Multifractal network generator.
Palla, Gergely; Lovász, László; Vicsek, Tamás
2010-04-27
We introduce a new approach to constructing networks with realistic features. Our method, in spite of its conceptual simplicity (it has only two parameters) is capable of generating a wide variety of network types with prescribed statistical properties, e.g., with degree or clustering coefficient distributions of various, very different forms. In turn, these graphs can be used to test hypotheses or as models of actual data. The method is based on a mapping between suitably chosen singular measures defined on the unit square and sparse infinite networks. Such a mapping has the great potential of allowing for graph theoretical results for a variety of network topologies. The main idea of our approach is to go to the infinite limit of the singular measure and the size of the corresponding graph simultaneously. A very unique feature of this construction is that with the increasing system size the generated graphs become topologically more structured. We present analytic expressions derived from the parameters of the--to be iterated--initial generating measure for such major characteristics of graphs as their degree, clustering coefficient, and assortativity coefficient distributions. The optimal parameters of the generating measure are determined from a simple simulated annealing process. Thus, the present work provides a tool for researchers from a variety of fields (such as biology, computer science, biology, or complex systems) enabling them to create a versatile model of their network data.
Multifractal analysis of complex networks
Institute of Scientific and Technical Information of China (English)
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 muttifractal analysis of complex networks.This algorithm is used to calculate the generalized fractal dimensions Dq 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 Dq due to changes in the parameters of the theoretical network models is also discussed.
Fractal and multifractal analyses of bipartite networks.
Liu, Jin-Long; Wang, Jian; Yu, Zu-Guo; Xie, Xian-Hua
2017-03-31
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.
Fractal and multifractal analyses of bipartite networks
Liu, Jin-Long; Wang, Jian; Yu, Zu-Guo; Xie, Xian-Hua
2017-01-01
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. PMID:28361962
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.
Multifractality and Network Analysis of Phase Transition
Li, Wei; Yang, Chunbin; Han, Jihui; Su, Zhu; Zou, Yijiang
2017-01-01
Many models and real complex systems possess critical thresholds at which the systems shift dramatically from one sate to another. The discovery of early-warnings in the vicinity of critical points are of great importance to estimate how far the systems are away from the critical states. Multifractal Detrended Fluctuation analysis (MF-DFA) and visibility graph method have been employed to investigate the multifractal and geometrical properties of the magnetization time series of the two-dimensional Ising model. Multifractality of the time series near the critical point has been uncovered from the generalized Hurst exponents and singularity spectrum. Both long-term correlation and broad probability density function are identified to be the sources of multifractality. Heterogeneous nature of the networks constructed from magnetization time series have validated the fractal properties. Evolution of the topological quantities of the visibility graph, along with the variation of multifractality, serve as new early-warnings of phase transition. Those methods and results may provide new insights about the analysis of phase transition problems and can be used as early-warnings for a variety of complex systems. PMID:28107414
A rainfall simulator based on multifractal generator
Akrour, Nawal; mallet, Cecile; barthes, Laurent; chazottes, Aymeric
2015-04-01
The Precipitations are due to complex meteorological phenomenon's and unlike other geophysical constituents such as water vapour concentration they present a relaxation behaviour leading to an alternation of dry and wet periods. Thus, precipitations can be described as intermittent process. The spatial and temporal variability of this phenomenon is significant and covers large scales. This high variability can cause extreme events which are difficult to observe properly because of their suddenness and their localized character. For all these reasons, the precipitations are therefore difficult to model. This study aims to adapt a one-dimensional time series model previously developed by the authors [Akrour et al., 2013, 2014] to a two-dimensional rainfall generator. The original time series model can be divided into 3 major steps : rain support generation, intra event rain rates generation using multifractal and finally calibration process. We use the same kind of methodology in the present study. Based on dataset obtained from meteorological radar of Météo France with a spatial resolution of 1 km x 1 km we present the used approach : Firstly, the extraction of rain support (rain/no rain area) allowing the retrieval of the rain support structure function (variogram) and fractal properties. This leads us to use either the rain support modelisation proposed by ScleissXXX [ref] or directly real rain support extracted from radar rain maps. Then, the generation (over rain areas) of rain rates is made thanks to a 2D multifractal Fractionnally Integrated Flux (FIF) model [ref]. This second stage is followed by a calibration/forcing step (forcing average rain rate per events) added in order to provide rain rate coherent with observed rain-rate distribution. The forcing process is based on a relation identified from the average rain rate of observed events and their surfaces. The presentation will first explain the different steps presented above, then some results
Multifractal to monofractal evolution of the London's street network
Murcio, Roberto; Arcaute, Elsa; Batty, Michael
2015-01-01
We perform a multifractal analysis of the evolution of London's street network from 1786 to 2010. First, we show that a single fractal dimension, commonly associated with the morphological description of cities, does not su ce to capture the dynamics of the system. Instead, for a proper characterization of such a dynamics, the multifractal spectrum needs to be considered. Our analysis reveals that London evolves from an inhomogeneous fractal structure, that can be described in terms of a multifractal, to a homogeneous one, that converges to monofractality. We argue that London's multifractal to monofracal evolution might be a special outcome of the constraint imposed on its growth by a green belt. Through a series of simulations, we show that multifractal objects, constructed through di usion limited aggregation, evolve towards monofractality if their growth is constrained by a non-permeable boundary.
Multifractal properties of the random resistor network
Barthelemy; Buldyrev; Havlin; Stanley
2000-04-01
We study the multifractal spectrum of the current in the two-dimensional random resistor network at the percolation threshold. We consider two ways of applying the voltage difference: (i) two parallel bars, and (ii) two points. Our numerical results suggest that in the infinite system limit, the probability distribution behaves for small i as P(i) approximately 1/i, where i is the current. As a consequence, the moments of i of order q
(Quantum) Fractional Brownian Motion and Multifractal Processes under the Loop of a Tensor Networks
Descamps, Benoît
2016-01-01
We derive fractional Brownian motion and stochastic processes with multifractal properties using a framework of network of Gaussian conditional probabilities. This leads to the derivation of new representations of fractional Brownian motion. These constructions are inspired from renormalization. The main result of this paper consists of constructing each increment of the process from two-dimensional gaussian noise inside the light-cone of each seperate increment. Not only does this allows us to derive fractional Brownian motion, we can introduce extensions with multifractal flavour. In another part of this paper, we discuss the use of the multi-scale entanglement renormalization ansatz (MERA), introduced in the study critical systems in quantum spin lattices, as a method for sampling integrals with respect to such multifractal processes. After proper calibration, a MERA promises the generation of a sample of size $N$ of a multifractal process in the order of $O(N\\log(N))$, an improvement over the known method...
Multifractal analysis and topological properties of a new family of weighted Koch networks
Huang, Da-Wen; Yu, Zu-Guo; Anh, Vo
2017-03-01
Weighted complex networks, especially scale-free networks, which characterize real-life systems better than non-weighted networks, have attracted considerable interest in recent years. Studies on the multifractality of weighted complex networks are still to be undertaken. In this paper, inspired by the concepts of Koch networks and Koch island, we propose a new family of weighted Koch networks, and investigate their multifractal behavior and topological properties. We find some key topological properties of the new networks: their vertex cumulative strength has a power-law distribution; there is a power-law relationship between their topological degree and weight strength; the networks have a high weighted clustering coefficient of 0.41004 (which is independent of the scaling factor c) in the limit of large generation t; the second smallest eigenvalue μ2 and the maximum eigenvalue μn are approximated by quartic polynomials of the scaling factor c for the general Laplacian operator, while μ2 is approximately a quartic polynomial of c and μn= 1.5 for the normalized Laplacian operator. Then, we find that weighted koch networks are both fractal and multifractal, their fractal dimension is influenced by the scaling factor c. We also apply these analyses to six real-world networks, and find that the multifractality in three of them are strong.
Multifractal analysis of weighted networks by a modified sandbox algorithm
Song, Yu-Qin; Liu, Jin-Long; Yu, Zu-Guo; Li, Bao-Gen
2015-12-01
Complex networks have attracted growing attention in many fields. As a generalization of fractal analysis, multifractal analysis (MFA) is a useful way to systematically describe the spatial heterogeneity of both theoretical and experimental fractal patterns. Some algorithms for MFA of unweighted complex networks have been proposed in the past a few years, including the sandbox (SB) algorithm recently employed by our group. In this paper, a modified SB algorithm (we call it SBw algorithm) is proposed for MFA of weighted networks. First, we use the SBw algorithm to study the multifractal property of two families of weighted fractal networks (WFNs): “Sierpinski” WFNs and “Cantor dust” WFNs. We also discuss how the fractal dimension and generalized fractal dimensions change with the edge-weights of the WFN. From the comparison between the theoretical and numerical fractal dimensions of these networks, we can find that the proposed SBw algorithm is efficient and feasible for MFA of weighted networks. Then, we apply the SBw algorithm to study multifractal properties of some real weighted networks — collaboration networks. It is found that the multifractality exists in these weighted networks, and is affected by their edge-weights.
Multifractal analysis of weighted networks by a modified sandbox algorithm
Song, Yu-Qin; Yu, Zu-Guo; Li, Bao-Gen
2015-01-01
Complex networks have attracted growing attention in many fields. As a generalization of fractal analysis, multifractal analysis (MFA) is a useful way to systematically describe the spatial heterogeneity of both theoretical and experimental fractal patterns. Some algorithms for MFA of unweighted complex networks have been proposed in the past a few years, including the sandbox (SB) algorithm recently employed by our group. In this paper, a modified SB algorithm (we call it SBw algorithm) is proposed for MFA of weighted networks.First, we use the SBw algorithm to study the multifractal property of two families of weighted fractal networks (WFNs): "Sierpinski" WFNs and "Cantor dust" WFNs. We also discuss how the fractal dimension and generalized fractal dimensions change with the edge-weights of the WFN. From the comparison between the theoretical and numerical fractal dimensions of these networks, we can find that the proposed SBw algorithm is efficient and feasible for MFA of weighted networks. Then, we apply...
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
Unveiling the Multi-fractal Structure of Complex Networks
Jalan, Sarika; Sarkar, Camellia; Boccaletti, Stefano
2016-01-01
The fractal nature of graphs has traditionally been investigated by using the nodes of networks as the basic units. Here, instead, we propose to concentrate on the graph edges, and introduce a practical and computationally not demanding method for revealing changes in the fractal behavior of networks, and particularly for allowing distinction between mono-fractal, quasi mono-fractal, and multi-fractal structures. We show that degree homogeneity plays a crucial role in determining the fractal nature of the underlying network, and report on six different protein-protein interaction networks along with their corresponding random networks. Our analysis allows to identify varying levels of complexity in the species.
On the multifractal effects generated by monofractal signals
Grech, Dariusz
2013-01-01
We study quantitatively the level of false multifractal signal one may encounter while analyzing multifractal phenomena in time series within multifractal detrended fluctuation analysis (MF-DFA). The investigated effect appears as a result of finite length of used data series and is additionally amplified by the long-term memory the data eventually may contain. We provide the detailed quantitative description of such apparent multifractal background signal as a threshold in spread of generalized Hurst exponent values $\\Delta h$ or a threshold in the width of multifractal spectrum $\\Delta \\alpha$ below which multifractal properties of the system are only apparent, i.e. do not exist, despite $\\Delta\\alpha\
Sandbox algorithm for multifractal analysis of complex networks
Liu, Jin-Long; Anh, Vo
2014-01-01
Complex networks have attracted much attention in diverse areas of science and technology. Multifractal analysis (MFA) is a useful way to systematically describe the spatial heterogeneity of both theoretical and experimental fractal patterns. In this paper, we introduce a new algorithm --- the sandbox (SB) algorithm, for MFA of complex networks. First we compare the SB algorithm with two existing algorithms of MFA for complex networks: the compact-box-burning (CBB) algorithm proposed by Furuya and Yakubo ( Phys. Rev. E, 84 (2011) 036118), and the improved box-counting (BC) algorithm proposed by Li et al. ( J. Stat. Mech.: Theor. Exp., 2014 (2014) P02020) by calculating the mass exponents tau(q) of some deterministic model networks. We make a detailed comparison between the numerical and theoretical results of these model networks. The comparison results show that the SB algorithm is the most effective and feasible algorithm to calculate the mass exponents tau(q) and to explore the multifractal behavior of com...
Scale-free networks emerging from multifractal time series
Budroni, Marcello A.; Baronchelli, Andrea; Pastor-Satorras, Romualdo
2017-05-01
Methods connecting dynamical systems and graph theory have attracted increasing interest in the past few years, with applications ranging from a detailed comparison of different kinds of dynamics to the characterization of empirical data. Here we investigate the effects of the (multi)fractal properties of a signal, common in time series arising from chaotic dynamics or strange attractors, on the topology of a suitably projected network. Relying on the box-counting formalism, we map boxes into the nodes of a network and establish analytic expressions connecting the natural measure of a box with its degree in the graph representation. We single out the conditions yielding to the emergence of a scale-free topology and validate our findings with extensive numerical simulations. We finally present a numerical analysis on the properties of weighted and directed network projections.
Scale-free networks emerging from multifractal time series.
Budroni, Marcello A; Baronchelli, Andrea; Pastor-Satorras, Romualdo
2017-05-01
Methods connecting dynamical systems and graph theory have attracted increasing interest in the past few years, with applications ranging from a detailed comparison of different kinds of dynamics to the characterization of empirical data. Here we investigate the effects of the (multi)fractal properties of a signal, common in time series arising from chaotic dynamics or strange attractors, on the topology of a suitably projected network. Relying on the box-counting formalism, we map boxes into the nodes of a network and establish analytic expressions connecting the natural measure of a box with its degree in the graph representation. We single out the conditions yielding to the emergence of a scale-free topology and validate our findings with extensive numerical simulations. We finally present a numerical analysis on the properties of weighted and directed network projections.
Stenull, O; Janssen, H K
2001-03-01
We study the multifractal moments of the current distribution in randomly diluted resistor networks near the percolation threshold. When an external current is applied between two terminals x and x(') of the network, the lth multifractal moment scales as M((l))(I)(x,x(')) approximately equal /x-x'/(psi(l)/nu), where nu is the correlation length exponent of the isotropic percolation universality class. By applying our concept of master operators [Europhys. Lett. 51, 539 (2000)] we calculate the family of multifractal exponents [psi(l)] for l>or=0 to two-loop order. We find that our result is in good agreement with numerical data for three dimensions.
Fractal and multifractal analysis of human retinal vascular network: a review
Directory of Open Access Journals (Sweden)
Ştefan Ţălu
2011-12-01
Full Text Available The objective of this paper is to present a synthesis concerning the results obtained in fractaland multifractal analysis of vascular network geometry of the human retina. The numerical results areuseful in mathematical models based on parametric representations, used in vitreo-retinal biomechanicalstudies. The fractal and multifractal analysis of retinal vascular network provides noninvasive powerfultools that allow physicians the early detection of patients with different retinal vascular diseases.
Determination of multifractal dimensions of complex networks by means of the sandbox algorithm
Liu, Jin-Long; Yu, Zu-Guo; Anh, Vo
2015-02-01
Complex networks have attracted much attention in diverse areas of science and technology. Multifractal analysis (MFA) is a useful way to systematically describe the spatial heterogeneity of both theoretical and experimental fractal patterns. In this paper, we employ the sandbox (SB) algorithm proposed by Tél et al. (Physica A 159, 155-166 (1989)), for MFA of complex networks. First, we compare the SB algorithm with two existing algorithms of MFA for complex networks: the compact-box-burning algorithm proposed by Furuya and Yakubo (Phys. Rev. E 84, 036118 (2011)), and the improved box-counting algorithm proposed by Li et al. (J. Stat. Mech.: Theor. Exp. 2014, P02020 (2014)) by calculating the mass exponents τ(q) of some deterministic model networks. We make a detailed comparison between the numerical and theoretical results of these model networks. The comparison results show that the SB algorithm is the most effective and feasible algorithm to calculate the mass exponents τ(q) and to explore the multifractal behavior of complex networks. Then, we apply the SB algorithm to study the multifractal property of some classic model networks, such as scale-free networks, small-world networks, and random networks. Our results show that multifractality exists in scale-free networks, that of small-world networks is not obvious, and it almost does not exist in random networks.
Analysis of normal human retinal vascular network architecture using multifractal geometry
Ţălu, Ştefan; Stach, Sebastian; Călugăru, Dan Mihai; Lupaşcu, Carmen Alina; Nicoară, Simona Delia
2017-01-01
AIM To apply the multifractal analysis method as a quantitative approach to a comprehensive description of the microvascular network architecture of the normal human retina. METHODS Fifty volunteers were enrolled in this study in the Ophthalmological Clinic of Cluj-Napoca, Romania, between January 2012 and January 2014. A set of 100 segmented and skeletonised human retinal images, corresponding to normal states of the retina were studied. An automatic unsupervised method for retinal vessel segmentation was applied before multifractal analysis. The multifractal analysis of digital retinal images was made with computer algorithms, applying the standard box-counting method. Statistical analyses were performed using the GraphPad InStat software. RESULTS The architecture of normal human retinal microvascular network was able to be described using the multifractal geometry. The average of generalized dimensions (Dq) for q=0, 1, 2, the width of the multifractal spectrum (Δα=αmax − αmin) and the spectrum arms' heights difference (|Δf|) of the normal images were expressed as mean±standard deviation (SD): for segmented versions, D0=1.7014±0.0057; D1=1.6507±0.0058; D2=1.5772±0.0059; Δα=0.92441±0.0085; |Δf|= 0.1453±0.0051; for skeletonised versions, D0=1.6303±0.0051; D1=1.6012±0.0059; D2=1.5531±0.0058; Δα=0.65032±0.0162; |Δf|= 0.0238±0.0161. The average of generalized dimensions (Dq) for q=0, 1, 2, the width of the multifractal spectrum (Δα) and the spectrum arms' heights difference (|Δf|) of the segmented versions was slightly greater than the skeletonised versions. CONCLUSION The multifractal analysis of fundus photographs may be used as a quantitative parameter for the evaluation of the complex three-dimensional structure of the retinal microvasculature as a potential marker for early detection of topological changes associated with retinal diseases. PMID:28393036
Multifractal modelling of runoffs of karstic springs
Márkus, L.
2003-04-01
A new multifractal stochastic process, Terdik and Iglói call the Limit of the Integrated Superposition of Diffusion processes with Linear differential Generator (LISDLG) , has been defined for modelling network traffic multifractality. The process is stationary, and exhibits long range dependency or long memory. Its characteristic property is that its bispectrum is real. It serves as the basis of distinction e.g. from the superposition of Levy-processes driven Ornstein-Uhlenbeck processes. Its further appealing property is that its finite dimensional distribution stems from multivariate Gamma, therefore it is inherently positive and skewed (and hence non-Gaussian). All together, this makes it a very promising candidate for modelling e.g. runoff data of springs or river flows. Quite recently Labat et al. (2002, J. of Hydrology, Vol 256, pp.176-195) pointed out multifractal properties of the runoff time series of French karstic springs. We show that runoff data of karstic springs in north-east Hungary possesses multifractal and cumulant-multifractal property as well as long range dependency and fit the above described LISDLG process, to model the phenomenon. Acknowledgement: This research was supported by the Nat. Sci. Research Fund OTKA, grant No.: T 032725.
Tokinaga, Shozo; Ikeda, Yoshikazu
In investments, it is not easy to identify traders'behavior from stock prices, and agent systems may help us. This paper deals with discriminant analyses of stock prices using multifractality of time series generated via multi-agent systems and interpolation based on Wavelet Transforms. We assume five types of agents where a part of agents prefer forecast equations or production rules. Then, it is shown that the time series of artificial stock price reveals as a multifractal time series whose features are defined by the Hausedorff dimension D(h). As a result, we see the relationship between the reliability (reproducibility) of multifractality and D(h) under sufficient number of time series data. However, generally we need sufficient samples to estimate D(h), then we use interpolations of multifractal times series based on the Wavelet Transform.
Salat, Hadrien; Arcaute, Elsa
2016-01-01
Various methods have been developed independently to study the multifractality of measures in many different contexts. Although they all convey the same intuitive idea of giving a "dimension" to sets where a quantity scales similarly within a space, they are not necessarily equivalent on a more rigorous level. This review article aims at unifying the multifractal methodology by presenting the multifractal theoretical framework and principal practical methods, namely the moment method, the histogram method, multifractal detrended fluctuation analysis (MDFA) and modulus maxima wavelet transform (MMWT), with a comparative and interpretative eye.
Directory of Open Access Journals (Sweden)
Ladislav Schwartz
2006-01-01
Full Text Available Two network types had been existing in Slovakia by the end of the year 2004 – public switched telephone network – PSTN and packet switched data network – DCN. The other network, known as the next generation network – NGN, has been put into operation since the beginning of the year 2005. The role of the next generation network is to merge the both previous network types into one unified complex network with the full centralised control, based on routing and packet switching. The T-Com company (previous Slovak Telecom was the first who did it.
Fractal and Multifractal Time Series
Kantelhardt, Jan W
2008-01-01
Data series generated by complex systems exhibit fluctuations on many time scales and/or broad distributions of the values. In both equilibrium and non-equilibrium situations, the natural fluctuations are often found to follow a scaling relation over several orders of magnitude, allowing for a characterisation of the data and the generating complex system by fractal (or multifractal) scaling exponents. In addition, fractal and multifractal approaches can be used for modelling time series and deriving predictions regarding extreme events. This review article describes and exemplifies several methods originating from Statistical Physics and Applied Mathematics, which have been used for fractal and multifractal time series analysis.
Decomposing Multifractal Crossovers
Nagy, Zoltan; Mukli, Peter; Herman, Peter; Eke, Andras
2017-01-01
Physiological processes—such as, the brain's resting-state electrical activity or hemodynamic fluctuations—exhibit scale-free temporal structuring. However, impacts common in biological systems such as, noise, multiple signal generators, or filtering by transport function, result in multimodal scaling that cannot be reliably assessed by standard analytical tools that assume unimodal scaling. Here, we present two methods to identify breakpoints or crossovers in multimodal multifractal scaling functions. These methods incorporate the robust iterative fitting approach of the focus-based multifractal formalism (FMF). The first approach (moment-wise scaling range adaptivity) allows for a breakpoint-based adaptive treatment that analyzes segregated scale-invariant ranges. The second method (scaling function decomposition method, SFD) is a crossover-based design aimed at decomposing signal constituents from multimodal scaling functions resulting from signal addition or co-sampling, such as, contamination by uncorrelated fractals. We demonstrated that these methods could handle multimodal, mono- or multifractal, and exact or empirical signals alike. Their precision was numerically characterized on ideal signals, and a robust performance was demonstrated on exemplary empirical signals capturing resting-state brain dynamics by near infrared spectroscopy (NIRS), electroencephalography (EEG), and blood oxygen level-dependent functional magnetic resonance imaging (fMRI-BOLD). The NIRS and fMRI-BOLD low-frequency fluctuations were dominated by a multifractal component over an underlying biologically relevant random noise, thus forming a bimodal signal. The crossover between the EEG signal components was found at the boundary between the δ and θ bands, suggesting an independent generator for the multifractal δ rhythm. The robust implementation of the SFD method should be regarded as essential in the seamless processing of large volumes of bimodal fMRI-BOLD imaging data for
Decomposing Multifractal Crossovers
Directory of Open Access Journals (Sweden)
Zoltan Nagy
2017-07-01
Full Text Available Physiological processes—such as, the brain's resting-state electrical activity or hemodynamic fluctuations—exhibit scale-free temporal structuring. However, impacts common in biological systems such as, noise, multiple signal generators, or filtering by transport function, result in multimodal scaling that cannot be reliably assessed by standard analytical tools that assume unimodal scaling. Here, we present two methods to identify breakpoints or crossovers in multimodal multifractal scaling functions. These methods incorporate the robust iterative fitting approach of the focus-based multifractal formalism (FMF. The first approach (moment-wise scaling range adaptivity allows for a breakpoint-based adaptive treatment that analyzes segregated scale-invariant ranges. The second method (scaling function decomposition method, SFD is a crossover-based design aimed at decomposing signal constituents from multimodal scaling functions resulting from signal addition or co-sampling, such as, contamination by uncorrelated fractals. We demonstrated that these methods could handle multimodal, mono- or multifractal, and exact or empirical signals alike. Their precision was numerically characterized on ideal signals, and a robust performance was demonstrated on exemplary empirical signals capturing resting-state brain dynamics by near infrared spectroscopy (NIRS, electroencephalography (EEG, and blood oxygen level-dependent functional magnetic resonance imaging (fMRI-BOLD. The NIRS and fMRI-BOLD low-frequency fluctuations were dominated by a multifractal component over an underlying biologically relevant random noise, thus forming a bimodal signal. The crossover between the EEG signal components was found at the boundary between the δ and θ bands, suggesting an independent generator for the multifractal δ rhythm. The robust implementation of the SFD method should be regarded as essential in the seamless processing of large volumes of bimodal f
Atwood, James
2014-01-01
The recent explosion in social network data has stimulated interest in probabilistic models of networks. Such models are appealing because they are empirically grounded; in contrast to more traditional network models, their parameters are estimated from data, and the models are evaluated on how well they represent the data. The exponential random graph model (ERGM, or, alternatively $p^*$) is currently the dominant framework for probabilistic network modeling. Despite their popularity, ERGMs suffer from a very serious flaw: near degeneracy. Briefly, an ERGM fit to a network or set of networks often ends up generating networks that look nothing at all like the training data. It is deeply troubling that the most likely model will generate instances that look nothing like data, and this calls the validity of models into question. In this work, we seek to address the general problem of learning to generate networks that do look like data. This is a large, challenging problem. To gain an understanding, we decompos...
Schertzer, Daniel; Tchiguirinskaia, Ioula
2017-04-01
Multifractal fields have opened a new approach in geophysics to explore "spatial chaos", i.e. processes that are not only complex in time but also in space, because their definition is rather independent of their domain dimension. However multifractals have been for too long restricted to be scalar valued, i.e. to have one-dimensional codomains. This has prevented to deal with the key question of complex component interactions of vector fields and their non trivial symmetries. On the theoretical level, this is resolved by considering the Lie algebra of stochastic generators of cascade processes with arbitrarily large codomains, e.g. flows of vector fields over large dimensional manifolds. We recently investigated the neat example of stable Levy generators on Clifford algebra that provide both universal statistical and robust algebraic properties to the basic symmetries of the corresponding fields (Schertzer and Tchiguirinskaia, 2015). This presentation will focus on the concrete analysis of observation data and their simulation in the Levy-Clifford algebra framework. This correspond to a wide and innovative generalisation of classical multifractal methodologies. Schertzer, D. & Tchiguirinskaia, I., 2015. Multifractal vector fields and stochastic Clifford algebra. Chaos: An Interdisciplinary Journal of Nonlinear Science, 25(12), p.123127.
Next Generation Social Networks
DEFF Research Database (Denmark)
Sørensen, Lene Tolstrup; Skouby, Knud Erik
2008-01-01
When it comes to discussing the future of electronic communication, social networking is the buzzword. The Internet has become a platform where new social networks emerge and the Internet it itself support the more traditional computer supported communication. The way users build and verifies...... 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...
Multifractal Analysis of Polyalanines Time Series
Figueirêdo, P H; Moret, M A; Coutinho, Sérgio; 10.1016/j.physa.2009.11.045
2010-01-01
Multifractal properties of the energy time series of short $\\alpha$-helix structures, specifically from a polyalanine family, are investigated through the MF-DFA technique ({\\it{multifractal detrended fluctuation analysis}}). Estimates for the generalized Hurst exponent $h(q)$ and its associated multifractal exponents $\\tau(q)$ are obtained for several series generated by numerical simulations of molecular dynamics in different systems from distinct initial conformations. All simulations were performed using the GROMOS force field, implemented in the program THOR. The main results have shown that all series exhibit multifractal behavior depending on the number of residues and temperature. Moreover, the multifractal spectra reveal important aspects on the time evolution of the system and suggest that the nucleation process of the secondary structures during the visits on the energy hyper-surface is an essential feature of the folding process.
Multifractal analysis and simulation of multifractal random walks
Schmitt, Francois G.; Huang, Yongxiang
2016-04-01
Multifractal time series, characterized by a scale invariance and large fluctuations at all scales, are found in many fields of natural and applied sciences. They are found i.e. in many geophysical fields, such as atmospheric and oceanic turbulence, hydrology, earth sciences. Here we consider a quite general type of multifractal time series, called multifractal random walk, as non stationary stochastic processes with intermittent stationary increments. We first quickly recall how such time series can be analyzed and characterized, using structure functions and arbitrary order Hilbert spectral analysis. We then discuss the simulation approach. The main object is to provide a stochastic process generating time series having the same multiscale properties We review recent works on this topic, and provide stochastic simulations in order to verify the theoretical predictions. In the lognormal framework we provide a h - μ plane expressing the scale invariant properties of these simulations. The theoretical plane is compared to simulation results.
Energy Technology Data Exchange (ETDEWEB)
Meson, Alejandro M., E-mail: meson@iflysib.unlp.edu.ar; Vericat, Fernando, E-mail: vericat@iflysib.unlp.edu.ar [CONICET-UNLP, Instituto de Fisica de Liquidos y Sistemas Biologicos (IFLYSIB) (Argentina)
2011-12-15
We analyze when a multifractal spectrum can be used to recover the potential. This phenomenon is known as multifractal rigidity. We prove that for a certain class of potentials the multifractal spectrum of local entropies uniquely determines their equilibrium states. This leads to a classification which identifies two systems up to a change of variables.
Gutfraind, Alexander; Safro, Ilya
2012-01-01
Networks are widely used in science and technology to represent relationships between entities, such as social or ecological links between organisms, enzymatic interactions in metabolic systems, or computer infrastructure. Statistical analyses of networks can provide critical insights into the structure, function, dynamics, and evolution of those systems. However, the structures of real-world networks are often not known completely, and they may exhibit considerable variation so that no single network is sufficiently representative of a system. In such situations, researchers may turn to proxy data from related systems, sophisticated methods for network inference, or synthetic networks. Here, we introduce a flexible method for synthesizing realistic ensembles of networks starting from a known network, through a series of mappings that coarsen and later refine the network structure by randomized editing. The method, MUSKETEER, preserves structural properties with minimal bias, including unknown or unspecified ...
MULTIFRACTAL STRUCTURE AND PRODUCT OF MATRICES
Institute of Scientific and Technical Information of China (English)
Lau Ka-sing
2003-01-01
There is a well established multifractal theory for self-similar measures generated by non-overlapping contractive similutudes.Our report here concerns those with overlaps.In particular we restrict our attention to the important classes of self-similar measures that have matrix representations.The dimension spectra and the Lq-spectra are analyzed through the product of matrices.There are abnormal behaviors on the multifrac-tal structure and they will be discussed in detail.
New Suns in the Cosmos III: multifractal signature analysis
de Freitas, D B; Junior, P R V de Moraes; Lopes, C E F; Leão, I C; Chagas, M L Das; Bravo, J P; Costa, A D; Martins, B L Canto; De Medeiros, J R
2016-01-01
In present paper, we investigate the multifractality signatures in hourly time series extracted from 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 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 rotation period of stars is inherently scaled by degree of multifractality. As a result, analyzing the multifractal degree of referred series, we uncover an evolution of mul...
Algorithms for Next Generation Networks
Cormode, Graham
2010-01-01
Data networking now plays a major role in everyday life and new applications continue to appear at a blinding pace. Yet we still do not have a sound foundation for designing, evaluating and managing these networks. This book covers topics at the intersection of algorithms and networking. It builds a complete picture of the current state of research on Next Generation Networks and the challenges for the years ahead. Particular focus is given to evolving research initiatives and the architecture they propose and implications for networking. Topics: Network design and provisioning, hardware issue
Generalized binomial multiplicative cascade processes and asymmetrical multifractal distributions
Cheng, Q.
2014-04-01
The concepts and models of multifractals have been employed in various fields in the geosciences to characterize singular fields caused by nonlinear geoprocesses. Several indices involved in multifractal models, i.e., asymmetry, multifractality, and range of singularity, are commonly used to characterize nonlinear properties of multifractal fields. An understanding of how these indices are related to the processes involved in the generation of multifractal fields is essential for multifractal modeling. In this paper, a five-parameter binomial multiplicative cascade model is proposed based on the anisotropic partition processes. Each partition divides the unit set (1-D length or 2-D area) into h equal subsets (segments or subareas) and m1 of them receive d1 (> 0) and m2 receive d2 (> 0) proportion of the mass in the previous subset, respectively, where m1+m2 ≤ h. The model is demonstrated via several examples published in the literature with asymmetrical fractal dimension spectra. This model demonstrates the various properties of asymmetrical multifractal distributions and multifractal indices with explicit functions, thus providing insight into and an understanding of the properties of asymmetrical binomial multifractal distributions.
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...
Regularities of Multifractal Measures
Indian Academy of Sciences (India)
Hun Ki Baek
2008-05-01
First, we prove the decomposition theorem for the regularities of multifractal Hausdorff measure and packing measure in $\\mathbb{R}^d$. 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 give some properties related to multifractal Hausdorff and packing densities. Finally, we extend the density theorem in [6] to any measurable set.
Multifractal approach for seafloor characterization
Digital Repository Service at National Institute of Oceanography (India)
Chakraborty, B.; Haris, K.; Latha, G.; Maslov, N.; Menezes, A.A.A.
to characterize the seafloor. Two distinct multifractal formalisms are applied to determine the characteristics. The first formalism employs data analyses using generalized dimension D(q) and multifractal singularity spectrum f(alpha) linked shape parameters...
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 (-∞ 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 prove useful to researchers who want to explore the correlative influence of texture on, for instance, flow and transport parameters. The advantage of using lacunarity instead of D2 in this context is that it can
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...
Next-generation photonic networks
Katagiri, Yoshitada
2002-10-01
Novel network architecture and key device technology are described for next-generation photonic networks enabling high-performance data communications. To accomplish full-mesh links for efficient data transportaion, time-shared wavelength-division multiplexing is the most promising under the limitation imposed on the total wavelength number available at network nodes. Optical add/drop multipelxing (OADM) using wavelngth-tunable devices is essential for temporal data link fomraiotn. Wavelength managemetn based on absolute wavelength calibraiotn is a key to OADM operations. A simple wavelength dscriminating device using a disk-shaped tunable optical bandpass filter under the synchro-scanned operation is useful for managing the laser wavelengths. High-speed data transmissions of greater than 40 Gbps necessary for efficient operation of the networks are also described. A key is photonic downconversion which enables phase deteciton for optical data streams at above the electrical limitation of around 50 GHz. This technique is applied not only to a phase-locked loop for synchronizing mode-locked pulses to an electrical signal in the much lower frequency range of around 10 GHz, but to timing extraction from 100-Gbps data streams.
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.
Nonlinear extensions of a fractal-multifractal approach for environmental modeling
Energy Technology Data Exchange (ETDEWEB)
Cortis, A.; Puente, C.E.; Sivakumar, B.
2008-10-15
We present the extension of a deterministic fractal geometric procedure aimed at representing the complexity of the spatio-temporal patterns encountered in environmental applications. The original procedure, which is based on transformations of multifractal distributions via fractal functions, is extended through the introduction of nonlinear perturbations to the underlying iterated linear maps. We demonstrate how the nonlinear perturbations generate yet a richer collection of patterns by means of various simulations that include evolutions of patterns based on changes in their parameters and in their statistical and multifractal properties. It is shown that the nonlinear extensions yield structures that closely resemble complex hydrologic temporal data sets, such as rainfall and runoff time series, and width-functions of river networks as a function of distance from the basin outlet. The implications of this nonlinear approach for environmental modeling and prediction are discussed.
Multifractal Detrended Fluctuation Analysis of Interevent Time Series in a Modified OFC Model
Institute of Scientific and Technical Information of China (English)
LIN Min; YAN Shuang-Xi; ZHAO Gang; WANG Gang
2013-01-01
We use multifractal detrended fluctuation analysis (MF-DFA) method to investigate the multifractal behavior of the interevent time series in a modified Olami-Feder-Christensen (OFC) earthquake model on assortative scale-free networks.We determine generalized Hurst exponent and singularity spectrum and find that these fluctuations have multifractal nature.Comparing the MF-DFA results for the original interevent time series with those for shuffled and surrogate series,we conclude that the origin of multifractality is due to both the broadness of probability density function and long-range correlation.
Dynamically multilayered visual system of the multifractal fly.
Baptista, M S; Grebogi, Celso; Köberle, Roland
2006-10-27
We dynamically analyze our experimental results on the motion sensitive spiking H1 neuron of the fly's visual system. We find that the fly uses an alphabet composed of a few letters to encode the information contained in the stimulus. The alphabet dynamics is multifractal both with and without stimulus, though the multifractality increases with the stimulus entropy. This is in sharp contrast to models generating independent spike intervals, whose dynamics is monofractal.
Selection of Multifractal Scaling Breaks and Separation of Geochemical and Geophysical Anomaly
Institute of Scientific and Technical Information of China (English)
无
2001-01-01
Spatially superimposed multiple processes such as multiplicative cascade processes often generate multifractal measures possessing so-called self-similarity or self-affinity that can be described by power-law type of functions within certain scale ranges. The multifractalities can be estimated by applying multifractal modeling to the measures reflecting the characteristics of the physical processes such as the element concentration values analyzed in rock and soil samples and caused by the underlying mineralization processes and the other geological processes. The local and regional geological processes may result in geochemical patterns with distinct multifractalities as well as variable scaling ranges. Separation of these multifractal measures on the basis of both the distinct multifractalities and the scaling ranges will be significant for both theoretical studies of multifractal modeling and its applications. Multifractal scaling breaks have been observed from various multifractal patterns. This paper introduces a technique for separating multifractal measures on the basis of scaling breaks. It has been demonstrated that the method is effective for decomposing geochemical and geophysical anomalies required for mineral exploration. A dataset containing the element concentration values of potassium and phosphorus in soil samples was employed for demonstrating the application of the method for studying the fertilizer and yield optimization in agriculture.
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.
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.
Stochastic Generator of Chemical Structure. 3. Reaction Network Generation
Energy Technology Data Exchange (ETDEWEB)
FAULON,JEAN-LOUP; SAULT,ALLEN G.
2000-07-15
A new method to generate chemical reaction network is proposed. The particularity of the method is that network generation and mechanism reduction are performed simultaneously using sampling techniques. Our method is tested for hydrocarbon thermal cracking. Results and theoretical arguments demonstrate that our method scales in polynomial time while other deterministic network generator scale in exponential time. This finding offers the possibility to investigate complex reacting systems such as those studied in petroleum refining and combustion.
Multiscale multifractal time irreversibility analysis of stock markets
Jiang, Chenguang; Shang, Pengjian; Shi, Wenbin
2016-11-01
Time irreversibility is one of the most important properties of nonstationary time series. Complex time series often demonstrate even multiscale time irreversibility, such that not only the original but also coarse-grained time series are asymmetric over a wide range of scales. We study the multiscale time irreversibility of time series. In this paper, we develop a method called multiscale multifractal time irreversibility analysis (MMRA), which allows us to extend the description of time irreversibility to include the dependence on the segment size and statistical moments. We test the effectiveness of MMRA in detecting multifractality and time irreversibility of time series generated from delayed Henon map and binomial multifractal model. Then we employ our method to the time irreversibility analysis of stock markets in different regions. We find that the emerging market has higher multifractality degree and time irreversibility compared with developed markets. In this sense, the MMRA method may provide new angles in assessing the evolution stage of stock markets.
PLANNING AND MANAGING VIRTUALIZED NEXT GENERATION NETWORKS
Directory of Open Access Journals (Sweden)
Sukant K. Mohapatra
2015-11-01
Full Text Available Service convergence, content digitization, rapid and flexible service delivery, reduction of capital and operating costs, economies of scale, changes in telecom policy and regulation, and ever increasing competition have been key factors in the evolution of virtualized Next Generation Networks (vNGN. IPcentric converged networks aim to provide a multitude of services over a single network infrastructure. Tremendous success and benefit of server virtualization in data centers is driving the adaption of network virtualization. Network virtualization is applicable to enterprise data center, and enterprise as well as wide area networks. The focus of this paper is network virtualization aspects of service providers’ next generation network. The key factors for moving to virtualized network is optimal use and sharing of network infrastructure even among competitive service providers, programmability of network and rapid introduction of new service and standard based on open platform rather than proprietary implementation. Evolving Software Defined Network (SDN and Network Function Virtualization (NFV shall enable common network infrastructure sharing, control, and management at a higher layer thus making network devices more generic and less intelligent, thus enabling cost competitiveness and quick service delivery. Network virtualization shall enable key benefits such as lower cost, flexibility, efficiency, and security, However, the deployment of virtualized next generation networks has brought its unique challenges for network managers and planners, as the network has to be planned in a comprehensive way with effective management of virtual network elements, its correlation with physical infrastructure and monitoring of control functions and server platforms. This paper discusses generic next generation network, its virtualization, and addresses the challenges related to the planning and managing of virtualized next generation networks. This
Pervasive Services for Next Generation Heterogeneous Networks
Aguiar, Rui; Bijwaard, Dennis; Farschian, Bakak A.; Jonas, Amardeo; Sarma, Amardeo
2006-01-01
The overall goal of the European collaborative project Daidalos is to design, develop and validate a framework for next generation mobility-enabled networks. Envisioned scenarios include heterogeneous access networks, while requiring ubiquitous, services of adequate quality, broadcast integration, a
Multifractal and lacunarity analysis of microvascular morphology and remodeling.
Gould, Daniel J; Vadakkan, Tegy J; Poché, Ross A; Dickinson, Mary E
2011-02-01
Classical measures of vessel morphology, including diameter and density, are employed to study microvasculature in endothelial membrane labeled mice. These measurements prove sufficient for some studies; however, they are less well suited for quantifying changes in microcirculatory networks lacking hierarchical structure. We demonstrate that automated multifractal analysis and lacunarity may be used with classical methods to quantify microvascular morphology. Using multifractal analysis and lacunarity, we present an automated extraction tool with a processing pipeline to characterize 2D representations of 3D microvasculature. We apply our analysis on four tissues and the hyaloid vasculature during remodeling. We found that the vessel networks analyzed have multifractal geometries and that kidney microvasculature has the largest fractal dimension and the lowest lacunarity compared to microvasculature networks in the cortex, skin, and thigh muscle. Also, we found that, during hyaloid remodeling, there were differences in multifractal spectra reflecting the functional transition from a space filling vasculature which nurtures the lens to a less dense vasculature as it regresses, permitting unobstructed vision. Multifractal analysis and lacunarity are valuable additions to classical measures of vascular morphology and will have utility in future studies of normal, developing, and pathological tissues. © 2011 John Wiley & Sons Ltd.
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.
Computational approach to multifractal music
Oświęcimka, Paweł; Celińska, Iwona; Drożdż, Stanisław; Rak, Rafał
2011-01-01
In this work we perform a fractal analysis of 160 pieces of music belonging to six different genres. We show that the majority of the pieces reveal characteristics that allow us to classify them as physical processes called the 1/f (pink) noise. However, this is not true for classical music represented here by Frederic Chopin's works and for some jazz pieces that are much more correlated than the pink noise. We also perform a multifractal (MFDFA) analysis of these music pieces. We show that all the pieces reveal multifractal properties. The richest multifractal structures are observed for pop and rock music. Also the viariably of multifractal features is best visible for popular music genres. This can suggest that, from the multifractal perspective, classical and jazz music is much more uniform than pieces of the most popular genres of music.
Gaussian Networks Generated by Random Walks
Javarone, Marco Alberto
2014-01-01
We propose a random walks based model to generate complex networks. Many authors studied and developed different methods and tools to analyze complex networks by random walk processes. Just to cite a few, random walks have been adopted to perform community detection, exploration tasks and to study temporal networks. Moreover, they have been used also to generate scale-free networks. In this work, we define a random walker that plays the role of "edges-generator". In particular, the random walker generates new connections and uses these ones to visit each node of a network. As result, the proposed model allows to achieve networks provided with a Gaussian degree distribution, and moreover, some features as the clustering coefficient and the assortativity show a critical behavior. Finally, we performed numerical simulations to study the behavior and the properties of the cited model.
Next generation network management technology
Baras, John S.; Atallah, George C.; Ball, Mike; Goli, Shravan; Karne, Ramesh K.; Kelley, Steve; Kumar, Harsha; Plaisant, Catherine; Roussopoulos, Nick; Schneiderman, Ben; Srinivasarao, Mulugu; Stathatos, Kosta; Teittinen, Marko; Whitefield, David
1995-01-01
Today's telecommunications networks are becoming increasingly large, complex, mission critical and heterogeneous in several dimensions. For example, the underlying physical transmission facilities of a given network may be ``mixed media'' (copper, fiber-optic, radio, and satellite); the subnetworks may be acquired from different vendors due to economic, performance, or general availability reasons; the information being transmitted over the network may be ``multimedia'' (video, data, voice, and images) and, finally, varying performance criteria may be imposed e.g., data transfer may require high throughput while the others, whose concern is voice communications, may require low call blocking probability. For these reasons, future telecommunications networks are expected to be highly complex in their services and operations. Due to this growing complexity and the disparity among management systems for individual sub-networks, efficient network management systems have become critical to the current and future success of telecommunications companies. This paper addresses a research and development effort which focuses on prototyping configuration management, since that is the central process of network management and all other network management functions must be built upon it. Our prototype incorporates ergonomically designed graphical user interfaces tailored to the network configuration management subsystem and to the proposed advanced object-oriented database structure. The resulting design concept follows open standards such as Open Systems Interconnection (OSI) and incorporates object oriented programming methodology to associate data with functions, permit customization, and provide an open architecture environment.
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....
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....
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.
Next Generation Reliable Transport Networks
DEFF Research Database (Denmark)
Zhang, Jiang
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......This thesis focuses the efforts on ensuring the reliability of transport networks and takes advantages and experiences from the transport networks into the networks for particular purposes. Firstly, the challenges of providing reliable multicast services on Multipath Label Switching......-Transport Profile (MPLS-TP) ring networks are addressed. Through the proposed protection structure and protection switching schemes, the recovery mechanism is enhanced in terms of recovery label consumption, operation simplicity and fine traffic engineering granularity. Furthermore, the extensions for existing...
Multifractal characterization of gold market: A multifractal detrended fluctuation analysis
Mali, Provash; Mukhopadhyay, Amitabha
2014-11-01
The multifractal detrended fluctuation analysis technique is employed to analyze the time series of gold consumer price index (CPI) and the market trend of three world’s highest gold consuming countries, namely China, India and Turkey for the period: 1993-July 2013. Various multifractal variables, such as the generalized Hurst exponent, the multifractal exponent and the singularity spectrum, are calculated and the results are fitted to the generalized binomial multifractal (GBM) series that consists of only two parameters. Special emphasis is given to identify the possible source(s) of multifractality in these series. Our analysis shows that the CPI series and all three market series are of multifractal nature. The origin of multifractality for the CPI time series and Indian market series is found due to a long-range time correlation, whereas it is mostly due to the fat-tailed probability distributions of the values for the Chinese and Turkey markets. The GBM model series more or less describes all the time series analyzed here.
Xi, Caiping; Zhang, Shunning; Xiong, Gang; Zhao, Huichang
2016-07-01
Multifractal detrended fluctuation analysis (MFDFA) and multifractal detrended moving average (MFDMA) algorithm have been established as two important methods to estimate the multifractal spectrum of the one-dimensional random fractal signal. They have been generalized to deal with two-dimensional and higher-dimensional fractal signals. This paper gives a brief introduction of the two-dimensional multifractal detrended fluctuation analysis (2D-MFDFA) and two-dimensional multifractal detrended moving average (2D-MFDMA) algorithm, and a detailed description of the application of the two-dimensional fractal signal processing by using the two methods. By applying the 2D-MFDFA and 2D-MFDMA to the series generated from the two-dimensional multiplicative cascading process, we systematically do the comparative analysis to get the advantages, disadvantages and the applicabilities of the two algorithms for the first time from six aspects such as the similarities and differences of the algorithm models, the statistical accuracy, the sensitivities of the sample size, the selection of scaling range, the choice of the q-orders and the calculation amount. The results provide a valuable reference on how to choose the algorithm from 2D-MFDFA and 2D-MFDMA, and how to make the schemes of the parameter settings of the two algorithms when dealing with specific signals in practical applications.
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 ...... concept in along these lines is the “Network Cell”....
Multifractal Value at Risk model
Lee, Hojin; Song, Jae Wook; Chang, Woojin
2016-06-01
In this paper new Value at Risk (VaR) model is proposed and investigated. We consider the multifractal property of financial time series and develop a multifractal Value at Risk (MFVaR). MFVaR introduced in this paper is analytically tractable and not based on simulation. Empirical study showed that MFVaR can provide the more stable and accurate forecasting performance in volatile financial markets where large loss can be incurred. This implies that our multifractal VaR works well for the risk measurement of extreme credit events.
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
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...
Convergence and Next Generation Networks
Sen, Jaydip; Hooli, Basavaraj
2010-01-01
The communications sector is undergoing significant changes, with the emergence of a number of platforms available to provide a different range of services. Some of these platforms are complementary to each other, while others are competitive, or can provide a valid substitute for some of the services provided. Up till now, the most important communications platform in most of the developing countries has been the public switched telecommunication network (PSTN) which provides access to all households and buildings. This universality in providing access has also meant that the network has generally been designated as one for universal service.This chapter focuses on the area where the most significant changes are taking place in the communication sector. The objective of this chapter is neither to give an overview of all communication platforms, nor is it aimed to assess the relative extent to which different platforms complement or compete with each other. The central theme of this chapter is to examine the ...
Entropy Function for Multifractal Thermodynamics
Institute of Scientific and Technical Information of China (English)
QiuhuaZENG
1999-01-01
The theory on multifractal thermodynamics has been studied by the method of series expansion.The method is able to overcome the shortages of Kohmoto's steepest desent method and the results have general meanings.
Multifractality and heart rate variability
Sassi, Roberto; Signorini, Maria Gabriella; Cerutti, Sergio
2009-06-01
In this paper, we participate to the discussion set forth by the editor of Chaos for the controversy, "Is the normal heart rate chaotic?" Our objective was to debate the question, "Is there some more appropriate term to characterize the heart rate variability (HRV) fluctuations?" We focused on the ≈24 h RR series prepared for this topic and tried to verify with two different techniques, generalized structure functions and wavelet transform modulus maxima, if they might be described as being multifractal. For normal and congestive heart failure subjects, the hq exponents showed to be decreasing for increasing q with both methods, as it should be for multifractal signals. We then built 40 surrogate series to further verify such hypothesis. For most of the series (≈75%-80% of cases) multifractality stood the test of the surrogate data employed. On the other hand, series coming from patients in atrial fibrillation showed a small, if any, degree of multifractality. The population analyzed is too small for definite conclusions, but the study supports the use of multifractal series to model HRV. Also it suggests that the regulatory action of autonomous nervous system might play a role in the observed multifractality.
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
Yang, Liansheng; Zhu, Yingming; Wang, Yudong
2016-06-01
In this paper, we investigate the impacts of oil price changes on energy stocks in Chinese stock market from the multifractal perspective. The well-known multifractal detrended fluctuation analysis (MF-DFA) is applied to detect the multifractality. We find that both returns and volatilities of energy industry index display apparent multifractal behavior. Oil market activity is an important source of multifractality in energy stocks index in addition to long-range correlations and fat-tail distributions.
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.
Multifractal modelling and 3D lacunarity analysis
Hanen, Akkari; Imen, Bhouri; Asma, Ben Abdallah; Patrick, Dubois; Hédi, Bedoui Mohamed
2009-09-01
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.
Weyl and Riemann-Liouville multifractional Ornstein-Uhlenbeck processes
Energy Technology Data Exchange (ETDEWEB)
Lim, S C [Faculty of Engineering, Multimedia University, Jalan Multimedia, Cyberjaya 63100, Selangor Darul Ehsan (Malaysia); Teo, L P [Faculty of Information Technology, Multimedia University, Jalan Multimedia, Cyberjaya, 63100, Selangor Darul Ehsan (Malaysia)
2007-06-08
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.
Symbolic regression of generative network models
Menezes, Telmo
2014-01-01
Networks are a powerful abstraction with applicability to a variety of scientific fields. Models explaining their morphology and growth processes permit a wide range of phenomena to be more systematically analysed and understood. At the same time, creating such models is often challenging and requires insights that may be counter-intuitive. Yet there currently exists no general method to arrive at better models. We have developed an approach to automatically detect realistic decentralised network growth models from empirical data, employing a machine learning technique inspired by natural selection and defining a unified formalism to describe such models as computer programs. As the proposed method is completely general and does not assume any pre-existing models, it can be applied "out of the box" to any given network. To validate our approach empirically, we systematically rediscover pre-defined growth laws underlying several canonical network generation models and credible laws for diverse real-world netwo...
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.
Understanding the multifractality in portfolio excess returns
Chen, Cheng; Wang, Yudong
2017-01-01
The multifractality in stock returns have been investigated extensively. However, whether the autocorrelations in portfolio returns are multifractal have not been considered in the literature. In this paper, we detect multifractal behavior of returns of portfolios constructed based on two popular trading rules, size and book-to-market (BM) ratio. Using the multifractal detrended fluctuation analysis, we find that the portfolio returns are significantly multifractal and the multifractality is mainly attributed to long-range dependence. We also investigate the multifractal cross-correlation between portfolio return and market average return using the detrended cross-correlation analysis. Our results show that the cross-correlations of small fluctuations are persistent, while those of large fluctuations are anti-persistent.
Automatic Metadata Generation using Associative Networks
Rodriguez, Marko A; Van de Sompel, Herbert
2008-01-01
In spite of its tremendous value, metadata is generally sparse and incomplete, thereby hampering the effectiveness of digital information services. Many of the existing mechanisms for the automated creation of metadata rely primarily on content analysis which can be costly and inefficient. The automatic metadata generation system proposed in this article leverages resource relationships generated from existing metadata as a medium for propagation from metadata-rich to metadata-poor resources. Because of its independence from content analysis, it can be applied to a wide variety of resource media types and is shown to be computationally inexpensive. The proposed method operates through two distinct phases. Occurrence and co-occurrence algorithms first generate an associative network of repository resources leveraging existing repository metadata. Second, using the associative network as a substrate, metadata associated with metadata-rich resources is propagated to metadata-poor resources by means of a discrete...
Network Generation Model Based on Evolution Dynamics To Generate Benchmark Graphs
Pasta, Muhammad Qasim
2016-01-01
Network generation models provide an understanding of the dynamics behind the formation and evolution of different networks including social networks, technological networks and biological networks. Two important applications of these models are to study the evolution dynamics of network formation and to generate benchmark networks with known community structures. Research has been conducted in both these directions relatively independent of the other application area. This creates a disjunct between real world networks and the networks generated to study community detection algorithms. In this paper, we propose to study both these application areas together i.e.\\ introduce a network generation model based on evolution dynamics of real world networks and generate networks with community structures that can be used as benchmark graphs to study community detection algorithms. The generated networks possess tunable modular structures which can be used to generate networks with known community structures. We stud...
Optimizing the next generation optical access networks
DEFF Research Database (Denmark)
Amaya Fernández, Ferney Orlando; Soto, Ana Cardenas; Tafur Monroy, Idelfonso
2009-01-01
of the optical amplification in the performance of the standardized PON is presented comparing the performance of the EDFA (Erbium Doped Fiber Amplifier) and the distributed Raman amplification. The effect of the Raman amplification in extending the reach of the NG-OAN is analyzed and some requirements......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...
Surface characterization of proteins using multi-fractal property of heat-denatured aggregates
Lahiri, Tapobrata; Mishra, Hrishikesh; Sarkar, Subrata; Misra, Krishna
2008-01-01
Multi-fractal property of heat-denatured protein aggregates (HDPA) is characteristic of its individual form. The visual similarity between digitally generated microscopic images of HDPA with that of surface-image of its individual X-ray structures in protein databank (PDB) displayed using Visual Molecular Dynamics (VMD) viewer is the basis of the study. We deigned experiments to view the fractal nature of proteins at different aggregate scales. Intensity based multi-fractal dimensions (ILMFD)...
Wavelet Neural Network Based Traffic Prediction for Next Generation Network
Institute of Scientific and Technical Information of China (English)
Zhao Qigang; Li Qunzhan; He Zhengyou
2005-01-01
By using netflow traffic collecting technology, some traffic data for analysis are collected from a next generation network (NGN) operator. To build a wavelet basis neural network (NN), the Sigmoid function is replaced with the wavelet in NN. Then the wavelet multiresolution analysis method is used to decompose the traffic signal, and the decomposed component sequences are employed to train the NN. By using the methods, an NGN traffic prediction model is built to predict one day's traffic. The experimental results show that the traffic prediction method of wavelet NN is more accurate than that without using wavelet in the NGN traffic forecasting.
Multifractal analyses of music sequences
Su, Zhi-Yuan; Wu, Tzuyin
2006-09-01
Multifractal analysis is applied to study the fractal property of music. In this paper, a method is proposed to transform both the melody and rhythm of a music piece into individual sets of distributed points along a one-dimensional line. The structure of the musical composition is thus manifested and characterized by the local clustering pattern of these sequences of points. Specifically, the local Hölder exponent and the multifractal spectrum are calculated for the transformed music sequences according to the multifractal formalism. The observed fluctuations of the Hölder exponent along the music sequences confirm the non-uniformity feature in the structures of melodic and rhythmic motions of music. Our present result suggests that the shape and opening width of the multifractal spectrum plot can be used to distinguish different styles of music. In addition, a characteristic curve is constructed by mapping the point sequences converted from the melody and rhythm of a musical work into a two-dimensional graph. Each different pieces of music has its own unique characteristic curve. This characteristic curve, which also exhibits a fractal trait, unveils the intrinsic structure of music.
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.
A Neural Network for Generating Adaptive Lessons
Directory of Open Access Journals (Sweden)
Hassina Seridi-Bouchelaghem
2005-01-01
Full Text Available Traditional sequencing technology developed in the field of intelligent tutoring systems have not find an immediate place in large-scale Web-based education. This study investigates the use of computational intelligence for adaptive lesson generation in a distance learning environment over the Web. An approach for adaptive pedagogical hypermedia document generation is proposed and implemented in a prototype called KnowledgeClass. This approach is based on a specialized artificial neural network model. The system allows automatic generation of individualised courses according to the learners goal and previous knowledge and can dynamically adapt the course according to the learners success in acquiring knowledge. Several experiments showed the effectiveness of the proposed method.
Revisiting the multifractality in stock returns and its modeling implications
He, Shanshan; Wang, Yudong
2017-02-01
In this paper, we investigate the multifractality of Chinese and the U.S. stock markets using a multifractal detrending moving average algorithm. The results show that stock returns in both markets are multifractal at a similar extent. We detect the source of multifractality and find that long-range correlations are one of the major sources of multifractality in the US market but not in the Chinese market. Fat-tailed distribution plays a crucial role in multifractality of both markets. As an innovation, we quantify the effect of extreme events on multifractality and find the strong evidence of their contribution to multifractality. Furthermore, we investigate the usefulness of popular ARFIMA-GARCH models with skew-t distribution in capturing multifractality. Our results indicate that these models can capture only a fraction of multifractality. More complex models do not necessarily perform better than simple GARCH models in describing multifractality in stock returns.
Modelling and control of broadband trafﬁc using multiplicative multifractal cascades
Indian Academy of Sciences (India)
P Murali Krishna; Vikram M Gadre; Uday B Desai
2002-12-01
We present the results on the modelling and synthesis of broadband trafﬁc processes namely ethernet inter-arrival times using the VVGM (variable variance gaussian multiplier) multiplicative multifractal model. This model is shown to be more appropriate for modelling network trafﬁc which possess time varying scaling/self-similarity and burstiness. The model gives a simple and efﬁcient technique to synthesise Ethernet inter-arrival times. The results of the detailed statistical and multifractal analysis performed on the original and the synthesised traces are presented and the performance is compared with other models in the literature, such as the Poisson process, and the Multifractal Wavelet Model (MWM) process. It is also shown empirically that a single server queue preserves the multifractal character of the process by analysing its inter-departure process when fed with the multifractal traces. The result of the existence of a global-scaling exponent for multifractal cascades and its application in queueing theory are discussed. We propose tracking and control algorithms for controlling network congestion with bursty trafﬁc modelled by multifractal cascade processes, characterised by the Holder exponents, the value of which at an interval indicates the burstiness in the trafﬁc at that point. This value has to be estimated and used for the estimation of the congestion and predictive control of the trafﬁc in broadband networks. The estimation can be done by employing wavelet transforms and a Kalman ﬁlter based predictor for predicting the burstiness of the trafﬁc.
Unified Model for Generation Complex Networks with Utility Preferential Attachment
Institute of Scientific and Technical Information of China (English)
WU Jian-Jun; GAO Zi-You; SUN Hui-Jun
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 ofthis new network are given.
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.
Application of multifractal wavelet analysis to spontaneous fermentation processes
Ibarra-Junquera, V; Escalante-Minakata, P; Rosu, H C
2007-01-01
An algorithm is presented here to get more detailed information, of mixed culture type, based exclusively on the biomass concentrations data for fermentation processes. The analysis is performed having available only the on-line measurements of the redox potential. It is a two-step procedure which includes an Artificial Neural Network (ANN) that relates the redox potential to the biomass concentrations in the first step. Next, a multifractal wavelet analysis is performed using the biomass estimates of the process. In this context, our results show that the redox potential is a valuable indicator of microorganism metabolic activity during the spontaneous fermentation. In this paper, the detailed design of the multifractal wavelet analysis is presented, as well as its direct experimental application at the laboratory level
Multifractal dimension and lacunarity of yolk sac vasculature after exposure to magnetic field.
Costa, Edbhergue Ventura Lola; Nogueira, Romildo de Albuquerque
2015-05-01
Several studies have reported about the effects of magnetic fields (MFs) on vascular tissue. Extremely low frequency magnetic fields (ELF-MFs) can promote either inhibition or stimulation of vasculogenesis and angiogenesis, depending upon the intensity and time of exposure to the MF. To investigate the possible effects of ELF-MF on vascular processes, it is necessary to employ methods that allow parameterization of the vascular network. Vascular network is a structure with fractal geometry; therefore, fractal methods have been used to evaluate its morphometric complexity. Here, we used the lacunarity parameter (complementary method of fractal analysis) and multifractal analyses to investigate angiogenesis and vasculogenesis in the embryonic yolk sac membrane (YSM) of Japanese quails (Coturnix japonica) with and without exposure to an external MF of 1 mT and 60 Hz. Lacunarity results showed that the vascular density was lower for the group exposed to the magnetic field for 9 h/day. In addition, multifractal analysis showed reduced vascularization in the experimental groups (6 h/day and 9 h/day of exposure to MF). Furthermore, multifractal analysis showed difference between the groups exposed for 12 and 24 h/day. Using multifractal methods (generalized dimensions and singularity spectrum), it was possible to characterize the vascular network of the quail embryo YSM as a multifractal object, therefore proving this method to be a more appropriate application than the traditional monofractal methods. Copyright © 2015 Elsevier Inc. All rights reserved.
Lin, Aijing; Shang, Pengjian
2016-04-01
Considering the diverse application of multifractal techniques in natural scientific disciplines, this work underscores the versatility of multiscale multifractal detrended fluctuation analysis (MMA) method to investigate artificial and real-world data sets. The modified MMA method based on cumulative distribution function is proposed with the objective of quantifying the scaling exponent and multifractality of nonstationary time series. It is demonstrated that our approach can provide a more stable and faithful description of multifractal properties in comprehensive range rather than fixing the window length and slide length. Our analyzes based on CDF-MMA method reveal significant differences in the multifractal characteristics in the temporal dynamics between US and Chinese stock markets, suggesting that these two stock markets might be regulated by very different mechanism. The CDF-MMA method is important for evidencing the stable and fine structure of multiscale and multifractal scaling behaviors and can be useful to deepen and broaden our understanding of scaling exponents and multifractal characteristics.
Using multifractals to evaluate oceanographic model skill
Skákala, Jozef; Cazenave, Pierre W.; Smyth, Timothy J.; Torres, Ricardo
2016-08-01
We are in an era of unprecedented data volumes generated from observations and model simulations. This is particularly true from satellite Earth Observations (EO) and global scale oceanographic models. This presents us with an opportunity to evaluate large-scale oceanographic model outputs using EO data. Previous work on model skill evaluation has led to a plethora of metrics. The paper defines two new model skill evaluation metrics. The metrics are based on the theory of universal multifractals and their purpose is to measure the structural similarity between the model predictions and the EO data. The two metrics have the following advantages over the standard techniques: (a) they are scale-free and (b) they carry important part of information about how model represents different oceanographic drivers. Those two metrics are then used in the paper to evaluate the performance of the FVCOM model in the shelf seas around the south-west coast of the UK.
Lorentz violations in multifractal spacetimes
Calcagni, Gianluca
2016-01-01
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 manifest 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 $E_*>10^{14}\\,\\text{GeV}$ (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...
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.)
Lorentz violations in multifractal spacetimes
Calcagni, Gianluca
2017-05-01
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_{*}>10^{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_{*}> 10^{17} {GeV} or greater.
Dam management and multifractal downscaling
Biaou, A.; Hubert, P.; Schertzer, D.; Hendrickx, F.; Tchiguirinskaia, I.
2003-04-01
In order to get a more efficient production management of reservoirs, it would be helpful to apply long-term meteorological forecasts to hydrological models. Unfortunately, the explicit scales of present meteorological models are quite larger than those of hydrological models. Therefore it is indispensable to proceed to a downscaling of the output of the former in order to obtain an input for the latter. In this paper, we discuss a multifractal downscaling procedure. This type of procedure was motivated because it deals with scaling variability of the fields. The site of the study is the region of the Doubs, but we make an extension on the whole France for the multifractale analysis to take into account well the spatial variabilities. We first present the results of a detailed multifractal analysis of various data bases. Concerning the development of our downscaling model, we show how to develop a scaling space-time cascade, which takes into account the distinct space and time scaling. We will present it first in the framework of the pedagogical b-model and a-model, then in the framework of universal multifractal models. The obtained results can be the object of an relief and microclimate conditioning before being compared with the real values.
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 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.
Multifractal Analysis of Inhomogeneous Bernoulli Products
Batakis, Athanasios; Testud, Benoît
2011-03-01
We are interested to the multifractal analysis of inhomogeneous Bernoulli products which are also known as coin tossing measures. We give conditions ensuring the validity of the multifractal formalism for such measures. On another hand, we show that these measures can have a dense set of phase transitions.
MIXED SELF-CONFORMAL MULTIFRACTAL MEASURES
Institute of Scientific and Technical Information of China (English)
Meifeng Dai
2009-01-01
Mixed multifractal analysis studies the simultaneous scaling behavior of finitely many measures. A self-conformal measure is a measure invariant under a set of conformal mappings. In this paper, we provide a description of the mixed multifractal theory of finitely many self-conformal measures.
Multifractal Properties of the Ukraine Stock Market
Ganchuk, A; Solovov, V
2006-01-01
Recently the statistical characterizations of financial markets based on physics concepts and methods attract considerable attentions. We used two possible procedures of analyzing multifractal properties of a time series. The first one uses the continuous wavelet transform and extracts scaling exponents from the wavelet transform amplitudes over all scales. The second method is the multifractal version of the detrended fluctuation analysis method (MF-DFA). The multifractality of a time series we analysed by means of the difference of values singularity stregth as a suitable way to characterise multifractality. Singularity spectrum calculated from daily returns using a sliding 1000 day time window in discrete steps of 1-10 days. We discovered that changes in the multifractal spectrum display distinctive pattern around significant "drawdowns". Finally, we discuss applications to the construction of crushes precursors at the financial markets.
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.
Directory of Open Access Journals (Sweden)
Stefan Tălu
2015-10-01
Full Text Available AIM:To characterize the human retinal vessel arborisation in normal and amblyopic eyes using multifractal geometry and lacunarity parameters.METHODS:Multifractal analysis using a box counting algorithm was carried out for a set of 12 segmented and skeletonized human retinal images, corresponding to both normal (6 images and amblyopia states of the retina (6 images.RESULTS:It was found that the microvascular geometry of the human retina network represents geometrical multifractals, characterized through subsets of regions having different scaling properties that are not evident in the fractal analysis. Multifractal analysis of the amblyopia images (segmented and skeletonized versions show a higher average of the generalized dimensions (Dq for q=0, 1, 2 indicating a higher degree of the tree-dimensional complexity associated with the human retinal microvasculature network whereas images of healthy subjects show a lower value of generalized dimensions indicating normal complexity of biostructure. On the other hand, the lacunarity analysis of the amblyopia images (segmented and skeletonized versions show a lower average of the lacunarity parameter Λ than the corresponding values for normal images (segmented and skeletonized versions.CONCLUSION:The multifractal and lacunarity analysis may be used as a non-invasive predictive complementary tool to distinguish amblyopic subjects from healthy subjects and hence this technique could be used for an early diagnosis of patients with amblyopia.
Tălu, Stefan; Vlăduţiu, Cristina; Lupaşcu, Carmen A
2015-01-01
To characterize the human retinal vessel arborisation in normal and amblyopic eyes using multifractal geometry and lacunarity parameters. Multifractal analysis using a box counting algorithm was carried out for a set of 12 segmented and skeletonized human retinal images, corresponding to both normal (6 images) and amblyopia states of the retina (6 images). It was found that the microvascular geometry of the human retina network represents geometrical multifractals, characterized through subsets of regions having different scaling properties that are not evident in the fractal analysis. Multifractal analysis of the amblyopia images (segmented and skeletonized versions) show a higher average of the generalized dimensions (Dq ) for q=0, 1, 2 indicating a higher degree of the tree-dimensional complexity associated with the human retinal microvasculature network whereas images of healthy subjects show a lower value of generalized dimensions indicating normal complexity of biostructure. On the other hand, the lacunarity analysis of the amblyopia images (segmented and skeletonized versions) show a lower average of the lacunarity parameter Λ than the corresponding values for normal images (segmented and skeletonized versions). The multifractal and lacunarity analysis may be used as a non-invasive predictive complementary tool to distinguish amblyopic subjects from healthy subjects and hence this technique could be used for an early diagnosis of patients with amblyopia.
Automatic Generation of Network Protocol Gateways
DEFF Research Database (Denmark)
Bromberg, Yérom-David; Réveillère, Laurent; Lawall, Julia
2009-01-01
, 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...... 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...... of issues common to protocols used in the home. Our evaluation of these gateways shows that z2z enables communication between incompatible devices without increasing the overall resource usage or response time....
Xi, Caiping; Zhang, Shuning; Xiong, Gang; Zhao, Huichang; Yang, Yonghong
2017-02-01
Many complex systems generate multifractal time series which are long-range cross-correlated. This paper introduces three multifractal cross-correlation analysis methods, such as multifractal cross-correlation analysis based on the partition function approach (MFXPF), multifractal detrended cross-correlation analysis (MFDCCA) methods based on detrended fluctuation analysis (MFXDFA) and detrended moving average analysis (MFXDMA), which only consider one moment order. We do comparative analysis of the artificial time series (binomial multiplicative cascades and Cantor sets with different probabilities) by these methods. Then we do a feasibility test of the fixed threshold target detection within sea clutter by applying the multifractal cross-correlation analysis methods to the IPIX radar sea clutter data. The results show that it is feasible to use the method of the fixed threshold based on the multifractal feature parameter Δf(α) by the MFXPF and MFXDFA-1 methods. At last, we give the main conclusions and provide a valuable reference on how to choose the multifractal algorithms, the detection parameters and the target detection methods within sea clutter in practice.
Computational approach to multifractal music
Oświęcimka, Paweł; Kwapień, Jarosław; Celińska, Iwona; Drożdż, Stanisław; Rak, Rafał
2011-01-01
In this work we perform a fractal analysis of 160 pieces of music belonging to six different genres. We show that the majority of the pieces reveal characteristics that allow us to classify them as physical processes called the 1/f (pink) noise. However, this is not true for classical music represented here by Frederic Chopin's works and for some jazz pieces that are much more correlated than the pink noise. We also perform a multifractal (MFDFA) analysis of these music pieces. We show that a...
Detrending moving average algorithm for multifractals
Gu, Gao-Feng; Zhou, Wei-Xing
2010-07-01
The detrending moving average (DMA) algorithm is a widely used technique to quantify the long-term correlations of nonstationary time series and the long-range correlations of fractal surfaces, which contains a parameter θ determining the position of the detrending window. We develop multifractal detrending moving average (MFDMA) algorithms for the analysis of one-dimensional multifractal measures and higher-dimensional multifractals, which is a generalization of the DMA method. The performance of the one-dimensional and two-dimensional MFDMA methods is investigated using synthetic multifractal measures with analytical solutions for backward (θ=0) , centered (θ=0.5) , and forward (θ=1) detrending windows. We find that the estimated multifractal scaling exponent τ(q) and the singularity spectrum f(α) are in good agreement with the theoretical values. In addition, the backward MFDMA method has the best performance, which provides the most accurate estimates of the scaling exponents with lowest error bars, while the centered MFDMA method has the worse performance. It is found that the backward MFDMA algorithm also outperforms the multifractal detrended fluctuation analysis. The one-dimensional backward MFDMA method is applied to analyzing the time series of Shanghai Stock Exchange Composite Index and its multifractal nature is confirmed.
Multifractal analysis of stock exchange crashes
Siokis, Fotios M.
2013-03-01
We analyze the complexity of rare events of the DJIA Index. We reveal that the returns of the time series exhibit strong multifractal properties meaning that temporal correlations play a substantial role. The effect of major stock market crashes can be best illustrated by the comparison of the multifractal spectra of the time series before and after the crash. Aftershock periods compared to foreshock periods exhibit richer and more complex dynamics. Compared to an average crash, calculated by taking into account the larger 5 crashes of the DJIA Index, the 1929 event exhibits significantly more increase in multifractality than the 1987 crisis.
A robust method for estimating the multifractal wavelet spectrum in geophysical images
Nicolis, Orietta; Porro, Francesco
2013-04-01
The description of natural phenomena by an analysis of the statistical scaling laws is always a popular topic. Many studies aim to identify the fractal feature by estimating the self-similar parameter H, considered constant at different scales of observation. However, most real world data exhibit a multifractal structure, that is, the self-similarity parameter varies erratically with time. The multifractal spectrum provide an efficient tool for characterizing the scaling and singularity structures in signals and images, proving useful in numerous applications such as fluid dynamics, internet network traffic, finance, image analysis, texture synthesis, meteorology, and geophysics. In recent years, the multifractal formalism has been implemented with wavelets. The advantages of using the wavelet-based multifractal spectrum are: the availability of fast algorithms for wavelet transform, the locality of wavelet representations in both time and scale, and intrinsic dyadic self-similarity of basis functions. In this work we propose a robust Wavelet-based Multifractal Spectrum Estimator for the analysis of geophysical signals and satellite images. Finally, a simulation study and examples are considered to test the performances of the estimator.
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.
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
Control Scheme for Distributed Generator Providing Network Voltage Support
Institute of Scientific and Technical Information of China (English)
2012-01-01
The distributed generator over the last 30 years has posed several challenges when they are connected to a distributed network. The most immediate problem is to change the voltage at the connection point depending on the power supplied to the network and may cause it to exceed statutory limits. This paper describes a new control scheme for a distributed generator for supporting the voltage control in the network, thus ensuring the distributed generator to contribute to network voltage management. The scheme performance is demonstrated by a model for a distributed generator connected to a distribution network. The result shows that using the new control scheme, the distribution network voltage constraints are maintained while maximizing the active power delivered by distributed generators.
Mali, P.; Mukhopadhyay, A.; Manna, S. K.; Haldar, P. K.; Singh, G.
2017-03-01
Horizontal visibility graphs (HVGs) and the sandbox (SB) algorithm usually applied for multifractal characterization of complex network systems that are converted from time series measurements, are used to characterize the fluctuations in pseudorapidity densities of singly charged particles produced in high-energy nucleus-nucleus collisions. Besides obtaining the degree distribution associated with event-wise pseudorapidity distributions, the common set of observables, typical of any multifractality measurement, are studied in 16O-Ag/Br and 32S-Ag/Br interactions, each at an incident laboratory energy of 200 GeV/nucleon. For a better understanding, we systematically compare the experiment with a Monte Carlo model simulation based on the Ultra-relativistic Quantum Molecular Dynamics (UrQMD). Our results suggest that the HVG-SB technique is an efficient tool that can characterize multifractality in multiparticle emission data, and in some cases, it is even superior to other methods more commonly used in this regard.
Traffic Management for Next Generation Transport Networks
DEFF Research Database (Denmark)
Yu, Hao
their network capacities. However, in order to provide more advanced video services than simply porting the traditional television services to the network, the service provider needs to do more than just augment the network capacity. Advanced traffic management capability is one of the relevant abilities...... 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...... the required bandwidth, multicast is favored for providing IPTV services. Currently, transport networks lack sufficient multicast abilities. With the increase of the network capacity, it is challenging to build a multicast-enabled switch for the transport network, because, from the traffic management’s...
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 aware traffic into the network emulation platform. Traffic generators are often systems that replay captured traffic packet-by-packet or generate traffic according to a specified model or preconfigured sequence. Many of these traffic generators can...
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
Next generation network performance management: a business perspective
CSIR Research Space (South Africa)
Harding, C
2010-08-01
Full Text Available This paper addresses a Next Generation Network (NGN) performance management model in a business context. The CSIR is currently in the process of the concept design for the new Next Generation Communications Network (NGCN) for a large South African...
Transient stability analysis of a distribution network with distributed generators
Xyngi, I.; Ishchenko, A.; Popov, M.; Van der Sluis, 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 investigat
Multifractal Models, Intertrade Durations and Return Volatility
Segnon, Mawuli Kouami
2015-01-01
This thesis covers the application of multifractal processes in modeling financial time series. It aims to demonstrate the capacity and the robustness of the multifractal processes to better model return volatility and ultra high frequency financial data than both the generalized autoregressive conditional heteroscedasticity (GARCH)-type and autoregressive conditional duration (ACD) models currently used in research and practice. The thesis is comprised of four main parts that ...
Neural networks as perpetual information generators
Englisch, Harald; Xiao, Yegao; Yao, Kailun
1991-07-01
The information gain in a neural network cannot be larger than the bit capacity of the synapses. It is shown that the equation derived by Engel et al. [Phys. Rev. A 42, 4998 (1990)] for the strongly diluted network with persistent stimuli contradicts this condition. Furthermore, for any time step the correct equation is derived by taking the correlation between random variables into account.
Strategies Towords Next Generation IP Over Optical Networks
Institute of Scientific and Technical Information of China (English)
无
2002-01-01
A consensus is emerging in industry on utilizing an IP-Centric control plane within optical networks to support dynamic provisioning and restoration of lightpaths. At the same time, there are divergent views of how IP routers interact with optical core networks to achieve end-to-end connectivity. This paper describes the strategies of optical communication's future development towards next generation IP over Optical Networks. The desirable extent of network transparency in advanced all-optical network architecture is studied. Architectural alternatives for interconnecting IP routers over optical networks, and the concerned routing and signaling issues are described.
Fast Adaptation in Generative Models with Generative Matching Networks
Bartunov, Sergey; Vetrov, Dmitry P.
2016-01-01
Despite recent advances, the remaining bottlenecks in deep generative models are necessity of extensive training and difficulties with generalization from small number of training examples. Both problems may be addressed by conditional generative models that are trained to adapt the generative distribution to additional input data. So far this idea was explored only under certain limitations such as restricting the input data to be a single object or multiple objects representing the same con...
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
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
Planar growth generates scale free networks
Haslett, Garvin; Brede, Markus
2016-01-01
In this paper we introduce a model of spatial network growth in which nodes are placed at randomly selected locations on a unit square in $\\mathbb{R}^2$, forming new connections to old nodes subject to the constraint that edges do not cross. The resulting network has a power law degree distribution, high clustering and the small world property. We argue that these characteristics are a consequence of the two defining features of the network formation procedure; growth and planarity conservation. We demonstrate that the model can be understood as a variant of random Apollonian growth and further propose a one parameter family of models with the Random Apollonian Network and the Deterministic Apollonian Network as extreme cases and our model as a midpoint between them. We then relax the planarity constraint by allowing edge crossings with some probability and find a smooth crossover from power law to exponential degree distributions when this probability is increased.
Pal, Mayukha; Kiran, V. Satya; Rao, P. Madhusudana; Manimaran, P.
2016-08-01
We characterized the multifractal nature and power law cross-correlation between any pair of genome sequence through an integrative approach combining 2D multifractal detrended cross-correlation analysis and chaos game representation. In this paper, we have analyzed genomes of some prokaryotes and calculated fractal spectra h(q) and f(α) . From our analysis, we observed existence of multifractal nature and power law cross-correlation behavior between any pair of genome sequences. Cluster analysis was performed on the calculated scaling exponents to identify the class affiliation and the same is represented as a dendrogram. We suggest this approach may find applications in next generation sequence analysis, big data analytics etc.
A Mixed Generalized Multifractal Formalism For Vector Valued Measures
Mabrouk, Anouar Ben
2012-01-01
We introduce a mixed generalized multifractal formalism which extends the mixed multifractal formalism introduced by L. Olsen based on generalizations of the Hausdorff and packing measures. The validity of such a formalism is proved in some special cases.
Quantum Networks for Generating Arbitrary Quantum States
Kaye, Phillip; Mosca, Michele
2004-01-01
Quantum protocols often require the generation of specific quantum states. We describe a quantum algorithm for generating any prescribed quantum state. For an important subclass of states, including pure symmetric states, this algorithm is efficient.
Automatic Generation of Network Protocol Gateways
Bromberg, Yérom-David; Réveillère, Laurent; Lawall, Julia L.; Muller, Gilles
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.
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.
Suleymanov, M K; Zborovský, I
2003-01-01
Using three different Monte Carlo generators of high energy proton-proton collisions (HIJING, NEXUS, and PSM) we study the energy dependence of multiplicity distributions of charged particles including the LHC energy range. Results are used for calculation of the information entropy, Renyi's dimensions and other multifractal characteristics of particle production.
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.
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
Glamočanin, D.
2017-05-01
In order to maintain the continuity of the telecom operators’ network construction, while monitoring development needs, increasing customers’ demands and application of technological improvements, it is necessary to migrate optical transport core network to the next generation networks - Carrier Grade Ethernet Optical Transport Network (OTN CE). The primary objective of OTN CE is to realize an environment that is based solely on the switching in the optical domain, i.e. the realization of transparent optical networks and optical switching to the second layer of ISO / OSI model. The realization of such a network provides opportunities for further development of existing, but also technologically more demanding, new services. It is also a prerequisite to provide higher scalability, reliability, security and quality of QoS service, as well as prerequisites for the establishment of SLA (Service Level Agreement) for existing services, especially traffic in real time. This study aims to clarify the proposed model, which has the potential to be eventually adjusted in accordance with new scientific knowledge in this field as well as market requirements.
Next Generation Network Routing and Control Plane
DEFF Research Database (Denmark)
Fu, Rong
-constrains). It is shown by the simulation and analysis that the proposed DPV enhanced PCE inter-domain routing architecture improves the performance of BRPC mechanism in terms of reducing the blocking probabilities and increasing the network inter-domain link utilization. The proposed algorithms enable the PCE compute......Concerning the high performance, QoS supported transport services, it is not sufficient that only the traffic transport under a single domain or Autonomous System (AS) is under the consideration. Inter-domain QoS routing is also in a great need. As there has been empirically and theoretically...... 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...
Classifying user states in next generation networks
He, Y.; Bilgic, A.
2011-08-01
In this paper we apply a classification method to learn geographic regions using Location Based Services (LBS) in IP Multimedia Subsystem (IMS). We assume that the information in Local Network (cellular network) can be freely exchanged with Global IP Network (IMS) and the information can be gathered in a data base. LBS in the IMS also provide location information for the data sets. Statistic classification methods are applied to the data sets in the data base. Depending on the information provided by the users, they are divided into different user groups (event classes) using Type Filters (TF). Then discriminant analysis is applied to the position information offered by LBS in IMS to determine the geographic regions of the different classes. The learned geographic regions can be used to inform the users in this region or other regions over IMS. This kind of service can be used for any location-based events.
The Operational Risk Assessment for Distribution Network with Distributed Generations
Hua, Xie; Yaqi, Wu; Yifan, Wang; Qian, Sun; Jianwei, Ma
2017-05-01
Distribution network is an important part of the power system and is connected to the consumers directly. Many distributed generations that have discontinuous output power are connected in the distribution networks, which may cause adverse impact to the distribution network. Therefore, to ensure the security and reliability of distribution network with numerous distributed generations, the risk analysis is necessary for this kind of distribution networks. After study of stochastic load flow algorithm, this paper applies it in the static security risk assessment. The wind and photovoltaic output probabilistic model are built. The voltage over-limit is chosen to calculate the risk indicators. As a case study, the IEEE 33 system is simulated for analyzing impact of distributed generations on system risk in the proposed method.
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.
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…
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...
Multifractality and intermittency in the solar wind
Directory of Open Access Journals (Sweden)
W. M. Macek
2007-11-01
Full Text Available Within the complex dynamics of the solar wind's fluctuating plasma parameters, there is a detectable, hidden order described by a chaotic strange attractor which has a multifractal structure. The multifractal spectrum has been investigated using Voyager (magnetic field data in the outer heliosphere and using Helios (plasma data in the inner heliosphere. We have also analyzed the spectrum for the solar wind attractor. The spectrum is found to be consistent with that for the multifractal measure of the self-similar one-scale weighted Cantor set with two parameters describing uniform compression and natural invariant probability measure of the attractor of the system. In order to further quantify the multifractality, we also consider a generalized weighted Cantor set with two different scales describing nonuniform compression. We investigate the resulting multifractal spectrum depending on two scaling parameters and one probability measure parameter, especially for asymmetric scaling. We hope that this generalized model will also be a useful tool for analysis of intermittent turbulence in space plasmas.
Generating Scaled Replicas of Real-World Complex Networks
Staudt, Christian L; Safro, Ilya; Gutfraind, Alexander; Meyerhenke, Henning
2016-01-01
Research on generative models plays a central role in the emerging field of network science, studying how statistical patterns found in real networks can be generated by formal rules. During the last two decades, a variety of models has been proposed with an ultimate goal of achieving comprehensive realism for the generated networks. In this study, we (a) introduce a new generator, termed ReCoN; (b) explore how models can be fitted to an original network to produce a structurally similar replica, and (c) aim for producing much larger networks than the original exemplar. In a comparative experimental study, we find ReCoN often superior to many other state-of-the-art network generation methods. Our design yields a scalable and effective tool for replicating a given network while preserving important properties at both micro- and macroscopic scales and (optionally) scaling the replica by orders of magnitude in size. We recommend ReCoN as a general practical method for creating realistic test data for the enginee...
The next generation of neural network chips
Energy Technology Data Exchange (ETDEWEB)
Beiu, V.
1997-08-01
There have been many national and international neural networks research initiatives: USA (DARPA, NIBS), Canada (IRIS), Japan (HFSP) and Europe (BRAIN, GALA TEA, NERVES, ELENE NERVES 2) -- just to mention a few. Recent developments in the field of neural networks, cognitive science, bioengineering and electrical engineering have made it possible to understand more about the functioning of large ensembles of identical processing elements. There are more research papers than ever proposing solutions and hardware implementations are by no means an exception. Two fields (computing and neuroscience) are interacting in ways nobody could imagine just several years ago, and -- with the advent of new technologies -- researchers are focusing on trying to copy the Brain. Such an exciting confluence may quite shortly lead to revolutionary new computers and it is the aim of this invited session to bring to light some of the challenging research aspects dealing with the hardware realizability of future intelligent chips. Present-day (conventional) technology is (still) mostly digital and, thus, occupies wider areas and consumes much more power than the solutions envisaged. The innovative algorithmic and architectural ideals should represent important breakthroughs, paving the way towards making neural network chips available to the industry at competitive prices, in relatively small packages and consuming a fraction of the power required by equivalent digital solutions.
Changes in multifractal properties for stable angina pectoris
Knežević, Andrea; Martinis, Mladen; Krstačić, Goran; Vargović, Emil
2005-12-01
The multifractal approach has been applied to temporal fluctuations of heartbeat (RR) intervals, measured in various regimes of physical activity (ergometric data), taken from healthy subjects and those having stable angina pectoris (SAP). The problem we address here is whether SAP changes multifractality observed in healthy subjects. The G-moment method is used to analyse the multifractal spectrum. It is observed that both sets of data characterize multifractality, but a different trend in multifractal behaviour is found for SAP disease, under pronounced physical activity.
Multifractal Analysis of Human Heartbeat in Sleep
Ding, Liang-Jing; Peng, Hu; Cai, Shi-Min; Zhou, Pei-Ling
2007-07-01
We study the dynamical properties of heart rate variability (HRV) in sleep by analysing the scaling behaviour with the multifractal detrended fluctuation analysis method. It is well known that heart rate is regulated by the interaction of two branches of the autonomic nervous system: the parasympathetic and sympathetic nervous systems. By investigating the multifractal properties of light, deep, rapid-eye-movement (REM) sleep and wake stages, we firstly find an increasing multifractal behaviour during REM sleep which may be caused by augmented sympathetic activities relative to non-REM sleep. In addition, the investigation of long-range correlations of HRV in sleep with second order detrended fluctuation analysis presents irregular phenomena. These findings may be helpful to understand the underlying regulating mechanism of heart rate by autonomic nervous system during wake-sleep transitions.
Multifractal Analysis of Human Heartbeat in Sleep
Institute of Scientific and Technical Information of China (English)
DING Liang-Jing; PENG Hu; CAI Shi-Min; ZHOU Pei-Ling
2007-01-01
We study the dynamical properties of heart rate variability (HRV) in sleep by analysing the scaling behaviour with the multifractal detrended fluctuation analysis method. It is well known that heart rate is regulated by the interaction of two branches of the autonomic nervous system: the parasympathetic and sympathetic nervous systems. By investigating the multifractal properties of light, deep, rapid-eye-movement (REM) sleep and wake stages, we firstly find an increasing multifractal behaviour during REM sleep which may be caused by augmented sympathetic activities relative to non-REM sleep. In addition, the investigation of long-range correlations of HRV in sleep with second order detrended fluctuation analysis presents irregular phenomena. These findings may be helpful to understand the underlying regulating mechanism of heart rate by autonomic nervous system during wake-sleep transitions.
Multifractal Framework Based on Blanket Method
Paskaš, Milorad P.; Reljin, Irini S.; Reljin, Branimir D.
2014-01-01
This paper proposes two local multifractal measures motivated by blanket method for calculation of fractal dimension. They cover both fractal approaches familiar in image processing. The first two measures (proposed Methods 1 and 3) support model of image with embedded dimension three, while the other supports model of image embedded in space of dimension three (proposed Method 2). While the classical blanket method provides only one value for an image (fractal dimension) multifractal spectrum obtained by any of the proposed measures gives a whole range of dimensional values. This means that proposed multifractal blanket model generalizes classical (monofractal) blanket method and other versions of this monofractal approach implemented locally. Proposed measures are validated on Brodatz image database through texture classification. All proposed methods give similar classification results, while average computation time of Method 3 is substantially longer. PMID:24578664
Deformed symmetries in noncommutative and multifractional spacetimes
Calcagni, Gianluca
2016-01-01
We clarify the relation between noncommutative spacetimes and multifractional geometries where the spacetime dimension changes with the probed scale. In the absence of curvature and comparing the symmetries of both position and momentum space, we show that $\\kappa$-Minkowski spacetime and the commutative multifractional theory with $q$-derivatives are physically inequivalent but they admit several contact points that allow one to describe certain aspects of $\\kappa$-Minkowski noncommutative geometry as a multifractional theory and vice versa. Contrary to previous literature, this result holds without assuming any specific measure for $\\kappa$-Minkowski. More generally, no well-defined $\\star$-product can be constructed from the $q$-theory, although the latter does admit a natural noncommutative extension with a given deformed Poincar\\'e algebra. A similar no-go theorem may be valid for all multiscale theories with factorizable measures. Turning gravity on, we write the algebras of gravitational first-class co...
Refined Multifractal Cross-Correlation Analysis
Oświȩcimka, Paweł; Forczek, Marcin; Jadach, Stanisław; Kwapień, Jarosław
2013-01-01
We propose a modified algorithm - Multifractal Cross-Correlation Analysis (MFCCA) - that is able to consistently identify and quantify multifractal cross-correlations between two time series. Our motivation for introducing this algorithm is that the already existing methods like MF-DXA have serious limitations for most of the signals describing complex natural processes. The principal component of the related improvement is proper incorporation of the sign of fluctuations. We present a broad analysis of the model fractal stochastic processes as well as of the real-world signals and show that MFCCA is a robust tool and allows a reliable quantification of the cross-correlative structure of analyzed processes. We, in particular, analyze a relation between the generalized Hurst exponent and the MFCCA parameter $\\lambda_q$. This relation provides information about the character of potential multifractality in cross-correlations of the processes under study and thus enables selective insight into their dynamics. Us...
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.
Multifractal characteristics of titanium nitride thin films
Directory of Open Access Journals (Sweden)
Ţălu Ştefan
2015-09-01
Full Text Available The study presents a multi-scale microstructural characterization of three-dimensional (3-D micro-textured surface of titanium nitride (TiN thin films prepared by reactive DC magnetron sputtering in correlation with substrate temperature variation. Topographical characterization of the surfaces, obtained by atomic force microscopy (AFM analysis, was realized by an innovative multifractal method which may be applied for AFM data. The surface micromorphology demonstrates that the multifractal geometry of TiN thin films can be characterized at nanometer scale by the generalized dimensions Dq and the singularity spectrum f(α. Furthermore, to improve the 3-D surface characterization according with ISO 25178-2:2012, the most relevant 3-D surface roughness parameters were calculated. To quantify the 3-D nanostructure surface of TiN thin films a multifractal approach was developed and validated, which can be used for the characterization of topographical changes due to the substrate temperature variation.
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.
Robotic velocity generation using neural network
Institute of Scientific and Technical Information of China (English)
无
2001-01-01
The fast-paced nature of robotic soccer necessitates real-time sensing coupled with quick decision making and behaving. The robot must have high response-rate, exact motion ability, and must robust enough to confront interfere during drastic match. But during the match, we find that the robot usually do not act exactly as the commands from host computer. In this paper, we analyze the reason and present a method that uses BP neural network to output robotic velocity directly instead of conventional path-plan strategy, to reduce the error between actual motion and ideal plan.
Modeling of regional warehouse network generation
Directory of Open Access Journals (Sweden)
Popov Pavel Vladimirovich
2016-08-01
Full Text Available One of the factors that has a significant impact on the socio-economic development of the Russian Federation’s regions is the logistics infrastructure. It provides integrated transportation and distribution service of material flows. One of the main elements of logistics infrastructure is a storage infrastructure, which includes distribution center, distribution-and-sortout and sortout warehouses. It is the most expedient to place distribution center in the vicinity of the regional center. One of the tasks of the distribution network creation within the regions of the Russian Federation is to determine the location, capacity and number of stores. When determining regional network location of general purpose warehouses methodological approaches to solving the problems of location of production and non-production can be used which depend on various economic factors. The mathematical models for solving relevant problems are the deployment models. However, the existing models focus on the dimensionless power storage. The purpose of the given work is to develop a model to determine the optimal location of general-purpose warehouses on the Russian Federation area. At the first stage of the work, the authors assess the main economic indicators influencing the choice of the location of general purpose warehouses. An algorithm for solving the first stage, based on ABC, discriminant and cluster analysis were proposed by the authors in earlier papers. At the second stage the specific locations of general purpose warehouses and their power is chosen to provide the cost minimization for the construction and subsequent maintenance of warehouses and transportation heterogeneous products. In order to solve this problem the authors developed a mathematical model that takes into account the possibility of delivery in heterogeneous goods from suppliers and manufacturers in the distribution and storage sorting with specified set of capacities. The model allows
Optical coherent technologies in next generation access networks
Iwatsuki, Katsumi; Tsukamoto, Katsutoshi
2012-01-01
This paper reviews optical coherent technologies in next generation access networks with the use of radio over fiber (RoF), which offer key enabling technologies of wired and wireless integrated and/or converged broadband access networks to accommodate rapidly widespread cloud computing services. We describe technical issues on conventional RoF based on subcarrier modulation (SCM) and their countermeasures. Two examples of RoF access networks with optical coherent technologies to solve the technical issues are introduced; a video distribution system with FM conversion and wired and wireless integrated wide-area access network with photonic up- and down-conversion.
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).
Levy Stability Index from Multifractal Spectrum
Yuan, H B; Lian Shou Liu; Yuan, Hu; Meiling, Yu; Lianshou, Liu
1999-01-01
A method for extracting the Levy stability index $\\mu$ from the multi-fractal spectrum $f(\\alpha)$ in high energy multiparticle production is proposed. This index is an important parameter, characterizing the non-linear behaviour of dynamical fluctuations in high energy collisions. Using the random cascading that this method, basing on a linear fit, is consistent with and more accurate than the usual method of fitting the ratio of $q$th to 2nd order multi-fractal (Rényi) dimensions to the Peschanski formula.
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.
Energy Technology Data Exchange (ETDEWEB)
Schertzer, D.; Lovejoy, S. [Univ. Pierre et Marie Curie, Paris (France)
1995-09-01
Multifractal techniques and notions are increasingly widely recognized as the most appropriate and straightforward framework within which to analyze and simulate not only the scale dependence of geophysical observables, but also their extreme variability over a wide range of scales. This is particularly the case for cloud fields and their radiative properties. Schertzer first recalled the original scalar framework of turbulent cascades, especially for the modeling and analysis of passive clouds, based on multifractal developments of the Corrsin-Obukhov spectral scaling of scalar variance. These developments are based on the scaling symmetries of the dynamical equations of both the velocity and liquid water density fields. He emphasized the power of straightforward simulation methods based on these physical arguments. Schertzer showed a video displaying a time evolution of multifractal cloud in the framework of universal multifractals. He insisted that with the aid of these tools, there is no real need to took for constructs such as bounded cascades. 6 refs.
Design and Modeling Billing solution to Next Generation Networks
Lakhtaria, Kamaljit I
2010-01-01
Next generation networks (NGN) services are assumed to be a new revenue stream for both network operators and service providers. New services especially focused on a mobile telecommunications that would be used not only as a communication de vice but also as a personal gateway to order or consume a variety of services and products [1]. This type of advanced services can be accomplished when the adaptability of the packet-networks (Internet) and the quality of service of the circuit switched networks are combined into one network [2]. New challenges appear in the billing of this heterogeneous multi services network. Some examples of such a services and possible solutions about charging and billing are examined in this paper. The first steps of mathematical model for billing are also considered.
Generative Benchmark Models for Mesoscale Structures in Multilayer Networks
Bazzi, Marya; Arenas, Alex; Howison, Sam D; Porter, Mason A
2016-01-01
Multilayer networks allow one to represent diverse and interdependent connectivity patterns --- e.g., time-dependence, multiple subsystems, or both --- that arise in many applications and which are difficult or awkward to incorporate into standard network representations. In the study of multilayer networks, it is important to investigate "mesoscale" (i.e., intermediate-scale) structures, such as dense sets of nodes known as "communities" that are connected sparsely to each other, to discover network features that are not apparent at the microscale or the macroscale. A variety of methods and algorithms are available to identify communities in multilayer networks, but they differ in their definitions and/or assumptions of what constitutes a community, and many scalable algorithms provide approximate solutions with little or no theoretical guarantee on the quality of their approximations. Consequently, it is crucial to develop generative models of networks to use as a common test of community-detection tools. I...
How memory generates heterogeneous dynamics in temporal networks
Vestergaard, Christian L; Barrat, Alain
2014-01-01
Empirical temporal networks display strong heterogeneities in their dynamics, which profoundly affect processes taking place on these networks, such as rumor and epidemic spreading. Despite the recent wealth of data on temporal networks, little work has been devoted to the understanding of how such heterogeneities can emerge from microscopic mechanisms at the level of nodes and links. Here we show that long-term memory effects are present in the creation and disappearance of links in empirical networks. We thus consider a simple generative modeling framework for temporal networks able to incorporate these memory mechanisms. This allows us to study separately the role of each of these mechanisms in the emergence of heterogeneous network dynamics. In particular, we show analytically and numerically how heterogeneous distributions of contact durations, of inter-contact durations and of numbers of contacts per link emerge. We also study the individual effect of heterogeneities on dynamical processes, such as the ...
Transmission Network Expansion Planning Considering Desired Generation Security
Directory of Open Access Journals (Sweden)
Samaneh GOLESTANI
2014-02-01
Full Text Available Transmission Network Expansion Planning (TNEP is an important part of power system planning in both conventional and new structured power market. Its goal is to minimize the network construction and operational cost while satisfying the demand increase, considering technical and economic conditions. Planning algorithm in this paper consisted of two stages. The former specifies highly uncertain lines and probability of congestion, considering desired generation security level (e.g. N-2 generation security level. The latter determines the optimal expansion capacity of existing lines. Splitting required capacity for reinforcement of weak lines due to desired generation security level simplifies the TNEP problem. In addition, it monitors the impact of generation uncertainty on transmission lines. Simulation results of the proposed idea are presented for IEEE-RTS-24bus network.
Application of Artificial Neural Networks for Predicting Generated Wind Power
Vijendra Singh
2016-01-01
This paper addresses design and development of an artificial neural network based system for prediction of wind energy produced by wind turbines. Now in the last decade, renewable energy emerged as an additional alternative source for electrical power generation. We need to assess wind power generation capacity by wind turbines because of its non-exhaustible nature. The power generation by electric wind turbines depends on the speed of wind, flow direction, fluctuations, density of air, gener...
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.
Thermalnet: a Deep Convolutional Network for Synthetic Thermal Image Generation
Kniaz, V. V.; Gorbatsevich, V. S.; Mizginov, V. A.
2017-05-01
Deep convolutional neural networks have dramatically changed the landscape of the modern computer vision. Nowadays methods based on deep neural networks show the best performance among image recognition and object detection algorithms. While polishing of network architectures received a lot of scholar attention, from the practical point of view the preparation of a large image dataset for a successful training of a neural network became one of major challenges. This challenge is particularly profound for image recognition in wavelengths lying outside the visible spectrum. For example no infrared or radar image datasets large enough for successful training of a deep neural network are available to date in public domain. Recent advances of deep neural networks prove that they are also capable to do arbitrary image transformations such as super-resolution image generation, grayscale image colorisation and imitation of style of a given artist. Thus a natural question arise: how could be deep neural networks used for augmentation of existing large image datasets? This paper is focused on the development of the Thermalnet deep convolutional neural network for augmentation of existing large visible image datasets with synthetic thermal images. The Thermalnet network architecture is inspired by colorisation deep neural networks.
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.
DEFF Research Database (Denmark)
Wulff-Jensen, Andreas; Rant, Niclas Nerup; Møller, Tobias Nordvig
2017-01-01
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 using Mean Square Error [1] and Structure Similarity Index [2]. Perlin noise is especially interesting...
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.
A Vector Network Analyzer Based on Pulse Generators
Directory of Open Access Journals (Sweden)
B. Schulte
2005-01-01
Full Text Available A fast four channel network analyzer is introduced to measure S-parameters in a frequency range from 10MHz to 3GHz. The signal generation for this kind of analyzer is based on pulse generators, which are realized with bipolar transistors. The output signal of the transistor is differentiated and two short pulses, a slow and a fast one, with opposite polarities are generated. The slow pulse is suppressed with a clipping network. Thus the generation of very short electrical pulses with a duration of about 100ps is possible. The structure of the following network analyzer is similar to the structure of a conventional four channel network analyzer. All four pulses, which contain the high frequency information of the device under test, are evaluated after the digitalization of intermediate frequencies. These intermediate frequencies are generated with sampling mixers. The recorded data is evaluated with a special analysis technique, which is based on a Fourier transformation. The calibration techniques used are the same as for conventional four channel network analyzers, no new calibration techniques need to be developed.
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.
Deformed symmetries in noncommutative and multifractional spacetimes
Calcagni, Gianluca; Ronco, Michele
2017-02-01
We clarify the relation between noncommutative spacetimes and multifractional geometries, two quantum-gravity-related approaches where the fundamental description of spacetime is not given by a classical smooth geometry. Despite their different conceptual premises and mathematical formalisms, both research programs allow for the spacetime dimension to vary with the probed scale. This feature and other similarities led to ask whether there is a duality between these two independent proposals. In the absence of curvature and comparing the symmetries of both position and momentum space, we show that κ -Minkowski spacetime and the commutative multifractional theory with q -derivatives are physically inequivalent but they admit several contact points that allow one to describe certain aspects of κ -Minkowski noncommutative geometry as a multifractional theory and vice versa. Contrary to previous literature, this result holds without assuming any specific measure for κ -Minkowski. More generally, no well-defined ⋆-product can be constructed from the q -theory, although the latter does admit a natural noncommutative extension with a given deformed Poincaré algebra. A similar no-go theorem may be valid for all multiscale theories with factorizable measures. Turning gravity on, we write the algebras of gravitational first-class constraints in the multifractional theories with q - and weighted derivatives and discuss their differences with respect to the deformed algebras of κ -Minkowski spacetime and of loop quantum gravity.
Optimizing multimedia content delivery over next-generation optical networks
Di Pascale, Emanuele
2015-01-01
This thesis analyzes the performance of a Peer-to-Peer (P2P) multimedia content delivery system for a network architecture based on next-generation Passive Optical Networks (PONs). A PON is an optical access technology that is able to deliver high bandwidth capacities at a fraction of the cost of traditional point-to-point fiber solutions; this is achieved by sharing the same feeder fiber among several customers through the use of optical splitters. Established standards such as G...
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.
Martin, Victor Manuel San
2016-01-01
A method for segmenting water bodies in optical and synthetic aperture radar (SAR) satellite images is proposed. It makes use of the textural features of the different regions in the image for segmentation. The method consists in a multiscale analysis of the images, which allows us to study the images regularity both, locally and globally. As results of the analysis, coarse multifractal spectra of studied images and a group of images that associates each position (pixel) with its corresponding value of local regularity (or singularity) spectrum are obtained. Thresholds are then applied to the multifractal spectra of the images for the classification. These thresholds are selected after studying the characteristics of the spectra under the assumption that water bodies have larger local regularity than other soil types. Classifications obtained by the multifractal method are compared quantitatively with those obtained by neural networks trained to classify the pixels of the images in covered against uncovered b...
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.
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
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.
UMTS-WIMAX VERTICAL HANDOVER IN NEXT GENERATION WIRELESS NETWORKS
Directory of Open Access Journals (Sweden)
Nada Alamri
2011-12-01
Full Text Available The vision of next generation wireless network (NGWN is to integrate different wireless accesstechnologies, each with its own characteristics, into a common IP-based core network to provide mobileuser with service continuity and seamless roaming. One of the major issues for the convergedheterogeneous networks is providing a seamless vertical handover (VHO with QoS support. In this paperwe have reviewed the various interworking architectures and handover scenarios between UMTS andWiMAX. Also, we have compared the proposed solutions based on different criteria and revealed the prosand cons of each scheme. The comparison aids to adopt a better interworking and handover mechanismin NGWN.
Optimal Network Reconfiguration with Distributed Generation Using NSGA II Algorithm
Directory of Open Access Journals (Sweden)
Jasna Hivziefendic
2016-10-01
Full Text Available This paper presents a method to solve electrical network reconfiguration problem in the presence of distributed generation (DG with an objective of minimizing real power loss and energy not supplied function in distribution system. A method based on NSGA II multi-objective algorithm is used to simultaneously minimize two objective functions and to identify the optimal distribution network topology. The constraints of voltage and branch current carrying capacity are included in the evaluation of the objective function. The method has been tested on radial electrical distribution network with 213 nodes, 248 lines and 72 switches. Numerical results are presented to demonstrate the performance and effectiveness of the proposed methodology.
Application of Artificial Neural Networks for Predicting Generated Wind Power
Directory of Open Access Journals (Sweden)
Vijendra Singh
2016-03-01
Full Text Available This paper addresses design and development of an artificial neural network based system for prediction of wind energy produced by wind turbines. Now in the last decade, renewable energy emerged as an additional alternative source for electrical power generation. We need to assess wind power generation capacity by wind turbines because of its non-exhaustible nature. The power generation by electric wind turbines depends on the speed of wind, flow direction, fluctuations, density of air, generator hours, seasons of an area, and wind turbine position. During a particular season, wind power generation access can be increased. In such a case, wind energy generation prediction is crucial for transmission of generated wind energy to a power grid system. It is advisable for the wind power generation industry to predict wind power capacity to diagnose it. The present paper proposes an effort to apply artificial neural network technique for measurement of the wind energy generation capacity by wind farms in Harshnath, Sikar, Rajasthan, India.
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.
Evidence of multifractality from emerging European stock markets.
Caraiani, Petre
2012-01-01
We test for the presence of multifractality in the daily returns of the three most important stock market indices from Central and Eastern Europe, Czech PX, Hungarian BUX and Polish WIG using the Empirical Mode Decomposition based Multifractal Detrended Fluctuation Analysis. We found that the global Hurst coefficient varies with the q coefficient and that there is multifractality evidenced through the multifractal spectrum. The exercise is replicated for the sample around the high volatility period corresponding to the last global financial crisis. Although no direct link has been found between the crisis and the multifractal spectrum, the crisis was found to influence the overall shape as quantified through the norm of the multifractal spectrum.
Evidence of multifractality from emerging European stock markets.
Directory of Open Access Journals (Sweden)
Petre Caraiani
Full Text Available We test for the presence of multifractality in the daily returns of the three most important stock market indices from Central and Eastern Europe, Czech PX, Hungarian BUX and Polish WIG using the Empirical Mode Decomposition based Multifractal Detrended Fluctuation Analysis. We found that the global Hurst coefficient varies with the q coefficient and that there is multifractality evidenced through the multifractal spectrum. The exercise is replicated for the sample around the high volatility period corresponding to the last global financial crisis. Although no direct link has been found between the crisis and the multifractal spectrum, the crisis was found to influence the overall shape as quantified through the norm of the multifractal spectrum.
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.
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
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...
Vitanov, N K; Vitanov, Nikolay K.; Yankulova, Elka D.
2006-01-01
Time series of heartbeat activity of humans can exhibit long-range correlations. In this paper we show that such kind of correlations can exist for the heartbeat activity of much simpler species like Drosophila melanogaster. By means of the method of multifractal detrended fluctuation analysis (MFDFA) we calculate fractal spectra $f(\\alpha)$ and $h(q)$ and investigate the correlation properties of heartbeat activity of Drosophila with genetic hearth defects for three consequent generations of species. We observe that opposite to the case of humans the time series of the heartbeat activity of healtly Drosophila do not have scaling properties. Time series from flies with genetic defects can be long-range correllated and can have multifractal properties. The fractal heartbeat dynamics of Drosophila is transferred from generation to generation.
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.
Directory of Open Access Journals (Sweden)
D. Kiyashchenko
2003-01-01
Full Text Available Investigations of the distribution of regional seismicity and the results of numerical simulations of the seismic process show the increase of inhomogenity in spatio-temporal distribution of the seismicity prior to large earthquakes and formation of inhomogeneous clusters in a wide range of scales. Since that, the multifractal approach is appropriate to investigate the details of such dynamics. Here we analyze the dynamics of the seismicity distribution before a number of strong earthquakes occurred in two seismically active regions of the world: Japan and Southern California. In order to study the evolution of spatial inhomogeneity of the seismicity distribution, we consider variations of two multifractal characteristics: information entropy of multifractal measure generation process and the higher-order generalized fractal dimension of the continuum of the earthquake epicenters. Also we studied the dynamics of the level of spatio-temporal correlations in the seismicity distribution. It is found that two aforementioned multifractal characteristics tend to decrease and the level of spatio-temporal correlations tends to increase before the majority of considered strong earthquakes. Such a tendency can be considered as an earthquake precursory signature. Therefore, the results obtained show the possibility to use multifractal and correlation characteristics of the spatio-temporal distribution of regional seismicity for seismic hazard risk evaluation.
Sensing network for electromagnetic fields generated by seismic activities
Gershenzon, Naum I.; Bambakidis, Gust; Ternovskiy, Igor V.
2014-06-01
The sensors network is becoming prolific and play now increasingly more important role in acquiring and processing information. Cyber-Physical Systems are focusing on investigation of integrated systems that includes sensing, networking, and computations. The physics of the seismic measurement and electromagnetic field measurement requires special consideration how to design electromagnetic field measurement networks for both research and detection earthquakes and explosions along with the seismic measurement networks. In addition, the electromagnetic sensor network itself could be designed and deployed, as a research tool with great deal of flexibility, the placement of the measuring nodes must be design based on systematic analysis of the seismic-electromagnetic interaction. In this article, we review the observations of the co-seismic electromagnetic field generated by earthquakes and man-made sources such as vibrations and explosions. The theoretical investigation allows the distribution of sensor nodes to be optimized and could be used to support existing geological networks. The placement of sensor nodes have to be determined based on physics of electromagnetic field distribution above the ground level. The results of theoretical investigations of seismo-electromagnetic phenomena are considered in Section I. First, we compare the relative contribution of various types of mechano-electromagnetic mechanisms and then analyze in detail the calculation of electromagnetic fields generated by piezomagnetic and electrokinetic effects.
harmonics: generation and suppression in ac system networks
African Journals Online (AJOL)
2012-11-03
Nov 3, 2012 ... HARMONICS: GENERATION AND SUPPRESSION IN AC. SYSTEM NETWORKS .... If Vs = 295V; Z = (8 + j6)Ω and δ = 2π/3, the output voltage, Vo and ... tor current assume the characteristics shown in figure. 8. The output ...
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...
Trajectory generation and modulation using dynamic neural networks.
Zegers, P; Sundareshan, M K
2003-01-01
Generation of desired trajectory behavior using neural networks involves a particularly challenging spatio-temporal learning problem. This paper introduces a novel solution, i.e., designing a dynamic system whose terminal behavior emulates a prespecified spatio-temporal pattern independently of its initial conditions. The proposed solution uses a dynamic neural network (DNN), a hybrid architecture that employs a recurrent neural network (RNN) in cascade with a nonrecurrent neural network (NRNN). The RNN generates a simple limit cycle, which the NRNN reshapes into the desired trajectory. This architecture is simple to train. A systematic synthesis procedure based on the design of relay control systems is developed for configuring an RNN that can produce a limit cycle of elementary complexity. It is further shown that a cascade arrangement of this RNN and an appropriately trained NRNN can emulate any desired trajectory behavior irrespective of its complexity. An interesting solution to the trajectory modulation problem, i.e., online modulation of the generated trajectories using external inputs, is also presented. Results of several experiments are included to demonstrate the capabilities and performance of the DNN in handling trajectory generation and modulation problems.
Network-Oriented Approach to Distributed Generation Planning
Kochukov, O.; Mutule, A.
2017-06-01
The main objective of the paper is to present an innovative complex approach to distributed generation planning and show the advantages over existing methods. The approach will be most suitable for DNOs and authorities and has specific calculation targets to support the decision-making process. The method can be used for complex distribution networks with different arrangement and legal base.
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. Howeve
Providing content based billing architecture over Next Generation Network
Lakhtaria, Kamaljit I
2010-01-01
Mobile Communication marketplace has stressed that "content is king" ever since the initial footsteps for Next Generation Networks like 3G, 3GPP, IP Multimedia subsystem (IMS) services. However, many carriers and content providers have struggled to drive revenue for content services, primarily due to current limitations of certain types of desirable content offerings, simplistic billing models, and the inability to support flexible pricing, charging and settlement. Unlike wire line carriers, wireless carriers have a limit to the volume of traffic they can carry, bounded by the finite wireless spectrum. Event based services like calling, conferencing etc., only perceive charge per event, while the Content based charging system attracts Mobile Network Operators (MNOs) to maximize service delivery to customer and achieve best ARPU. With the Next Generation Networks, the number of data related services that can be offered, is increased significantly. The wireless carrier will be able to move from offering wireles...
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.
Generating three-qubit quantum circuits with neural networks
Swaddle, Michael; Noakes, Lyle; Smallbone, Harry; Salter, Liam; Wang, Jingbo
2017-10-01
A new method for compiling quantum algorithms is proposed and tested for a three qubit system. The proposed method is to decompose a unitary matrix U, into a product of simpler Uj via a neural network. These Uj can then be decomposed into product of known quantum gates. Key to the effectiveness of this approach is the restriction of the set of training data generated to paths which approximate minimal normal subRiemannian geodesics, as this removes unnecessary redundancy and ensures the products are unique. The two neural networks are shown to work effectively, each individually returning low loss values on validation data after relatively short training periods. The two networks are able to return coefficients that are sufficiently close to the true coefficient values to validate this method as an approach for generating quantum circuits. There is scope for more work in scaling this approach for larger quantum systems.
Epidemic progression on networks based on disease generation time
Davoudi, Bahman; Moser, Flavia; Brauer, Fred; Pourbohloul, Babak
2013-01-01
We investigate the time evolution of disease spread on a network and present an analytical framework using the concept of disease generation time. Assuming a susceptible–infected–recovered epidemic process, this network-based framework enables us to calculate in detail the number of links (edges) within the network that are capable of producing new infectious nodes (individuals), the number of links that are not transmitting the infection further (non-transmitting links), as well as the number of contacts that individuals have with their neighbours (also known as degree distribution) within each epidemiological class, for each generation period. Using several examples, we demonstrate very good agreement between our analytical calculations and the results of computer simulations. PMID:23889499
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.
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.
Chen, Feier; Tian, Kang; Ding, Xiaoxu; Miao, Yuqi; Lu, Chunxia
2016-11-01
Analysis of freight rate volatility characteristics attracts more attention after year 2008 due to the effect of credit crunch and slowdown in marine transportation. The multifractal detrended fluctuation analysis technique is employed to analyze the time series of Baltic Dry Bulk Freight Rate Index and the market trend of two bulk ship sizes, namely Capesize and Panamax for the period: March 1st 1999-February 26th 2015. In this paper, the degree of the multifractality with different fluctuation sizes is calculated. Besides, multifractal detrending moving average (MF-DMA) counting technique has been developed to quantify the components of multifractal spectrum with the finite-size effect taken into consideration. Numerical results show that both Capesize and Panamax freight rate index time series are of multifractal nature. The origin of multifractality for the bulk freight rate market series is found mostly due to nonlinear correlation.
Institute of Scientific and Technical Information of China (English)
Zhou Yu; Leung Yee; Yu Zu-Guo
2011-01-01
Multifractal detrended fluctuation analysis (MF-DFA) is a relatively new method of multifractal analysis. It is extended from detrended fluctuation analysis (DFA),which was developed for detecting the long-range correlation and the fractal properties in stationary and non-stationary time series. Although MF-DFA has become a widely used method,some relationships among the exponents established in the original paper seem to be incorrect under the general situation. In this paper,we theoretically and experimentally demonstrate the invalidity of the expression τ(q)＝qh(q)-1 stipulating the relationship between the multifractal exponent τ(q) and the generalized Hurst exponent h(q). As a replacement,a general relationship is established on the basis of the universal multifractal formalism for the stationary series as τ(q)＝qh(q)-qH'-1,where H'is the nonconservation parameter in the universal multifractal formalism. The singular spectra,a and f (a),are also derived according to this new relationship.
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
In-Network Redundancy Generation for Opportunistic Speedup of Backup
Pamies-Juarez, Lluis; Oggier, Frédérique
2011-01-01
Erasure coding is a storage-efficient alternative to replication for achieving reliable data backup in distributed storage systems. During the storage process, traditional erasure codes require a unique source node to create and upload all the redundant data to the different storage nodes. However, such a source node may have limited communication and computation capabilities, which constrain the storage process throughput. Moreover, the source node and the different storage nodes might not be able to send and receive data simultaneously -e.g., nodes might be busy in a datacenter setting, or simply be offline in a peer-to-peer setting- which can further threaten the efficacy of the overall storage process. In this paper we propose an "in-network" redundancy generation process that leverages on the self-repairing property of the novel SRC codes. This in-network redundancy generation allows storage nodes to generate new redundant data by exchanging partial information among themselves, improving the throughput ...
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
Data Generators for Learning Systems Based on RBF Networks.
Robnik-Sikonja, Marko
2016-05-01
There are plenty of problems where the data available is scarce and expensive. We propose a generator of semiartificial data with similar properties to the original data, which enables the development and testing of different data mining algorithms and the optimization of their parameters. The generated data allow large-scale experimentation and simulations without danger of overfitting. The proposed generator is based on radial basis function networks, which learn sets of Gaussian kernels. These Gaussian kernels can be used in a generative mode to generate new data from the same distributions. To assess the quality of the generated data, we evaluated the statistical properties of the generated data, structural similarity, and predictive similarity using supervised and unsupervised learning techniques. To determine usability of the proposed generator we conducted a large scale evaluation using 51 data sets. The results show a considerable similarity between the original and generated data and indicate that the method can be useful in several development and simulation scenarios. We analyze possible improvements in the classification performance by adding different amounts of the generated data to the training set, performance on high-dimensional data sets, and conditions when the proposed approach is successful.
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.
Energy Technology Data Exchange (ETDEWEB)
Ni Xiaohui [School of Business, East China University of Science and Technology, Shanghai 200237 (China)] [School of Science, East China University of Science and Technology, Shanghai 200237 (China)] [Research Center for Econophysics, East China University of Science and Technology, Shanghai 200237 (China); Jiang Zhiqiang [School of Business, East China University of Science and Technology, Shanghai 200237 (China)] [School of Science, East China University of Science and Technology, Shanghai 200237 (China)] [Research Center for Econophysics, East China University of Science and Technology, Shanghai 200237 (China)] [Chair of Entrepreneurial Risks, D-MTEC, ETH Zurich, Kreuplatz 5, CH-8032 Zurich (Switzerland); Zhou Weixing, E-mail: wxzhou@ecust.edu.c [School of Business, East China University of Science and Technology, Shanghai 200237 (China)] [School of Science, East China University of Science and Technology, Shanghai 200237 (China)] [Research Center for Econophysics, East China University of Science and Technology, Shanghai 200237 (China)] [Engineering Research Center of Process Systems Engineering (Ministry of Education), East China University of Science and Technology, Shanghai 200237 (China)] [Research Center on Fictitious Economics and Data Science, Chinese Academy of Sciences, Beijing 100080 (China)
2009-10-12
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 alpha 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 alphaapproxH linear relationship.
Particle-physics constraints on multifractal spacetimes
Calcagni, Gianluca; Rodríguez-Fernández, David
2016-01-01
We study electroweak interactions in the multiscale theory with $q$-derivatives, a framework where spacetime has the typical features of a multifractal. In the simplest case with only one characteristic time, length and energy scale $t_*$, $\\ell_*$, and $E_*$, we consider (i) the muon decay rate and (ii) the Lamb shift in the hydrogen atom, and constrain the corrections to the ordinary results. We obtain the independent absolute upper bounds (i) $t_* 35\\,\\text{MeV}$. Under some mild theoretical assumptions, the Lamb shift alone yields the even tighter ranges $t_*450\\,\\text{GeV}$. To date, these are the first robust constraints on the scales at which the multifractal features of the geometry can become important in a physical process.
How to Achieve Next-Generation Public Safety Networks
Energy Technology Data Exchange (ETDEWEB)
Juan D. Deaton
2008-07-01
Cellular technologies have dramatically affected our culture and the way we communicate. High-feature cellular handsets have enabled a cornucopia of new addictive information services. Meanwhile, public safety workers frequently are given antiquated wireless technologies, some systems more than 15 years old, to perform the important job of saving the lives of others while risking their own. Achieving nationwide interoperability and migrating public safety to next generation networks is a complicated, variegated problem that requires solutions in multiple arenas. Using the strategic solutions of cellular communication networks with backup capabilities, public safety data prioritization mechanisms, software development standards, and a public safety MVNO.
Pseudo Random Number Generator Based on Back Propagation Neural Network
Institute of Scientific and Technical Information of China (English)
WANG Bang-ju; WANG Yu-hua; NIU Li-ping; ZHANG Huan-guo
2007-01-01
Random numbers play an increasingly important role in secure wire and wireless communication.Thus the design quality of random number generator(RNG) is significant in information security.A novel pseudo RNG is proposed for improving the security of network communication.The back propagation neural network(BPNN) is nonlinear,which can be used to improve the traditional RNG.The novel pseudo RNG is based on BPNN techniques.The result of test suites standardized by the U.S shows that the RNG can satisfy the security of communication.
A multifractal formalism for countable alphabet subshifts
Energy Technology Data Exchange (ETDEWEB)
Meson, Alejandro [Instituto de Fisica de Liquidos y Sistemas Biologicos (IFLYSIB), CONICET-UNLP-CICPBA and Grupo de Aplicaciones Matematicas y Estadisticas de la Facultad de Ingenieria (GAMEFI) UNLP, La Plata (Argentina)], E-mail: vericat@gw-iflysib.iflysib.unlp.edu.ar; Vericat, Fernando [Instituto de Fisica de Liquidos y Sistemas Biologicos (IFLYSIB), CONICET-UNLP-CICPBA and Grupo de Aplicaciones Matematicas y Estadisticas de la Facultad de Ingenieria (GAMEFI) UNLP, La Plata (Argentina)], E-mail: meson@iflysib.unlp.edu.ar
2009-01-15
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.
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.
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.
Complex multifractal nature in Mycobacterium tuberculosis genome
Mandal, Saurav; Roychowdhury, Tanmoy; Chirom, Keilash; Bhattacharya, Alok; Brojen Singh, R. K.
2017-04-01
The mutifractal and long range correlation (C(r)) properties of strings, such as nucleotide sequence can be a useful parameter for identification of underlying patterns and variations. In this study C(r) and multifractal singularity function f(α) have been used to study variations in the genomes of a pathogenic bacteria Mycobacterium tuberculosis. Genomic sequences of M. tuberculosis isolates displayed significant variations in C(r) and f(α) reflecting inherent differences in sequences among isolates. M. tuberculosis isolates can be categorised into different subgroups based on sensitivity to drugs, these are DS (drug sensitive isolates), MDR (multi-drug resistant isolates) and XDR (extremely drug resistant isolates). C(r) follows significantly different scaling rules in different subgroups of isolates, but all the isolates follow one parameter scaling law. The richness in complexity of each subgroup can be quantified by the measures of multifractal parameters displaying a pattern in which XDR isolates have highest value and lowest for drug sensitive isolates. Therefore C(r) and multifractal functions can be useful parameters for analysis of genomic sequences.
Soni, Jalpa; Ghosh, Sayantan; Pradhan, Asima; Sengupta, Tapas K; Panigrahi, Prasanta K; Ghosh, Nirmalya
2011-01-01
The refractive index fluctuations in the connective tissue layer (stroma) of human cervical tissues having different grades of precancers (dysplasia) was quantified using a wavelet-based multifractal detrended fluctuation analysis model. The results show clear signature of multi-scale self-similarity in the index fluctuations of the tissues. Importantly, the refractive index fluctuations were found to be more anti-correlated at higher grades of precancers. Moreover, the strength of multifractality was also observed to be considerably weaker in higher grades of precancers. These results were further complemented by Fourier domain analysis of the spectral fluctuations.
Advances Made in the Next Generation of Satellite Networks
Bhasin, Kul B.
1999-01-01
Because of the unique networking characteristics of communications satellites, global satellite networks are moving to the forefront in enhancing national and global information infrastructures. Simultaneously, broadband data services, which are emerging as the major market driver for future satellite and terrestrial networks, are being widely acknowledged as the foundation for an efficient global information infrastructure. In the past 2 years, various task forces and working groups around the globe have identified pivotal topics and key issues to address if we are to realize such networks in a timely fashion. In response, industry, government, and academia undertook efforts to address these topics and issues. A workshop was organized to provide a forum to assess the current state-of-the-art, identify key issues, and highlight the emerging trends in the next-generation architectures, data protocol development, communication interoperability, and applications. The Satellite Networks: Architectures, Applications, and Technologies Workshop was hosted by the Space Communication Program at the NASA Lewis Research Center in Cleveland, Ohio. Nearly 300 executives and technical experts from academia, industry, and government, representing the United States and eight other countries, attended the event (June 2 to 4, 1998). The program included seven panels and invited sessions and nine breakout sessions in which 42 speakers presented on technical topics. The proceedings covers a wide range of topics: access technology and protocols, architectures and network simulations, asynchronous transfer mode (ATM) over satellite networks, Internet over satellite networks, interoperability experiments and applications, multicasting, NASA interoperability experiment programs, NASA mission applications, and Transmission Control Protocol/Internet Protocol (TCP/IP) over satellite: issues, relevance, and experience.
Detection of mobile user location on next generation wireless networks
DEFF Research Database (Denmark)
Schou, Saowanee; Olesen, Henning
2005-01-01
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...... look up the current location of other mobile users on a unified IP network by using a ¡§search by identifier¡¨ feature. Furthermore, the entire population of mobile terminals in a specific area is available for search requests.......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...
Secret Key Generation for a Pairwise Independent Network Model
Nitinawarat, Sirin; Barg, Alexander; Narayan, Prakash; Reznik, Alex
2010-01-01
We consider secret key generation for a "pairwise independent network" model in which every pair of terminals observes correlated sources that are independent of sources observed by all other pairs of terminals. The terminals are then allowed to communicate publicly with all such communication being observed by all the terminals. The objective is to generate a secret key shared by a given subset of terminals at the largest rate possible, with the cooperation of any remaining terminals. Secrecy is required from an eavesdropper that has access to the public interterminal communication. A (single-letter) formula for secret key capacity brings out a natural connection between the problem of secret key generation and a combinatorial problem of maximal packing of Steiner trees in an associated multigraph. An explicit algorithm is proposed for secret key generation based on a maximal packing of Steiner trees in a multigraph; the corresponding maximum rate of Steiner tree packing is thus a lower bound for the secret ...
Mapping Generative Models onto a Network of Digital Spiking Neurons.
Pedroni, Bruno U; Das, Srinjoy; Arthur, John V; Merolla, Paul A; Jackson, Bryan L; Modha, Dharmendra S; Kreutz-Delgado, Kenneth; Cauwenberghs, Gert
2016-08-01
Stochastic neural networks such as Restricted Boltzmann Machines (RBMs) have been successfully used in applications ranging from speech recognition to image classification, and are particularly interesting because of their potential for generative tasks. Inference and learning in these algorithms use a Markov Chain Monte Carlo procedure called Gibbs sampling, where a logistic function forms the kernel of this sampler. On the other side of the spectrum, neuromorphic systems have shown great promise for low-power and parallelized cognitive computing, but lack well-suited applications and automation procedures. In this work, we propose a systematic method for bridging the RBM algorithm and digital neuromorphic systems, with a generative pattern completion task as proof of concept. For this, we first propose a method of producing the Gibbs sampler using bio-inspired digital noisy integrate-and-fire neurons. Next, we describe the process of mapping generative RBMs trained offline onto the IBM TrueNorth neurosynaptic processor-a low-power digital neuromorphic VLSI substrate. Mapping these algorithms onto neuromorphic hardware presents unique challenges in network connectivity and weight and bias quantization, which, in turn, require architectural and design strategies for the physical realization. Generative performance is analyzed to validate the neuromorphic requirements and to best select the neuron parameters for the model. Lastly, we describe a design automation procedure which achieves optimal resource usage, accounting for the novel hardware adaptations. This work represents the first implementation of generative RBM inference on a neuromorphic VLSI substrate.
Multifractal detrending moving-average cross-correlation analysis.
Jiang, Zhi-Qiang; Zhou, Wei-Xing
2011-07-01
There are a number of situations in which several signals are simultaneously recorded in complex systems, which exhibit long-term power-law cross correlations. The multifractal detrended cross-correlation analysis (MFDCCA) approaches can be used to quantify such cross correlations, such as the MFDCCA based on the detrended fluctuation analysis (MFXDFA) method. We develop in this work a class of MFDCCA algorithms based on the detrending moving-average analysis, called MFXDMA. The performances of the proposed MFXDMA algorithms are compared with the MFXDFA method by extensive numerical experiments on pairs of time series generated from bivariate fractional Brownian motions, two-component autoregressive fractionally integrated moving-average processes, and binomial measures, which have theoretical expressions of the multifractal nature. In all cases, the scaling exponents h(xy) extracted from the MFXDMA and MFXDFA algorithms are very close to the theoretical values. For bivariate fractional Brownian motions, the scaling exponent of the cross correlation is independent of the cross-correlation coefficient between two time series, and the MFXDFA and centered MFXDMA algorithms have comparative performances, which outperform the forward and backward MFXDMA algorithms. For two-component autoregressive fractionally integrated moving-average processes, we also find that the MFXDFA and centered MFXDMA algorithms have comparative performances, while the forward and backward MFXDMA algorithms perform slightly worse. For binomial measures, the forward MFXDMA algorithm exhibits the best performance, the centered MFXDMA algorithms performs worst, and the backward MFXDMA algorithm outperforms the MFXDFA algorithm when the moment order q0. We apply these algorithms to the return time series of two stock market indexes and to their volatilities. For the returns, the centered MFXDMA algorithm gives the best estimates of h(xy)(q) since its h(xy)(2) is closest to 0.5, as expected, and
Photonic devices for next-generation broadband fiber access networks
Kazovsky, Leonid G.; Yen, She-Hwa; Wong, Shing-Wa
2011-01-01
Next-generation optical access networks will deliver substantial benefits to consumers including a dedicated high-QoS access to bit rates of hundreds of Megabits per second. They must include the following features such as: reduced total cost of ownership, higher reliability, lower energy consumption, better flexibility and efficiency. This paper will describe recent progress and technology toward that goal using novel photonic devices
The origin of an increasing or decreasing multifractal spectrum.
Opheusden, van J.H.J.
1998-01-01
The multifractal dimensionality Dq as a function of q expresses the distribution of measure over space. When all the moments scale with resolution in exactly the same way, we have a flat spectrum, and a single monofractal dimensionality. We argue that for multifractal spectra the scaling of the
Econophysics vs Cardiophysics: the Dual Face of Multifractality
Struzik, Z.R.
2003-01-01
Multifractality 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 with fat-ta
Empirical extraction of mechanisms underlying real world network generation
Itzhack, Royi; Muchnik, Lev; Erez, Tom; Tsaban, Lea; Goldenberg, Jacob; Solomon, Sorin; Louzoun, Yoram
2010-11-01
The generation mechanisms of real world networks have been described using multiple models. The mathematical features of these models are usually extrapolated from statistical properties of a snapshot of these networks. We here propose an alternative method based on direct measurement of a sequence of consecutive snapshots to uncover the dynamics underlying real world generation. We assume that the probability of adding a node or an edge depends only on local features surrounding the newly added node/edge, and directly measure the contribution of these features to the node/edge addition probability. These measurements are performed using newly defined N-node local structures. Each N-node local structure represents the configuration of edges surrounding a newly added edge. The N-node local structure measurements reproduce for some networks the now classical addition of edges between high degree node mechanisms. It also provides quantitative estimates of more complex mechanisms driving other networks’ evolution, such as the effect of common first and second neighbors. This new methodology reveals the relative importance of different generation mechanisms. We show, for example, that the main mechanism driving hyperlink addition between two websites is the existence of a third website linking to both the source and the target of the new hyperlink.
Toward robust AV conferencing on next-generation networks
Liu, Haining; Cheng, Liang; El Zarki, Magda
2005-01-01
In order to enable a truly pervasive computing environment, next generation networks (including B3G and 4G) will merge the broadband wireless and wireline networking infrastructure. However, due to the tremendous complexity in administration and the unreliability of the wireless channel, provision of hard-guarantees for services on such networks will not happen in the foreseeable future. This consequently makes it particularly challenging to offer viable AV conferencing services due to their stringent synchronization, delay and data fidelity requirements. We propose in this paper a robust application-level solution for wireless mobile AV conferencing on B3G/4G networks. Expecting no special treatment from the network, we apply a novel adaptive delay and synchronization control mechanism to maintain the synchronization and reduce the latency as much as possible. We also employ a robust video coding technique that has better error-resilience capability. We investigate the performance of the proposed solution through simulations using a three-state hidden Markov chain as the generic end-to-end transport channel model. The results show that our scheme yields tight synchronization performance, relatively low end-to-end latency and satisfactory presentation quality. The scheme successfully provides a fairly robust AV conferencing service.
Building future generation service-oriented information broker networks
Directory of Open Access Journals (Sweden)
Mohamed Bourimi
2013-12-01
Full Text Available Future generation networks target collecting intelligence from multiple sources based on end-users' data and their social interaction in order to draw useful conclusions on enabling users to execute their rights to online privacy. These networks form a rising class of service-oriented broker platforms. Designers and providers of such network platforms during the design and development of their systems focus primarily on technical specifications and issues. However, given the importance and richness of user information collected, they should already at the design phase take into account legal and ethical requirements. Failure to do so, may result in privacy violations, which may, in turn, affect the success of the network due to increasing awareness with respect to users’ privacy and security concerns, and may incur future costs. In this paper, we show how the di.me system balanced technical and legal requirements through both its design and implementation, while building a decentralized social networking platform. We report on our advances and experiences through a prototypical technology realizing such a platform, analyze the legal implications within the EU legal framework, and provide recommendations and conclusions for user-friendly service-oriented broker platforms.
Enhancing QOS and QOE in IMS enabled next generation networks
Lakhtaria, Kamaljit I
2010-01-01
Managing network complexity, accommodating greater numbers of subscribers, improving coverage to support data services (e.g. email, video, and music downloads), keeping up to speed with fast-changing technology, and driving maximum value from existing networks - all while reducing CapEX and OpEX and ensuring Quality of Service (QoS) for the network and Quality of Experience (QoE) for the user. These are just some of the pressing business issues faced by mobileservice providers, summarized by the demand to "achieve more, for less." The ultimate goal of optimization techniques at the network and application layer is to ensure End-user perceived QoS. The next generation networks (NGN), a composite environment of proven telecommunications and Internet-oriented mechanisms have become generally recognized as the telecommunications environment of the future. However, the nature of the NGN environment presents several complex issues regarding quality assurance that have not existed in the legacy environments (e.g., m...
Multifractal analysis of sentence lengths in English literary texts
Grabska-Gradzińska, Iwona; Kwapień, Jarosław; Oświ\\kecimka, Paweł; Drożdż, Stanisław
2012-01-01
This paper presents analysis of 30 literary texts written in English by different authors. For each text, there were created time series representing length of sentences in words and analyzed its fractal properties using two methods of multifractal analysis: MFDFA and WTMM. Both methods showed that there are texts which can be considered multifractal in this representation but a majority of texts are not multifractal or even not fractal at all. Out of 30 books, only a few have so-correlated lengths of consecutive sentences that the analyzed signals can be interpreted as real multifractals. An interesting direction for future investigations would be identifying what are the specific features which cause certain texts to be multifractal and other to be monofractal or even not fractal at all.
Assessment of petrophysical quantities inspired by joint multifractal approach
Lai, Z Koohi; Jafari, G R
2015-01-01
In this paper joint multifractal random walk approach is carried out to analyze some petrophysical quantities for characterizing the petroleum reservoir. These quantities include Gamma emission (GR), sonic transient time (DT) and Neutron porosity (NPHI) which are collected from four wells of a reservoir. To quantify mutual interaction of petrophysical quantities, joint multifractal random walk is implemented. This approach is based on the mutual multiplicative cascade notion in the multifractal formalism and in this approach $L_0$ represents a benchmark to describe the nature of cross-correlation between two series. The analysis of the petrophysical quantities revealed that GR for all wells has strongly multifractal nature due to the considerable abundance of large fluctuations in various scales. The variance of probability distribution function, $\\lambda_{\\ell}^2$, at scale $\\ell$ and its intercept determine the multifractal properties of the data sets sourced by probability density function. The value of $\\...
Surface characterization of proteins using multi-fractal property of heat-denatured aggregates
Lahiri, Tapobrata; Mishra, Hrishikesh; Sarkar, Subrata; Misra, Krishna
2008-01-01
Multi-fractal property of heat-denatured protein aggregates (HDPA) is characteristic of its individual form. The visual similarity between digitally generated microscopic images of HDPA with that of surface-image of its individual X-ray structures in protein databank (PDB) displayed using Visual Molecular Dynamics (VMD) viewer is the basis of the study. We deigned experiments to view the fractal nature of proteins at different aggregate scales. Intensity based multi-fractal dimensions (ILMFD) extracted from various planes of digital microscopic images of protein aggregates were used to characterize HDPA into different classes. Moreover, the ILMFD parameters extracted from aggregates show similar classification pattern to digital images of protein surface displayed by VMD viewer using PDB entry. We discuss the use of irregular patterns of heat-denatured aggregate proteins to understand various surface properties in native proteins. PMID:18795110
Multifractal age? Multifractal analysis of cardiac interbeat intervals in assessing of healthy aging
Makowiec, Danuta; Wdowczyk-Szulc, Joanna; Zarczynska-Buchowiecka, Marta; Gruchal, Marcin; Rynkiewicz, Andrzej
2013-01-01
24-hour Holter recordings of 124 healthy people at different age are studied. The nocturnal signals of young people reveal the presence of the multiplicative structure. This structure is significantly weaker in diurnal signals and becomes less evident for elderly people. Multifractal analysis allows us to propose qualitative and quantitative methods to estimate the advancement of the aging process for healthy humans.
Leonardis, E; Chapman, S C; Daughton, W; Roytershteyn, V; Karimabadi, H
2013-05-17
Recent fully nonlinear, kinetic three-dimensional simulations of magnetic reconnection [W. Daughton et al., Nat. Phys. 7, 539 (2011)] evolve structures and exhibit dynamics on multiple scales, in a manner reminiscent of turbulence. These simulations of reconnection are among the first to be performed at sufficient spatiotemporal resolution to allow formal quantitative analysis of statistical scaling, which we present here. We find that the magnetic field fluctuations generated by reconnection are anisotropic, have nontrivial spatial correlation, and exhibit the hallmarks of finite range fluid turbulence: they have non-Gaussian distributions, exhibit extended self-similarity in their scaling, and are spatially multifractal. Furthermore, we find that the rate at which the fields do work on the particles, J · E, is also multifractal, so that magnetic energy is converted to plasma kinetic energy in a manner that is spatially intermittent. This suggests that dissipation in this sense in collisionless reconnection on kinetic scales has an analogue in fluidlike turbulent phenomenology, in that it proceeds via multifractal structures generated by an intermittent cascade.
Yu, Zu-Guo; Zhang, Huan; Huang, Da-Wen; Lin, Yong; Anh, Vo
2016-03-01
Many studies have shown that additional information can be gained on time series by investigating their associated complex networks. In this work, we investigate the multifractal property and Laplace spectrum of the horizontal visibility graphs (HVGs) constructed from fractional Brownian motions. We aim to identify via simulation and curve fitting the form of these properties in terms of the Hurst index H. First, we use the sandbox algorithm to study the multifractality of these HVGs. It is found that multifractality exists in these HVGs. We find that the average fractal dimension of HVGs approximately satisfies the prominent linear formula =2-H ; while the average information dimension and average correlation dimension are all approximately bi-linear functions of H when H≥slant 0.15 . Then, we calculate the spectrum and energy for the general Laplacian operator and normalized Laplacian operator of these HVGs. We find that, for the general Laplacian operator, the average logarithm of second-smallest eigenvalue , the average logarithm of third-smallest eigenvalue , and the average logarithm of maximum eigenvalue of these HVGs are approximately linear functions of H; while the average Laplacian energy is approximately a quadratic polynomial function of H. For the normalized Laplacian operator, and of these HVGs approximately satisfy linear functions of H; while and are approximately a 4th and cubic polynomial function of H respectively.
Code generation: a strategy for neural network simulators.
Goodman, Dan F M
2010-10-01
We demonstrate a technique for the design of neural network simulation software, runtime code generation. This technique can be used to give the user complete flexibility in specifying the mathematical model for their simulation in a high level way, along with the speed of code written in a low level language such as C+ +. It can also be used to write code only once but target different hardware platforms, including inexpensive high performance graphics processing units (GPUs). Code generation can be naturally combined with computer algebra systems to provide further simplification and optimisation of the generated code. The technique is quite general and could be applied to any simulation package. We demonstrate it with the 'Brian' simulator ( http://www.briansimulator.org ).
Identifying network topologies that can generate turing pattern.
Zheng, M Mocarlo; Shao, Bin; Ouyang, Qi
2016-11-07
Turing pattern provides a paradigm of non-equilibrium self-organization in reaction-diffusion systems. On the basis of many mathematical studies, it has been proposed that various biological development processes use Turing instability to achieve periodic patterns. In this paper, we introduce a framework to systematic identify network topologies that are capable for Turing pattern formation. All possible 2, 3-node genetic regulatory networks are enumerated and linear stability analysis is applied to access their ability to generate Turing instability. We find that all 3-node networks that can achieve Turing pattern can be mapped to either pure or cross activator-inhibitor mechanisms, and the pure activator-inhibitor system is more robust for Turing pattern formation than the other one. Additional linkages can further increase the performance of the circuit by either introducing another core topology or complementing existing regulations. Moreover, we find that addition of a fixed node enables the formation of Turing pattern even when the diffusion coefficients of two morphogens are fairly close to each other. Our results provide the design principle of robust circuits for Turing pattern generation and can be further applied for systematically exploring other bifurcation phenomena.
Generating route choice sets with operation information on metro networks
Directory of Open Access Journals (Sweden)
Wei Zhu
2016-06-01
Full Text Available In recent years, the metro system has advanced into an efficient transport system and become the mainstay of urban passenger transport in many mega-cities. Passenger flow is the foundation of making and coordinating operation plans for the metro system, and therefore, a variety of studies were conducted on transit assignment models. Nevertheless route choice sets of passengers also play a paramount role in flow estimation and demand prediction. This paper first discusses the main route constraints of which the train schedule is the most important, that distinguish rail networks from road networks. Then, a two-step approach to generate route choice set in a metro network is proposed. Particularly, the improved approach introduces a route filtering with train operational information based on the conventional method. An initial numerical test shows that the proposed approach gives more reasonable route choice sets for scheduled metro networks, and, consequently, obtains more accurate results from passenger flow assignment. Recommendations for possible opportunities to apply this approach to metro operations are also provided, including its integration into a metro passenger flow assignment and simulation system in practice to help metro authorities provide more precise guidance information for passengers to travel.
Design of the next generation cognitive mobile ad hoc networks
Amjad, Ali; Wang, Huiqiang; Chen, Xiaoming
Cognition capability has been seen by researchers as the way forward for the design of next generation of Mobile Ad Hoc Networks (MANETs). The reason why a cognitive paradigm would be more suited to a MANET is because MANETs are highly dynamic networks. The topology may change very frequently during the operation of a MANET. Traffic patterns in MANETs can vary from time to time depending on the need of the users. The size of a MANET and node density is also very dynamic and may change without any predictable pattern. In a MANET environment, most of these parameters may change very rapidly and keeping track of them manually would be very difficult. Previous studies have shown that the performance of a certain routing approach in MANETs is dependent on the size of the network and node density. The choice of whether to use a reactive or proactive routing approach comes down to the network size parameter. Static or offline approaches to fine tune a MANET to achieve certain performance goals is hence not very productive as a lot of these parameters keep changing during the course of operation of MANETs. Similarly, the performance of MANETs would improve greatly if the MAC layer entity could operate in a more flexible manner. In this paper we propose a cognitive MANET design that will ensure that all these dynamic parameters are automatically monitored and decisions are based on the current status of these parameters.
Morphological Transformation and Force Generation of Active Cytoskeletal Networks
Maruri, Daniel; Kamm, Roger D.
2017-01-01
Cells assemble numerous types of actomyosin bundles that generate contractile forces for biological processes, such as cytokinesis and cell migration. One example of contractile bundles is a transverse arc that forms via actomyosin-driven condensation of actin filaments in the lamellipodia of migrating cells and exerts significant forces on the surrounding environments. Structural reorganization of a network into a bundle facilitated by actomyosin contractility is a physiologically relevant and biophysically interesting process. Nevertheless, it remains elusive how actin filaments are reoriented, buckled, and bundled as well as undergo tension buildup during the structural reorganization. In this study, using an agent-based computational model, we demonstrated how the interplay between the density of myosin motors and cross-linking proteins and the rigidity, initial orientation, and turnover of actin filaments regulates the morphological transformation of a cross-linked actomyosin network into a bundle and the buildup of tension occurring during the transformation. PMID:28114384
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...... 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...... 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...
A fraud management system architecture for next-generation networks.
Bihina Bella, M A; Eloff, J H P; Olivier, M S
2009-03-10
This paper proposes an original architecture for a fraud management system (FMS) for convergent. Next-generation networks (NGNs), which are based on the Internet protocol (IP). The architecture has the potential to satisfy the requirements of flexibility and application-independency for effective fraud detection in NGNs that cannot be met by traditional FMSs. The proposed architecture has a thorough four-stage detection process that analyses billing records in IP detail record (IPDR) format - an emerging IP-based billing standard - for signs of fraud. Its key feature is its usage of neural networks in the form of self-organising maps (SOMs) to help uncover unknown NGN fraud scenarios. A prototype was implemented to test the effectiveness of using a SOM for fraud detection and is also described in the paper.
Generating function formula of heat transfer in harmonic networks
Saito, Keiji; Dhar, Abhishek
2011-04-01
We consider heat transfer across an arbitrary classical harmonic network connected to two heat baths at different temperatures. The network has N positional degrees of freedom, of which NL are connected to a bath at temperature TL and NR are connected to a bath at temperature TR. We derive an exact formula for the cumulant generating function for heat transfer between the two baths. The formula is valid even for NL≠NR and satisfies the Gallavotti-Cohen fluctuation symmetry. Since harmonic crystals in three dimensions are known to exhibit different regimes of transport such as ballistic, anomalous, and diffusive, our result implies validity of the fluctuation theorem in all regimes. Our exact formula provides a powerful tool to study other properties of nonequilibrium current fluctuations.
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.
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.
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.)
Multifractal cross-correlation analysis in electricity spot market
Fan, Qingju; Li, Dan
2015-07-01
In this paper, we investigate the multiscale cross-correlations between electricity price and trading volume in Czech market based on a newly developed algorithm, called Multifractal Cross-Correlation Analysis (MFCCA). The new algorithm is a natural multifractal generalization of the Detrended Cross-Correlation Analysis (DCCA), and is sensitive to cross-correlation structure and free from limitations of other algorithms. By considering the original sign of the cross-covariance, it allows us to properly quantify and detect the subtle characteristics of two simultaneous recorded time series. First, the multifractality and the long range anti-persistent auto-correlations of price return and trading volume variation are confirmed using Multifractal Detrended Fluctuation Analysis (MF-DFA). Furthermore, we show that there exist long-range anti-persistent cross-correlations between price return and trading volume variation by MFCCA. And we also identify that the cross-correlations disappear on the level of relative small fluctuations. In order to obtain deeper insight into the dynamics of the electricity market, we analyze the relation between generalized Hurst exponent and the multifractal cross-correlation scaling exponent λq. We find that the difference between the generalized Hurst exponent and the multifractal cross-correlation scaling exponent is significantly different for smaller fluctuation, which indicates that the multifractal character of cross-correlations resembles more each other for electricity price and trading volume on the level of large fluctuations and weakens for the smaller ones.
Multifractal detrended moving average analysis of global temperature records
Mali, Provash
2015-01-01
Long-range correlation and multifractal nature of the global monthly mean temperature anomaly time series over the period 1850-2012 are studied in terms of the multifractal detrended moving average (MFDMA) method. We try to address the source(s) of multifractality in the time series by comparing the results derived from the actual series with those from a set of shuffled and surrogate series. It is seen that the newly developed MFDMA method predicts a multifractal structure of the temperature anomaly time series that is more or less similar to that observed by other multifractal methods. In our analysis the major contribution of multifractality in the temperature records is found to be stemmed from long-range temporal correlation among the measurements, however the contribution of fat-tail distribution function of the records is not negligible. The results of the MFDMA analysis, which are found to depend upon the location of the detrending window, tend towards the observations of the multifractal detrended fl...
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
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.
Interleaving distribution of multifractal strength of 16-channel EEG signals
Institute of Scientific and Technical Information of China (English)
WANG Wei; NING Xinbao; WANG Jun; ZHANG Sheng; CHEN Jie; LI Lejia
2003-01-01
Multifractal characteristics of 16-channel human electroencephalogram (EEG) signals under eye-closed rest are analyzed for the first time. The result shows that the EEGs from the different sites on the scalp have different multifractal characteristics and the multifractal strength value Δα exhibits a kind of interleaving and left-right opposite distribution on scalp. This distribution rule is consistent with the localization of function and the lateralization theory in physiology. SoΔα can become an effective parameter to describe the brain potential character. And such a Δα stable distribution rule on sites of the scalp means a classic cerebral cortex active state.
Multifractal Analysis of Infinite Products of Stationary Jump Processes
Directory of Open Access Journals (Sweden)
Petteri Mannersalo
2010-01-01
Full Text Available There has been a growing interest in constructing stationary measures with known multifractal properties. In an earlier paper, the authors introduced the multifractal products of stochastic processes (MPSP and provided basic properties concerning convergence, nondegeneracy, and scaling of moments. This paper considers a subclass of MPSP which is determined by jump processes with i.i.d. exponentially distributed interjump times. Particularly, the information dimension and a multifractal spectrum of the MPSP are computed. As a side result it is shown that the random partitions imprinted naturally by a family of Poisson point processes are sufficient to determine the spectrum in this case.
Image edge detection based on multi-fractal spectrum analysis
Institute of Scientific and Technical Information of China (English)
WANG Shao-yuan; WANG Yao-nan
2006-01-01
In this paper,an image edge detection method based on multi-fractal spectrum analysis is presented.The coarse grain H(o)lder exponent of the image pixels is first computed,then,its multi-fractal spectrum is estimated by the kernel estimation method.Finally,the image edge detection is done by means of different multi-fractal spectrum values.Simulation results show that this method is efficient and has better locality compared with the traditional edge detection methods such as the Sobel method.
Multifractal Model of Asset Returns versus real stock market dynamics
Oswiecimka, P; Drozdz, S; Górski, A Z; Rak, R
2006-01-01
There is more and more empirical evidence that multifractality constitutes another and perhaps the most significant financial stylized fact. A realistic model of the financial dynamics should therefore incorporate this effect. The most promising in this respect is the Multifractal Model of Asset Returns (MMAR) introduced by Mandelbrot in which multifractality is carried by time deformation. In our study we focus on the Lux extension to MMAR and empirical data from Warsaw Stock Exchange. We show that this model is able to reproduce relevant aspects of the real stock market dynamics.
Empirical Study on the Multifractal Phenomenon of Chinese Stock Market
Institute of Scientific and Technical Information of China (English)
魏宇; 黄登仕
2003-01-01
Many recent researches with empirical data have demonstrated that financial data have multifractal properties. To study the properties of Chinese stock market, the Shanghai Stock Exchange Composite Index (SSECI) from January 1999 to July 2001 (a quotation taken every 5 min) is analyzed using multifractal theories, and it is found that the return volatility correlations are of power-laws with a non-unique scaling exponent. It is verified that Chinese stock market is quite similar to foreign financial markets in terms of multifractal properties.
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.
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
Multifractal Simulation of Geochemical Map Patterns
Institute of Scientific and Technical Information of China (English)
无
2001-01-01
Using a simple multifractal model based on the model De Wijs, various geochemical map patterns for element concentration values are being simulated. Each pattern is self-similar on the average in that a similar pattern can be derived by application of the multiplicative cascade model used to any small subarea on the pattern. In other experiments, the original, self-similar pattern is distorted by superimposing a 2-dimensional trend pattern and by mixing it with a constant concentration value model. It is investigated how such distortions change the multifractal spectrum estimated by means of the 3-step method of moments. Discrete and continuous frequency distribution models are derived for patterns that satisfy the model of De Wijs. These simulated patterns satisfy a discrete frequency distribution model that as upper bound has a continuous frequency distribution to which it approaches in form when the subdivisions of the multiplicative cascade model are repeated indefinitely. This limiting distribution is lognormal in the center and has Pareto tails. Potentially, this approach has important implications in mineral and oil resource evaluation.
Identification of Geochemical Anomaly by Multifractal Analysis
Institute of Scientific and Technical Information of China (English)
Xie Shuyun; Cheng Qiuming; Ke Xianzhong; Bao Zhengyu; Wang Changming; Quan Haoli
2008-01-01
The separation of anomalies from geochemical background is an important part of data analysis because lack of such identifications might have profound influence on or even distort the final analysis results. In this article, 1 672 geochemical analytical data of 11 elements, including Cu, Mo, Ag, Sn, and others, from a region within Tibet, South China, are used as one example. Together with the traditional anomaly recognition method of using the iterative mean ±2σ, local multifractality theory has been utilized to delineate the ranges of geochemical anomalies of the elements. To different degrees, on the basis of original data mapping, C-A fractal analysis and singularity exponents, Sn differs from the other 10 elements. Moreover, geochemical mapping results based on values of the multifractal asymmetry index for all elements delineate the highly anomalous area. Similar to other 10 elements, the anomalous areas of Sn delineated by the asymmetry index distribute along the main structure orientations. According to the asymmetry indexes, the 11 elements could be classified into 3 groups: (1) Ag and Au, (2) As-Sb-Cu-Pb-Zn-Mo, and (3) Sn-Bi-W.This paragenetic association of elements can be used to interpret possible origins of mineralization, which is in agreement with petrological analysis and field survey results.
Multifractals, random walks and Arctic sea ice
Agarwal, Sahil; Wettlaufer, John
We examine the long-term correlations and multifractal properties of daily satellite retrievals of Arctic sea ice albedo, extent, and ice velocity for decadal periods. The approach harnesses a recent development called Multifractal Temporally Weighted Detrended Fluctuation Analysis (MF-TWDFA), which exploits the intuition that points closer in time are more likely to be related than distant points. In both data sets we extract multiple crossover times, as characterized by generalized Hurst exponents, ranging from synoptic to decadal. The method goes beyond treatments that assume a single decay scale process, such as a first-order autoregression, which cannot be justifiably fit to these observations. The ice extent data exhibits white noise behavior from seasonal to bi-seasonal time scales, whereas the clear fingerprints of the short (weather) and long (~ 7 and 9 year) time scales remain, the latter associated with the recent decay in the ice cover. Thus, long term persistence is reentrant beyond the seasonal scale and it is not possible to distinguish whether a given ice extent minimum/maximum will be followed by a minimum/maximum that is larger or smaller in magnitude. The ice velocity data show long term persistence in auto covariance. NASA Grant NNH13ZDA001N-CRYO and Swedish Research Council Grant No. 638-2013-9243.
Generative Model Selection Using a Scalable and Size-Independent Complex Network Classifier
Motallebi, Sadegh; Aliakbary, Sadegh; Habibi, Jafar
2013-01-01
Real networks exhibit nontrivial topological features such as heavy-tailed degree distribution, high clustering, and small-worldness. Researchers have developed several generative models for synthesizing artificial networks that are structurally similar to real networks. An important research problem is to identify the generative model that best fits to a target network. In this paper, we investigate this problem and our goal is to select the model that is able to generate graphs similar to a...
Beyond multi-fractals: surrogate time series and fields
Venema, V.; Simmer, C.
2007-12-01
Most natural complex are characterised by variability on a large range of temporal and spatial scales. The two main methodologies to generate such structures are Fourier/FARIMA based algorithms and multifractal methods. The former is restricted to Gaussian data, whereas the latter requires the structure to be self-similar. This work will present so-called surrogate data as an alternative that works with any (empirical) distribution and power spectrum. The best-known surrogate algorithm is the iterative amplitude adjusted Fourier transform (IAAFT) algorithm. We have studied six different geophysical time series (two clouds, runoff of a small and a large river, temperature and rain) and their surrogates. The power spectra and consequently the 2nd order structure functions were replicated accurately. Even the fourth order structure function was more accurately reproduced by the surrogates as would be possible by a fractal method, because the measured structure deviated too strong from fractal scaling. Only in case of the daily rain sums a fractal method could have been more accurate. Just as Fourier and multifractal methods, the current surrogates are not able to model the asymmetric increment distributions observed for runoff, i.e., they cannot reproduce nonlinear dynamical processes that are asymmetric in time. Furthermore, we have found differences for the structure functions on small scales. Surrogate methods are especially valuable for empirical studies, because the time series and fields that are generated are able to mimic measured variables accurately. Our main application is radiative transfer through structured clouds. Like many geophysical fields, clouds can only be sampled sparsely, e.g. with in-situ airborne instruments. However, for radiative transfer calculations we need full 3-dimensional cloud fields. A first study relating the measured properties of the cloud droplets and the radiative properties of the cloud field by generating surrogate cloud
Xiao, Xiaojun; Du, Chunsheng; Zhou, Rongsheng
2004-04-01
As a result of data traffic"s exponential growth, network is currently evolving from fixed circuit switched services to dynamic packet switched services, which has brought unprecedented changes to the existing transport infrastructure. It is generally agreed that automatic switched optical network (ASON) is one of the promising solutions for the next generation optical networks. In this paper, we present the results of our experimental tests and economic analysis on ASON. The intention of this paper is to present our perspective, in terms of evolution strategy toward ASON, on next generation optical networks. It is shown through experimental tests that the performance of current Pre-standard ASON enabled equipments satisfies the basic requirements of network operators and is ready for initial deployment. The results of the economic analysis show that network operators can be benefit from the deployment of ASON from three sides. Firstly, ASON can reduce the CAPEX for network expanding by integrating multiple ADM & DCS into one box. Secondly, ASON can reduce the OPEX for network operation by introducing automatic resource control scheme. Finally, ASON can increase margin revenue by providing new optical network services such as Bandwidth on Demand, optical VPN etc. Finally, the evolution strategy is proposed as our perspective toward next generation optical networks. We hope the evolution strategy introduced may be helpful for the network operators to gracefully migrate their fixed ring based legacy networks to next generation dynamic mesh based network.
Common multifractality in the heart rate variability and brain activity of healthy humans
Lin, D. C.; Sharif, A.
2010-06-01
The influence from the central nervous system on the human multifractal heart rate variability (HRV) is examined under the autonomic nervous system perturbation induced by the head-up-tilt body maneuver. We conducted the multifractal factorization analysis to factor out the common multifractal factor in the joint fluctuation of the beat-to-beat heart rate and electroencephalography data. Evidence of a central link in the multifractal HRV was found, where the transition towards increased (decreased) HRV multifractal complexity is associated with a stronger (weaker) multifractal correlation between the central and autonomic nervous systems.
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.
Multifractal properties of Chinese stock market in Shanghai
Du, Guoxiong; Ning, Xuanxi
2008-01-01
In this article, we apply three methods of multifractal analysis, partition function method, singular spectrum method and multifractal detrended fluctuation analysis method, to analyze the closing index fluctuations of Shanghai stock market during the past seven years. We have found that Shanghai stock market has weak multifractal features and there are long-range power-law correlations between index series. The shapes of singular spectrums do not change with time scales and their strengths weaken when the scales shorten. But when the orders of partition function increase, the strengths of multifractal increase, the singular spectrums become rougher and the general Hurst exponents decrease. These results provide solid and important values for further study on the dynamic mechanism of stock market price fluctuation.
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.
A new measure to characterize multifractality of sleep electroencephalogram
Institute of Scientific and Technical Information of China (English)
MA Qianli; NING Xinbao; WANG Jun; BIAN Chunhua
2006-01-01
Traditional methods for nonlinear dynamic analysis, such as correlation dimension,Lyapunov exponent, approximate entropy, detrended fluctuation analysis, using a single parameter, cannot fully describe the extremely sophisticated behavior of electroencephalogram (EEG). The multifractal formalism reveals more "hidden" information of EEG by using singularity spectrum to characterize its nonlinear dynamics. In this paper, the zero-crossing time intervals of sleep EEG were studied using multifractal analysis. A new multifractal measure △asα was proposed to describe the asymmetry of singularity spectrum, and compared with the singularity strength range △α that was normally used as a degree indicator of multifractality. One-way analysis of variance and multiple comparison tests showed that the new measure we proposed gave better discrimination of sleep stages, especially in the discrimination between sleep and awake, and between sleep stages 3and 4.
Generative models of rich clubs in Hebbian neuronal networks and large-scale human brain networks.
Vértes, Petra E; Alexander-Bloch, Aaron; Bullmore, Edward T
2014-10-05
Rich clubs arise when nodes that are 'rich' in connections also form an elite, densely connected 'club'. In brain networks, rich clubs incur high physical connection costs but also appear to be especially valuable to brain function. However, little is known about the selection pressures that drive their formation. Here, we take two complementary approaches to this question: firstly we show, using generative modelling, that the emergence of rich clubs in large-scale human brain networks can be driven by an economic trade-off between connection costs and a second, competing topological term. Secondly we show, using simulated neural networks, that Hebbian learning rules also drive the emergence of rich clubs at the microscopic level, and that the prominence of these features increases with learning time. These results suggest that Hebbian learning may provide a neuronal mechanism for the selection of complex features such as rich clubs. The neural networks that we investigate are explicitly Hebbian, and we argue that the topological term in our model of large-scale brain connectivity may represent an analogous connection rule. This putative link between learning and rich clubs is also consistent with predictions that integrative aspects of brain network organization are especially important for adaptive behaviour.
Amplified CWDM-based Next Generation Broadband Access Networks
Peiris, Sasanthi Chamarika
The explosive growth of both fixed and mobile data-centric traffic along with the inevitable trend towards all-IP/Ethernet transport protocols and packet switched networks will ultimately lead to an all-packet-based converged fixed-mobile optical transport network from the core all the way out to the access network. To address the increasing capacity and speed requirements in the access networks, Wavelength-Division Multiplexed (WDM) and/or Coarse WDM (CWDM)-based Passive Optical Networks (PONs) are expected to emerge as the next-generation optical access infrastructures. However, due to several techno-economic hurdles, CWDM-PONs are still considered an expensive solution and have not yet made any significant inroads into the current access area. One of the key technology hurdles is the scalability of the CWDM-based PONs. Passive component optical insertion losses limit the reach of the network or the number of served optical network units (ONUs). In the recent years, optical amplified CWDM approaches have emerged and new designs of optical amplifiers have been proposed and demonstrated. The critical design parameter for these amplifiers is the very wide optical amplification bandwidth (e.g., 340 nm combined for both directions). The objective of this PhD dissertation work is first to engineer ring and tree-ring based PON architectures that can achieve longer unamplified PON reach and/or provide service to a greater number of ONUs and customers. Secondly is to develop new novel optical amplifier schemes to further address the scalability limitation of the CWDM-based PONs. Specifically, this work proposes and develops novel ultra wide-band hybrid Raman-Optical parametric amplifier (HROPA) schemes that operate over nearly the entire specified CWDM band to provide 340 nm bidirectional optical gain bandwidth over the amplified PON's downstream and upstream CWDM wavelength bands (about 170 nm in each direction). The performance of the proposed HROPA schemes is assessed
Performance of multifractal detrended fluctuation analysis on short time series
Lopez, Juan Luis
2013-01-01
The performance of the multifractal detrended analysis on short time series is evaluated for synthetic samples of several mono- and multifractal models. The reconstruction of the generalized Hurst exponents is used to determine the range of applicability of the method and the precision of its results as a function of the decreasing length of the series. As an application the series of the daily exchange rate between the U.S. dollar and the euro is studied.
Asymmetric joint multifractal analysis in Chinese stock markets
Chen, Yuwen; Zheng, Tingting
2017-04-01
In this paper, the asymmetric joint multifractal analysis method based on statistical physics is proposed to explore the asymmetric correlation between daily returns and trading volumes in Chinese stock markets. The result shows asymmetric multifractal correlations exist between return and trading volume in Chinese stock markets. Moreover, when the stock indexes are upward, the fluctuations of returns are always weaker than when they are downward, whether the trading volumes are more or less.
INDIVIDUAL COMMUNICATION TRANSMITTER IDENTIFICATION BASED ON MULTIFRACTAL ANALYSIS
Institute of Scientific and Technical Information of China (English)
Ren Chunhui; Wei Ping; Lou Zhiyou; Xiao Xianci
2005-01-01
In this letter, the communication transmitter transient signals are analyzed based on the time-variant hierarchy exponents of multifractal analysis. The species of optimized sample set is selected as the template of transmitter identification, so that the individual communication transmitter identification can be realized. The turn-on signals of four transmitters are used in the simulation. The experimental results show that the multifractal character of transmitter transient signals is an effective character of individual transmitter identification.
Detrended cross-correlation analysis consistently extended to multifractality.
Oświecimka, Paweł; Drożdż, Stanisław; Forczek, Marcin; Jadach, Stanisław; Kwapień, Jarosław
2014-02-01
We propose an algorithm, multifractal cross-correlation analysis (MFCCA), which constitutes a consistent extension of the detrended cross-correlation analysis and is able to properly identify and quantify subtle characteristics of multifractal cross-correlations between two time series. Our motivation for introducing this algorithm is that the already existing methods, like multifractal extension, have at best serious limitations for most of the signals describing complex natural processes and often indicate multifractal cross-correlations when there are none. The principal component of the present extension is proper incorporation of the sign of fluctuations to their generalized moments. Furthermore, we present a broad analysis of the model fractal stochastic processes as well as of the real-world signals and show that MFCCA is a robust and selective tool at the same time and therefore allows for a reliable quantification of the cross-correlative structure of analyzed processes. In particular, it allows one to identify the boundaries of the multifractal scaling and to analyze a relation between the generalized Hurst exponent and the multifractal scaling parameter λ(q). This relation provides information about the character of potential multifractality in cross-correlations and thus enables a deeper insight into dynamics of the analyzed processes than allowed by any other related method available so far. By using examples of time series from the stock market, we show that financial fluctuations typically cross-correlate multifractally only for relatively large fluctuations, whereas small fluctuations remain mutually independent even at maximum of such cross-correlations. Finally, we indicate possible utility of MFCCA to study effects of the time-lagged cross-correlations.
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 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....
Direct Evidence for Inversion Formula in Multifractal Financial Volatility Measure
Institute of Scientific and Technical Information of China (English)
JIANG Zhi-Qiang; ZHOU Wei-Xing
2009-01-01
The inversion formula for conservative multifractal measures was unveiled mathematically a decade ago, which is however not well tested in real complex systems. We propose to verify the inversion formula using high-frequency 1982 to 1999 and its inverse measure of exit time. Both the direct and inverse measures exhibit nice multifractal nature, whose scaling ranges are not irrelevant. Empirical investigation shows that the inversion formula holds in financial markets.
When Van Gogh meets Mandelbrot: Multifractal Classification of Painting's Texture
Abry, Patrice; Wendt, Herwig; Jaffard, Stéphane
2013-01-01
International audience; In a recent past, there has been a growing interest for examining the po- tential of Image Processing tools to assist Art Investigation. Simultaneously, several research works showed the interest of using multifractal analysis for the description of homogeneous textures in images. In this context, the goal of the present contribution is to study the benefits of using the wavelet leader based multifractal formalism to characterize paintings. To that end, after a brief r...
Generative model selection using a scalable and size-independent complex network classifier.
Motallebi, Sadegh; Aliakbary, Sadegh; Habibi, Jafar
2013-12-01
Real networks exhibit nontrivial topological features, such as heavy-tailed degree distribution, high clustering, and small-worldness. Researchers have developed several generative models for synthesizing artificial networks that are structurally similar to real networks. An important research problem is to identify the generative model that best fits to a target network. In this paper, we investigate this problem and our goal is to select the model that is able to generate graphs similar to a given network instance. By the means of generating synthetic networks with seven outstanding generative models, we have utilized machine learning methods to develop a decision tree for model selection. Our proposed method, which is named "Generative Model Selection for Complex Networks," outperforms existing methods with respect to accuracy, scalability, and size-independence.
Generative model selection using a scalable and size-independent complex network classifier
Energy Technology Data Exchange (ETDEWEB)
Motallebi, Sadegh, E-mail: motallebi@ce.sharif.edu; Aliakbary, Sadegh, E-mail: aliakbary@ce.sharif.edu; Habibi, Jafar, E-mail: jhabibi@sharif.edu [Department of Computer Engineering, Sharif University of Technology, Tehran (Iran, Islamic Republic of)
2013-12-15
Real networks exhibit nontrivial topological features, such as heavy-tailed degree distribution, high clustering, and small-worldness. Researchers have developed several generative models for synthesizing artificial networks that are structurally similar to real networks. An important research problem is to identify the generative model that best fits to a target network. In this paper, we investigate this problem and our goal is to select the model that is able to generate graphs similar to a given network instance. By the means of generating synthetic networks with seven outstanding generative models, we have utilized machine learning methods to develop a decision tree for model selection. Our proposed method, which is named “Generative Model Selection for Complex Networks,” outperforms existing methods with respect to accuracy, scalability, and size-independence.
High Performance Ethernet Packet Processor Core for Next Generation Networks
Directory of Open Access Journals (Sweden)
Raja Jitendra Nayaka
2012-10-01
Full Text Available As the demand for high speed Internet significantly increasing to meet the requirement of large datatransfers, real-time communication and High Definition ( HD multimedia transfer over IP, the IP basednetwork products architecture must evolve and change. Application specific processors require highperformance, low power and high degree of programmability is the limitation in many general processorbased applications. This paper describes the design of Ethernet packet processor for system-on-chip (SoCwhich performs all core packet processing functions, including segmentation and reassembly, packetizationclassification, route and queue management which will speedup switching/routing performance making itmore suitable for Next Generation Networks (NGN. Ethernet packet processor design can be configuredfor use with multiple projects targeted to a FPGA device the system is designed to support 1/10/20/40/100Gigabit links with a speed and performance advantage. VHDL has been used to implement and simulatedthe required functions in FPGA.
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.
Multifractal analysis of high resolution solar wind proton density measurements
Sorriso-Valvo, Luca; Carbone, Francesco; Leonardis, Ersilia; Chen, Christopher H. K.; Šafránková, Jana; Němeček, Zdenek
2017-03-01
The solar wind is a highly turbulent medium, with a high level of field fluctuations throughout a broad range of scales. These include an inertial range where a turbulent cascade is assumed to be active. The solar wind cascade shows intermittency, which however may depend on the wind conditions. Recent observations have shown that ion-scale magnetic turbulence is almost self-similar, rather than intermittent. A similar result was observed for the high resolution measurements of proton density provided by the spacecraft Spektr-R. Intermittency may be interpreted as the result of the multifractal properties of the turbulent cascade. In this perspective, this paper is devoted to the description of the multifractal properties of the high resolution density measurements. In particular, we have used the standard coarse-graining technique to evaluate the generalized dimensions Dq , and from these the multifractal spectrum f (α) , in two ranges of scale. A fit with the p-model for intermittency provided a quantitative measure of multifractality. Such indicator was then compared with alternative measures: the width of the multifractal spectrum, the peak of the kurtosis, and its scaling exponent. The results indicate that the small-scale fluctuations are multifractal, and suggest that different measures of intermittency are required to fully understand the small scale cascade.
Exoplanetary Detection By Multifractal Spectral Analysis
Agarwal, Sahil; Wettlaufer, John S
2016-01-01
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 time scales that characterize planetary orbital motion around the host star. Without fitting spectral data to stellar models, 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 time scales obtained to primary transit and secondary exoplanet 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 dop...
Network Formation Games Among Relay Stations in Next Generation Wireless Networks
Saad, Walid; Başar, Tamer; Debbah, Mérouane; Hjørungnes, Are
2012-01-01
The introduction of relay station (RS) nodes is a key feature in next generation wireless networks such as 3GPP's long term evolution advanced (LTE-Advanced), or the forthcoming IEEE 802.16j WiMAX standard. This paper presents, using game theory, a novel approach for the formation of the tree architecture that connects the RSs and their serving base station in the \\emph{uplink} of the next generation wireless multi-hop systems. Unlike existing literature which mainly focused on performance analysis, we propose a distributed algorithm for studying the \\emph{structure} and \\emph{dynamics} of the network. We formulate a network formation game among the RSs whereby each RS aims to maximize a cross-layer utility function that takes into account the benefit from cooperative transmission, in terms of reduced bit error rate, and the costs in terms of the delay due to multi-hop transmission. For forming the tree structure, a distributed myopic algorithm is devised. Using the proposed algorithm, each RS can individuall...
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
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.
Intelligent Joint Admission Control for Next Generation Wireless Networks
Mohsen, Abdulqader M.; Al-Akwaa, Fadhl M.; Mohammed M. Alkhawlani
2012-01-01
The Heterogeneous Wireless Network (HWN) integrates different wireless networks into one common network. The integrated networks often overlap coverage in the same wireless service areas, leading to the availability of a great variety of innovative services based on user demands in a cost-efficient manner. Joint Admission Control (JAC) handles all new or handoff service requests in the HWN. It checks whether the incoming service request to the selected Radio Access Network (RAN) by the initia...
Tălu, Stefan
2013-07-01
The purpose of this paper is to determine a quantitative assessment of the human retinal vascular network architecture for patients with diabetic macular edema (DME). Multifractal geometry and lacunarity parameters are used in this study. A set of 10 segmented and skeletonized human retinal images, corresponding to both normal (five images) and DME states of the retina (five images), from the DRIVE database was analyzed using the Image J software. Statistical analyses were performed using Microsoft Office Excel 2003 and GraphPad InStat software. The human retinal vascular network architecture has a multifractal geometry. The average of generalized dimensions (Dq) for q = 0, 1, 2 of the normal images (segmented versions), is similar to the DME cases (segmented versions). The average of generalized dimensions (Dq) for q = 0, 1 of the normal images (skeletonized versions), is slightly greater than the DME cases (skeletonized versions). However, the average of D2 for the normal images (skeletonized versions) is similar to the DME images. The average of lacunarity parameter, Λ, for the normal images (segmented and skeletonized versions) is slightly lower than the corresponding values for DME images (segmented and skeletonized versions). The multifractal and lacunarity analysis provides a non-invasive predictive complementary tool for an early diagnosis of patients with DME.
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 ...
Computer-generated global map of valley networks on Mars
Luo, Wei; Stepinski, T. F.
2009-11-01
The presence of valley networks (VN) on Mars suggests that early Mars was warmer and wetter than present. However, detailed geomorphic analyses of individual networks have not led to a consensus regarding their origin. An additional line of evidence can be provided by the global pattern of dissection on Mars, but the currently available global map of VN, compiled from Viking images, is incomplete and outdated. We created an updated map of VN by using a computer algorithm that parses topographic data and recognizes valleys by their morphologic signature. This computer-generated map was visually inspected and edited to produce the final updated map of VN. The new map shows an increase in total VN length by a factor of 2.3. A global map of dissection density, D, derived from the new VN map, shows that the most highly dissected region forms a belt located between the equator and mid-southern latitudes. The most prominent regions of high values of D are the northern Terra Cimmeria and the Margaritifer Terra where D reaches the value of 0.12 km-1 over extended areas. The average value of D is 0.062 km-1, only 2.6 times lower than the terrestrial value of D as measured in the same fashion. These relatively high values of dissection density over extensive regions of the planet point toward precipitation-fed runoff erosion as the primary mechanism of valley formation. Assuming a warm and wet early Mars, peculiarity of the global pattern of dissection is interpreted in the terms of climate controlling factors influenced by the topographic dichotomy.
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...... and effective Network-on-Chip (NoC) development and debugging environment. By capturing the type and the timestamp of communication events at the boundary of an IP core in a reference environment, the TG can subsequently emulate the core's communication behavior in different environments. Access patterns...
Single and Joint Multifractal Analysis of Soil Particle Size Distributions
Institute of Scientific and Technical Information of China (English)
LI Yi; LI Min; R.HORTON
2011-01-01
It is noted that there has been little research to compare volume-based and number-based soil particle size distributions (PSDs).Our objectives were to characterize the scaling properties and the possible connections between volume-based and number-based PSDs by applying single and joint multifractal analysis.Twelve soil samples were taken from selected sites in Northwest China and their PSDs were analyzed using laser diffractometry.The results indicated that the volume-based PSDs of all 12 samples and thc number-based PSDs of 4 samples had multifractal scalings for moment order -6 ＜ q ＜ 6.Some empirical relationships were identified between the extreme probability values, maximum probability (Pmax), minimum probability (Pmin), and Pmax/Pmin, and the multifractal indices,the difference and the ratio of generalized dimensions at q=0 and 1(D0-D1 and D1/D0), maximum and minimum singularity strength (αmax and αmin) and their difference (αmax - αmin, spectrum width), and asymmetric index (RD).An increase in Pmax generally resulted in corresponding increases of D0 - D1, αmax, αmax - αmin, and RD, which indicated that a large Pmax increased the multifractality of a distribution.Joint multifractal analysis showed that there was significant correlation between the scaling indices of volume-based and number-based PSDs.The multifractality indices indicated that for a given soil, the volume-based PSD was more homogeneous than the number-based PSD, and more likely to display monofractal rather than multifractal scaling.
Milazzo, Lorenzo
2016-01-01
A multifractal analysis (MFA) is performed on three-dimensional grayscale images associated with natural porous structures (soil samples). First, computed tomography (CT) scans are carried out on the samples to generate 3D grayscale images. Then, a preliminary analysis is conducted to evaluate key quantities associated with the porosity, such as void fraction, pore volume, connectivity, and surface area. Finally, the samples are successfully identified and separated into two different structure families by using the MFA. A new software (Munari) to carry out the MFA of 3D grayscale images is also presented.
Multifractal spatial patterns and diversity in an ecological succession.
Saravia, Leonardo Ariel; Giorgi, Adonis; Momo, Fernando
2012-01-01
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.
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.
Are crude oil markets multifractal? Evidence from MF-DFA and MF-SSA perspectives
He, Ling-Yun; Chen, Shu-Peng
2010-08-01
In this article, we investigated the multifractality and its underlying formation mechanisms in international crude oil markets, namely, Brent and WTI, which are the most important oil pricing benchmarks globally. We attempt to find the answers to the following questions: (1) Are those different markets multifractal? (2) What are the dynamical causes for multifractality in those markets (if any)? To answer these questions, we applied both multifractal detrended fluctuation analysis (MF-DFA) and multifractal singular spectrum analysis (MF-SSA) based on the partition function, two widely used multifractality detecting methods. We found that both markets exhibit multifractal properties by means of these methods. Furthermore, in order to identify the underlying formation mechanisms of multifractal features, we destroyed the underlying nonlinear temporal correlation by shuffling the original time series; thus, we identified that the causes of the multifractality are influenced mainly by a nonlinear temporal correlation mechanism instead of a non-Gaussian distribution. At last, by tracking the evolution of left- and right-half multifractal spectra, we found that the dynamics of the large price fluctuations is significantly different from that of the small ones. Our main contribution is that we not only provided empirical evidence of the existence of multifractality in the markets, but also the sources of multifractality and plausible explanations to current literature; furthermore, we investigated the different dynamical price behaviors influenced by large and small price fluctuations.
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......Mobile communication networks are evolving towards smaller cells, higher throughput, better security and provision of better services. Wireless short-range technologies, such as the WLAN 802.11 standards family and Bluetooth, are expected to play a major role in future networks. The mobile core...... their current point of attachment to the network and hence provide the current location of the mobile user automatically. The convergence of wireless short-range networks, mobile networks and Internet technology will provide the mobile user's location without any add-in equipment for location measurement...
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.
Challenges in Second-Generation Wireless Mesh Networks
Directory of Open Access Journals (Sweden)
Thomas Huehn
2008-10-01
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.
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.
R&D on wireless broadband communication systems: new generation ubiquitous mobile network
Ogawa, Hiroyo
2007-09-01
R&D on new generation mobile network has attracted a growing interest over the world on the background of rapid market growth for 2nd and 3rd - generation cellular networks and wireless LANs/MANs. The National Institute of Information and Communications Technology (NICT) has been carried out the New Generation Mobile Network Project from April 2002 to March 2006, and has developed fundamental technologies to enable seamless and secure integration of various wireless access networks such as existing cellular networks, wireless LANs, home networks, intelligent transport systems (ITS), the Beyond-3G (B3G) cellular and other wireless access systems. From April 2006, Ubiquitous Mobile Network project focused on cognitive radio technology and integrated seamless networking technology was started. This paper overviews the achievement and the future plan of these projects.
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.
Hybrid scheduling mechanisms for Next-generation Passive Optical Networks based on network coding
Zhao, Jijun; Bai, Wei; Liu, Xin; Feng, Nan; Maier, Martin
2014-10-01
Network coding (NC) integrated into Passive Optical Networks (PONs) is regarded as a promising solution to achieve higher throughput and energy efficiency. To efficiently support multimedia traffic under this new transmission mode, novel NC-based hybrid scheduling mechanisms for Next-generation PONs (NG-PONs) including energy management, time slot management, resource allocation, and Quality-of-Service (QoS) scheduling are proposed in this paper. First, we design an energy-saving scheme that is based on Bidirectional Centric Scheduling (BCS) to reduce the energy consumption of both the Optical Line Terminal (OLT) and Optical Network Units (ONUs). Next, we propose an intra-ONU scheduling and an inter-ONU scheduling scheme, which takes NC into account to support service differentiation and QoS assurance. The presented simulation results show that BCS achieves higher energy efficiency under low traffic loads, clearly outperforming the alternative NC-based Upstream Centric Scheduling (UCS) scheme. Furthermore, BCS is shown to provide better QoS assurance.
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
Caraiani, Petre
2012-07-01
We investigate the properties of the returns of the main emerging stock markets from Europe by means of complex networks. We transform the series of daily returns into complex networks, and analyze the local properties of these networks with respect to degree distributions, clustering, or average line length. We further use the clustering coefficients as quantities describing the local structure of the network, and approach them by using multifractal analysis. We find evidence of scale-free networks and multifractality of clustering coefficients.
Next-Generation WDM Network Design and Routing
Tsang, Danny H. K.; Bensaou, Brahim
2003-10-01
Call for Papers The Editors of JON are soliciting papers on WDM Network Design and Routing. The aim in this focus issue is to publish original research on topics including - but not limited to - the following: - WDM network architectures and protocols - GMPLS network architectures - Wavelength converter placement in WDM networks - Routing and wavelength assignment (RWA) in WDM networks - Protection and restoration strategies and algorithms in WDM networks - Traffic grooming in WDM networks - Dynamic routing strategies and algorithms - Optical burst switching - Support of multicast - Protection and restoration in WDM networks - Performance analysis and optimization in WDM networks Manuscript Submission To submit to this special issue, follow the normal procedure for submission to JON, indicating "WDM Network Design" in the "Comments" field of the online submission form. For all other questions relating to this focus issue, please send an e-mail to jon@osa.org, subject line "WDM Network Design." Additional information can be found on the JON website: http://www.osa-jon.org/submission/. Schedule - Paper Submission Deadline: November 1, 2003 - Notification to Authors: January 15, 2004 - Final Manuscripts to Publisher: February 15, 2004 - Publication of Focus Issue: February/March 2004
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.
Multifractality in fidelity sequences of optimized Toffoli gates
Moqadam, Jalil Khatibi; Welter, Guilherme S.; Esquef, Paulo A. A.
2016-11-01
We analyze the multifractality in the fidelity sequences of several engineered Toffoli gates. Using quantum control methods, we consider several optimization problems whose global solutions realize the gate in a chain of three qubits with XY Heisenberg interaction. Applying a minimum number of control pulses assuring a fidelity above 99 % in the ideal case, we design stable gates that are less sensitive to variations in the interqubits couplings. The most stable gate has the fidelity above 91 % with variations about 0.1 %, for up to 10 % variation in the nominal couplings. We perturb the system by introducing a single source of 1 / f noise that affects all the couplings. In order to quantify the performance of the proposed optimized gates, we calculate the fidelity of a large set of optimized gates under prescribed levels of coupling perturbation. Then, we run multifractal analysis on the sequence of attained fidelities. This way, gate performance can be assessed beyond mere average results, since the chosen multifractality measure (the width of the multifractal spectrum) encapsulates into a single performance indicator the spread of fidelity values around the mean and the presence of outliers. The higher the value of the performance indicator the more concentrated around the mean the fidelity values are and rarer is the occurrence of outliers. The results of the multifractal analysis on the fidelity sequences demonstrate the effectiveness of the proposed optimized gate implementations, in the sense they are rendered less sensitive to variations in the interqubits coupling strengths.
Multifractal detrended fluctuation analysis of optogenetic modulation of neural activity
Kumar, S.; Gu, L.; Ghosh, N.; Mohanty, S. K.
2013-02-01
Here, we introduce a computational procedure to examine whether optogenetically activated neuronal firing recordings could be characterized as multifractal series. Optogenetics is emerging as a valuable experimental tool and a promising approach for studying a variety of neurological disorders in animal models. The spiking patterns from cortical region of the brain of optogenetically-stimulated transgenic mice were analyzed using a sophisticated fluctuation analysis method known as multifractal detrended fluctuation analysis (MFDFA). We observed that the optogenetically-stimulated neural firings are consistent with a multifractal process. Further, we used MFDFA to monitor the effect of chemically induced pain (formalin injection) and optogenetic treatment used to relieve the pain. In this case, dramatic changes in parameters characterizing a multifractal series were observed. Both the generalized Hurst exponent and width of singularity spectrum effectively differentiates the neural activities during control and pain induction phases. The quantitative nature of the analysis equips us with better measures to quantify pain. Further, it provided a measure for effectiveness of the optogenetic stimulation in inhibiting pain. MFDFA-analysis of spiking data from other deep regions of the brain also turned out to be multifractal in nature, with subtle differences in the parameters during pain-induction by formalin injection and inhibition by optogenetic stimulation. Characterization of neuronal firing patterns using MFDFA will lead to better understanding of neuronal response to optogenetic activation and overall circuitry involved in the process.
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.
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…
Jia, Zhanliang; Cui, Meilan; Li, Handong
2012-02-01
We examine the multifractal properties of the realized volatility (RV) and realized bipower variation (RBV) series in the Shanghai Stock Exchange Composite Index (SSECI) by using the multifractal detrended fluctuation analysis (MF-DFA) method. We find that there exist distinct multifractal characteristics in the volatility series. The contributions of two different types of source of multifractality, namely, fat-tailed probability distributions and nonlinear temporal correlations, are studied. By using the unit root test, we also find the strength of the multifractality of the volatility time series is insensitive to the sampling frequency but that the long memory of these series is sensitive.
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
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
Generating weighted community networks based on local events
Institute of Scientific and Technical Information of China (English)
Xu Qi-Xin; Xu Xin-Jian
2009-01-01
realistic networks have community structures, namely, a network consists of groups of nodes within which links are dense but among which links are sparse. This paper proposes a growing network model based on local processes, the addition of new nodes intra-community and new links intra- or inter-community. Also, it utilizes the preferential attachment for building connections determined by nodes' strengths, which evolves dynamically during the growth of the system. The resulting network reflects the intrinsic community structure with generalized power-law distributions of nodes' degrees and strengths.
Multifractal analysis of atmospheric sub-micron particle data
Arizabalo, Rubén Darío; González-Ávalos, Eugenio; Korvin, Gabor
2015-03-01
Multifractal analysis was used to describe air pollution by sub-micrometric atmospheric particles. Atmospheric particle concentrations were studied from March 31 to April 21, 2006, as part of the MILAGRO campaign at the Jasso Station by means of an SMPS. Sixteen campaign days were selected to carry out the multifractal analysis of the experimental data through Singularity Spectra f(α). In this work, the roughness/smoothness feature of atmospheric particle distributions was studied by means of the Hölder exponent (α), which can be associated with the intensity of particle emissions through time and the randomness of the external emission sources. Multifractal analysis has been found to be a useful tool to establish intensity fluctuations of atmospheric data.
Automatic detection of microcalcifications with multi-fractal spectrum.
Ding, Yong; Dai, Hang; Zhang, Hang
2014-01-01
For improving the detection of micro-calcifications (MCs), this paper proposes an automatic detection of MC system making use of multi-fractal spectrum in digitized mammograms. The approach of automatic detection system is based on the principle that normal tissues possess certain fractal properties which change along with the presence of MCs. In this system, multi-fractal spectrum is applied to reveal such fractal properties. By quantifying the deviations of multi-fractal spectrums between normal tissues and MCs, the system can identify MCs altering the fractal properties and finally locate the position of MCs. The performance of the proposed system is compared with the leading automatic detection systems in a mammographic image database. Experimental results demonstrate that the proposed system is statistically superior to most of the compared systems and delivers a superior performance.
Coupled uncertainty provided by a multifractal random walker
Energy Technology Data Exchange (ETDEWEB)
Koohi Lai, Z. [Department of Physics, Firoozkooh Branch, Islamic Azad University, Firoozkooh (Iran, Islamic Republic of); Vasheghani Farahani, S. [Department of Physics, Tafresh University, P.O. Box 39518-79611, Tafresh (Iran, Islamic Republic of); Movahed, S.M.S. [Department of Physics, Shahid Beheshti University, G.C., Evin, Tehran 19839 (Iran, Islamic Republic of); The Abdus Salam International Centre for Theoretical Physics, Strada Costiera, 11, Trieste 34151 (Italy); Jafari, G.R., E-mail: g_jafari@sbu.ac.ir [Department of Physics, Shahid Beheshti University, G.C., Evin, Tehran 19839 (Iran, Islamic Republic of)
2015-10-09
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 Detrended Cross-Correlation Analysis of agricultural futures markets
Energy Technology Data Exchange (ETDEWEB)
He Lingyun, E-mail: lyhe@amss.ac.cn [Center for Futures and Financial Derivatives, College of Economics and Management, China Agricultural University, Beijing 100083 (China); Chen Shupeng [Center for Futures and Financial Derivatives, College of Economics and Management, China Agricultural University, Beijing 100083 (China)
2011-06-15
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 and greater than the latter 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 and greater than the averaged GHE when q > 0.
Kondo, Taro; Baba, Jumpei; Yokoyama, Akihiko
In recent years, there is a great deal of interest in distributed generations from viewpoints of environmental problem and energy saving measure. Thus, a lot of distributed generators will be connected to the distribution network in the future. However, increase of distributed generators, which convert natural energy into electric energy, is concerned on their adverse effects on distribution network. Therefore, control of distribution networks using Flexible AC Transmission System (FACTS) devices is considered in order to adjust the voltage profile, and as a result more distributed generations can be installed into the networks. In this paper, four types of FACTS devices, Static Synchronous Compensator (STATCOM), Static Synchronous Series Compensator (SSSC), Unified Power Flow Controller (UPFC) and self-commutated Back-To-Back converter (BTB), are analyzed by comparison of required minimum capacity of the inverters in a residential distribution network with a large penetration of photovoltaic generations.
Multi-Fraction Bayesian Sediment Transport Model
Directory of Open Access Journals (Sweden)
Mark L. Schmelter
2015-09-01
Full Text Available A Bayesian approach to sediment transport modeling can provide a strong basis for evaluating and propagating model uncertainty, which can be useful in transport applications. Previous work in developing and applying Bayesian sediment transport models used a single grain size fraction or characterized the transport of mixed-size sediment with a single characteristic grain size. Although this approach is common in sediment transport modeling, it precludes the possibility of capturing processes that cause mixed-size sediments to sort and, thereby, alter the grain size available for transport and the transport rates themselves. This paper extends development of a Bayesian transport model from one to k fractional dimensions. The model uses an existing transport function as its deterministic core and is applied to the dataset used to originally develop the function. The Bayesian multi-fraction model is able to infer the posterior distributions for essential model parameters and replicates predictive distributions of both bulk and fractional transport. Further, the inferred posterior distributions are used to evaluate parametric and other sources of variability in relations representing mixed-size interactions in the original model. Successful OPEN ACCESS J. Mar. Sci. Eng. 2015, 3 1067 development of the model demonstrates that Bayesian methods can be used to provide a robust and rigorous basis for quantifying uncertainty in mixed-size sediment transport. Such a method has heretofore been unavailable and allows for the propagation of uncertainty in sediment transport applications.
Exoplanetary Detection by Multifractal Spectral Analysis
Agarwal, Sahil; Del Sordo, Fabio; Wettlaufer, John S.
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.
Multifractal behavior of commodity markets: Fuel versus non-fuel products
Delbianco, Fernando; Tohmé, Fernando; Stosic, Tatijana; Stosic, Borko
2016-09-01
We investigate multifractal properties of commodity time series using multifractal detrended fluctuation analysis (MF-DFA). We find that agricultural and energy-related commodities exhibit very similar behavior, while the multifractal behavior of daily and monthly commodity series is rather different. Daily series demonstrate overall uncorrelated behavior, lower degree of multifractality and the dominance of small fluctuations. On the other hand, monthly commodity series show overall persistent behavior, higher degree of multifractality and the dominance of large fluctuations. After shuffling the series, we find that the multifractality is due to a broad probability density function for daily commodities series, while for monthly commodities series multifractality is caused by both a broad probability density function and long term correlations.
Lacunarity Analyses of Multifractal and Natural Grayscale Patterns
Roy, Ankur; Perfect, Edmund
2014-09-01
Lacunarity (L) is a scale (r)-dependent parameter that was developed for quantifying clustering in fractals and has subsequently been employed to characterize various natural patterns. For multifractals it can be shown analytically that L is related to the correlation dimension, D2, by: dlog(L)/dlog(r) = D2 - 2. We empirically tested this equation using two-dimensional multifractal grayscale patterns with known correlation dimensions. These patterns were analyzed for their lacunarity using the gliding-box algorithm. D2 values computed from the dlog(L)/dlog(r) analysis gave a 1:1 relationship with the known D2 values. Lacunarity analysis was also employed in discriminating between multifractal grayscale patterns with the same D2 values, but different degrees of scale-dependent clustering. For this purpose, a new lacunarity parameter, , was formulated based on the weighted mean of the log-transformed lacunarity values at different scales. This approach was further used to evaluate scale-dependent clustering in soil thin section grayscale images that had previously been classified as multifractals based on standard method of moments box-counting. Our results indicate that lacunarity analysis may be a more sensitive indicator of multifractal behavior in natural grayscale patterns than the standard approach. Thus, multifractal behavior can be checked without having to compute the whole spectrum of non-integer dimensions, Dq(-∞ parameter should be useful to researchers who want to explore the correlative influence of clustering on flow and transport in grayscale representations of soil aggregates and heterogeneous aquifers.
A Study of the Next Generation Intelligent Networks Interworking with IP Networks
Institute of Scientific and Technical Information of China (English)
无
2001-01-01
In the past three years, the author has participated in several projects involved in Intelligent Network (IN). In 1997, we started our research on the project “The Integration of IN and B-ISDN” supported by National Science Foundation. Since 1999, the author has engaged in the project “the Next Generation IN Based Service Platform Interworking with IP Networks” supported by the National 863 Project. While working on the project, the author made a deep research on the architecture and the key technology of the next generation IN defined by ITU-T IN CS3 and CS4. In the following parts. 1. I conclude the research work and the innovation in my dissertation. The early research on the interworking of IN and Internet, despite the shortage of materials, the interworking architecture by means of IAF is analyzed. Some key techniques like triggering intelligent service and reporting dynamic IP address are solved. Some new SIBs and INAPs are added, and the dial-up software of users is enhanced, too. The incoming call notification service is designed. What we have done paves the way for the future research. 2. The gateway based architecture for the interworking of IN and Internet is described. Considering the research results from ITU, PINT work group and TIPHON work group, we emphasize that the interworking scenario through MG,SCG and C/BG is promising. Based on the CIN software developed by ourselves, we provide the scenario to enhance the function entities and signaling protocol. We address the function of entities and the interaction of signaling with an example like ICW service. 3. With the introduction of mobile agent technology, the author proposes the distributed IN which can be integrated with IP networks. According to the drawbacks of the centralized IN, we address the architecture and conceptual model of distributed IN to support advanced service in IP Telephony. We try to illustrate the role and relationship between function entities. We also present a
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...
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.
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......-Wolfe reformulation and a novel column generation framework to solve the problem efficiently. Preliminary results are presented for the IEEE-118 bus network with 19 generator units. Active switching is shown to reduce total cost by up to 15 % for a particular 24-hour period. Furthermore, the need for generator...
Active biopolymer networks generate scale-free but euclidean clusters
Sheinman, M; Alvarado, J; Koenderink, G H; MacKintosh, F C
2014-01-01
We report analytical and numerical modelling of active elastic networks, motivated by experiments on crosslinked actin networks contracted by myosin motors. Within a broad range of parameters, the motor-driven collapse of active elastic networks leads to a critical state. We show that this state is qualitatively different from that of the random percolation model. Intriguingly, it possesses both euclidean and scale-free structure with Fisher exponent smaller than $2$. Remarkably, an indistinguishable Fisher exponent and the same euclidean structure is obtained at the critical point of the random percolation model after absorbing all enclaves into their surrounding clusters. We propose that in the experiment the enclaves are absorbed due to steric interactions of network elements. We model the network collapse, taking into account the steric interactions. The model shows how the system robustly drives itself towards the critical point of the random percolation model with absorbed enclaves, in agreement with th...
Recurrent Network Models of Sequence Generation and Memory.
Rajan, Kanaka; Harvey, Christopher D; Tank, David W
2016-04-01
Sequential activation of neurons is a common feature of network activity during a variety of behaviors, including working memory and decision making. Previous network models for sequences and memory emphasized specialized architectures in which a principled mechanism is pre-wired into their connectivity. Here we demonstrate that, starting from random connectivity and modifying a small fraction of connections, a largely disordered recurrent network can produce sequences and implement working memory efficiently. We use this process, called Partial In-Network Training (PINning), to model and match cellular resolution imaging data from the posterior parietal cortex during a virtual memory-guided two-alternative forced-choice task. Analysis of the connectivity reveals that sequences propagate by the cooperation between recurrent synaptic interactions and external inputs, rather than through feedforward or asymmetric connections. Together our results suggest that neural sequences may emerge through learning from largely unstructured network architectures.
Channel modeling for fifth generation cellular networks and wireless sensor networks
Torabi, Amir
In view of exponential growth in data traffic demand, the wireless communications industry has aimed to increase the capacity of existing networks by 1000 times over the next 20 years. A combination of extreme cell densification, more bandwidth, and higher spectral efficiency is needed to support the data traffic requirements for fifth generation (5G) cellular communications. In this research, the potential improvements achieved by using three major 5G enabling technologies (i.e., small cells, millimeter-wave spectrum, and massive MIMO) in rural and urban environments are investigated. This work develops SPM and KA-based ray models to investigate the impact of geometrical parameters on terrain-based multiuser MIMO channel characteristic. Moreover, a new directional 3D channel model is developed for urban millimeter-wave (mmW) small cells. Path-loss, spatial correlation, coverage distance, and coherence length are studied in urban areas. Exploiting physical optics (PO) and geometric optics (GO) solutions, closed form expressions are derived for spatial correlation. Achievable spatial diversity is evaluated using horizontal and vertical linear arrays as well as planar 2D arrays. In another study, a versatile near-ground field prediction model is proposed to facilitate accurate wireless sensor network (WSN) simulations. Monte Carlo simulations are used to investigate the effects of antenna height, frequency of operation, polarization, and terrain dielectric and roughness properties on WSNs performance.
Multifractal properties of solar wind turbulence: theory and observations.
Milovanov, A. V.; Avanov, L. A.; Zastenker, G. N.; Zelenyj, L. M.
1996-10-01
A fractal model of the solar wind is presented. This model treats fluctuations of the solar wind velocity from the viewpoint of nonlinear processes originating in the convective region and photosphere of the Sun. The multifractal structure of proton velocity fluctuations in a region of heliocentric distances from 0.2 to 0.8 AU is a result of these processes. Continuous measurements of solar wind velocity aboard the ISEE-3 spacecraft during one month were used to compare the theoretical and experimental results. It is shown that fluctuations of proton velocity have a multifractal structure in a frequency range of 10-5 - 10-3Hz.
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...
Multifractal analysis of dynamic infrared imaging of breast cancer
Gerasimova, E.; Audit, B.; Roux, S. G.; Khalil, A.; Argoul, F.; Naimark, O.; Arneodo, A.
2013-12-01
The wavelet transform modulus maxima (WTMM) method was used in a multifractal analysis of skin breast temperature time-series recorded using dynamic infrared (IR) thermography. Multifractal scaling was found for healthy breasts as the signature of a continuous change in the shape of the probability density function (pdf) of temperature fluctuations across time scales from \\sim0.3 to 3 s. In contrast, temperature time-series from breasts with malignant tumors showed homogeneous monofractal temperature fluctuations statistics. These results highlight dynamic IR imaging as a very valuable non-invasive technique for preliminary screening in asymptomatic women to identify those with risk of breast cancer.
Variable bit rate video traffic modeling by multiplicative multifractal model
Institute of Scientific and Technical Information of China (English)
Huang Xiaodong; Zhou Yuanhua; Zhang Rongfu
2006-01-01
Multiplicative multifractal process could well model video traffic. The multiplier distributions in the multiplicative multifractal model for video traffic are investigated and it is found that Gaussian is not suitable for describing the multipliers on the small time scales. A new statistical distribution-symmetric Pareto distribution is introduced. It is applied instead of Gaussian for the multipliers on those scales. Based on that, the algorithm is updated so that symmetric pareto distribution and Gaussian distribution are used to model video traffic but on different time scales. The simulation results demonstrate that the algorithm could model video traffic more accurately.
Coupled uncertainty provided by a multifractal random walker
Lai, Z Koohi; 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.
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.
Zhu, Chen-Ping; Yang, Hui-Jie; Xiong, Shi-Jie; Gu, Zhi-Ming; Shi, Da-Ning; He, Da-Ren; Wang, Bing-Hong
2007-01-01
Competitive exclusion, a key principle of ecology, can be generalized to understand many other complex systems. Individuals under surviving pressure tend to be different from others, and correlations among them change correspondingly to the updating of their states. We show with numerical simulation that these aptitudes can contribute to group formation or speciation in social fields. Moreover, they can lead to power-law topological correlations of complex networks. By coupling updating states of nodes with variation of connections in a network, structural properties with power-laws and functions like multifractality, spontaneous ranking and evolutionary branching of node states can emerge out simultaneously from the present self-organized model of coevolutionary process.
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
MULTIFRACTAL ANALYSIS OF PROTEIN AGGREGATES TO DERIVE PROTEIN-SPECIFIC SIGNATURE
Directory of Open Access Journals (Sweden)
Hrishikesh Mishra, Tapobrata Lahiri*
2010-11-01
Full Text Available Deriving a property of a protein that is unique to it has well known significance since the study on ab initio model based derivation of protein structure where uniqueness of protein sequence is taken as the source of specificity of protein structure. In this direction, Heat denatured protein aggregates (HDPA of proteins were studied with an objective to derive some multi-fractal markers specific to constituent protein that may be further utilized to extract information of the seed protein. Since Ordinary microscopic images of aggregates were analyzed to extract Intensity Level-based Multifractal Dimension (ILMFD features. ILMFD features include four different features, perimeter fractal dimension (ILMFDP, perimeter-area relationship (ILMFDPAR, Area fractal dimension (ILMFDA and Perimeter-area fractal dimension (ILMFDPA that were calculated using fractal computations considering perimeter, and area of aggregate images. Feed forward backpropagation network was used to classify the proteins using different ILMFD parameters. It was found that ILMFD features could discriminate the proteins used in our study, that points to their potential to serve as unique property or marker of a protein. Further to validate the results, the outputs from ANN were clustered, and the outputs clustered in the largest cluster were found to significantly improve the result in class decision given by ANN.
COMPARATIVE STUDY OF NEXT GENERATION HIGH SPEED WIRELESS NETWORK
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RAHUL MALHOTRA
2011-06-01
Full Text Available Advances in mobile communication theory have enabled the development of different wireless access technologies. Alongside the revolutionary progress in wireless access technologies, advances in wireless access devices such as laptops, palmtops, and cell phones and mobile middleware have paved the way for the deliveryof beyond-voice-type services while on the move. This sets the platform for high-speed mobile communications that provide high-speed data and both real and non-real time multimedia to mobile users. Today's wireless world uses several communication infrastructures such as Bluetooth for personal area, IEEE 802.11 for local area,Universal Mobile Telecommunication System (UMTS for wide area, and Satellite networks for global networking other hand, since these wireless networks are complementary to each other, their integration and coordinated operation can provide ubiquitous “always best connection" quality mobile communications to the users. This paper discusses the different architectures of wireless networks and the different factors to be considered while designing a hybrid wireless network. The different factors to be considered for design of ahybrid wireless network and the different networks have been explored in this paper.
Intelligent Joint Admission Control for Next Generation Wireless Networks
Directory of Open Access Journals (Sweden)
Abdulqader M. Mohsen
2012-04-01
Full Text Available The Heterogeneous Wireless Network (HWN integrates different wireless networks into one common network. The integrated networks often overlap coverage in the same wireless service areas, leading to the availability of a great variety of innovative services based on user demands in a cost-efficient manner. Joint Admission Control (JAC handles all new or handoff service requests in the HWN. It checks whether the incoming service request to the selected Radio Access Network (RAN by the initial access network selection or the vertical handover module can be admitted and allocated the suitable resources. In this paper, a decision support system is developed to address the JAC problem in the modern HWN networks. This system combines fuzzy logic and the PROMETHEE II multiple criteria decision making system algorithm, to the problem of JAC. This combination decreases the influence of the dissimilar, imprecise, and contradictory measurements for the JAC criteria coming from different sources. A performance analysis is done and the results are compared with traditional algorithms for JAC. These results demonstrate a significant improvement with our developed algorithm.
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...
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
A space-time multifractal analysis on radar rainfall sequences from central Poland
Licznar, Paweł; Deidda, Roberto
2014-05-01
Rainfall downscaling belongs to most important tasks of modern hydrology. Especially from the perspective of urban hydrology there is real need for development of practical tools for possible rainfall scenarios generation. Rainfall scenarios of fine temporal scale reaching single minutes are indispensable as inputs for hydrological models. Assumption of probabilistic philosophy of drainage systems design and functioning leads to widespread application of hydrodynamic models in engineering practice. However models like these covering large areas could not be supplied with only uncorrelated point-rainfall time series. They should be rather supplied with space time rainfall scenarios displaying statistical properties of local natural rainfall fields. Implementation of a Space-Time Rainfall (STRAIN) model for hydrometeorological applications in Polish conditions, such as rainfall downscaling from the large scales of meteorological models to the scale of interest for rainfall-runoff processes is the long-distance aim of our research. As an introduction part of our study we verify the veracity of the following STRAIN model assumptions: rainfall fields are isotropic and statistically homogeneous in space; self-similarity holds (so that, after having rescaled the time by the advection velocity, rainfall is a fully homogeneous and isotropic process in the space-time domain); statistical properties of rainfall are characterized by an "a priori" known multifractal behavior. We conduct a space-time multifractal analysis on radar rainfall sequences selected from the Polish national radar system POLRAD. Radar rainfall sequences covering the area of 256 km x 256 km of original 2 km x 2 km spatial resolution and 15 minutes temporal resolution are used as study material. Attention is mainly focused on most severe summer convective rainfalls. It is shown that space-time rainfall can be considered with a good approximation to be a self-similar multifractal process. Multifractal
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.
Global, Computer-generated Map of Valley Networks on Mars
Luo, W.; Stepinski, T. F.
2009-03-01
The new, global map of valley networks on Mars has been created entirely by a computer algorithm parsing topographic data. Dependencies between dissection density and its potential controlling factors are derived and discussed.
Directory of Open Access Journals (Sweden)
Do Nguyet Quang
2014-02-01
Full Text Available In smart grid communication implementation, network traffic pattern is one of the main factors that affect the system’s performance. Examining different traffic patterns in smart grid is therefore crucial when analyzing the network performance. Due to the heterogeneous and hybrid nature of smart grid, the type of traffic distribution in the network is still unknown. The traffic that popularly used for simulation and analysis no longer reflects the real traffic in a multi-technology and bi-directional communication system. Hence, in this study, a single-board computer is implemented as a traffic generator which can generate network traffic similar to those generated by various applications in the fully operational smart grid. By placing in a strategic and appropriate position, a collection of traffic generators allow network administrators to investigate and test the effect of heavy traffic on performance of smart grid communication system.
40G and 100G modules enable next generation networks
Hong, Jin; Schmidt, Ted; Traverso, Matt; Yoshikazu, Era
2009-11-01
With the wide scale deployment of 40Gbps in carrier networks underway and 100Gbps products on the horizon, 40Gbps and 100Gbps modules based on Multi Source Agreements (MSA) are gaining considerable interest and market acceptance. This paper discusses developments in 40Gbps and 100Gbps line side DWDM MSA modules and CFP based client side MSA modules as suppliers strive to address various system and network applications.
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.
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
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.
Ethernet-Based Services for Next Generation Networks
Hernandez-Valencia, Enrique
Over the last few years, Ethernet technology and services have emerged as an indispensable component of the broadband networking and telecommunications infrastructure, both for network operators and service providers. As an example, Worldwide Enterprise customer demand for Ethernet services by itself is expected to hit the 30B US mark by year 2012. Use of Ethernet technology in the feeder networks that support residential applications, such as "triple play" voice, data, and video services, is equally on the rise. As the synergies between packet-aware transport and service oriented equipment continue to be exploited in the path toward transport convergence. Ethernet technology is expected to play a critical part in the evolution toward converged Optical/Packet Transport networks. Here we discuss the main business motivations, services, and technologies driving the specifications of so-called carrier Ethernet and highlight challenges associated with delivering the expectations for low implementation complexity, easy of use, provisioning and management of networks and network elements embracing this technology.
Perelló, Josep; Masoliver, Jaume; Kasprzak, Andrzej; Kutner, Ryszard
2008-09-01
Social, technological, and economic time series are divided by events which are usually assumed to be random, albeit with some hierarchical structure. It is well known that the interevent statistics observed in these contexts differs from the Poissonian profile by being long-tailed distributed with resting and active periods interwoven. Understanding mechanisms generating consistent statistics has therefore become a central issue. The approach we present is taken from the continuous-time random-walk formalism and represents an analytical alternative to models of nontrivial priority that have been recently proposed. Our analysis also goes one step further by looking at the multifractal structure of the interevent times of human decisions. We here analyze the intertransaction time intervals of several financial markets. We observe that empirical data describe a subtle multifractal behavior. Our model explains this structure by taking the pausing-time density in the form of a superstatistics where the integral kernel quantifies the heterogeneous nature of the executed tasks. A stretched exponential kernel provides a multifractal profile valid for a certain limited range. A suggested heuristic analytical profile is capable of covering a broader region.
Multifraction separation in countercurrent chromatography (MCSGP).
Krättli, Martin; Müller-Späth, Thomas; Morbidelli, Massimo
2013-09-01
The multicolumn countercurrent solvent gradient purification (MCSGP) process is a continuous countercurrent multicolumn chromatography process capable of performing three fraction separations while applying a linear gradient of some modifier. This process can then be used either for the purification of a single species from a multicomponent mixture or to separate a three component mixture in one single operation. In this work, this process is extended to the separation of multifractions, in principle with no limitation. To achieve this goal the MCSGP standard process is extended by introducing one extra separation section per extra fraction to be isolated. Such an extra separation section is realized in this work through a single additional column, so that a n fraction MCSGP process can be realized using a minimum of n columns. Two separation processes were considered to experimentally demonstrate the possibility of realizing a four-fraction MCSGP unit able to purify two intermediate products in a given multicomponent mixture. The first one was a model mixture containing four different proteins. The two proteins eluting in the center of the chromatogram were purified with yields equal to 95% for the early eluting and 92% for the later eluting one. The corresponding purities were 94% and 97%, respectively. Such performance was well superior to that of the batch operation with the same modifier gradient which for the same purity values could not achieve yields larger than 67% and 81%, respectively. Similar performance improvements were found for the second separation where two out of seven charge variants which constitute the mAb Cetuximab currently available on the market have been purified in one single operation using a four-fraction MCSGP unit. In this case, yields of 81% and 65% were obtained with purities of 90% and 89%, respectively. These data compare well with the corresponding data from batch chromatography where with the same gradient and for the same
Reinforcement-Based Fuzzy Neural Network ontrol with Automatic Rule Generation
Institute of Scientific and Technical Information of China (English)
无
1999-01-01
A reinforcemen-based fuzzy neural network control with automatic rule generation RBFNNC) is pro-posed. A set of optimized fuzzy control rules can be automatically generated through reinforcement learning based onthe state variables of object system. RBFNNC was applied to a cart-pole balancing system and simulation resultshows significant improvements on the rule generation.
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
Power Optimization Techniques for Next Generation Wireless Networks
Directory of Open Access Journals (Sweden)
Ratheesh R
2016-02-01
Full Text Available The massive data traffic and the need for high speed wireless communication is increasing day by day corresponds to an exponential increase in the consumption of power by Information and Communication Technology (ICT sector. Reducing consumption of power in wireless network is a challenging topic and has attracted the attention of researches around the globe. Many techniques like multiple-input multiple-output (MIMO, cognitive radio, cooperative heterogeneous communications and new network strategies such as heterogeneous networks, scattered antennas, multi-hop communication, etc., as well as radio and resource managing techniques like various sleep mode algorithms, cross layer optimization etc., have been proposed as solutions for this problem. In this paper, we present an overview of some of these techniques to optimize power in cellular network and MANET from various literatures. The green energy approaches as an alternate to grid power to optimize power consumption of BS is also reviewed. We also proposed a methodology to optimize power consumption in LTE-A network by jointly deploying RSs at cell edges.
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.
Nonlinear dynamics of wind waves: multifractal phase/time effects
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R. H. Mellen
1994-01-01
Full Text Available In addition to the bispectral coherence method, phase/time analysis of analytic signals is another promising avenue for the investigation of phase effects in wind waves. Frequency spectra of phase fluctuations obtained from both sea and laboratory experiments follow an F-β power law over several decades, suggesting that a fractal description is appropriate. However, many similar natural phenomena have been shown to be multifractal. Universal multifractals are quantified by two additional parameters: the Lévy index 0 α 2 for the type of multifractal and the co-dimension 0 C1 1 for intermittence. The three parameters are a full statistical measure the nonlinear dynamics. Analysis of laboratory flume data is reported here and the results indicate that the phase fluctuations are 'hard multifractal' (α > 1. The actual estimate is close to the limiting value α = 2, which is consistent with Kolmogorov's lognormal model for turbulent fluctuations. Implications for radar and sonar backscattering from the sea surface are briefly considered.
A NOTE ON MULTIFRACTAL PACKING DIMENSION OF MEASURES
Institute of Scientific and Technical Information of China (English)
Jinjun Li
2009-01-01
The relations between the multifractal packing dimension of Borel probability measures and the asymptotic behavior of the function φ*(x)=lim sup/r→0 logv(V(x, r))-qlogμ(B(x, r))/logr are discussed and some applications are given.
Multifractal Analysis of Local Entropies for Gibbs Measures
Takens, Floris; Verbitski, Evgeni
1998-01-01
Recently a complete multifractal analysis of local dimensions, entropies and Lyapunov exponents of conformal expanding maps and surface Axion A diffeomorphisms for Gibbs measures was performed. The main goal of this was primarily the analysis of the local (pointwise) dimensions. This is an extremely
Multifractal and mechanical analysis of amorphous solid dispersions.
Adler, Camille; Teleki, Alexandra; Kuentz, Martin
2017-03-09
The formulation of lipophilic and hydrophobic compounds is a challenge for the pharmaceutical industry and it requires the development of complex formulations. Our first aim was to investigate hot-melt extrudate microstructures by means of multifractal analysis using scanning electron microscopy imaging. Since the microstructure can affect solid dosage form performance such as mechanical properties, a second objective was to study the influence of the type of adsorbent and of the presence of an amorphous compound on extrudate hardness. β-Carotene (BC) was chosen as poorly water-soluble model compound. Formulations containing a polymer, a lipid and two different silica based inorganic carriers were produced by hot-melt extrusion. Based on scanning electron microscopy/energy dispersive X-ray spectroscopy, the obtained images were analyzed using multifractal formalism. The breaking force of the strands was assessed by a three point bending test. Multifractal analysis and three point bending results showed that the nature of interparticle interactions in the inorganic carrier as well as the presence of amorphous BC had an influence on the microstructure and thus on the mechanical performance. The use of multifractal analysis and the study of the mechanical properties were complementary to better characterize and understand complex formulations obtained by hot-melt extrusion.
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.
H.264/AVC Video Compressed Traces: Multifractal and Fractal Analysis
Directory of Open Access Journals (Sweden)
Samčović Andreja
2006-01-01
Full Text Available Publicly available long video traces encoded according to H.264/AVC were analyzed from the fractal and multifractal points of view. It was shown that such video traces, as compressed videos (H.261, H.263, and MPEG-4 Version 2 exhibit inherent long-range dependency, that is, fractal, property. Moreover they have high bit rate variability, particularly at higher compression ratios. Such signals may be better characterized by multifractal (MF analysis, since this approach describes both local and global features of the process. From multifractal spectra of the frame size video traces it was shown that higher compression ratio produces broader and less regular MF spectra, indicating to higher MF nature and the existence of additive components in video traces. Considering individual frames (I, P, and B and their MF spectra one can approve additive nature of compressed video and the particular influence of these frames to a whole MF spectrum. Since compressed video occupies a main part of transmission bandwidth, results obtained from MF analysis of compressed video may contribute to more accurate modeling of modern teletraffic. Moreover, by appropriate choice of the method for estimating MF quantities, an inverse MF analysis is possible, that means, from a once derived MF spectrum of observed signal it is possible to recognize and extract parts of the signal which are characterized by particular values of multifractal parameters. Intensive simulations and results obtained confirm the applicability and efficiency of MF analysis of compressed video.
Multifractal Decomposition of Statistically Self-Similar Sets
Institute of Scientific and Technical Information of China (English)
Jing Hu YU; Di He HU
2001-01-01
Let K be a statistically self-similar set defined by Graf. In this paper, we construct arandom measure p which is supported by K and study the multifractal decomposition for K with p.Under such a decomposition, we obtain the expression of the spectrum function f(α).
Media access control and resource allocation for next generation passive optical networks
Ansari, Nirwan
2013-01-01
This book focuses on various Passive optical networks (PONs) types, including currently deployed Ethernet PON (EPON) and Gigabit PON (GPON) as well as next generation WDM PON and OFDM PON. Also this book examines the integrated optical and wireless access networks. Concentrating on two issues in these networks: media access control (MAC) and resource allocation. These two problems can greatly affect performances of PONs such as network resource utilization and QoS of end users. Finally this book will discuss various solutions to address the MAC and resource allocation issues in various PON networks.
Developing an Efficient DMCIS with Next-Generation Wireless Networks
Pathan, Al-Sakib Khan
2007-01-01
The impact of extreme events across the globe is extraordinary which continues to handicap the advancement of the struggling developing societies and threatens most of the industrialized countries in the globe. Various fields of Information and Communication Technology have widely been used for efficient disaster management; but only to a limited extent though, there is a tremendous potential for increasing efficiency and effectiveness in coping with disasters with the utilization of emerging wireless network technologies. Early warning, response to the particular situation and proper recovery are among the main focuses of an efficient disaster management system today. Considering these aspects, in this paper we propose a framework for developing an efficient Disaster Management Communications and Information System (DMCIS) which is basically benefited by the exploitation of the emerging wireless network technologies combined with other networking and data processing technologies.
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.
Black holes in multi-fractional and Lorentz-violating models
Calcagni, Gianluca; Rodríguez Fernández, David; Ronco, Michele
2017-05-01
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.
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.
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.
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
Assessing microstructures of pyrrhotites in basalts by multifractal analysis
Directory of Open Access Journals (Sweden)
S. Xie
2010-07-01
Full Text Available Understanding and describing spatial arrangements of mineral particles and determining the mineral distribution structure are important to model the rock-forming process. Geometric properties of individual mineral particles can be estimated from thin sections, and different models have been proposed to quantify the spatial complexity of mineral arrangement. The Gejiu tin-polymetallic ore-forming district, located in Yunnan province, southwestern China, is chosen as the study area. The aim of this paper is to apply fractal and multifractal analysis to quantify distribution patterns of pyrrhotite particles from twenty-eight binary images obtained from seven basalt segments and then to discern the possible petrological formation environments of the basalts based on concentrations of trace elements. The areas and perimeters of pyrrhotite particles were measured for each image. Perimeter-area fractal analysis shows that the perimeter and area of pyrrhotite particles follow a power-law relationship, which implies the scale-invariance of the shapes of the pyrrhotites. Furthermore, the spatial variation of the pyrrhotite particles in space was characterized by multifractal analysis using the method of moments. The results show that the average values of the area-perimeter exponent (D_{AP}, the width of the multifractal spectra (Δ(D(0−D(2 and Δ(D(q_{min}−D(q_{max} and the multifractality index (τ"(1 for the pyrrhotite particles reach their minimum in the second basalt segment, which implies that the spatial arrangement of pyrrhotite particles in Segment 2 is less heterogeneous. Geochemical trace element analysis results distinguish the second basalt segment sample from other basalt samples. In this aspect, the fractal and multifractal analysis may provide new insights into the quantitative assessment of mineral microstructures which may be closely associated with the petrogenesis as shown by the
Automatic Security Assessment for Next Generation Wireless Mobile Networks
Directory of Open Access Journals (Sweden)
Francesco Palmieri
2011-01-01
Full Text Available Wireless networks are more and more popular in our life, but their increasing pervasiveness and widespread coverage raises serious security concerns. Mobile client devices potentially migrate, usually passing through very light access control policies, between numerous and heterogeneous wireless environments, bringing with them software vulnerabilities as well as possibly malicious code. To cope with these new security threats the paper proposes a new active third party authentication, authorization and security assessment strategy in which, once a device enters a new Wi-Fi environment, it is subjected to analysis by the infrastructure, and if it is found to be dangerously insecure, it is immediately taken out from the network and denied further access until its vulnerabilities have been fixed. The security assessment module, that is the fundamental component of the aforementioned strategy, takes advantage from a reliable knowledge base containing semantically-rich information about the mobile node under examination, dynamically provided by network mapping and configuration assessment facilities. It implements a fully automatic security analysis framework, based on AHP, which has been conceived to be flexible and customizable, to provide automated support for real-time execution of complex security/risk evaluation tasks which depends on the results obtained from different kind of analysis tools and methodologies. Encouraging results have been achieved utilizing a proof-of-concept model based on current technology and standard open-source networking tools.
Zulai, Luis G. T.; Durand, Fábio R.; Abrão, Taufik
2015-05-01
In this article, an energy-efficiency mechanism for next-generation passive optical networks is investigated through heuristic particle swarm optimization. Ten-gigabit Ethernet-wavelength division multiplexing optical code division multiplexing-passive optical network next-generation passive optical networks are based on the use of a legacy 10-gigabit Ethernet-passive optical network with the advantage of using only an en/decoder pair of optical code division multiplexing technology, thus eliminating the en/decoder at each optical network unit. The proposed joint mechanism is based on the sleep-mode power-saving scheme for a 10-gigabit Ethernet-passive optical network, combined with a power control procedure aiming to adjust the transmitted power of the active optical network units while maximizing the overall energy-efficiency network. The particle swarm optimization based power control algorithm establishes the optimal transmitted power in each optical network unit according to the network pre-defined quality of service requirements. The objective is controlling the power consumption of the optical network unit according to the traffic demand by adjusting its transmitter power in an attempt to maximize the number of transmitted bits with minimum energy consumption, achieving maximal system energy efficiency. Numerical results have revealed that it is possible to save 75% of energy consumption with the proposed particle swarm optimization based sleep-mode energy-efficiency mechanism compared to 55% energy savings when just a sleeping-mode-based mechanism is deployed.
Intrinsic bursters increase the robustness of rhythm generation in an excitatory network.
Purvis, L K; Smith, J C; Koizumi, H; Butera, R J
2007-02-01
The pre-Botzinger complex (pBC) is a vital subcircuit of the respiratory central pattern generator. Although the existence of neurons with pacemaker-like bursting properties in this network is not questioned, their role in network rhythmogenesis is unresolved. Modeling is ideally suited to address this debate because of the ease with which biophysical parameters of individual cells and network architecture can be manipulated. We modeled the parameter variability of experimental data from pBC bursting pacemaker and nonpacemaker neurons using a modified version of our previously developed pBC neuron and network models. To investigate the role of pacemakers in networkwide rhythmogenesis, we simulated networks of these neurons and varied the fraction of the population made up of pacemakers. For each number of pacemaker neurons, we varied the amount of tonic drive to the network and measured the frequency of synchronous networkwide bursting produced. Both excitatory networks with all-to-all coupling and sparsely connected networks were explored for several levels of synaptic coupling strength. Networks containing only nonpacemakers were able to produce networkwide bursting, but with a low probability of bursting and low input and output ranges. Our results indicate that inclusion of pacemakers in an excitatory network increases robustness of the network by more than tripling the input and output ranges compared with networks containing no pacemakers. The largest increase in dynamic range occurs when the number of pacemakers in the network is greater than 20% of the population. Experimental tests of our model predictions are proposed.
NSGIC GIS Inventory (aka Ramona) — This High Accuracy Reference Network (HARN) dataset, was produced all or in part from Field Survey/GPS information as of 1993. It is described as 'Points generated...
Column generation for studying capacity and energy trade-off in LTE-like network
Ouni, Anis; Rivano, Hervé; Valois, Fabrice
2010-01-01
In this paper, we focus on broadband wireless mesh networks like 3GPP LTE-Advanced. This technology is a key enabler for next generation cellular networks which are about to increase by an order of magnitude the capacity provided to users. Such an objective needs a significative densification of cells which requires an efficient backhauling infrastructure. In many urban areas as well as under-developed countries, wireless mesh networking is the only available solu- tion. Besides, economical a...
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 performance...... 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....
Génération de signaux multifractals possédant une structure de branchement sous-jacente
Decrouez, Geoffrey
2009-01-01
Fractal geometry, pioneered by Mandelbrot in the 70s, has been recognized in many areas of science. The novelty of this thesis is the generation of fractal and multifractal processes with underlying construction tree. I study two models in particular. The first one is a generalisation of Iterated Function Systems (IFS), introduced by Hutchinson in the early 80s. IFS are an efficient tool to generate fractal sets and functions, by iterating a given set of operators. The idea here is to allow a...
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.
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.
Chen, Y.; Zuurbier, F.S.; Zuylen, H.J. van; Hoogendoorn, S.P.
2006-01-01
This paper presents a generic methodology to generate optimal controlled dynamic prescriptive route guidance to be disseminated by means of variable message signs (VMS). The methodology is generic in the sense it can be used on any network topology and network model, with any number of VMS’s, for di
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…
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…
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.
Mixed Multifractal Analysis of Crude Oil, Gold and Exchange Rate Series
Dai, Meifeng; Shao, Shuxiang; Gao, Jianyu; Sun, Yu; Su, Weiyi
2016-11-01
The multifractal analysis of one time series, e.g. crude oil, gold and exchange rate series, is often referred. In this paper, we apply the classical multifractal and mixed multifractal spectrum to study multifractal properties of crude oil, gold and exchange rate series and their inner relationships. The obtained results show that in general, the fractal dimension of gold and crude oil is larger than that of exchange rate (RMB against the US dollar), reflecting a fact that the price series in gold and crude oil are more heterogeneous. Their mixed multifractal spectra have a drift and the plot is not symmetric, so there is a low level of mixed multifractal between each pair of crude oil, gold and exchange rate series.
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.
User Generated Content Consumption and Social Networking in Knowledge-Sharing OSNs
Lussier, Jake T.; Raeder, Troy; Chawla, Nitesh V.
Knowledge-sharing online social networks are becoming increasingly pervasive and popular. While the user-to-user interactions in these networks have received substantial attention, the consumption of user generated content has not been studied extensively. In this work, we use data gathered from digg.com to present novel findings and draw important sociological conclusions regarding the intimate relationship between consumption and social networking. We first demonstrate that individuals' consumption habits influence their friend networks, consistent with the concept of homophily. We then show that one's social network can also influence the consumption of a submission through the activation of an extended friend network. Finally, we investigate the level of reciprocity, or balance, in the network and uncover relationships that are significantly less balanced than expected.
Vertical Handoff with Predictive Received Signal Strength in Next Generation Wireless Network
Directory of Open Access Journals (Sweden)
Jyoti Madaan
2016-08-01
Full Text Available Since the last few decades, tremendous innovations and inventions have been observed in every field, but especially in wireless network technology. The prevailing demand curves and trends in this particular area of communication show the importance of real-time multimedia applications over several networks with guaranteed quality of service (QoS. The Next Generation Wireless Network (NGWN consists of heterogeneous wireless networks that will grant high data rate and bandwidth to mobile users. The primary aim of Next Generation Wireless Network (NGWN is to conceal heterogeneities and to achieve convergence of diverse networks to provide seamless mobility. So that mobile user can move freely between networks without losing the connection or changing the setting at any moment. When the mobile user moves between different networks, there is a requirement to handover the channel, from one network to another by considering its services, features and user preferences. Channel handover between two different networks is done with the help of vertical handoff (VHO. In a heterogeneous environment, numerous technologies co-exist with their unique characteristics. Therefore, it is very difficult to design efficient handoff decision algorithm. The poorly designed handoff algorithm tends to increase the traffic load and, thereby tend to dramatic decrease in quality of service. A mobile node equipped with multiple network interfaces will be able to access heterogeneous wireless access network. But the availability of alternatives give rise to a problem of unnecessary handoff. To avoid this, we have proposed a decision algorithm based on predictive received signal strength, hysteresis margin and dwell time to select an optimum target network. The handoff policies are designed using received signal strength (RSS, available bandwidth, service cost, user preference, type of application and network condition to reduce the number of handoffs, decision delay
Digital Repository Service at National Institute of Oceanography (India)
Haris, K.; Chakraborty, B.
location (Fig. 1b). Depth-dependent correction Apart from the processing steps described in the preceding subsection, the echo-envelope data require an additional cor- rection for the sonar footprint dimension prior to stochas- tic multifractal analyses... ensemble averaged to obtain a representative stable acous- tic signal (at each location) prior to multifractal analyses. be multifractal over various ranges (Lovejoy and Schertzer, 2007a). However, in the specific case of echo envelopes, the power...
An Expert System Using A Neural Network For Steam Generator Tube Inspection
Energy Technology Data Exchange (ETDEWEB)
Kim, Kilyoo; Huh, Younghwan [Korea Atomic Energy Research Institute, Daejeon (Korea, Republic of); Woo, Heegon; Choi, Sungsoo [Korea Electric Power Corporation, Daejeon (Korea, Republic of)
1991-04-15
An expert system using neural network is built to automatically evaluate eddy current (EC) signals generated during steam generator (S/G) tubes inspection. The system consists of three subsystem, i.e., syntactic pattern recognition subsystem, neural network subsystem and rule based production subsystem. The syntactic pattern recognition subsystem makes it easy to process the vast EC signal data, screens EC signals and detects event signals such as defect signals and structural signals. The neural network subsystem is useful to classify the event signals which often contain noise signals. The expert system implemented on HP 9000/370 workstation also supplies a good EC test data management function.
Semi-automatic simulation model generation of virtual dynamic networks for production flow planning
Krenczyk, D.; Skolud, B.; Olender, M.
2016-08-01
Computer modelling, simulation and visualization of production flow allowing to increase the efficiency of production planning process in dynamic manufacturing networks. The use of the semi-automatic model generation concept based on parametric approach supporting processes of production planning is presented. The presented approach allows the use of simulation and visualization for verification of production plans and alternative topologies of manufacturing network configurations as well as with automatic generation of a series of production flow scenarios. Computational examples with the application of Enterprise Dynamics simulation software comprising the steps of production planning and control for manufacturing network have been also presented.
Next generation communications satellites: multiple access and network studies
Meadows, H. E.; Schwartz, M.; Stern, T. E.; Ganguly, S.; Kraimeche, B.; Matsuo, K.; Gopal, I.
1982-01-01
Efficient resource allocation and network design for satellite systems serving heterogeneous user populations with large numbers of small direct-to-user Earth stations are discussed. Focus is on TDMA systems involving a high degree of frequency reuse by means of satellite-switched multiple beams (SSMB) with varying degrees of onboard processing. Algorithms for the efficient utilization of the satellite resources were developed. The effect of skewed traffic, overlapping beams and batched arrivals in packet-switched SSMB systems, integration of stream and bursty traffic, and optimal circuit scheduling in SSMB systems: performance bounds and computational complexity are discussed.
An Airborne Radar Clutter Tracking Algorithm Based on Multifractal and Fuzzy C-Mean Cluster
Institute of Scientific and Technical Information of China (English)
Wei Zhang; Sheng-Lin Yu; Gong Zhang
2007-01-01
For an airborne lookdown radar, clutter power often changes dynamically about 80 dB with wide distributions as the platform moves. Therefore, clutter tracking techniques are required to guide the selection of const false alarm rate (CFAR) schemes. In this work, clutter tracking is done in image domain and an algorithm combining multifractal and fuzzy C-mean (FCM) cluster is proposed. The clutter with large dynamic distributions in power density is converted to steady distributions of multifractal exponents by the multifractal transformation with the optimum moment. Then, later, the main lobe and side lobe are tracked from the multifractal exponents by FCM clustering method.
Turbulence in magnetized plasmas and financial markets: comparative study of multifractal statistics
Budaev, V. P.
2004-12-01
The turbulence in magnetized plasma and financial data of Russian market have been studied in terms of the multifractal formalism revisited with wavelets. The multifractal formalism based on wavelet calculations allows one to study the scaling properties of turbulent fluctuations. It is observed that both plasma edge turbulence in fusion devices and Russian financial markets demonstrate multifractal statistics, i.e., the scaling behaviour of absolute moments is described by a convex function. Multifractality parameter defined in multiplicative cacade model, seems to be of the same magnitude for the plasma and financial time series considered in this paper.
Multifractal properties of ECG patterns of patients suffering from congestive heart failure
Dutta, Srimonti
2010-12-01
The multifractal properties of two-channel ECG patterns of patients suffering from severe congestive heart failure (New York Heart Association (NYHA) classes III-IV) are studied and are compared with those for normal healthy people using the multifractal detrended fluctuation analysis methodology. Ivanov et al (1999 Nature 399 461) have studied the multifractality of human heart rate dynamics using the wavelet transformation modulus maxima (WTMM) methodology. But it has been observed by several scientists that multifractal detrended fluctuation analysis (MFDFA) works better than the WTMM method in the detection of monofractal and multifractal characteristics of the data. Galaska et al (2008 Ann. Noninvasive Electrocardiol. 13 155) have observed that MFDFA is more sensitive compared to the WTMM method in the differentiation between multifractal properties of the heart rate in healthy subjects and patients with left ventricular systolic dysfunction. In the present work the variation of two parameters of the multifractal spectrum—its width W (related to the degree of multifractality) and the value of the Hölder exponent α0—for the healthy and congestive heart failure patients is studied. α0 is a measure of the degree of correlation. The degree of multifractality varies appreciably (85-90% C.L.) for the normal and the CHF sets for channel I. For channel II no significant change in the values is observed. The degree of correlation is found to be comparatively high for the normal healthy people compared to those suffering from CHF.
Image Network Generation of Uncalibrated Uav Images with Low-Cost GPS Data
Huang, Shan; Zhang, Zuxun; He, Jianan; Ke, Tao
2016-06-01
The use of unmanned air vehicle (UAV) images acquired by a non-metric digital camera to establish an image network is difficult in cases without accurate camera model parameters. Although an image network can be generated by continuously calculating camera model parameters during data processing as an incremental structure from motion (SfM) methods, the process is time consuming. In this study, low-cost global position system (GPS) information is employed in image network generation to decrease computational expenses. Each image is considered as reference, and its neighbor images are determined based on GPS coordinates during processing. The reference image and its neighbor images constitute an image group, which is used to generate a free network through image matching and relative orientation. Data are then transformed from the free network coordinate system of each group into the GPS coordinate system by using the GPS coordinates of each image. After the exterior elements of each image are determined in the GPS coordinate system, the initial image network is established. Finally, self-calibration bundle adjustment constrained by GPS coordinates is conducted to refine the image network. The proposed method is validated on three fields. Results confirm that the method can achieve good image network when accurate camera model parameters are unavailable.
On multifractality of high-latitude geomagnetic fluctuations
Directory of Open Access Journals (Sweden)
Z. Vörös
Full Text Available In order to contribute to the understanding of solar wind-magnetosphere interactions the multifractal scaling properties of high-latitude geomagnetic fluctuations observed at the Thule observatory have been studied. Using the local observatory data and the present experimental knowledge only it seems hard to characterize directly the, presumably intermittent, mesoscale energy accumulation and dissipation processes taking place at the magnetotail, auroral region, etc. Instead a positive probability measure, describing the accumulated local geomagnetic signal energy content at the given time scales has been introduced and its scaling properties have been studied. There is evidence for the multifractal nature of the so defined intermittent field ε, a result obtained by using the recently introduced technique of large deviation multifractal spectra. This technique allows us to describe the geomagnetic fluctuations locally in time by means of singularity exponents α, which represent a generalization of the local degree of differentiability and characterize the power-law scaling dependence of the introduced measure on resolution. A global description of the geomagnetic fluctuations is insured by the spectrum of exponents f(α which represents a rate function quantifying the deviations of the observed singularities α from the expected value. The results show that there exists a multifractal counterpart of the previously reported spectral break and different types of f(α spectra describe the fluctuations in direct dissipation or loading-unloading regimes of the solar wind-magnetosphere interaction. On the time scale of substorms and storms the multi-fractal structure of the loading-unloading mode fluctuations seems to be analogous to the simple multiplicative P-model, while the f(α spectra in direct dissipation regime are close but not equal to the features of a uniform distribution. Larger deviations from the multiplicative
Choice set generation in multi-modal transportation networks
Fiorenzo-Catalano, M.S.
2007-01-01
Multi-modal transport relates to trips for which travellers use two or more transport modes, for example bicycle and train, train and bus, or private car and metro. The main theme in this dissertation is to establish a choice set generation model and algorithm, and demonstrate its validity and
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…
John Michael Salgado Cebola
2016-01-01
Comparative study between the performance of Convolutional Networks using pretrained models and statistical generative models on tasks of image classification in semi-supervised enviroments.Study of multiple ensembles using these techniques and generated data from estimated pdfs.Pretrained Convents, LDA, pLSA, Fisher Vectors, Sparse-coded SPMs, TSVMs being the key models worked upon.
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 s
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.
Syudy of Token Generation for Burst Traffic Shaping in Optical Burst Switching Networks
Institute of Scientific and Technical Information of China (English)
Tang Wan; So Won-ho; Lu Ji-guang; Kim Young-chon
2004-01-01
Traffic shaping is one of important control operation to guarantee the Quality of Service (QoS) in optical burst switching (OBS) networks. The efficiency of traffic shaping is mainly determined by token generation method. In this paper, token generation methods of traffic shaping are evaluated by using three kinds of probability distribution, and are analyzed in terms of burst blocking probability, throughput and correlation by simulation. The simulation results show that the token generation methods decrease the burst correlation of Label Switched Paths (LSPs), and solve traffic congestion as well. The different burst arrival processes have small impact on the blocking probability for OBS networks.
An efficient algorithm for generating AoA networks
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Nasser Eddine Mouhoub
2012-01-01
Full Text Available The activities, in project scheduling, can be represented graphically in two different ways, by either assigning the activities to the nodes 'AoN directed acyclic graph (dag or to the arcs 'AoA dag. In this paper, a new algorithm is proposed for generating, for a given project scheduling problem, an Activity-on-Arc dag starting from the Activity-on-Node dag using the concepts of line graphs of graphs.
Mobile location services for the next generation wireless network
DEFF Research Database (Denmark)
Schou, Saowanee
2008-01-01
in this thesis to resolve the lack of indoor location capability, and a conceptual service architecture for adaptive mobile location services has been developed to facilitate the provision of compelling mobile location services for the future network. The developed service architecture allows the mobile location......Mobile location services exploit mobile location technologies for determining where a mobile user is geographically located. This information can then be used for providing location-specific content to the mobile user. The mobile location services can be used, for example, for finding points...... of interest, getting weather information, and tracking the whereabouts of a child. Mobile location services gained a great deal of interest in 2000, and they were envisioned by the business players in the mobile service market as one of the few service categories where the mobile users would be willing to pay...
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
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...... 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...
Multifractality and herding behavior in the Japanese stock market
Energy Technology Data Exchange (ETDEWEB)
Cajueiro, Daniel O. [Universidade Catolica de Brasilia, Doutorado em Economia de Empresas, SGAN 916, Modulo B, Asa Norte, DF 70790-160 (Brazil); Tabak, Benjamin M. [Banco Central do Brasil, SBS Quadra 3, Bloco B, 9 andar, DF 70074-900 (Brazil)], E-mail: benjamin@ucb.br
2009-04-15
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.
Multifractal analysis of non-uniformly contracting iterated function systems
Ye, Yuan-Ling
2017-05-01
Let X = [0,1]. Given a non-uniformly contracting conformal iterated function system (IFS) ≤ft\\{{{w}j}\\right\\}j=1m and a family of positive Dini continuous potential functions ≤ft\\{ {{p}j}\\right\\}j=1m , the triple system ≤ft(X,≤ft\\{{{w}j}\\right\\}j=1m,≤ft\\{ {{p}j}\\right\\}j=1m\\right) , under some conditions, determines uniquely a probability invariant measure, denoted by μ. In this paper, we study the pressure function of the system and multifractal structure of μ. We prove that the pressure function is Gateaux differentiable and the multifractal formalism holds, if the IFS ≤ft\\{{{w}j}\\right\\}j=1m has non-overlapping.
Seismic Interevent Time: A Spatial Scaling and Multifractality
Molchan, G
2005-01-01
The optimal scaling problem for the time t(LxL) between two successive events in a seismogenic cell of size L is considered. The quantity t(LxL) is defined for a random cell of a grid covering a seismic region G. We solve that problem in terms of a multifractal characteristic of epicenters in G known as the tau-function or generalized fractal dimensions; the solution depends on the type of cell randomization. Our theoretical deductions are corroborated by California seismicity with magnitude M>2. In other words, the population of waiting time distributions for L = 10-100 km provides positive information on the multifractal nature of seismicity, which impedes the population to be converted into a unified law by scaling. This study is a follow-up of our analysis of power/unified laws for seismicity (see PAGEOPH 162 (2005), 1135 and GJI 162 (2005), 899).
Distributed-order diffusion equations and multifractality: Models and solutions
Sandev, Trifce; Chechkin, Aleksei V.; Korabel, Nickolay; Kantz, Holger; Sokolov, Igor M.; Metzler, Ralf
2015-10-01
We study distributed-order time fractional diffusion equations characterized by multifractal memory kernels, in contrast to the simple power-law kernel of common time fractional diffusion equations. Based on the physical approach to anomalous diffusion provided by the seminal Scher-Montroll-Weiss continuous time random walk, we analyze both natural and modified-form distributed-order time fractional diffusion equations and compare the two approaches. The mean squared displacement is obtained and its limiting behavior analyzed. We derive the connection between the Wiener process, described by the conventional Langevin equation and the dynamics encoded by the distributed-order time fractional diffusion equation in terms of a generalized subordination of time. A detailed analysis of the multifractal properties of distributed-order diffusion equations is provided.
Multifractal heart rate dynamics in human cardiovascular model
Kotani, Kiyoshi; Takamasu, Kiyoshi; Safonov, Leonid; Yamamoto, Yoshiharu
2003-05-01
Human cardiovascular and/or cardio-respiratory systems are shown to exhibit both multifractal and synchronous dynamics, and we recently developed a nonlinear, physiologically plausible model for the synchronization between heartbeat and respiration (Kotani, et al. Phys. Rev. E 65: 051923, 2002). By using the same model, we now show the multifractality in the heart rate dynamics. We find that beat-to-beat monofractal noise (fractional Brownian motion) added to the brain stem cardiovascular areas results in significantly broader singularity spectra for heart rate through interactions between sympathetic and parasympathetic nervous systems. We conclude that the model proposed here would be useful in studying the complex cardiovascular and/or cardio- respiratory dynamics in humans.
Multifractal modeling of the production of concentrated sugar syrup crystal
Sheng, Bi; Jianbo, Gao
2016-07-01
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.
Multifractional Spacetimes, Asymptotic Safety and HOŘAVA-LIFSHITZ Gravity
Calcagni, Gianluca
2013-07-01
We compare the recently formulated multifractional spacetimes with field theories of quantum gravity based on the renormalization group (RG), such as asymptotic safety and Hořava-Lifshitz gravity. The change of spacetime dimensionality with the probed scale is realized in both cases by an adaptation of the measurement tools ("rods") to the scale, but in different ways. In the multifractional case, by an adaptation of the position-space measure, which can be encoded into an explicit scale dependence of effective coordinates. In the case of RG-based theories, by an adaptation of the momenta. The two pictures are mapped into each other, thus presenting the fractal structure of spacetime in RG-based theories under an alternative perspective.
Irregularities and scaling in signal and image processing: multifractal analysis
Abry, Patrice; Jaffard, Herwig; Wendt, Stéphane
2015-03-01
B. Mandelbrot gave a new birth to the notions of scale invariance, self-similarity and non-integer dimensions, gathering them as the founding corner-stones used to build up fractal geometry. The first purpose of the present contribution is to review and relate together these key notions, explore their interplay and show that they are different facets of a single intuition. Second, we will explain how these notions lead to the derivation of the mathematical tools underlying multifractal analysis. Third, we will reformulate these theoretical tools into a wavelet framework, hence enabling their better theoretical understanding as well as their efficient practical implementation. B. Mandelbrot used his concept of fractal geometry to analyze real-world applications of very different natures. As a tribute to his work, applications of various origins, and where multifractal analysis proved fruitful, are revisited to illustrate the theoretical developments proposed here.
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
DMS - basis for increasing of green distributed generation penetration in distribution networks
Directory of Open Access Journals (Sweden)
Strezoski Vladimir C.
2012-01-01
Full Text Available Modern (electric power distribution utilities are faced with high penetration of distributed (electric generation. Renewable generation is of prime interest. Within this generation, the green one incorporating solar (photovoltaic and wind generation is the most important. Consequently, the following two imperatives are established in modern distribution utilities: 1 absorption of as much of available (connected to network green generation as possible and 2 increasing of the limit of green distributed generation penetration. This generation is a significant basis of Smart Distribution Grid Concept. Distributed generation transfers passive distribution network into active one. The active distribution network analysis, control, operation management and planning become significantly complex. This complexity radically hinders the achievement of two above stated imperatives referring to the distributed generation penetration. This paper proves that Distribution Management System is a unique powerful system that integrates all tools necessary for surpassing main difficulties in the achievement of the both imperatives. The proof is obtained by the elaboration of a set of power applications (mathematical calculations integrated in the Distribution Management System. The most important power applications, which deal with voltage / reactive power control, are specially stressed.
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.
Physical layer secret key generation for fiber-optical networks.
Kravtsov, Konstantin; Wang, Zhenxing; Trappe, Wade; Prucnal, Paul R
2013-10-07
We propose and experimentally demonstrate a method for generating and sharing a secret key using phase fluctuations in fiber optical links. The obtained key can be readily used to support secure communication between the parties. The security of our approach is based on a fundamental asymmetry associated with the optical physical layer: the sophistication of tools needed by an eavesdropping adversary to subvert the key establishment is significantly greater and more costly than the complexity needed by the legitimate parties to implement the scheme. In this sense, the method is similar to the classical asymmetric algorithms (Diffie-Hellman, RSA, etc.).
On the spin wave multifractal spectra in magnetic multilayers
Bezerra, C. G.; Albuquerque, E. L.; , E. Nogueira, Jr.
The multifractal properties of spin wave bandwidths in quasiperiodic magnetic multilayers are studied. The profiles of the bandwidths are analyzed and the f( α) function is calculated for different values of the dimensionless in-plane wave vector kxa and for four different sequences: Fibonacci, double-period, Thue-Morse and Rudin-Shapiro. We note that the f( α) spectra is qualitatively the same for different values of kxa.
Multifractal Measure of Post Distribution in Post System
Institute of Scientific and Technical Information of China (English)
CHEN Li; HUANG Deng-shi
2009-01-01
In order to investigate the true post distribution in the whole society, microelasticity (MIE) and macroelasticity (MAE) were defined by regarding all posts as a system. On this basis, the method for measuring post distribution was proposed. Using the Legendre dual transformation between MIE and MAE to highlight the probabilities of different levels, the post distribution were analyzed hierarchically. The two-scale Cantor model verified that the multifractal measure is applicable to the post distribution evolution process.
Scaling and multifractal fields in the solid earth and topography
Directory of Open Access Journals (Sweden)
S. Lovejoy
2007-08-01
Full Text Available Starting about thirty years ago, new ideas in nonlinear dynamics, particularly fractals and scaling, provoked an explosive growth of research both in modeling and in experimentally characterizing geosystems over wide ranges of scale. In this review we focus on scaling advances in solid earth geophysics including the topography. To reduce the review to manageable proportions, we restrict our attention to scaling fields, i.e. to the discussion of intensive quantities such as ore concentrations, rock densities, susceptibilities, and magnetic and gravitational fields.
We discuss the growing body of evidence showing that geofields are scaling (have power law dependencies on spatial scale, resolution, over wide ranges of both horizontal and vertical scale. Focusing on the cases where both horizontal and vertical statistics have both been estimated from proximate data, we argue that the exponents are systematically different, reflecting lithospheric stratification which – while very strong at small scales – becomes less and less pronounced at larger and larger scales, but in a scaling manner. We then discuss the necessity for treating the fields as multifractals rather than monofractals, the latter being too restrictive a framework. We discuss the consequences of multifractality for geostatistics, we then discuss cascade processes in which the same dynamical mechanism repeats scale after scale over a range. Using the binomial model first proposed by de Wijs (1951 as an example, we discuss the issues of microcanonical versus canonical conservation, algebraic ("Pareto" versus long tailed (e.g. lognormal distributions, multifractal universality, conservative and nonconservative multifractal processes, codimension versus dimension formalisms. We compare and contrast different scaling models (fractional Brownian motion, fractional Levy motion, continuous (in scale cascades, showing that they are all based on fractional integrations of noises
From fractional Brownian motion to multifractional and multistable motion
Falconer, Kenneth
2015-03-01
Fractional Brownian motion, introduced by Benoit Mandelbrot and John Van Ness in 1968, has had a major impact on stochastic processes and their applications. We survey a few of the many developments that have stemmed from their ideas. In particular we discuss the local structure of fractional and multifractional Brownian, stable and multistable processes, emphasising the `diagonal' construction of such processes. In all this, the ubiquity and centrality of fractional Brownian motion is striking.
Efficient Moment Matrix Generation for Arbitrary Chemical Networks.
Smadbeck, P; Kaznessis, Y N
2012-12-24
As stochastic simulations become increasingly common in biological research, tools for analysis of such systems are in demand. The deterministic analogue to stochastic models, a set of probability moment equations equivalent to the Chemical Master Equation (CME), offers the possibility of a priori analysis of systems without the need for computationally costly Monte Carlo simulations. Despite the drawbacks of the method, in particular non-linearity in even the simplest of cases, the use of moment equations combined with moment-closure techniques has been used effectively in many fields. The techniques currently available to generate moment equations rely upon analytical expressions that are not efficient upon scaling. Additionally, the resulting moment-dependent matrix is lower diagonal and demands massive memory allocation in extreme cases. Here it is demonstrated that by utilizing factorial moments and the probability generating function (the Z-transform of the probability distribution) a recursive algorithm is produced. The resulting method is scalable and particularly efficient when high-order moments are required. The matrix produced is banded and often demands substantially less memory resources.
Jamshidi, Saeid; Boozarjomehry, Ramin Bozorgmehry; Pishvaie, Mahmoud Reza
2009-10-01
In pore network modeling, the void space of a rock sample is represented at the microscopic scale by a network of pores connected by throats. Construction of a reasonable representation of the geometry and topology of the pore space will lead to a reliable prediction of the properties of porous media. Recently, the theory of multi-cellular growth (or L-systems) has been used as a flexible tool for generation of pore network models which do not require any special information such as 2D SEM or 3D pore space images. In general, the networks generated by this method are irregular pore network models which are inherently closer to the complicated nature of the porous media rather than regular lattice networks. In this approach, the construction process is controlled only by the production rules that govern the development process of the network. In this study, genetic algorithm has been used to obtain the optimum values of the uncertain parameters of these production rules to build an appropriate irregular lattice network capable of the prediction of both static and hydraulic information of the target porous medium.
Autothermal hydrogen generation from methanol in a ceramic microchannel network
Moreno, Angela M.; Wilhite, Benjamin A.
In this paper, the authors present the first demonstration of a new class of integrated ceramic microchannel reactors for all-in-one reforming of hydrocarbon fuels. The reactor concept employs precision-machined metal distributors capable of realizing complex flow distribution patterns with extruded ceramic microchannel networks for cost-effective thermal integration of multiple chemical processes. The presently reported reactor is comprised of five methanol steam reforming channels packed with CuO/γ-Al 2O 3, interspersed with four methanol combustion channels washcoated with Pt/γ-Al 2O 3, for autothermal hydrogen production (i.e., without external heating). Results demonstrate the capability of this new device for integrating combustion and steam reforming of methanol for autothermal production of hydrogen, owing to the axially self-insulating nature of distributor-packaged ceramic microchannels. In the absence of any external insulation, stable reforming of methanol to hydrogen at conversions >90% and hydrogen yields >70% was achieved at a maximum reactor temperature of 400 °C, while simultaneously maintaining a packaging temperature <50 °C.
Lacunarity and multifractal analysis of the large DLA mass distribution
Rodriguez-Romo, Suemi; Sosa-Herrera, Antonio
2013-08-01
We show the methodology used to analyze fractal and mass-multifractal properties of very large Diffusion-Limited Aggregation (DLA) clusters with a maximum of 109 particles for 2D aggregates and 108 particles for 3D clusters, to support our main result; the scaling behavior obtained by our experimental results corresponds to the expected performance of monofractal objects. In order to estimate lacunarity measures for large DLA clusters, we develop a variant of the gliding-box algorithm which reduces the computer time needed to obtain experimental results. We show how our mass multifractal data have a tendency to present monofractal behavior for the mass distribution of the cases presented in this paper in the limit of very large clusters. Lacunarity analysis shows, provided we study small clusters mass distributions, data which might be interpreted as two different values of fractal dimensions while the cluster grows; however, this effect tends to vanish when the cluster size increases further, in such a way that monofractality is achieved. The outcomes of this paper lead us to conclude that the previously reported mass multifractality behavior (Vicsek et al., 1990 [13]) detected for DLA clusters is a consequence of finite size effects and floating point precision limitations and not an intrinsic feature of the phenomena, since the scaling behavior of our DLA clusters space corresponds to monofractal objects, being this situation remarkably noticeable in the limit of very large clusters.
Multifractal comparison of the painting techniques of adults and children
Mureika, J. R.; Fairbanks, M. S.; Taylor, R. P.
2010-02-01
Statistical analysis of art, particularly of the abstract genre, is becoming an increasingly important tool for understanding the image creation process. We present a multifractal clustering analysis of non-representational images painted by adults and children using a 'pouring' technique. The effective dimensions (D0) are measured for each, as is the associated multifractal depth ▵D = D0 - DOO. It is shown that children create paintings whose dimensions D0 are less than those created by adults. The effective dimensions for adult painters tend to cluster around 1.8, while those for children assume typical values of 1.6. In a similar fashion, the multifractal depths for images painted by adults and children show statistically-significant differences in their values. Adult paintings show a relatively shallow depth (▵D ~ 0.02), while children's paintings show a much greater depth (▵D ~ 0.1). Given that the 'pouring' technique reflects the body motions of the artist, the results suggest that the differences in the paintings' fractal characteristics are potential indicators of artist physiology.
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.
Multifractal analysis of low-latitude geomagnetic fluctuations
Directory of Open Access Journals (Sweden)
M. J. A. Bolzan
2009-02-01
Full Text Available The technique of large deviation multifractal spectrum has shown that the high-latitude (77.5° N, 69.2° W geomagnetic fluctuations can be described from direct dissipation process or loading-unloading regimes of the solar wind-magnetosphere coupling. In this paper, we analyze the H-component of low-latitude (22.4° S, 43.6° W geomagnetic field variability observed during the month of July 2000 at the Geomagnetic Observatory, Vassouras, RJ, Brazil. The variability pattern during this period is a mixture of quiet and disturbed days including the Bastille Day intense geomagnetic storm on 15 July. Due to the complexity of this data, we pursue a detailed analysis of the geomagnetic fluctuations in different time scales including a multifractal approach using the singular power spectrum deviations obtained from the wavelet transform modulus maxima (WTMM. The results suggest, as observed from high-latitude data, the occurrence of low-latitude multifractal processes driving the intermittent coupling between the solar wind-magnetosphere and geomagnetic field variations. On finer scales possible physical mechanisms in the context of nonlinear magnetosphere response are discussed.
Strong anticipation: Multifractal cascade dynamics modulate scaling in synchronization behaviors
Energy Technology Data Exchange (ETDEWEB)
Stephen, Damian G., E-mail: foovian@gmail.co [Wyss Institute for Biologically Inspired Engineering, Harvard University, 3 Blackfan Circle, Floor 5, Boston, MA 02115 (United States); Dixon, James A. [Department of Psychology, University of Connecticut, 406 Babbidge Rd., Unit 1020, Storrs, CT 06269-1020 (United States); Haskins Laboratories, 300 George St., New Haven, CT 06511 (United States)
2011-01-15
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.
Symmetry relations for multifractal spectra at random critical points
Monthus, Cécile; Berche, Bertrand; Chatelain, Christophe
2009-12-01
Random critical points are generically characterized by multifractal properties. In the field of Anderson localization, Mirlin et al (2006 Phys. Rev. Lett. 97 046803) have proposed that the singularity spectrum f(α) of eigenfunctions satisfies the exact symmetry f(2d-α) = f(α)+d-α. In the present paper, we analyze the physical origin of this symmetry in relation to the Gallavotti-Cohen fluctuation relations of large deviation functions that are well known in the field of non-equilibrium dynamics: the multifractal spectrum of the disordered model corresponds to the large deviation function of the rescaling exponent γ = (α-d) along a renormalization trajectory in the effective time t = lnL. We conclude that the symmetry discovered for the specific example of Anderson transitions should actually be satisfied at many other random critical points after an appropriate translation. For many-body random phase transitions, where the critical properties are usually analyzed in terms of the multifractal spectrum H(a) and of the moment exponents X(N) of the two-point correlation function (Ludwig 1990 Nucl. Phys. B 330 639), the symmetry becomes H(2X(1)-a) = H(a)+a-X(1), or equivalently Δ(N) = Δ(1-N) for the anomalous parts \\Delta (N) \\equiv X(N)-NX(1) . We present numerical tests favoring this symmetry for the 2D random Q-state Potts model with varying Q.
Stochastic Calculus with respect to multifractional Brownian motion
Lebovits, Joachim
2011-01-01
Stochastic calculus with respect to fractional Brownian motion (fBm) has attracted a lot of interest in recent years, motivated in particular by applications in finance and Internet traffic modeling. Multifractional Brownian motion (mBm) is a Gaussian extension of fBm that allows to control the pointwise regularity of the paths of the process and to decouple it from its long range dependence properties. This generalization is obtained by replacing the constant Hurst parameter H of fBm by a function h(t). Multifractional Brownian motion has proved useful in many applications, including the ones just mentioned. In this work we extend to mBm the construction of a stochastic integral with respect to fBm. This stochastic integral is based on white noise theory, as originally proposed in [15], [6], [4] and in [5]. In that view, a multifractional white noise is defined, which allows to integrate with respect to mBm a large class of stochastic processes using Wick products. It\\^o formulas (both for tempered distribut...
Using Layer Recurrent Neural Network to Generate Pseudo Random Number Sequences
Directory of Open Access Journals (Sweden)
Veena Desai
2012-03-01
Full Text Available Pseudo Random Numbers (PRNs are required for many cryptographic applications. This paper proposes a new method for generating PRNs using Layer Recurrent Neural Network (LRNN. The proposed technique generates PRNs from the weight matrix obtained from the layer weights of the LRNN. The LRNN random number generator (RNG uses a short keyword as a seed and generates a long sequence as a pseudo PRN sequence. The number of bits generated in the PRN sequence depends on the number of neurons in the input layer of the LRNN. The generated PRN sequence changes, with a change in the training function of the LRNN .The sequences generated are a function of the keyword, initial state of network and the training function. In our implementation the PRN sequences have been generated using 3 training functions: 1Scaled Gradient Descent 2Levenberg-Marquartz (TRAINLM and 3 TRAINBGF. The generated sequences are tested for randomness using ENT and NIST test suites. The ENT test can be applied for sequences of small size. NIST has 16 tests to test random numbers. The LRNN generated PRNs pass in 11 tests, show no observations for 4 tests, and fail in 1 test when subjected to NIST .This paper presents the test results for random number sequence ranging from 25 bits to 1000 bits, generated using LRNN.
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
Schertzer, Daniel
2015-04-01
The EGU's 2015 theme 'a voyage through scales' is a recognition of the wild variability of geophysical fields over wide ranges of scales. However, we cannot forget Samuel Becket's criticism of all voyages: 'We don't travel for the fun of it, as far as I know; we're foolish, but not that foolish.' Such travels would be in fact hardly manageable: atmospheric dynamics are already beyond the yotta scale (1024)! Fortunately, Pandora's box has been opened enough to take us on a motionless travel across scales à la Gulliver. Scale symmetry is becoming generalized to the point that geophysical systems can be perceived as fixed points of (generalized) space-time contractions/dilations, depending on the side of the Wonderland mushrooms bitten by Alice. The now dated scale dependent observables are going to be replaced by scale independent singularities yielding scale free (nonlinear) geophysics. The (not yet solved) millennium problem of hydrodynamic turbulence is surprisingly a pedagogical example to illustrate what is at stake and motivated a series of paradigm shifts. Indeed, this problem can be stripped down to a network of triadic interactions. This graphically highlights how field components 'talk' to each other, i.e. how an infinitely small perturbation propagates through this network. This points out the dead ends of previous approaches (e.g. quasi-normal assumptions) and provide a first tier of concepts such as: multifractal cascades, singularities, universality, phase transitions and predictability limits. These concepts already provide a wealth of non trivial results, particularly the emergent 'dressed' properties generated by the whole set of interactions with respect to the 'bare' properties resulting from a scale truncation. Their extremes can be qualitatively different, having respectively 'heavy' and 'thin' tailed probability distributions. Moreover, the ubiquitous anisotropy of geophysical fields and patterns required another paradigm shift: a generalized
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.
Energy Technology Data Exchange (ETDEWEB)
Hoeffler, Felix [Koeln Univ. (Germany). Energiewirtschaftliches Inst.; Max-Planck-Institute for Research on Collective Goods, Bonn (Germany); Wambach, Achim [Cologne Univ. (Germany). Dept. of Economics
2013-06-15
Liberalization of network industries frequently separates the network from the other parts of the industry. This is important in particular for the elec- tricity industry where private firms invest into generation facilities, while network investments usually are controlled by regulators. We discuss two regulatory regimes. First, the regulator can only decide on the network extension. Second, she can additionally use a ''capacity market'' with payments contingent on private generation investment. For the first case, we find that even absent asymmetric information, a lack of regulatory commitment can cause inefficiently high or inefficiently low investments. For the second case, we develop a standard handicap auction which implements the first best under asymmetric information, if there are no shadow costs of public funds. With shadow costs, no simple mechanism can implement the second best outcome.
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...
A policy-based billing management architecture for the next generation IP-based network
Institute of Scientific and Technical Information of China (English)
Cheng Lu; Qiu Xuesong; Meng Luoming
2006-01-01
IP billing is not only a basic functionality to operate IP services, but also it is fundamental to offer customers with a stable and QoS-enabled network environment. As IP-based network has been widely agreed to be the core network of NGN, and existing IP billing system is too simple to fulfill the emerging requirements, the next generation IP billing has become an interesting topic in recent years. Policy-based management brings flexibility and scalability to systems by describing management logic and functions through policies, and thus reduces the complexity of the management of large-scale systems. Working on existing efforts, this paper proposed an improved IETF policy framework based upon which a policy-based billing management architecture for the next generation IP-based network was presented. Then a prototype with some basic functionalities was developed. The results of the experiment validated the expected improvements specified in this paper.
Crowdsourcing User-Generated Mobile Sensor Weather Data for Densifying Static Geosensor Networks
Directory of Open Access Journals (Sweden)
Shay Sosko
2017-02-01
Full Text Available Static geosensor networks are comprised of stations with sensor devices providing data relevant for monitoring environmental phenomena in their geographic perimeter. Although early warning systems for disaster management rely on data retrieved from these networks, some limitations exist, largely in terms of insufficient coverage and low density. Crowdsourcing user-generated data is emerging as a working methodology for retrieving real-time data in disaster situations, reducing the aforementioned limitations, and augmenting with real-time data generated voluntarily by nearby citizens. This paper explores the use of crowdsourced user-generated sensor weather data from mobile devices for the creation of a unified and densified geosensor network. Different scenario experiments are adapted, in which weather data are collected using smartphone sensors, integrated with the development of a stabilization algorithm, for determining the user-generated weather data reliability and usability. Showcasing this methodology on a large data volume, a spatiotemporal algorithm was developed for filtering on-line user-generated weather data retrieved from WeatherSignal, and used for simulation and assessment of densifying the static geosensor weather network of Israel. Geostatistical results obtained proved that, although user-generated weather data show small discrepancies when compared to authoritative data, with considerations they can be used alongside authoritative data, producing a densified and augmented weather map that is detailed and continuous.
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.
Study of predicting breakdown voltage of stator insulation in generator based on BP neural network
Institute of Scientific and Technical Information of China (English)
Jiang Yuao; Zhang Aide; Liu Libing; Du Yu; Gao Naikui; Peng Zongren
2007-01-01
The breakdown voltage plays an important role in evaluating residual life of stator insulation in generator. In this paper, we discussed BP neural network that was used to predict the breakdown voltage of stator insulation in generator of 300 MW/18 kV. At first the neural network has been trained by the samples that include the varieties of dielectric loss factor tanδ, the partial discharge parameters and breakdown voltage. Then we tried to predict the breakdown voltage of samples and stator insulations subjected to multi-stress aging by the trained neural network. We found that it's feasible and accurate to predict the voltage. This method can be applied to predict breakdown voltage of other generators which have the same insulation structure and material.
Multifractal Geophysical Extremes: Nonstationarity and Long Range Correlations
Tchiguirinskaia, I.; Schertzer, D.; Lovejoy, S.
2012-04-01
Throughout the world, extremes in environmental sciences are of prime importance. They are key variables not only for risk assessments and engineering designs (e.g. of dams and bridges), but also for resource management (e.g. water and energy) and for land use. A better understanding of them is more and more indispensable in settling the debate on their possible climatological evolution. Whereas it took decades before a uniform technique for estimating flow frequencies within a stationary framework, it is often claimed that « stationarity is dead ! ». The fact that geophysical and environmental fields are variable over a wider range of scales than previously thought require to go beyond the limits of the (classical) Extreme Value Theory (EVT). Indeed, long-range correlations are beyond the scope of the classical EVT theory. We show that multifractal concepts and techniques are particularly appealing because they can effectively deal with a cascade of interactions concentrating for instance energy, liquid water, etc. into smaller and smaller space-time domains. Furthermore, a general outcome of these cascade processes -which surprisingly was realized only rather recently- is that rather independently of their details they yield probability distributions with power-law fall-offs, often called (asymptotic) Pareto or Zipf laws. We discuss the corresponding probability distributions of their maxima and its relationship with the Frechet law. We use these multifractal techniques to investigate the possibility of using very short or incomplete data records for reliable statistical predictions of the extremes. In particular we assess the multifractal parameter uncertainty with the help of long synthetic multifractal series and their sub-samples, in particular to obtain an approximation of confidence intervals that would be particularly important for the predictions of multifractal extremes. We finally illustrate the efficiency of this approach with its application to
Approach of virtual observations generation of a multi-reference GPS station network
Yu, Guorong
2007-11-01
The generation of virtual reference station observations to relay the corrections to the rover receiver for use with standard RTK software is one of important architectures of reference station networks RTK positioning. The approach of virtual observations generation based on a multi-reference GPS station network is presented in this paper. Ambiguities for the baselines in the reference network are determined firstly. The inter-reference-station differential spatially-correlated errors are estimated using highly accurate coordinates of the reference stations and resolved ambiguities. These spatially-correlated errors are interpolated among the network region as corrections. These network-generated corrections are used to correct the zero-differential observables of one reference station, which is usually the closest one to the rover (the so-called primary reference station). These corrected zero-differential observables, named virtual observations, are processed using conventional single reference station differential GPS algorithms. A test conducted using regional reference networks in Jiangsu(China) demonstrates the effectiveness of the approach to reduce the time to integer ambiguity resolution, and to increase the distance over which centimeter level accuracies can be achieved.
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
Guerrier, Claire; Hayes, John A; Fortin, Gilles; Holcman, David
2015-08-04
How might synaptic dynamics generate synchronous oscillations in neuronal networks? We address this question in the preBötzinger complex (preBötC), a brainstem neural network that paces robust, yet labile, inspiration in mammals. The preBötC is composed of a few hundred neurons that alternate bursting activity with silent periods, but the mechanism underlying this vital rhythm remains elusive. Using a computational approach to model a randomly connected neuronal network that relies on short-term synaptic facilitation (SF) and depression (SD), we show that synaptic fluctuations can initiate population activities through recurrent excitation. We also show that a two-step SD process allows activity in the network to synchronize (bursts) and generate a population refractory period (silence). The model was validated against an array of experimental conditions, which recapitulate several processes the preBötC may experience. Consistent with the modeling assumptions, we reveal, by electrophysiological recordings, that SF/SD can occur at preBötC synapses on timescales that influence rhythmic population activity. We conclude that nondeterministic neuronal spiking and dynamic synaptic strengths in a randomly connected network are sufficient to give rise to regular respiratory-like rhythmic network activity and lability, which may play an important role in generating the rhythm for breathing and other coordinated motor activities in mammals.
Palamara, Simone; Vergara, Christian; Faggiano, Elena; Nobile, Fabio
2015-02-01
The Purkinje network is responsible for the fast and coordinated distribution of the electrical impulse in the ventricle that triggers its contraction. Therefore, it is necessary to model its presence to obtain an accurate patient-specific model of the ventricular electrical activation. In this paper, we present an efficient algorithm for the generation of a patient-specific Purkinje network, driven by measures of the electrical activation acquired on the endocardium. The proposed method provides a correction of an initial network, generated by means of a fractal law, and it is based on the solution of Eikonal problems both in the muscle and in the Purkinje network. We present several numerical results both in an ideal geometry with synthetic data and in a real geometry with patient-specific clinical measures. These results highlight an improvement of the accuracy provided by the patient-specific Purkinje network with respect to the initial one. In particular, a cross-validation test shows an accuracy increase of 19% when only the 3% of the total points are used to generate the network, whereas an increment of 44% is observed when a random noise equal to 20% of the maximum value of the clinical data is added to the measures.
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.
Mesh Generation from Dense 3D Scattered Data Using Neural Network
Institute of Scientific and Technical Information of China (English)
ZHANGWei; JIANGXian-feng; CHENLi-neng; MAYa-liang
2004-01-01
An improved self-organizing feature map (SOFM) neural network is presented to generate rectangular and hexagonal lattic with normal vector attached to each vertex. After the neural network was trained, the whole scattered data were divided into sub-regions where classified core were represented by the weight vectors of neurons at the output layer of neural network. The weight vectors of the neurons were used to approximate the dense 3-D scattered points, so the dense scattered points could be reduced to a reasonable scale, while the topological feature of the whole scattered points were remained.
UMTS-WiMAX Vertical Handover in Next Generation Wireless Networks
Alamri, Nada
2012-01-01
The vision of next generation wireless network (NGWN) is to integrate different wireless access technologies, each with its own characteristics, into a common IP-based core network to provide mobile user with service continuity and seamless roaming. One of the major issues for the converged heterogeneous networks is providing a seamless vertical handover (VHO) with QoS support. In this paper we have reviewed the various interworking architectures and handover scenarios between UMTS and WiMAX. Also, we have compared the proposed solutions based on different criteria and revealed the pros and cons of each scheme. The comparison aids to adopt a better interworking and handover mechanism in NGWN.
Disorder generated by interacting neural networks: application to econophysics and cryptography
Energy Technology Data Exchange (ETDEWEB)
Kinzel, Wolfgang [Institut fuer Theoretische Physik, Universitaet Wuerzburg, Am Hubland, 97074 Wuerzburg (Germany); Kanter, Ido [Department of Physics, Bar Ilan University, Ramat Gan (Israel)
2003-10-31
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.
Energy Technology Data Exchange (ETDEWEB)
Ito, Kazumasa; Yongkoo, Seol
2003-04-09
Water fluxes in unsaturated, fractured rock involve the physical processes occurring at fracture-matrix interfaces within fracture networks. Modeling these water fluxes using a discrete fracture network model is a complicated effort. Existing preprocessors for TOUGH2 are not suitable to generate grids for fracture networks with various orientations and inclinations. There are several 3-D discrete-fracture-network simulators for flow and transport, but most of them do not capture fracture-matrix interaction. We have developed a new 3-D discrete-fracture-network mesh generator, FRACMESH, to provide TOUGH2 with information about the fracture network configuration and fracture-matrix interactions. FRACMESH transforms a discrete fracture network into a 3 dimensional uniform mesh, in which fractures are considered as elements with unique rock material properties and connected to surrounding matrix elements. Using FRACMESH, individual fractures may have uniform or random aperture distributions to consider heterogeneity. Fracture element volumes and interfacial areas are calculated from fracture geometry within individual elements. By using FRACMESH and TOUGH2, fractures with various inclinations and orientations, and fracture-matrix interaction, can be incorporated. In this paper, results of flow and transport simulations in a fractured rock block utilizing FRACMESH are presented.
Multifractal Analysis of Typhoons: the case study of Bolaven (2012)
Lee, Jisun; Paz, Igor; Ichiba, Abdellah; Tchiguirinskaia, Ioulia; Schertzer, Daniel; Lee, Dong-In; Kuo, Hung-Chi
2017-04-01
Multifractals have become rather standard tools to analyze and simulate meteorological and hydrological data, especially radar data that have the rare advantage of providing space-time (3D+1) fields. However, in spite of their inherent capacity to deal with extreme multiscale phenomena like typhoons, as well as an increased availability of higher quality data, there had been not so many multifractal studies of typhoons since pioneering studies (Chygyrynsakaia et al 1994, Lazarev et al 1994), which relied on time series data obtained from 1D aircraft or balloon trajectories. This lack of new developments might have impeded significant progress in predicting typhoon evolution prediction. We therefore decided to jointly understand the dynamics and rainfall by multifractal space-time analysis with the help of the joint measurements of the Typhoon Bolaven by three Doppler S-band radars. This experimental set-up not only provided accurate estimates of the rainfall intensity, but also of the 3 components of the wind velocity. Typhoon Bolaven is one of the typhoons that caused the largest damages with severe rainfall all over Korea including Jeju Island with more than 250 mm in 2 days in 2012. It was regarded as the most powerful storm to strike the Korean Peninsula in nearly a decade, with wind gusts measured up to 186 km h-1. The three radars were respectively located in Gosan, and Seongsan, in Jeju Island, and Jindo, in southwest of Korea peninsula, i.e. all around the region where the typhoon intensity was the largest. The largest distance between the radars was approximately 100km, and the rainfall and wind velocity were estimated on a grid of 360×360×60 every ten minutes. The multifractal analysis of this large amount of data (space time Trace Method and Double Trace Method) was performed to better understand through scales the fast transformation of potential energy into kinetic energy and the premier role of convection. In particular, this analysis confirms power
Technical Note: Automatic river network generation for a physically-based river catchment model
Directory of Open Access Journals (Sweden)
S. J. Birkinshaw
2010-09-01
Full Text Available SHETRAN is a physically-based distributed modelling system that gives detailed simulations in time and space of water flow and sediment and solute transport in river catchments. Standard algorithms for the automatic generation of river channel networks from digital elevation data are impossible to apply in SHETRAN and other similar models because the river channels are assumed to run along the edges of grid cells. In this work a new algorithm for the automatic generation of a river channel network in SHETRAN is described and its use in an example catchment demonstrated.
Technical Note: Automatic river network generation for a physically-based river catchment model
Birkinshaw, S. J.
2010-09-01
SHETRAN is a physically-based distributed modelling system that gives detailed simulations in time and space of water flow and sediment and solute transport in river catchments. Standard algorithms for the automatic generation of river channel networks from digital elevation data are impossible to apply in SHETRAN and other similar models because the river channels are assumed to run along the edges of grid cells. In this work a new algorithm for the automatic generation of a river channel network in SHETRAN is described and its use in an example catchment demonstrated.
Technical Note: Automatic river network generation for a physically-based river catchment model
Directory of Open Access Journals (Sweden)
S. J. Birkinshaw
2010-05-01
Full Text Available SHETRAN is a physically-based distributed modelling system that gives detailed simulations in time and space of water flow and sediment and solute transport in river catchments. Standard algorithms for the automatic generation of river channel networks from digital elevation data are impossible to apply in SHETRAN and other similar models because the river channels are assumed to run along the edges of grid cells. In this work a new algorithm for the automatic generation of a river channel network in SHETRAN is described and its use in an example catchment demonstrated.
Asymmetric multifractal detrending moving average analysis in time series of PM2.5 concentration
Zhang, Chen; Ni, Zhiwei; Ni, Liping; Li, Jingming; Zhou, Longfei
2016-09-01
In this paper, we propose the asymmetric multifractal detrending moving average analysis (A-MFDMA) method to explore the asymmetric correlation in non-stationary time series. The proposed method is applied to explore the asymmetric correlation of PM2.5 daily average concentration with uptrends or downtrends in China. In addition, shuffling and phase randomization procedures are applied to detect the sources of multifractality. The results show that existences of asymmetric correlations, and the asymmetric correlations are multifractal. Further, the multifractal scaling behavior in the Chinese PM2.5 is caused not only by long-range correlation but also by fat-tailed distribution, but the major source of multifractality is fat-tailed distribution.
Multifractal analysis of the fracture surfaces of foamed polypropylene/polyethylene blends
Liu, Chuang; Jiang, Xiu-Lei; Liu, Tao; Zhao, Ling; Zhou, Wei-Xing; Yuan, Wei-Kang
2009-01-01
The two-dimensional multifractal detrended fluctuation analysis is applied to reveal the multifractal properties of the fracture surfaces of foamed polypropylene/polyethylene (PP/PE) blends at different temperatures. Nice power-law scaling relationship between the detrended fluctuation function Fq and the scale s is observed for different orders q and the scaling exponent h(q) is found to be a nonlinear function of q, confirming the presence of multifractality in the fracture surfaces. The multifractal spectra f(α) are obtained numerically through Legendre transform. The shape of the multifractal spectrum of singularities can be well captured by the width of spectrum Δα and the difference of dimension Δf. With the increase of the PE content, the fracture surface becomes more irregular and complex, as is manifested by the facts that Δα increases and Δf decreases from positive to negative. A qualitative interpretation is provided based on the foaming process.
A comparison between two OLS-based approaches to estimating urban multifractal parameters
Huang, Linshan
2016-01-01
Multifractal theory provides a powerful tool to describe urban form and growth, but many basic problems remain to be solved. Among various pending problems, the most significant one is how to obtain proper multifractal dimension spectrums. If an algorithm is improperly used, the parameter values will be abnormal. This paper is devoted to drawing a comparison between two OLS-based approaches for estimating urban multifractal parameters. Using observational data and empirical analysis, we will demonstrate how to utilize the double logarithmic linear regression to evaluate multifractal parameters. The OLS regression analysis has two different approaches. One is to fix the intercept to zero, and the other is not to fix it. The case studies show that the advisable method is to constrain the intercept to zero. The zero-intercept regression yields proper multifractal parameter spectrums within certain scale range of moment order, while the common regression results are not normal. In practice, the zero-intercept reg...
Sequential generation of two distinct synapse-driven network patterns in developing neocortex.
Allène, Camille; Cattani, Adriano; Ackman, James B; Bonifazi, Paolo; Aniksztejn, Laurent; Ben-Ari, Yehezkel; Cossart, Rosa
2008-11-26
Developing cortical networks generate a variety of coherent activity patterns that participate in circuit refinement. Early network oscillations (ENOs) are the dominant network pattern in the rodent neocortex for a short period after birth. These large-scale calcium waves were shown to be largely driven by glutamatergic synapses albeit GABA is a major excitatory neurotransmitter in the cortex at such early stages, mediating synapse-driven giant depolarizing potentials (GDPs) in the hippocampus. Using functional multineuron calcium imaging together with single-cell and field potential recordings to clarify distinct network dynamics in rat cortical slices, we now report that the developing somatosensory cortex generates first ENOs then GDPs, both patterns coexisting for a restricted time period. These patterns markedly differ by their developmental profile, dynamics, and mechanisms: ENOs are generated before cortical GDPs (cGDPs) by the activation of glutamatergic synapses mostly through NMDARs; cENOs are low-frequency oscillations (approximately 0.01 Hz) displaying slow kinetics and gradually involving the entire network. At the end of the first postnatal week, GABA-driven cortical GDPs can be reliably monitored; cGDPs are recurrent oscillations (approximately 0.1 Hz) that repetitively synchronize localized neuronal assemblies. Contrary to cGDPs, cENOs were unexpectedly facilitated by short anoxic conditions suggesting a contribution of glutamate accumulation to their generation. In keeping with this, alterations of extracellular glutamate levels significantly affected cENOs, which are blocked by an enzymatic glutamate scavenger. Moreover, we show that a tonic glutamate current contributes to the neuronal membrane excitability when cENOs dominate network patterns. Therefore, cENOs and cGDPs are two separate aspects of neocortical network maturation that may be differentially engaged in physiological and pathological processes.
Wilhelm, Matthias; Schmitt, Jens B
2010-01-01
Key management in wireless sensor networks faces several new challenges. The scale, resource limitations, and new threats such as node capture necessitate the use of an on-line key generation by the nodes themselves. However, the cost of such schemes is high since their secrecy is based on computational complexity. Recently, several research contributions justified that the wireless channel itself can be used to generate information-theoretic secure keys. By exchanging sampling messages during movement, a bit string can be derived that is only known to the involved entities. Yet, movement is not the only possibility to generate randomness. The channel response is also strongly dependent on the frequency of the transmitted signal. In our work, we introduce a protocol for key generation based on the frequency-selectivity of channel fading. The practical advantage of this approach is that we do not require node movement. Thus, the frequent case of a sensor network with static motes is supported. Furthermore, the...
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.
Technical Note: Automatic river network generation for a physically-based river catchment model
2010-01-01
SHETRAN is a physically-based distributed modelling system that gives detailed simulations in time and space of water flow and sediment and solute transport in river catchments. Standard algorithms for the automatic generation of river channel networks from digital elevation data are impossible to apply in SHETRAN and other similar models because the river channels are assumed to run along the edges of grid cells. In this work a new algorithm for the automatic generation of a river cha...
Technical Note: Automatic river network generation for a physically-based river catchment model
2010-01-01
SHETRAN is a physically-based distributed modelling system that gives detailed simulations in time and space of water flow and sediment and solute transport in river catchments. Standard algorithms for the automatic generation of river channel networks from digital elevation data are impossible to apply in SHETRAN and other similar models because the river channels are assumed to run along the edges of grid cells. In this work a new algorithm for the automatic generation of a river channel ne...
Conditions for Multi-functionality in a Rhythm Generating Network Inspired by Turtle Scratching.
Snyder, Abigail C; Rubin, Jonathan E
2015-12-01
Rhythmic behaviors such as breathing, walking, and scratching are vital to many species. Such behaviors can emerge from groups of neurons, called central pattern generators, in the absence of rhythmic inputs. In vertebrates, the identification of the cells that constitute the central pattern generator for particular rhythmic behaviors is difficult, and often, its existence has only been inferred. For example, under experimental conditions, intact turtles generate several rhythmic scratch motor patterns corresponding to non-rhythmic stimulation of different body regions. These patterns feature alternating phases of motoneuron activation that occur repeatedly, with different patterns distinguished by the relative timing and duration of activity of hip extensor, hip flexor, and knee extensor motoneurons. While the central pattern generator network responsible for these outputs has not been located, there is hope to use motoneuron recordings to deduce its properties. To this end, this work presents a model of a previously proposed central pattern generator network and analyzes its capability to produce two distinct scratch rhythms from a single neuron pool, selected by different combinations of tonic drive parameters but with fixed strengths of connections within the network. We show through simulation that the proposed network can achieve the desired multi-functionality, even though it relies on hip unit generators to recruit appropriately timed knee extensor motoneuron activity, including a delay relative to hip activation in rostral scratch. Furthermore, we develop a phase space representation, focusing on the inputs to and the intrinsic slow variable of the knee extensor motoneuron, which we use to derive sufficient conditions for the network to realize each rhythm and which illustrates the role of a saddle-node bifurcation in achieving the knee extensor delay. This framework is harnessed to consider bistability and to make predictions about the responses of the
Shahbazi, Hamed; Parandeh, Reyhaneh; Jamshidi, Kamal
2016-11-01
In this paper a new design of neural networks is introduced, which is able to generate oscillatory patterns. The fundamental building block of the neural network is O-neurons that can generate an oscillation in its transfer functions. Since the natural policy gradient learning has been used in training a central pattern generator paradigm, it is called Natural Learner CPG Neural Networks (NLCPGNN). O-neurons are connected and coupled to each other in order to shape a network and their unknown parameters are found by a natural policy gradient learning algorithm. The main contribution of this paper is design of this learning algorithm which is able to simultaneously search for the weights and topology of the network. This system is capable to obtain any complex motion and rhythmic trajectory via first layer and learn rhythmic trajectories in the second layer and converge towards all these movements. Moreover this two layers system is able to provide various features of a learner model for instance resistance against perturbations, modulation of trajectories amplitude and frequency. Simulation of the learning system in the robot simulator (WEBOTS) that is linked with MATLAB software has been done. Implementation on a real NAO robot demonstrates that the robot has learned desired motion with high accuracy. These results show proposed system produces high convergence rate and low test errors.
Quality of Service for Real-Time Applications Over Next Generation Data Networks
Ivancic, William; Atiquzzaman, Mohammed; Bai, Haowei; Su, Hongjun; Jain, Raj; Duresi, Arjan; Goyal, Mukyl; Bharani, Venkata; Liu, Chunlei; Kota, Sastri
2001-01-01
This project, which started on January 1, 2000, was funded by NASA Glenn Research Center for duration of one year. The deliverables of the project included the following tasks: Study of QoS mapping between the edge and core networks envisioned in the Next Generation networks will provide us with the QoS guarantees that can be obtained from next generation networks. Buffer management techniques to provide strict guarantees to real-time end-to-end applications through preferential treatment to packets belonging to real-time applications. In particular, use of ECN to help reduce the loss on high bandwidth-delay product satellite networks needs to be studied. Effect of Prioritized Packet Discard to increase goodput of the network and reduce the buffering requirements in the ATM switches. Provision of new IP circuit emulation services over Satellite IP backbones using MPLS will be studied. Determine the architecture and requirements for internetworking ATN and the Next Generation Internet for real-time applications.
Condition Monitoring and Faults Diagnosis for Synchronous Generator Using Artificial Neural Networks
Directory of Open Access Journals (Sweden)
Omer Elfaki Elbashir
2013-09-01
Full Text Available Early detection and diagnosis of incipient fault is desirable for on line condition assessment production quality assurance and improved operational efficiency of synchronous generator running of power supply. Artificial Intelligent techniques are increasly used for condition monitoring and fault diagnosis of machines. In this paper, Artificial Neural Network (ANN approach employed for fault diagnosis in the generator, based on monitoring generator currents to give indication of the winding faults. Feed-forward Network, error back propagation training algorithm are used to perform the generator faults diagnosis and their values. NN which has been trained for all possible operating condition of the machine used to classify the incoming data. The inputs of the NN are the stator and rotor currents, and the output represents the running condition of the generator. The training of the NN achieved by the data through a mathematical model based approach to simulate the generator faults at various degree of severity.This paper evaluates through simulation line currents magnitude of the generator .The final results have been represented on a monitoring unit, built using matlab program, to give early warning of the generator failure.
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 ausgewäh
Generation of whistler-wave heated discharges with planar resonant RF networks.
Guittienne, Ph; Howling, A A; Hollenstein, Ch
2013-09-20
Magnetized plasma discharges generated by a planar resonant rf network are investigated. A regime transition is observed above a magnetic field threshold, associated with rf waves propagating in the plasma and which present the characteristics of whistler waves. These wave heated regimes can be considered as analogous to conventional helicon discharges, but in planar geometry.
Koene, R.A.; Tijms, B.; van Hees, P.; Postma, F.; de Ridder, A.; Ramakers, G.J.A.; van Pelt, J.; van Ooyen, A.
2009-01-01
We present a simulation framework, called NETMORPH, for the developmental generation of 3D large-scale neuronal networks with realistic neuron morphologies. In NETMORPH, neuronal morphogenesis is simulated from the perspective of the individual growth cone. For each growth cone in a growing axonal o
Niesten, E.M.M.I.
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, del
Estimating Voltage Asymmetry Making by One Phase Micro-generator in Low Voltage Network
Directory of Open Access Journals (Sweden)
Marian Sobierajski
2014-12-01
Full Text Available Connection of one phase micro-generator to the low voltage network increases voltage asymmetry. The voltage asymmetry is defined as the quotient of negative and positive voltage components. The mathematical background of exact and rough computation of the asymmetry quotient is presented in the paper. Considerations are illustrated by simple examples.
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
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 ausgewäh
Channel-Based Key Generation for Encrypted Body-Worn Wireless Sensor Networks
Van Torre, Patrick
2016-01-01
Body-worn sensor networks are important for rescue-workers, medical and many other applications. Sensitive data are often transmitted over such a network, motivating the need for encryption. Body-worn sensor networks are deployed in conditions where the wireless communication channel varies dramatically due to fading and shadowing, which is considered a disadvantage for communication. Interestingly, these channel variations can be employed to extract a common encryption key at both sides of the link. Legitimate users share a unique physical channel and the variations thereof provide data series on both sides of the link, with highly correlated values. An eavesdropper, however, does not share this physical channel and cannot extract the same information when intercepting the signals. This paper documents a practical wearable communication system implementing channel-based key generation, including an implementation and a measurement campaign comprising indoor as well as outdoor measurements. The results provide insight into the performance of channel-based key generation in realistic practical conditions. Employing a process known as key reconciliation, error free keys are generated in all tested scenarios. The key-generation system is computationally simple and therefore compatible with the low-power micro controllers and low-data rate transmissions commonly used in wireless sensor networks. PMID:27618051
On the Potential of PUF for Pseudonym Generation in Vehicular Networks
Petit, Jonathan; Bösch, Christoph; 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 creat
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...
Channel-Based Key Generation for Encrypted Body-Worn Wireless Sensor Networks.
Van Torre, Patrick
2016-09-08
Body-worn sensor networks are important for rescue-workers, medical and many other applications. Sensitive data are often transmitted over such a network, motivating the need for encryption. Body-worn sensor networks are deployed in conditions where the wireless communication channel varies dramatically due to fading and shadowing, which is considered a disadvantage for communication. Interestingly, these channel variations can be employed to extract a common encryption key at both sides of the link. Legitimate users share a unique physical channel and the variations thereof provide data series on both sides of the link, with highly correlated values. An eavesdropper, however, does not share this physical channel and cannot extract the same information when intercepting the signals. This paper documents a practical wearable communication system implementing channel-based key generation, including an implementation and a measurement campaign comprising indoor as well as outdoor measurements. The results provide insight into the performance of channel-based key generation in realistic practical conditions. Employing a process known as key reconciliation, error free keys are generated in all tested scenarios. The key-generation system is computationally simple and therefore compatible with the low-power micro controllers and low-data rate transmissions commonly used in wireless sensor networks.
Layer 1 VPN services in distributed next-generation SONET/SDH networks with inverse multiplexing
Ghani, N.; Muthalaly, M. V.; Benhaddou, D.; Alanqar, W.
2006-05-01
Advances in next-generation SONET/SDH along with GMPLS control architectures have enabled many new service provisioning capabilities. In particular, a key services paradigm is the emergent Layer 1 virtual private network (L1 VPN) framework, which allows multiple clients to utilize a common physical infrastructure and provision their own 'virtualized' circuit-switched networks. This precludes expensive infrastructure builds and increases resource utilization for carriers. Along these lines, a novel L1 VPN services resource management scheme for next-generation SONET/SDH networks is proposed that fully leverages advanced virtual concatenation and inverse multiplexing features. Additionally, both centralized and distributed GMPLS-based implementations are also tabled to support the proposed L1 VPN services model. Detailed performance analysis results are presented along with avenues for future research.
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.
The Nuclear Network Generator NETGEN v10.0: A Tool for Nuclear Astrophysics
Xu, Y.; Goriely, S.; Jorissen, A.; Takahashi, K.; Arnould, M.
2011-09-01
We present an updated release of the Brussels Nuclear Network Generator. NETGEN is a tool to help astrophysicists build nuclear reaction networks by generating tables of rates of light-particle (mostly n, p, α) induced reactions, nucleus-nucleus fusion reactions, and photodisintegrations, as well as β-decays and electron captures on temperature grids specified by the user. Nuclear reaction networks relevant to a large variety of astrophysical situations can be constructed, including Big-Bang nucleosynthesis, stellar hydrostatic and explosive hydrogen-, helium- and later burning phases, as well as the synthesis of heavy nuclides (s-, r-, p-, rp-, α-processes). The latest version, NETGEN v10.0, is available on the ULB-IAA website www.astro.ulb.ac.be/Netgen/form.html.