domain QoS routing and traffic engineering. The PCE based inter-domain routing architecture is enhanced...
Plan Generation and Evaluation Using Action Networks
National Research Council Canada - National Science Library
Peot, Mark
2003-01-01
... from potential actions of the plan. Methods used to accomplish these results included the use of Action Networks, and development of a suite of analysis tools in support of the AFRL Campaign Assessment Tool...
Super-Resolution Reconstruction of Remote Sensing Images Using Multifractal Analysis
Directory of Open Access Journals (Sweden)
Mao-Gui Hu
2009-10-01
Full Text Available Satellite remote sensing (RS is an important contributor to Earth observation, providing various kinds of imagery every day, but low spatial resolution remains a critical bottleneck in a lot of applications, restricting higher spatial resolution analysis (e.g., intraurban. In this study, a multifractal-based super-resolution reconstruction method is proposed to alleviate this problem. The multifractal characteristic is common in Nature. The self-similarity or self-affinity presented in the image is useful to estimate details at larger and smaller scales than the original. We first look for the presence of multifractal characteristics in the images. Then we estimate parameters of the information transfer function and noise of the low resolution image. Finally, a noise-free, spatial resolutionenhanced image is generated by a fractal coding-based denoising and downscaling method. The empirical case shows that the reconstructed super-resolution image performs well indetail enhancement. This method is not only useful for remote sensing in investigating Earth, but also for other images with multifractal characteristics.
Multiplicative multifractal modeling and discrimination of human neuronal activity
International Nuclear Information System (INIS)
Zheng Yi; Gao Jianbo; Sanchez, Justin C.; Principe, Jose C.; Okun, Michael S.
2005-01-01
Understanding neuronal firing patterns is one of the most important problems in theoretical neuroscience. It is also very important for clinical neurosurgery. In this Letter, we introduce a computational procedure to examine whether neuronal firing recordings could be characterized by cascade multiplicative multifractals. By analyzing raw recording data as well as generated spike train data from 3 patients collected in two brain areas, the globus pallidus externa (GPe) and the globus pallidus interna (GPi), we show that the neural firings are consistent with a multifractal process over certain time scale range (t 1 ,t 2 ), where t 1 is argued to be not smaller than the mean inter-spike-interval of neuronal firings, while t 2 may be related to the time that neuronal signals propagate in the major neural branching structures pertinent to GPi and GPe. The generalized dimension spectrum D q effectively differentiates the two brain areas, both intra- and inter-patients. For distinguishing between GPe and GPi, it is further shown that the cascade model is more effective than the methods recently examined by Schiff et al. as well as the Fano factor analysis. Therefore, the methodology may be useful in developing computer aided tools to help clinicians perform precision neurosurgery in the operating room
Multifractal rainfall extremes: Theoretical analysis and practical estimation
International Nuclear Information System (INIS)
Langousis, Andreas; Veneziano, Daniele; Furcolo, Pierluigi; Lepore, Chiara
2009-01-01
We study the extremes generated by a multifractal model of temporal rainfall and propose a practical method to estimate the Intensity-Duration-Frequency (IDF) curves. The model assumes that rainfall is a sequence of independent and identically distributed multiplicative cascades of the beta-lognormal type, with common duration D. When properly fitted to data, this simple model was found to produce accurate IDF results [Langousis A, Veneziano D. Intensity-duration-frequency curves from scaling representations of rainfall. Water Resour Res 2007;43. (doi:10.1029/2006WR005245)]. Previous studies also showed that the IDF values from multifractal representations of rainfall scale with duration d and return period T under either d → 0 or T → ∞, with different scaling exponents in the two cases. We determine the regions of the (d, T)-plane in which each asymptotic scaling behavior applies in good approximation, find expressions for the IDF values in the scaling and non-scaling regimes, and quantify the bias when estimating the asymptotic power-law tail of rainfall intensity from finite-duration records, as was often done in the past. Numerically calculated exact IDF curves are compared to several analytic approximations. The approximations are found to be accurate and are used to propose a practical IDF estimation procedure.
Multifractal characteristics of NDVI maps in space and time in the Community of Madrid (Spain)
Sotoca, Juan J. Martin; Saa-Requejo, Antonio; Grau, Juan B.; Tarquis, Ana M.
2015-04-01
Satellite information has contributed to improve our understanding of the spatial variability of hydro-climatic and ecological processes. Vegetation activity is tightly coupled with climate, hydro-ecological fluxes, and terrain dynamics in river basins at a wide range of space-time scales (Scheuring and Riedi, 1994). Indices of vegetation activity are constructed using satellite information of reflectance of the relevant spectral bands which enhance the contribution of vegetation being Normalized Difference Vegetation Index (NDVI) widely used. How can we study such a complex system? Multifractals and fractals are related techniques mainly used in physics to characterize the scaling behaviour of a system; they differ in that fractals look at the geometry of presence/absence patterns, while multifractals look at the arrangement of quantities such as population or biomass densities (Saravia et al., 2012). Scaling laws are an emergent general feature of ecological systems; they reflect constraints in their organization that can provide tracks about the underlying mechanisms (Solé and Bascompte, 2006). In this work, we have applied these techniques to study the spatial pattern through one year of NDVI maps. A rectangular area that includes the Community of Madrid and part of the surroundings, consisting of 300 x 280 pixels with a resolution of 500 x 500 m2 has been selected and monthly NDVI maps analyzed using the multifractal spectrum and the map of singularities (Cheng and Agterberg, 1996). The results show a cyclical pattern in the multifractal behaviour and singularity points related to river basin networks (Martín-Sotoca, 2014). References Cheng, Q. and Agterberg, F.P. (1996). Multifractal modeling and spatial statistics. Math. Geol. Vol 28, 1-16. Martín-Sotoca, J.J. (2014) Estructura Espacial de la Sequía en Pastos y sus Aplicaciones en el Seguro Agrario. Master Thesis, UPM (In Spanish). Saravia LA, Giorgi A, Momo F.: Multifractal growth in periphyton
Wulff-Jensen, Andreas; Rant, Niclas Nerup; Møller, Tobias Nordvig; Billeskov, Jonas Aksel
2018-01-01
This paper proposes a novel framework for improving procedural generation of 3D landscapes using machine learning. We utilized a Deep Convolutional Generative Adversarial Network (DC-GAN) to generate heightmaps. The network was trained on a dataset consisting of Digital Elevation Maps (DEM) of the alps. During map generation, the batch size and learning rate were optimized for the most efficient and satisfying map production. The diversity of the final output was tested against Perlin noise u...
Do-it-yourself networks: a novel method of generating weighted networks.
Shanafelt, D W; Salau, K R; Baggio, J A
2017-11-01
Network theory is finding applications in the life and social sciences for ecology, epidemiology, finance and social-ecological systems. While there are methods to generate specific types of networks, the broad literature is focused on generating unweighted networks. In this paper, we present a framework for generating weighted networks that satisfy user-defined criteria. Each criterion hierarchically defines a feature of the network and, in doing so, complements existing algorithms in the literature. We use a general example of ecological species dispersal to illustrate the method and provide open-source code for academic purposes.
Individual heterogeneity generating explosive system network dynamics.
Manrique, Pedro D; Johnson, Neil F
2018-03-01
Individual heterogeneity is a key characteristic of many real-world systems, from organisms to humans. However, its role in determining the system's collective dynamics is not well understood. Here we study how individual heterogeneity impacts the system network dynamics by comparing linking mechanisms that favor similar or dissimilar individuals. We find that this heterogeneity-based evolution drives an unconventional form of explosive network behavior, and it dictates how a polarized population moves toward consensus. Our model shows good agreement with data from both biological and social science domains. We conclude that individual heterogeneity likely plays a key role in the collective development of real-world networks and communities, and it cannot be ignored.
Individual heterogeneity generating explosive system network dynamics
Manrique, Pedro D.; Johnson, Neil F.
2018-03-01
Individual heterogeneity is a key characteristic of many real-world systems, from organisms to humans. However, its role in determining the system's collective dynamics is not well understood. Here we study how individual heterogeneity impacts the system network dynamics by comparing linking mechanisms that favor similar or dissimilar individuals. We find that this heterogeneity-based evolution drives an unconventional form of explosive network behavior, and it dictates how a polarized population moves toward consensus. Our model shows good agreement with data from both biological and social science domains. We conclude that individual heterogeneity likely plays a key role in the collective development of real-world networks and communities, and it cannot be ignored.
Multifractal analysis of managed and independent float exchange rates
Stošić, Darko; Stošić, Dusan; Stošić, Tatijana; Stanley, H. Eugene
2015-06-01
We investigate multifractal properties of daily price changes in currency rates using the multifractal detrended fluctuation analysis (MF-DFA). We analyze managed and independent floating currency rates in eight countries, and determine the changes in multifractal spectrum when transitioning between the two regimes. We find that after the transition from managed to independent float regime the changes in multifractal spectrum (position of maximum and width) indicate an increase in market efficiency. The observed changes are more pronounced for developed countries that have a well established trading market. After shuffling the series, we find that the multifractality is due to both probability density function and long term correlations for managed float regime, while for independent float regime multifractality is in most cases caused by broad probability density function.
Mobile location services over the next generation IP core network
DEFF Research Database (Denmark)
Thongthammachart, Saowanee; Olesen, Henning
2003-01-01
network is changing from circuit-switched to packet-switched technology and evolving to an IP core network based on IPv6. The IP core network will allow all IP devices to be connected seamlessly. Due to the movement detection mechanism of Mobile IPv6, mobile terminals will periodically update....... The concept of mobile location services over the next generation IP networks is described. We also discuss the effectiveness of the short-range wireless network regarding a mobile user's position inside buildings and hotspot areas....
Convergence of wireless, wireline, and photonics next generation networks
Iniewski, Krzysztof
2010-01-01
Filled with illustrations and practical examples from industry, this book provides a brief but comprehensive introduction to the next-generation wireless networks that will soon replace more traditional wired technologies. Written by a mixture of top industrial experts and key academic professors, it is the only book available that covers both wireless networks (such as wireless local area and personal area networks) and optical networks (such as long-haul and metropolitan networks) in one volume. It gives engineers and engineering students the necessary knowledge to meet challenges of next-ge
CSIR Research Space (South Africa)
Schwegmann, Colin P
2017-07-01
Full Text Available such as Synthetic Aperture Radar imagery. To aid in the creation of improved machine learning-based ship detection and discrimination methods this paper applies a type of neural network known as an Information Maximizing Generative Adversarial Network. Generative...
Probing next Generation Portuguese Academic Network
Friacas, Carlos; Massano, Emanuel; Domingues, Monica; Veiga, Pedro
2008-01-01
Purpose: The purpose of this article is to provide several viewpoints about monitoring aspects related to recent deployments of a new technology (IPv6). Design/methodology/approach: Several views and domains were used, with a common point: the Portuguese research and education network (RCTS). Findings: A significant amount of work is yet to be…
Multifractal Detrended Fluctuation Analysis of Human gait Diseases
Directory of Open Access Journals (Sweden)
Srimonti eDutta
2013-10-01
Full Text Available IIn this paper multifractal detrended fluctuation analysis is used to study the human gait time series for normal and diseased sets. It is observed that long range correlation is primarily responsible for the origin of multifractality. The study reveals that the degree of multifractality is more for normal set compared to diseased set. However the method fails to distinguish between the two diseased sets.
Multifractal detrended fluctuation analysis of analog random multiplicative processes
Energy Technology Data Exchange (ETDEWEB)
Silva, L.B.M.; Vermelho, M.V.D. [Instituto de Fisica, Universidade Federal de Alagoas, Maceio - AL, 57072-970 (Brazil); Lyra, M.L. [Instituto de Fisica, Universidade Federal de Alagoas, Maceio - AL, 57072-970 (Brazil)], E-mail: marcelo@if.ufal.br; Viswanathan, G.M. [Instituto de Fisica, Universidade Federal de Alagoas, Maceio - AL, 57072-970 (Brazil)
2009-09-15
We investigate non-Gaussian statistical properties of stationary stochastic signals generated by an analog circuit that simulates a random multiplicative process with weak additive noise. The random noises are originated by thermal shot noise and avalanche processes, while the multiplicative process is generated by a fully analog circuit. The resulting signal describes stochastic time series of current interest in several areas such as turbulence, finance, biology and environment, which exhibit power-law distributions. Specifically, we study the correlation properties of the signal by employing a detrended fluctuation analysis and explore its multifractal nature. The singularity spectrum is obtained and analyzed as a function of the control circuit parameter that tunes the asymptotic power-law form of the probability distribution function.
Physical Configuration of the Next Generation Home Network
Terada, Shohei; Kakishima, Yu; Hanawa, Dai; Oguchi, Kimio
The number of broadband users is rapidly increasing worldwide. Japan already has over 10 million FTTH users. Another trend is the rapid digitalization of home electrical equipment e. g. digital cameras and hard disc recorders. These trends will encourage the emergence of the next generation home network. In this paper, we introduce the next generation home network image and describe the five domains into which home devices can be classified. We then clarify the optimum medium with which to configure the network given the requirements imposed by the home environment. Wiring cable lengths for three network topologies are calculated. The results gained from the next generation home network implemented on the first phase testbed are shown. Finally, our conclusions are given.
International Nuclear Information System (INIS)
Cao, Guangxi; Xu, Wei
2016-01-01
Basing on daily price data of carbon emission rights in futures markets of Certified Emission Reduction (CER) and European Union Allowances (EUA), we analyze the multiscale characteristics of the markets by using empirical mode decomposition (EMD) and multifractal detrended fluctuation analysis (MFDFA) based on EMD. The complexity of the daily returns of CER and EUA futures markets changes with multiple time scales and multilayered features. The two markets also exhibit clear multifractal characteristics and long-range correlation. We employ shuffle and surrogate approaches to analyze the origins of multifractality. The long-range correlations and fat-tail distributions significantly contribute to multifractality. Furthermore, we analyze the influence of high returns on multifractality by using threshold method. The multifractality of the two futures markets is related to the presence of high values of returns in the price series.
Quantum computation of multifractal exponents through the quantum wavelet transform
International Nuclear Information System (INIS)
Garcia-Mata, Ignacio; Giraud, Olivier; Georgeot, Bertrand
2009-01-01
We study the use of the quantum wavelet transform to extract efficiently information about the multifractal exponents for multifractal quantum states. We show that, combined with quantum simulation algorithms, it enables to build quantum algorithms for multifractal exponents with a polynomial gain compared to classical simulations. Numerical results indicate that a rough estimate of fractality could be obtained exponentially fast. Our findings are relevant, e.g., for quantum simulations of multifractal quantum maps and of the Anderson model at the metal-insulator transition.
Directory of Open Access Journals (Sweden)
Gopa Bhoumik
2016-01-01
Full Text Available We have studied the multifractality of pion emission process in 16O-AgBr interactions at 2.1 AGeV and 60 AGeV, 12C-AgBr and 24Mg-AgBr interactions at 4.5 AGeV, and 32S-AgBr interactions at 200 AGeV using Multifractal Detrended Fluctuation Analysis (MFDFA method which is capable of extracting the actual multifractal property filtering out the average trend of fluctuation. The analysis reveals that the pseudorapidity distribution of the shower particles is multifractal in nature for all the interactions; that is, pion production mechanism has inbuilt multiscale self-similarity property. We have employed MFDFA method for randomly generated events for 32S-AgBr interactions at 200 AGeV. Comparison of expt. results with those obtained from randomly generated data set reveals that the source of multifractality in our data is the presence of long range correlation. Comparing the results obtained from different interactions, it may be concluded that strength of multifractality decreases with projectile mass for the same projectile energy and for a particular projectile it increases with energy. The values of ordinary Hurst exponent suggest that there is long range correlation present in our data for all the interactions.
Harmonics: Generation and Suppression in AC System Networks ...
African Journals Online (AJOL)
However, reactive power flow in electrical networks has adverse effects depending on their magnitude and the nature of the supply network. How these harmonics are generated by nonlinear loads and the means by which they can be kept low are the focus of this paper. Keywords: non-linear loads, harmonics, reactive ...
Distributed network generation based on preferential attachment in ABS
K. Azadbakht (Keyvan); N. Bezirgiannis (Nikolaos); F.S. de Boer (Frank)
2017-01-01
textabstractGeneration of social networks using Preferential Attachment (PA) mechanism is proposed in the Barabasi-Albert model. In this mechanism, new nodes are introduced to the network sequentially and they attach to the existing nodes preferentially where the preference can be based on the
Liu, Ruipeng; Di Matteo, T.; Lux, Thomas
2007-09-01
In this paper, we consider daily financial data of a collection of different stock market indices, exchange rates, and interest rates, and we analyze their multi-scaling properties by estimating a simple specification of the Markov-switching multifractal (MSM) model. In order to see how well the estimated model captures the temporal dependence of the data, we estimate and compare the scaling exponents H(q) (for q=1,2) for both empirical data and simulated data of the MSM model. In most cases the multifractal model appears to generate ‘apparent’ long memory in agreement with the empirical scaling laws.
ALGORITHMS FOR TETRAHEDRAL NETWORK (TEN) GENERATION
Institute of Scientific and Technical Information of China (English)
无
2000-01-01
The Tetrahedral Network(TEN) is a powerful 3-D vector structure in GIS, which has a lot of advantages such as simple structure, fast topological relation processing and rapid visualization. The difficulty of TEN application is automatic creating data structure. Al though a raster algorithm has been introduced by some authors, the problems in accuracy, memory requirement, speed and integrity are still existent. In this paper, the raster algorithm is completed and a vector algorithm is presented after a 3-D data model and structure of TEN have been introducted. Finally, experiment, conclusion and future work are discussed.
Penetration tests in next generation networks
Rezac, Filip; Voznak, Miroslav
2012-06-01
SIP proxy server is without any doubts centerpiece of any SIP IP telephony infrastructure. It also often provides other services than those related to VoIP traffic. These softswitches are, however, very often become victims of attacks and threats coming from public networks. The paper deals with a system that we developed as an analysis and testing tool to verify if the target SIP server is adequately secured and protected against any real threats. The system is designed as an open-source application, thus allowing independent access and is fully extensible to other test modules.
Automated Item Generation with Recurrent Neural Networks.
von Davier, Matthias
2018-03-12
Utilizing technology for automated item generation is not a new idea. However, test items used in commercial testing programs or in research are still predominantly written by humans, in most cases by content experts or professional item writers. Human experts are a limited resource and testing agencies incur high costs in the process of continuous renewal of item banks to sustain testing programs. Using algorithms instead holds the promise of providing unlimited resources for this crucial part of assessment development. The approach presented here deviates in several ways from previous attempts to solve this problem. In the past, automatic item generation relied either on generating clones of narrowly defined item types such as those found in language free intelligence tests (e.g., Raven's progressive matrices) or on an extensive analysis of task components and derivation of schemata to produce items with pre-specified variability that are hoped to have predictable levels of difficulty. It is somewhat unlikely that researchers utilizing these previous approaches would look at the proposed approach with favor; however, recent applications of machine learning show success in solving tasks that seemed impossible for machines not too long ago. The proposed approach uses deep learning to implement probabilistic language models, not unlike what Google brain and Amazon Alexa use for language processing and generation.
A multifractal formalism for countable alphabet subshifts
International Nuclear Information System (INIS)
Meson, Alejandro; Vericat, Fernando
2009-01-01
We study here the multifractal spectrum of local entropies for subshifts with an infinite alphabet. The description of this spectrum is obtained from the Legendre transform of a free energy map and Gibbs states associated with adequate potentials. The lack of compactness in the symbolic space necessitates modifications to the description for the compact case, i.e. for finite alphabet. In particular, the class of potentials must be restricted to a narrower one than that considered for the compact case
Multifractal properties of ball milling dynamics
Energy Technology Data Exchange (ETDEWEB)
Budroni, M. A., E-mail: mabudroni@uniss.it; Pilosu, V.; Rustici, M. [Dipartimento di Chimica e Farmacia, Università degli Studi di Sassari, Via Vienna 2, Sassari 07100 (Italy); Delogu, F. [Dipartimento di Ingegneria Meccanica, Chimica, e dei Materiali, Università degli Studi di Cagliari, via Marengo 2, Cagliari 09123 (Italy)
2014-06-15
This work focuses on the dynamics of a ball inside the reactor of a ball mill. We show that the distribution of collisions at the reactor walls exhibits multifractal properties in a wide region of the parameter space defining the geometrical characteristics of the reactor and the collision elasticity. This feature points to the presence of restricted self-organized zones of the reactor walls where the ball preferentially collides and the mechanical energy is mainly dissipated.
Generating pipeline networks for corrosion assessment
Energy Technology Data Exchange (ETDEWEB)
Ferguson, J. [Cimarron Engineering Ltd., Calgary, AB (Canada)
2008-07-01
Production characteristics and gas-fluid compositions of fluids must be known in order to assess pipelines for internal corrosion risk. In this study, a gathering system pipeline network was built in order to determine corrosion risk for gathering system pipelines. Connections were established between feeder and collector lines in order measure upstream production and the weighted average of the upstream composition of each pipeline in the system. A Norsok M-506 carbon dioxide (CO{sub 2}) corrosion rate model was used to calculate corrosion rates. A spreadsheet was then used to tabulate the obtained data. The analysis used straight lines drawn between the 'from' and 'to' legal sub-division (LSD) endpoints in order to represent pipelines on an Alberta township system (ATS) and identify connections between pipelines. Well connections were established based on matching surface hole location and 'from' LSDs. Well production, composition, pressure, and temperature data were sourced and recorded as well attributes. XSL hierarchical computations were used to determine the production and composition properties of the commingled inflows. It was concluded that the corrosion assessment process can identify locations within the pipeline network where potential deadlegs branched off from flowing pipelines. 4 refs., 2 tabs., 2 figs.
Searching for a multifractal signature of the lake algal proliferation, a multifractal correlation
Mezemate, Yacine; Tchiguirinskaia, Ioulia; Bonhomme, Celine; Schertzer, Daniel; Lemaire, Bruno Jacques; Vinçon leite, Brigitte; Lovejoy, Shaun
2013-04-01
Green algae proliferations affect water bodies such as the Lake Bourget (France). They are an environmental issue as well as a mater of public health. In the framework of the PROLIPHYC project a system based on temperature and chlorophyll measurements coupled to a lake model was implemented to predict sudden algal blooms. This classical approach relies on the analysis of large scale trends of the measured fields and does not take into account small scale fluctuations. A more innovative approach has been developed by the R2DS PLUMMME project to investigate the correlation between environmental fields across the full range of space-time scales, down to the smallest scale of observations. The first results of the project demonstrate that multi-scaling behaviour of environmental fields, such as temperature and chlorophyll, becomes evident only after the removal of the large-scale data trends that otherwise induce biases to the multifractal parameter estimates. First, a spectral analysis of temperature and chlorophyll data is performed on sub-samples of the time series to investigate the scaling behaviour. The multifractal analysis (Trace Moment, Double Trace Moment) directly applied on each sub-sample shows unsatisfying results on some sub-samples, in particular on those having a strong gradient compared with the amplitude of the fluctuations. Hence, non-stationary and seasonal effects should be first removed from the time series. To put on evidence a good scaling of the analysed data, we choose the Hilbert-Huang transform to de-trend the data. This method has been widely used for different fields (see F.G.Schmitt et al, 2009 for review). After having applied this method, the K(q) function shows that the investigated fields are indeed multifractal and the determination of their multifractal parameters becomes robust. Then, we proceed to a multifractal correlation analysis between the fields. In conclusion, we discuss the prediction of algal blooms based on multifractal
Voltage regulation in distribution networks with distributed generation
Blažič, B.; Uljanić, B.; Papič, I.
2012-11-01
The paper deals with the topic of voltage regulation in distribution networks with relatively high distributed energy resources (DER) penetration. The problem of voltage rise is described and different options for voltage regulation are given. The influence of DER on voltage profile and the effectiveness of the investigated solutions are evaluated by means of simulation in DIgSILENT. The simulated network is an actual distribution network in Slovenia with a relatively high penetration of distributed generation. Recommendations for voltage control in networks with DER penetration are given at the end.
Big Data Perspective and Challenges in Next Generation Networks
Directory of Open Access Journals (Sweden)
Kashif Sultan
2018-06-01
Full Text Available With the development towards the next generation cellular networks, i.e., 5G, the focus has shifted towards meeting the higher data rate requirements, potential of micro cells and millimeter wave spectrum. The goals for next generation networks are very high data rates, low latency and handling of big data. The achievement of these goals definitely require newer architecture designs, upgraded technologies with possible backward support, better security algorithms and intelligent decision making capability. In this survey, we identify the opportunities which can be provided by 5G networks and discuss the underlying challenges towards implementation and realization of the goals of 5G. This survey also provides a discussion on the recent developments made towards standardization, the architectures which may be potential candidates for deployment and the energy concerns in 5G networks. Finally, the paper presents a big data perspective and the potential of machine learning for optimization and decision making in 5G networks.
International Nuclear Information System (INIS)
Ni Xiaohui; Jiang Zhiqiang; Zhou Weixing
2009-01-01
The dynamics of a complex system is usually recorded in the form of time series, which can be studied through its visibility graph from a complex network perspective. We investigate the visibility graphs extracted from fractional Brownian motions and multifractal random walks, and find that the degree distributions exhibit power-law behaviors, in which the power-law exponent α is a linear function of the Hurst index H of the time series. We also find that the degree distribution of the visibility graph is mainly determined by the temporal correlation of the original time series with minor influence from the possible multifractal nature. As an example, we study the visibility graphs constructed from three Chinese stock market indexes and unveil that the degree distributions have power-law tails, where the tail exponents of the visibility graphs and the Hurst indexes of the indexes are close to the α∼H linear relationship.
Comparing Generative Adversarial Network Techniques for Image Creation and Modification
Pieters, Mathijs; Wiering, Marco
2018-01-01
Generative adversarial networks (GANs) have demonstrated to be successful at generating realistic real-world images. In this paper we compare various GAN techniques, both supervised and unsupervised. The effects on training stability of different objective functions are compared. We add an encoder
Innovation and networking among entrepreneurs across generations of Asian tigers
DEFF Research Database (Denmark)
Brambini-Pedersen, Jan Vang; Jensen, Kent W; Schøtt, Thomas
2017-01-01
entrepreneurship monitor (GEM) data, this paper aims at reducing this research gap by conducting an analysis of the generational differences between the tiger economies entrepreneurs in respect to their innovative performance, their inclination to network and the importance of the quality of the network......Much attention has been paid to analysing the determinants of the economic development in the different generations of Asian tiger economies. This stream of research has provided valuable insights on the particular generational challenges, the tigers face in implementing successful catching up...
Patch layout generation by detecting feature networks
Cao, Yuanhao
2015-02-01
The patch layout of 3D surfaces reveals the high-level geometric and topological structures. In this paper, we study the patch layout computation by detecting and enclosing feature loops on surfaces. We present a hybrid framework which combines several key ingredients, including feature detection, feature filtering, feature curve extension, patch subdivision and boundary smoothing. Our framework is able to compute patch layouts through concave features as previous approaches, but also able to generate nice layouts through smoothing regions. We demonstrate the effectiveness of our framework by comparing with the state-of-the-art methods.
MTGAN: Speaker Verification through Multitasking Triplet Generative Adversarial Networks
Ding, Wenhao; He, Liang
2018-01-01
In this paper, we propose an enhanced triplet method that improves the encoding process of embeddings by jointly utilizing generative adversarial mechanism and multitasking optimization. We extend our triplet encoder with Generative Adversarial Networks (GANs) and softmax loss function. GAN is introduced for increasing the generality and diversity of samples, while softmax is for reinforcing features about speakers. For simplification, we term our method Multitasking Triplet Generative Advers...
Econophysics vs Cardiophysics: the Dual Face of Multifractality
Z.R. Struzik
2003-01-01
textabstractMultifractality in physiological time series and notably in human adult heart rate has been primarily attributed to the Fourier phase ordering of the signal [1]. In contrast, the primary cause for the width of the multifractal spectrum in financial time series has recently been connected
Mobility management techniques for the next-generation wireless networks
Sun, Junzhao; Howie, Douglas P.; Sauvola, Jaakko J.
2001-10-01
The tremendous demands from social market are pushing the booming development of mobile communications faster than ever before, leading to plenty of new advanced techniques emerging. With the converging of mobile and wireless communications with Internet services, the boundary between mobile personal telecommunications and wireless computer networks is disappearing. Wireless networks of the next generation need the support of all the advances on new architectures, standards, and protocols. Mobility management is an important issue in the area of mobile communications, which can be best solved at the network layer. One of the key features of the next generation wireless networks is all-IP infrastructure. This paper discusses the mobility management schemes for the next generation mobile networks through extending IP's functions with mobility support. A global hierarchical framework model for the mobility management of wireless networks is presented, in which the mobility management is divided into two complementary tasks: macro mobility and micro mobility. As the macro mobility solution, a basic principle of Mobile IP is introduced, together with the optimal schemes and the advances in IPv6. The disadvantages of the Mobile IP on solving the micro mobility problem are analyzed, on the basis of which three main proposals are discussed as the micro mobility solutions for mobile communications, including Hierarchical Mobile IP (HMIP), Cellular IP, and Handoff-Aware Wireless Access Internet Infrastructure (HAWAII). A unified model is also described in which the different micro mobility solutions can coexist simultaneously in mobile networks.
Generation of clusters in complex dynamical networks via pinning control
International Nuclear Information System (INIS)
Li Kezan; Fu Xinchu; Small, Michael
2008-01-01
Many real-world networks show community structure, i.e., groups (or clusters) of nodes that have a high density of links within them but with a lower density of links between them. In this paper, by applying feedback injections to a fraction of network nodes, various clusters are synchronized independently according to the community structure generated by the group partition of the network (cluster synchronization). This control is achieved by pinning (i.e. applying linear feedback control) to a subset of the network nodes. Those pinned nodes are selected not randomly but according to the topological structure of communities of a given network. Specifically, for a given group partition of a network, those nodes with direct connections between groups must be pinned in order to achieve cluster synchronization. Both the local stability and global stability of cluster synchronization are investigated. Taking the tree-shaped network and the most modular network as two particular examples, we illustrate in detail how the pinning strategy influences the generation of clusters. The simulations verify the efficiency of the pinning schemes used in this paper
Learning Orthographic Structure With Sequential Generative Neural Networks.
Testolin, Alberto; Stoianov, Ivilin; Sperduti, Alessandro; Zorzi, Marco
2016-04-01
Learning the structure of event sequences is a ubiquitous problem in cognition and particularly in language. One possible solution is to learn a probabilistic generative model of sequences that allows making predictions about upcoming events. Though appealing from a neurobiological standpoint, this approach is typically not pursued in connectionist modeling. Here, we investigated a sequential version of the restricted Boltzmann machine (RBM), a stochastic recurrent neural network that extracts high-order structure from sensory data through unsupervised generative learning and can encode contextual information in the form of internal, distributed representations. We assessed whether this type of network can extract the orthographic structure of English monosyllables by learning a generative model of the letter sequences forming a word training corpus. We show that the network learned an accurate probabilistic model of English graphotactics, which can be used to make predictions about the letter following a given context as well as to autonomously generate high-quality pseudowords. The model was compared to an extended version of simple recurrent networks, augmented with a stochastic process that allows autonomous generation of sequences, and to non-connectionist probabilistic models (n-grams and hidden Markov models). We conclude that sequential RBMs and stochastic simple recurrent networks are promising candidates for modeling cognition in the temporal domain. Copyright © 2015 Cognitive Science Society, Inc.
Carrier ethernet network control plane based on the Next Generation Network
DEFF Research Database (Denmark)
Fu, Rong; Wang, Yanmeng; Berger, Michael Stubert
2008-01-01
This paper contributes on presenting a step towards the realization of Carrier Ethernet control plane based on the next generation network (NGN). Specifically, transport MPLS (T-MPLS) is taken as the transport technology in Carrier Ethernet. It begins with providing an overview of the evolving...... architecture of the next generation network (NGN). As an essential candidate among the NGN transport technologies, the definition of Carrier Ethernet (CE) is also introduced here. The second part of this paper depicts the contribution on the T-MPLS based Carrier Ethernet network with control plane based on NGN...... at illustrating the improvement of the Carrier Ethernet network with the NGN control plane....
Intrinsically-generated fluctuating activity in excitatory-inhibitory networks
Mastrogiuseppe, Francesca; Ostojic, Srdjan
2017-01-01
Recurrent networks of non-linear units display a variety of dynamical regimes depending on the structure of their synaptic connectivity. A particularly remarkable phenomenon is the appearance of strongly fluctuating, chaotic activity in networks of deterministic, but randomly connected rate units. How this type of intrinsically generated fluctuations appears in more realistic networks of spiking neurons has been a long standing question. To ease the comparison between rate and spiking networks, recent works investigated the dynamical regimes of randomly-connected rate networks with segregated excitatory and inhibitory populations, and firing rates constrained to be positive. These works derived general dynamical mean field (DMF) equations describing the fluctuating dynamics, but solved these equations only in the case of purely inhibitory networks. Using a simplified excitatory-inhibitory architecture in which DMF equations are more easily tractable, here we show that the presence of excitation qualitatively modifies the fluctuating activity compared to purely inhibitory networks. In presence of excitation, intrinsically generated fluctuations induce a strong increase in mean firing rates, a phenomenon that is much weaker in purely inhibitory networks. Excitation moreover induces two different fluctuating regimes: for moderate overall coupling, recurrent inhibition is sufficient to stabilize fluctuations; for strong coupling, firing rates are stabilized solely by the upper bound imposed on activity, even if inhibition is stronger than excitation. These results extend to more general network architectures, and to rate networks receiving noisy inputs mimicking spiking activity. Finally, we show that signatures of the second dynamical regime appear in networks of integrate-and-fire neurons. PMID:28437436
Toward green next-generation passive optical networks
Srivastava, Anand
2015-01-01
Energy efficiency has become an increasingly important aspect of designing access networks, due to both increased concerns for global warming and increased network costs related to energy consumption. Comparing access, metro, and core, the access constitutes a substantial part of the per subscriber network energy consumption and is regarded as the bottleneck for increased network energy efficiency. One of the main opportunities for reducing network energy consumption lies in efficiency improvements of the customer premises equipment. Access networks in general are designed for low utilization while supporting high peak access rates. The combination of large contribution to overall network power consumption and low Utilization implies large potential for CPE power saving modes where functionality is powered off during periods of idleness. Next-generation passive optical network, which is considered one of the most promising optical access networks, has notably matured in the past few years and is envisioned to massively evolve in the near future. This trend will increase the power requirements of NG-PON and make it no longer coveted. This paper will first provide a comprehensive survey of the previously reported studies on tackling this problem. A novel solution framework is then introduced, which aims to explore the maximum design dimensions and achieve the best possible power saving while maintaining the QoS requirements for each type of service.
Formal Specification Based Automatic Test Generation for Embedded Network Systems
Directory of Open Access Journals (Sweden)
Eun Hye Choi
2014-01-01
Full Text Available Embedded systems have become increasingly connected and communicate with each other, forming large-scaled and complicated network systems. To make their design and testing more reliable and robust, this paper proposes a formal specification language called SENS and a SENS-based automatic test generation tool called TGSENS. Our approach is summarized as follows: (1 A user describes requirements of target embedded network systems by logical property-based constraints using SENS. (2 Given SENS specifications, test cases are automatically generated using a SAT-based solver. Filtering mechanisms to select efficient test cases are also available in our tool. (3 In addition, given a testing goal by the user, test sequences are automatically extracted from exhaustive test cases. We’ve implemented our approach and conducted several experiments on practical case studies. Through the experiments, we confirmed the efficiency of our approach in design and test generation of real embedded air-conditioning network systems.
Robust network topologies for generating switch-like cellular responses.
Directory of Open Access Journals (Sweden)
Najaf A Shah
2011-06-01
Full Text Available Signaling networks that convert graded stimuli into binary, all-or-none cellular responses are critical in processes ranging from cell-cycle control to lineage commitment. To exhaustively enumerate topologies that exhibit this switch-like behavior, we simulated all possible two- and three-component networks on random parameter sets, and assessed the resulting response profiles for both steepness (ultrasensitivity and extent of memory (bistability. Simulations were used to study purely enzymatic networks, purely transcriptional networks, and hybrid enzymatic/transcriptional networks, and the topologies in each class were rank ordered by parametric robustness (i.e., the percentage of applied parameter sets exhibiting ultrasensitivity or bistability. Results reveal that the distribution of network robustness is highly skewed, with the most robust topologies clustering into a small number of motifs. Hybrid networks are the most robust in generating ultrasensitivity (up to 28% and bistability (up to 18%; strikingly, a purely transcriptional framework is the most fragile in generating either ultrasensitive (up to 3% or bistable (up to 1% responses. The disparity in robustness among the network classes is due in part to zero-order ultrasensitivity, an enzyme-specific phenomenon, which repeatedly emerges as a particularly robust mechanism for generating nonlinearity and can act as a building block for switch-like responses. We also highlight experimentally studied examples of topologies enabling switching behavior, in both native and synthetic systems, that rank highly in our simulations. This unbiased approach for identifying topologies capable of a given response may be useful in discovering new natural motifs and in designing robust synthetic gene networks.
Satellite communications for the next generation telecommunication services and networks
Chitre, D. M.
1991-01-01
Satellite communications can play an important role in provisioning the next-generation telecommunication services and networks, provided the protocols specifying these services and networks are satellite-compatible and the satellite subnetworks, consisting of earth stations interconnected by the processor and the switch on board the satellite, interwork effectively with the terrestrial networks. The specific parameters and procedures of frame relay and broadband integrated services digital network (B-ISDN) protocols which are impacted by a satellite delay. Congestion and resource management functions for frame relay and B-ISDN are discussed in detail, describing the division of these functions between earth stations and on board the satellite. Specific onboard and ground functions are identified as potential candidates for their implementation via neural network technology.
The effects of observational correlated noises on multifractal detrended fluctuation analysis
Gulich, Damián; Zunino, Luciano
2012-08-01
We have numerically investigated the effects that observational correlated noises have on the generalized Hurst exponents, h(q), estimated by using the multifractal generalization of detrended fluctuation analysis (MF-DFA). More precisely, artificially generated stochastic binomial multifractals with increased amount of colored noises were analyzed via MF-DFA. It has been recently shown that for moderate additions of white noise, the generalized Hurst exponents are significantly underestimated for qeffects of additive noise, short- term memory and periodic trends, Physica A 390 (2011) 2480-2490]. In this paper, we have found that h(q) with q≥2 are also affected when correlated noises are considered. This is due to the fact that the spurious correlations influence the scaling behaviors associated to large fluctuations. The results obtained are significant for practical situations, where noises with different correlations are inherently present.
International Nuclear Information System (INIS)
Provata, A.; Katsaloulis, P.; Verganelakis, D.A.
2012-01-01
Highlights: ► Calculation of human brain multifractal spectra. ► Calculations are based on Diffusion Tensor MRI Images. ► Spectra are modelled by coupled Ikeda map dynamics. ► Coupled lattice Ikeda maps model well only positive multifractal spectra. ► Appropriately modified coupled lattice Ikeda maps give correct spectra. - Abstract: The multifractal spectra of 3d Diffusion Tensor Images (DTI) obtained by magnetic resonance imaging of the human brain are studied. They are shown to deviate substantially from artificial brain images with the same white matter intensity. All spectra, obtained from 12 healthy subjects, show common characteristics indicating non-trivial moments of the intensity. To model the spectra the dynamics of the chaotic Ikeda map are used. The DTI multifractal spectra for positive q are best approximated by 3d coupled Ikeda maps in the fully developed chaotic regime. The coupling constants are as small as α = 0.01. These results reflect not only the white tissue non-trivial architectural complexity in the human brain, but also demonstrate the presence and importance of coupling between neuron axons. The architectural complexity is also mirrored by the deviations in the negative q-spectra, where the rare events dominate. To obtain a good agreement in the DTI negative q-spectrum of the brain with the Ikeda dynamics, it is enough to slightly modify the most rare events of the coupled Ikeda distributions. The representation of Diffusion Tensor Images with coupled Ikeda maps is not unique: similar conclusions are drawn when other chaotic maps (Tent, Logistic or Henon maps) are employed in the modelling of the neuron axons network.
Embedded generation connection incentives for distribution network operators
Energy Technology Data Exchange (ETDEWEB)
Williams, P.; Andrews, S.
2002-07-01
This is the final report with respect to work commissioned by the Department of Trade and Industry (DTI) as part of the New and Renewable Energy Programme into incentives for distribution network operators (DNOs) for the connection of embedded generation. This report, which incorporates the contents of the interim report submitted in February 2002, considers the implications of changes in the structure and regulation in the UK electricity industry on the successful technical and commercial integrated of embedded generation into distribution networks. The report examines: the obligations of public electricity suppliers (PESs); current DNO practices regarding the connection of embedded generation; the changes introduced by the Utilities Act 2000, including the impact of new obligations placed on DNOs on the connection of embedded generation and the requirements of the new Electricity Distribution Standard Licence conditions; and problems and prospects for DNO incentives.
Application of Generative Adversarial Networks (GANs) to jet images
CERN. Geneva
2017-01-01
https://arxiv.org/abs/1701.05927 We provide a bridge between generative modeling in the Machine Learning community and simulated physical processes in High Energy Particle Physics by applying a novel Generative Adversarial Network (GAN) architecture to the production of jet images -- 2D representations of energy depositions from particles interacting with a calorimeter. We propose a simple architecture, the Location-Aware Generative Adversarial Network, that learns to produce realistic radiation patterns from simulated high energy particle collisions. The pixel intensities of GAN-generated images faithfully span over many orders of magnitude and exhibit the desired low-dimensional physical properties (i.e., jet mass, n-subjettiness, etc.). We shed light on limitations, and provide a novel empirical validation of image quality and validity of GAN-produced simulations of the natural world. This work provides a base for further explorations of GANs for use in faster simulation in High Energy Particle Physics.
Interaction Networks: Generating High Level Hints Based on Network Community Clustering
Eagle, Michael; Johnson, Matthew; Barnes, Tiffany
2012-01-01
We introduce a novel data structure, the Interaction Network, for representing interaction-data from open problem solving environment tutors. We show how using network community detecting techniques are used to identify sub-goals in problems in a logic tutor. We then use those community structures to generate high level hints between sub-goals.…
Multifractal analysis of the Korean agricultural market
Kim, Hongseok; Oh, Gabjin; Kim, Seunghwan
2011-11-01
We have studied the long-term memory effects of the Korean agricultural market using the detrended fluctuation analysis (DFA) method. In general, the return time series of various financial data, including stock indices, foreign exchange rates, and commodity prices, are uncorrelated in time, while the volatility time series are strongly correlated. However, we found that the return time series of Korean agricultural commodity prices are anti-correlated in time, while the volatility time series are correlated. The n-point correlations of time series were also examined, and it was found that a multifractal structure exists in Korean agricultural market prices.
Multifractal spectra in homogeneous shear flow
Deane, A. E.; Keefe, L. R.
1988-01-01
Employing numerical simulations of 3-D homogeneous shear flow, the associated multifractal spectra of the energy dissipation, scalar dissipation and vorticity fields were calculated. The results for (128) cubed simulations of this flow, and those obtained in recent experiments that analyzed 1- and 2-D intersections of atmospheric and laboratory flows, are in some agreement. A two-scale Cantor set model of the energy cascade process which describes the experimental results from 1-D intersections quite well, describes the 3-D results only marginally.
Creating Turbulent Flow Realizations with Generative Adversarial Networks
King, Ryan; Graf, Peter; Chertkov, Michael
2017-11-01
Generating valid inflow conditions is a crucial, yet computationally expensive, step in unsteady turbulent flow simulations. We demonstrate a new technique for rapid generation of turbulent inflow realizations that leverages recent advances in machine learning for image generation using a deep convolutional generative adversarial network (DCGAN). The DCGAN is an unsupervised machine learning technique consisting of two competing neural networks that are trained against each other using backpropagation. One network, the generator, tries to produce samples from the true distribution of states, while the discriminator tries to distinguish between true and synthetic samples. We present results from a fully-trained DCGAN that is able to rapidly draw random samples from the full distribution of possible inflow states without needing to solve the Navier-Stokes equations, eliminating the costly process of spinning up inflow turbulence. This suggests a new paradigm in physics informed machine learning where the turbulence physics can be encoded in either the discriminator or generator. Finally, we also propose additional applications such as feature identification and subgrid scale modeling.
Price-volume multifractal analysis of the Moroccan stock market
El Alaoui, Marwane
2017-11-01
In this paper, we analyzed price-volume multifractal cross-correlations of Moroccan Stock Exchange. We chose the period from January 1st 2000 to January 20th 2017 to investigate the multifractal behavior of price change and volume change series. Then, we used multifractal detrended cross-correlations analysis method (MF-DCCA) and multifractal detrended fluctuation analysis (MF-DFA) to analyze the series. We computed bivariate generalized Hurst exponent, Rényi exponent and spectrum of singularity for each pair of indices to measure quantitatively cross-correlations. Furthermore, we used detrended cross-correlations coefficient (DCCA) and cross-correlation test (Q(m)) to analyze cross-correlation quantitatively and qualitatively. By analyzing results, we found existence of price-volume multifractal cross-correlations. The spectrum width has a strong multifractal cross-correlation. We remarked that volume change series is anti-persistent when we analyzed the generalized Hurst exponent for all moments q. The cross-correlation test showed the presence of a significant cross-correlation. However, DCCA coefficient had a small positive value, which means that the level of correlation is not very significant. Finally, we analyzed sources of multifractality and their degree of contribution in the series.
Generating private recommendations in a social trust network
Erkin, Z.; Veugen, P.J.M.; Lagendijk, R.L.
2011-01-01
Recommender systems have become increasingly important in e-commerce as they can guide customers with finding personalized services and products. A variant of recommender systems that generates recommendations from a set of trusted people is recently getting more attention in social networks.
Generative adversarial networks for anomaly detection in images
Batiste Ros, Guillem
2018-01-01
Anomaly detection is used to identify abnormal observations that don t follow a normal pattern. Inthis work, we use the power of Generative Adversarial Networks in sampling from image distributionsto perform anomaly detection with images and to identify local anomalous segments within thisimages. Also, we explore potential application of this method to support pathological analysis ofbiological tissues
Facilitate generation connections on Orkney by automatic distribution network management
Energy Technology Data Exchange (ETDEWEB)
NONE
2004-07-01
This report summarises the results of a study assessing the capability and limitations of the Orkney Network under a variety of conditions of demand, generation connections, network configuration, and reactive compensation). A conceptual active management scheme (AMS) suitable for the conditions on Orkney is developed and evaluated. Details are given of a proposed framework for the design and evaluation of future active management schemes, logic control sequences for managed generation units, and a proposed evaluation method for the active management scheme. Implications of introducing the proposed AMS are examined, and the commercial aspects of an AMS and system security are considered. The existing Orkney network is described; and an overview of the SHEPDL (Scottish Hydro Electric Power Distribution Ltd.) SCADA system is presented with a discussion of AMS identification, selection, and development.
Converged Wireless Networking and Optimization for Next Generation Services
Directory of Open Access Journals (Sweden)
J. Rodriguez
2010-01-01
Full Text Available The Next Generation Network (NGN vision is tending towards the convergence of internet and mobile services providing the impetus for new market opportunities in combining the appealing services of internet with the roaming capability of mobile networks. However, this convergence does not go far enough, and with the emergence of new coexistence scenarios, there is a clear need to evolve the current architecture to provide cost-effective end-to-end communication. The LOOP project, a EUREKA-CELTIC driven initiative, is one piece in the jigsaw by helping European industry to sustain a leading role in telecommunications and manufacturing of high-value products and machinery by delivering pioneering converged wireless networking solutions that can be successfully demonstrated. This paper provides an overview of the LOOP project and the key achievements that have been tunneled into first prototypes for showcasing next generation services for operators and process manufacturers.
Distribution network planning method considering distributed generation for peak cutting
International Nuclear Information System (INIS)
Ouyang Wu; Cheng Haozhong; Zhang Xiubin; Yao Liangzhong
2010-01-01
Conventional distribution planning method based on peak load brings about large investment, high risk and low utilization efficiency. A distribution network planning method considering distributed generation (DG) for peak cutting is proposed in this paper. The new integrated distribution network planning method with DG implementation aims to minimize the sum of feeder investments, DG investments, energy loss cost and the additional cost of DG for peak cutting. Using the solution techniques combining genetic algorithm (GA) with the heuristic approach, the proposed model determines the optimal planning scheme including the feeder network and the siting and sizing of DG. The strategy for the site and size of DG, which is based on the radial structure characteristics of distribution network, reduces the complexity degree of solving the optimization model and eases the computational burden substantially. Furthermore, the operation schedule of DG at the different load level is also provided.
Tri-generation in urban networks; Trigeneration en reseau urbain
Energy Technology Data Exchange (ETDEWEB)
Malahieude, J.M. [Trigen Energy Corp., New-York (United States)
1996-12-31
The concepts of tri-generation (simultaneous production of heat, electric power and refrigerating energy) and thermal energy distribution networks, are presented. The different components of the tri-generation system from Trigen Energy Corp. are ammonia as a refrigerant for the production of cooled water, screw compressors, gas turbines and an induction motor-generator in order to optimize the combined gas turbine and compressor utilization. The energy efficiency and pollution reduction of the system are evaluated; the system has been enhanced through re-powering and post combustion
Beyond Fractals and 1/f Noise: Multifractal Analysis of Complex Physiological Time Series
Ivanov, Plamen Ch.; Amaral, Luis A. N.; Ashkenazy, Yosef; Stanley, H. Eugene; Goldberger, Ary L.; Hausdorff, Jeffrey M.; Yoneyama, Mitsuru; Arai, Kuniharu
2001-03-01
We investigate time series with 1/f-like spectra generated by two physiologic control systems --- the human heartbeat and human gait. We show that physiological fluctuations exhibit unexpected ``hidden'' structures often described by scaling laws. In particular, our studies indicate that when analyzed on different time scales the heartbeat fluctuations exhibit cascades of branching patterns with self-similar (fractal) properties, characterized by long-range power-law anticorrelations. We find that these scaling features change during sleep and wake phases, and with pathological perturbations. Further, by means of a new wavelet-based technique, we find evidence of multifractality in the healthy human heartbeat even under resting conditions, and show that the multifractal character and nonlinear properties of the healthy heart are encoded in the Fourier phases. We uncover a loss of multifractality for a life-threatening condition, congestive heart failure. In contrast to the heartbeat, we find that the interstride interval time series of healthy human gait, a voluntary process under neural regulation, is described by a single fractal dimension (such as classical 1/f noise) indicating monofractal behavior. Thus our approach can help distinguish physiological and physical signals with comparable frequency spectra and two-point correlations, and guide modeling of their control mechanisms.
Overcoming barriers to scheduling embedded generation to support distribution networks
Energy Technology Data Exchange (ETDEWEB)
Wright, A.J.; Formby, J.R.
2000-07-01
Current scheduling of embedded generation for distribution in the UK is limited and patchy. Some DNOs actively schedule while others do none. The literature on the subject is mainly about accommodating volatile wind output, and optimising island systems, for both cost of supply and network stability. The forthcoming NETA will lower prices, expose unpredictable generation to imbalance markets and could introduce punitive constraint payments on DNOs, but at the same time create a dynamic market for both power and ancillary services from embedded generators. Most renewable generators either run as base load (e.g. waste ) or according to the vagaries of the weather (e.g. wind, hydro), so offer little scope for scheduling other than 'off'. CHP plant is normally heat- led for industrial processes or building needs, but supplementary firing or thermal storage often allow considerable scope for scheduling. Micro-CHP with thermal storage could provide short-term scheduling, but tends to be running anyway during the evening peak. Standby generation appears to be ideal for scheduling, but in practice operators may be unwilling to run parallel with the network, and noise and pollution problems may preclude frequent operation. Statistical analysis can be applied to calculate the reliability of several generators compared to one; with a large number of generators such as micro-CHP reliability of a proportion of load is close to unity. The type of communication for generation used will depend on requirements for bandwidth, cost, reliability and whether it is bundled with other services. With high levels of deeply embedded, small-scale generation using induction machines, voltage control and black start capability will become important concerns on 11 kV and LV networks. This will require increased generation monitoring and remote control of switchgear. Examples of cost benefits from scheduling are given, including deferred reinforcement, increased exports on non
Address Translation Problems in IMS Based Next Generation Networks
Directory of Open Access Journals (Sweden)
Balazs Godor
2006-01-01
Full Text Available The development of packed based multimedia networks reached a turning point when the ITU-T and the ETSIhave incorporated the IMS to the NGN. With the fast development of mobile communication more and more services andcontent are available. In contrast with fix network telephony both the services and the devices are personalized in the “mobileworld”. Services, known from the Internet - like e-mail, chat, browsing, presence, etc. – are already available via mobiledevices as well. The IMS originally wanted to exploit both the benefits of mobile networks and the fancy services of theInternet. But today it is already more than that. IMS is the core of the next generation telecommunication networks and abasis for fix-mobile convergent services. The fact however that IMS was originally a “mobile” standard, where IPv6 was notoddity generated some problems for the fix networks, where IPv4 is used. In this article I give an overview of these problemsand mention some solutions as well.
A method of generating moving objects on the constrained network
Zhang, Jie; Ma, Linbing
2008-10-01
Moving objects databases have become an important research issue in recent years. In case large real data sets acquired by GPS, PDA or other mobile devices are not available, benchmarking requires the generation of artificial data sets following the real-world behavior of spatial objects that change their locations over time. In the field of spatiotemporal databases, a number of publications about the generation of test data are restricted to few papers. However, most of the existing moving-object generators assume a fixed and often unrealistic mobility model and do not consider several important characteristics of the network. In this paper, a new generator is presented to solve these problems. First of all, the network is realistic transportation network of Guangzhou. Second, the observation records of vehicle flow are available. Third, in order to simplify the whole simulation process and to help us visualize the process, this framework is built under .Net development platform of Microsoft and ArcEngine9 environment.
Neural network based control of Doubly Fed Induction Generator in wind power generation
Barbade, Swati A.; Kasliwal, Prabha
2012-07-01
To complement the other types of pollution-free generation wind energy is a viable option. Previously wind turbines were operated at constant speed. The evolution of technology related to wind systems industry leaded to the development of a generation of variable speed wind turbines that present many advantages compared to the fixed speed wind turbines. In this paper the phasor model of DFIG is used. This paper presents a study of a doubly fed induction generator driven by a wind turbine connected to the grid, and controlled by artificial neural network ANN controller. The behaviour of the system is shown with PI control, and then as controlled by ANN. The effectiveness of the artificial neural network controller is compared to that of a PI controller. The SIMULINK/MATLAB simulation for Doubly Fed Induction Generator and corresponding results and waveforms are displayed.
Daily extreme temperature multifractals in Catalonia (NE Spain)
Energy Technology Data Exchange (ETDEWEB)
Burgueño, A. [Departament d' Astronomia i Meteorologia, Universitat de Barcelona, Barcelona (Spain); Lana, X., E-mail: francisco.javier.lana@upc.edu [Departament de Física i Enginyeria Nuclear, Universitat Politècnica de Catalunya, Barcelona (Spain); Serra, C. [Departament de Física i Enginyeria Nuclear, Universitat Politècnica de Catalunya, Barcelona (Spain); Martínez, M.D. [Departament de Física Aplicada, Universitat Politècnica de Catalunya, Barcelona (Spain)
2014-02-01
The multifractal character of the daily extreme temperatures in Catalonia (NE Spain) is analyzed by means of the multifractal detrended fluctuation analysis (MF-DFA) applied to 65 thermometric records covering years 1950–2004. Although no clear spatial patterns of the multifractal spectrum parameters appear, factor scores deduced from Principal Component analysis indicate some signs of spatial gradients. Additionally, the daily extreme temperature series are classified depending on their complex time behavior, through four multifractal parameters (Hurst exponent, Hölder exponent with maximum spectrum, spectrum asymmetry and spectrum width). As a synthesis of the three last parameters, a basic measure of complexity is proposed through a normalized Complexity Index. Its regional behavior is found to be free of geographical dependences. This index represents a new step towards the description of the daily extreme temperatures complexity.
The Multifractal Structure of Small-Scale Artificial Ionospheric Turbulence
Directory of Open Access Journals (Sweden)
Vybornov F. I.
2013-03-01
Full Text Available We present the results of investigation of a multifractal structure of the artificial ionospheric turbulence when the midlatitude ionosphere is affected by high-power radio waves. The experimental studies were performed on the basis of the SURA heating facility with the help of radio sounding of the disturbed region of ionospheric plasma by signals from the Earth’s orbital satellities. In the case of vertical radio sounding of the disturbed ionosphere region, the measured multipower and generalized multifractal spectra of turbulence coincide well with similar multifractal characteristics of the ionosperic turbulence under the natural conditions. In the case of oblique sounding of the disturbance region at small angles between the line of sight to the satellite and the direction of the Earth’s magnetic field, a nonuniform structure of the small-scale turbulence with a relatively narrow multipower spectrum and small variations in the generalized multifractal spectrum of the electron density was detected.
Daily extreme temperature multifractals in Catalonia (NE Spain)
International Nuclear Information System (INIS)
Burgueño, A.; Lana, X.; Serra, C.; Martínez, M.D.
2014-01-01
The multifractal character of the daily extreme temperatures in Catalonia (NE Spain) is analyzed by means of the multifractal detrended fluctuation analysis (MF-DFA) applied to 65 thermometric records covering years 1950–2004. Although no clear spatial patterns of the multifractal spectrum parameters appear, factor scores deduced from Principal Component analysis indicate some signs of spatial gradients. Additionally, the daily extreme temperature series are classified depending on their complex time behavior, through four multifractal parameters (Hurst exponent, Hölder exponent with maximum spectrum, spectrum asymmetry and spectrum width). As a synthesis of the three last parameters, a basic measure of complexity is proposed through a normalized Complexity Index. Its regional behavior is found to be free of geographical dependences. This index represents a new step towards the description of the daily extreme temperatures complexity.
Multifractal analysis of Moroccan family business stock returns
Lahmiri, Salim
2017-11-01
In this paper, long-range temporal correlations at different scales in Moroccan family business stock returns are investigated. For comparison purpose, presence of multifractality is also investigated in Casablanca Stock Exchange (CSE) major indices: MASI which is the all shares index and MADEX which is the index of most liquid shares. It is found that return series of both family business companies and major stock market indices show strong evidence of multifractality. In particular, empirical results reveal that short (long) fluctuations in family business stock returns are less (more) persistent (anti-persistent) than short fluctuations in market indices. In addition, both serial correlation and distribution characteristics significantly influence the strength of the multifractal spectrums of CSE and family business stocks returns. Furthermore, results from multifractal spectrum analysis suggest that family business stocks are less risky. Thus, such differences in price dynamics could be exploited by investors and forecasters in active portfolio management.
Multifractal analysis of three-dimensional histogram from color images
International Nuclear Information System (INIS)
Chauveau, Julien; Rousseau, David; Richard, Paul; Chapeau-Blondeau, Francois
2010-01-01
Natural images, especially color or multicomponent images, are complex information-carrying signals. To contribute to the characterization of this complexity, we investigate the possibility of multiscale organization in the colorimetric structure of natural images. This is realized by means of a multifractal analysis applied to the three-dimensional histogram from natural color images. The observed behaviors are confronted to those of reference models with known multifractal properties. We use for this purpose synthetic random images with trivial monofractal behavior, and multidimensional multiplicative cascades known for their actual multifractal behavior. The behaviors observed on natural images exhibit similarities with those of the multifractal multiplicative cascades and display the signature of elaborate multiscale organizations stemming from the histograms of natural color images. This type of characterization of colorimetric properties can be helpful to various tasks of digital image processing, as for instance modeling, classification, indexing.
Introduction to multifractal detrended fluctuation analysis in matlab.
Ihlen, Espen A F
2012-01-01
Fractal structures are found in biomedical time series from a wide range of physiological phenomena. The multifractal spectrum identifies the deviations in fractal structure within time periods with large and small fluctuations. The present tutorial is an introduction to multifractal detrended fluctuation analysis (MFDFA) that estimates the multifractal spectrum of biomedical time series. The tutorial presents MFDFA step-by-step in an interactive Matlab session. All Matlab tools needed are available in Introduction to MFDFA folder at the website www.ntnu.edu/inm/geri/software. MFDFA are introduced in Matlab code boxes where the reader can employ pieces of, or the entire MFDFA to example time series. After introducing MFDFA, the tutorial discusses the best practice of MFDFA in biomedical signal processing. The main aim of the tutorial is to give the reader a simple self-sustained guide to the implementation of MFDFA and interpretation of the resulting multifractal spectra.
Thermodynamic and multifractal formalism and the Bowen-series map
International Nuclear Information System (INIS)
Rudolph, O.
1994-07-01
In the theory of quantum chaos one studies the semiclassical behaviour of quantum mechanical systems whose corresponding classical counterparts exhibit chaos. These systems are sometimes considered as model systems in the theory of quantum chaos since they are well understood from a mathematical point of view. In this work we study the multifractal formalism for the geodesic flow on surfaces with constant negative curvature. The multifractal analysis of measures has been developed in order to characterize the scaling behaviour of measures on attractors of classical chaotic dynamical systems globally. In order to relate the multifractal formalism with quantities usually considered in the study of the geodesic flow on Riemann surfaces with constant negative curvature, it is necessary to establish the assertions of the multifractal formalism in a mathematically rigorous way. This is achieved with the help of the thermodynamic formalism for hyperbolic dynamical systems developed by Ruelle, Bowen and others. (orig.)
Multifractal detrended cross-correlation analysis in the MENA area
El Alaoui, Marwane; Benbachir, Saâd
2013-12-01
In this paper, we investigated multifractal cross-correlations qualitatively and quantitatively using a cross-correlation test and the Multifractal detrended cross-correlation analysis method (MF-DCCA) for markets in the MENA area. We used cross-correlation coefficients to measure the level of this correlation. The analysis concerns four stock market indices of Morocco, Tunisia, Egypt and Jordan. The countries chosen are signatory of the Agadir agreement concerning the establishment of a free trade area comprising Arab Mediterranean countries. We computed the bivariate generalized Hurst exponent, Rényi exponent and spectrum of singularity for each pair of indices to measure quantitatively the cross-correlations. By analyzing the results, we found the existence of multifractal cross-correlations between all of these markets. We compared the spectrum width of these indices; we also found which pair of indices has a strong multifractal cross-correlation.
Prioritizing Signaling Information Transmission in Next Generation Networks
Directory of Open Access Journals (Sweden)
Jasmina Baraković
2011-01-01
Full Text Available Next generation transport network is characterized by the use of in-band signaling, where Internet Protocol (IP packets carrying signaling or media information are mixed in transmission. Since transport resources are limited, when any segment of access or core network is congested, IP packets carrying signaling information may be discarded. As a consequence, it may be impossible to implement reachability and quality of service (QoS. Since present approaches are insufficient to completely address this problem, a novel approach is proposed, which is based on prioritizing signaling information transmission. To proof the concept, a simulation study was performed using Network Simulator version 2 (ns-2 and independently developed Session Initiation Protocol (SIP module. The obtained results were statistically processed using Statistical Package for the Social Sciences (SPSS version 15.0. Summarizing our research results, several issues are identified for future work.
An artificial neural network model for periodic trajectory generation
Shankar, S.; Gander, R. E.; Wood, H. C.
A neural network model based on biological systems was developed for potential robotic application. The model consists of three interconnected layers of artificial neurons or units: an input layer subdivided into state and plan units, an output layer, and a hidden layer between the two outer layers which serves to implement nonlinear mappings between the input and output activation vectors. Weighted connections are created between the three layers, and learning is effected by modifying these weights. Feedback connections between the output and the input state serve to make the network operate as a finite state machine. The activation vector of the plan units of the input layer emulates the supraspinal commands in biological central pattern generators in that different plan activation vectors correspond to different sequences or trajectories being recalled, even with different frequencies. Three trajectories were chosen for implementation, and learning was accomplished in 10,000 trials. The fault tolerant behavior, adaptiveness, and phase maintenance of the implemented network are discussed.
Estimation of the global regularity of a multifractional Brownian motion
DEFF Research Database (Denmark)
Lebovits, Joachim; Podolskij, Mark
This paper presents a new estimator of the global regularity index of a multifractional Brownian motion. Our estimation method is based upon a ratio statistic, which compares the realized global quadratic variation of a multifractional Brownian motion at two different frequencies. We show that a ...... that a logarithmic transformation of this statistic converges in probability to the minimum of the Hurst functional parameter, which is, under weak assumptions, identical to the global regularity index of the path....
Multifractal characterisation and classification of bread crumb digital images
Baravalle, Rodrigo Guillermo; Delrieux, Claudio Augusto; Gómez, Juan Carlos
2017-01-01
Adequate models of the bread crumb structure can be critical for understanding flow and transport processes in bread manufacturing, creating synthetic bread crumb images for photo-realistic rendering, evaluating similarities, and establishing quality features of different bread crumb types. In this article, multifractal analysis, employing the multifractal spectrum (MFS), has been applied to study the structure of the bread crumb in four varieties of bread (baguette, sliced, bran, and sandwic...
Gender roles in social network sites from generation Y
Directory of Open Access Journals (Sweden)
F. Javier Rondan-Cataluña
2017-12-01
Full Text Available One of the fundamental and most commonly used communication tools by the generation Y or Millennials are online social networks. The first objective of this study is to model the effects that exercise social participation, community integration and trust in community satisfaction, as an antecedent of routinization. Besides, we propose as a second objective checking if gender roles proposed to underlie the different behaviors that develop social network users. An empirical study was carried out on a sample of 1,448 undergraduate students that are SNS users from Generation Y. First, we applied a structural equation modeling approach to test the proposed model. Second, we followed a methodology using a scale of masculinity and femininity to categorize the sample obtaining three groups: feminine, masculine, and androgynous.
Loss optimization in distribution networks with distributed generation
DEFF Research Database (Denmark)
Pokhrel, Basanta Raj; Nainar, Karthikeyan; Bak-Jensen, Birgitte
2017-01-01
This paper presents a novel power loss minimization approach in distribution grids considering network reconfiguration, distributed generation and storage installation. Identification of optimum configuration in such scenario is one of the main challenges faced by distribution system operators...... in highly active distribution grids. This issue is tackled by formulating a hybrid loss optimization problem and solved using the Interior Point Method. Sensitivity analysis is used to identify the optimum location of storage units. Different scenarios of reconfiguration, storage and distributed generation...... penetration are created to test the proposed algorithm. It is tested in a benchmark medium voltage network to show the effectiveness and performance of the algorithm. Results obtained are found to be encouraging for radial distribution system. It shows that we can reduce the power loss by more than 30% using...
Towards Third-Generation Living Lab Networks in Cities
Directory of Open Access Journals (Sweden)
Seppo Leminen
2017-11-01
Full Text Available Many cities engage in diverse experimentation, innovation, and development activities with a broad variety of environments and stakeholders to the benefit of citizens, companies, municipalities, and other organizations. Hence, this article discusses such engagement in terms of next-generation living lab networks in the city context. In so doing, the study contributes to the discussion on living labs by introducing a framework of collaborative innovation networks in cities and suggesting a typology of third-generation living labs. Our framework is characterized by diverse platforms and participation approaches, resulting in four distinctive modes of collaborative innovation networks where the city is: i a provider, ii a neighbourhood participator, iii a catalyst, or iv a rapid experimenter. The typology is based on an analysis of 118 interviews with participants in six Finnish cities and reveals various ways to organize innovation activities in the city context. In particular, cities can benefit from innovation networks by simultaneously exploiting multiple platforms such as living labs for innovation. We conclude by discussing implications to theory and practice, and suggesting directions for future research.
User-generated content curation with deep convolutional neural networks
Tous Liesa, Rubén; Wust, Otto; Gómez, Mauro; Poveda, Jonatan; Elena, Marc; Torres Viñals, Jordi; Makni, Mouna; Ayguadé Parra, Eduard
2016-01-01
In this paper, we report a work consisting in using deep convolutional neural networks (CNNs) for curating and filtering photos posted by social media users (Instagram and Twitter). The final goal is to facilitate searching and discovering user-generated content (UGC) with potential value for digital marketing tasks. The images are captured in real time and automatically annotated with multiple CNNs. Some of the CNNs perform generic object recognition tasks while others perform what we call v...
Two-dimensional multifractal cross-correlation analysis
International Nuclear Information System (INIS)
Xi, Caiping; Zhang, Shuning; Xiong, Gang; Zhao, Huichang; Yang, Yonghong
2017-01-01
Highlights: • We study the mathematical models of 2D-MFXPF, 2D-MFXDFA and 2D-MFXDMA. • Present the definition of the two-dimensional N 2 -partitioned multiplicative cascading process. • Do the comparative analysis of 2D-MC by 2D-MFXPF, 2D-MFXDFA and 2D-MFXDMA. • Provide a reference on the choice and parameter settings of these methods in practice. - Abstract: There are a number of situations in which several signals are simultaneously recorded in complex systems, which exhibit long-term power-law cross-correlations. This paper presents two-dimensional multifractal cross-correlation analysis based on the partition function (2D-MFXPF), two-dimensional multifractal cross-correlation analysis based on the detrended fluctuation analysis (2D-MFXDFA) and two-dimensional multifractal cross-correlation analysis based on the detrended moving average analysis (2D-MFXDMA). We apply these methods to pairs of two-dimensional multiplicative cascades (2D-MC) to do a comparative study. Then, we apply the two-dimensional multifractal cross-correlation analysis based on the detrended fluctuation analysis (2D-MFXDFA) to real images and unveil intriguing multifractality in the cross correlations of the material structures. At last, we give the main conclusions and provide a valuable reference on how to choose the multifractal algorithms in the potential applications in the field of SAR image classification and detection.
Investigation of multifractality in the Brazilian stock market
Maganini, Natália Diniz; Da Silva Filho, Antônio Carlos; Lima, Fabiano Guasti
2018-05-01
Many studies point to a possible new stylized fact for financial time series: the multifractality. Several authors have already detected this characteristic in multiple time series in several countries. With that in mind and based on Multifractal Detrended Fluctuation Analysis (MFDFA) method, this paper analyzes the multifractality in the Brazilian market. This analysis is performed with daily data from IBOVESPA index (Brazilian stock exchange's main index) and other four highly marketable stocks in the Brazilian market (VALE5, ITUB4, BBDC4 and CIEL3), which represent more than 25% of the index composition, making up 1961 observations for each asset in the period from June 26 2009 to May 31 2017. We found that the studied stock prices and Brazilian index are multifractal, but that the multifractality degree is not the same for all the assets. The use of shuffled and surrogated series indicates that for the period and the actions considered the long-range correlations do not strongly influence the multifractality, but the distribution (fat tails) exerts a possible influence on IBOVESPA and CIEL3.
Multifractal Model of Soil Water Erosion
Oleshko, Klaudia
2017-04-01
Breaking of solid surface symmetry during the interaction between the rainfall of high erosivity index and internally unstable volcanic soil/vegetation systems, results in roughness increasing as well as fertile horizon loosing. In these areas, the sustainability of management practices depends on the ability to select and implement the precise indicators of soil erodibility and vegetation capacity to protect the system against the extreme damaging precipitation events. Notwithstanding, the complex, non-linear and scaling nature of the phenomena involved in the interaction among the soil, vegetation and precipitation is still not taken into account by the numerous commonly used empirical, mathematical and computer simulation models: for instance, by the universal soil loss equation (USLE). The soil erodibility factor (K-factor) is still measuring by a set of empirical, dimensionless parameters and indexes, without taking into account the scaling (frequently multifractal) origin of a broad range of heterogeneous, anisotropic and dynamical phenomena involved in hydric erosion. Their mapping is not representative of this complex system spatial variability. In our research, we propose to use the toolbox of fractals and multifractals techniques in vista of its ability to measure the scale invariance and type/degree of soil, vegetation and precipitation symmetry breaking. The hydraulic units are chosen as the precise measure of soil/vegetation stability. These units are measured and modeled for soils with contrasting architecture, based on their porosity/permeability (Poroperm) as well as retention capacity relations. The simple Catalog of the most common Poroperm relations is proposed and the main power law relations among the elements of studied system are established and compared for some representative agricultural and natural Biogeosystems of Mexico. All resulted are related with the Mandelbrot' Baby Theorem in order to construct the universal Phase Diagram which
Multifractal analysis of a GCM climate
Carl, P.
2003-04-01
Multifractal analysis using the Wavelet Transform Modulus Maxima (WTMM) approach is being applied to the climate of a Mintz--Arakawa type, coarse resolution, two--layer AGCM. The model shows a backwards running period multiplication scenario throughout the northern summer, subsequent to a 'hard', subcritical Hopf bifurcation late in spring. This 'route out of chaos' (seen in cross sections of a toroidal phase space structure) is born in the planetary monsoon system which inflates the seasonal 'cycle' into these higher order structures and is blamed for the pronounced intraseasonal--to--centennial model climate variability. Previous analyses of the latter using advanced modal decompositions showed regularity based patterns in the time--frequency plane which are qualitatively similar to those obtained from the real world. The closer look here at the singularity structures, as a fundamental diagnostic supplement, aims at both more complete understanding (and quantification) of the model's qualitative dynamics and search for further tools of model intercomparison and verification in this respect. Analysing wavelet is the 10th derivative of the Gaussian which might suffice to suppress regular patterns in the data. Intraseasonal attractors, studied in time series of model precipitation over Central India, show shifting and braodening singularity spectra towards both more violent extreme events (premonsoon--monsoon transition) and weaker events (late summer to postmonsoon transition). Hints at a fractal basin boundary are found close to transition from period--2 to period--1 in the monsoon activity cycle. Interannual analyses are provided for runs with varied solar constants. To address the (in--)stationarity issue, first results are presented with a windowed multifractal analysis of longer--term runs ("singularity spectrogram").
Generation and prediction of time series by a neural network
International Nuclear Information System (INIS)
Eisenstein, E.; Kanter, I.; Kessler, D.A.; Kinzel, W.
1995-01-01
Generation and prediction of time series are analyzed for the case of a bit generator: a perceptron where in each time step the input units are shifted one bit to the right with the state of the leftmost input unit set equal to the output unit in the previous time step. The long-time dynamical behavior of the bit generator consists of cycles whose typical period scales polynomially with the size of the network and whose spatial structure is periodic with a typical finite wavelength. The generalization error on a cycle is zero for a finite training set, and global dynamical behaviors can also be learned in a finite time. Hence, a projection of a rule can be learned in a finite time
Small Distributed Renewable Energy Generation for Low Voltage Distribution Networks
Directory of Open Access Journals (Sweden)
Chindris M.
2016-08-01
Full Text Available Driven by the existing energy policies, the use of renewable energy has increased considerably all over the world in order to respond to the increasing energy consumption and to reduce the environmental impact of the electricity generation. Although most policy makers and companies are focusing on large applications, the use of cheap small generation units, based on local renewable resources, has become increasingly attractive for the general public, small farms and remote communities. The paper presents several results of a research project aiming to identify the power quality issues and the impact of RES based distributed generation (DG or other non-linear loads on low voltage (LV distribution networks in Romania; the final goal is to develop a Universal Power Quality Conditioner (UPQC able to diminish the existing disturbances. Basically, the work analyses the existing DG technologies and identifies possible solutions for their integration in Romania; taking into account the existent state of the art, the attention was paid on small systems, using wind and solar energy, and on possibility to integrate them into suburban and rural LV distribution networks. The presence of DG units at distribution voltage level means the transition from traditional passive to active distribution networks. In general, the relatively low penetration levels of DG does not produce problems; however, the nowadays massive increase of local power generation have led to new integration challenges in order to ensure the reliability and quality of the power supply. Power quality issues are identified and their assessment is the key element in the design of measures aiming to diminish all existing disturbances.
Directory of Open Access Journals (Sweden)
Xuefei Wu
2014-01-01
Full Text Available A novel linear complex system for hydroturbine-generator sets in multimachine power systems is suggested in this paper and synchronization of the power-grid networks is studied. The advanced graph theory and stability theory are combined to solve the problem. Here we derive a sufficient condition under which the synchronous state of power-grid networks is stable in disturbance attenuation. Finally, numerical simulations are provided to illustrate the effectiveness of the results by the IEEE 39 bus system.
Understanding the Generation of Network Bursts by Adaptive Oscillatory Neurons
Directory of Open Access Journals (Sweden)
Tanguy Fardet
2018-02-01
Full Text Available Experimental and numerical studies have revealed that isolated populations of oscillatory neurons can spontaneously synchronize and generate periodic bursts involving the whole network. Such a behavior has notably been observed for cultured neurons in rodent's cortex or hippocampus. We show here that a sufficient condition for this network bursting is the presence of an excitatory population of oscillatory neurons which displays spike-driven adaptation. We provide an analytic model to analyze network bursts generated by coupled adaptive exponential integrate-and-fire neurons. We show that, for strong synaptic coupling, intrinsically tonic spiking neurons evolve to reach a synchronized intermittent bursting state. The presence of inhibitory neurons or plastic synapses can then modulate this dynamics in many ways but is not necessary for its appearance. Thanks to a simple self-consistent equation, our model gives an intuitive and semi-quantitative tool to understand the bursting behavior. Furthermore, it suggests that after-hyperpolarization currents are sufficient to explain bursting termination. Through a thorough mapping between the theoretical parameters and ion-channel properties, we discuss the biological mechanisms that could be involved and the relevance of the explored parameter-space. Such an insight enables us to propose experimentally-testable predictions regarding how blocking fast, medium or slow after-hyperpolarization channels would affect the firing rate and burst duration, as well as the interburst interval.
Handover Based IMS Registration Scheme for Next Generation Mobile Networks
Directory of Open Access Journals (Sweden)
Shireen Tahira
2017-01-01
Full Text Available Next generation mobile networks aim to provide faster speed and more capacity along with energy efficiency to support video streaming and massive data sharing in social and communication networks. In these networks, user equipment has to register with IP Multimedia Subsystem (IMS which promises quality of service to the mobile users that frequently move across different access networks. After each handover caused due to mobility, IMS provides IPSec Security Association establishment and authentication phases. The main issue is that unnecessary reregistration after every handover results in latency and communication overhead. To tackle these issues, this paper presents a lightweight Fast IMS Mobility (FIM registration scheme that avoids unnecessary conventional registration phases such as security associations, authentication, and authorization. FIM maintains a flag to avoid deregistration and sends a subsequent message to provide necessary parameters to IMS servers after mobility. It also handles the change of IP address for user equipment and transferring the security associations from old to new servers. We have validated the performance of FIM by developing a testbed consisting of IMS servers and user equipment. The experimental results demonstrate the performance supremacy of FIM. It reduces media disruption time, number of messages, and packet loss up to 67%, 100%, and 61%, respectively, as compared to preliminaries.
Detection of mobile user location on next generation wireless networks
DEFF Research Database (Denmark)
Schou, Saowanee; Olesen, Henning
2005-01-01
This paper proposes a novel conceptual mechanism for detecting the location of a mobile user on next generation wireless networks. This mechanism can provide location information of a mobile user at different levels of accuracy, by applying the movement detection mechanism of Mobile IPv6 at both...... macro- and micromobility level. In this scheme, an intradomain mobility management protocol (IDMP) is applied to manage the location of the mobile terminal. The mobile terminal needs two care-of addresses, a global care-of address (GCoA) and a local care-of address (LCoA). The current location...... of a Mobile IPv6 device can be determined by mapping the geographical location information with the two care-of-addresses and the physical address of the access point where the user is connected. Such a mechanism makes location services for mobile entities available on a global IP network. The end-users can...
Prediction of municipal solid waste generation using nonlinear autoregressive network.
Younes, Mohammad K; Nopiah, Z M; Basri, N E Ahmad; Basri, H; Abushammala, Mohammed F M; Maulud, K N A
2015-12-01
Most of the developing countries have solid waste management problems. Solid waste strategic planning requires accurate prediction of the quality and quantity of the generated waste. In developing countries, such as Malaysia, the solid waste generation rate is increasing rapidly, due to population growth and new consumption trends that characterize society. This paper proposes an artificial neural network (ANN) approach using feedforward nonlinear autoregressive network with exogenous inputs (NARX) to predict annual solid waste generation in relation to demographic and economic variables like population number, gross domestic product, electricity demand per capita and employment and unemployment numbers. In addition, variable selection procedures are also developed to select a significant explanatory variable. The model evaluation was performed using coefficient of determination (R(2)) and mean square error (MSE). The optimum model that produced the lowest testing MSE (2.46) and the highest R(2) (0.97) had three inputs (gross domestic product, population and employment), eight neurons and one lag in the hidden layer, and used Fletcher-Powell's conjugate gradient as the training algorithm.
Artificial earthquake record generation using cascade neural network
Directory of Open Access Journals (Sweden)
Bani-Hani Khaldoon A.
2017-01-01
Full Text Available This paper presents the results of using artificial neural networks (ANN in an inverse mapping problem for earthquake accelerograms generation. This study comprises of two parts: 1-D site response analysis; performed for Dubai Emirate at UAE, where eight earthquakes records are selected and spectral matching are performed to match Dubai response spectrum using SeismoMatch software. Site classification of Dubai soil is being considered for two classes C and D based on shear wave velocity of soil profiles. Amplifications factors are estimated to quantify Dubai soil effect. Dubai’s design response spectra are developed for site classes C & D according to International Buildings Code (IBC -2012. In the second part, ANN is employed to solve inverse mapping problem to generate time history earthquake record. Thirty earthquakes records and their design response spectrum with 5% damping are used to train two cascade forward backward neural networks (ANN1, ANN2. ANN1 is trained to map the design response spectrum to time history and ANN2 is trained to map time history records to the design response spectrum. Generalized time history earthquake records are generated using ANN1 for Dubai’s site classes C and D, and ANN2 is used to evaluate the performance of ANN1.
Neural network based daily precipitation generator (NNGEN-P)
Energy Technology Data Exchange (ETDEWEB)
Boulanger, Jean-Philippe [LODYC, UMR CNRS/IRD/UPMC, Paris (France); University of Buenos Aires, Departamento de Ciencias de la Atmosfera y los Oceanos, Facultad de Ciencias Exactas y Naturales, Buenos Aires (Argentina); Martinez, Fernando; Segura, Enrique C. [University of Buenos Aires, Departamento de Computacion, Facultad de Ciencias Exactas y Naturales, Buenos Aires (Argentina); Penalba, Olga [University of Buenos Aires, Departamento de Ciencias de la Atmosfera y los Oceanos, Facultad de Ciencias Exactas y Naturales, Buenos Aires (Argentina)
2007-02-15
Daily weather generators are used in many applications and risk analyses. The present paper explores the potential of neural network architectures to design daily weather generator models. Focusing this first paper on precipitation, we design a collection of neural networks (multi-layer perceptrons in the present case), which are trained so as to approximate the empirical cumulative distribution (CDF) function for the occurrence of wet and dry spells and for the precipitation amounts. This approach contributes to correct some of the biases of the usual two-step weather generator models. As compared to a rainfall occurrence Markov model, NNGEN-P represents fairly well the mean and standard deviation of the number of wet days per month, and it significantly improves the simulation of the longest dry and wet periods. Then, we compared NNGEN-P to three parametric distribution functions usually applied to fit rainfall cumulative distribution functions (Gamma, Weibull and double-exponential). A data set of 19 Argentine stations was used. Also, data corresponding to stations in the United States, in Europe and in the Tropics were included to confirm the results. One of the advantages of NNGEN-P is that it is non-parametric. Unlike other parametric function, which adapt to certain types of climate regimes, NNGEN-P is fully adaptive to the observed cumulative distribution functions, which, on some occasions, may present complex shapes. On-going works will soon produce an extended version of NNGEN to temperature and radiation. (orig.)
Advanced optical components for next-generation photonic networks
Yoo, S. J. B.
2003-08-01
Future networks will require very high throughput, carrying dominantly data-centric traffic. The role of Photonic Networks employing all-optical systems will become increasingly important in providing scalable bandwidth, agile reconfigurability, and low-power consumptions in the future. In particular, the self-similar nature of data traffic indicates that packet switching and burst switching will be beneficial in the Next Generation Photonic Networks. While the natural conclusion is to pursue Photonic Packet Switching and Photonic Burst Switching systems, there are significant challenges in realizing such a system due to practical limitations in optical component technologies. Lack of a viable all-optical memory technology will continue to drive us towards exploring rapid reconfigurability in the wavelength domain. We will introduce and discuss the advanced optical component technologies behind the Photonic Packet Routing system designed and demonstrated at UC Davis. The system is capable of packet switching and burst switching, as well as circuit switching with 600 psec switching speed and scalability to 42 petabit/sec aggregated switching capacity. By utilizing a combination of rapidly tunable wavelength conversion and a uniform-loss cyclic frequency (ULCF) arrayed waveguide grating router (AWGR), the system is capable of rapidly switching the packets in wavelength, time, and space domains. The label swapping module inside the Photonic Packet Routing system containing a Mach-Zehnder wavelength converter and a narrow-band fiber Bragg-grating achieves all-optical label swapping with optical 2R (potentially 3R) regeneration while maintaining optical transparency for the data payload. By utilizing the advanced optical component technologies, the Photonic Packet Routing system successfully demonstrated error-free, cascaded, multi-hop photonic packet switching and routing with optical-label swapping. This paper will review the advanced optical component technologies
Multifractal spatial patterns and diversity in an ecological succession.
Directory of Open Access Journals (Sweden)
Leonardo Ariel Saravia
Full Text Available We analyzed the relationship between biodiversity and spatial biomass heterogeneity along an ecological succession developed in the laboratory. Periphyton (attached microalgae biomass spatial patterns at several successional stages were obtained using digital image analysis and at the same time we estimated the species composition and abundance. We show that the spatial pattern was self-similar and as the community developed in an homogeneous environment the pattern is self-organized. To characterize it we estimated the multifractal spectrum of generalized dimensions D(q. Using D(q we analyze the existence of cycles of heterogeneity during succession and the use of the information dimension D(1 as an index of successional stage. We did not find cycles but the values of D(1 showed an increasing trend as the succession developed and the biomass was higher. D(1 was also negatively correlated with Shannon's diversity. Several studies have found this relationship in different ecosystems but here we prove that the community self-organizes and generates its own spatial heterogeneity influencing diversity. If this is confirmed with more experimental and theoretical evidence D(1 could be used as an index, easily calculated from remote sensing data, to detect high or low diversity areas.
Custom Topology Generation for Network-on-Chip
DEFF Research Database (Denmark)
Stuart, Matthias Bo; Sparsø, Jens
2007-01-01
This paper compares simulated annealing and tabu search for generating custom topologies for applications with periodic behaviour executing on a network-on-chip. The approach differs from previous work by starting from a fixed mapping of IP-cores to routers and performing design space exploration...... around an initial topology. The tabu search has been modified from its normally encountered form to allow easier escaping from local minima. A number of synthetic benchmarks are used for tuning the parameters of both heuristics and for testing the quality of the solutions each heuristic produces...
Wireless next generation networks a virtue-based trust model
Harvey, Melissa
2014-01-01
This SpringerBrief proposes a trust model motivated by virtue epistemology, addressing the need for a more efficient and flexible trust model for wireless next generation networks. This theory of trust simplifies the computation and communication overhead of strictly cognitive-computational models of trust. Both the advantages and the challenges of virtue-based trust models are discussed. This brief offers new research and a general theory of rationality that enables users to interpret trust and reason as complementary mechanisms that guide our rational conduct at two different epistemic level
Reactive power management of power networks with wind generation
Amaris, Hortensia; Ortega, Carlos Alvarez
2012-01-01
As the energy sector shifts and changes to focus on renewable technologies, the optimization of wind power becomes a key practical issue. Reactive Power Management of Power Networks with Wind Generation brings into focus the development and application of advanced optimization techniques to the study, characterization, and assessment of voltage stability in power systems. Recent advances on reactive power management are reviewed with particular emphasis on the analysis and control of wind energy conversion systems and FACTS devices. Following an introduction, distinct chapters cover the 5 key
The European Nuclear Society Young Generation Network: Five years of networking experience
International Nuclear Information System (INIS)
Meskens, Gaston
2000-01-01
In 1995, Mr Jan Runermark (Sweden), aware of a need for an exchange of knowledge from the older to the younger generation, came up with the idea of starting a European Nuclear Society Young Generation Network. A first network was formed with Sweden, the Netherlands, Spain, Finland, Germany and Belgium. The ENSYGN is now affiliated to the European Nuclear Society and brings together young students and professionals from 21 member countries Belgium, Bulgaria, Croatia, Czech Republic, Denmark Finland, France, Germany, Hungary, Italy, Netherlands, Poland, Romania, Russia, Slovak Republic, Slovenia, Spain, Sweden, Switzerland, Ukraine, and United Kingdom, The ENSYGN Core group meets (at least) twice a year and elects its own chair and co chair for a term of two years. The ENSYGN chair has a seat in the ENS Steering Committee and in the ENS Board. The ENSYGN works closely together with other young generation networks from the US, Australia, Japan and South America. ENSYGN organises workshops and courses on European level, takes part in international meetings (fl. UNFCCC, OECD) and stimulates networking on national level
Implementing Value Added Applications in Next Generation Networks
Directory of Open Access Journals (Sweden)
Yuan-Kuang Tu
2010-08-01
Full Text Available One of the major issues in the future Internet is the integration of telecom networks with the Internet. In many countries, large Internet Service Providers (ISPs are also telecom operators that have been focusing on providing Internet services through their telecom networks with telecom-grade mechanisms. In this article, we show that IP Multimedia Subsystem (IMS is a telecom-grade mechanism that addresses this important issue. In Next Generation Network (NGN, IMS supports IP-based multimedia services that can be accessed from various wireless and wired access technologies through fixed-mobile convergence. We show how to integrate Internet Protocol Television (IPTV with NGN/IMS to offer enhanced IPTV services for subscribers with set-top boxes or mobile phones. We specifically describe the implementations of three services: weather forecasts, short messages on TV screens and TV shopping/food ordering for mobile users. Although these services can be directly implemented in the Internet, our commercial operation experiences indicate that the NGN/IMS implementation has advantages in terms of telecom-grade security, Quality of Service (QoS, and flexible service creation.
An Intelligent Handover Management System for Future Generation Wireless Networks
Directory of Open Access Journals (Sweden)
Kassar Meriem
2008-01-01
Full Text Available Abstract Future generation wireless networks should provide to mobile users the best connectivity to services anywhere at anytime. The most challenging problem is the seamless intersystem/vertical mobility across heterogeneous wireless networks. In order to answer it, a vertical handover management system is needed. In our paper, we propose an intelligent solution answering user requirements and ensuring service continuity. We focus on a vertical handover decision strategy based on the context-awareness concept. The given strategy chooses the appropriate time and the most suitable access network among those available to perform a handover. It uses advanced decision algorithms (for more efficiency and intelligence and it is governed by handover policies as decision rules (for more flexibility and optimization. To maintain a seamless service continuity, handover execution is based on mobile IP functionalities. We study our decision system in a case of a 3G/UMTS-WLAN scenario and we discuss all the handover decision issues in our solution.
StackGAN++: Realistic Image Synthesis with Stacked Generative Adversarial Networks
Zhang, Han; Xu, Tao; Li, Hongsheng; Zhang, Shaoting; Wang, Xiaogang; Huang, Xiaolei; Metaxas, Dimitris
2017-01-01
Although Generative Adversarial Networks (GANs) have shown remarkable success in various tasks, they still face challenges in generating high quality images. In this paper, we propose Stacked Generative Adversarial Networks (StackGAN) aiming at generating high-resolution photo-realistic images. First, we propose a two-stage generative adversarial network architecture, StackGAN-v1, for text-to-image synthesis. The Stage-I GAN sketches the primitive shape and colors of the object based on given...
Improved moment scaling estimation for multifractal signals
Directory of Open Access Journals (Sweden)
D. Veneziano
2009-11-01
Full Text Available A fundamental problem in the analysis of multifractal processes is to estimate the scaling exponent K(q of moments of different order q from data. Conventional estimators use the empirical moments μ^_{r}^{q}=⟨ | ε_{r}(τ|^{q}⟩ of wavelet coefficients ε_{r}(τ, where τ is location and r is resolution. For stationary measures one usually considers "wavelets of order 0" (averages, whereas for functions with multifractal increments one must use wavelets of order at least 1. One obtains K^(q as the slope of log( μ^_{r}^{q} against log(r over a range of r. Negative moments are sensitive to measurement noise and quantization. For them, one typically uses only the local maxima of | ε_{r}(τ| (modulus maxima methods. For the positive moments, we modify the standard estimator K^(q to significantly reduce its variance at the expense of a modest increase in the bias. This is done by separately estimating K(q from sub-records and averaging the results. For the negative moments, we show that the standard modulus maxima estimator is biased and, in the case of additive noise or quantization, is not applicable with wavelets of order 1 or higher. For these cases we propose alternative estimators. We also consider the fitting of parametric models of K(q and show how, by splitting the record into sub-records as indicated above, the accuracy of standard methods can be significantly improved.
Finite-size effect and the components of multifractality in financial volatility
International Nuclear Information System (INIS)
Zhou Weixing
2012-01-01
Highlights: ► The apparent multifractality can be decomposed quantitatively. ► There is a marked finite-size effect in the detection of multifractality. ► The effective multifractality can be further decomposed into two components. ► A time series exhibits effective multifractality only if it possesses nonlinearity. ► The daily DJIA volatility is analyzed as an example. - Abstract: Many financial variables are found to exhibit multifractal nature, which is usually attributed to the influence of temporal correlations and fat-tailedness in the probability distribution (PDF). Based on the partition function approach of multifractal analysis, we show that there is a marked finite-size effect in the detection of multifractality, and the effective multifractality is the apparent multifractality after removing the finite-size effect. We find that the effective multifractality can be further decomposed into two components, the PDF component and the nonlinearity component. Referring to the normal distribution, we can determine the PDF component by comparing the effective multifractality of the original time series and the surrogate data that have a normal distribution and keep the same linear and nonlinear correlations as the original data. We demonstrate our method by taking the daily volatility data of Dow Jones Industrial Average from 26 May 1896 to 27 April 2007 as an example. Extensive numerical experiments show that a time series exhibits effective multifractality only if it possesses nonlinearity and the PDF has an impact on the effective multifractality only when the time series possesses nonlinearity. Our method can also be applied to judge the presence of multifractality and determine its components of multifractal time series in other complex systems.
Generative Recurrent Networks for De Novo Drug Design.
Gupta, Anvita; Müller, Alex T; Huisman, Berend J H; Fuchs, Jens A; Schneider, Petra; Schneider, Gisbert
2018-01-01
Generative artificial intelligence models present a fresh approach to chemogenomics and de novo drug design, as they provide researchers with the ability to narrow down their search of the chemical space and focus on regions of interest. We present a method for molecular de novo design that utilizes generative recurrent neural networks (RNN) containing long short-term memory (LSTM) cells. This computational model captured the syntax of molecular representation in terms of SMILES strings with close to perfect accuracy. The learned pattern probabilities can be used for de novo SMILES generation. This molecular design concept eliminates the need for virtual compound library enumeration. By employing transfer learning, we fine-tuned the RNN's predictions for specific molecular targets. This approach enables virtual compound design without requiring secondary or external activity prediction, which could introduce error or unwanted bias. The results obtained advocate this generative RNN-LSTM system for high-impact use cases, such as low-data drug discovery, fragment based molecular design, and hit-to-lead optimization for diverse drug targets. © 2017 The Authors. Published by Wiley-VCH Verlag GmbH & Co. KGaA.
Optimal power flow for distribution networks with distributed generation
Directory of Open Access Journals (Sweden)
Radosavljević Jordan
2015-01-01
Full Text Available This paper presents a genetic algorithm (GA based approach for the solution of the optimal power flow (OPF in distribution networks with distributed generation (DG units, including fuel cells, micro turbines, diesel generators, photovoltaic systems and wind turbines. The OPF is formulated as a nonlinear multi-objective optimization problem with equality and inequality constraints. Due to the stochastic nature of energy produced from renewable sources, i.e. wind turbines and photovoltaic systems, as well as load uncertainties, a probabilisticalgorithm is introduced in the OPF analysis. The Weibull and normal distributions are employed to model the input random variables, namely the wind speed, solar irradiance and load power. The 2m+1 point estimate method and the Gram Charlier expansion theory are used to obtain the statistical moments and the probability density functions (PDFs of the OPF results. The proposed approach is examined and tested on a modified IEEE 34 node test feeder with integrated five different DG units. The obtained results prove the efficiency of the proposed approach to solve both deterministic and probabilistic OPF problems for different forms of the multi-objective function. As such, it can serve as a useful decision-making supporting tool for distribution network operators. [Projekat Ministarstva nauke Republike Srbije, br. TR33046
Integrating generation and transmission networks reliability for unit commitment solution
International Nuclear Information System (INIS)
Jalilzadeh, S.; Shayeghi, H.; Hadadian, H.
2009-01-01
This paper presents a new method with integration of generation and transmission networks reliability for the solution of unit commitment (UC) problem. In fact, in order to have a more accurate assessment of system reserve requirement, in addition to unavailability of generation units, unavailability of transmission lines are also taken into account. In this way, evaluation of the required spinning reserve (SR) capacity is performed by applying reliability constraints based on loss of load probability and expected energy not supplied (EENS) indices. Calculation of the above parameters is accomplished by employing a novel procedure based on the linear programming which it also minimizes them to achieve optimum level of the SR capacity and consequently a cost-benefit reliability constrained UC schedule. In addition, a powerful solution technique called 'integer-coded genetic algorithm (ICGA)' is being used for the solution of the proposed method. Numerical results on the IEEE reliability test system show that the consideration of transmission network unavailability has an important influence on reliability indices of the UC schedules
Dynamic simulation of a steam generator by neural networks
International Nuclear Information System (INIS)
Masini, R.; Padovani, E.; Ricotti, M.E.; Zio, E.
1999-01-01
Numerical simulation by computers of the dynamic evolution of complex systems and components is a fundamental phase of any modern engineering design activity. This is of particular importance for risk-based design projects which require that the system behavior be analyzed under several and often extreme conditions. The traditional methods of simulation typically entail long, iterative, processes which lead to large simulation times, often exceeding the transients real time. Artificial neural networks (ANNs) may be exploited in this context, their advantages residing mainly in the speed of computation, in the capability of generalizing from few examples, in the robustness to noisy and partially incomplete data and in the capability of performing empirical input-output mapping without complete knowledge of the underlying physics. In this paper we present a novel approach to dynamic simulation by ANNs based on a superposition scheme in which a set of networks are individually trained, each one to respond to a different input forcing function. The dynamic simulation of a steam generator is considered as an example to show the potentialities of this tool and to point out the difficulties and crucial issues which typically arise when attempting to establish an efficient neural network simulator. The structure of the networks system is such to feedback, at each time step, a portion of the past evolution of the transient and this allows a good reproduction of also non-linear dynamic behaviors. A nice characteristic of the approach is that the modularization of the training reduces substantially its burden and gives this neural simulation tool a nice feature of transportability. (orig.)
Modeling of steam generator in nuclear power plant using neural network ensemble
International Nuclear Information System (INIS)
Lee, S. K.; Lee, E. C.; Jang, J. W.
2003-01-01
Neural network is now being used in modeling the steam generator is known to be difficult due to the reverse dynamics. However, Neural network is prone to the problem of overfitting. This paper investigates the use of neural network combining methods to model steam generator water level and compares with single neural network. The results show that neural network ensemble is effective tool which can offer improved generalization, lower dependence of the training set and reduced training time
Multifractal analysis of oceanic chlorophyll maps remotely sensed from space
Directory of Open Access Journals (Sweden)
L. de Montera
2011-03-01
Full Text Available Phytoplankton patchiness has been investigated with multifractal analysis techniques. We analyzed oceanic chlorophyll maps, measured by the SeaWiFS orbiting sensor, which are considered to be good proxies for phytoplankton. The study area is the Senegalo-Mauritanian upwelling region, because it has a low cloud cover and high chlorophyll concentrations. Multifractal properties are observed, from the sub-mesoscale up to the mesoscale, and are found to be consistent with the Corssin-Obukhov scale law of passive scalars. This result indicates that, in this specific region and within this scale range, turbulent mixing would be the dominant effect leading to the observed variability of phytoplankton fields. Finally, it is shown that multifractal patchiness can be responsible for significant biases in the nonlinear source and sink terms involved in biogeochemical numerical models.
Coupled uncertainty provided by a multifractal random walker
International Nuclear Information System (INIS)
Koohi Lai, Z.; Vasheghani Farahani, S.; Movahed, S.M.S.; Jafari, G.R.
2015-01-01
The aim here is to study the concept of pairing multifractality between time series possessing non-Gaussian distributions. The increasing number of rare events creates “criticality”. We show how the pairing between two series is affected by rare events, which we call “coupled criticality”. A method is proposed for studying the coupled criticality born out of the interaction between two series, using the bivariate multifractal random walk (BiMRW). This method allows studying dependence of the coupled criticality on the criticality of each individual system. This approach is applied to data sets of gold and oil markets, and inflation and unemployment. - Highlights: • The coupled criticality between two systems is modeled by the bivariate multifractal random walk. • This coupled criticality is generally directed. • This coupled criticality is inversely proportional to the criticality of either of the systems. • The coupled criticality can emerge when at least one of the systems posses a Gaussian distribution
Multifractal structure of multiplicity distributions and negative binomials
International Nuclear Information System (INIS)
Malik, S.; Delhi, Univ.
1997-01-01
The paper presents experimental results of the multifractal structure analysis in proton-emulsion interactions at 800 GeV. The multiplicity moments have a power law dependence on the mean multiplicity in varying bin sizes of pseudorapidity. The values of generalised dimensions are calculated from the slope value. The multifractal characteristics are also examined in the light of negative binomials. The observed multiplicity moments and those derived from the negative-binomial fits agree well with each other. Also the values of D q , both observed and derived from the negative-binomial fits not only decrease with q typifying multifractality but also agree well each other showing consistency with the negative-binomial form
Multifractal Detrended Cross-Correlation Analysis of agricultural futures markets
International Nuclear Information System (INIS)
He Lingyun; Chen Shupeng
2011-01-01
Highlights: → We investigated cross-correlations between China's and US agricultural futures markets. → Power-law cross-correlations are found between the geographically far but correlated markets. → Multifractal features are significant in all the markets. → Cross-correlation exponent is less than averaged GHE when q 0. - Abstract: We investigated geographically far but temporally correlated China's and US agricultural futures markets. We found that there exists a power-law cross-correlation between them, and that multifractal features are significant in all the markets. It is very interesting that the geographically far markets show strong cross-correlations and share much of their multifractal structure. Furthermore, we found that for all the agricultural futures markets in our studies, the cross-correlation exponent is less than the averaged generalized Hurst exponents (GHE) when q 0.
EXOPLANETARY DETECTION BY MULTIFRACTAL SPECTRAL ANALYSIS
Energy Technology Data Exchange (ETDEWEB)
Agarwal, Sahil; Wettlaufer, John S. [Program in Applied Mathematics, Yale University, New Haven, CT (United States); Sordo, Fabio Del [Department of Astronomy, Yale University, New Haven, CT (United States)
2017-01-01
Owing to technological advances, the number of exoplanets discovered has risen dramatically in the last few years. However, when trying to observe Earth analogs, it is often difficult to test the veracity of detection. We have developed a new approach to the analysis of exoplanetary spectral observations based on temporal multifractality, which identifies timescales that characterize planetary orbital motion around the host star and those that arise from stellar features such as spots. Without fitting stellar models to spectral data, we show how the planetary signal can be robustly detected from noisy data using noise amplitude as a source of information. For observation of transiting planets, combining this method with simple geometry allows us to relate the timescales obtained to primary and secondary eclipse of the exoplanets. Making use of data obtained with ground-based and space-based observations we have tested our approach on HD 189733b. Moreover, we have investigated the use of this technique in measuring planetary orbital motion via Doppler shift detection. Finally, we have analyzed synthetic spectra obtained using the SOAP 2.0 tool, which simulates a stellar spectrum and the influence of the presence of a planet or a spot on that spectrum over one orbital period. We have demonstrated that, so long as the signal-to-noise-ratio ≥ 75, our approach reconstructs the planetary orbital period, as well as the rotation period of a spot on the stellar surface.
Repair during multifraction exposures: spheroids versus monolayers
International Nuclear Information System (INIS)
Durand, R.E.
1984-01-01
Many type of mammalian cells, when grown in culture as multicell spheroids, display an increased ability to accumulate and repair sublethal radiation damage which has been called the ''contact effect''. Since this effect has the potential to markedly modify the multifraction radiation response of cells in V79 spheroids relative to cells in monolayer cultures, an investigation was made of regimens ranging from 1 to 100 fractions. Effective dose rates were chosen near 1 Gy h -1 to inhibit cell progression and thus simplify analysis of the results. As expected, larger doses per fraction produced more net cell killing in both systems than lower doses per fraction. Additionally, less killing of spheroid cells was observed in all regimens, in accord with their greater potential for repair. However, when the data were expressed as isoeffect curves, the spheroid and monolayer curves converged as the number of fractions increased. Thus, quite similar inherent sensitivity and repair capabilities would be predicted for ultra-low doses per fraction. High precision techniques for defining survival after doses of radiation from 0.2 to 1 Gy were, however, still able to demonstrate a survival advantage for cells grown as spheroids. (author)
Directory of Open Access Journals (Sweden)
Jun Taek Lee
2017-01-01
Full Text Available Multifractal (or singularity spectra widths w allow diagnosing cascade structure through comparing original series’ widths wOrig to surrogate series’ widths wSurr. However, interpretations of 0
Monofractal or multifractal: a case study of spatial distribution of mining-induced seismic activity
Directory of Open Access Journals (Sweden)
M. Eneva
1994-01-01
Full Text Available Using finite data sets and limited size of study volumes may result in significant spurious effects when estimating the scaling properties of various physical processes. These effects are examined with an example featuring the spatial distribution of induced seismic activity in Creighton Mine (northern Ontario, Canada. The events studied in the present work occurred during a three-month period, March-May 1992, within a volume of approximate size 400 x 400 x 180 m3. Two sets of microearthquake locations are studied: Data Set 1 (14,338 events and Data Set 2 (1654 events. Data Set 1 includes the more accurately located events and amounts to about 30 per cent of all recorded data. Data Set 2 represents a portion of the first data set that is formed by the most accurately located and the strongest microearthquakes. The spatial distribution of events in the two data sets is examined for scaling behaviour using the method of generalized correlation integrals featuring various moments q. From these, generalized correlation dimensions are estimated using the slope method. Similar estimates are made for randomly generated point sets using the same numbers of events and the same study volumes as for the real data. Uniform and monofractal random distributions are used for these simulations. In addition, samples from the real data are randomly extracted and the dimension spectra for these are examined as well. The spectra for the uniform and monofractal random generations show spurious multifractality due only to the use of finite numbers of data points and limited size of study volume. Comparing these with the spectra of dimensions for Data Set 1 and Data Set 2 allows us to estimate the bias likely to be present in the estimates for the real data. The strong multifractality suggested by the spectrum for Data Set 2 appears to be largely spurious; the spatial distribution, while different from uniform, could originate from a monofractal process. The spatial
Multifractal structure of multiparticle production in the branching models
International Nuclear Information System (INIS)
Chiu, C.B.; Hwa, R.C.
1990-01-01
A procedure is described for the multifractal analysis of data on multiparticle production obtained at high energy either in experiment or in Monte Carlo simulation. It is shown how the spectrum f(α) of the rapidity-density index α can be determined from the multiplicity fluctuation of the rapidity distribution, as the resolution is changed. The branching model is used to illustrate the procedure. It is found that the φ 3 model has a narrower f(α) than the gluon model, suggesting that multifractality is a useful arena for confrontation between theory and experiment. 13 refs., 2 figs
Multi-fractal analysis of highway traffic data
Institute of Scientific and Technical Information of China (English)
Shang Peng-Jian; Shen Jin-Sheng
2007-01-01
The purpose of the present study is to investigate the presence of multi-fractal behaviours in the traffic time series not only by statistical approaches but also by geometrical approaches. The pointwise H(o)lder exponent of a function is calculated by developing an algorithm for the numerical evaluation of H(o)lder exponent of time series. The traffic time series observed on the Beijing Yuquanying highway are analysed. The results from all these methods indicate that the traffic data exhibit the multi-fractal behaviour.
Apparent scale correlations in a random multifractal process
DEFF Research Database (Denmark)
Cleve, Jochen; Schmiegel, Jürgen; Greiner, Martin
2008-01-01
We discuss various properties of a homogeneous random multifractal process, which are related to the issue of scale correlations. By design, the process has no built-in scale correlations. However, when it comes to observables like breakdown coefficients, which are based on a coarse......-graining of the multifractal field, scale correlations do appear. In the log-normal limit of the model process, the conditional distributions and moments of breakdown coefficients reproduce the observations made in fully developed small-scale turbulence. These findings help to understand several puzzling empirical details...
Latest generation interconnect technologies in APEnet+ networking infrastructure
Ammendola, Roberto; Biagioni, Andrea; Cretaro, Paolo; Frezza, Ottorino; Lo Cicero, Francesca; Lonardo, Alessandro; Martinelli, Michele; Stanislao Paolucci, Pier; Pastorelli, Elena; Rossetti, Davide; Simula, Francesco; Vicini, Piero
2017-10-01
In this paper we present the status of the 3rd generation design of the APEnet board (V5) built upon the 28nm Altera Stratix V FPGA; it features a PCIe Gen3 x8 interface and enhanced embedded transceivers with a maximum capability of 12.5Gbps each. The network architecture is designed in accordance to the Remote DMA paradigm. The APEnet+ V5 prototype is built upon the Stratix V DevKit with the addition of a proprietary, third party IP core implementing multi-DMA engines. Support for zero-copy communication is assured by the possibility of DMA-accessing either host and GPU memory, offloading the CPU from the chore of data copying. The current implementation plateaus to a bandwidth for memory read of 4.8GB/s. Here we describe the hardware optimization to the memory write process which relies on the use of two independent DMA engines and an improved TLB.
Efficient Pruning Method for Ensemble Self-Generating Neural Networks
Directory of Open Access Journals (Sweden)
Hirotaka Inoue
2003-12-01
Full Text Available Recently, multiple classifier systems (MCS have been used for practical applications to improve classification accuracy. Self-generating neural networks (SGNN are one of the suitable base-classifiers for MCS because of their simple setting and fast learning. However, the computation cost of the MCS increases in proportion to the number of SGNN. In this paper, we propose an efficient pruning method for the structure of the SGNN in the MCS. We compare the pruned MCS with two sampling methods. Experiments have been conducted to compare the pruned MCS with an unpruned MCS, the MCS based on C4.5, and k-nearest neighbor method. The results show that the pruned MCS can improve its classification accuracy as well as reducing the computation cost.
Morren, J.; Haan, de S.W.H.
2008-01-01
An increasing number of distributed generation units (DG units) are connected to the distribution network. These generators affect the operation and coordination of the distribution network protection. The influence from DG units that are coupled to the network with a power electronic converter
Mali, P.; Manna, S. K.; Mukhopadhyay, A.; Haldar, P. K.; Singh, G.
2018-03-01
Multiparticle emission data in nucleus-nucleus collisions are studied in a graph theoretical approach. The sandbox algorithm used to analyze complex networks is employed to characterize the multifractal properties of the visibility graphs associated with the pseudorapidity distribution of charged particles produced in high-energy heavy-ion collisions. Experimental data on 28Si+Ag/Br interaction at laboratory energy Elab = 14 . 5 A GeV, and 16O+Ag/Br and 32S+Ag/Br interactions both at Elab = 200 A GeV, are used in this analysis. We observe a scale free nature of the degree distributions of the visibility and horizontal visibility graphs associated with the event-wise pseudorapidity distributions. Equivalent event samples simulated by ultra-relativistic quantum molecular dynamics, produce degree distributions that are almost identical to the respective experiment. However, the multifractal variables obtained by using sandbox algorithm for the experiment to some extent differ from the respective simulated results.
Integration of a network aware traffic generation device into a computer network emulation platform
CSIR Research Space (South Africa)
Von Solms, S
2014-07-01
Full Text Available Flexible, open source network emulation tools can provide network researchers with significant benefits regarding network behaviour and performance. The evaluation of these networks can benefit greatly from the integration of realistic, network...
Drożdż, Stanisław; Kwapień, Jarosław; Oświȩcimka, Paweł; Rak, Rafał
2010-10-01
We present a systematic study of various statistical characteristics of high-frequency returns from the foreign exchange market. This study is based on six exchange rates forming two triangles: EUR-GBP-USD and GBP-CHF-JPY. It is shown that the exchange rate return fluctuations for all of the pairs considered are well described by the non-extensive statistics in terms of q-Gaussians. There exist some small quantitative variations in the non-extensivity q-parameter values for different exchange rates (which depend also on the time scales studied), and this can be related to the importance of a given exchange rate in the world's currency trade. Temporal correlations organize the series of returns such that they develop the multifractal characteristics for all of the exchange rates, with a varying degree of symmetry of the singularity spectrum f(α), however. The most symmetric spectrum is identified for the GBP/USD. We also form time series of triangular residual returns and find that the distributions of their fluctuations develop disproportionately heavier tails as compared to small fluctuations, which excludes description in terms of q-Gaussians. The multifractal characteristics of these residual returns reveal such anomalous properties as negative singularity exponents and even negative singularity spectra. Such anomalous multifractal measures have so far been considered in the literature in connection with diffusion-limited aggregation and with turbulence. Studying the cross-correlations among different exchange rates, we found that market inefficiency on short time scales leads to the occurrence of the Epps effect on much longer time scales, but comparable to the ones for the stock market. Although the currency market is much more liquid than the stock markets and has a much greater transaction frequency, the building up of correlations takes up to several hours—a duration that does not differ much from what is observed in the stock markets. This may suggest
Optimizing Low Speed VoIP Network for Rural Next Generation Network (R-NGN
Directory of Open Access Journals (Sweden)
Yoanes Bandung
2007-11-01
Full Text Available In this research, we propose an optimization method based-on E-Model for designing an efficient low speed VoIP network for Rural Next Generation Network (R-NGN. We are choosing 128 kbps and 256 kbps bandwidth as the typical community link to be used in the designing of R-NGN infrastructure. The method is based on selection of some VoIP network parameters such as voice coder, communication protocol, packet loss level, network utilization and resource allocation. We draw analytic approach for achieving rating value (R of E-model that represent level of quality of service. In this approach, we focus on delay and packet loss calculation to find the rating value. We state the rating value = 70 as minimum level of quality of service for each call, equivalent to 3.6 of Mean Opinion Score (MOS. In our experiments, either G.723.1 5.3 kbps or G.729 is chosen for maximizing the number of VoIP calls, it depends on link utilization and level of packet loss.
Guesmi, Latifa; Hraghi, Abir; Menif, Mourad
2015-03-01
A new technique for Automatic Modulation Format Recognition (AMFR) in next generation optical communication networks is presented. This technique uses the Artificial Neural Network (ANN) in conjunction with the features of Linear Optical Sampling (LOS) of the detected signal at high bit rates using direct detection or coherent detection. The use of LOS method for this purpose mainly driven by the increase of bit rates which enables the measurement of eye diagrams. The efficiency of this technique is demonstrated under different transmission impairments such as chromatic dispersion (CD) in the range of -500 to 500 ps/nm, differential group delay (DGD) in the range of 0-15 ps and the optical signal tonoise ratio (OSNR) in the range of 10-30 dB. The results of numerical simulation for various modulation formats demonstrate successful recognition from a known bit rates with a higher estimation accuracy, which exceeds 99.8%.
Dynamical Mechanism of Scaling Behaviors in Multifractal Structure
Kim, Kyungsik; Jung, Jae Won; Kim, Soo Yong
2010-03-01
The pattern of stone distribution in the game of Go (Baduk, Weiqi, or Igo) can be treated in the mathematical and physical languages of multifractals. The concepts of fractals and multifractals have relevance to many fields of science and even arts. A significant and fascinating feature of this approach is that it provides a proper interpretation for the pattern of the two-colored (black and white) stones in terms of the numerical values of the generalized dimension and the scaling exponent. For our case, these statistical quantities can be estimated numerically from the black, white, and mixed stones, assuming the excluded edge effect that the cell form of the Go game has the self-similar structure. The result from the multifractal structure allows us to find a definite and reliable fractal dimension, and it precisely verifies that the fractal dimension becomes larger, as the cell of grids increases. We also find the strength of multifractal structures from the difference in the scaling exponents in the black, white, and mixed stones.
Thermodynamic and multifractal formalism and the Bowen-series map
International Nuclear Information System (INIS)
Rudolph, O.
1995-01-01
In the theory of quantum chaos one studies the semiclassical behaviour of quantum mechanical systems whose corresponding classical counterparts exhibit chaos. The geodesic motion of a free classical particle on closed Riemann surfaces with constant negative curvature is strongly chaotic. Selberg's theory relates the classical and the quantum mechanical systems. These systems are sometimes considered as model systems in the theory of quantum chaos since they are well understood from a mathematical point of view. In this work we study the multifractal formalism for the geodesic flow on surfaces with constant negative curvature. The multifractal analysis of measures has been developed in order to characterize the scaling behaviour of measures on attractors of classical chaotic dynamical systems globally. In order to relate the multifractal formalism with quantities usually considered in the study of the geodesic flow on Riemann surfaces with constant negative curvature, it is necessary to establish the assertions of the multifractal formalism in a mathematically rigorous way. This is achieved with the help of the thermodynamic formalism for hyperbolic dynamical systems developed by Ruelle, Bowen and others. (orig.)
Understanding the source of multifractality in financial markets
Czech Academy of Sciences Publication Activity Database
Baruník, Jozef; Aste, T.; Di Matteo, T.; Liu, R.
2012-01-01
Roč. 391, č. 17 (2012), s. 4234-4251 ISSN 0378-4371 R&D Projects: GA ČR GA402/09/0965 Institutional research plan: CEZ:AV0Z10750506 Keywords : Multifractality * Financial markets * Hurst exponent Subject RIV: AH - Economics Impact factor: 1.676, year: 2012 http://www.sciencedirect.com/science/article/pii/S0378437112002890
MULTIFRACTAL STRUCTURES DETECTED BY VOYAGER 1 AT THE HELIOSPHERIC BOUNDARIES
International Nuclear Information System (INIS)
Macek, W. M.; Wawrzaszek, A.; Burlaga, L. F.
2014-01-01
To better understand the dynamics of turbulent systems, we have proposed a phenomenological model based on a generalized Cantor set with two rescaling and one weight parameters. In this Letter, using recent Voyager 1 magnetic field data, we extend our two-scale multifractal analysis further in the heliosheath beyond the heliospheric termination shock, and even now near the heliopause, when entering the interstellar medium for the first time in human history. We have identified the scaling inertial region for magnetized heliospheric plasma between the termination shock and the heliopause. We also show that the degree of multifractality decreases with the heliocentric distance and is still modulated by the phases of the solar cycle in the entire heliosphere including the heliosheath. Moreover, we observe the change of scaling toward a nonintermittent (nonmultifractal) behavior in the nearby interstellar medium, just beyond the heliopause. We argue that this loss of multifractal behavior could be a signature of the expected crossing of the heliopause by Voyager 2 in the near future. The results obtained demonstrate that our phenomenological multifractal model exhibits some properties of intermittent turbulence in the solar system plasmas, and we hope that it could shed light on universal characteristics of turbulence
Influence of urban morphology on total noise pollution: multifractal description.
Ariza-Villaverde, Ana B; Jiménez-Hornero, Francisco J; Gutiérrez De Ravé, Eduardo
2014-02-15
Exposure to ambient noise levels above 65 dB can cause public health problems. The spatial distribution of this kind of pollution is linked to various elements which make up the urban form, such as construction density, the existence of open spaces and the shape and physical position of buildings. Since urban morphology displays multifractal behaviour, the present research studies for the first time the relationship between total noise pollution and urban features, such as street width and building height by means of a joint multifractal spectrum in two neighbourhoods of the city of Cordoba (Andalusia, Spain). According to the results, the joint multifractal spectrum reveals a positive correlation between the total noise pollution and the street width to building height ratio, this being more evident when urban morphology is regular. The information provided by the multifractal analysis completes the description obtained by using urban indexes and landscape metrics and might be useful for urban planning once the linkage between both frameworks has been done. Copyright © 2013 Elsevier B.V. All rights reserved.
MULTIFRACTAL STRUCTURES DETECTED BY VOYAGER 1 AT THE HELIOSPHERIC BOUNDARIES
Energy Technology Data Exchange (ETDEWEB)
Macek, W. M. [Faculty of Mathematics and Natural Sciences, Cardinal Stefan Wyszyński University, Wóycickiego 1/3, 01-938 Warsaw (Poland); Wawrzaszek, A. [Space Research Centre, Polish Academy of Sciences, Bartycka 18 A, 00-716 Warszawa (Poland); Burlaga, L. F., E-mail: macek@cbk.waw.pl, E-mail: anna.wawrzaszek@cbk.waw.pl, E-mail: lburlagahsp@verizon.net [NASA Goddard Space Flight Center, Code 673, Greenbelt, MD 20771 (United States)
2014-10-01
To better understand the dynamics of turbulent systems, we have proposed a phenomenological model based on a generalized Cantor set with two rescaling and one weight parameters. In this Letter, using recent Voyager 1 magnetic field data, we extend our two-scale multifractal analysis further in the heliosheath beyond the heliospheric termination shock, and even now near the heliopause, when entering the interstellar medium for the first time in human history. We have identified the scaling inertial region for magnetized heliospheric plasma between the termination shock and the heliopause. We also show that the degree of multifractality decreases with the heliocentric distance and is still modulated by the phases of the solar cycle in the entire heliosphere including the heliosheath. Moreover, we observe the change of scaling toward a nonintermittent (nonmultifractal) behavior in the nearby interstellar medium, just beyond the heliopause. We argue that this loss of multifractal behavior could be a signature of the expected crossing of the heliopause by Voyager 2 in the near future. The results obtained demonstrate that our phenomenological multifractal model exhibits some properties of intermittent turbulence in the solar system plasmas, and we hope that it could shed light on universal characteristics of turbulence.
Laurito, Andres; The ATLAS collaboration
2017-01-01
Simulation is an important tool to validate the performance impact of control decisions in Software Defined Networks (SDN). Yet, the manual modeling of complex topologies that may change often during a design process can be a tedious error-prone task. We present TopoGen, a general purpose architecture and tool for systematic translation and generation of network topologies. TopoGen can be used to generate network simulation models automatically by querying information available at diverse sources, notably SDN controllers. The DEVS modeling and simulation framework facilitates a systematic translation of structured knowledge about a network topology into a formal modular and hierarchical coupling of preexisting or new models of network entities (physical or logical). TopoGen can be flexibly extended with new parsers and generators to grow its scope of applicability. This permits to design arbitrary workflows of topology transformations. We tested TopoGen in a network engineering project for the ATLAS detector ...
Laurito, Andres; The ATLAS collaboration
2018-01-01
Simulation is an important tool to validate the performance impact of control decisions in Software Defined Networks (SDN). Yet, the manual modeling of complex topologies that may change often during a design process can be a tedious error-prone task. We present TopoGen, a general purpose architecture and tool for systematic translation and generation of network topologies. TopoGen can be used to generate network simulation models automatically by querying information available at diverse sources, notably SDN controllers. The DEVS modeling and simulation framework facilitates a systematic translation of structured knowledge about a network topology into a formal modular and hierarchical coupling of preexisting or new models of network entities (physical or logical). TopoGen can be flexibly extended with new parsers and generators to grow its scope of applicability. This permits to design arbitrary workflows of topology transformations. We tested TopoGen in a network engineering project for the ATLAS detector ...
International Nuclear Information System (INIS)
Vitanov, Nikolay K.; Yankulova, Elka D.
2006-01-01
By means of the multifractal detrended fluctuation analysis (MFDFA) we investigate long-range correlations in the interbeat time series of heart activity of Drosophila melanogaster-the classical object of research in genetics. Our main investigation tool are the fractal spectra f(α) and h(q) by means of which we trace the correlation properties of Drosophila heartbeat dynamics for three consequent generations of species. We observe that opposite to the case of humans the time series of the heartbeat activity of healthy Drosophila do not have scaling properties. Time series from species with genetic defects can be long-range correlated. Different kinds of genetic heart defects lead to different shape of the fractal spectra. The fractal heartbeat dynamics of Drosophila is transferred from generation to generation
Black holes in multi-fractional and Lorentz-violating models
Energy Technology Data Exchange (ETDEWEB)
Calcagni, Gianluca [CSIC, Instituto de Estructura de la Materia, Madrid (Spain); Rodriguez Fernandez, David [Universidad de Oviedo, Department of Physics, Oviedo (Spain); Ronco, Michele [Universita di Roma ' ' La Sapienza' ' , Dipartimento di Fisica, Rome (Italy); INFN, Rome (Italy)
2017-05-15
We study static and radially symmetric black holes in the multi-fractional theories of gravity with q-derivatives and with weighted derivatives, frameworks where the spacetime dimension varies with the probed scale and geometry is characterized by at least one fundamental length l{sub *}. In the q-derivatives scenario, one finds a tiny shift of the event horizon. Schwarzschild black holes can present an additional ring singularity, not present in general relativity, whose radius is proportional to l{sub *}. In the multi-fractional theory with weighted derivatives, there is no such deformation, but non-trivial geometric features generate a cosmological-constant term, leading to a de Sitter-Schwarzschild black hole. For both scenarios, we compute the Hawking temperature and comment on the resulting black-hole thermodynamics. In the case with q-derivatives, black holes can be hotter than usual and possess an additional ring singularity, while in the case with weighted derivatives they have a de Sitter hair of purely geometric origin, which may lead to a solution of the cosmological constant problem similar to that in unimodular gravity. Finally, we compare our findings with other Lorentz-violating models. (orig.)
Black holes in multi-fractional and Lorentz-violating models
International Nuclear Information System (INIS)
Calcagni, Gianluca; Rodriguez Fernandez, David; Ronco, Michele
2017-01-01
We study static and radially symmetric black holes in the multi-fractional theories of gravity with q-derivatives and with weighted derivatives, frameworks where the spacetime dimension varies with the probed scale and geometry is characterized by at least one fundamental length l_*. In the q-derivatives scenario, one finds a tiny shift of the event horizon. Schwarzschild black holes can present an additional ring singularity, not present in general relativity, whose radius is proportional to l_*. In the multi-fractional theory with weighted derivatives, there is no such deformation, but non-trivial geometric features generate a cosmological-constant term, leading to a de Sitter-Schwarzschild black hole. For both scenarios, we compute the Hawking temperature and comment on the resulting black-hole thermodynamics. In the case with q-derivatives, black holes can be hotter than usual and possess an additional ring singularity, while in the case with weighted derivatives they have a de Sitter hair of purely geometric origin, which may lead to a solution of the cosmological constant problem similar to that in unimodular gravity. Finally, we compare our findings with other Lorentz-violating models. (orig.)
Black holes in multi-fractional and Lorentz-violating models.
Calcagni, Gianluca; Rodríguez Fernández, David; Ronco, Michele
2017-01-01
We study static and radially symmetric black holes in the multi-fractional theories of gravity with q -derivatives and with weighted derivatives, frameworks where the spacetime dimension varies with the probed scale and geometry is characterized by at least one fundamental length [Formula: see text]. In the q -derivatives scenario, one finds a tiny shift of the event horizon. Schwarzschild black holes can present an additional ring singularity, not present in general relativity, whose radius is proportional to [Formula: see text]. In the multi-fractional theory with weighted derivatives, there is no such deformation, but non-trivial geometric features generate a cosmological-constant term, leading to a de Sitter-Schwarzschild black hole. For both scenarios, we compute the Hawking temperature and comment on the resulting black-hole thermodynamics. In the case with q -derivatives, black holes can be hotter than usual and possess an additional ring singularity, while in the case with weighted derivatives they have a de Sitter hair of purely geometric origin, which may lead to a solution of the cosmological constant problem similar to that in unimodular gravity. Finally, we compare our findings with other Lorentz-violating models.
Multifractal signal reconstruction based on singularity power spectrum
International Nuclear Information System (INIS)
Xiong, Gang; Yu, Wenxian; Xia, Wenxiang; Zhang, Shuning
2016-01-01
Highlights: • We propose a novel multifractal reconstruction method based on singularity power spectrum analysis (MFR-SPS). • The proposed MFR-SPS method has better power characteristic than the algorithm in Fraclab. • Further, the SPS-ISE algorithm performs better than the SPS-MFS algorithm. • Based on the proposed MFR-SPS method, we can restructure singularity white fractal noise (SWFN) and linear singularity modulation (LSM) multifractal signal, in equivalent sense, similar with the linear frequency modulation(LFM) signal and WGN in the Fourier domain. - Abstract: Fractal reconstruction (FR) and multifractal reconstruction (MFR) can be considered as the inverse problem of singularity spectrum analysis, and it is challenging to reconstruct fractal signal in accord with multifractal spectrum (MFS). Due to the multiple solutions of fractal reconstruction, the traditional methods of FR/MFR, such as FBM based method, wavelet based method, random wavelet series, fail to reconstruct fractal signal deterministically, and besides, those methods neglect the power spectral distribution in the singular domain. In this paper, we propose a novel MFR method based singularity power spectrum (SPS). Supposing the consistent uniform covering of multifractal measurement, we control the traditional power law of each scale of wavelet coefficients based on the instantaneous singularity exponents (ISE) or MFS, simultaneously control the singularity power law based on the SPS, and deduce the principle and algorithm of MFR based on SPS. Reconstruction simulation and error analysis of estimated ISE, MFS and SPS show the effectiveness and the improvement of the proposed methods compared to those obtained by the Fraclab package.
Challenges in Second-Generation Wireless Mesh Networks
Directory of Open Access Journals (Sweden)
Pescapé Antonio
2008-01-01
Full Text Available Wireless mesh networks have the potential to provide ubiquitous high-speed Internet access at low costs. The good news is that initial deployments of WiFi meshes show the feasibility of providing ubiquitous Internet connectivity. However, their performance is far below the necessary and achievable limit. Moreover, users' subscription in the existing meshes is dismal even though the technical challenges to get connectivity are low. This paper provides an overview of the current status of mesh networks' deployment, and highlights the technical, economical, and social challenges that need to be addressed in the next years. As a proof-of-principle study, we discuss the above-mentioned challenges with reference to three real networks: (i MagNets, an operator-driven planned two-tier mesh network; (ii Berlin Freifunk network as a pure community-driven single-tier network; (iii Weimar Freifunk network, also a community-driven but two-tier network.
Pythoscape: A framework for generation of large protein similarity networks
Babbitt, Patricia; Barber, AE; Babbitt, PC
2012-01-01
Pythoscape is a framework implemented in Python for processing large protein similarity networks for visualization in other software packages. Protein similarity networks are graphical representations of sequence, structural and other similarities among pr
Automatic generation of investigator bibliographies for institutional research networking systems.
Johnson, Stephen B; Bales, Michael E; Dine, Daniel; Bakken, Suzanne; Albert, Paul J; Weng, Chunhua
2014-10-01
Publications are a key data source for investigator profiles and research networking systems. We developed ReCiter, an algorithm that automatically extracts bibliographies from PubMed using institutional information about the target investigators. ReCiter executes a broad query against PubMed, groups the results into clusters that appear to constitute distinct author identities and selects the cluster that best matches the target investigator. Using information about investigators from one of our institutions, we compared ReCiter results to queries based on author name and institution and to citations extracted manually from the Scopus database. Five judges created a gold standard using citations of a random sample of 200 investigators. About half of the 10,471 potential investigators had no matching citations in PubMed, and about 45% had fewer than 70 citations. Interrater agreement (Fleiss' kappa) for the gold standard was 0.81. Scopus achieved the best recall (sensitivity) of 0.81, while name-based queries had 0.78 and ReCiter had 0.69. ReCiter attained the best precision (positive predictive value) of 0.93 while Scopus had 0.85 and name-based queries had 0.31. ReCiter accesses the most current citation data, uses limited computational resources and minimizes manual entry by investigators. Generation of bibliographies using named-based queries will not yield high accuracy. Proprietary databases can perform well but requite manual effort. Automated generation with higher recall is possible but requires additional knowledge about investigators. Copyright © 2014 Elsevier Inc. All rights reserved.
Persona: Network Layer Anonymity and Accountability for Next Generation Internet
Mallios, Yannis; Modi, Sudeep; Agarwala, Aditya; Johns, Christina
Individual privacy has become a major concern, due to the intrusive nature of the services and websites that collect increasing amounts of private information. One of the notions that can lead towards privacy protection is that of anonymity. Unfortunately, anonymity can also be maliciously exploited by attackers to hide their actions and identity. Thus some sort of accountability is also required. The current Internet has failed to provide both properties, as anonymity techniques are difficult to fully deploy and thus are easily attacked, while the Internet provides limited level of accountability. The Next Generation Internet (NGI) provides us with the opportunity to examine how these conflicting properties could be efficiently applied and thus protect users’ privacy while holding malicious users accountable. In this paper we present the design of a scheme, called Persona that can provide anonymity and accountability in the network layer of NGI. More specifically, our design requirements are to combine these two conflicting desires in a stateless manner within routers. Persona allows users to choose different levels of anonymity, while it allows the discovery of malicious nodes.
Ichthyoplankton Classification Tool using Generative Adversarial Networks and Transfer Learning
Aljaafari, Nura
2018-04-15
The study and the analysis of marine ecosystems is a significant part of the marine science research. These systems are valuable resources for fisheries, improving water quality and can even be used in drugs production. The investigation of ichthyoplankton inhabiting these ecosystems is also an important research field. Ichthyoplankton are fish in their early stages of life. In this stage, the fish have relatively similar shape and are small in size. The currently used way of identifying them is not optimal. Marine scientists typically study such organisms by sending a team that collects samples from the sea which is then taken to the lab for further investigation. These samples need to be studied by an expert and usually end needing a DNA sequencing. This method is time-consuming and requires a high level of experience. The recent advances in AI have helped to solve and automate several difficult tasks which motivated us to develop a classification tool for ichthyoplankton. We show that using machine learning techniques, such as generative adversarial networks combined with transfer learning solves such a problem with high accuracy. We show that using traditional machine learning algorithms fails to solve it. We also give a general framework for creating a classification tool when the dataset used for training is a limited dataset. We aim to build a user-friendly tool that can be used by any user for the classification task and we aim to give a guide to the researchers so that they can follow in creating a classification tool.
ACO-Initialized Wavelet Neural Network for Vibration Fault Diagnosis of Hydroturbine Generating Unit
Directory of Open Access Journals (Sweden)
Zhihuai Xiao
2015-01-01
Full Text Available Considering the drawbacks of traditional wavelet neural network, such as low convergence speed and high sensitivity to initial parameters, an ant colony optimization- (ACO- initialized wavelet neural network is proposed in this paper for vibration fault diagnosis of a hydroturbine generating unit. In this method, parameters of the wavelet neural network are initialized by the ACO algorithm, and then the wavelet neural network is trained by the gradient descent algorithm. Amplitudes of the frequency components of the hydroturbine generating unit vibration signals are used as feature vectors for wavelet neural network training to realize mapping relationship from vibration features to fault types. A real vibration fault diagnosis case result of a hydroturbine generating unit shows that the proposed method has faster convergence speed and stronger generalization ability than the traditional wavelet neural network and ACO wavelet neural network. Thus it can provide an effective solution for online vibration fault diagnosis of a hydroturbine generating unit.
Application of Integrated Neural Network Method to Fault Diagnosis of Nuclear Steam Generator
International Nuclear Information System (INIS)
Zhou Gang; Yang Li
2009-01-01
A new fault diagnosis method based on integrated neural networks for nuclear steam generator (SG) was proposed in view of the shortcoming of the conventional fault monitoring and diagnosis method. In the method, two neural networks (ANNs) were employed for the fault diagnosis of steam generator. A neural network, which was used for predicting the values of steam generator operation parameters, was taken as the dynamics model of steam generator. The principle of fault monitoring method using the neural network model is to detect the deviations between process signals measured from an operating steam generator and corresponding output signals from the neural network model of steam generator. When the deviation exceeds the limit set in advance, the abnormal event is thought to occur. The other neural network as a fault classifier conducts the fault classification of steam generator. So, the fault types of steam generator are given by the fault classifier. The clear information on steam generator faults was obtained by fusing the monitoring and diagnosis results of two neural networks. The simulation results indicate that employing integrated neural networks can improve the capacity of fault monitoring and diagnosis for the steam generator. (authors)
Effects of traffic generation patterns on the robustness of complex networks
Wu, Jiajing; Zeng, Junwen; Chen, Zhenhao; Tse, Chi K.; Chen, Bokui
2018-02-01
Cascading failures in communication networks with heterogeneous node functions are studied in this paper. In such networks, the traffic dynamics are highly dependent on the traffic generation patterns which are in turn determined by the locations of the hosts. The data-packet traffic model is applied to Barabási-Albert scale-free networks to study the cascading failures in such networks and to explore the effects of traffic generation patterns on network robustness. It is found that placing the hosts at high-degree nodes in a network can make the network more robust against both intentional attacks and random failures. It is also shown that the traffic generation pattern plays an important role in network design.
Breskovic, Damir; Sikirica, Mladen; Begusic, Dinko
2018-05-01
This paper gives an overview and background of optical access network deployment in Croatia. Optical access network development in Croatia has been put into a global as well as in the European Union context. All the challenges and the driving factors for optical access networks deployment are considered. Optical access network architectures that have been deployed by most of the investors in Croatian telecommunication market are presented, as well as the architectures that are in early phase of deployment. Finally, an overview on current status of mobile networks of the fifth generation and Internet of Things is given.
International Nuclear Information System (INIS)
Nisten, E.
2010-02-01
The increase in the distributed generation of electricity, with wind turbines and solar panels, necessitates investments in the distribution network. The current tariff regulation in the Dutch electricity industry, with its ex post evaluation of the efficiency of investments and the frontier shift in the x-factor, delays these investments. In the unbundled electricity industry, the investments in the network need to be coordinated with those in the distributed generation of electricity to enable the DSOs to build enough network capacity. The current Dutch regulations do not provide for a sufficient information exchange between the generators and the system operators to coordinate the investments. This paper analyses these two effects of the Dutch regulation, and suggests improvements to the regulation of the network connection and transportation tariffs to allow for sufficient network capacity and coordination between the investments in the network and in the generation of electricity. These improvements include locally differentiated tariffs that increase with an increasing concentration of distributed generators.
International Nuclear Information System (INIS)
Niesten, Eva
2010-01-01
An increase in the distributed generation of electricity necessitates investments in the distribution network. The current tariff regulation in the Dutch electricity industry, with its ex post evaluation of the efficiency of investments, average benchmarking and a frontier shift in the x-factor, delays these investments. In the unbundled electricity industry, the investments in the network need to be coordinated with those in the distributed generation of electricity to enable the system operators to build enough network capacity. The current Dutch regulations do not provide for a sufficient information exchange between the generators and the system operators to coordinate the investments. This paper analyses these two effects of the Dutch regulations, and suggests improvements to the regulation of the network connection and transportation tariffs to allow for sufficient network capacity and coordination between the investments in the network and in the generation of electricity. These improvements include locally differentiated tariffs that increase with an increasing concentration of distributed generation.
Optogenetic stimulation effectively enhances intrinsically generated network synchrony
Directory of Open Access Journals (Sweden)
Ahmed eEl Hady
2013-10-01
Full Text Available Synchronized bursting is found in many brain areas and has also been implicated in the pathophysiology of neuropsychiatric disorders such as epilepsy, Parkinson’s disease and schizophrenia. Despite extensive studies of network burst synchronization, it is insufficiently understood how this type of network wide synchronization can be strengthened, reduced or even abolished. We combined electrical recording using multi-electrode array with optical stimulation of cultured channelrhodopsin-2 transducted hippocampal neurons to study and manipulate network burst synchronization. We found low frequency photo-stimulation protocols that are sufficient to induce potentiation of network bursting, modifying bursting dynamics and increasing interneuronal synchronization. Surprisingly, slowly fading-in light stimulation, which substantially delayed and reduced light driven spiking, was at least as effective in reorganizing network dynamics as much stronger pulsed light stimulation. Our study shows that mild stimulation protocols that do not enforce particular activity patterns onto the network can be highly effective inducers of network-level plasticity.
Optogenetic stimulation effectively enhances intrinsically generated network synchrony
El Hady, Ahmed; Afshar, Ghazaleh; Bröking, Kai; Schlüter, Oliver M.; Geisel, Theo; Stühmer, Walter; Wolf, Fred
2013-01-01
Synchronized bursting is found in many brain areas and has also been implicated in the pathophysiology of neuropsychiatric disorders such as epilepsy, Parkinson’s disease, and schizophrenia. Despite extensive studies of network burst synchronization, it is insufficiently understood how this type of network wide synchronization can be strengthened, reduced, or even abolished. We combined electrical recording using multi-electrode array with optical stimulation of cultured channelrhodopsin-2 transducted hippocampal neurons to study and manipulate network burst synchronization. We found low frequency photo-stimulation protocols that are sufficient to induce potentiation of network bursting, modifying bursting dynamics, and increasing interneuronal synchronization. Surprisingly, slowly fading-in light stimulation, which substantially delayed and reduced light-driven spiking, was at least as effective in reorganizing network dynamics as much stronger pulsed light stimulation. Our study shows that mild stimulation protocols that do not enforce particular activity patterns onto the network can be highly effective inducers of network-level plasticity. PMID:24155695
Question Generation and Adaptation Using a Bayesian Network of the Learner’s Achievements
Wißner, M.; Linnebank, F.; Liem, J.; Bredeweg, B.; André, E.; Lane, H.C.; Yacef, K.; Mostow, J.; Pavlik, P.
2013-01-01
This paper presents a domain independent question generation and interaction procedure that automatically generates multiple-choice questions for conceptual models created with Qualitative Reasoning vocabulary. A Bayesian Network is deployed that captures the learning progress based on the answers
Generation of teletraffic of generalized Cauchy type
International Nuclear Information System (INIS)
Li Ming
2010-01-01
Generation of long-range-dependent (LRD) traffic is crucial for networking, e.g. simulating the Internet. In this respect, it is necessary to generate an LRD traffic series according to a given correlation structure that may well reflect the statistics of real traffic. Recent research on traffic modeling exhibits that the LRD traffic is well modeled by the generalized Cauchy (GC) process indexed by two parameters that separately characterize the self-similarity (SS), which is a local property described by the fractal dimension D, and long-range dependence (LRD), which is a global property measured by the Hurst parameter H. This paper gives a computational method to generate the LRD traffic based on the correlation form of the GC process in both the unifractal and multifractal cases. It may nevertheless be used as a way to flexibly simulate the realizations that reflect the fractal phenomena of traffic for both short-term lags and long-term ones.
Bhaduri, Anirban; Ghosh, Dipak
2016-01-01
The cardiac dynamics during meditation is explored quantitatively with two chaos-based non-linear techniques viz. multi-fractal detrended fluctuation analysis and visibility network analysis techniques. The data used are the instantaneous heart rate (in beats/minute) of subjects performing Kundalini Yoga and Chi meditation from PhysioNet. The results show consistent differences between the quantitative parameters obtained by both the analysis techniques. This indicates an interesting phenomenon of change in the complexity of the cardiac dynamics during meditation supported with quantitative parameters. The results also produce a preliminary evidence that these techniques can be used as a measure of physiological impact on subjects performing meditation.
International Nuclear Information System (INIS)
Telesca, Luciano; Colangelo, Gerardo; Lapenna, Vincenzo; Macchiato, Maria
2004-01-01
We analyzed fluctuations in the time dynamics of nonstationary geoelectrical data, recorded in a seismic area of southern Italy, by means of the multifractal detrended fluctuation analysis (MF-DFA). The multifractal character of the signal depends mostly on the different long-range properties for small and large fluctuations. The time variation of indices, denoting the departure from monofractal behaviour, reveals an enhancement of the multifractality of the signal prior seismic occurrences
Xie, Wen-Jie; Han, Rui-Qi; Jiang, Zhi-Qiang; Wei, Lijian; Zhou, Wei-Xing
2017-08-01
Complex network is not only a powerful tool for the analysis of complex system, but also a promising way to analyze time series. The algorithm of horizontal visibility graph (HVG) maps time series into graphs, whose degree distributions are numerically and analytically investigated for certain time series. We derive the degree distributions of HVGs through an iterative construction process of HVGs. The degree distributions of the HVG and the directed HVG for random series are derived to be exponential, which confirms the analytical results from other methods. We also obtained the analytical expressions of degree distributions of HVGs and in-degree and out-degree distributions of directed HVGs transformed from multifractal binomial measures, which agree excellently with numerical simulations.
CHAOS AND STOCHASTICITY IN DETERMINISTICALLY GENERATED MULTIFRACTAL MEASURES. (R824780)
The perspectives, information and conclusions conveyed in research project abstracts, progress reports, final reports, journal abstracts and journal publications convey the viewpoints of the principal investigator and may not represent the views and policies of ORD and EPA. Concl...
Security management of next generation telecommunications networks and services
Jacobs, Stuart
2014-01-01
This book will cover network management security issues and currently available security mechanisms by discussing how network architectures have evolved into the contemporary NGNs which support converged services (voice, video, TV, interactive information exchange, and classic data communications). It will also analyze existing security standards and their applicability to securing network management. This book will review 21st century security concepts of authentication, authorization, confidentiality, integrity, nonrepudiation, vulnerabilities, threats, risks, and effective approaches to enc
Cisco Networking Academy: Next-Generation Assessments and Their Implications for K-12 Education
Liu, Meredith
2014-01-01
To illuminate the possibilities for next-generation assessments in K-12 schools, this case study profiles the Cisco Networking Academy, which creates comprehensive online training curriculum to teach networking skills. Since 1997, the Cisco Networking Academy has served more than five million high school and college students and now delivers…
Generation of arbitrary two-point correlated directed networks with given modularity
International Nuclear Information System (INIS)
Zhou Jie; Xiao Gaoxi; Wong, Limsoon; Fu Xiuju; Ma, Stefan; Cheng, Tee Hiang
2010-01-01
In this Letter, we introduce measures of correlation in directed networks and develop an efficient algorithm for generating directed networks with arbitrary two-point correlation. Furthermore, a method is proposed for adjusting community structure in directed networks without changing the correlation. Effectiveness of both methods is verified by numerical results.
Next Generation Flexible and Cognitive Heterogeneous Optical Networks
DEFF Research Database (Denmark)
Tomkos, Ioannis; Angelou, Marianna; Barroso, Ramón J. Durán
2012-01-01
Optical networking is the cornerstone of the Future Internet as it provides the physical infrastructure of the core backbone networks. Recent developments have enabled much better quality of service/experience for the end users, enabled through the much higher capacities that can be supported...... the capabilities of the Future Internet. In this book chapter, we highlight the latest activities of the optical networking community and in particular what has been the focus of EU funded research. The concepts of flexible and cognitive optical networks are introduced and their key expected benefits...
Multifractal analysis of forest fires in complex regions
Vega Orozco, C. D.; Kanevski, M.; Golay, J.; Tonini, M.; Conedera, M.
2012-04-01
Forest fires can be studied as point processes where the ignition points represent the set of locations of the observed events in a defined study region. Their spatial and temporal patterns can be characterized by their fractal properties; which quantify the global aspect of the geometry of the support data. However, a monofractal dimension can not completely describe the pattern structure and related scaling properties. Enhancements in fractal theory had developed the multifractal concept which describes the measures from which interlinked fractal sets can be retrieved and characterized by their fractal dimension and singularity strength [1, 2]. The spatial variability of forest fires is conditioned by an intermixture of human, topographic, meteorological and vegetation factors. This heterogeneity makes fire patterns complex scale-invariant processes difficult to be depicted by a single scale. Therefore, this study proposes an exploratory data analysis through a multifractal formalism to characterize and quantify the multiscaling behaviour of the spatial distribution pattern of this phenomenon in a complex region like the Swiss Alps. The studied dataset is represented by 2,401 georeferenced forest fire ignition points in canton Ticino, Switzerland, in a 40-years period from 1969 to 2008. Three multifractal analyses are performed: one assesses the multiscaling behaviour of fire occurrence probability of the support data (raw data) and four random patterns simulated within three different support domains; second analysis studies the multifractal behavior of patterns from anthropogenic and natural ignited fires (arson-, accident- and lightning-caused fires); and third analysis aims at detecting scale-dependency of the size of burned area. To calculate the generalized dimensions, Dq, a generalization of the box counting methods is carried out based on the generalization of Rényi information of the qth order moment of the probability distribution. For q > 0, Dq
VIGAN: Missing View Imputation with Generative Adversarial Networks.
Shang, Chao; Palmer, Aaron; Sun, Jiangwen; Chen, Ko-Shin; Lu, Jin; Bi, Jinbo
2017-01-01
In an era when big data are becoming the norm, there is less concern with the quantity but more with the quality and completeness of the data. In many disciplines, data are collected from heterogeneous sources, resulting in multi-view or multi-modal datasets. The missing data problem has been challenging to address in multi-view data analysis. Especially, when certain samples miss an entire view of data, it creates the missing view problem. Classic multiple imputations or matrix completion methods are hardly effective here when no information can be based on in the specific view to impute data for such samples. The commonly-used simple method of removing samples with a missing view can dramatically reduce sample size, thus diminishing the statistical power of a subsequent analysis. In this paper, we propose a novel approach for view imputation via generative adversarial networks (GANs), which we name by VIGAN. This approach first treats each view as a separate domain and identifies domain-to-domain mappings via a GAN using randomly-sampled data from each view, and then employs a multi-modal denoising autoencoder (DAE) to reconstruct the missing view from the GAN outputs based on paired data across the views. Then, by optimizing the GAN and DAE jointly, our model enables the knowledge integration for domain mappings and view correspondences to effectively recover the missing view. Empirical results on benchmark datasets validate the VIGAN approach by comparing against the state of the art. The evaluation of VIGAN in a genetic study of substance use disorders further proves the effectiveness and usability of this approach in life science.
The effect of increasing levels of embedded generation on the distribution network. Final report
Energy Technology Data Exchange (ETDEWEB)
Collinson, A; Earp, G K; Howson, D; Owen, R D; Wright, A J
1999-10-01
This report was commissioned as part of the EA Technology Strategic Technology Programme under guidance of the Module 5 (Embedded Generation) Steering Group. This report aims to provide information related to the distribution and supply of electricity in the context of increasing levels of embedded generation. There is a brief description of the operating environment within which electricity companies in the UK must operate. Technical issues related to the connection of generation to the existing distribution infrastructure are highlighted and the design philosophy adopted by network designers in accommodating applications for the connection of embedded generation to the network is discussed. The effects embedded generation has on the network and the issues raised are presented as many of them present barriers to the connection of embedded generators. The final chapters cover the forecast of required connection to 2010 and solutions to restrictions preventing the connection of more embedded generation to the network. (author)
Network as a service for next generation internet
Duan, Qiang
2017-01-01
This book presents the state of the art of the Network-as-a-Service (NaaS) paradigm, including its concepts, architecture, key technologies, applications, and development directions for future network service provisioning. It provides a comprehensive reference that reflects the most current technical developments related to NaaS.
Yang, Shan; Tong, Xiangqian
2016-01-01
Power flow calculation and short circuit calculation are the basis of theoretical research for distribution network with inverter based distributed generation. The similarity of equivalent model for inverter based distributed generation during normal and fault conditions of distribution network and the differences between power flow and short circuit calculation are analyzed in this paper. Then an integrated power flow and short circuit calculation method for distribution network with inverte...
Pythoscape: a framework for generation of large protein similarity networks.
Barber, Alan E; Babbitt, Patricia C
2012-11-01
Pythoscape is a framework implemented in Python for processing large protein similarity networks for visualization in other software packages. Protein similarity networks are graphical representations of sequence, structural and other similarities among proteins for which pairwise all-by-all similarity connections have been calculated. Mapping of biological and other information to network nodes or edges enables hypothesis creation about sequence-structure-function relationships across sets of related proteins. Pythoscape provides several options to calculate pairwise similarities for input sequences or structures, applies filters to network edges and defines sets of similar nodes and their associated data as single nodes (termed representative nodes) for compression of network information and output data or formatted files for visualization.
ACO-Initialized Wavelet Neural Network for Vibration Fault Diagnosis of Hydroturbine Generating Unit
Xiao, Zhihuai; He, Xinying; Fu, Xiangqian; Malik, O. P.
2015-01-01
Considering the drawbacks of traditional wavelet neural network, such as low convergence speed and high sensitivity to initial parameters, an ant colony optimization- (ACO-) initialized wavelet neural network is proposed in this paper for vibration fault diagnosis of a hydroturbine generating unit. In this method, parameters of the wavelet neural network are initialized by the ACO algorithm, and then the wavelet neural network is trained by the gradient descent algorithm. Amplitudes of the fr...
The Influence of Social Network on Consumer Purchase Intention of Young Generation in Manado
Tumewu, Ferdinand; Korompis, Prycilia Novita
2014-01-01
Social network now is very prevalent in the society. Today, many small enterprises sell and promote their product through social network and also many people are likely to make an online purchase especially for young generation. Social network is play a vital role in increasing someone intention to buy a product. This research is designed because there are some factor in social network that influence someone purchase intention. The original purpose of this research is to know the influence of...
A two-stage flow-based intrusion detection model for next-generation networks.
Umer, Muhammad Fahad; Sher, Muhammad; Bi, Yaxin
2018-01-01
The next-generation network provides state-of-the-art access-independent services over converged mobile and fixed networks. Security in the converged network environment is a major challenge. Traditional packet and protocol-based intrusion detection techniques cannot be used in next-generation networks due to slow throughput, low accuracy and their inability to inspect encrypted payload. An alternative solution for protection of next-generation networks is to use network flow records for detection of malicious activity in the network traffic. The network flow records are independent of access networks and user applications. In this paper, we propose a two-stage flow-based intrusion detection system for next-generation networks. The first stage uses an enhanced unsupervised one-class support vector machine which separates malicious flows from normal network traffic. The second stage uses a self-organizing map which automatically groups malicious flows into different alert clusters. We validated the proposed approach on two flow-based datasets and obtained promising results.
Multifractal modeling of the production of concentrated sugar syrup crystal
International Nuclear Information System (INIS)
Bi Sheng; Gao Jianbo
2016-01-01
High quality, concentrated sugar syrup crystal is produced in a critical step in cane sugar production: the clarification process. It is characterized by two variables: the color of the produced sugar and its clarity degree. We show that the temporal variations of these variables follow power-law distributions and can be well modeled by multiplicative cascade multifractal processes. These interesting properties suggest that the degradation in color and clarity degree has a system-wide cause. In particular, the cascade multifractal model suggests that the degradation in color and clarity degree can be equivalently accounted for by the initial “impurities” in the sugarcane. Hence, more effective cleaning of the sugarcane before the clarification stage may lead to substantial improvement in the effect of clarification. (paper)
Multifractality and herding behavior in the Japanese stock market
International Nuclear Information System (INIS)
Cajueiro, Daniel O.; Tabak, Benjamin M.
2009-01-01
In this paper we present evidence of multifractality and herding behavior for a large set of Japanese stocks traded in the Tokyo Stock Exchange. We find evidence that herding behavior occurs in periods of extreme market movements. Therefore, based on the intuition behind the tests to detect herding phenomenon developed, for instance, in Christie and Huang [Christie W, Huang R. Following the pied pier: do individual returns herd around the market? Financ Analysts J 1995;51:31-7] and Chang et al. [Chang EC, Cheng JW, Khorana A. Examination of herd behavior in equity markets: an international perspective. J Bank Finance 2000;24:1651-99], we suggest that herding behavior may be one of the causes of multifractality.
Zhang, Xianjun
The combined heat and power (CHP)-based distributed generation (DG) or dis-tributed energy resources (DERs) are mature options available in the present energy market, considered to be an effective solution to promote energy efficiency. In the urban environment, the electricity, water and natural gas distribution networks are becoming increasingly interconnected with the growing penetration of the CHP-based DG. Subsequently, this emerging interdependence leads to new topics meriting serious consideration: how much of the CHP-based DG can be accommodated and where to locate these DERs, and given preexisting constraints, how to quantify the mutual impacts on operation performances between these urban energy distribution networks and the CHP-based DG. The early research work was conducted to investigate the feasibility and design methods for one residential microgrid system based on existing electricity, water and gas infrastructures of a residential community, mainly focusing on the economic planning. However, this proposed design method cannot determine the optimal DG sizing and siting for a larger test bed with the given information of energy infrastructures. In this context, a more systematic as well as generalized approach should be developed to solve these problems. In the later study, the model architecture that integrates urban electricity, water and gas distribution networks, and the CHP-based DG system was developed. The proposed approach addressed the challenge of identifying the optimal sizing and siting of the CHP-based DG on these urban energy networks and the mutual impacts on operation performances were also quantified. For this study, the overall objective is to maximize the electrical output and recovered thermal output of the CHP-based DG units. The electricity, gas, and water system models were developed individually and coupled by the developed CHP-based DG system model. The resultant integrated system model is used to constrain the DG's electrical
Multifractal analysis for the historic set in topological dynamical systems
International Nuclear Information System (INIS)
Zhou, Xiaoyao; Chen, Ercai
2013-01-01
In this paper the historic set is divided into different level sets and we use topological pressure to describe the size of these level sets. We give an application of these results to dimension theory. Our primary focus is using topological pressure to describe the relative multifractal spectrum of ergodic averages and to give a positive answer to the conjecture posed by Olsen (2003 J. Math. Pures Appl. 82 1591–649). (paper)
Multifractal analysis of real and imaginary movements: EEG study
Pavlov, Alexey N.; Maksimenko, Vladimir A.; Runnova, Anastasiya E.; Khramova, Marina V.; Pisarchik, Alexander N.
2018-04-01
We study abilities of the wavelet-based multifractal analysis in recognition specific dynamics of electrical brain activity associated with real and imaginary movements. Based on the singularity spectra we analyze electroencephalograms (EEGs) acquired in untrained humans (operators) during imagination of hands movements, and show a possibility to distinguish between the related EEG patterns and the recordings performed during real movements or the background electrical brain activity. We discuss how such recognition depends on the selected brain region.
Chang, Gee-Kung; Ellinas, Georgios
2017-01-01
This book investigates new enabling technologies for Fi-Wi convergence. The editors discuss Fi-Wi technologies at the three major network levels involved in the path towards convergence: system level, network architecture level, and network management level. The main topics will be: a. At system level: Radio over Fiber (digitalized vs. analogic, standardization, E-band and beyond) and 5G wireless technologies; b. Network architecture level: NGPON, WDM-PON, BBU Hotelling, Cloud Radio Access Networks (C-RANs), HetNets. c. Network management level: SDN for convergence, Next-generation Point-of-Presence, Wi-Fi LTE Handover, Cooperative MultiPoint. • Addresses the Fi-Wi convergence issues at three different levels, namely at the system level, network architecture level, and network management level • Provides approaches in communication systems, network architecture, and management that are expected to steer the evolution towards fiber-wireless convergence • Contributions from leading experts in the field of...
Active local distribution network management for embedded generation
Energy Technology Data Exchange (ETDEWEB)
White, S.
2005-07-01
With the newer electric power transmission networks, there is a requirement for power to flow in two different directions and this calls for more intelligent forms of management. To satisfy these demands, GENEVAC has produced a controller that aims to increase the energy that power plants can feed to the distribution networks. The software and hardware have undergone trials at two 33/11 kV substations in England. The hardware was designed to monitor voltage, current and phase angle at various points in the network. The software estimates the value of the voltages at every node in the network. The results showed good correlation between estimated and measured voltages: other findings are reported. Recommendations for further work are made including development of a full commercial system. The study was conducted by Econnect Ltd under contract to the DTI.
Intermittency and multifractional Brownian character of geomagnetic time series
Directory of Open Access Journals (Sweden)
G. Consolini
2013-07-01
Full Text Available The Earth's magnetosphere exhibits a complex behavior in response to the solar wind conditions. This behavior, which is described in terms of mutifractional Brownian motions, could be the consequence of the occurrence of dynamical phase transitions. On the other hand, it has been shown that the dynamics of the geomagnetic signals is also characterized by intermittency at the smallest temporal scales. Here, we focus on the existence of a possible relationship in the geomagnetic time series between the multifractional Brownian motion character and the occurrence of intermittency. In detail, we investigate the multifractional nature of two long time series of the horizontal intensity of the Earth's magnetic field as measured at L'Aquila Geomagnetic Observatory during two years (2001 and 2008, which correspond to different conditions of solar activity. We propose a possible double origin of the intermittent character of the small-scale magnetic field fluctuations, which is related to both the multifractional nature of the geomagnetic field and the intermittent character of the disturbance level. Our results suggest a more complex nature of the geomagnetic response to solar wind changes than previously thought.
A Macroscopic Multifractal Analysis of Parabolic Stochastic PDEs
Khoshnevisan, Davar; Kim, Kunwoo; Xiao, Yimin
2018-05-01
It is generally argued that the solution to a stochastic PDE with multiplicative noise—such as \\dot{u}= 1/2 u''+uξ, where {ξ} denotes space-time white noise—routinely produces exceptionally-large peaks that are "macroscopically multifractal." See, for example, Gibbon and Doering (Arch Ration Mech Anal 177:115-150, 2005), Gibbon and Titi (Proc R Soc A 461:3089-3097, 2005), and Zimmermann et al. (Phys Rev Lett 85(17):3612-3615, 2000). A few years ago, we proved that the spatial peaks of the solution to the mentioned stochastic PDE indeed form a random multifractal in the macroscopic sense of Barlow and Taylor (J Phys A 22(13):2621-2626, 1989; Proc Lond Math Soc (3) 64:125-152, 1992). The main result of the present paper is a proof of a rigorous formulation of the assertion that the spatio-temporal peaks of the solution form infinitely-many different multifractals on infinitely-many different scales, which we sometimes refer to as "stretch factors." A simpler, though still complex, such structure is shown to also exist for the constant-coefficient version of the said stochastic PDE.
Dual-induced multifractality in online viewing activity
Qin, Yu-Hao; Zhao, Zhi-Dan; Cai, Shi-Min; Gao, Liang; Stanley, H. Eugene
2018-01-01
Although recent studies have found that the long-term correlations relating to the fat-tailed distribution of inter-event times exist in human activity and that these correlations indicate the presence of fractality, the property of fractality and its origin have not been analyzed. We use both detrended fluctuation analysis and multifractal detrended fluctuation analysis to analyze the time series in online viewing activity separating from Movielens and Netflix. We find long-term correlations at both the individual and communal levels and that the extent of correlation at the individual level is determined by the activity level. These long-term correlations also indicate that there is fractality in the pattern of online viewing. We first find a multifractality that results from the combined effect of the fat-tailed distribution of inter-event times (i.e., the times between successive viewing actions of individuals) and the long-term correlations in online viewing activity and verify this finding using three synthesized series. Therefore, it can be concluded that the multifractality in online viewing activity is caused by both the fat-tailed distribution of inter-event times and the long-term correlations and that this enlarges the generic property of human activity to include not just physical space but also cyberspace.
A Macroscopic Multifractal Analysis of Parabolic Stochastic PDEs
Khoshnevisan, Davar; Kim, Kunwoo; Xiao, Yimin
2018-04-01
It is generally argued that the solution to a stochastic PDE with multiplicative noise—such as \\dot{u}= 1/2 u''+uξ, where {ξ} denotes space-time white noise—routinely produces exceptionally-large peaks that are "macroscopically multifractal." See, for example, Gibbon and Doering (Arch Ration Mech Anal 177:115-150, 2005), Gibbon and Titi (Proc R Soc A 461:3089-3097, 2005), and Zimmermann et al. (Phys Rev Lett 85(17):3612-3615, 2000). A few years ago, we proved that the spatial peaks of the solution to the mentioned stochastic PDE indeed form a random multifractal in the macroscopic sense of Barlow and Taylor (J Phys A 22(13):2621-2626, 1989; Proc Lond Math Soc (3) 64:125-152, 1992). The main result of the present paper is a proof of a rigorous formulation of the assertion that the spatio-temporal peaks of the solution form infinitely-many different multifractals on infinitely-many different scales, which we sometimes refer to as "stretch factors." A simpler, though still complex, such structure is shown to also exist for the constant-coefficient version of the said stochastic PDE.
Efficient Key Generation and Distribution on Wireless Sensor Networks
Ariño Pérez, Víctor
2013-01-01
Projecte realitzat en el marc d’un programa de mobilitat amb la KTH Electrical Engineering [ANGLÈS] Wireless Sensor Networks have become popular during the last years. The introduction of IPv6 which broadened the address space available, IEEE802.15.4 and adaptation layers such as 6loWPAN have allowed the intercommunication of small devices. These networks are useful in many scenarios such as civil monitoring, mining, battlefield operations, as well as consumer products. Hence, practical se...
GLEON: An Example of Next Generation Network Biogeoscience
Weathers, K. C.; Hanson, P. C.
2014-12-01
When we think of sensor networks, we often focus on hardware development and deployments and the resulting data and synthesis. Yet, for networks that cross institutional boundaries, such as distributed federations of observatories, people are the critical network resource. They establish the linkages and enable access to and interpretation of the data. In the Global Lake Ecological Observatory Network (GLEON), we found that careful integration of three networks --people, hardware, and data--was essential to providing an effective research environment. Accomplishing this integration is not trivial and requires a shared vision among members, explicit attention to the emerging tenets of the science of team science, and training of scientists at all career stages. In GLEON these efforts have resulted in scientific inferences covering new scales, crossing broad ecosystem gradients, and capturing important environmental events. Network-level capital has been increased by the deployment of instrumented buoys, the creation of new data sets and publicly available models, and new ways to synthesize and analyze high frequency data. The formation of international teams of scientists is essential to these goals. Our approach unites a diverse membership in GLEON-style team science, with emphasis on training and engagement of graduate students while creating knowledge. Examples of the bottom-up scientific output from GLEON include creating and confronting models using high frequency data from sensor networks; interpreting output from biological sensors (e.g., algal pigment sensors) as predictors for water quality indices such as water clarity; and understanding the relationship between occasional, highly noxious algal blooms and fluorometric measurements of pigments from sensor networks. Numerical simulation models are not adequate for predicting highly skewed distributions of phytoplankton in eutrophic lakes, suggesting that our fundamental understanding of phytoplankton
A review on the impact of embedded generation to network fault level
Yahaya, M. S.; Basar, M. F.; Ibrahim, Z.; Nasir, M. N. N.; Lada, M. Y.; Bukhari, W. M.
2015-05-01
The line of Embedded Generation (EG) in power systems especially for renewable energy has increased markedly in recent years. The interconnection of EG has a technical impact which needs to considered. One of the technical challenges faced by the Distribution Network Operator (DNO) is the network fault level. In this paper, the different methods of interconnection with and without EG on the network is analyze by looking at the impact of network fault level. This comparative study made to determine the most effective method to reduce fault level or fault current. This paper will gives basic understanding on the fault level effect when synchronous generator connected to network by different method of interconnection. A three phase fault is introduced at one network bus bar. By employ it to simple network configuration of network configurations which is normal interconnection and splitting network connection with and without EG, the fault level has been simulated and analyzed. Developing the network model by using PSS-Viper™ software package, the fault level for both networks will be showed and the difference is defines. From the review, network splitting was found the best interconnection method and greatest potential for reducing the fault level in the network.
Network Edge Intelligence for the Emerging Next-Generation Internet
Directory of Open Access Journals (Sweden)
Salekul Islam
2010-11-01
Full Text Available The success of the Content Delivery Networks (CDN in the recent years has demonstrated the increased benefits of the deployment of some form of “intelligence” within the network. Cloud computing, on the other hand, has shown the benefits of economies of scale and the use of a generic infrastructure to support a variety of services. Following that trend, we propose to move away from the smart terminal-dumb network dichotomy to a model where some degree of intelligence is put back into the network, specifically at the edge, with the support of Cloud technology. In this paper, we propose the deployment of an Edge Cloud, which integrates a variety of user-side and server-side services. On the user side, surrogate, an application running on top of the Cloud, supports a virtual client. The surrogate hides the underlying network infrastructure from the user, thus allowing for simpler, more easily managed terminals. Network side services supporting delivery of and exploiting content are also deployed on this infrastructure, giving the Internet Service Providers (ISP many opportunities to become directly involved in content and service delivery.
Novel mechanism of network protection against the new generation of cyber attacks
Milovanov, Alexander; Bukshpun, Leonid; Pradhan, Ranjit
2012-06-01
A new intelligent mechanism is presented to protect networks against the new generation of cyber attacks. This mechanism integrates TCP/UDP/IP protocol stack protection and attacker/intruder deception to eliminate existing TCP/UDP/IP protocol stack vulnerabilities. It allows to detect currently undetectable, highly distributed, low-frequency attacks such as distributed denial-of-service (DDoS) attacks, coordinated attacks, botnet, and stealth network reconnaissance. The mechanism also allows insulating attacker/intruder from the network and redirecting the attack to a simulated network acting as a decoy. As a result, network security personnel gain sufficient time to defend the network and collect the attack information. The presented approach can be incorporated into wireless or wired networks that require protection against known and the new generation of cyber attacks.
The multifractal nature of plume structure in high-Rayleigh-number convection
Puthenveettil, Baburaj A.; Ananthakrishna, G.; Arakeri, Jaywant H.
2005-03-01
The geometrically different planforms of near-wall plume structure in turbulent natural convection, visualized by driving the convection using concentration differences across a membrane, are shown to have a common multifractal spectrum of singularities for Rayleigh numbers in the range 1010-1011 at Schmidt number of 602. The scaling is seen for a length scale range of 25 and is independent of the Rayleigh number, the flux, the strength and nature of the large-scale flow, and the aspect ratio. Similar scaling is observed for the plume structures obtained in the presence of a weak flow across the membrane. This common non-trivial spatial scaling is proposed to be due to the same underlying generating process for the near-wall plume structures.
Radio-location of mobile stations in third generation networks
Directory of Open Access Journals (Sweden)
Milan Manojle Šunjevarić
2013-06-01
Full Text Available Mobile station localization in mobile networks started with simple methods (e.g. Cell-ID method which required only slight modifications of network infrastructures. Principally, it was about network localization by which a localization service became available to all types of mobile phones. Due to low precision, the initiated development of more sophisticated methods has not been finished yet. Among the advanced location-based methods are those based on the measurement of location parameters in the time domain. In this paper the general consideration of radio location methods in 3G (UMTS radio networks is presented. The use of time based measurement methods was analysed in detail. Due to the limited article length, the use of other locating methods in 3G networks (based on power measurements, on radio direction measurement, and on cells identification – Cell ID and global positioning system - GPS are not described. Introduction Mobile station localization within modern cellular networks increases the level of user security and opens wide opportunities for commercial operators who provide this service. The major obstacle for the implementation of this service, which also prevents its practical usage, is the modification of the existing network infrastructure. In general, depending on the infrastructure used, positioning methods can be divided into two groups: integrated and independent. Integrated methods are primarily created for communication networks. A possibility to locate users represents just an additional service within a radio network. Independent methods are totally detached from the communication network in which the user whose location is being determined is. Radio location methods Determining the location of a mobile radio station is performed by determining the intersection of two or more lines of position. These lines represent the position of the set of points at which the mobile station may be located. These lines can be: (a
Didactic Networks: A Proposal for e-learning Content Generation
Directory of Open Access Journals (Sweden)
F. Javier Del Alamo
2010-12-01
Full Text Available The Didactic Networks proposed in this paper are based on previous publications in the field of the RSR (Rhetorical-Semantic Relations. The RSR is a set of primitive relations used for building a specific kind of semantic networks for artificial intelligence applications on the web: the RSN (Rhetorical-Semantic Networks. We bring into focus the RSR application in the field of elearning, by defining Didactic Networks as a new set of semantic patterns oriented to the development of elearning applications. The different lines we offer in our research fall mainly into three levels: (1 The most basic one is in the field of computational linguistics and related to Logical Operations on RSR (RSR Inverses and plurals, RSR combinations, etc, once they have been created. The application of Walter Bosma's results regarding rhetorical distance application and treatment as semantic weighted networks is one of the important issues here. (2 In parallel, we have been working on the creation of a knowledge representation and storage model and data architecture capable of supporting the definition of knowledge networks based on RSR. (3 The third strategic line is in the meso-level, the formulation of a molecular structure of knowledge based on the most frequently used patterns. The main contribution at this level is the set of Fundamental Cognitive Networks (FCN as an application of Novak's mental maps proposal. This paper is part of this third intermediate level, and the Fundamental Didactic Networks (FDN are the result of the application of rhetorical theory procedures to the instructional theory. We have formulated a general set of RSR capable of building discourse, making it possible to express any concept, procedure or principle in terms of knowledge nodes and RSRs. The Instructional knowledge can then be elaborated in the same way. This network structure expressing the instructional knowledge in terms of RSR makes the objective of developing web
Multifractality as a Measure of Complexity in Solar Flare Activity
Sen, Asok K.
2007-03-01
In this paper we use the notion of multifractality to describe the complexity in H α flare activity during the solar cycles 21, 22, and 23. Both northern and southern hemisphere flare indices are analyzed. Multifractal behavior of the flare activity is characterized by calculating the singularity spectrum of the daily flare index time series in terms of the Hölder exponent. The broadness of the singularity spectrum gives a measure of the degree of multifractality or complexity in the flare index data. The broader the spectrum, the richer and more complex is the structure with a higher degree of multifractality. Using this broadness measure, complexity in the flare index data is compared between the northern and southern hemispheres in each of the three cycles, and among the three cycles in each of the two hemispheres. Other parameters of the singularity spectrum can also provide information about the fractal properties of the flare index data. For instance, an asymmetry to the left or right in the singularity spectrum indicates a dominance of high or low fractal exponents, respectively, reflecting a relative abundance of large or small fluctuations in the total energy emitted by the flares. Our results reveal that in the even (22nd) cycle the singularity spectra are very similar for the northern and southern hemispheres, whereas in the odd cycles (21st and 23rd) they differ significantly. In particular, we find that in cycle 21, the northern hemisphere flare index data have higher complexity than its southern counterpart, with an opposite pattern prevailing in cycle 23. Furthermore, small-scale fluctuations in the flare index time series are predominant in the northern hemisphere in the 21st cycle and are predominant in the southern hemisphere in the 23rd cycle. Based on these findings one might suggest that, from cycle to cycle, there exists a smooth switching between the northern and southern hemispheres in the multifractality of the flaring process. This new
Automatic theory generation from analyst text files using coherence networks
Shaffer, Steven C.
2014-05-01
This paper describes a three-phase process of extracting knowledge from analyst textual reports. Phase 1 involves performing natural language processing on the source text to extract subject-predicate-object triples. In phase 2, these triples are then fed into a coherence network analysis process, using a genetic algorithm optimization. Finally, the highest-value sub networks are processed into a semantic network graph for display. Initial work on a well- known data set (a Wikipedia article on Abraham Lincoln) has shown excellent results without any specific tuning. Next, we ran the process on the SYNthetic Counter-INsurgency (SYNCOIN) data set, developed at Penn State, yielding interesting and potentially useful results.
Dynamic Session-Key Generation for Wireless Sensor Networks
Directory of Open Access Journals (Sweden)
Chen Chin-Ling
2008-01-01
Full Text Available Abstract Recently, wireless sensor networks have been used extensively in different domains. For example, if the wireless sensor node of a wireless sensor network is distributed in an insecure area, a secret key must be used to protect the transmission between the sensor nodes. Most of the existing methods consist of preselecting keys from a key pool and forming a key chain. Then, the sensor nodes make use of the key chain to encrypt the data. However, while the secret key is being transmitted, it can easily be exposed during transmission. We propose a dynamic key management protocol, which can improve the security of the key juxtaposed to existing methods. Additionally, the dynamic update of the key can lower the probability of the key to being guessed correctly. In addition, with the new protocol, attacks on the wireless sensor network can be avoided.
Dynamic Session-Key Generation for Wireless Sensor Networks
Directory of Open Access Journals (Sweden)
Cheng-Ta Li
2008-09-01
Full Text Available Recently, wireless sensor networks have been used extensively in different domains. For example, if the wireless sensor node of a wireless sensor network is distributed in an insecure area, a secret key must be used to protect the transmission between the sensor nodes. Most of the existing methods consist of preselecting m keys from a key pool and forming a key chain. Then, the sensor nodes make use of the key chain to encrypt the data. However, while the secret key is being transmitted, it can easily be exposed during transmission. We propose a dynamic key management protocol, which can improve the security of the key juxtaposed to existing methods. Additionally, the dynamic update of the key can lower the probability of the key to being guessed correctly. In addition, with the new protocol, attacks on the wireless sensor network can be avoided.
Multifractal properties of diffusion-limited aggregates and random multiplicative processes
International Nuclear Information System (INIS)
Canessa, E.
1991-04-01
We consider the multifractal properties of irreversible diffusion-limited aggregation (DLA) from the point of view of the self-similarity of fluctuations in random multiplicative processes. In particular we analyse the breakdown of multifractal behaviour and phase transition associated with the negative moments of the growth probabilities in DLA. (author). 20 refs, 5 figs
Statistical classifiers on multifractal parameters for optical diagnosis of cervical cancer
Mukhopadhyay, Sabyasachi; Pratiher, Sawon; Kumar, Rajeev; Krishnamoorthy, Vigneshram; Pradhan, Asima; Ghosh, Nirmalya; Panigrahi, Prasanta K.
2017-06-01
An augmented set of multifractal parameters with physical interpretations have been proposed to quantify the varying distribution and shape of the multifractal spectrum. The statistical classifier with accuracy of 84.17% validates the adequacy of multi-feature MFDFA characterization of elastic scattering spectroscopy for optical diagnosis of cancer.
Virtual networks pluralistic approach for the next generation of Internet
Duarte, Otto Carlos M B
2013-01-01
The first chapter of this title concerns virtualization techniques that allow sharing computational resources basically, slicing a real computational environment into virtual computational environments that are isolated from one another.The Xen and OpenFlow virtualization platforms are then presented in Chapter 2 and a performance analysis of both is provided. This chapter also defines the primitives that the network virtualization infrastructure must provide for allowing the piloting plane to manage virtual network elements.Following this, interfaces for system management of the two platform
Next-generation science information network for leading-edge applications
International Nuclear Information System (INIS)
Urushidani, S.; Matsukata, J.
2008-01-01
High-speed networks are definitely essential tools for leading-edge applications in many research areas, including nuclear fusion research. This paper describes a number of advanced features in the Japanese next-generation science information network, called SINET3, and gives researchers clues on the uses of advanced high-speed network for their applications. The network services have four categories, multiple layer transfer, enriched virtual private network, enhanced quality-of-service, and bandwidth on demand services, and comprise a versatile service platform. The paper also describes the network architecture and advanced networking capabilities that enable economical service accommodation and flexible network resource assignment as well as effective use of Japan's first 40-Gbps lines
Next-generation science information network for leading-edge applications
Energy Technology Data Exchange (ETDEWEB)
Urushidani, S. [National Institute of Informatics, 2-1-2 Hitotsubashi Chiyoda-ku, Tokyo 101-8430 (Japan)], E-mail: urushi@nii.ac.jp; Matsukata, J. [National Institute of Informatics, 2-1-2 Hitotsubashi Chiyoda-ku, Tokyo 101-8430 (Japan)
2008-04-15
High-speed networks are definitely essential tools for leading-edge applications in many research areas, including nuclear fusion research. This paper describes a number of advanced features in the Japanese next-generation science information network, called SINET3, and gives researchers clues on the uses of advanced high-speed network for their applications. The network services have four categories, multiple layer transfer, enriched virtual private network, enhanced quality-of-service, and bandwidth on demand services, and comprise a versatile service platform. The paper also describes the network architecture and advanced networking capabilities that enable economical service accommodation and flexible network resource assignment as well as effective use of Japan's first 40-Gbps lines.
International Nuclear Information System (INIS)
Joode, J. de; Jansen, J.C.; Welle, A.J. van der; Scheepers, M.J.J.
2009-01-01
The amount of decentralised electricity generation (DG) connected to distribution networks increases across EU member states. This increasing penetration of DG units poses potential costs and benefits for distribution system operators (DSOs). These DSOs are regulated since the business of electricity distribution is considered to be a natural monopoly. This paper identifies the impact of increasing DG penetration on the DSO business under varying parameters (network characteristics, DG technologies, network management type) and argues that current distribution network regulation needs to be improved in order for DSOs to continue to facilitate the integration of DG in the network. Several possible adaptations are analysed.
Transient stability of distributed generation in MV-ring networks
Coster, E.J.; Myrzik, J.M.A.; Kling, W.L.
2008-01-01
Due to the increase of distributed generation (DG) in the future it can become important to keep DG connected to the grid in order to maintain balance between consumed and generated electrical power. Keeping DG-units connected to the grid during a disturbance, the dynamic behavior of the DG-units
Multifractal in Volatility of Family Business Stocks Listed on Casablanca STOCK Exchange
Lahmiri, Salim
In this paper, we check for existence of multifractal in volatility of Moroccan family business stock returns and in volatility of Casablanca market index returns based on multifractal detrended fluctuation analysis (MF-DFA) technique. Empirical results show strong evidence of multifractal characteristics in volatility series of both family business stocks and market index. In addition, it is found that small variations in volatility of family business stocks are persistent, whilst small variations in volatility of market index are anti-persistent. However, large variations in family business volatility and market index volatility are both anti-persistent. Furthermore, multifractal spectral analysis based results show strong evidence that volatility in Moroccan family business companies exhibits more multifractality than volatility in the main stock market. These results may provide insightful information for risk managers concerned with family business stocks.
Rank-ordered multifractal analysis for intermittent fluctuations with global crossover behavior
International Nuclear Information System (INIS)
Tam, Sunny W. Y.; Chang, Tom; Kintner, Paul M.; Klatt, Eric M.
2010-01-01
The rank-ordered multifractal analysis (ROMA), a recently developed technique that combines the ideas of parametric rank ordering and one-parameter scaling of monofractals, has the capabilities of deciphering the multifractal characteristics of intermittent fluctuations. The method allows one to understand the multifractal properties through rank-ordered scaling or nonscaling parametric variables. The idea of the ROMA technique is applied to analyze the multifractal characteristics of the auroral zone electric-field fluctuations observed by the SIERRA sounding rocket. The observed fluctuations span across contiguous multiple regimes of scales with different multifractal characteristics. We extend the ROMA technique such that it can take into account the crossover behavior - with the possibility of collapsing probability distribution functions - over these contiguous regimes.
Reconfiguration of sustainable thermoelectric generation using wireless sensor network
DEFF Research Database (Denmark)
Chen, Min
2014-01-01
wireless sensor networks (WSNs), where remotely deployed temperature and voltage sensors as well as latching relays can be organized as a whole to intelligently identify and execute the optimal interconnection of TEM strings. A reconfigurable TEM array with a WSN controller and a maximum power point...
Generating Predictive Movie Recommendations from Trust in Social Networks
National Research Council Canada - National Science Library
Golbeck, Jennifer
2006-01-01
.... Using the FilmTrust system as a foundation, they show that these recommendations are more accurate than other techniques when the user's opinions about a film are divergent from the average. They discuss this technique both as an application of social network analysis and how it suggests other analyses that can be performed to help improve collaborative filtering algorithms of all types.
Next generation network performance management: a business perspective
CSIR Research Space (South Africa)
Harding, C
2010-08-01
Full Text Available multitude of transport and access technologies on almost any user device. The most important and integral component of the NGCN NGN Architectural Framework is the physical and logical management of the network elements and services to provide maximum utility...
Perspectives on next-generation technology for environmental sensor networks
Barbara J. Benson; Barbara J. Bond; Michael P. Hamilton; Russell K. Monson; Richard Han
2009-01-01
Sensor networks promise to transform and expand environmental science. However, many technological difficulties must be overcome to achieve this potential. Partnerships of ecologists with computer scientists and engineers are critical in meeting these challenges. Technological issues include promoting innovation in new sensor design, incorporating power optimization...
Optimal placement of distributed generation in distribution networks ...
African Journals Online (AJOL)
This paper proposes the application of Particle Swarm Optimization (PSO) technique to find the optimal size and optimum location for the placement of DG in the radial distribution networks for active power compensation by reduction in real power losses and enhancement in voltage profile. In the first segment, the optimal ...
IMECCHI-DATANETWORK: empowering knowledge generation through international data network
Directory of Open Access Journals (Sweden)
Marie Annick Le Pogam
2017-04-01
Within the IMECCHI-DATANETWORK initiative, databases from various countries will be locally converted in a CDM which will facilitate study replication in a distributed fashion while granting interoperability across coding systems. Through such international data networks, data are empowered for creating results which are generalizable to multiple countries. Cross-border data sharing and international comparisons are also facilitated.
The Impact of Distributed Generation on Distribution Networks ...
African Journals Online (AJOL)
Their advantages are the ability to reduce or postpone the need for investment in the transmission and distribution infrastructure when optimally located; the ability to reduce technical losses within the transmission and distribution networks as well as general improvement in power quality and system reliability. This paper ...
Life cycle assessment of second generation (2G) and third generation (3G) mobile phone networks.
Scharnhorst, Wolfram; Hilty, Lorenz M; Jolliet, Olivier
2006-07-01
The environmental performance of presently operated GSM and UMTS networks was analysed concentrating on the environmental effects of the End-of-Life (EOL) phase using the Life Cycle Assessment (LCA) method. The study was performed based on comprehensive life cycle inventory and life cycle modelling. The environmental effects were quantified using the IMPACT2002+ method. Based on technological forecasts, the environmental effects of forthcoming mobile telephone networks were approximated. The results indicate that a parallel operation of GSM and UMTS networks is environmentally detrimental and the transition phase should be kept as short as possible. The use phase (i.e. the operation) of the radio network components account for a large fraction of the total environmental impact. In particular, there is a need to lower the energy consumption of those network components. Seen in relation to each other, UMTS networks provide an environmentally more efficient mobile communication technology than GSM networks. In assessing the EOL phase, recycling the electronic scrap of mobile phone networks was shown to have clear environmental benefits. Under the present conditions, material recycling could help lower the environmental impact of the production phase by up to 50%.
The generation of random directed networks with prescribed 1-node and 2-node degree correlations
Energy Technology Data Exchange (ETDEWEB)
Zamora-Lopez, Gorka; Kurths, Juergen [Institute of Physics, University of Potsdam, PO Box 601553, 14415 Potsdam (Germany); Zhou Changsong [Department of Physics, Hong Kong Baptist University, Kowloon Tong, Hong Kong (China); Zlatic, Vinko [Rudjer Boskovic Institute, PO Box 180, HR-10002 Zagreb (Croatia)
2008-06-06
The generation of random networks is a very common problem in complex network research. In this paper, we have studied the correlation nature of several real networks and found that, typically, a large number of links are deterministic, i.e. they cannot be randomized. This finding permits fast generation of ensembles of maximally random networks with prescribed 1-node and 2-node degree correlations. When the introduction of self-loops or multiple-links are not desired, random network generation methods typically reach blocked states. Here, a mechanism is proposed, the 'force-and-drop' method, to overcome such states. Our algorithm can be easily simplified for undirected graphs and reduced to account for any subclass of 2-node degree correlations.
The generation of random directed networks with prescribed 1-node and 2-node degree correlations
International Nuclear Information System (INIS)
Zamora-Lopez, Gorka; Kurths, Juergen; Zhou Changsong; Zlatic, Vinko
2008-01-01
The generation of random networks is a very common problem in complex network research. In this paper, we have studied the correlation nature of several real networks and found that, typically, a large number of links are deterministic, i.e. they cannot be randomized. This finding permits fast generation of ensembles of maximally random networks with prescribed 1-node and 2-node degree correlations. When the introduction of self-loops or multiple-links are not desired, random network generation methods typically reach blocked states. Here, a mechanism is proposed, the 'force-and-drop' method, to overcome such states. Our algorithm can be easily simplified for undirected graphs and reduced to account for any subclass of 2-node degree correlations
Power generation using photovoltaic induction in an isolated power network
International Nuclear Information System (INIS)
Kalantar, M.; Jiang, J.
2001-01-01
Owing to increased emphasis on renewable resources, the development of suitable isolated power generators driven by energy sources, the development of suitable isolated power generators driven by energy sources such as photovoltaic, wind, small hydroelectric, biogas and etc. has recently assumed greater significance. A single phase capacitor self excited induction generator has emerged as a suitable candidate of isolated power sources. This paper presents performance analysis of a single phase self-excited induction generator driven by photovoltaic (P V) system for low power isolated stand-alone applications. A single phase induction machine can work as a self-excited induction generator when its rotor is driven at suitable speed by an photovoltaic powered do motor. Its excitation is provided by connecting a single phase capacitor bank at a stator terminals. Either to augment grid power or to get uninterrupted power during grid failure stand-alone low capacity ac generators are used. These are driven by photovoltaic, wind power or I C engines using kerosene, diesel, petrol or biogas as fuel. Self-excitation with capacitors at the stator terminals of the stator terminals of the induction machines is well demonstrated experimentally on a P V powered dc motor-induction machine set. The parameters and the excitation requirements of the induction machine run in self-excited induction generator mode are determined. The effects of variations in prime mover speed,terminal capacitance and load power factor on the machine terminal voltage are studied
Directory of Open Access Journals (Sweden)
Dustin eFetterhoff
2015-09-01
Full Text Available Fractality, represented as self-similar repeating patterns, is ubiquitous in nature and the brain. Dynamic patterns of hippocampal spike trains are known to exhibit multifractal properties during working memory processing; however, it is unclear whether the multifractal properties inherent to hippocampal spike trains reflect active cognitive processing. To examine this possibility, hippocampal neuronal ensembles were recorded from rats before, during and after a spatial working memory task following administration of tetrahydrocannabinol (THC, a memory-impairing component of cannabis. Multifractal detrended fluctuation analysis was performed on hippocampal interspike interval sequences to determine characteristics of monofractal long-range temporal correlations (LRTCs, quantified by the Hurst exponent, and the degree/magnitude of multifractal complexity, quantified by the width of the singularity spectrum. Our results demonstrate that multifractal firing patterns of hippocampal spike trains are a marker of functional memory processing, as they are more complex during the working memory task and significantly reduced following administration of memory impairing THC doses. Conversely, LRTCs are largest during resting state recordings, therefore reflecting different information compared to multifractality. In order to deepen conceptual understanding of multifractal complexity and LRTCs, these measures were compared to classical methods using hippocampal frequency content and firing variability measures. These results showed that LRTCs, multifractality, and theta rhythm represent independent processes, while delta rhythm correlated with multifractality. Taken together, these results provide a novel perspective on memory function by demonstrating that the multifractal nature of spike trains reflects hippocampal microcircuit activity that can be used to detect and quantify cognitive, physiological and pathological states.
Next generation network based carrier ethernet test bed for IPTV traffic
DEFF Research Database (Denmark)
Fu, Rong; Berger, Michael Stübert; Zheng, Yu
2009-01-01
This paper presents a Carrier Ethernet (CE) test bed based on the Next Generation Network (NGN) framework. After the concept of CE carried out by Metro Ethernet Forum (MEF), the carrier-grade Ethernet are obtaining more and more interests and being investigated as the low cost and high performanc...... services of transport network to carry the IPTV traffic. This test bed is approaching to support the research on providing a high performance carrier-grade Ethernet transport network for IPTV traffic....
Optimal placement of distributed generation in distribution networks
African Journals Online (AJOL)
user
The objective of power system operation is to meet the demand at all the locations ... The traditional electric power generation systems utilize the conventional energy resources, such as fossil ..... Power Distribution Planning Reference Book.
Generation of tunable and pulsatile concentration gradients via microfluidic network
Zhou, Bingpu; Xu, Wei; Wang, Cong; Chau, Yeungyeung; Zeng, Xiping; Zhang, Xixiang; Shen, Rong; Wen, Weijia
2014-01-01
We demonstrate a compact Polydimethylsiloxane microfluidic chip which can quickly generate ten different chemical concentrations simultaneously. The concentration magnitude of each branch can be flexibly regulated based on the flow rate ratios
Social network indices in the Generations and Gender Survey: An appraisal
Directory of Open Access Journals (Sweden)
Pearl A. Dykstra
2016-06-01
Full Text Available Background: In this contribution we critically appraise the social network indices in the Generations and Gender Survey (GGS. Objective: After discussing the rationale for including social network indices in the GGS, we provide descriptive information on social network characteristics and an overview of substantive questions that have been addressed using GGS social network data: antecedents and consequences of demographic behaviour, care, and differences in well-being. We identify topics that have received relatively little attention in GGS research so far, despite the availability of novel and appropriate social network data. We end with a discussion of what is unique about the social network indices in the GGS. Methods: The descriptive information on social network characteristics is based on empirical analyses of GGS data, and an experimental pilot study. The overview of GGS research using social network indices is based on a library search. The identification of what is unique about the social network indices in the GGS is based on a comparison with the European Quality of Life Survey (EQLS, the Survey of Health, Ageing and Retirement (SHARE, and the International Social Survey Program (ISSP. Results: Results show a high representation of family members in the social networks, and confirm the adequacy of using a cap of five names for network-generating questions. GGS research using the social network indices has largely focused on determinants of fertility behaviour, intergenerational linkages in families, and downward care transfers. Conclusions: Topics that have received relatively little attention are demographic behaviours other than those related to parenthood, upward transfers of practical support, ties with siblings, and stepfamily ties. Social network indices in the GGS show a high degree of overlap with those in other international surveys. The unique features are the inventory of family ties ever born and still living, and the
Techno Generation: Social Networking amongst Youth in South Africa
Basson, Antoinette; Makhasi, Yoliswa; van Vuuren, Daan
Internet and cell phones can be considered as new media compared to traditional media types and have become a fundamental part of the lives of many young people across the globe. The exploratory research study investigated the diffusion and adoption of new media innovations among adolescents. It was found that new media have diffused at a high rate among South African adolescents who are not only the innovators in this area, but also changing their life styles to adapt to the new media. Social networking grew to prominence in South Africa especially among the youth. The protection of children from potential harmful exposure and other risks remain a concern and adequate measures need to be initiated and implemented for children to enjoy social networks and other forms of new media. The exploratory research study provided worthwhile and interesting insights into the role of the new media, in the lives of adolescents in South Africa.
Sequential Triangle Strip Generator based on Hopfield Networks
Czech Academy of Sciences Publication Activity Database
Šíma, Jiří; Lněnička, Radim
2009-01-01
Roč. 21, č. 2 (2009), s. 583-617 ISSN 0899-7667 R&D Projects: GA MŠk(CZ) 1M0545; GA AV ČR 1ET100300517; GA MŠk 1M0572 Institutional research plan: CEZ:AV0Z10300504; CEZ:AV0Z10750506 Keywords : sequential triangle strip * combinatorial optimization * Hopfield network * minimum energy * simulated annealing Subject RIV: IN - Informatics, Computer Science Impact factor: 2.175, year: 2009
Lawler, James P.; Molluzzo, John C.; Doshi, Vijal
2012-01-01
Social networking on the Internet continues to be a frequent avenue of communication, especially among Net Generation consumers, giving benefits both personal and professional. The benefits may be eventually hindered by issues in information gathering and sharing on social networking sites. This study evaluates the perceptions of students taking a…
Fluid power network for centralized electricity generation in offshore wind farms
Jarquin-Laguna, A.
2014-01-01
An innovative and completely different wind-energy conversion system is studied where a centralized electricity generation within a wind farm is proposed by means of a hydraulic network. This paper presents the dynamic interaction of two turbines when they are coupled to the same hydraulic network.
Column Generation for Transmission Switching of Electricity Networks with Unit Commitment
DEFF Research Database (Denmark)
Villumsen, Jonas Christoffer; Philpott, Andy B.
2011-01-01
This paper presents the problem of finding the minimum cost dispatch and commitment of power generation units in a transmission network with active switching.We use the term active switching to denote the use of switches to optimize network topology in an operational context. We propose a Dantzig...
Privacy and Generation Y: Applying Library Values to Social Networking Sites
Fernandez, Peter
2010-01-01
Librarians face many challenges when dealing with issues of privacy within the mediated space of social networking sites. Conceptually, social networking sites differ from libraries on privacy as a value. Research about Generation Y students, the primary clientele of undergraduate libraries, can inform librarians' relationship to this important…
Andrews-Hanna, Jessica R.; Smallwood, Jonathan; Spreng, R. Nathan
2014-01-01
Though only a decade has elapsed since the default network was first emphasized as being a large-scale brain system, recent years have brought great insight into the network’s adaptive functions. A growing theme highlights the default network as playing a key role in internally-directed—or self-generated—thought. Here, we synthesize recent findings from cognitive science, neuroscience, and clinical psychology to focus attention on two emerging topics as current and future directions surrounding the default network. First, we present evidence that self-generated thought is a multi-faceted construct whose component processes are supported by different subsystems within the network. Second, we highlight the dynamic nature of the default network, emphasizing its interaction with executive control systems when regulating aspects of internal thought. We conclude by discussing clinical implications of disruptions to the integrity of the network, and consider disorders when thought content becomes polarized or network interactions become disrupted or imbalanced. PMID:24502540
Distributed generation connected to the local network - a guide
Energy Technology Data Exchange (ETDEWEB)
NONE
2005-07-01
This guide provides advice to the developers and operators of small distributed generation plant (including microgenerators) in the UK about the practical issues associated with connecting their plant and trading their output. Particular attention is given to sales revenues and how to access these revenue streams, including the mechanisms for purchasing Renewable Obligation Certificates (ROCs). The guide clarifies key terms, explains the wholesale trading system and provides an overview of sales opportunities (including ROCs and Levy Exemption Certificates (LECs)). Requirements on small distributed generation (including licensing, claiming class exemptions and metering) are described and the commercial aspects of connection (including the recent reduction in the barriers to connection) examined. Microgeneration (ie generators below 10 kW) issues are covered in their own chapter. The six appendices contain: background information about the industry; a list of purchasers of electricity from small distributed generators; descriptions of the generation, transmission and supply industries; information about industry standards and their governance; the role of government departments and institutions; and a glossary and other links.
Statistical and Multifractal Evaluation of Soil Compaction in a Vineyard
Marinho, M.; Raposo, J. R.; Mirás Avalos, J. M.; Paz González, A.
2012-04-01
One of the detrimental effects caused by agricultural machines is soil compaction, which can be defined by an increase in soil bulk density. Soil compaction often has a negative impact on plant growth, since it reduces the macroporosity and soil permeability and increases resistance to penetration. Our research explored the effect of the agricultural machinery on soil when trafficking through a vineyard at a small spatial scale, based on the evaluation of the soil compaction status. The objectives of this study were: i) to quantify soil bulk density along transects following wine row, wheel track and outside track, and, ii) to characterize the variability of the bulk density along these transects using multifractal analysis. The field work was conducted at the experimental farm of EVEGA (Viticulture and Enology Centre of Galicia) located in Ponte San Clodio, Leiro, Orense, Spain. Three parallel transects were marked on positions with contrasting machine traffic effects, i.e. vine row, wheel-track and outside-track. Undisturbed samples were collected in 16 points of each transect, spaced 0.50 m apart, for bulk density determination using the cylinder method. Samples were taken in autumn 2011, after grape harvest. Since soil between vine rows was tilled and homogenized beginning spring 2011, cumulative effects of traffic during the vine growth period could be evaluated. The distribution patterns of soil bulk density were characterized by multifractal analysis carried out by the method of moments. Multifractality was assessed by several indexes derived from the mass exponent, τq, the generalized dimension, Dq, and the singularity spectrum, f(α), curves. Mean soil bulk density values determined for vine row, outside-track and wheel-track transects were 1.212 kg dm-3, 1.259 kg dm-3and 1.582 kg dm-3, respectively. The respective coefficients of variation (CV) for these three transects were 7.76%, 4.82% and 2.03%. Therefore mean bulk density under wheel-track was 30
Generating prior probabilities for classifiers of brain tumours using belief networks
Directory of Open Access Journals (Sweden)
Arvanitis Theodoros N
2007-09-01
Full Text Available Abstract Background Numerous methods for classifying brain tumours based on magnetic resonance spectra and imaging have been presented in the last 15 years. Generally, these methods use supervised machine learning to develop a classifier from a database of cases for which the diagnosis is already known. However, little has been published on developing classifiers based on mixed modalities, e.g. combining imaging information with spectroscopy. In this work a method of generating probabilities of tumour class from anatomical location is presented. Methods The method of "belief networks" is introduced as a means of generating probabilities that a tumour is any given type. The belief networks are constructed using a database of paediatric tumour cases consisting of data collected over five decades; the problems associated with using this data are discussed. To verify the usefulness of the networks, an application of the method is presented in which prior probabilities were generated and combined with a classification of tumours based solely on MRS data. Results Belief networks were constructed from a database of over 1300 cases. These can be used to generate a probability that a tumour is any given type. Networks are presented for astrocytoma grades I and II, astrocytoma grades III and IV, ependymoma, pineoblastoma, primitive neuroectodermal tumour (PNET, germinoma, medulloblastoma, craniopharyngioma and a group representing rare tumours, "other". Using the network to generate prior probabilities for classification improves the accuracy when compared with generating prior probabilities based on class prevalence. Conclusion Bayesian belief networks are a simple way of using discrete clinical information to generate probabilities usable in classification. The belief network method can be robust to incomplete datasets. Inclusion of a priori knowledge is an effective way of improving classification of brain tumours by non-invasive methods.
Strong anticipation: Multifractal cascade dynamics modulate scaling in synchronization behaviors
International Nuclear Information System (INIS)
Stephen, Damian G.; Dixon, James A.
2011-01-01
Research highlights: → We investigated anticipatory behaviors in response to chaotic metronomes. → We assessed multifractal structure in tap intervals and onset intervals. → Strength of multifractality in tap intervals appears to match that in onset intervals. - Abstract: Previous research on anticipatory behaviors has found that the fractal scaling of human behavior may attune to the fractal scaling of an unpredictable signal [Stephen DG, Stepp N, Dixon JA, Turvey MT. Strong anticipation: Sensitivity to long-range correlations in synchronization behavior. Physica A 2008;387:5271-8]. We propose to explain this attunement as a case of multifractal cascade dynamics [Schertzer D, Lovejoy S. Generalised scale invariance in turbulent phenomena. Physico-Chem Hydrodyn J 1985;6:623-5] in which perceptual-motor fluctuations are coordinated across multiple time scales. This account will serve to sharpen the contrast between strong and weak anticipation: whereas the former entails a sensitivity to the intermittent temporal structure of an unpredictable signal, the latter simply predicts sensitivity to an aggregate description of an unpredictable signal irrespective of actual sequence. We pursue this distinction through a reanalysis of Stephen et al.'s data by examining the relationship between the widths of singularity spectra for intertap interval time series and for each corresponding interonset interval time series. We find that the attunement of fractal scaling reported by Stephen et al. was not the trivial result of sensitivity to temporal structure in aggregate but reflected a subtle sensitivity to the coordination across multiple time scales of fluctuation in the unpredictable signal.
Embedded generation: issues arising in network charging and supply
International Nuclear Information System (INIS)
1999-01-01
This study has been commissioned by ETSU, as part of the DTI's New and Renewable Energy Commercialisation programme, with the intention of informing the debate about the appropriate basis for transmission and distribution charges for, and supply of electricity by, Embedded Generators (EGs). (Author)
Centralized electricity generation in offshore wind farms using hydraulic networks
Jarquin Laguna, A.
2017-01-01
The work presented in this thesis explores a new way of generation, collection and transmission of wind energy inside a wind farm, in which the electrical conversion does not occur during any intermediate conversion step before the energy has reached the offshore central platform. A centralized
Embedded generation: issues arising in network charging and supply
Energy Technology Data Exchange (ETDEWEB)
NONE
1999-07-01
This study has been commissioned by ETSU, as part of the DTI's New and Renewable Energy Commercialisation programme, with the intention of informing the debate about the appropriate basis for transmission and distribution charges for, and supply of electricity by, Embedded Generators (EGs). (Author)
Learning Orthographic Structure with Sequential Generative Neural Networks
Testolin, Alberto; Stoianov, Ivilin; Sperduti, Alessandro; Zorzi, Marco
2016-01-01
Learning the structure of event sequences is a ubiquitous problem in cognition and particularly in language. One possible solution is to learn a probabilistic generative model of sequences that allows making predictions about upcoming events. Though appealing from a neurobiological standpoint, this approach is typically not pursued in…
Multifractal characterization of cerebrovascular dynamics in newborn rats
International Nuclear Information System (INIS)
Pavlov, A.N.; Semyachkina-Glushkovskaya, O.V.; Lychagov, V.V.; Abdurashitov, A.S.; Pavlova, O.N.; Sindeeva, O.A.; Sindeev, S.S.
2015-01-01
In this paper we study the cerebrovascular dynamics in newborn rats using the wavelet-based multifractal formalism in order to reveal effective markers of early pathological changes in the macro- and microcirculation at the hidden stage of the development of intracranial hemorrhage (ICH). We demonstrate that the singularity spectrum estimated with the wavelet-transform modulus maxima (WTMM) technique allows clear characterization of a reduced complexity of blood flow dynamics and changes of the correlation properties at the transformation of normal physiological processes into pathological dynamics that are essentially different at the level of large and small blood vessels
Column generation algorithms for virtual network embedding in flexi-grid optical networks.
Lin, Rongping; Luo, Shan; Zhou, Jingwei; Wang, Sheng; Chen, Bin; Zhang, Xiaoning; Cai, Anliang; Zhong, Wen-De; Zukerman, Moshe
2018-04-16
Network virtualization provides means for efficient management of network resources by embedding multiple virtual networks (VNs) to share efficiently the same substrate network. Such virtual network embedding (VNE) gives rise to a challenging problem of how to optimize resource allocation to VNs and to guarantee their performance requirements. In this paper, we provide VNE algorithms for efficient management of flexi-grid optical networks. We provide an exact algorithm aiming to minimize the total embedding cost in terms of spectrum cost and computation cost for a single VN request. Then, to achieve scalability, we also develop a heuristic algorithm for the same problem. We apply these two algorithms for a dynamic traffic scenario where many VN requests arrive one-by-one. We first demonstrate by simulations for the case of a six-node network that the heuristic algorithm obtains very close blocking probabilities to exact algorithm (about 0.2% higher). Then, for a network of realistic size (namely, USnet) we demonstrate that the blocking probability of our new heuristic algorithm is about one magnitude lower than a simpler heuristic algorithm, which was a component of an earlier published algorithm.
International Nuclear Information System (INIS)
Scheepers, M.J.J.; Jansen, J.C.; De Joode, J.; Bauknecht, D.; Gomez, T.; Pudjianto, D.; Strbac, G.; Ropenus, S.
2007-11-01
The growth of distributed electricity supply of renewable energy sources (RES-E) and combined heat and power (CHP) - so called distributed generation (DG) - can cause technical problems for electricity distribution networks. These integration problems can be overcome by reinforcing the network. Many European Member States apply network regulation that does not account for the impact of DG growth on the network costs. Passing on network integration costs to the DG-operator who is responsible for these extra costs may result in discrimination between different DG plants and between DG and large power generation. Therefore, in many regulatory systems distribution system operators (DSOs) are not being compensated for the DG integration costs. The DG-GRID project analysed technical and economical barriers for integration of distributed generation into electricity distribution networks. The project looked into the impact of a high DG deployment on the electricity distribution system costs and the impact on the financial position of the DSO. Several ways for improving network regulation in order to compensate DSOs for the increasing DG penetration were identified and tested. The DG-GRID project looked also into stimulating network innovations through economic regulation. The project was co-financed by the European Commission and carried out by nine European universities and research institutes. This report summarises the project results and is based on a number of DG-GRID reports that describe the conducted analyses and their results
Fractal and multifractal analysis of LiF thin film surface
International Nuclear Information System (INIS)
Yadav, R.P.; Dwivedi, S.; Mittal, A.K.; Kumar, M.; Pandey, A.C.
2012-01-01
Highlights: ► Fractal and multifractal analysis of surface morphologies of the LiF thin films. ► Complexity and roughness of the LiF thin films increases as thickness increases. ► LiF thin films are multifractal in nature. ► Strength of the multifractality increases with thickness of the film. - Abstract: Fractal and multifractal analysis is performed on the atomic force microscopy (AFM) images of the surface morphologies of the LiF thin films of thickness 10 nm, 20 nm, and 40 nm, respectively. Autocorrelation function, height–height correlation function, and two-dimensional multifractal detrended fluctuation analysis (MFDFA) are used for characterizing the surface. It is found that the interface width, average roughness, lateral correlation length, and fractal dimension of the LiF thin film increase with the thickness of the film, whereas the roughness exponent decreases with thickness. Thus, the complexity and roughness of the LiF thin films increases as thickness increases. It is also demonstrated that the LiF thin films are multifractal in nature. Strength of the multifractality increases with thickness of the film.
Stokking, H.M.; Kaptein, A.M.; Veenhuizen, A.T.; Spitters4, M.M.; Niamut, O.A.
2013-01-01
This paper describes the work in the FP7 STEER project on augmenting a live broadcast with live user generated content. This user generated content consists of both video content, captured with mobile devices, and social network content, such as Facebook or Twitter messages. To enable multi-source
Securing Networks from Modern Threats using Next Generation Firewalls
Delgiusto, Valter
2016-01-01
Classic firewalls have long been unable to cope with modern threats that ordinary Internet users are exposed to. This thesis discusses their successors - the next-generation firewalls. The first part of the thesis describes modern threats and attacks. We described in detail the DoS and APT attacks, which are among the most frequent and which may cause most damage to the system under attack. Then we explained the theoretical basics of firewalls and described the functionalities of next gen...
Network integration of distributed generation: international research and development
Energy Technology Data Exchange (ETDEWEB)
Watson, J.
2003-07-01
This report provides information on privately and publicly funded research and development programmes in distributed generation (DG) in the USA, the European Union and Japan. Protection systems for the installation of DG, power electronics for the connection of DG to electricity distribution systems, reliability modelling, power quality issues, connection standards, and simulation and computer modelling are examined. The relevance of the programmes to the UK is considered.
Generation of Complex Karstic Conduit Networks with a Hydro-chemical Model
De Rooij, R.; Graham, W. D.
2016-12-01
The discrete-continuum approach is very well suited to simulate flow and solute transport within karst aquifers. Using this approach, discrete one-dimensional conduits are embedded within a three-dimensional continuum representative of the porous limestone matrix. Typically, however, little is known about the geometry of the karstic conduit network. As such the discrete-continuum approach is rarely used for practical applications. It may be argued, however, that the uncertainty associated with the geometry of the network could be handled by modeling an ensemble of possible karst conduit networks within a stochastic framework. We propose to generate stochastically realistic karst conduit networks by simulating the widening of conduits as caused by the dissolution of limestone over geological relevant timescales. We illustrate that advanced numerical techniques permit to solve the non-linear and coupled hydro-chemical processes efficiently, such that relatively large and complex networks can be generated in acceptable time frames. Instead of specifying flow boundary conditions on conduit cells to recharge the network as is typically done in classical speleogenesis models, we specify an effective rainfall rate over the land surface and let model physics determine the amount of water entering the network. This is advantageous since the amount of water entering the network is extremely difficult to reconstruct, whereas the effective rainfall rate may be quantified using paleoclimatic data. Furthermore, we show that poorly known flow conditions may be constrained by requiring a realistic flow field. Using our speleogenesis model we have investigated factors that influence the geometry of simulated conduit networks. We illustrate that our model generates typical branchwork, network and anastomotic conduit systems. Flow, solute transport and water ages in karst aquifers are simulated using a few illustrative networks.
Directory of Open Access Journals (Sweden)
Shan Yang
2016-01-01
Full Text Available Power flow calculation and short circuit calculation are the basis of theoretical research for distribution network with inverter based distributed generation. The similarity of equivalent model for inverter based distributed generation during normal and fault conditions of distribution network and the differences between power flow and short circuit calculation are analyzed in this paper. Then an integrated power flow and short circuit calculation method for distribution network with inverter based distributed generation is proposed. The proposed method let the inverter based distributed generation be equivalent to Iθ bus, which makes it suitable to calculate the power flow of distribution network with a current limited inverter based distributed generation. And the low voltage ride through capability of inverter based distributed generation can be considered as well in this paper. Finally, some tests of power flow and short circuit current calculation are performed on a 33-bus distribution network. The calculated results from the proposed method in this paper are contrasted with those by the traditional method and the simulation method, whose results have verified the effectiveness of the integrated method suggested in this paper.
Probabilistic generation of random networks taking into account information on motifs occurrence.
Bois, Frederic Y; Gayraud, Ghislaine
2015-01-01
Because of the huge number of graphs possible even with a small number of nodes, inference on network structure is known to be a challenging problem. Generating large random directed graphs with prescribed probabilities of occurrences of some meaningful patterns (motifs) is also difficult. We show how to generate such random graphs according to a formal probabilistic representation, using fast Markov chain Monte Carlo methods to sample them. As an illustration, we generate realistic graphs with several hundred nodes mimicking a gene transcription interaction network in Escherichia coli.
DEFF Research Database (Denmark)
Wulff-Jensen, Andreas; Rant, Niclas Nerup; Møller, Tobias Nordvig
2018-01-01
as it has been used to generate game maps in previous productions [3, 4]. The diversity test showed the generated maps had a significantly greater diversity than the Perlin noise maps. Afterwards the heightmaps was converted to 3D maps in Unity3D. The 3D maps’ perceived realism and videogame usability...
A Methodology for Physical Interconnection Decisions of Next Generation Transport Networks
DEFF Research Database (Denmark)
Gutierrez Lopez, Jose Manuel; Riaz, M. Tahir; Madsen, Ole Brun
2011-01-01
of possibilities when designing the physical network interconnection. This paper develops and presents a methodology in order to deal with aspects related to the interconnection problem of optical transport networks. This methodology is presented as independent puzzle pieces, covering diverse topics going from......The physical interconnection for optical transport networks has critical relevance in the overall network performance and deployment costs. As telecommunication services and technologies evolve, the provisioning of higher capacity and reliability levels is becoming essential for the proper...... development of Next Generation Networks. Currently, there is a lack of specific procedures that describe the basic guidelines to design such networks better than "best possible performance for the lowest investment". Therefore, the research from different points of view will allow a broader space...
Cheng, K.; Guo, L. M.; Wang, Y. K.; Zafar, M. T.
2017-11-01
In order to select effective samples in the large number of data of PV power generation years and improve the accuracy of PV power generation forecasting model, this paper studies the application of clustering analysis in this field and establishes forecasting model based on neural network. Based on three different types of weather on sunny, cloudy and rainy days, this research screens samples of historical data by the clustering analysis method. After screening, it establishes BP neural network prediction models using screened data as training data. Then, compare the six types of photovoltaic power generation prediction models before and after the data screening. Results show that the prediction model combining with clustering analysis and BP neural networks is an effective method to improve the precision of photovoltaic power generation.
Generation of tunable and pulsatile concentration gradients via microfluidic network
Zhou, Bingpu
2014-06-04
We demonstrate a compact Polydimethylsiloxane microfluidic chip which can quickly generate ten different chemical concentrations simultaneously. The concentration magnitude of each branch can be flexibly regulated based on the flow rate ratios of the two injecting streams. The temporal/pulsatile concentration gradients are achieved by integrating on-chip pneumatic actuated valves controlled by the external signals. The temporal concentration gradients can also be tuned precisely by varying applied frequency and duty cycle of the trigger signal. It is believed that such microdevice will be potentially used for some application areas of producing stable chemical gradients as well as allowing fast, pulsatile gradient transformation in seconds.
Multifractality in edge localized modes in Japan Atomic Energy Research Institute Tokamak-60 Upgrade
International Nuclear Information System (INIS)
Bak, P.E.; Asakura, N.; Miura, Y.; Nakano, T.; Yoshino, R.
2001-01-01
The temporal losses of confinement during edge localized modes in the Japan Atomic Energy Research Institute Tokamak-60 Upgrade (JT-60U) show multifractal scaling and the spectra are generally smooth, but in some cases there are signs of discontinuous derivatives. Dynamics of the Sugama-Horton model, interpreted as edge localized modes, also display multifractal scaling. The spectra display singularities in the derivative, which can be interpreted as a phase transition. It is argued that the multifractal spectra of edge localized modes can be used to discriminate between different experimental discharges and validate edge localized mode models
Multifractals in Western Major STOCK Markets Historical Volatilities in Times of Financial Crisis
Lahmiri, Salim
In this paper, the generalized Hurst exponent is used to investigate multifractal properties of historical volatility (CHV) in stock market price and return series before, during and after 2008 financial crisis. Empirical results from NASDAQ, S&P500, TSE, CAC40, DAX, and FTSE stock market data show that there is strong evidence of multifractal patterns in HV of both price and return series. In addition, financial crisis deeply affected the behavior and degree of multifractality in volatility of Western financial markets at price and return levels.
Network Characteristics and the Value of Collaborative User-Generated Content
Sam Ransbotham; Gerald C. Kane; Nicholas H. Lurie
2012-01-01
User-generated content is increasingly created through the collaborative efforts of multiple individuals. In this paper, we argue that the value of collaborative user-generated content is a function both of the direct efforts of its contributors and of its embeddedness in the content-contributor network that creates it. An analysis of Wikipedia's WikiProject Medicine reveals a curvilinear relationship between the number of distinct contributors to user-generated content and viewership. A two-...
Software Defined Networking for Next Generation Converged Metro-Access Networks
Ruffini, M.; Slyne, F.; Bluemm, C.; Kitsuwan, N.; McGettrick, S.
2015-12-01
While the concept of Software Defined Networking (SDN) has seen a rapid deployment within the data center community, its adoption in telecommunications network has progressed slowly, although the concept has been swiftly adopted by all major telecoms vendors. This paper presents a control plane architecture for SDN-driven converged metro-access networks, developed through the DISCUS European FP7 project. The SDN-based controller architecture was developed in a testbed implementation targeting two main scenarios: fast feeder fiber protection over dual-homed Passive Optical Networks (PONs) and dynamic service provisioning over a multi-wavelength PON. Implementation details and results of the experiment carried out over the second scenario are reported in the paper, showing the potential of SDN in providing assured on-demand services to end-users.
Toward the automated generation of genome-scale metabolic networks in the SEED.
DeJongh, Matthew; Formsma, Kevin; Boillot, Paul; Gould, John; Rycenga, Matthew; Best, Aaron
2007-04-26
Current methods for the automated generation of genome-scale metabolic networks focus on genome annotation and preliminary biochemical reaction network assembly, but do not adequately address the process of identifying and filling gaps in the reaction network, and verifying that the network is suitable for systems level analysis. Thus, current methods are only sufficient for generating draft-quality networks, and refinement of the reaction network is still largely a manual, labor-intensive process. We have developed a method for generating genome-scale metabolic networks that produces substantially complete reaction networks, suitable for systems level analysis. Our method partitions the reaction space of central and intermediary metabolism into discrete, interconnected components that can be assembled and verified in isolation from each other, and then integrated and verified at the level of their interconnectivity. We have developed a database of components that are common across organisms, and have created tools for automatically assembling appropriate components for a particular organism based on the metabolic pathways encoded in the organism's genome. This focuses manual efforts on that portion of an organism's metabolism that is not yet represented in the database. We have demonstrated the efficacy of our method by reverse-engineering and automatically regenerating the reaction network from a published genome-scale metabolic model for Staphylococcus aureus. Additionally, we have verified that our method capitalizes on the database of common reaction network components created for S. aureus, by using these components to generate substantially complete reconstructions of the reaction networks from three other published metabolic models (Escherichia coli, Helicobacter pylori, and Lactococcus lactis). We have implemented our tools and database within the SEED, an open-source software environment for comparative genome annotation and analysis. Our method sets the
Toward the automated generation of genome-scale metabolic networks in the SEED
Directory of Open Access Journals (Sweden)
Gould John
2007-04-01
Full Text Available Abstract Background Current methods for the automated generation of genome-scale metabolic networks focus on genome annotation and preliminary biochemical reaction network assembly, but do not adequately address the process of identifying and filling gaps in the reaction network, and verifying that the network is suitable for systems level analysis. Thus, current methods are only sufficient for generating draft-quality networks, and refinement of the reaction network is still largely a manual, labor-intensive process. Results We have developed a method for generating genome-scale metabolic networks that produces substantially complete reaction networks, suitable for systems level analysis. Our method partitions the reaction space of central and intermediary metabolism into discrete, interconnected components that can be assembled and verified in isolation from each other, and then integrated and verified at the level of their interconnectivity. We have developed a database of components that are common across organisms, and have created tools for automatically assembling appropriate components for a particular organism based on the metabolic pathways encoded in the organism's genome. This focuses manual efforts on that portion of an organism's metabolism that is not yet represented in the database. We have demonstrated the efficacy of our method by reverse-engineering and automatically regenerating the reaction network from a published genome-scale metabolic model for Staphylococcus aureus. Additionally, we have verified that our method capitalizes on the database of common reaction network components created for S. aureus, by using these components to generate substantially complete reconstructions of the reaction networks from three other published metabolic models (Escherichia coli, Helicobacter pylori, and Lactococcus lactis. We have implemented our tools and database within the SEED, an open-source software environment for comparative
Creating, generating and comparing random network models with NetworkRandomizer.
Tosadori, Gabriele; Bestvina, Ivan; Spoto, Fausto; Laudanna, Carlo; Scardoni, Giovanni
2016-01-01
Biological networks are becoming a fundamental tool for the investigation of high-throughput data in several fields of biology and biotechnology. With the increasing amount of information, network-based models are gaining more and more interest and new techniques are required in order to mine the information and to validate the results. To fill the validation gap we present an app, for the Cytoscape platform, which aims at creating randomised networks and randomising existing, real networks. Since there is a lack of tools that allow performing such operations, our app aims at enabling researchers to exploit different, well known random network models that could be used as a benchmark for validating real, biological datasets. We also propose a novel methodology for creating random weighted networks, i.e. the multiplication algorithm, starting from real, quantitative data. Finally, the app provides a statistical tool that compares real versus randomly computed attributes, in order to validate the numerical findings. In summary, our app aims at creating a standardised methodology for the validation of the results in the context of the Cytoscape platform.
Asymmetric multi-fractality in the U.S. stock indices using index-based model of A-MFDFA
International Nuclear Information System (INIS)
Lee, Minhyuk; Song, Jae Wook; Park, Ji Hwan; Chang, Woojin
2017-01-01
Highlights: • ‘Index-based A-MFDFA’ model is proposed to assess the asymmetric multi-fractality. • The asymmetric multi-fractality in the U.S. stock indices are investigated using ‘Index-based’ and ‘Return-based’ A-MFDFA. • The asymmetric feature is more significantly identified by ‘Index-based’ model than ‘return-based’ model. • Source of multi-fractality and time-varying features are analyzed. - Abstract: We detect the asymmetric multi-fractality in the U.S. stock indices based on the asymmetric multi-fractal detrended fluctuation analysis (A-MFDFA). Instead using the conventional return-based approach, we propose the index-based model of A-MFDFA where the trend based on the evolution of stock index rather than stock price return plays a role for evaluating the asymmetric scaling behaviors. The results show that the multi-fractal behaviors of the U.S. stock indices are asymmetric and the index-based model detects the asymmetric multi-fractality better than return-based model. We also discuss the source of multi-fractality and its asymmetry and observe that the multi-fractal asymmetry in the U.S. stock indices has a time-varying feature where the degree of multi-fractality and asymmetry increase during the financial crisis.
Entropy and Multifractality in Relativistic Ion-Ion Collisions
Directory of Open Access Journals (Sweden)
Shaista Khan
2018-01-01
Full Text Available Entropy production in multiparticle systems is investigated by analyzing the experimental data on ion-ion collisions at AGS and SPS energies and comparing the findings with those reported earlier for hadron-hadron, hadron-nucleus, and nucleus-nucleus collisions. It is observed that the entropy produced in limited and full phase space, when normalized to maximum rapidity, exhibits a kind of scaling which is nicely supported by Monte Carlo model HIJING. Using Rényi’s order q information entropy, multifractal characteristics of particle production are examined in terms of generalized dimensions, Dq. Nearly the same values of multifractal specific heat, c, observed in hadronic and ion-ion collisions over a wide range of incident energies suggest that the quantity c might be used as a universal characteristic of multiparticle production in hadron-hadron, hadron-nucleus, and nucleus-nucleus collisions. The analysis is extended to the study of spectrum of scaling indices. The findings reveal that Rényi’s order q information entropy could be another way to investigate the fluctuations in multiplicity distributions in terms of spectral function f(α, which has been argued to be a convenient function for comparison sake not only among different experiments but also between the data and theoretical models.
Log-Normality and Multifractal Analysis of Flame Surface Statistics
Saha, Abhishek; Chaudhuri, Swetaprovo; Law, Chung K.
2013-11-01
The turbulent flame surface is typically highly wrinkled and folded at a multitude of scales controlled by various flame properties. It is useful if the information contained in this complex geometry can be projected onto a simpler regular geometry for the use of spectral, wavelet or multifractal analyses. Here we investigate local flame surface statistics of turbulent flame expanding under constant pressure. First the statistics of local length ratio is experimentally obtained from high-speed Mie scattering images. For spherically expanding flame, length ratio on the measurement plane, at predefined equiangular sectors is defined as the ratio of the actual flame length to the length of a circular-arc of radius equal to the average radius of the flame. Assuming isotropic distribution of such flame segments we convolute suitable forms of the length-ratio probability distribution functions (pdfs) to arrive at corresponding area-ratio pdfs. Both the pdfs are found to be near log-normally distributed and shows self-similar behavior with increasing radius. Near log-normality and rather intermittent behavior of the flame-length ratio suggests similarity with dissipation rate quantities which stimulates multifractal analysis. Currently at Indian Institute of Science, India.
Multifractality and value-at-risk forecasting of exchange rates
Batten, Jonathan A.; Kinateder, Harald; Wagner, Niklas
2014-05-01
This paper addresses market risk prediction for high frequency foreign exchange rates under nonlinear risk scaling behaviour. We use a modified version of the multifractal model of asset returns (MMAR) where trading time is represented by the series of volume ticks. Our dataset consists of 138,418 5-min round-the-clock observations of EUR/USD spot quotes and trading ticks during the period January 5, 2006 to December 31, 2007. Considering fat-tails, long-range dependence as well as scale inconsistency with the MMAR, we derive out-of-sample value-at-risk (VaR) forecasts and compare our approach to historical simulation as well as a benchmark GARCH(1,1) location-scale VaR model. Our findings underline that the multifractal properties in EUR/USD returns in fact have notable risk management implications. The MMAR approach is a parsimonious model which produces admissible VaR forecasts at the 12-h forecast horizon. For the daily horizon, the MMAR outperforms both alternatives based on conditional as well as unconditional coverage statistics.
Cosmic microwave background and inflation in multi-fractional spacetimes
Energy Technology Data Exchange (ETDEWEB)
Calcagni, Gianluca [Instituto de Estructura de la Materia,CSIC, Serrano 121, 28006 Madrid (Spain); Kuroyanagi, Sachiko [Department of Physics, Nagoya University,Chikusa, Nagoya 464-8602 (Japan); Institute for Advanced Research, Nagoya University,Chikusa, Nagoya 464-8602 (Japan); Tsujikawa, Shinji [Department of Physics, Faculty of Science, Tokyo University of Science,1-3, Kagurazaka, Shinjuku-ku, Tokyo 162-8601 (Japan)
2016-08-18
We use FIRAS and Planck 2015 data to place observational bounds on inflationary scenarios in multi-fractional spacetimes with q-derivatives. While a power-law expansion in the geometric time coordinate is subject to the usual constraints from the tensor-to-scalar ratio, model-independent best fits of the black-body and scalar spectra yield upper limits on the free parameters of the multi-fractal measure of the theory. When the measure describing the fractal spacetime geometry is non-oscillating, information on the CMB black-body spectrum places constraints on the theory independent from but weaker than those obtained from the Standard Model, astrophysical gravitational waves and gamma-ray bursts (GRBs). When log oscillations are included and the measure describes a discrete fractal spacetime at microscopic scales, we obtain the first observational constraints on the amplitudes of such oscillations and find, in general, strong constraints on the multi-scale geometry and on the dimension of space. These results complete the scan and reduction of the parameter space of the theory. Black-body bounds are obtained also for the theory with weighted derivatives.
ABC of multi-fractal spacetimes and fractional sea turtles
Energy Technology Data Exchange (ETDEWEB)
Calcagni, Gianluca [Instituto de Estructura de la Materia, CSIC, Madrid (Spain)
2016-04-15
We clarify what it means to have a spacetime fractal geometry in quantum gravity and show that its properties differ from those of usual fractals. A weak and a strong definition of multi-scale and multi-fractal spacetimes are given together with a sketch of the landscape of multi-scale theories of gravitation. Then, in the context of the fractional theory with q-derivatives, we explore the consequences of living in a multi-fractal spacetime. To illustrate the behavior of a non-relativistic body, we take the entertaining example of a sea turtle. We show that, when only the time direction is fractal, sea turtles swim at a faster speed than in an ordinary world, while they swim at a slower speed if only the spatial directions are fractal. The latter type of geometry is the one most commonly found in quantum gravity. For time-like fractals, relativistic objects can exceed the speed of light, but strongly so only if their size is smaller than the range of particle-physics interactions. We also find new results about log-oscillating measures, the measure presentation and their role in physical observations and in future extensions to nowhere-differentiable stochastic spacetimes. (orig.)
ABC of multi-fractal spacetimes and fractional sea turtles
International Nuclear Information System (INIS)
Calcagni, Gianluca
2016-01-01
We clarify what it means to have a spacetime fractal geometry in quantum gravity and show that its properties differ from those of usual fractals. A weak and a strong definition of multi-scale and multi-fractal spacetimes are given together with a sketch of the landscape of multi-scale theories of gravitation. Then, in the context of the fractional theory with q-derivatives, we explore the consequences of living in a multi-fractal spacetime. To illustrate the behavior of a non-relativistic body, we take the entertaining example of a sea turtle. We show that, when only the time direction is fractal, sea turtles swim at a faster speed than in an ordinary world, while they swim at a slower speed if only the spatial directions are fractal. The latter type of geometry is the one most commonly found in quantum gravity. For time-like fractals, relativistic objects can exceed the speed of light, but strongly so only if their size is smaller than the range of particle-physics interactions. We also find new results about log-oscillating measures, the measure presentation and their role in physical observations and in future extensions to nowhere-differentiable stochastic spacetimes. (orig.)
Cosmic microwave background and inflation in multi-fractional spacetimes
International Nuclear Information System (INIS)
Calcagni, Gianluca; Kuroyanagi, Sachiko; Tsujikawa, Shinji
2016-01-01
We use FIRAS and Planck 2015 data to place observational bounds on inflationary scenarios in multi-fractional spacetimes with q-derivatives. While a power-law expansion in the geometric time coordinate is subject to the usual constraints from the tensor-to-scalar ratio, model-independent best fits of the black-body and scalar spectra yield upper limits on the free parameters of the multi-fractal measure of the theory. When the measure describing the fractal spacetime geometry is non-oscillating, information on the CMB black-body spectrum places constraints on the theory independent from but weaker than those obtained from the Standard Model, astrophysical gravitational waves and gamma-ray bursts (GRBs). When log oscillations are included and the measure describes a discrete fractal spacetime at microscopic scales, we obtain the first observational constraints on the amplitudes of such oscillations and find, in general, strong constraints on the multi-scale geometry and on the dimension of space. These results complete the scan and reduction of the parameter space of the theory. Black-body bounds are obtained also for the theory with weighted derivatives.
ABC of multi-fractal spacetimes and fractional sea turtles
Calcagni, Gianluca
2016-04-01
We clarify what it means to have a spacetime fractal geometry in quantum gravity and show that its properties differ from those of usual fractals. A weak and a strong definition of multi-scale and multi-fractal spacetimes are given together with a sketch of the landscape of multi-scale theories of gravitation. Then, in the context of the fractional theory with q-derivatives, we explore the consequences of living in a multi-fractal spacetime. To illustrate the behavior of a non-relativistic body, we take the entertaining example of a sea turtle. We show that, when only the time direction is fractal, sea turtles swim at a faster speed than in an ordinary world, while they swim at a slower speed if only the spatial directions are fractal. The latter type of geometry is the one most commonly found in quantum gravity. For time-like fractals, relativistic objects can exceed the speed of light, but strongly so only if their size is smaller than the range of particle-physics interactions. We also find new results about log-oscillating measures, the measure presentation and their role in physical observations and in future extensions to nowhere-differentiable stochastic spacetimes.
Physician directed networks: the new generation of managed care.
Bennett, T; O'Sullivan, D
1996-07-01
The external pressure to reduce cost while maintaining quality and services is moving the whole industry into a rapid mode of integration. Hospitals, vendors, MCOs, and now, physicians, are faced with the difficult decisions concerning how their operations will be integrated into the larger health care delivery system. These pressures have forced physicians to consolidate, build leverage, and create efficiencies to become more productive; thereby better positioning themselves to respond to the challenges and the opportunities that lie before them. This initial phase of consolidation has given many physicians the momentum to begin to wrestle back the control of health care and the courage to design the next generation of managed care: Physician Directed Managed Care. What will be the next phase? Perhaps, the next step will be fully-integrated specialty and multi-specialty groups leading to alternate delivery sites. "Everyone thinks of changing the world, but no one thinks of changing himself." - Leo Tolstoy
New-generation security network with synergistic IP sensors
Peshko, Igor
2007-09-01
Global Dynamic Monitoring and Security Network (GDMSN) for real-time monitoring of (1) environmental and atmospheric conditions: chemical, biological, radiological and nuclear hazards, climate/man-induced catastrophe areas and terrorism threats; (2) water, soil, food chain quantifiers, and public health care; (3) large government/public/ industrial/ military areas is proposed. Each GDMSN branch contains stationary or mobile terminals (ground, sea, air, or space manned/unmanned vehicles) equipped with portable sensors. The sensory data are transferred via telephone, Internet, TV, security camera and other wire/wireless or optical communication lines. Each sensor is a self-registering, self-reporting, plug-and-play, portable unit that uses unified electrical and/or optical connectors and operates with IP communication protocol. The variant of the system based just on optical technologies cannot be disabled by artificial high-power radio- or gamma-pulses or sunbursts. Each sensor, being supplied with a battery and monitoring means, can be used as a separate portable unit. Military personnel, police officers, firefighters, miners, rescue teams, and nuclear power plant personnel may individually use these sensors. Terminals may be supplied with sensors essential for that specific location. A miniature "universal" optical gas sensor for specific applications in life support and monitoring systems was designed and tested. The sensor is based on the physics of absorption and/or luminescence spectroscopy. It can operate at high pressures and elevated temperatures, such as in professional and military diving equipment, submarines, underground shelters, mines, command stations, aircraft, space shuttles, etc. To enable this capability, the multiple light emitters, detectors and data processing electronics are located within a specially protected chamber.
Lynch, Kevin; Hogan, John
2016-01-01
This study, using in-depth interviews and focus groups, examines perceptions of social networking sites as a means of communicating with Generation Z, from the perspectives of the major Irish political parties using these online resources and the perspective of their young target audience. There are two research questions: (1) How do political parties perceive social networking sites’ role in communicating with Generation Z? and (2) How do members of Generation Z perceive social networking si...
Synchronous ethernet and IEEE 1588 in telecoms next generation synchronization networks
2013-01-01
This book addresses the multiple technical aspects of the distribution of synchronization in new generation telecommunication networks, focusing in particular on synchronous Ethernet and IEEE1588 technologies. Many packet network engineers struggle with understanding the challenges that precise synchronization distribution can impose on networks. The usual “why”, “when” and particularly “how” can cause problems for many engineers. In parallel to this, some other markets have identical synchronization requirements, but with their own design requirements, generating further questions. This book attempts to respond to the different questions by providing background technical information. Invaluable information on state of-the-art packet network synchronization and timing architectures is provided, as well as an unbiased view on the synchronization technologies that have been internationally standardized over recent years, with the aim of providing the average reader (who is not skilled in the art) wi...
International Nuclear Information System (INIS)
Arantes Monteiro, Raul Vitor; Caixeta Guimarães, Geraldo; Rocio Castillo, Madeleine; Matheus Moura, Fabrício Augusto; Tamashiro, Márcio Augusto
2016-01-01
Current energy policies are encouraging the connection of power generation based on low-polluting technologies, mainly those using renewable sources, to distribution networks. Hence, it becomes increasingly important to understand technical challenges, facing high penetration of PV systems at the grid, especially considering the effects of intermittence of this source on the power quality, reliability and stability of the electric distribution system. This fact can affect the distribution networks on which they are attached causing overvoltage, undervoltage and frequency oscillations. In order to predict these disturbs, artificial neural networks are used. This article aims to analyze 3 training algorithms used in artificial neural networks for temporal prediction of the generated active power thru photovoltaic panels. As a result it was concluded that the algorithm with the best performance among the 3 analyzed was the Levenberg-Marquadrt.
Li, Yu; Rezgui, Yacine
2018-01-01
District heating (DH) is a promising energy pathway to alleviate environmental negative impacts induced by fossil fuels. Improving the performance of DH systems is one of the major challenges facing its wide adoption. This paper discusses the heat losses of the next generation DH based on the constructed Simulink model. Results show that lower distribution temperature and advanced insulation technology greatly reduce network heat losses. Also, the network heat loss can be further minimized by a reduction of heat demand in buildings.
Dixit, Abhishek; Lannoo, Bart; Colle, Didier; Pickavet, Mario; Demeester, Piet
2012-12-10
The optical network unit (ONU), installed at a customer's premises, accounts for about 60% of power in current fiber-to-the-home (FTTH) networks. We propose a power consumption model for the ONU and evaluate the ONU power consumption in various next generation optical access (NGOA) architectures. Further, we study the impact of the power savings of the ONU in various low power modes such as power shedding, doze and sleep.
Transfer of spatio-temporal multifractal properties of rainfall to simulated surface runoff
Gires, Auguste; Giangola-Murzyn, Agathe; Richard, Julien; Abbes, Jean-Baptiste; Tchiguirinskaia, Ioulia; Schertzer, Daniel; Willinger, Bernard; Cardinal, Hervé; Thouvenot, Thomas
2014-05-01
In this paper we suggest to use scaling laws and more specifically Universal Multifractals (UM) to analyse in a spatio-temporal framework both the radar rainfall and the simulated surface runoff. Such tools have been extensively used to analyse and simulate geophysical fields extremely variable over wide range of spatio-temporal scales such as rainfall, but have not often if ever been applied to surface runoff. Such novel combined analysis helps to improve the understanding of the rainfall-runoff relationship. Two catchments of the chair "Hydrology for resilient cities" sponsored by Véolia, and of the European Interreg IV RainGain project are used. They are both located in the Paris area: a 144 ha flat urban area in the Seine-Saint-Denis County, and a 250 ha urban area with a significant portion of forest located on a steep hillside of the Bièvre River. A fully distributed urban hydrological model currently under development called Multi-Hydro is implemented to represent the catchments response. It consists in an interacting core between open source software packages, each of them representing a portion of the water cycle in urban environment. The fully distributed model is tested with pixels of size 5, 10 and 20 m. In a first step the model is validated for three rainfall events that occurred in 2010 and 2011, for which the Météo-France radar mosaic with a resolution of 1 km in space and 5 min in time is available. These events generated significant surface runoff and some local flooding. The sensitivity of the model to the rainfall resolution is briefly checked by stochastically generating an ensemble of realistic downscaled rainfall fields (obtained by continuing the underlying cascade process which is observed on the available range of scales) and inputting them into the model. The impact is significant on both the simulated sewer flow and surface runoff. Then rainfall fields are generated with the help of discrete multifractal cascades and inputted in the
DEFF Research Database (Denmark)
Dheer, D.K.; Doolla, S.; Bandyopadhyay, S.
2017-01-01
, small signal stability margin is on the fore. The present research studied the effect of location of droop-controlled DGs on small signal stability margin and network loss on a modified IEEE 13 bus system, an IEEE 33-bus distribution system and a practical 22-bus radial distribution network. A complete...... loss and stability margin is further investigated by identifying the Pareto fronts for modified IEEE 13 bus, IEEE 33 and practical 22-bus radial distribution network with application of Reference point based Non-dominated Sorting Genetic Algorithm (R-NSGA). Results were validated by time domain......For a utility-connected system, issues related to small signal stability with Distributed Generators (DGs) are insignificant due to the presence of a very strong grid. Optimally placed sources in utility connected microgrid system may not be optimal/stable in islanded condition. Among others issues...
A Comparative Study of Multiplexing Schemes for Next Generation Optical Access Networks
Imtiaz, Waqas A.; Khan, Yousaf; Shah, Pir Mehar Ali; Zeeshan, M.
2014-09-01
Passive optical network (PON) is a high bandwidth, economical solution which can provide the necessary bandwidth to end-users. Wavelength division multiplexed passive optical networks (WDM PONs) and time division multiplexed passive optical networks (TDM PONs) are considered as an evolutionary step for next-generation optical access (NGOA) networks. However they fail to provide highest transmission capacity, efficient bandwidth access, and robust dispersion tolerance. Thus future PONs are considered on simpler, efficient and potentially scalable, optical code division multiplexed (OCDM) PONs. This paper compares the performance of existing PONs with OCDM PON to determine a suitable scheme for NGOA networks. Two system parameter are used in this paper: fiber length, and bit rate. Performance analysis using Optisystem shows that; for a sufficient system performance parameters i.e. bit error rate (BER) ≤ 10-9, and maximum quality factor (Q) ≥ 6, OCDMA PON efficiently performs upto 50 km with 10 Gbit/s per ONU.
Generation of artificial accelerograms using neural networks for data of Iran
International Nuclear Information System (INIS)
Bargi, Kh.; Loux, C.; Rohani, H.
2002-01-01
A new method for generation of artificial earthquake accelerograms from response spectra is proposed by Ghaboussi and Lin in 1997 using neural networks. In this paper the methodology has been extended and enhanced for data of Iran. For this purpose, first 40 records of Iran acceleration is chosen, then an RBF neural network which called generalized regression neural network learn the inverse mapping directly from the response spectrum to the Discrete Cosine Transform of accelerograms. Discrete Cosine Transform has been used as an assisting device to extract the content of frequency domain. Learning of network is reasonable and a generalized regression neural network learns it in a few second. Outputs are presented to demonstrate the performance of this method and show its capabilities
Khambhati, Ankit N.; Davis, Kathryn A.; Oommen, Brian S.; Chen, Stephanie H.; Lucas, Timothy H.; Litt, Brian; Bassett, Danielle S.
2015-01-01
The epileptic network is characterized by pathologic, seizure-generating ‘foci’ embedded in a web of structural and functional connections. Clinically, seizure foci are considered optimal targets for surgery. However, poor surgical outcome suggests a complex relationship between foci and the surrounding network that drives seizure dynamics. We developed a novel technique to objectively track seizure states from dynamic functional networks constructed from intracranial recordings. Each dynamical state captures unique patterns of network connections that indicate synchronized and desynchronized hubs of neural populations. Our approach suggests that seizures are generated when synchronous relationships near foci work in tandem with rapidly changing desynchronous relationships from the surrounding epileptic network. As seizures progress, topographical and geometrical changes in network connectivity strengthen and tighten synchronous connectivity near foci—a mechanism that may aid seizure termination. Collectively, our observations implicate distributed cortical structures in seizure generation, propagation and termination, and may have practical significance in determining which circuits to modulate with implantable devices. PMID:26680762
Yang, Liansheng; Zhu, Yingming; Wang, Yudong; Wang, Yiqi
2016-11-01
Based on the daily price data of spot prices of West Texas Intermediate (WTI) crude oil and ten CSI300 sector indices in China, we apply multifractal detrended cross-correlation analysis (MF-DCCA) method to investigate the cross-correlations between crude oil and Chinese sector stock markets. We find that the strength of multifractality between WTI crude oil and energy sector stock market is the highest, followed by the strength of multifractality between WTI crude oil and financial sector market, which reflects a close connection between energy and financial market. Then we do vector autoregression (VAR) analysis to capture the interdependencies among the multiple time series. By comparing the strength of multifractality for original data and residual errors of VAR model, we get a conclusion that vector auto-regression (VAR) model could not be used to describe the dynamics of the cross-correlations between WTI crude oil and the ten sector stock markets.
Multifractal aspects of the scaling laws in fully developed compressible turbulence
International Nuclear Information System (INIS)
Shivamoggi, B.K.
1995-01-01
In this paper, multifractal aspects of the scalings laws in fully developed compressible turbulence are considered. Compressibility effects on known results of incompressible turbulence are pointed out. copyright 1995 Academic Press, Inc
Disorder generated by interacting neural networks: application to econophysics and cryptography
International Nuclear Information System (INIS)
Kinzel, Wolfgang; Kanter, Ido
2003-01-01
When neural networks are trained on their own output signals they generate disordered time series. In particular, when two neural networks are trained on their mutual output they can synchronize; they relax to a time-dependent state with identical synaptic weights. Two applications of this phenomenon are discussed for (a) econophysics and (b) cryptography. (a) When agents competing in a closed market (minority game) are using neural networks to make their decisions, the total system relaxes to a state of good performance. (b) Two partners communicating over a public channel can find a common secret key
Network Dynamics: Modeling And Generation Of Very Large Heterogeneous Social Networks
2015-11-23
P11035 (2014). [19] P. L. Krapivsky and S. Redner, Phys. Rev. E. 71, 036118 (2005). [20] M. O. Jackson and B. W. Rogers, Amer. Econ . Rev. 97, 890...P06004 (2010). [24] M. E. J. Newman, Networks: An Introduction (Oxford Univ. Press, Oxford, 2010). [25] P. J. Flory, Principles of Polymer Chemistry
Schaffter, Thomas; Marbach, Daniel; Floreano, Dario
2011-08-15
Over the last decade, numerous methods have been developed for inference of regulatory networks from gene expression data. However, accurate and systematic evaluation of these methods is hampered by the difficulty of constructing adequate benchmarks and the lack of tools for a differentiated analysis of network predictions on such benchmarks. Here, we describe a novel and comprehensive method for in silico benchmark generation and performance profiling of network inference methods available to the community as an open-source software called GeneNetWeaver (GNW). In addition to the generation of detailed dynamical models of gene regulatory networks to be used as benchmarks, GNW provides a network motif analysis that reveals systematic prediction errors, thereby indicating potential ways of improving inference methods. The accuracy of network inference methods is evaluated using standard metrics such as precision-recall and receiver operating characteristic curves. We show how GNW can be used to assess the performance and identify the strengths and weaknesses of six inference methods. Furthermore, we used GNW to provide the international Dialogue for Reverse Engineering Assessments and Methods (DREAM) competition with three network inference challenges (DREAM3, DREAM4 and DREAM5). GNW is available at http://gnw.sourceforge.net along with its Java source code, user manual and supporting data. Supplementary data are available at Bioinformatics online. dario.floreano@epfl.ch.
Hafner, K.; Davis, P.; Wilson, D.; Sumy, D.
2017-12-01
The Global Seismographic Network (GSN) recently received delivery of the next generation Very Broadband (VBB) borehole sensors purchased through funding from the DOE. Deployment of these sensors will be underway during the end of summer and fall of 2017 and they will eventually replace the aging KS54000 sensors at approximately one-third of the GSN network stations. We will present the latest methods of deploying these sensors in the existing deep boreholes. To achieve lower noise performance at some sites, emplacement in shallow boreholes might result in lower noise performance for the existing site conditions. In some cases shallow borehole installations may be adapted to vault stations (which make up two thirds of the network), as a means of reducing tilt-induced signals on the horizontal components. The GSN is creating a prioritized list of equipment upgrades at selected stations with the ultimate goal of optimizing overall network data availability and noise performance. For an overview of the performance of the current GSN relative to selected set of metrics, we are utilizing data quality metrics and Probability Density Functions (PDFs)) generated by the IRIS Data Management Centers' (DMC) MUSTANG (Modular Utility for Statistical Knowledge Gathering) and LASSO (Latest Assessment of Seismic Station Observations) tools. We will present our metric analysis of GSN performance in 2016, and show the improvements at GSN sites resulting from recent instrumentation and infrastructure upgrades.
Modeling the video distribution link in the Next Generation Optical Access Networks
DEFF Research Database (Denmark)
Amaya, F.; Cárdenas, A.; Tafur Monroy, Idelfonso
2011-01-01
In this work we present a model for the design and optimization of the video distribution link in the next generation optical access network. We analyze the video distribution performance in a SCM-WDM link, including the noise, the distortion and the fiber optic nonlinearities. Additionally, we...... consider in the model the effect of distributed Raman amplification, used to extent the capacity and the reach of the optical link. In the model, we use the nonlinear Schrödinger equation with the purpose to obtain capacity limitations and design constrains of the next generation optical access networks....
Modeling the video distribution link in the Next Generation Optical Access Networks
International Nuclear Information System (INIS)
Amaya, F; Cardenas, A; Tafur, I
2011-01-01
In this work we present a model for the design and optimization of the video distribution link in the next generation optical access network. We analyze the video distribution performance in a SCM-WDM link, including the noise, the distortion and the fiber optic nonlinearities. Additionally, we consider in the model the effect of distributed Raman amplification, used to extent the capacity and the reach of the optical link. In the model, we use the nonlinear Schroedinger equation with the purpose to obtain capacity limitations and design constrains of the next generation optical access networks.
International Nuclear Information System (INIS)
Abdullah, M.A.; Agalgaonkar, A.P.; Muttaqi, K.M.
2014-01-01
Highlights: • Difficulties in assessing distribution network adequacy with DG are addressed. • Indices are proposed to assess adequacy of energy supply and service continuity. • Analytical methodology is developed to assess the proposed indices. • Concept of joint probability distribution of demand and generation is applied. - Abstract: Continuity of electricity supply with renewable distributed generation (DG) is a topical issue for distribution system planning and operation, especially due to the stochastic nature of power generation and time varying load demand. The conventional adequacy and reliability analysis methods related to bulk generation systems cannot be applied directly for the evaluation of adequacy criteria such as ‘energy supply’ and ‘continuity of service’ for distribution networks embedded with renewable DG. In this paper, new indices highlighting ‘available supply capacity’ and ‘continuity of service’ are proposed for ‘energy supply’ and ‘continuation of service’ evaluation of generation-rich distribution networks, and analytical techniques are developed for their quantification. A probability based analytical method has been developed using the joint probability of the demand and generation, and probability distributions of the proposed indices have been used to evaluate the network adequacy in energy supply and service continuation. A data clustering technique has been used to evaluate the joint probability between coincidental demand and renewable generation. Time sequential Monte Carlo simulation has been used to compare the results obtained using the proposed analytical method. A standard distribution network derived from Roy Billinton test system and a practical radial distribution network have been used to test the proposed method and demonstrate the estimation of the well-being of a system for hosting renewable DG units. It is found that renewable DG systems improve the ‘energy supply’ and
Dutta, Srimonti; Ghosh, Dipak; Chatterjee, Sucharita
2016-12-01
The manuscript studies autocorrelation and cross correlation of SENSEX fluctuations and Forex Exchange Rate in respect to Indian scenario. Multifractal detrended fluctuation analysis (MFDFA) and multifractal detrended cross correlation analysis (MFDXA) were employed to study the correlation between the two series. It was observed that the two series are strongly cross correlated. The change of degree of cross correlation with time was studied and the results are interpreted qualitatively.
International Nuclear Information System (INIS)
Kai Wu; Nagurney, A.; University of Massachusetts, Amherst, MA; Zugang Liu; Stranlund, J.K.
2006-01-01
Global climate change and fuel security risks have encouraged international and regional adoption of pollution/carbon taxes. A major portion of such policy interventions is directed at the electric power industry with taxes applied according to the type of fuel used by the power generators in their power plants. This paper proposes an electric power supply chain network model that captures the behavior of power generators faced with a portfolio of power plant options and subject to pollution taxes. We demonstrate that this general model can be reformulated as a transportation network equilibrium model with elastic demands and qualitatively analyzed and solved as such. The connections between these two different modeling schemas is done through finite-dimensional variational inequality theory. The numerical examples illustrate how changes in the pollution/carbon taxes affect the equilibrium electric power supply chain network production outputs, the transactions between the various decision-makers the demand market prices, as well as the total amount of carbon emissions generated. (author)
Technical guide to the connection of generation to the distribution network
Energy Technology Data Exchange (ETDEWEB)
Jarrett, K.; Hedgecock, J.; Gregory, R.; Warham, T.
2003-07-01
This guide provides a 'route map' of the processes of getting a generation scheme connected to the network and is intended to help developers of any form of distributed generation connected to the UK's local electricity networks, eg: renewable energy schemes; waste-to-energy schemes; on-site generation and combined heat and power (CHP) schemes; and peak lopping schemes using back-up generators. Where necessary, the guide distinguishes between arrangements that apply in Scotland and those that apply in England and Wales. The guide aims to: provide background information about the electricity industry; highlight common technical issues that arise during connection negotiation and their implications for distribution network operators (DNOs) and developers; examine the main factors affecting connection costs and timescales for achieving connections; and identify the different types of contracts relating to connection. The report considers the connection process, the connection application process and timescales, costs and charges, competition in connection, the structure of the UK electricity industry, the statutory framework, the effects of distributed generation of the distribution system, earthing and protection design, safety issues and DNO network information. It includes a glossary, checklists, useful contact details and information about standards and other useful documents.
Assessment of 48 Stock markets using adaptive multifractal approach
Ferreira, Paulo; Dionísio, Andreia; Movahed, S. M. S.
2017-11-01
In this paper, Stock market comovements are examined using cointegration, Granger causality tests and nonlinear approaches in context of mutual information and correlations. Since underlying data sets are affected by non-stationarities and trends, we also apply Adaptive Multifractal Detrended Fluctuation Analysis (AMF-DFA) and Adaptive Multifractal Detrended Cross-Correlation Analysis (AMF-DXA). We find only 170 pair of Stock markets cointegrated, and according to the Granger causality and mutual information, we realize that the strongest relations lies between emerging markets, and between emerging and frontier markets. According to scaling exponent given by AMF-DFA, h(q = 2) > 1, we find that all underlying data sets belong to non-stationary process. According to Efficient Market Hypothesis (EMH), only 8 markets are classified in uncorrelated processes at 2 σ confidence interval. 6 Stock markets belong to anti-correlated class and dominant part of markets has memory in corresponding daily index prices during January 1995 to February 2014. New-Zealand with H = 0 . 457 ± 0 . 004 and Jordan with H = 0 . 602 ± 0 . 006 are far from EMH. The nature of cross-correlation exponents based on AMF-DXA is almost multifractal for all pair of Stock markets. The empirical relation, Hxy ≤ [Hxx +Hyy ] / 2, is confirmed. Mentioned relation for q > 0 is also satisfied while for q behavior of markets for small fluctuations is affected by contribution of major pair. For larger fluctuations, the cross-correlation contains information from both local (internal) and global (external) conditions. Width of singularity spectrum for auto-correlation and cross-correlation are Δαxx ∈ [ 0 . 304 , 0 . 905 ] and Δαxy ∈ [ 0 . 246 , 1 . 178 ] , respectively. The wide range of singularity spectrum for cross-correlation confirms that the bilateral relation between Stock markets is more complex. The value of σDCCA indicates that all pairs of stock market studied in this time interval
The weather and Climate: emergent laws and multifractal cascades
Lovejoy, S.
2016-12-01
In the atmosphere, nonlinear terms are typically about a trillion times larger than linear ones; we anticipate the emergence of high level turbulence laws. The classical turbulence laws were restricted to homogeneous and isotropic systems; to apply them to the atmosphere they must be generalized to account for strong anisotropy (especially stratification) and variability (intermittency). Over the last 30 years, using scaling symmetry principles and multifractal cascades, this has been done. While hitherto they were believed applicable only up to ≈ 100 m, (generalized) turbulence laws now anisotropic and multifractal, they cover spatial scales up planetary in extent and in time well beyond weather scales to include the climate. These higher level laws are stochastic in nature and provide the theoretical basis both for stochastic parametrizations as well as stochastic forecasting. In the time domain the emergent laws for fluctuations DT (for example in temperature T) have means T > ≈ DtH i.e. they are scaling (power laws) in the time interval Dt. We find find exponents H>0 (fluctuations increase with scale) up to ≈ Dt ≈10 days (the lifetime of planetary scale structures, the analogous transition in the ocean is at Dt ≈ 1 year on Mars it is Dt ≈ 2 sols). At larger Dt, there is a transition to a new "macroweather" regime with H≈30 years (anthropocene; larger in the pre-industrial epoch), new climate processes begin to dominate, leading to H>0. "The climate is what you expect, the weather is what you get": the climate is thought to be a kind of "average weather". However this "expected" behavior is macroweather, not the climate. On the contrary, the climate is the new even lower frequency regime at scales Dt> 30 yrs and it has statistical properties very similar to the weather. At these scales, "macroweather is what you expect, the climate is what you get". The scaling in the macroweather regime implies that there is a long-term memory. We show how the
Linearization effect in multifractal analysis: Insights from the Random Energy Model
Angeletti, Florian; Mézard, Marc; Bertin, Eric; Abry, Patrice
2011-08-01
The analysis of the linearization effect in multifractal analysis, and hence of the estimation of moments for multifractal processes, is revisited borrowing concepts from the statistical physics of disordered systems, notably from the analysis of the so-called Random Energy Model. Considering a standard multifractal process (compound Poisson motion), chosen as a simple representative example, we show the following: (i) the existence of a critical order q∗ beyond which moments, though finite, cannot be estimated through empirical averages, irrespective of the sample size of the observation; (ii) multifractal exponents necessarily behave linearly in q, for q>q∗. Tailoring the analysis conducted for the Random Energy Model to that of Compound Poisson motion, we provide explicative and quantitative predictions for the values of q∗ and for the slope controlling the linear behavior of the multifractal exponents. These quantities are shown to be related only to the definition of the multifractal process and not to depend on the sample size of the observation. Monte Carlo simulations, conducted over a large number of large sample size realizations of compound Poisson motion, comfort and extend these analyses.
M. L. Kavvas; T. Tu; A. Ercan; J. Polsinelli
2017-01-01
Using fractional calculus, a dimensionally consistent governing equation of transient, saturated groundwater flow in fractional time in a multi-fractional confined aquifer is developed. First, a dimensionally consistent continuity equation for transient saturated groundwater flow in fractional time and in a multi-fractional, multidimensional confined aquifer is developed. For the equation of water flux within a multi-fractional multidimensional confined aquifer, a dimensionally...
Lewis Research Center studies of multiple large wind turbine generators on a utility network
Gilbert, L. J.; Triezenberg, D. M.
1979-01-01
A NASA-Lewis program to study the anticipated performance of a wind turbine generator farm on an electric utility network is surveyed. The paper describes the approach of the Lewis Wind Energy Project Office to developing analysis capabilities in the area of wind turbine generator-utility network computer simulations. Attention is given to areas such as, the Lewis Purdue hybrid simulation, an independent stability study, DOE multiunit plant study, and the WEST simulator. Also covered are the Lewis mod-2 simulation including analog simulation of a two wind turbine system and comparison with Boeing simulation results, and gust response of a two machine model. Finally future work to be done is noted and it is concluded that the study shows little interaction between the generators and between the generators and the bus.
Directory of Open Access Journals (Sweden)
Anirban eBhaduri
2016-02-01
Full Text Available Abstract: Abstract: The cardiac dynamics during meditation is explored quantitatively with two chaos-based non-linear techniques viz. multi-fractal detrended fluctuation analysis and visibility network analysis techniques. The data used are the instantaneous heart rate (in beats/minute of subjects performing Kundalini Yoga and Chi meditation from PhysioNet. The results show consistent differences between the quantitative parameters obtained by both the analysis techniques. This indicates an interesting phenomenon of change in the complexity of the cardiac dynamics during meditation supported with quantitative parameters.The results also produce a preliminary evidence that these techniques can be used as a measure of physiological impact on subjects performing meditation.
Game-theoretic modeling of curtailment rules and network investments with distributed generation
International Nuclear Information System (INIS)
Andoni, Merlinda; Robu, Valentin; Früh, Wolf-Gerrit; Flynn, David
2017-01-01
Highlights: •Comparative study on curtailment rules and their effects on RES profitability. •Proposal of novel fair curtailment rule which minimises generators’ disruption. •Modeling of private network upgrade as leader-follower (Stackelberg) game. •New model incorporating stochastic generation and variable demand. •New methodology for setting transmission charges in private network upgrade. -- Abstract: Renewable energy has achieved high penetration rates in many areas, leading to curtailment, especially if existing network infrastructure is insufficient and energy generated cannot be exported. In this context, Distribution Network Operators (DNOs) face a significant knowledge gap about how to implement curtailment rules that achieve desired operational objectives, but at the same time minimise disruption and economic losses for renewable generators. In this work, we study the properties of several curtailment rules widely used in UK renewable energy projects, and their effect on the viability of renewable generation investment. Moreover, we propose a new curtailment rule which guarantees fair allocation of curtailment amongst all generators with minimal disruption. Another key knowledge gap faced by DNOs is how to incentivise private network upgrades, especially in settings where several generators can use the same line against the payment of a transmission fee. In this work, we provide a solution to this problem by using tools from algorithmic game theory. Specifically, this setting can be modelled as a Stackelberg game between the private transmission line investor and local renewable generators, who are required to pay a transmission fee to access the line. We provide a method for computing the equilibrium of this game, using a model that captures the stochastic nature of renewable energy generation and demand. Finally, we use the practical setting of a grid reinforcement project from the UK and a large dataset of wind speed measurements and demand
Directory of Open Access Journals (Sweden)
Simone Benella
2017-07-01
Full Text Available Many out-of-equilibrium systems respond to external driving with nonlinear and self-similar dynamics. This near scale-invariant behavior of relaxation events has been modeled through sand pile cellular automata. However, a common feature of these models is the assumption of a local connectivity, while in many real systems, we have evidence for longer range connectivity and a complex topology of the interacting structures. Here, we investigate the role that longer range connectivity might play in near scale-invariant systems, by analyzing the results of a sand pile cellular automaton model on a Newman–Watts network. The analysis clearly indicates the occurrence of a crossover phenomenon in the statistics of the relaxation events as a function of the percentage of longer range links and the breaking of the simple Finite Size Scaling (FSS. The more complex nature of the dynamics in the presence of long-range connectivity is investigated in terms of multi-scaling features and analyzed by the Rank-Ordered Multifractal Analysis (ROMA.
Multifractal-based nuclei segmentation in fish images.
Reljin, Nikola; Slavkovic-Ilic, Marijeta; Tapia, Coya; Cihoric, Nikola; Stankovic, Srdjan
2017-09-01
The method for nuclei segmentation in fluorescence in-situ hybridization (FISH) images, based on the inverse multifractal analysis (IMFA) is proposed. From the blue channel of the FISH image in RGB format, the matrix of Holder exponents, with one-by-one correspondence with the image pixels, is determined first. The following semi-automatic procedure is proposed: initial nuclei segmentation is performed automatically from the matrix of Holder exponents by applying predefined hard thresholding; then the user evaluates the result and is able to refine the segmentation by changing the threshold, if necessary. After successful nuclei segmentation, the HER2 (human epidermal growth factor receptor 2) scoring can be determined in usual way: by counting red and green dots within segmented nuclei, and finding their ratio. The IMFA segmentation method is tested over 100 clinical cases, evaluated by skilled pathologist. Testing results show that the new method has advantages compared to already reported methods.
Directory of Open Access Journals (Sweden)
Christian Nowke
2018-06-01
Full Text Available Simulation models in many scientific fields can have non-unique solutions or unique solutions which can be difficult to find. Moreover, in evolving systems, unique final state solutions can be reached by multiple different trajectories. Neuroscience is no exception. Often, neural network models are subject to parameter fitting to obtain desirable output comparable to experimental data. Parameter fitting without sufficient constraints and a systematic exploration of the possible solution space can lead to conclusions valid only around local minima or around non-minima. To address this issue, we have developed an interactive tool for visualizing and steering parameters in neural network simulation models. In this work, we focus particularly on connectivity generation, since finding suitable connectivity configurations for neural network models constitutes a complex parameter search scenario. The development of the tool has been guided by several use cases—the tool allows researchers to steer the parameters of the connectivity generation during the simulation, thus quickly growing networks composed of multiple populations with a targeted mean activity. The flexibility of the software allows scientists to explore other connectivity and neuron variables apart from the ones presented as use cases. With this tool, we enable an interactive exploration of parameter spaces and a better understanding of neural network models and grapple with the crucial problem of non-unique network solutions and trajectories. In addition, we observe a reduction in turn around times for the assessment of these models, due to interactive visualization while the simulation is computed.
Probing Rubber Cross-Linking Generation of Industrial Polymer Networks at Nanometer Scale.
Gabrielle, Brice; Gomez, Emmanuel; Korb, Jean-Pierre
2016-06-23
We present improved analyses of rheometric torque measurements as well as (1)H double-quantum (DQ) nuclear magnetic resonance (NMR) buildup data on polymer networks of industrial compounds. This latter DQ NMR analysis allows finding the distribution of an orientation order parameter (Dres) resulting from the noncomplete averaging of proton dipole-dipole couplings within the cross-linked polymer chains. We investigate the influence of the formulation (filler and vulcanization systems) as well as the process (curing temperature) ending to the final polymer network. We show that DQ NMR follows the generation of the polymer network during the vulcanization process from a heterogeneous network to a very homogeneous one. The time variations of microscopic Dres and macroscopic rheometric torques present power-law behaviors above a threshold time scale with characteristic exponents of the percolation theory. We observe also a very good linear correlation between the kinetics of Dres and rheometric data routinely performed in industry. All these observations confirm the description of the polymer network generation as a critical phenomenon. On the basis of all these results, we believe that DQ NMR could become a valuable tool for investigating in situ the cross-linking of industrial polymer networks at the nanometer scale.
Sloep, Peter
2009-01-01
Sloep, P. B. (2009). Innovation as a distributed, collaborative process of knowledge generation: open, networked innovation. In V. Hornung-Prähauser & M. Luckmann (Eds.), Kreativität und Innovationskompetenz im digitalen Netz - Creativity and Innovation Competencies in the Web, Sammlung von
Distributed generation in the Dutch LV network - self-supporting residential area
Mes, M.; Vanalme, G.M.A.; Myrzik, J.M.A.; Bongaerts, M.; Verbong, G.P.J.; Kling, W.L.
2008-01-01
A self-supporting residential area is seen as an alternative operational approach of power supply in low voltage (LV) networks. The intention of the new approach is to exploit the advantages of distributed generation (DG) and avoid the difficulties, that come with DG when implemented in the
GalaxyGAN: Generative Adversarial Networks for recovery of galaxy features
Schawinski, Kevin; Zhang, Ce; Zhang, Hantian; Fowler, Lucas; Krishnan Santhanam, Gokula
2017-02-01
GalaxyGAN uses Generative Adversarial Networks to reliably recover features in images of galaxies. The package uses machine learning to train on higher quality data and learns to recover detailed features such as galaxy morphology by effectively building priors. This method opens up the possibility of recovering more information from existing and future imaging data.
On the Potential of PUF for Pseudonym Generation in Vehicular Networks
Petit, Jonathan; Bösch, C.T.; Feiri, Michael; Kargl, Frank
2012-01-01
Most proposals for security of vehicular networks foresee the generation of a comparatively large number of changing pseudonyms to prevent vehicles from being identified or tracked. Most proposals rely on communication with backend pseudonym providers to refill a vehicle’s pseudonym pool which
Challenges to the Learning Organization in the Context of Generational Diversity and Social Networks
Kaminska, Renata; Borzillo, Stefano
2018-01-01
Purpose: The purpose of this paper is to gain a better understanding of the challenges to the emergence of a learning organization (LO) posed by a context of generational diversity and an enterprise social networking system (ESNS). Design/methodology/approach: This study uses a qualitative methodology based on an analysis of 20 semi-structured…
Definition of Distribution Network Tariffs Considering Distribution Generation and Demand Response
DEFF Research Database (Denmark)
Soares, Tiago; Faria, Pedro; Vale, Zita
2014-01-01
The use of distribution networks in the current scenario of high penetration of Distributed Generation (DG) is a problem of great importance. In the competitive environment of electricity markets and smart grids, Demand Response (DR) is also gaining notable impact with several benefits for the wh......The use of distribution networks in the current scenario of high penetration of Distributed Generation (DG) is a problem of great importance. In the competitive environment of electricity markets and smart grids, Demand Response (DR) is also gaining notable impact with several benefits...... the determination of topological distribution factors, and consequent application of the MW-mile method. The application of the proposed tariffs definition methodology is illustrated in a distribution network with 33 buses, 66 DG units, and 32 consumers with DR capacity...
Li, Jinze; Qu, Zhi; He, Xiaoyang; Jin, Xiaoming; Li, Tie; Wang, Mingkai; Han, Qiu; Gao, Ziji; Jiang, Feng
2018-02-01
Large-scale access of distributed power can improve the current environmental pressure, at the same time, increasing the complexity and uncertainty of overall distribution system. Rational planning of distributed power can effectively improve the system voltage level. To this point, the specific impact on distribution network power quality caused by the access of typical distributed power was analyzed and from the point of improving the learning factor and the inertia weight, an improved particle swarm optimization algorithm (IPSO) was proposed which could solve distributed generation planning for distribution network to improve the local and global search performance of the algorithm. Results show that the proposed method can well reduce the system network loss and improve the economic performance of system operation with distributed generation.
Berlow, Noah; Pal, Ranadip
2011-01-01
Genetic Regulatory Networks (GRNs) are frequently modeled as Markov Chains providing the transition probabilities of moving from one state of the network to another. The inverse problem of inference of the Markov Chain from noisy and limited experimental data is an ill posed problem and often generates multiple model possibilities instead of a unique one. In this article, we address the issue of intervention in a genetic regulatory network represented by a family of Markov Chains. The purpose of intervention is to alter the steady state probability distribution of the GRN as the steady states are considered to be representative of the phenotypes. We consider robust stationary control policies with best expected behavior. The extreme computational complexity involved in search of robust stationary control policies is mitigated by using a sequential approach to control policy generation and utilizing computationally efficient techniques for updating the stationary probability distribution of a Markov chain following a rank one perturbation.
NASCENT: an automatic protein interaction network generation tool for non-model organisms.
Banky, Daniel; Ordog, Rafael; Grolmusz, Vince
2009-04-24
Large quantity of reliable protein interaction data are available for model organisms in public depositories (e.g., MINT, DIP, HPRD, INTERACT). Most data correspond to experiments with the proteins of Saccharomyces cerevisiae, Drosophila melanogaster, Homo sapiens, Caenorhabditis elegans, Escherichia coli and Mus musculus. For other important organisms the data availability is poor or non-existent. Here we present NASCENT, a completely automatic web-based tool and also a downloadable Java program, capable of modeling and generating protein interaction networks even for non-model organisms. The tool performs protein interaction network modeling through gene-name mapping, and outputs the resulting network in graphical form and also in computer-readable graph-forms, directly applicable by popular network modeling software. http://nascent.pitgroup.org.
A generative modeling approach to connectivity-Electrical conduction in vascular networks
DEFF Research Database (Denmark)
Hald, Bjørn Olav
2016-01-01
The physiology of biological structures is inherently dynamic and emerges from the interaction and assembly of large collections of small entities. The extent of coupled entities complicates modeling and increases computational load. Here, microvascular networks are used to present a novel...... to synchronize vessel tone across the vast distances within a network. We hypothesize that electrical conduction capacity is delimited by the size of vascular structures and connectivity of the network. Generation and simulation of series of dynamical models of electrical spread within vascular networks...... of different size and composition showed that (1) Conduction is enhanced in models harboring long and thin endothelial cells that couple preferentially along the longitudinal axis. (2) Conduction across a branch point depends on endothelial connectivity between branches. (3) Low connectivity sub...
Comprehensive evaluation of impacts of distributed generation integration in distribution network
Peng, Sujiang; Zhou, Erbiao; Ji, Fengkun; Cao, Xinhui; Liu, Lingshuang; Liu, Zifa; Wang, Xuyang; Cai, Xiaoyu
2018-04-01
All Distributed generation (DG) as the supplement to renewable energy centralized utilization, is becoming the focus of development direction of renewable energy utilization. With the increasing proportion of DG in distribution network, the network power structure, power flow distribution, operation plans and protection are affected to some extent. According to the main impacts of DG, a comprehensive evaluation model of distributed network with DG is proposed in this paper. A comprehensive evaluation index system including 7 aspects, along with their corresponding index calculation method is established for quantitative analysis. The indices under different access capacity of DG in distribution network are calculated based on the IEEE RBTS-Bus 6 system and the evaluation result is calculated by analytic hierarchy process (AHP). The proposed model and method are verified effective and validity through case study.
A Network Traffic Generator Model for Fast Network-on-Chip Simulation
DEFF Research Database (Denmark)
Mahadevan, Shankar; Angiolini, Frederico; Storgaard, Michael
2005-01-01
For Systems-on-Chip (SoCs) development, a predominant part of the design time is the simulation time. Performance evaluation and design space exploration of such systems in bit- and cycle-true fashion is becoming prohibitive. We propose a traffic generation (TG) model that provides a fast...
Lin, Jinshan; Chen, Qian
2013-07-01
Vibration data of faulty rolling bearings are usually nonstationary and nonlinear, and contain fairly weak fault features. As a result, feature extraction of rolling bearing fault data is always an intractable problem and has attracted considerable attention for a long time. This paper introduces multifractal detrended fluctuation analysis (MF-DFA) to analyze bearing vibration data and proposes a novel method for fault diagnosis of rolling bearings based on MF-DFA and Mahalanobis distance criterion (MDC). MF-DFA, an extension of monofractal DFA, is a powerful tool for uncovering the nonlinear dynamical characteristics buried in nonstationary time series and can capture minor changes of complex system conditions. To begin with, by MF-DFA, multifractality of bearing fault data was quantified with the generalized Hurst exponent, the scaling exponent and the multifractal spectrum. Consequently, controlled by essentially different dynamical mechanisms, the multifractality of four heterogeneous bearing fault data is significantly different; by contrast, controlled by slightly different dynamical mechanisms, the multifractality of homogeneous bearing fault data with different fault diameters is significantly or slightly different depending on different types of bearing faults. Therefore, the multifractal spectrum, as a set of parameters describing multifractality of time series, can be employed to characterize different types and severity of bearing faults. Subsequently, five characteristic parameters sensitive to changes of bearing fault conditions were extracted from the multifractal spectrum and utilized to construct fault features of bearing fault data. Moreover, Hilbert transform based envelope analysis, empirical mode decomposition (EMD) and wavelet transform (WT) were utilized to study the same bearing fault data. Also, the kurtosis and the peak levels of the EMD or the WT component corresponding to the bearing tones in the frequency domain were carefully checked
Diaz-Pier, Sandra; Naveau, Mikaël; Butz-Ostendorf, Markus; Morrison, Abigail
2016-01-01
With the emergence of new high performance computation technology in the last decade, the simulation of large scale neural networks which are able to reproduce the behavior and structure of the brain has finally become an achievable target of neuroscience. Due to the number of synaptic connections between neurons and the complexity of biological networks, most contemporary models have manually defined or static connectivity. However, it is expected that modeling the dynamic generation and deletion of the links among neurons, locally and between different regions of the brain, is crucial to unravel important mechanisms associated with learning, memory and healing. Moreover, for many neural circuits that could potentially be modeled, activity data is more readily and reliably available than connectivity data. Thus, a framework that enables networks to wire themselves on the basis of specified activity targets can be of great value in specifying network models where connectivity data is incomplete or has large error margins. To address these issues, in the present work we present an implementation of a model of structural plasticity in the neural network simulator NEST. In this model, synapses consist of two parts, a pre- and a post-synaptic element. Synapses are created and deleted during the execution of the simulation following local homeostatic rules until a mean level of electrical activity is reached in the network. We assess the scalability of the implementation in order to evaluate its potential usage in the self generation of connectivity of large scale networks. We show and discuss the results of simulations on simple two population networks and more complex models of the cortical microcircuit involving 8 populations and 4 layers using the new framework.
Generation of hourly irradiation synthetic series using the neural network multilayer perceptron
Energy Technology Data Exchange (ETDEWEB)
Hontoria, L.; Aguilera, J. [Universidad de Jaen, Linares-Jaen (Spain). Dpto. de Electronica; Zufiria, P. [Ciudad Universitaria, Madrid (Spain). Grupo de Redes Neuronales
2002-05-01
In this work, a methodology based on the neural network model called multilayer perceptron (MLP) to solve a typical problem in solar energy is presented. This methodology consists of the generation of synthetic series of hourly solar irradiation. The model presented is based on the capacity of the MLP for finding relations between variables for which interrelation is unknown explicitly. The information available can be included progressively at the series generator at different stages. A comparative study with other solar irradiation synthetic generation methods has been done in order to demonstrate the validity of the one proposed. (author)
Research of PV Power Generation MPPT based on GABP Neural Network
Su, Yu; Lin, Xianfu
2018-05-01
Photovoltaic power generation has become the main research direction of new energy power generation. But high investment and low efficiency of photovoltaic industry arouse concern in some extent. So maximum power point tracking of photovoltaic power generation has been a popular study point. Due to slow response, oscillation at maximum power point and low precision, the algorithm based on genetic algorithm combined with BP neural network are designed detailedly in this paper. And the modeling and simulation are completed by use of MATLAB/SIMULINK. The results show that the algorithm is effective and the maximum power point can be tracked accurately and quickly.
DEFF Research Database (Denmark)
Ropenus, Stephanie; Jacobsen, Henrik; Schröder, Sascha Thorsten
2011-01-01
This article seeks to investigate the interactions between the policy dimensions of support schemes and network regulation and how they affect distributed generation. Firstly, the incentives of distributed generators and distribution system operators are examined. Frequently there exists a trade......-off between the incentives for these two market agents to facilitate the integration of distributed generation. Secondly, the interaction of these policy dimensions is analyzed, including case studies based on five EU Member States. Aspects of operational nature and investments in grid and distributed...
DEFF Research Database (Denmark)
Möller, Bernd
2002-01-01
In the past decade, Denmark has dramatically increased the share of distributed power generation from wind power and decentralised co-generation of heat and power (DCHP). This trend will conti-nue, with the consequence that the power transmission network will face capacity problems in the future....... At some times electricity has to be exported to neighbouring countries at market prices pro-bably lower than the costs of generation. To match production and consumption in the future, and at the same time maintain a good economy, alternative regulation instruments have to be found. These could consist...... electricity markets....
Reconstruction of three-dimensional porous media using generative adversarial neural networks
Mosser, Lukas; Dubrule, Olivier; Blunt, Martin J.
2017-10-01
To evaluate the variability of multiphase flow properties of porous media at the pore scale, it is necessary to acquire a number of representative samples of the void-solid structure. While modern x-ray computer tomography has made it possible to extract three-dimensional images of the pore space, assessment of the variability in the inherent material properties is often experimentally not feasible. We present a method to reconstruct the solid-void structure of porous media by applying a generative neural network that allows an implicit description of the probability distribution represented by three-dimensional image data sets. We show, by using an adversarial learning approach for neural networks, that this method of unsupervised learning is able to generate representative samples of porous media that honor their statistics. We successfully compare measures of pore morphology, such as the Euler characteristic, two-point statistics, and directional single-phase permeability of synthetic realizations with the calculated properties of a bead pack, Berea sandstone, and Ketton limestone. Results show that generative adversarial networks can be used to reconstruct high-resolution three-dimensional images of porous media at different scales that are representative of the morphology of the images used to train the neural network. The fully convolutional nature of the trained neural network allows the generation of large samples while maintaining computational efficiency. Compared to classical stochastic methods of image reconstruction, the implicit representation of the learned data distribution can be stored and reused to generate multiple realizations of the pore structure very rapidly.
Pricing of embedded generation: Incorporation of externalities and avoided network losses
International Nuclear Information System (INIS)
Rodrigo, Asanka S.; Wijayatunga, Priyantha D.C.
2007-01-01
Traditionally, the electricity purchase tariff of embedded generators reflected only the cost of production and delivery of electricity to the consumers, which includes the costs of labor, capital, operation, taxes and insurance. However, the production of electricity causes adverse impacts on the environment. At present, this issue has not been widely addressed by the existing pricing methodologies. This paper proposes a pricing methodology for renewable energy based embedded electricity generation, incorporating the cost of externalities with a case study on the Sri Lanka power system. It recommends that the embedded generation tariff be based on the principle of 'avoided cost', considering the cost of energy production, cost of externalities and the cost of network losses. While the 'impact path way' approach is proposed for calculation of the cost of externalities of energy, the nodal-based cost calculation is proposed for the avoided cost of network losses calculation. The pricing methodology proposed in the paper provides important information for investors when choosing the most economical site for their development. It can also be used to optimize the network use. These will allow the developers of embedded generation facilities and the utilities operating the national grid to maximize the potential of embedded generation. (author)
Molina, Martin; Sanchez-Soriano, Javier; Corcho, Oscar
2015-07-03
Providing descriptions of isolated sensors and sensor networks in natural language, understandable by the general public, is useful to help users find relevant sensors and analyze sensor data. In this paper, we discuss the feasibility of using geographic knowledge from public databases available on the Web (such as OpenStreetMap, Geonames, or DBpedia) to automatically construct such descriptions. We present a general method that uses such information to generate sensor descriptions in natural language. The results of the evaluation of our method in a hydrologic national sensor network showed that this approach is feasible and capable of generating adequate sensor descriptions with a lower development effort compared to other approaches. In the paper we also analyze certain problems that we found in public databases (e.g., heterogeneity, non-standard use of labels, or rigid search methods) and their impact in the generation of sensor descriptions.
Directory of Open Access Journals (Sweden)
Martin Molina
2015-07-01
Full Text Available Providing descriptions of isolated sensors and sensor networks in natural language, understandable by the general public, is useful to help users find relevant sensors and analyze sensor data. In this paper, we discuss the feasibility of using geographic knowledge from public databases available on the Web (such as OpenStreetMap, Geonames, or DBpedia to automatically construct such descriptions. We present a general method that uses such information to generate sensor descriptions in natural language. The results of the evaluation of our method in a hydrologic national sensor network showed that this approach is feasible and capable of generating adequate sensor descriptions with a lower development effort compared to other approaches. In the paper we also analyze certain problems that we found in public databases (e.g., heterogeneity, non-standard use of labels, or rigid search methods and their impact in the generation of sensor descriptions.
Nagashino, Hirofumi; Kinouchi, Yohsuke; Danesh, Ali A; Pandya, Abhijit S
2013-01-01
Tinnitus is the perception of sound in the ears or in the head where no external source is present. Sound therapy is one of the most effective techniques for tinnitus treatment that have been proposed. In order to investigate mechanisms of tinnitus generation and the clinical effects of sound therapy, we have proposed conceptual and computational models with plasticity using a neural oscillator or a neuronal network model. In the present paper, we propose a neuronal network model with simplified tonotopicity of the auditory system as more detailed structure. In this model an integrate-and-fire neuron model is employed and homeostatic plasticity is incorporated. The computer simulation results show that the present model can show the generation of oscillation and its cessation by external input. It suggests that the present framework is promising as a modeling for the tinnitus generation and the effects of sound therapy.
Complex network structure of musical compositions: Algorithmic generation of appealing music
Liu, Xiao Fan; Tse, Chi K.; Small, Michael
2010-01-01
In this paper we construct networks for music and attempt to compose music artificially. Networks are constructed with nodes and edges corresponding to musical notes and their co-occurring connections. We analyze classical music from Bach, Mozart, Chopin, as well as other types of music such as Chinese pop music. We observe remarkably similar properties in all networks constructed from the selected compositions. We conjecture that preserving the universal network properties is a necessary step in artificial composition of music. Power-law exponents of node degree, node strength and/or edge weight distributions, mean degrees, clustering coefficients, mean geodesic distances, etc. are reported. With the network constructed, music can be composed artificially using a controlled random walk algorithm, which begins with a randomly chosen note and selects the subsequent notes according to a simple set of rules that compares the weights of the edges, weights of the nodes, and/or the degrees of nodes. By generating a large number of compositions, we find that this algorithm generates music which has the necessary qualities to be subjectively judged as appealing.
Data-Driven Handover Optimization in Next Generation Mobile Communication Networks
Directory of Open Access Journals (Sweden)
Po-Chiang Lin
2016-01-01
Full Text Available Network densification is regarded as one of the important ingredients to increase capacity for next generation mobile communication networks. However, it also leads to mobility problems since users are more likely to hand over to another cell in dense or even ultradense mobile communication networks. Therefore, supporting seamless and robust connectivity through such networks becomes a very important issue. In this paper, we investigate handover (HO optimization in next generation mobile communication networks. We propose a data-driven handover optimization (DHO approach, which aims to mitigate mobility problems including too-late HO, too-early HO, HO to wrong cell, ping-pong HO, and unnecessary HO. The key performance indicator (KPI is defined as the weighted average of the ratios of these mobility problems. The DHO approach collects data from the mobile communication measurement results and provides a model to estimate the relationship between the KPI and features from the collected dataset. Based on the model, the handover parameters, including the handover margin and time-to-trigger, are optimized to minimize the KPI. Simulation results show that the proposed DHO approach could effectively mitigate mobility problems.
Exploiting Mobile Ad Hoc Networking and Knowledge Generation to Achieve Ambient Intelligence
Directory of Open Access Journals (Sweden)
Anna Lekova
2012-01-01
Full Text Available Ambient Intelligence (AmI joins together the fields of ubiquitous computing and communications, context awareness, and intelligent user interfaces. Energy, fault-tolerance, and mobility are newly added dimensions of AmI. Within the context of AmI the concept of mobile ad hoc networks (MANETs for “anytime and anywhere” is likely to play larger roles in the future in which people are surrounded and supported by small context-aware, cooperative, and nonobtrusive devices that will aid our everyday life. The connection between knowledge generation and communication ad hoc networking is symbiotic—knowledge generation utilizes ad hoc networking to perform their communication needs, and MANETs will utilize the knowledge generation to enhance their network services. The contribution of the present study is a distributed evolving fuzzy modeling framework (EFMF to observe and categorize relationships and activities in the user and application level and based on that social context to take intelligent decisions about MANETs service management. EFMF employs unsupervised online one-pass fuzzy clustering method to recognize nodes' mobility context from social scenario traces and ubiquitously learn “friends” and “strangers” indirectly and anonymously.
Chen, Shu-Peng; He, Ling-Yun
2010-04-01
Based on Partition Function and Multifractal Spectrum Analysis, we investigated the nonlinear dynamical mechanisms in China’s agricultural futures markets, namely, Dalian Commodity Exchange (DCE for short) and Zhengzhou Commodity Exchange (ZCE for short), where nearly all agricultural futures contracts are traded in the two markets. Firstly, we found nontrivial multifractal spectra, which are the empirical evidence of the existence of multifractal features, in 4 representative futures markets in China, that is, Hard Winter wheat (HW for short) and Strong Gluten wheat (SG for short) futures markets from ZCE and Soy Meal (SM for short) futures and Soy Bean No.1 (SB for short) futures markets from DCE. Secondly, by shuffling the original time series, we destroyed the underlying nonlinear temporal correlation; thus, we identified that long-range correlation mechanism constitutes major contributions in the formation in the multifractals of the markets. Thirdly, by tracking the evolution of left- and right-half spectra, we found that there exist critical points, between which there are different behaviors, in the left-half spectra for large price fluctuations; but for the right-hand spectra for small price fluctuations, the width of those increases slowly as the delay t increases in the long run. Finally, the dynamics of large fluctuations is significantly different from that of the small ones, which implies that there exist different underlying mechanisms in the formation of multifractality in the markets. Our main contributions focus on that we not only provided empirical evidence of the existence of multifractal features in China agricultural commodity futures markets; but also we pioneered in investigating the sources of the multifractality in China’s agricultural futures markets in current literature; furthermore, we investigated the nonlinear dynamical mechanisms based on spectrum analysis, which offers us insights into the underlying dynamical mechanisms in
Imaging the Where and When of Tic Generation and Resting State Networks in Adult Tourette Patients
Directory of Open Access Journals (Sweden)
Irene eNeuner
2014-05-01
Full Text Available Introduction: Tourette syndrome (TS is a neuropsychiatric disorder with the core phenomenon of tics, whose origin and temporal pattern are unclear. We investigated the When and Where of tic generation and resting state networks (RSNs via functional magnetic resonance imaging (fMRI.Methods: Tic-related activity and the underlying resting state networks in adult TS were studied within one fMRI session. Participants were instructed to lie in the scanner and to let tics occur freely. Tic onset times, as determined by video-observance were used as regressors and added to preceding time-bins of one second duration each to detect prior activation. RSN were identified by independent component analysis (ICA and correlated to disease severity by the means of dual regression.Results: Two seconds before a tic, the supplementary motor area (SMA, ventral primary motor cortex, primary sensorimotor cortex and parietal operculum exhibited activation; one second before a tic, the anterior cingulate, putamen, insula, amygdala, cerebellum and the extrastriatal-visual cortex exhibited activation; with tic-onset, the thalamus, central operculum, primary motor and somatosensory cortices exhibited activation. Analysis of resting state data resulted in 21 components including the so-called default-mode network. Network strength in those regions in SMA of two premotor ICA maps that were also active prior to tic occurrence, correlated significantly with disease severity according to the Yale Global Tic Severity Scale (YGTTS scores.Discussion: We demonstrate that the temporal pattern of tic generation follows the cortico-striato-thalamo-cortical circuit, and that cortical structures precede subcortical activation. The analysis of spontaneous fluctuations highlights the role of cortical premotor structures. Our study corroborates the notion of TS as a network disorder in which abnormal resting state network activity might contribute to the generation of tics in SMA.
International Nuclear Information System (INIS)
Wright, Glen
2012-01-01
Australia is heavily dependent on coal for electricity generation. The Renewable Energy Target has spurred growth in the utilization of renewable energy sources, with further growth expected into the future. Australia's strongest renewable energy sources are generally distant from the transmission network in resource ‘basins’. Investment is needed to augment the transmission network to enable delivery of electricity from these sources to consumers. Considerable economies of scale flow from anticipating the connection of numerous generators in an area over time and sizing augmentations accordingly. Following a lengthy rulemaking process, the National Electricity Rules were recently amended by a new rule, designed to facilitate the construction of such efficiently sized augmentations. However, the new rule is more conservative than initially envisaged, making little substantive change to the current frameworks for augmentation and connection. This paper outlines these frameworks and the rulemaking process and identifies the key debates surrounding the rule change are identified. This paper then provides a detailed analysis of the new rule, concluding that it is defective in a number of respects and is unlikely to result in the efficient and timely augmentation of the network needed to unlock the potential of Australia's strongest renewable energy resources. - Highlights: ► Remoteness of renewable energy sources is a barrier to greater renewable energy utilization. ► Significant economies of scale flow from efficiently-sized transmission network augmentation. ► Current frameworks in Australia do not incentivise efficiently-sized network augmentations. ► The lack of property rights in an augmentation is particularly problematic. ► The new Scale Efficient Network Extensions rule is not apt to facilitate efficiently-sized network augmentations.
Energy Technology Data Exchange (ETDEWEB)
Galdi, Vincenzo [Dipartimento di Ingegneria dell' Informazione e Ingegneria Elettrica, Universita degli studi di Salerno, Via Ponte Don Melillo 1, 84084 Fisciano (Italy); Vaccaro, Alfredo; Villacci, Domenico [Dipartimento di Ingegneria, Universita degli Studi del Sannio, Piazza Roma 21, 82100 Benevento (Italy)
2008-05-15
This paper puts forward the role of learning techniques in addressing the problem of an efficient and optimal centralized voltage control in distribution networks equipped with dispersed generation systems (DGSs). The proposed methodology employs a radial basis function network (RBFN) to identify the multidimensional nonlinear mapping between a vector of observable variables describing the network operating point and the optimal set points of the voltage regulating devices. The RBFN is trained by numerical data generated by solving the voltage regulation problem for a set of network operating points by a rigorous multiobjective solution methodology. The RBFN performance is continuously monitored by a supervisor process that notifies when there is the need of a more accurate solution of the voltage regulation problem if nonoptimal network operating conditions (ex post monitoring) or excessive distances between the actual network state and the neuron's centres (ex ante monitoring) are detected. A more rigorous problem solution, if required, can be obtained by solving the voltage regulation problem by a conventional multiobjective optimization technique. This new solution, in conjunction with the corresponding input vector, is then adopted as a new train data sample to adapt the RBFN. This online training process allows RBFN to (i) adaptively learn the more representative domain space regions of the input/output mapping without needing a prior knowledge of a complete and representative training set, and (ii) manage effectively any time varying phenomena affecting this mapping. The results obtained by simulating the regulation policy in the case of a medium-voltage network are very promising. (author)
History of electricity network control and distributed generation in the UK and Western Denmark
International Nuclear Information System (INIS)
Lehtonen, Markku; Nye, Sheridan
2009-01-01
Achieving the ambitious targets for renewable electricity generation in Europe will require harnessing a diverse range of energy sources, many of which are decentralised, small scale, and will be connected directly to the distribution networks. To control the two-way flows of electricity, the current passive network configurations will need to be replaced by active network management. This will require, in particular, innovations in intelligent IT-based network control. This paper draws on research on Large Technical Systems (LTS) and control systems in other sectors to analyse the evolution of electricity network control in western Denmark and the UK, since the Second World War. It concludes that lack of progress in network control has only recently-largely because of the combined needs to provide greater reliability and 'green' electricity within liberalised markets-emerged as a 'reverse salient' that will prevent the further development of the LTS of electricity supply industry towards desired direction. Breaking the inertia in the LTS and its control systems will require determined government action to promote learning and collaborative search for solutions. The UK might well draw lessons from the Danish pragmatism in fostering innovation through targeted support to collaborative R and D efforts towards sustainability objectives.
History of electricity network control and distributed generation in the UK and Western Denmark
Energy Technology Data Exchange (ETDEWEB)
Lehtonen, Markku [Sussex Energy Group, SPRU, University of Sussex, Freeman Centre, Falmer, Brighton, East Sussex BN1 9QE (United Kingdom); Nye, Sheridan [SPRU, University of Sussex, Freeman Centre, Falmer, Brighton, East Sussex BN1 9QE (United Kingdom)
2009-06-15
Achieving the ambitious targets for renewable electricity generation in Europe will require harnessing a diverse range of energy sources, many of which are decentralised, small scale, and will be connected directly to the distribution networks. To control the two-way flows of electricity, the current passive network configurations will need to be replaced by active network management. This will require, in particular, innovations in intelligent IT-based network control. This paper draws on research on Large Technical Systems (LTS) and control systems in other sectors to analyse the evolution of electricity network control in western Denmark and the UK, since the Second World War. It concludes that lack of progress in network control has only recently - largely because of the combined needs to provide greater reliability and 'green' electricity within liberalised markets - emerged as a 'reverse salient' that will prevent the further development of the LTS of electricity supply industry towards desired direction. Breaking the inertia in the LTS and its control systems will require determined government action to promote learning and collaborative search for solutions. The UK might well draw lessons from the Danish pragmatism in fostering innovation through targeted support to collaborative R and D efforts towards sustainability objectives. (author)
Fluid power network for centralized electricity generation in offshore wind farms
International Nuclear Information System (INIS)
Jarquin-Laguna, A
2014-01-01
An innovative and completely different wind-energy conversion system is studied where a centralized electricity generation within a wind farm is proposed by means of a hydraulic network. This paper presents the dynamic interaction of two turbines when they are coupled to the same hydraulic network. Due to the stochastic nature of the wind and wake interaction effects between turbines, the operating parameters (i.e. pitch angle, rotor speed) of each turbine are different. Time domain simulations, including the main turbine dynamics and laminar transient flow in pipelines, are used to evaluate the efficiency and rotor speed stability of the hydraulic system. It is shown that a passive control of the rotor speed, as proposed in previous work for a single hydraulic turbine, has strong limitations in terms of performance for more than one turbine coupled to the same hydraulic network. It is concluded that in order to connect several turbines, a passive control strategy of the rotor speed is not sufficient and a hydraulic network with constant pressure is suggested. However, a constant pressure network requires the addition of active control at the hydraulic motors and spear valves, increasing the complexity of the initial concept. Further work needs to be done to incorporate an active control strategy and evaluate the feasibility of the constant pressure hydraulic network
Translation-aware semantic segmentation via conditional least-square generative adversarial networks
Zhang, Mi; Hu, Xiangyun; Zhao, Like; Pang, Shiyan; Gong, Jinqi; Luo, Min
2017-10-01
Semantic segmentation has recently made rapid progress in the field of remote sensing and computer vision. However, many leading approaches cannot simultaneously translate label maps to possible source images with a limited number of training images. The core issue is insufficient adversarial information to interpret the inverse process and proper objective loss function to overcome the vanishing gradient problem. We propose the use of conditional least squares generative adversarial networks (CLS-GAN) to delineate visual objects and solve these problems. We trained the CLS-GAN network for semantic segmentation to discriminate dense prediction information either from training images or generative networks. We show that the optimal objective function of CLS-GAN is a special class of f-divergence and yields a generator that lies on the decision boundary of discriminator that reduces possible vanished gradient. We also demonstrate the effectiveness of the proposed architecture at translating images from label maps in the learning process. Experiments on a limited number of high resolution images, including close-range and remote sensing datasets, indicate that the proposed method leads to the improved semantic segmentation accuracy and can simultaneously generate high quality images from label maps.
Unbundling in Current Broadband and Next-Generation Ultra-Broadband Access Networks
Gaudino, Roberto; Giuliano, Romeo; Mazzenga, Franco; Valcarenghi, Luca; Vatalaro, Francesco
2014-05-01
This article overviews the methods that are currently under investigation for implementing multi-operator open-access/shared-access techniques in next-generation access ultra-broadband architectures, starting from the traditional "unbundling-of-the-local-loop" techniques implemented in legacy twisted-pair digital subscriber line access networks. A straightforward replication of these copper-based unbundling-of-the-local-loop techniques is usually not feasible on next-generation access networks, including fiber-to-the-home point-to-multipoint passive optical networks. To investigate this issue, the article first gives a concise description of traditional copper-based unbundling-of-the-local-loop solutions, then focalizes on both next-generation access hybrid fiber-copper digital subscriber line fiber-to-the-cabinet scenarios and on fiber to the home by accounting for the mix of regulatory and technological reasons driving the next-generation access migration path, focusing mostly on the European situation.
3D conditional generative adversarial networks for high-quality PET image estimation at low dose.
Wang, Yan; Yu, Biting; Wang, Lei; Zu, Chen; Lalush, David S; Lin, Weili; Wu, Xi; Zhou, Jiliu; Shen, Dinggang; Zhou, Luping
2018-07-01
Positron emission tomography (PET) is a widely used imaging modality, providing insight into both the biochemical and physiological processes of human body. Usually, a full dose radioactive tracer is required to obtain high-quality PET images for clinical needs. This inevitably raises concerns about potential health hazards. On the other hand, dose reduction may cause the increased noise in the reconstructed PET images, which impacts the image quality to a certain extent. In this paper, in order to reduce the radiation exposure while maintaining the high quality of PET images, we propose a novel method based on 3D conditional generative adversarial networks (3D c-GANs) to estimate the high-quality full-dose PET images from low-dose ones. Generative adversarial networks (GANs) include a generator network and a discriminator network which are trained simultaneously with the goal of one beating the other. Similar to GANs, in the proposed 3D c-GANs, we condition the model on an input low-dose PET image and generate a corresponding output full-dose PET image. Specifically, to render the same underlying information between the low-dose and full-dose PET images, a 3D U-net-like deep architecture which can combine hierarchical features by using skip connection is designed as the generator network to synthesize the full-dose image. In order to guarantee the synthesized PET image to be close to the real one, we take into account of the estimation error loss in addition to the discriminator feedback to train the generator network. Furthermore, a concatenated 3D c-GANs based progressive refinement scheme is also proposed to further improve the quality of estimated images. Validation was done on a real human brain dataset including both the normal subjects and the subjects diagnosed as mild cognitive impairment (MCI). Experimental results show that our proposed 3D c-GANs method outperforms the benchmark methods and achieves much better performance than the state
Directory of Open Access Journals (Sweden)
Pommerening, Klaus
2006-06-01
Full Text Available The Society for Paediatric Oncology and Haematology (GPOH and the corresponding Competence Network Paediatric Oncology and Haematology conduct various clinical trials. The comprehensive analysis requires reliable identification of the recruited patients. Therefore, a personal identifier (PID generator is used to assign unambiguous, pseudonymous, non-reversible PIDs to participants in those trials. We tested the matching algorithm of the PID generator using a configuration specific to the GPOH. False data was used to verify the correct processing of PID requests (functionality tests, while test data was used to evaluate the matching outcome. We also assigned PIDs to more than 44,000 data records from the German Childhood Cancer Registry (GCCR and assessed the status of the associated patient list which contains the PIDs, partly encrypted data items and information on the PID generation process for each data record. All the functionality tests showed the expected results. Neither 14,915 test data records nor the GCCR data records yielded any homonyms. Six synonyms were found in the test data, due to erroneous birth dates, and 22 synonyms were found when the GCCR data was run against the actual patient list of 2579 records. In the resulting patient list of 45,693 entries, duplicate record submissions were found for about 7% of all listed patients, while more frequent submissions occurred in less than 1% of cases. The synonym error rate depends mainly on the quality of the input data and on the frequency of multiple submissions. Depending on the requirements on maximally tolerable synonym and homonym error rates, additional measures for securing input data quality might be necessary. The results demonstrate that the PID generator is an appropriate tool for reliably identifying trial participants in medical research networks.
State of the art of the virtual utility: the smart distributed generation network
International Nuclear Information System (INIS)
Coll-Mayor, D.; Picos, R.; Garcia-Moreno, E.
2004-01-01
The world of energy has lately experienced a revolution, and new rules are being defined. The climate change produced by the greenhouse gases, the inefficiency of the energy system or the lack of power supply infrastructure in most of the poor countries, the liberalization of the energy market and the development of new technologies in the field of distributed generation (DG) are the key factors of this revolution. It seems clear that the solution at the moment is the DG. The advantage of DG is the energy generation close to the demand point. It means that DG can lower costs, reduce emissions, or expand the energy options of the consumers. DG may add redundancy that increases grid security even while powering emergency lighting or other critical systems and reduces power losses in the electricity distribution. After the development of the different DG and high efficiency technologies such as co-generation and tri-generation, the next step in the DG world is the interconnection of different small distributed generation facilities which act together in a DG network as a large power plant controlled by a centralized energy management system (EMS). The main aim of the EMS is to reach the targets of low emissions and high efficiency. The EMS gives priority to renewable energy sources instead of the use of fossil fuels. This new concept of energy infrastructure is referred to as virtual utility (VU). The VU can be defined as a new model of energy infrastructure which consists of integrating different kind of distributed generation utilities in an energy (electricity and heat) generation network controlled by a central energy management system (EMS). The electricity production in the network is subordinated to the heat necessity of every user. The thermal energy is consumed on site; the electricity is generated and distributed in the entire network. The network is composed of one centralized control with the EMS and different clusters of distributed generation utilities
Multifractal analysis of 2D gray soil images
González-Torres, Ivan; Losada, Juan Carlos; Heck, Richard; Tarquis, Ana M.
2015-04-01
Soil structure, understood as the spatial arrangement of soil pores, is one of the key factors in soil modelling processes. Geometric properties of individual and interpretation of the morphological parameters of pores can be estimated from thin sections or 3D Computed Tomography images (Tarquis et al., 2003), but there is no satisfactory method to binarized these images and quantify the complexity of their spatial arrangement (Tarquis et al., 2008, Tarquis et al., 2009; Baveye et al., 2010). The objective of this work was to apply a multifractal technique, their singularities (α) and f(α) spectra, to quantify it without applying any threshold (Gónzalez-Torres, 2014). Intact soil samples were collected from four horizons of an Argisol, formed on the Tertiary Barreiras group of formations in Pernambuco state, Brazil (Itapirema Experimental Station). The natural vegetation of the region is tropical, coastal rainforest. From each horizon, showing different porosities and spatial arrangements, three adjacent samples were taken having a set of twelve samples. The intact soil samples were imaged using an EVS (now GE Medical. London, Canada) MS-8 MicroCT scanner with 45 μm pixel-1 resolution (256x256 pixels). Though some samples required paring to fit the 64 mm diameter imaging tubes, field orientation was maintained. References Baveye, P.C., M. Laba, W. Otten, L. Bouckaert, P. Dello, R.R. Goswami, D. Grinev, A. Houston, Yaoping Hu, Jianli Liu, S. Mooney, R. Pajor, S. Sleutel, A. Tarquis, Wei Wang, Qiao Wei, Mehmet Sezgin. Observer-dependent variability of the thresholding step in the quantitative analysis of soil images and X-ray microtomography data. Geoderma, 157, 51-63, 2010. González-Torres, Iván. Theory and application of multifractal analysis methods in images for the study of soil structure. Master thesis, UPM, 2014. Tarquis, A.M., R.J. Heck, J.B. Grau; J. Fabregat, M.E. Sanchez and J.M. Antón. Influence of Thresholding in Mass and Entropy Dimension of 3-D
Du, Tingsong; Hu, Yang; Ke, Xianting
2015-01-01
An improved quantum artificial fish swarm algorithm (IQAFSA) for solving distributed network programming considering distributed generation is proposed in this work. The IQAFSA based on quantum computing which has exponential acceleration for heuristic algorithm uses quantum bits to code artificial fish and quantum revolving gate, preying behavior, and following behavior and variation of quantum artificial fish to update the artificial fish for searching for optimal value. Then, we apply the proposed new algorithm, the quantum artificial fish swarm algorithm (QAFSA), the basic artificial fish swarm algorithm (BAFSA), and the global edition artificial fish swarm algorithm (GAFSA) to the simulation experiments for some typical test functions, respectively. The simulation results demonstrate that the proposed algorithm can escape from the local extremum effectively and has higher convergence speed and better accuracy. Finally, applying IQAFSA to distributed network problems and the simulation results for 33-bus radial distribution network system show that IQAFSA can get the minimum power loss after comparing with BAFSA, GAFSA, and QAFSA.
Directory of Open Access Journals (Sweden)
Titov Sergei
2016-01-01
Full Text Available Engineering companies engaged in business of industry control systems need to manage the processes of generation of innovations within and across their projects. Generation and diffusion of innovations materialize through the communication networks of project teams. Therefore, it is possible to hypothesize that the characteristics of communication networks play role in generation of new knowledge. With the data from 14 industry control system projects of a Russian engineering company the communication network structure characteristics were calculated and the analysis of correlation between these characteristics and knowledge generation capabilities was performed. As a result correlation between centralization of communication and the number of new technical solutions developed in projects was discovered.
Energy Technology Data Exchange (ETDEWEB)
Yadav, R.P. [Department of Physics, University of Allahabad, Allahabad, UP 211002 (India); Dwivedi, S., E-mail: suneetdwivedi@gmail.com [K Banerjee Centre of Atmospheric and Ocean Studies, University of Allahabad, Allahabad, UP 211002 (India); Mittal, A.K. [Department of Physics, University of Allahabad, Allahabad, UP 211002 (India); K Banerjee Centre of Atmospheric and Ocean Studies, University of Allahabad, Allahabad, UP 211002 (India); Kumar, Manvendra [Nanotechnology Application Centre, University of Allahabad, Allahabad, UP 211002 (India); Pandey, A.C. [K Banerjee Centre of Atmospheric and Ocean Studies, University of Allahabad, Allahabad, UP 211002 (India); Nanotechnology Application Centre, University of Allahabad, Allahabad, UP 211002 (India)
2014-07-01
The Atomic Force Microscopy technique is used to characterize the surface morphology of LiF thin films deposited at substrate temperatures 77 K, 300 K and 500 K, respectively. It is found that the surface roughness of thin film increases with substrate temperature. The multifractal nature of the LiF thin film at each substrate temperature is investigated using the backward two-dimensional multifractal detrended moving average analysis. The strength of multifractility and the non-uniformity of the height probabilities of the thin films increase as the substrate temperature increases. Both the width of the multifractal spectrum and the difference of fractal dimensions of the thin films increase sharply as the temperature reaches 500 K, indicating that the multifractility of the thin films becomes more pronounced at the higher substrate temperatures with greater cluster size. - Highlights: • Analyzing LiF thin films using multifractal detrended moving average technique • Surface roughness of LiF thin film increases with substrate temperature. • LiF thin films at each substrate temperature exhibit multifractality. • Multifractility becomes more pronounced at the higher substrate temperatures.
Directory of Open Access Journals (Sweden)
M. S. Jouini
2011-12-01
Full Text Available Pore spaces heterogeneity in carbonates rocks has long been identified as an important factor impacting reservoir productivity. In this paper, we study the heterogeneity of carbonate rocks pore spaces based on the image analysis of scanning electron microscopy (SEM data acquired at various magnifications. Sixty images of twelve carbonate samples from a reservoir in the Middle East were analyzed. First, pore spaces were extracted from SEM images using a segmentation technique based on watershed algorithm. Pores geometries revealed a multifractal behavior at various magnifications from 800x to 12 000x. In addition, the singularity spectrum provided quantitative values that describe the degree of heterogeneity in the carbonates samples. Moreover, for the majority of the analyzed samples, we found low variations (around 5% in the multifractal dimensions for magnifications between 1700x and 12 000x. Finally, these results demonstrate that multifractal analysis could be an appropriate tool for characterizing quantitatively the heterogeneity of carbonate pore spaces geometries. However, our findings show that magnification has an impact on multifractal dimensions, revealing the limit of applicability of multifractal descriptions for these natural structures.
Price-volume multifractal analysis and its application in Chinese stock markets
Yuan, Ying; Zhuang, Xin-tian; Liu, Zhi-ying
2012-06-01
An empirical research on Chinese stock markets is conducted using statistical tools. First, the multifractality of stock price return series, ri(ri=ln(Pt+1)-ln(Pt)) and trading volume variation series, vi(vi=ln(Vt+1)-ln(Vt)) is confirmed using multifractal detrended fluctuation analysis. Furthermore, a multifractal detrended cross-correlation analysis between stock price return and trading volume variation in Chinese stock markets is also conducted. It is shown that the cross relationship between them is also found to be multifractal. Second, the cross-correlation between stock price Pi and trading volume Vi is empirically studied using cross-correlation function and detrended cross-correlation analysis. It is found that both Shanghai stock market and Shenzhen stock market show pronounced long-range cross-correlations between stock price and trading volume. Third, a composite index R based on price and trading volume is introduced. Compared with stock price return series ri and trading volume variation series vi, R variation series not only remain the characteristics of original series but also demonstrate the relative correlation between stock price and trading volume. Finally, we analyze the multifractal characteristics of R variation series before and after three financial events in China (namely, Price Limits, Reform of Non-tradable Shares and financial crisis in 2008) in the whole period of sample to study the changes of stock market fluctuation and financial risk. It is found that the empirical results verified the validity of R.
Timetable-based simulation method for choice set generation in large-scale public transport networks
DEFF Research Database (Denmark)
Rasmussen, Thomas Kjær; Anderson, Marie Karen; Nielsen, Otto Anker
2016-01-01
The composition and size of the choice sets are a key for the correct estimation of and prediction by route choice models. While existing literature has posed a great deal of attention towards the generation of path choice sets for private transport problems, the same does not apply to public...... transport problems. This study proposes a timetable-based simulation method for generating path choice sets in a multimodal public transport network. Moreover, this study illustrates the feasibility of its implementation by applying the method to reproduce 5131 real-life trips in the Greater Copenhagen Area...... and to assess the choice set quality in a complex multimodal transport network. Results illustrate the applicability of the algorithm and the relevance of the utility specification chosen for the reproduction of real-life path choices. Moreover, results show that the level of stochasticity used in choice set...
Measuring complexity with multifractals in texts. Translation effects
International Nuclear Information System (INIS)
Ausloos, M.
2012-01-01
Highlights: ► Two texts in English and one in Esperanto are transformed into 6 time series. ► D(q) and f(alpha) of such (and shuffled) time series are obtained. ► A model for text construction is presented based on a parametrized Cantor set. ► The model parameters can also be used when examining machine translated texts. ► Suggested extensions to higher dimensions: in 2D image analysis and on hypertexts. - Abstract: Should quality be almost a synonymous of complexity? To measure quality appears to be audacious, even very subjective. It is hereby proposed to use a multifractal approach in order to quantify quality, thus through complexity measures. A one-dimensional system is examined. It is known that (all) written texts can be one-dimensional nonlinear maps. Thus, several written texts by the same author are considered, together with their translation, into an unusual language, Esperanto, and asa baseline their corresponding shuffled versions. Different one-dimensional time series can be used: e.g. (i) one based on word lengths, (ii) the other based on word frequencies; both are used for studying, comparing and discussing the map structure. It is shown that a variety in style can be measured through the D(q) and f(α) curves characterizing multifractal objects. This allows to observe on the one hand whether natural and artificial languages significantly influence the writing and the translation, and whether one author’s texts differ technically from each other. In fact, the f(α) curves of the original texts are similar to each other, but the translated text shows marked differences. However in each case, the f(α) curves are far from being parabolic, – in contrast to the shuffled texts. Moreover, the Esperanto text has more extreme values. Criteria are thereby suggested for estimating a text quality, as if it is a time series only. A model is introduced in order to substantiate the findings: it consists in considering a text as a random Cantor set
Reflection on Migration Scenarios 2G and 3G Mobile Networks to Fourth Generation in Colombia
Directory of Open Access Journals (Sweden)
Sergio A. Sepúlveda-Leiva
2013-11-01
Full Text Available In the development of the following article is an analysis of some of the migration scenarios third generation mobile technologies for fourth generation mobile technologies, in order to select which is the most suitable migration scenario for mobile operators Colombia, taking into account the characteristics of the market and the needs that are more optimally suited for the needs of mobile operators in the country, the whole development of the article is based on operators with own infrastructure is not analyzed migration characteristics of mobile virtual network operators.
Dahlem, Markus A.
2013-12-01
Migraine is a common disabling headache disorder characterized by recurrent episodes sometimes preceded or accompanied by focal neurological symptoms called aura. The relation between two subtypes, migraine without aura (MWoA) and migraine with aura (MWA), is explored with the aim to identify targets for neuromodulation techniques. To this end, a dynamically regulated control system is schematically reduced to a network of the trigeminal nerve, which innervates the cranial circulation, an associated descending modulatory network of brainstem nuclei, and parasympathetic vasomotor efferents. This extends the idea of a migraine generator region in the brainstem to a larger network and is still simple and explicit enough to open up possibilities for mathematical modeling in the future. In this study, it is suggested that the migraine generator network (MGN) is driven and may therefore respond differently to different spatio-temporal noxious input in the migraine subtypes MWA and MWoA. The noxious input is caused by a cortical perturbation of homeostasis, known as spreading depression (SD). The MGN might even trigger SD in the first place by a failure in vasomotor control. As a consequence, migraine is considered as an inherently dynamical disease to which a linear course from upstream to downstream events would not do justice. Minimally invasive and noninvasive neuromodulation techniques are briefly reviewed and their rational is discussed in the context of the proposed mechanism.
Universal Intelligent Small Cell (UnISCell for next generation cellular networks
Directory of Open Access Journals (Sweden)
Mohammad Patwary
2016-11-01
Full Text Available Exploring innovative cellular architectures to achieve enhanced system capacity and good coverage has become a critical issue towards realizing the next generation of wireless communications. In this context, this paper proposes a novel concept of Universal Intelligent Small Cell (UnISCell for enabling the densification of the next generation of cellular networks. The proposed novel concept envisions an integrated platform of providing a strong linkage between different stakeholders such as street lighting networks, landline telephone networks and future wireless networks, and is universal in nature being independent of the operating frequency bands and traffic types. The main motivating factors for the proposed small cell concept are the need of public infrastructure re-engineering, and the recent advances in several enabling technologies. First, we highlight the main concepts of the proposed UnISCell platform. Subsequently, we present two deployment scenarios for the proposed UnISCell concept considering infrastructure sharing and service sharing as important aspects. We then describe the key future technologies for enabling the proposed UnISCell concept and present a use case example with the help of numerical results. Finally, we conclude this article by providing some interesting future recommendations.
Ghazzai, Hakim
2016-09-16
Over the last decade, mobile communications have been witnessing a noteworthy increase of data traffic demand that is causing an enormous energy consumption in cellular networks. The reduction of their fossil fuel consumption in addition to the huge energy bills paid by mobile operators is considered as the most important challenges for the next-generation cellular networks. Although most of the proposed studies were focusing on individual physical layer power optimizations, there is a growing necessity to meet the green objective of fifth-generation cellular networks while respecting the user\\'s quality of service. This paper investigates four important techniques that could be exploited separately or together in order to enable wireless operators achieve significant economic benefits and environmental savings: 1) the base station sleeping strategy; 2) the optimized energy procurement from the smart grid; 3) the base station energy sharing; and 4) the green networking collaboration between competitive mobile operators. The presented simulation results measure the gain that could be obtained using these techniques compared with that of traditional scenarios. Finally, this paper discusses the issues and challenges related to the implementations of these techniques in real environments. © 2016 IEEE.
Robust transient stabilisation problem for a synchronous generator in a power network
Verrelli, C. M.; Damm, G.
2010-04-01
The robust transient stabilisation problem (with stability proof) of a synchronous generator in an uncertain power network with transfer conductances is rigorously formulated and solved. The generator angular speed and electrical power are required to be kept close, when mechanical and electrical perturbations occur, to the synchronous speed and mechanical input power, respectively, while the generator terminal voltage is to be regulated, when perturbations are removed, to its pre-fault reference constant value. A robust adaptive nonlinear feedback control algorithm is designed on the basis of a third-order model of the synchronous machine: only two system parameters (synchronous machine damping and inertia constants) along with upper and lower bounds on the remaining uncertain ones are supposed to be known. The conditions to be satisfied by the remote network dynamics for guaranteeing ℒ2 and ℒ∞ robustness and asymptotic relative speed and voltage regulation to zero are weaker than those required by the single machine-infinite bus approximation: dynamic interactions between the local deviations of the generator states from the corresponding equilibrium values and the remote generators states are allowed.
Directory of Open Access Journals (Sweden)
A.M. Ibrahim
2016-09-01
Full Text Available This paper presents an adaptive protection coordination scheme for optimal coordination of DOCRs in interconnected power networks with the impact of DG, the used coordination technique is the Artificial Bee Colony (ABC. The scheme adapts to system changes; new relays settings are obtained as generation-level or system-topology changes. The developed adaptive scheme is applied on the IEEE 30-bus test system for both single- and multi-DG existence where results are shown and discussed.
Yun, Kyongsik; Lu, Thomas; Chow, Edward
2018-01-01
Firefighters suffer a variety of life-threatening risks, including line-of-duty deaths, injuries, and exposures to hazardous substances. Support for reducing these risks is important. We built a partially occluded object reconstruction method on augmented reality glasses for first responders. We used a deep learning based on conditional generative adversarial networks to train associations between the various images of flammable and hazardous objects and their partially occluded counterparts....
Das, Nandan Kumar; Dey, Rajib; Chakraborty, Semanti; Panigrahi, Prasanta K.; Meglinski, Igor; Ghosh, Nirmalya
2018-04-01
A number of tissue-like disordered media exhibit local anisotropy of scattering in the scaling behavior. Scaling behavior contains wealth of fractal or multifractal properties. We demonstrate that the spatial dielectric fluctuations in a sample of biological tissue exhibit multifractal anisotropy. Multifractal anisotropy encoded in the wavelength variation of the light scattering Mueller matrix and manifesting as an intriguing spectral diattenuation effect. We developed an inverse method for the quantitative assessment of the multifractal anisotropy. The method is based on the processing of relevant Mueller matrix elements in Fourier domain by using Born approximation, followed by the multifractal analysis. The approach promises for probing subtle micro-structural changes in biological tissues associated with the cancer and precancer, as well as for non-destructive characterization of a wide range of scattering materials.
International Nuclear Information System (INIS)
Ţălu, Ştefan; Marković, Zoran; Stach, Sebastian; Todorović Marković, B.; Ţălu, Mihai
2014-01-01
This study presents a multifractal approach, obtained with atomic force microscopy analysis, to characterize the structural evolution of single wall carbon nanotube thin films upon exposure to optical parametric oscillator laser irradiation at wavelength of 430 nm. Microstructure and morphological changes of carbon nanotube films deposited on different substrates (mica and TGX grating) were recorded by atomic force microscope. A detailed methodology for surface multifractal characterization, which may be applied for atomic force microscopy data, was presented. Multifractal analysis of surface roughness revealed that carbon nanotube films surface has a multifractal geometry at various magnifications. The generalized dimension D q and the singularity spectrum f(α) provided quantitative values that characterize the local scale properties of carbon nanotube films surface morphology at nanometer scale. Multifractal analysis provides different yet complementary information to that offered by traditional surface statistical parameters.
Directory of Open Access Journals (Sweden)
J. C. Ochoa-Rivera
2002-01-01
Full Text Available A model for multivariate streamflow generation is presented, based on a multilayer feedforward neural network. The structure of the model results from two components, the neural network (NN deterministic component and a random component which is assumed to be normally distributed. It is from this second component that the model achieves the ability to incorporate effectively the uncertainty associated with hydrological processes, making it valuable as a practical tool for synthetic generation of streamflow series. The NN topology and the corresponding analytical explicit formulation of the model are described in detail. The model is calibrated with a series of monthly inflows to two reservoir sites located in the Tagus River basin (Spain, while validation is performed through estimation of a set of statistics that is relevant for water resources systems planning and management. Among others, drought and storage statistics are computed and compared for both the synthetic and historical series. The performance of the NN-based model was compared to that of a standard autoregressive AR(2 model. Results show that NN represents a promising modelling alternative for simulation purposes, with interesting potential in the context of water resources systems management and optimisation. Keywords: neural networks, perceptron multilayer, error backpropagation, hydrological scenario generation, multivariate time-series..
Directory of Open Access Journals (Sweden)
Braden Manns
2014-04-01
Full Text Available Patients with chronic kidney disease (CKD do not always receive care consistent with guidelines, in part due to complexities in CKD management, lack of randomized trial data to inform care, and a failure to disseminate best practice. At a 2007 conference of key Canadian stakeholders in kidney disease, attendees noted that the impact of Canadian Society of Nephrology (CSN guidelines was attenuated given limited formal linkages between the CSN Clinical Practice Guidelines Group, kidney researchers, decision makers and knowledge users, and that further knowledge was required to guide care in patients with kidney disease. The idea for the Canadian Kidney Knowledge Translation and Generation Network (CANN-NET developed from this meeting. CANN-NET is a pan-Canadian network established in partnership with CSN, the Kidney Foundation of Canada and other professional societies to improve the care and outcomes of patients with and at risk for kidney disease. The initial priority areas for knowledge translation include improving optimal timing of dialysis initiation, and increasing the appropriate use of home dialysis. Given the urgent need for new knowledge, CANN-NET has also brought together a national group of experienced Canadian researchers to address knowledge gaps by encouraging and supporting multicentre randomized trials in priority areas, including management of cardiovascular disease in patients with kidney failure.
Manns, Braden; Barrett, Brendan; Evans, Michael; Garg, Amit; Hemmelgarn, Brenda; Kappel, Joanne; Klarenbach, Scott; Madore, Francois; Parfrey, Patrick; Samuel, Susan; Soroka, Steven; Suri, Rita; Tonelli, Marcello; Wald, Ron; Walsh, Michael; Zappitelli, Michael
2014-01-01
Patients with chronic kidney disease (CKD) do not always receive care consistent with guidelines, in part due to complexities in CKD management, lack of randomized trial data to inform care, and a failure to disseminate best practice. At a 2007 conference of key Canadian stakeholders in kidney disease, attendees noted that the impact of Canadian Society of Nephrology (CSN) guidelines was attenuated given limited formal linkages between the CSN Clinical Practice Guidelines Group, kidney researchers, decision makers and knowledge users, and that further knowledge was required to guide care in patients with kidney disease. The idea for the Canadian Kidney Knowledge Translation and Generation Network (CANN-NET) developed from this meeting. CANN-NET is a pan-Canadian network established in partnership with CSN, the Kidney Foundation of Canada and other professional societies to improve the care and outcomes of patients with and at risk for kidney disease. The initial priority areas for knowledge translation include improving optimal timing of dialysis initiation, and increasing the appropriate use of home dialysis. Given the urgent need for new knowledge, CANN-NET has also brought together a national group of experienced Canadian researchers to address knowledge gaps by encouraging and supporting multicentre randomized trials in priority areas, including management of cardiovascular disease in patients with kidney failure.
Yin, Xiangyu; Zhang, Yue; Guo, Qiuquan; Cai, Xiaobing; Xiao, Junfeng; Ding, Zhifeng; Yang, Jun
2018-04-04
Solar steam generation is one of the most promising solar-energy-harvesting technologies to address the issue of water shortage. Despite intensive efforts to develop high-efficiency solar steam generation devices, challenges remain in terms of the relatively low solar thermal efficiency, complicated fabrications, high cost, and difficulty in scaling up. Herein, a double-network hydrogel with a porous structure (p-PEGDA-PANi) is demonstrated for the first time as a flexible, recyclable, and efficient photothermal platform for low-cost and scalable solar steam generation. As a novel photothermal platform, the p-PEGDA-PANi involves all necessary properties of efficient broadband solar absorption, exceptional hydrophilicity, low heat conductivity, and porous structure for high-efficiency solar steam generation. As a result, the hydrogel-based solar steam generator exhibits a maximum solar thermal efficiency of 91.5% with an evaporation rate of 1.40 kg m -2 h -1 under 1 sun illumination, which is comparable to state-of-the-art solar steam generation devices. Furthermore, the good durability and environmental stability of the p-PEGDA-PANi hydrogel enables a convenient recycling and reusing process toward real-life applications. The present research not only provides a novel photothermal platform for solar energy harvest but also opens a new avenue for the application of the hydrogel materials in solar steam generation.
Multifractality and quantum diffusion from self-consistent theory of localization
Energy Technology Data Exchange (ETDEWEB)
Suslov, I. M., E-mail: suslov@kapitza.ras.ru [Kapitza Institute for Physical Problems (Russian Federation)
2015-11-15
Multifractal properties of wave functions in a disordered system can be derived from self-consistent theory of localization by Vollhardt and Wölfle. A diagrammatic interpretation of results allows to obtain all scaling relations used in numerical experiments. The arguments are given that the one-loop Wegner result for a space dimension d = 2 + ϵ is exact, so the multifractal spectrum is strictly parabolical. The σ-models are shown to be deficient at the four-loop level and the possible reasons of that are discussed. The extremely slow convergence to the thermodynamic limit is demonstrated. The open question on the relation between multifractality and a spatial dispersion of the diffusion coefficient D(ω, q) is resolved in the compromise manner due to ambiguity of the D(ω, q) definition. Comparison is made with the extensive numerical material.
Empirical method to measure stochasticity and multifractality in nonlinear time series
Lin, Chih-Hao; Chang, Chia-Seng; Li, Sai-Ping
2013-12-01
An empirical algorithm is used here to study the stochastic and multifractal nature of nonlinear time series. A parameter can be defined to quantitatively measure the deviation of the time series from a Wiener process so that the stochasticity of different time series can be compared. The local volatility of the time series under study can be constructed using this algorithm, and the multifractal structure of the time series can be analyzed by using this local volatility. As an example, we employ this method to analyze financial time series from different stock markets. The result shows that while developed markets evolve very much like an Ito process, the emergent markets are far from efficient. Differences about the multifractal structures and leverage effects between developed and emergent markets are discussed. The algorithm used here can be applied in a similar fashion to study time series of other complex systems.
Li, Jingchao; Cao, Yunpeng; Ying, Yulong; Li, Shuying
2016-01-01
Bearing failure is one of the dominant causes of failure and breakdowns in rotating machinery, leading to huge economic loss. Aiming at the nonstationary and nonlinear characteristics of bearing vibration signals as well as the complexity of condition-indicating information distribution in the signals, a novel rolling element bearing fault diagnosis method based on multifractal theory and gray relation theory was proposed in the paper. Firstly, a generalized multifractal dimension algorithm was developed to extract the characteristic vectors of fault features from the bearing vibration signals, which can offer more meaningful and distinguishing information reflecting different bearing health status in comparison with conventional single fractal dimension. After feature extraction by multifractal dimensions, an adaptive gray relation algorithm was applied to implement an automated bearing fault pattern recognition. The experimental results show that the proposed method can identify various bearing fault types as well as severities effectively and accurately.
Lethal and sublethal cellular injury in multifraction irradiation
International Nuclear Information System (INIS)
Withers, H.R.
1975-01-01
Work has been carried out on cellular injury in multifraction irradiation of mouse tissues and compared with similar work on human skin reported earlier by Dutreix et al (Eur. J. Cancer.; 9:159 (1973)). In agreement with Dutreix et al it is emphasized that the absolute amount of sublethal injury repaired per fractionation interval (Dsub(r)) is not as important to radiotherapists as the change in the amount repaired (ΔDsub(r)) when the dose-per-fraction is altered. It was found that although there is a critical divergence at low doses, the data for mouse tissues are similar to those previously given for human skin and support the conclusions: (i) That the capacity of many normal cells for accumulating and repairing sublethal radiation injury is probably not greatly different. (ii) That fixed exponents used for fraction number and time in iso-effect formulae are inaproporiate. At low doses-per-fraction, repair of sublethal injury is complete, or nearly so, and hence, additional fractionation of dose does not give appreciable additional sparing, whereas rapidly-regenerating tissues, due to the lengthening of overall time, would continue being spared by repopulation. (U.K.)
Characterizing Detrended Fluctuation Analysis of multifractional Brownian motion
Setty, V. A.; Sharma, A. S.
2015-02-01
The Hurst exponent (H) is widely used to quantify long range dependence in time series data and is estimated using several well known techniques. Recognizing its ability to remove trends the Detrended Fluctuation Analysis (DFA) is used extensively to estimate a Hurst exponent in non-stationary data. Multifractional Brownian motion (mBm) broadly encompasses a set of models of non-stationary data exhibiting time varying Hurst exponents, H(t) as against a constant H. Recently, there has been a growing interest in time dependence of H(t) and sliding window techniques have been used to estimate a local time average of the exponent. This brought to fore the ability of DFA to estimate scaling exponents in systems with time varying H(t) , such as mBm. This paper characterizes the performance of DFA on mBm data with linearly varying H(t) and further test the robustness of estimated time average with respect to data and technique related parameters. Our results serve as a bench-mark for using DFA as a sliding window estimator to obtain H(t) from time series data.
Multifractal analysis of implied volatility in index options
Oh, GabJin
2014-06-01
In this paper, we analyze the statistical and the non-linear properties of the log-variations in implied volatility for the CAC40, DAX and S& P500 daily index options. The price of an index option is generally represented by its implied volatility surface, including its smile and skew properties. We utilize a Lévy process model as the underlying asset to deepen our understanding of the intrinsic property of the implied volatility in the index options and estimate the implied volatility surface. We find that the options pricing models with the exponential Lévy model can reproduce the smile or sneer features of the implied volatility that are observed in real options markets. We study the variation in the implied volatility for at-the-money index call and put options, and we find that the distribution function follows a power-law distribution with an exponent of 3.5 ≤ γ ≤ 4.5. Especially, the variation in the implied volatility exhibits multifractal spectral characteristics, and the global financial crisis has influenced the complexity of the option markets.
Energy Management Optimization for Cellular Networks under Renewable Energy Generation Uncertainty
Rached, Nadhir B.
2017-03-28
The integration of renewable energy (RE) as an alternative power source for cellular networks has been deeply investigated in literature. However, RE generation is often assumed to be deterministic; an impractical assumption for realistic scenarios. In this paper, an efficient energy procurement strategy for cellular networks powered simultaneously by the smart grid (SG) and locally deployed RE sources characterized by uncertain processes is proposed. For a one-day operation cycle, the mobile operator aims to reduce its total energy cost by optimizing the amounts of energy to be procured from the local RE sources and SG at each time period. Additionally, it aims to determine the amount of extra generated RE to be sold back to SG. A chance constrained optimization is first proposed to deal with the RE generation uncertainty. Then, two convex approximation approaches: Chernoff and Chebyshev methods, characterized by different levels of knowledge about the RE generation, are developed to determine the energy procurement strategy for different risk levels. In addition, their performances are analyzed for various daily scenarios through selected simulation results. It is shown that the higher complex Chernoff method outperforms the Chebyshev one for different risk levels set by the operator.
A priori data-driven multi-clustered reservoir generation algorithm for echo state network.
Directory of Open Access Journals (Sweden)
Xiumin Li
Full Text Available Echo state networks (ESNs with multi-clustered reservoir topology perform better in reservoir computing and robustness than those with random reservoir topology. However, these ESNs have a complex reservoir topology, which leads to difficulties in reservoir generation. This study focuses on the reservoir generation problem when ESN is used in environments with sufficient priori data available. Accordingly, a priori data-driven multi-cluster reservoir generation algorithm is proposed. The priori data in the proposed algorithm are used to evaluate reservoirs by calculating the precision and standard deviation of ESNs. The reservoirs are produced using the clustering method; only the reservoir with a better evaluation performance takes the place of a previous one. The final reservoir is obtained when its evaluation score reaches the preset requirement. The prediction experiment results obtained using the Mackey-Glass chaotic time series show that the proposed reservoir generation algorithm provides ESNs with extra prediction precision and increases the structure complexity of the network. Further experiments also reveal the appropriate values of the number of clusters and time window size to obtain optimal performance. The information entropy of the reservoir reaches the maximum when ESN gains the greatest precision.
Energy Management Optimization for Cellular Networks under Renewable Energy Generation Uncertainty
Rached, Nadhir B.; Ghazzai, Hakim; Kadri, Abdullah; Alouini, Mohamed-Slim
2017-01-01
The integration of renewable energy (RE) as an alternative power source for cellular networks has been deeply investigated in literature. However, RE generation is often assumed to be deterministic; an impractical assumption for realistic scenarios. In this paper, an efficient energy procurement strategy for cellular networks powered simultaneously by the smart grid (SG) and locally deployed RE sources characterized by uncertain processes is proposed. For a one-day operation cycle, the mobile operator aims to reduce its total energy cost by optimizing the amounts of energy to be procured from the local RE sources and SG at each time period. Additionally, it aims to determine the amount of extra generated RE to be sold back to SG. A chance constrained optimization is first proposed to deal with the RE generation uncertainty. Then, two convex approximation approaches: Chernoff and Chebyshev methods, characterized by different levels of knowledge about the RE generation, are developed to determine the energy procurement strategy for different risk levels. In addition, their performances are analyzed for various daily scenarios through selected simulation results. It is shown that the higher complex Chernoff method outperforms the Chebyshev one for different risk levels set by the operator.
Imaging the where and when of tic generation and resting state networks in adult Tourette patients
Neuner, Irene; Werner, Cornelius J.; Arrubla, Jorge; Stöcker, Tony; Ehlen, Corinna; Wegener, Hans P.; Schneider, Frank; Shah, N. Jon
2014-01-01
Introduction: Tourette syndrome (TS) is a neuropsychiatric disorder with the core phenomenon of tics, whose origin and temporal pattern are unclear. We investigated the When and Where of tic generation and resting state networks (RSNs) via functional magnetic resonance imaging (fMRI). Methods: Tic-related activity and the underlying RSNs in adult TS were studied within one fMRI session. Participants were instructed to lie in the scanner and to let tics occur freely. Tic onset times, as determined by video-observance were used as regressors and added to preceding time-bins of 1 s duration each to detect prior activation. RSN were identified by independent component analysis (ICA) and correlated to disease severity by the means of dual regression. Results: Two seconds before a tic, the supplementary motor area (SMA), ventral primary motor cortex, primary sensorimotor cortex and parietal operculum exhibited activation; 1 s before a tic, the anterior cingulate, putamen, insula, amygdala, cerebellum and the extrastriatal-visual cortex exhibited activation; with tic-onset, the thalamus, central operculum, primary motor and somatosensory cortices exhibited activation. Analysis of resting state data resulted in 21 components including the so-called default-mode network. Network strength in those regions in SMA of two premotor ICA maps that were also active prior to tic occurrence, correlated significantly with disease severity according to the Yale Global Tic Severity Scale (YGTTS) scores. Discussion: We demonstrate that the temporal pattern of tic generation follows the cortico-striato-thalamo-cortical circuit, and that cortical structures precede subcortical activation. The analysis of spontaneous fluctuations highlights the role of cortical premotor structures. Our study corroborates the notion of TS as a network disorder in which abnormal RSN activity might contribute to the generation of tics in SMA. PMID:24904391
Impact of Distributed Generation Grid Code Requirements on Islanding Detection in LV Networks
Directory of Open Access Journals (Sweden)
Fabio Bignucolo
2017-01-01
Full Text Available The recent growing diffusion of dispersed generation in low voltage (LV distribution networks is entailing new rules to make local generators participate in network stability. Consequently, national and international grid codes, which define the connection rules for stability and safety of electrical power systems, have been updated requiring distributed generators and electrical storage systems to supply stabilizing contributions. In this scenario, specific attention to the uncontrolled islanding issue has to be addressed since currently required anti-islanding protection systems, based on relays locally measuring voltage and frequency, could no longer be suitable. In this paper, the effects on the interface protection performance of different LV generators’ stabilizing functions are analysed. The study takes into account existing requirements, such as the generators’ active power regulation (according to the measured frequency and reactive power regulation (depending on the local measured voltage. In addition, the paper focuses on other stabilizing features under discussion, derived from the medium voltage (MV distribution network grid codes or proposed in the literature, such as fast voltage support (FVS and inertia emulation. Stabilizing functions have been reproduced in the DIgSILENT PowerFactory 2016 software environment, making use of its native programming language. Later, they are tested both alone and together, aiming to obtain a comprehensive analysis on their impact on the anti-islanding protection effectiveness. Through dynamic simulations in several network scenarios the paper demonstrates the detrimental impact that such stabilizing regulations may have on loss-of-main protection effectiveness, leading to an increased risk of unintentional islanding.
Multifractal analysis of vertical profiles of soil penetration resistance at the field scale
Directory of Open Access Journals (Sweden)
G. M. Siqueira
2013-07-01
Full Text Available Soil penetration resistance (PR is widely used as an indirect indicator of soil strength. Soil PR is linked to basic soil properties and correlated to root growth and plant production, and as such it is extensively used as a practical tool for assessing soil compaction and to evaluate the effects of soil management. This study investigates how results from multifractal analysis can quantify key elements of depth-dependent soil PR profiles and how this information can be used at the field scale. We analysed multifractality of 50 PR vertical profiles, measured from 0 to 60 cm depth and randomly located on a 6.5 ha sugar cane field in northeastern Brazil. The scaling property of each profile was typified by singularity, and Rényi spectra estimated by the method of moments. The Hurst exponent was used to parameterize the autocorrelation of the vertical PR data sets. The singularity and Rènyi spectra showed that the vertical PR data sets exhibited a well-defined multifractal structure. Hurst exponent values were close to 1, ranging from 0.944 to 0.988, indicating strong persistence in PR variation with soil depth. Also, the Hurst exponent was negatively and significantly correlated to coefficient of variation (CV, skewness and maximum values of the depth-dependent PR. Multifractal analysis added valuable information to describe the spatial arrangement of depth-dependent penetrometer data sets, which was not taken into account by classical statistical indices. Multifractal parameters were mapped over the experimental field and compared with mean and maximum values of PR. Combination of spatial variability survey and multifractal analysis appear to be useful to manage soil compaction.
Multifractal analysis of vertical profiles of soil penetration resistance at the field scale
Siqueira, G. M.; Silva, E. F. F.; Montenegro, A. A. A.; Vidal Vázquez, E.; Paz-Ferreiro, J.
2013-07-01
Soil penetration resistance (PR) is widely used as an indirect indicator of soil strength. Soil PR is linked to basic soil properties and correlated to root growth and plant production, and as such it is extensively used as a practical tool for assessing soil compaction and to evaluate the effects of soil management. This study investigates how results from multifractal analysis can quantify key elements of depth-dependent soil PR profiles and how this information can be used at the field scale. We analysed multifractality of 50 PR vertical profiles, measured from 0 to 60 cm depth and randomly located on a 6.5 ha sugar cane field in northeastern Brazil. The scaling property of each profile was typified by singularity, and Rényi spectra estimated by the method of moments. The Hurst exponent was used to parameterize the autocorrelation of the vertical PR data sets. The singularity and Rènyi spectra showed that the vertical PR data sets exhibited a well-defined multifractal structure. Hurst exponent values were close to 1, ranging from 0.944 to 0.988, indicating strong persistence in PR variation with soil depth. Also, the Hurst exponent was negatively and significantly correlated to coefficient of variation (CV), skewness and maximum values of the depth-dependent PR. Multifractal analysis added valuable information to describe the spatial arrangement of depth-dependent penetrometer data sets, which was not taken into account by classical statistical indices. Multifractal parameters were mapped over the experimental field and compared with mean and maximum values of PR. Combination of spatial variability survey and multifractal analysis appear to be useful to manage soil compaction.
Tlelo-Cuautle, Esteban; de la Fraga, Luis Gerardo
2016-01-01
This book offers readers a clear guide to implementing engineering applications with FPGAs, from the mathematical description to the hardware synthesis, including discussion of VHDL programming and co-simulation issues. Coverage includes FPGA realizations such as: chaos generators that are described from their mathematical models; artificial neural networks (ANNs) to predict chaotic time series, for which a discussion of different ANN topologies is included, with different learning techniques and activation functions; random number generators (RNGs) that are realized using different chaos generators, and discussions of their maximum Lyapunov exponent values and entropies. Finally, optimized chaotic oscillators are synchronized and realized to implement a secure communication system that processes black and white and grey-scale images. In each application, readers will find VHDL programming guidelines and computer arithmetic issues, along with co-simulation examples with Active-HDL and Simulink. Readers will b...
Singularity spectra of fractional Brownian motions as a multi-fractal
International Nuclear Information System (INIS)
Kim, T.S.; Kim, S.
2004-01-01
Fractional Brownian motion acts as a random process with statistical self-similarity in time and self-affinity in shape. From these properties, the complicated patterns can be suitably represented by it with a minimal parameter and less memory. By considering its statistical property through the power spectrum density we can see that this process is not stationary, even though its differential motion is stationary. So in this paper, by taking the wavelet transform instead of Fourier transformation we investigate its multi-fractal spectrum as a multi-fractal model
To be and not to be: scale correlations in random multifractal processes
DEFF Research Database (Denmark)
Cleve, Jochen; Schmiegel, Jürgen; Greiner, Martin
We discuss various properties of a random multifractal process, which are related to the issue of scale correlations. By design, the process is homogeneous, non-conservative and has no built-in scale correlations. However, when it comes to observables like breakdown coefficients, which are based...... on a coarse-graining of the multifractal field, scale correlations do appear. In the log-normal limit of the model process, the conditional distributions and moments of breakdown coefficients reproduce the observations made in fully developed small-scale turbulence. These findings help to understand several...
An 8-GW long-pulse generator based on Tesla transformer and pulse forming network.
Su, Jiancang; Zhang, Xibo; Li, Rui; Zhao, Liang; Sun, Xu; Wang, Limin; Zeng, Bo; Cheng, Jie; Wang, Ying; Peng, Jianchang; Song, Xiaoxin
2014-06-01
A long-pulse generator TPG700L based on a Tesla transformer and a series pulse forming network (PFN) is constructed to generate intense electron beams for the purpose of high power microwave (HPM) generation. The TPG700L mainly consists of a 12-stage PFN, a built-in Tesla transformer in a pulse forming line, a three-electrode gas switch, a transmission line with a trigger, and a load. The Tesla transformer and the compact PFN are the key technologies for the development of the TPG700L. This generator can output electrical pulses with a width as long as 200 ns at a level of 8 GW and a repetition rate of 50 Hz. When used to drive a relative backward wave oscillator for HPM generation, the electrical pulse width is about 100 ns on a voltage level of 520 kV. Factors affecting the pulse waveform of the TPG700L are also discussed. At present, the TPG700L performs well for long-pulse HPM generation in our laboratory.
An 8-GW long-pulse generator based on Tesla transformer and pulse forming network
Energy Technology Data Exchange (ETDEWEB)
Su, Jiancang; Zhang, Xibo; Li, Rui; Zhao, Liang, E-mail: zhaoliang0526@163.com; Sun, Xu; Wang, Limin; Zeng, Bo; Cheng, Jie; Wang, Ying; Peng, Jianchang; Song, Xiaoxin [Science and Technology on High Power Microwave Laboratory, Northwest Institute of Nuclear Technology, Xi' an, Shaanxi 710024 (China)
2014-06-15
A long-pulse generator TPG700L based on a Tesla transformer and a series pulse forming network (PFN) is constructed to generate intense electron beams for the purpose of high power microwave (HPM) generation. The TPG700L mainly consists of a 12-stage PFN, a built-in Tesla transformer in a pulse forming line, a three-electrode gas switch, a transmission line with a trigger, and a load. The Tesla transformer and the compact PFN are the key technologies for the development of the TPG700L. This generator can output electrical pulses with a width as long as 200 ns at a level of 8 GW and a repetition rate of 50 Hz. When used to drive a relative backward wave oscillator for HPM generation, the electrical pulse width is about 100 ns on a voltage level of 520 kV. Factors affecting the pulse waveform of the TPG700L are also discussed. At present, the TPG700L performs well for long-pulse HPM generation in our laboratory.
Islam, Mujahidul
A sustainable energy delivery infrastructure implies the safe and reliable accommodation of large scale penetration of renewable sources in the power grid. In this dissertation it is assumed there will be no significant change in the power transmission and distribution structure currently in place; except in the operating strategy and regulatory policy. That is to say, with the same old structure, the path towards unveiling a high penetration of switching power converters in the power system will be challenging. Some of the dimensions of this challenge are power quality degradation, frequent false trips due to power system imbalance, and losses due to a large neutral current. The ultimate result is the reduced life of many power distribution components - transformers, switches and sophisticated loads. Numerous ancillary services are being developed and offered by the utility operators to mitigate these problems. These services will likely raise the system's operational cost, not only from the utility operators' end, but also reflected on the Independent System Operators and by the Regional Transmission Operators (RTO) due to an unforeseen backlash of frequent variation in the load-side generation or distributed generation. The North American transmission grid is an interconnected system similar to a large electrical circuit. This circuit was not planned but designed over 100 years. The natural laws of physics govern the power flow among loads and generators except where control mechanisms are installed. The control mechanism has not matured enough to withstand the high penetration of variable generators at uncontrolled distribution ends. Unlike a radial distribution system, mesh or loop networks can alleviate complex channels for real and reactive power flow. Significant variation in real power injection and absorption on the distribution side can emerge as a bias signal on the routing reactive power in some physical links or channels that are not distinguishable
Distributed generation of shared RSA keys in mobile ad hoc networks
Liu, Yi-Liang; Huang, Qin; Shen, Ying
2005-12-01
Mobile Ad Hoc Networks is a totally new concept in which mobile nodes are able to communicate together over wireless links in an independent manner, independent of fixed physical infrastructure and centralized administrative infrastructure. However, the nature of Ad Hoc Networks makes them very vulnerable to security threats. Generation and distribution of shared keys for CA (Certification Authority) is challenging for security solution based on distributed PKI(Public-Key Infrastructure)/CA. The solutions that have been proposed in the literature and some related issues are discussed in this paper. The solution of a distributed generation of shared threshold RSA keys for CA is proposed in the present paper. During the process of creating an RSA private key share, every CA node only has its own private security. Distributed arithmetic is used to create the CA's private share locally, and that the requirement of centralized management institution is eliminated. Based on fully considering the Mobile Ad Hoc network's characteristic of self-organization, it avoids the security hidden trouble that comes by holding an all private security share of CA, with which the security and robustness of system is enhanced.