statistical analysis of airport network of china through the study of airport network of china anc composed of 128 airports nodes and 1165 flights edges we show the topological structure of anc conveys two characteristics of small worlds a short average path length 2 067 and a high degree of clustering 0 733 the cumulative degree distributions of both directed and undirected anc obey two regime power laws with different exponents i e the so called double pareto law in degrees and out degrees of each airport have positive correlations whereas the undirected degrees of adjacent airports have significant linear anticorrelations it is demonstrated both weekly and daily cumulative distributions of flight weights frequencies of anc have power law tails besides the weight of any given flight is proportional to the degrees of both airports at the two ends of that flight it is also shown the diameter of each subcluster consisting of an airport and all those airports to which it is linked is inversely proportional to its density of connectivity efficiency of anc and of its subclusters is measured through a simple definition in terms of that the efficiency of anc s subclusters increases as the density of connectivity does anc is found to have an efficiency of 0 484

a directed network of greek and roman mythology abstract we construct a directed network using a dictionary of greek and roman mythology in which the nodes represent the entries listed in the dictionary and we make directional links from an entry to other entries that appear in its explanatory part we find that this network is clearly not a random network but a directed scale free network in which the distributions of out degree and in degree follow a power law with exponents out 3 0 and in 2 5 respectively also we measure several quantities which describe the topological properties of the network and compare it to that of other real networks

mixing patterns in networks we study assortative mixing in networks the tendency for vertices in networks to be connected to other vertices that are like or unlike them in some way we consider mixing according to discrete characteristics such as language or race in social networks and scalar characteristics such as age as a special example of the latter we consider mixing according to vertex degree i e according to the number of connections vertices have to other vertices do gregarious people tend to associate with other gregarious people we propose a number of measures of assortative mixing appropriate to the various mixing types and apply them to a variety of real world networks showing that assortative mixing is a pervasive phenomenon found in many networks we also propose several models of assortatively mixed networks both analytic ones based on generating function methods and numerical ones based on monte carlo graph generation techniques we use these models to probe the properties of networks as their level of assortativity is varied in the particular case of mixing by degree we find strong variation with assortativity in the connectivity of the network and in the resilience of the network to the removal of vertices

theory of differential offset continuation i introduce a partial differential equation to describe the process of prestack reflection data transformation in the offset midpoint and time coordinates the equation is proved theoretically to provide correct kinematics and amplitudes on the transformed constant offset sections solving an initial value problem with the proposed equation leads to integral and frequency domain offset continuation operators which reduce to the known forms of dip moveout operators in the case of continuation to zero offset

the applicability of dip moveout azimuth moveout in the presence of caustics reflection seismic data continuation is the computation of data at source and receiver locations that differ from those in the original data using whatever data are available we develop a general theory of data continuation in the presence of caustics and illustrate it with three examples dip moveout dmo azimuth moveout amo and offset continuation this theory does not require knowledge of the reflector positions we construct the output data set from the input through the composition of three operators an imaging operator a modeling operator and a restriction operator this results in a single operator that maps directly from the input data to the desired output data we use the calculus of fourier integral operators to develop this theory in the presence of caustics for both dmo and amo we compute impulse responses in a constant velocity model and in a more complicated model in which caustics arise this analysis reveals errors that can be introduced by assuming for example a model with a constant vertical velocity gradient when the true model is laterally heterogeneous data continuation uses as input a subset common offset common angle of the available data which may introduce artifacts in the continued data one could suppress these artifacts by stacking over a neighborhood of input data using a small range of offsets or angles for example we test data continuation on synthetic data from a model known to generate imaging artifacts we show that stacking over input scattering angles suppresses artifacts in the continued data

assortativity and act degree distribution of some collaboration networks empirical investigation results on weighted and un weighted assortativity act degree distribution degree distribution and node strength distribution of nine real world collaboration networks have been presented the investigations propose that act degree distribution degree distribution and node strength distribution usually show so called shifted power law spl function forms which can continuously vary from an ideal power law to an ideal exponential decay two parameters a and z can be used for description of the distribution functions another conclusion is that assortativity coefficient and the parameter a or z is monotonously dependent on each other by the collaboration network evolution model introduced in a reference p zhang et al physica a 360 2006 599 we analytically derived the spl distributions which typically appeared in general situations where nodes are selected partially randomly with a probability p and partially by linear preferential principle with the probability 1 p the analytic discussion gives an explicit expression on the relationship between the random selection proportion p and the parameters a and z the numerical simulation results by the model show a monotonic dependence of assortativity on the random selection proportion p the empirically obtained assortativity versus a or z curve for the four collaboration networks with small maximal act size t max shows a good agreement with the model prediction according to the curves one can qualitatively judge the random selection proportion of the real world network in its evolution process r 2007 elsevier b v all rights reserved

regularizing 3 d data sets with dmo the combination of dmo and dmo 1 is used here to change the original acquisition geometry of a 3 d seismic data set into a more convenient form for example irregular 3 d surveys can be projected onto a regular midpoint offset grid with zero source receiver azimuth and equal increments in offset the algorithm presented here is based on a new nonaliased 3 d dmo algorithm in f x domain it does not require any knowledge of the velocity function for constant or rms velocity variations the computer program was designed to process and to output very large multifold 3 d data sets a synthetic example of a point diffractor in 3 d space and a 3 d experiment in a physical modeling tank are used to demonstrate the procedure in both cases the results obtained after the data set is regularized are compared with a data set that was acquired initially with the desired configuration these comparisons show very good agreement analysis of the procedure indicates that it may not reconstruct avo correctly this i

bisimulations for weighted automata over an additively idempotent semiring weshowthatthemethodologyfordecidingtheexistenceandcomputationofthegreatestsimulationsandbisimulations developed in the framework of fuzzy automata m ciric et al fuzzy sets and systems 186 2012 100 139 208 2012 22 42 can be applied in a similar form to weighted automata over an additively idempotent semiring we define two types of simulations and four types of bisimulations for weighted automata over an additively idempotent semiring as solutions to particular systems of matrix inequalities and we provide polynomial time algorithms for deciding whether there is a simulation or bisimulation of a given type between two weighted automata and for computing the greatest one if it exists the algorithms are based on the concept of relative boolean residuation for matrices over an additively idempotent semiring that we introduce here we also prove that two weighted automata a and b are forward bisimulation equivalent i e there is a row and column complete forward bisimulation between them if and only if the factor weighted automata with respect to the greatest forward bisimulation equivalence matrices on a and b are isomorphic in addition we show that the factor weighted automaton with respect to the greatest forward bisimulationequivalence matrix on aweighted automaton a is the unique upto an isomorphism minimal automaton in the class of all weighted automata which are forward bisimulation equivalent to a

topology of technology graphs small world patterns in electronic circuits recent theoretical studies and extensive data analyses have revealed a common feature displayed by biological social and technological networks the presence of small world patterns here we analyze this problem by using several graphs obtained from one of the most common technological systems electronic circuits it is shown that both analogic and digital circuits exhibit small world behavior we conjecture that the small world pattern arises from the compact design in which many elements share a small close physical neighborhood plus the fact that the system must define a single connected component which requires shortcuts connecting different integrated clusters the degree distributions displayed are consistent with a conjecture concerning the sharp cutoffs associated to the presence of costly connections amaral et al proc natl acad sci usa 97 11 149 2000 thus providing a limit case for the classes of universality of small world patterns from real artificial networks the consequences for circuit design are outlined

dynamic weight evolution network with preferential attachment abstract a dynamic weight evolution network with preferential attachment is introduced the network includes two significant characteristics i topological growth triggered by newly added node with m links at each time step each new edge carries an initial weight growing nonlinearly with time ii weight dynamics the weight between two existing nodes experiences increasing or decreasing in a nonlinear way by using continuum theory and mean field method we study the strength the degree the weight and their distributions we find that the distributions exhibit a power law feature in particular the relationship between the degree and the strength is nonlinear and the power law exponents of the three are the same all the theoretical predictions are successfully contrasted with numerical simulations

from unweighted to weighted networks with local information abstract in this paper we analyze an evolving model with local information which can generate a class of networks by choosing different values of the parameter p the model introduced exhibits the transition from unweighted networks to weighted networks because the distribution of the edge weight can be widely tuned with the increase in the local information the degree correlation of the network transforms from assortative to disassortative we also study the distribution of the degree strength and edge weight which all show crossover between exponential and scale free finally an application of the proposed model to the study of the synchronization is considered it is concluded that the synchronizability is enhanced when the heterogeneity of the edge weight is reduced

stabilizing weighted complex networks real networks often consist of local units which interact with each other via asymmetric and heterogeneous connections in this paper the v stability problem is investigated for a class of asymmetric weighted coupled networks with nonidentical node dynamics which includes the unweighted network as a special case pinning control is suggested to stabilize such a coupled network the complicated stabilization problem is reduced to measuring the semi negative property of the characteristic matrix which embodies not only the network topology but also the node self dynamics and the control gains it is found that network stabilizability depends critically on the second largest eigenvalue of the characteristic matrix the smaller the second largest eigenvalue is the more the network is pinning controllable numerical simulations of two representative networks composed of non chaotic systems and chaotic systems respectively are shown for illustration and verification

modeling the evolution of weighted networks we present a general model for the growth of weighted networks in which the structural growth is coupled with the edges weight dynamical evolution the model is based on a simple weight driven dynamics and a weights reinforcement mechanism coupled to the local network growth that coupling can be generalized in order to include the effect of additional randomness and nonlinearities which can be present in real world networks the model generates weighted graphs exhibiting the statistical properties observed in several real world systems in particular the model yields a nontrivial time evolution of vertices properties and scale free behavior with exponents depending on the microscopic parameters characterizing the coupling rules very interestingly the generated graphs spontaneously achieve a complex hierarchical architecture characterized by clustering and connectivity correlations varying as a function of the vertices degree

antileakage fourier transform for seismic data regularization in higher dimensions wide azimuth seismic data sets are generally acquired more sparsely than narrow azimuth seismic data sets this brings new challenges to seismic data regularization algorithms which aim to reconstruct seismic data for regularly sampled acquisition geometries from seismic data recorded from irregularly sampled acquisition geometries the fourier basedseismicdataregularizationalgorithmfirstestimates the spatial frequency content on an irregularly sampled input grid then it reconstructs the seismic data on any desired grid three main difficulties arise in this process the spectral leakage problem the accurate estimation of fourier components and the effective antialiasing scheme used inside the algorithm the antileakage fourier transform algorithm can overcome the spectral leakage problem and handles aliased data to generalize it to higher dimensions we propose an area weighting scheme to accurately estimate the fourier components however the computational cost dramatically increases with the sampling dimensions a windowed fourier transform reduces the computational cost in high dimension applications but causes undersampling in wavenumber domain and introduces some artifacts known as gibbs phenomena as a solution we propose a wavenumber domain oversampling inversion scheme the robustness and effectiveness of the proposed algorithm are demonstrated with some applications to both synthetic and real data examples

visibility graph analysis of heart rate time series and bio marker of congestive heart failure abstract study of rr interval time series for congestive heart failure had been an area of study with different methods including non linear methods in this article the cardiac dynamics of heart beat are explored in the light of complex network analysis viz visibility graph method heart beat rr interval time series data taken from physionet database 46 47 belonging to two groups of subjects diseased congestive heart failure 29 in number and normal 54 in number are analyzed with the technique the overall results show that a quantitative parameter can significantly differentiate between the diseased subjects and the normal subjects as well as different stages of the disease further the data when split into periods of around 1 hour each and analyzed separately also shows the same consistent differences this quantitative parameter obtained using the visibility graph analysis thereby can be used as a potential bio marker as well as a subsequent alarm generation mechanism for predicting the onset of congestive heart failure

analytic results for scaling function and moments for a different type of avalanche in the bak sneppen evolution model starting from the master equation for the hierarchical structure of avalanches of a different kind within the frame of the bak sneppen evolution model we derive the exact formula of the scaling function describing the probability distribution of avalanches the scaling function displays features required by the scaling ansatz and verified by simulations using the scaling function we investigate the avalanche moment denoted by s k ensuremath delta overline f it is found that for any non negative integer k s k ensuremath delta overline f diverges as ensuremath delta f ensuremath k which gives an infinite group of exact critical exponents simulation outcomes of avalanche moments with k 1 2 3 are found to be consistent with the corresponding analytical results

offset continuation stacking theory and proof of concept abstractthe offset continuation operation oco is a seismic configuration transform designed to simulate a seismic section as if obtained with a certain source receiver offset using the data measured with another offset based on this operation we have introduced the oco stack which is a multiparameter stacking technique that transforms 2d 2 5d prestack multicoverage data into a stacked common offset co section similarly to common midpoint and common reflection surface stacks the oco stack does not rely on an a priori velocity model but provided velocity information itself because oco is dependent on the velocity model used in the process the method can be combined with trial stacking techniques for a set of models thus allowing for the extraction of velocity information the algorithm consists of data stacking along so called oco trajectories which approximate the common reflection point trajectory i e the position of a reflection event in the multicoverage data as a function of source rec

different hierarchy of avalanches observed in the bak sneppen evolution model a quantity overline f denoting the average fitness of an ecosystem is introduced in the bak sneppen model through this quantity a different hierarchy of avalanches f 0 avalanche is observed in the evolution of bak sneppen model an exact gap equation governing the self organization of the model is presented in terms of overline f it is found that self organized threshold f c can be exactly obtained two basic exponents of the new avalanche ensuremath tau avalanche distribution and d avalanche dimension are given through simulations of one and two dimensional bak sneppen models it is suggested that overline f may be a good quantity in determining the emergence of criticality

the pareto law of incomes an explanation and an extension abstract a stochastic model for the generation of observed income distributions is used to provide an explanation for the pareto law of incomes analysis of the model also yields a prediction of paretian power law behaviour in the lower tail of the distribution and this is shown to occur in a number of empirical distributions a tractable four parameter distribution is derived and shown to fit extremely well to a number of different empirical income distributions

random graphs with arbitrary degree distributions and their applications recent work on the structure of social networks and the internet has focused attention on graphs with distributions of vertex degree that are significantly different from the poisson degree distributions that have been widely studied in the past in this paper we develop in detail the theory of random graphs with arbitrary degree distributions in addition to simple undirected unipartite graphs we examine the properties of directed and bipartite graphs among other results we derive exact expressions for the position of the phase transition at which a giant component first forms the mean component size the size of the giant component if there is one the mean number of vertices a certain distance away from a randomly chosen vertex and the average vertex vertex distance within a graph we apply our theory to some real world graphs including the worldwide web and collaboration graphs of scientists and fortune 1000 company directors we demonstrate that in some cases random graphs with appropriate distributions of vertex degree predict with surprising accuracy the behavior of the real world while in others there is a measurable discrepancy between theory and reality perhaps indicating the presence of additional social structure in the network that is not captured by the random graph

statistical analysis of 22 public transport networks in poland public transport systems in 22 polish cities have been analyzed the sizes of these networks range from n 152 to 2881 depending on the assumed definition of network topology the degree distribution can follow a power law or can be described by an exponential function distributions of path lengths in all considered networks are given by asymmetric unimodal functions clustering assortativity and betweenness are studied all considered networks exhibit small world behavior and are hierarchically organized a transition between dissortative small networks n approximately or 500 is observed

a study on some urban bus transport networks abstract in this paper we present the empirical investigation results on the urban bus transport networks btns of four major cities in china in btn nodes are bus stops two nodes are connected by an edge when the stops are serviced by a common bus route the empirical results show that the degree distributions of btns take exponential function forms other two statistical properties of btns are also considered and they are suggested as the distributions of so called the number of stops in a bus route represented by s and the number of bus routes a stop joins by r the distributions of r also show exponential function forms while the distributions of s follow asymmetric unimodal functions to explain these empirical results and attempt to simulate a possible evolution process of btn we introduce a model by which the analytic and numerical result obtained agrees well with the empirical facts finally we also discuss some other possible evolution cases where the degree distribution shows a power law or an interpolation between the power law and the exponential decay

exact equations and scaling relations for f0 avalanche in the bak sneppen evolution model an infinite hierarchy of exact equations is derived for the newly observed f0 avalanche in the bak sneppen model by solving the first order exact equation we find that the critical exponent gamma governing the divergence of the average avalanche size is exactly 1 for all dimensions which has been confirmed by extensive simulations solution of the gap equation yields another universal result rho 1 rho is the exponent of relaxation to attractor scaling relations are established among the critical exponents gamma tau d sigma and nu for the f0 avalanche