a maximum entropy framework for nonexponential distributions probability distributions having power law tails are observed in a broad range of social economic and biological systems we describe here a potentially useful common framework we derive distribution functions for situations in which a joiner particle k pays some form of price to enter a community of size where costs are subject to economies of scale maximizing the boltzmann gibbs shannon entropy subject to this energy like constraint predicts a distribution having a power law tail it reduces to the boltzmann distribution in the absence of economies of scale we show that the predicted function gives excellent fits to 13 different distribution functions ranging from friendship links in social networks to protein protein interactions to the severity of terrorist attacks this approach may give useful insights into when to expect power law distributions in the natural and social sciences

error estimation and adaptation for functional outputs in time dependent flow problems the paper presents an adjoint based approach for determining global error in the time domain that is relevant to functional outputs from unsteady flow simulations the algorithm is derived for the unsteady euler equations that are discretized for second order accuracy in both space and time and takes into account the effect of dynamic meshes in addition to error due to temporal resolution the formulation also takes into account algebraic error arising from partial convergence of the governing equations at each implicit time step the resulting error distributions are then used to drive adaptation of the temporal resolution and the convergence tolerances for the governing equations at each time step the method is demonstrated in the context of both time integrated and instantaneous functionals and the results are compared against traditional adaptation methods

multifractal property of chinese stock market in the csi 800 index based on mf dfa approach abstract csi 800 index consists of csi 500 index and csi 300 index aiming to reflect the performance of stocks with large mid and small size of china a share market in this paper we analyze the multifractal structure of chinese stock market in the csi 800 index based on the multifractal detrended fluctuation analysis mf dfa method we find that the fluctuation of the closing logarithmic returns have multifractal properties the shape and width of multifractal spectrum are depended on the weighing order q more interestingly we observe a bigger market crash in june august 2015 than the one in 2008 based on the local hurst exponents the result provides important information for further study on dynamic mechanism of return fluctuation and whether it would trigger a new financial crisis

implicit time discretization schemes for mixed least squares finite element formulations abstract this work is an extension of the ideas in averweg et al 2019 with the focus on a detailed investigation of implicit time discretization schemes to model instationary fluid flow based on the incompressible navier stokes equations and linear elastodynamic structural behavior the variational approaches for fluid and solid mechanics are based on a mixed least squares finite element method the l 2 norm minimization of the residuals of the constructed first order systems of the governing differential equations is based on two field stress velocity sv functionals for the time discretization of the sv fluid formulation four different types of implicit integration schemes are investigated namely the houbolt method the crank nicolson method and two explicit singly diagonally implicit runge kutta methods esdirk the sv formulation for the solid is discretized applying the houbolt method the presented time integration schemes are validated investigating an unsteady fluid flow and an elastodynamic structural benchmark since both fluid and solid sv formulations are discretized using conforming finite element spaces in h div and h 1 respectively the inherent fulfillment of coupling conditions when modeling fluid structure interaction problems is given a priori therefore the applicability is also examined by two simplified fsi problems for small deformations in order to represent the main characteristics of the presented approach

multifractal analysis of chinese stock volatilities based on the partition function approach abstract we have performed a detailed multifractal analysis on the 1 min volatility of two indexes and 1139 stocks in the chinese stock markets based on the partition function approach the partition function q s scales as a power law with respect to the box size s the scaling exponents q form a nonlinear function of q statistical tests based on bootstrapping show that the extracted multifractal nature is significant at the 1 significance level the individual securities can be well modeled by the p model in turbulence with p 0 40 0 02 based on the idea of ensemble averaging including quenched and annealed average we treat each stock exchange as a whole and confirm the existence of multifractal nature in the chinese stock markets

multifractal detrended cross correlation analysis of carbon and crude oil markets abstract the complex dynamics between carbon and crude oil markets have been an increasingly interesting area of research in this paper we try to take a fresh look at the cross correlations between carbon and crude oil markets as well as their dynamic behavior employing multifractal detrended cross correlation analysis first we find that the return series of carbon and crude oil markets are significantly cross correlated second we confirm the existence of multifractality for the return series of carbon and crude oil markets by the multifractal detrended fluctuation analysis third based on the multifractal detrended cross correlation analysis we find the existence of power law cross correlations between carbon and crude oil markets the cross correlated behavior of small fluctuations is found to be more persistent than that of large fluctuations at last some relevant discussions and implications of the empirical results are presented

mesh independent spectra in the moving finite element equations we derive the moving finite element mfe equations for the solution of a scalar evolutionary equation in d space dimensions d geqq 1 and introduce the elementwise approach to mfe this approa

temporal adaptive euler navier stokes algorithm involving unstructured dynamic meshes a temporal adaptive algorithm for the time integration of the two dimensional euler or navier stokes equations is presented the flow solver involves an upwind flux split spatial discretization for the convective terms and central differencing for the shear stress and heat flux terms on an unstructured mesh of triangles the temporal adaptive algorithm is a time accurate integration procedure that allows flows with high spatial and temporal gradients to be computed efficiently by advancing each grid cell near its maximum allowable time step

spreading dynamics following bursty human activity patterns we study the susceptible infected model with power law waiting time distributions p ensuremath tau ensuremath tau ensuremath ensuremath alpha as a model of spreading dynamics under heterogeneous human activity patterns we found that the average number of new infections n t at time t decays as a power law in the long time limit n t t ensuremath ensuremath beta leading to extremely slow prevalence decay we also found that the exponent in the spreading dynamics ensuremath beta is related to that in the waiting time distribution ensuremath alpha in a way depending on the interactions between agents but insensitive to the network topology these observations are well supported by both the theoretical predictions and the long prevalence decay time in real social spreading phenomena our results unify individual activity patterns with macroscopic collective dynamics at the network level

on thompsonʼs conjecture for some finite simple groups in this article we prove a conjecture of j g thompson for an infinite class of simple groups of lie type more precisely we show that every finite group g with the property z g 1 and cs g cs psln q is necessarily isomorphic to psln q note that cs g is the set of lengths of conjugacy classes of g

linear groups with orders having certain large prime divisors in this paper we obtain a classification of those subgroups of the finite general linear group gld q with orders divisible by a primitive prime divisor of qe 1 for some in the course of the analysis we obtain new results on modular representations of finite almost simple groups in particular in the last section we obtain substantial extensions of the results of landazuri and seitz on small cross characteristic representations of some of the finite classical groups 1991 mathematics subject classification primary 20g40 secondary 20c20 20c33 20c34 20e99

individual and group dynamics in purchasing activity abstract as a major part of the daily operation in an enterprise purchasing frequency is in constant change recent approaches on the human dynamics can provide some new insights into the economic behavior of companies in the supply chain this paper captures the attributes of creation times of purchase orders to an individual vendor as well as to all vendors and further investigates whether they have some kind of dynamics by applying logarithmic binning to the construction of distribution plots it s found that the former displays a power law distribution with approximate exponent 2 0 while the latter is fitted by a mixture distribution with both power law and exponential characteristics obviously two distinctive characteristics are presented for the interval time distribution from the perspective of individual dynamics and group dynamics actually this mixing feature can be attributed to the fitting deviations as they are negligible for individual dynamics but those of different vendors are cumulated and then lead to an exponential factor for group dynamics to better describe the mechanism generating the heterogeneity of the purchase order assignment process from the objective company to all its vendors a model driven by product life cycle is introduced and then the analytical distribution and the simulation result are obtained which are in good agreement with the empirical data

adjoint based sensitivity formulation for fully coupled unsteady aeroelasticity problems a method to compute sensitivities for use in gradient based shape optimization applied to unsteady aeroelasticity problems is presented the method takes into account the coupling between all three fundamental aspects of computational aeroelasticity namely unsteady flow equations time varying structural response to aerodynamic loads and dynamic meshes that accommodate geometric deformations the devised method provides discretely exact sensitivities of time integrated and non time integrated objective functions with respect to design variables that control the shape of geometry the algorithm is formulated in a general manner and can be readily extended to coupled multidisciplinary problems involving any number of disciplines the algorithm is applied to a simple two dimensional flutter model to demonstrate the proof of concept

chaos in rainfall the question is posed regarding possible chaotic dynamics in the temporal rainfall of storm events chaotic dynamics implies a nonlinear deterministic system very sensitive to initial conditions which yields outputs indistinguishable from a stochastic process by standard techniques the trajectories of these systems in the phase space are characterized by being contained in a strange attractor of fractal dimension a time series of 1990 points of 15 s rainfall for the storm of october 25 1980 in boston is analyzed in detail toward this objective it is found that both the characteristics of the correlation integral and the lyapunov exponents of the historical data give preliminary support to the presence of chaotic dynamics with a strange attractor the implications of these findings for the modeling of storm rainfall and for the limits of predictability of the process are discussed jointly with the research challenges lying ahead in this field

measuring multifractality of stock price fluctuation using multifractal detrended fluctuation analysis abstract analyzing the shanghai stock price index daily returns using mf dfa method it is found that there are two different types of sources for multifractality in time series namely fat tailed probability distributions and non linear temporal correlations based on that a sliding window of 240 frequency data in 5 trading days was used to study stock price index fluctuation it is found that when the stock price index fluctuates sharply a strong variability is clearly characterized by the generalized hurst exponents h q therefore two measures h and based on generalized hurst exponents were proposed to compare financial risks before and after price limits and reform of non tradable shares the empirical results verify the validity of the measures and this has led to a better understanding of complex stock markets

dynamic numerical models of stock market price from microscopic determinism to macroscopic randomness abstract a variant of threshold dynamics is introduced to model the behaviors of a large assembly of dealers in a stock market although the microscopic evolution dynamics is deterministic the collective behaviors such as market prices show seemingly stochastic fluctuations the statistical properties of market price change can be well approximated by a simple discrete langevin type equation with random amplification the macroscopic stochastic equation is solved both numerically and analytically showing that the market price change generally follow power law distributions in the steady state the reason for the appearance of rapid decay in the distribution tails are discussed

time integration algorithms for the two dimensional euler equations on unstructured meshes explicit and implicit time integration algorithms for the two dimensional euler equations on unstructured grids are presented both cell centered and cell vertex finite volume upwind schemes utilizing roe s approximate riemann solver are developed for the cell vertex scheme a four stage runge kutta time integration a four stage runge kutta time integration with implicit residual averaging a point jacobi method a symmetric point gauss seidel method and two methods utilizing preconditioned sparse matrix solvers are presented for the cell centered scheme a runge kutta scheme an implicit tridiagonal relaxation scheme modeled after line gaussseidel a fully implicit lower upper lu decomposition and a hybrid scheme utilizing both runge kutta and lu methods are presented

mesh deformation strategy optimized by the adjoint method on unstructured meshes an adjoint based optimization procedure is proposed for improving the robustness and extending the range of linear elasticity based mesh deformation techniques using the values of the modulus of elasticity e defined in each mesh cell as the design variables the procedure seeks to determine an optimum distribution of e throughout the mesh in order to minimize a global objective function which reflects the skewness or lack of quality of the deformed mesh the technique is applied to highly stretched mixed element meshes in two and three dimensions on complex geometries and is shown to be capable of recovering a valid mesh in a small number of optimization cycles for cases where the non optimized linear elasticity approach fails however the solution of the optimization problem remains relatively costly in terms of cpu time compared to a non optimized mesh deformation calculation making this technique best suited for precomputing improved e distributions prior to the simulation or for use as a plug in module to be invoked in cases where the non optimized procedure fails

directional agglomeration multigrid techniques for high reynolds number viscous flows a preconditioned directional implicit agglomeration algorithm is developed for solving two and three dimensional viscous flows on highly anisotropic unstructured meshes of mixed element types the multigrid smoother consists of a pre conditioned point or line implicit solver which operates on lines constructed in the unstructured mesh using a weighted graph algorithm directional coarsening or agglomeration is achieved using a similar weighted graph algorithm a tight coupling of the line construction and directional agglomeration algorithms enables the use of aggressive coarsening ratios in the multigrid algorithm which in turn reduces the cost of a multigrid cycle convergence rates which are independent of the degree of grid stretching are demonstrated in both two and three dimensions further improvement of the three dimensional convergence rates through a gmres technique is also demonstrated

second order time accurate and geometrically conservative implicit schemes for flow computations on unstructured dynamic meshes abstract we consider the solution of two and three dimensional flow problems with moving boundaries using the arbitrary lagrangian eulerian formulation or dynamic meshes we focus on the case where spatial discretization is performed by unstructured finite volumes and or finite elements we formulate the consequence of the geometric conservation law on the second order implicit temporal discretization of the semi discrete equations governing such problems and use it as a guideline to construct a new family of second order time accurate and geometrically conservative implicit numerical schemes for flow computations on moving grids we apply these new algorithms to the solution of three dimensional flow problems with moving and deforming boundaries demonstrate their superior accuracy and computational efficiency and highlight their impact on the simulation of fluid structure interaction problems

effects of diversity and procrastination in priority queuing theory the different power law regimes empirical analyses show that after the update of a browser or the publication of the vulnerability of a software or the discovery of a cyber worm the fraction of computers still using the older browser or software version or not yet patched or exhibiting worm activity decays as a power law ensuremath sim 1 t ensuremath alpha with 0l ensuremath alpha ensuremath le 1 over a time scale of years we present a simple model for this persistence phenomenon framed within the standard priority queuing theory of a target task which has the lowest priority compared to all other tasks that flow on the computer of an individual we identify a time deficit control parameter ensuremath beta and a bifurcation to a regime where there is a nonzero probability for the target task to never be completed the distribution of waiting time mathcal t until the completion of the target task has the power law tail ensuremath sim 1 t 1 2 resulting from a first passage solution of an equivalent wiener process taking into account a diversity of time deficit parameters in a population of individuals the power law tail is changed into 1 t ensuremath alpha with ensuremath alpha 0 5 ensuremath infty including the well known case 1 t we also study the effect of procrastination defined as the situation in which the target task may be postponed or delayed even after the individual has solved all other pending tasks this regime provides an explanation for even slower apparent decay and longer persistence

scaling characteristics in the taiwan stock market some statistical tools including histogram spectral analysis and fractal theory were used on the daily taiwan stock price index tspi from 1987 to 2002 to examine the possible scale invariant behavior and the clustering characteristics in taiwan stock market it was found that the tspi data exhibited the characteristic of right skewed frequency distribution the long term memory and the possibility of scale invariance were roughly identified through the analysis of autocorrelation and power spectrum respectively the monofractal analysis was then performed by the box counting method scale invariance was clearly found in the time series and the box dimension was shown to be a decreasing function of the threshold index level implying multifractal characteristics i e the low and high regions scale differently to test this hypothesis the time series were transferred into a useful compact form through the multifractal formalism namely the q q and f plots the analysis confirmed the existence of multifractal characteristics in the investigated time series the origin of multifractal phenomena in taiwan stock market might be interpreted in terms of the multiplicative cascade process of stock market information

torsional springs for two dimensional dynamic unstructured fluid meshes abstract dynamic fluid grids are commonly used for the solution of flow problems with moving boundaries they are often represented by a network of fictitious lineal springs that can become unreliable when the fluid mesh undergoes large displacements and or deformations in this paper we propose to control the arbitrary motion of two dimensional dynamic unstructured fluid grids with additional torsional springs we show that such springs can be designed to prohibit the interpenetration of neighboring triangles and therefore to provide the method of spring analogy with the robustness needed for enlarging its range of applications we illustrate our new dynamic mesh motion algorithm with several examples that highlight its advantages in terms of robustness quality and performance

stochastic queueing theory approach to human dynamics recently numerous studies have shown that human dynamics cannot be described accurately by exponential laws for instance barabasi nature london 435 207 2005 demonstrates that waiting times of tasks to be performed by a human are more suitably modeled by power laws he presumes that these power laws are caused by a priority selection mechanism among the tasks priority models are well developed in queueing theory e g for telecommunication applications and this paper demonstrates the quasi immediate applicability of such a stochastic priority model to human dynamics by calculating generating functions and by studying them in their dominant singularity we prove that nonexponential tails result naturally contrary to popular belief however these are not necessarily triggered by the priority selection mechanism

discrete adjoint based approach for optimization problems on three dimensional unstructured meshes a comprehensive strategy for developing and implementing discrete adjoint methods for aerodynamic shape optimization problems is presented by linearizing each procedure in the entire optimization problem transposing each linearization and reversing the sequential order of operations the adjoint of the complete optimization problem including flow equations and mesh motion equations is constructed in a modular and verifiable fashion this construction is also shown to produce minimal memory overheads and retain the same convergence characteristics of the original analysis problem in the sensitivity analysis these techniques are implemented in a three dimensional unstructured multigrid navierstokes solver and demonstrated on a transonic drag reduction problem for a wing body configuration

unsteady transonic two dimensional euler solutions using finite elements a finite element solution of the unsteady euler equations is presented and demonstrated for two dimensional airfoil configurations oscillating in transonic flows computations are performed by spatially discretizing the conservation equations using the galerkin weighted residual method and then employing a multistage rungekutta scheme to march forward in time triangular finite elements are employed in an unstructured o mesh computational grid surrounding the airfoil grid points are fixed in space at the far field boundary and are constrained to move with the airfoil surface to form the near field boundary a mesh deformation scheme has been developed to efficiently move interior points in a smooth fashion as the airfoil undergoes rigid body pitch and plunge motion both steady and unsteady results are presented and a comparison is made with solutions obtained using finite volume techniques the effects of using either a lumped or consistent mass matrix were studied and are presented results show the finite element method provides an accurate solution for unsteady transonic flows about isolated airfoils he accurate determination of the unsteady flowfield surrounding an oscillating airfoil or wing in transonic flow is of paramount importance in the prediction of the flutter characteristics of the body transonic flutter remains an active research topic because of the continued interest by both the military and commercial sectors to operate in these flight regimes with vehicles that are ever lighter and as a result more flexible typically analysis of fluid structure interaction in flight vehicles involves describing the vehicle structure using finite elements whereas finite difference methods are used to model the surrounding fluid coupling of the two dissimilar models then presents problems because of the disparity between the two solution techniques additional complexities arise because of phase mismatching between the fluid pressures and the displacements of the structure it seems a natural progression to use finite element methods to describe the behavior of both the fluid and structure thus bringing more commonality into the analysis of the two media early research efforts concentrated on using the transonic small disturbance equation or the nonlinear full potential equation as the model for the gas dynamic behavior in transonic flows unfortunately this idealization leads to errors when strong shocks are present because of their inability to account for the production of entropy and vorticity to properly account for these effects within the framework of the conservation laws the euler equations must be used these equations although they neglect fluid viscosity have become the standard when unsteady transonic solutions are desired the absence of a viscosity representation is an important limitation of the present formulation and must be considered

modelling financial time series using multifractal random walks abstract multifractal random walks mrw correspond to simple solvable stochastic volatility processes moreover they provide a simple interpretation of multifractal scaling laws and multiplicative cascade process paradigms in terms of volatility correlations we show that they are able to reproduce most of the recent empirical findings concerning financial time series no correlation between price variations long range volatility correlations and multifractal statistics

empirical analysis on temporal statistics of human correspondence patterns abstract recently extensive empirical evidence shows that the timing of human behaviors obeys non possion statistics with heavy tailed interevent time distribution in this paper we empirically study the correspondence pattern of a great chinese scientist named hsue shen tsien both the interevent time distribution and response time distributions deviate from the poisson statistics showing an approximate power law decaying the two power law exponents are more or less the same about 2 1 which strongly support the hypothesis in a vazquez j g oliveira z dezso k i goh i kondor a l barabasi phys rev e 73 2006 036127 that the response time distribution of the tasks could in fact drive the interevent time distribution and both the two distributions should decay with the same exponent our result is against the claim in a vazquez j g oliveira z dezso k i goh i kondor a l barabasi phys rev e 73 2006 036127 which suggests the human correspondence pattern belongs to a universality class with exponent 1 5

convergence analysis of the gauss seidel preconditioner for discretized one dimensional euler equations we consider the nonlinear system of equations that results from the van leer flux vector splitting discretization of the one dimensional euler equations this nonlinear system is linearized at the discrete solution the main topic of this paper is a convergence analysis of block gauss seidel methods applied to this linear system of equations both the lexicographic and the symmetric block gauss seidel method are considered we derive results which quantify the quality of these methods as preconditioners these results show for example that for the subsonic case the symmetric gauss seidel method can be expected to be a much better preconditioner than the lexicographic variant sharp bounds for the condition number of the preconditioned matrix are derived

multifractal analysis of hang seng index in hong kong stock market abstract in this paper the daily hang seng index in hong kong stock market is analyzed by multifractal the correlation of the parameters of the multifractal spectra with the variation of close return z is studied statistically it is found that the amount of the variation of return is correlated with the amount of of that day the increase or decrease of the return is related to the positive or negative value of f the gain probability and the increasing day s probability can be higher than 70 at the larger f region and be lower than 20 at the more negative region

generalized priority queue network dynamics impact of team and hierarchy we study the effect of team and hierarchy on the waiting time dynamics of priority queue networks to this end we introduce generalized priority queue network models incorporating interaction rules based on team execution and hierarchy in decision making respectively it is numerically found that the waiting time distribution exhibits a power law for long waiting times in both cases yet with different exponents depending on the team size and the position of queue nodes in the hierarchy respectively the observed power law behaviors have in many cases a corresponding single or pairwise interacting queue dynamics suggesting that the pairwise interaction may constitute a major dynamic consequence in the priority queue networks it is also found that the reciprocity of influence is a relevant factor for the priority queue network dynamics

on the mass matrix spectrum bounds of wathen and the local moving finite elements of baines andrew wathen has shown that the eigenvalues of the diagonally preconditioned piecewise linear moving finite element mfe or finite element fe mass matrix in n dimensions lie in frac 1 2 1 frac 1 2 n baines using similar considerations has designed very local mfe methods with block diagonal mass matrices in this paper a simplified proof of wathen s basic spectrum bound is given it results from a simple comparison bound between the l 2 norm and a certain diagonal norm for discontinuous piecewise linear functions on an arbitrary triangular grid the simplicity of our comparison lets us extend wathen s result to other situations such as miller s gradient weighted mfe method gwmfe it also lets us design very local mfe and fe and gwmfe methods which minimize the pde residual dot u l u not in l 2 norm but in a comparable norm these methods turn out to be equivalent to those of baines these methods retain the desired conservation properties for pde s in conservation l

a threshold model for australian stock exchange equities abstract in this paper we present a threshold model to describe the phenomena of zero return enhancement that is present in australian stock exchange data we examine the intraday behaviour of the asx data and construct a new measure for the market activity using principal component analysis we use this measure to create a business time scale that keeps the level of zero return enhancement constant throughout trading hours operating in this new time scale we fit the model to data for small and large time scales and find that the model affords an excellent approximation of the distribution of stock returns

human dynamics scaling characteristics for aerial inbound logistics operation abstract in recent years the study of power law scaling characteristics of real life networks has attracted much interest from scholars it deviates from the poisson process in this paper we take the whole process of aerial inbound operation in a logistics company as the empirical object the main aim of this work is to study the statistical scaling characteristics of the task restricted work patterns we found that the statistical variables have the scaling characteristics of unimodal distribution with a power law tail in five statistical distributions that is to say there obviously exists a peak in each distribution the shape of the left part closes to a poisson distribution and the right part has a heavy tailed scaling statistics furthermore to our surprise there is only one distribution where the right parts can be approximated by the power law form with exponent 1 50 others are bigger than 1 50 three of four are about 2 50 one of four is about 3 00 we then obtain two inferences based on these empirical results first the human behaviors probably both close to the poisson statistics and power law distributions on certain levels and the human computer interaction behaviors may be the most common in the logistics operational areas even in the whole task restricted work pattern areas second the hypothesis in vazquez et al 2006 a vazquez j g oliveira z dezso k i goh i kondor a l barabasi modeling burst and heavy tails in human dynamics phys rev e 73 2006 036127 is probably not sufficient it claimed that human dynamics can be classified as two discrete university classes there may be a new human dynamics mechanism that is different from the classical barabasi models

on thompson s conjecture abstract let g be a finite group and n g n n g has a conjugacy class c such that c n professor j g thompson has conjectured that if g be a finite group with z g 1 and m a nonabelian simple group satisfying that n g n m then g m we have proved that if m is a sporadic simple group then thompson s conjecture is correct in this paper we shall further prove that if m is a finite simple group having at least three prime graph components then the conjecture is also correct

implicit method for the computation of unsteady flows on unstructured grids an implicit method for the computation of unsteady flows on unstructured grids is presented following a finite difference approximation for the time derivative the resulting nonlinear system of equations is solved at each time step by using an agglomeration multigrid procedure the method allows for arbitrarily large time steps and is efficient in terms of computational effort and storage inviscid and viscous unsteady flows are computed to validate the procedure the issue of the mass matrix which arises with vertex centered finite volume schemes is addressed the present formulation allows the mass matrix to be inverted indirectly a mesh point movement and reconnection procedure is described that allows the grids to evolve with the motion of bodies as an example of flow over bodies in relative motion flow over a multi element airfoil system undergoing deployment is computed

fractal analysis on human dynamics of library loans abstract in this paper the fractal characteristic of human behaviors is investigated from the perspective of time series constructed with the amount of library loans the values of the hurst exponent and length of non periodic cycle calculated through rescaled range analysis indicate that the time series of human behaviors and their sub series are fractal with self similarity and long range dependence then the time series are converted into complex networks by the visibility algorithm the topological properties of the networks such as scale free property and small world effect imply that there is a close relationship among the numbers of repetitious behaviors performed by people during certain periods of time our work implies that there is intrinsic regularity in the human collective repetitious behaviors the conclusions may be helpful to develop some new approaches to investigate the fractal feature and mechanism of human dynamics and provide some references for the management and forecast of human collective behaviors

effect of linear and nonlinear filters on multifractal analysis in this paper we investigate how various linear and nonlinear transformations affect the multifractal properties of both artificial and traffic signals using the multifractal analysis based on partition function with comparison with the multifractal detrended fluctuation analysis specifically we study the effect of three types of transforms which are often encountered in physical and biological processes linear nonlinear polynomial and logarithmic filters we compare the multifractal scaling properties of signals before and after the transform it is shown that linear filters do not change the multifractal properties while the effect of nonlinear polynomial depends on the power of the polynomial filter in addition the maximum value of the multifractal spectrum remains almost unchanged after the logarithmic filter however we find that the width of the multifractal spectrum changes significantly even for much smaller value of the offset parameter

price volume multifractal analysis and its application in chinese stock markets abstract an empirical research on chinese stock markets is conducted using statistical tools first the multifractality of stock price return series r i r i ln p t 1 ln p t and trading volume variation series v i v i ln v t 1 ln v t is confirmed using multifractal detrended fluctuation analysis furthermore a multifractal detrended cross correlation analysis between stock price return and trading volume variation in chinese stock markets is also conducted it is shown that the cross relationship between them is also found to be multifractal second the cross correlation between stock price p i and trading volume v i is empirically studied using cross correlation function and detrended cross correlation analysis it is found that both shanghai stock market and shenzhen stock market show pronounced long range cross correlations between stock price and trading volume third a composite index r based on price and trading volume is introduced compared with stock price return series r i and trading volume variation series v i r variation series not only remain the characteristics of original series but also demonstrate the relative correlation between stock price and trading volume finally we analyze the multifractal characteristics of r variation series before and after three financial events in china namely price limits reform of non tradable shares and financial crisis in 2008 in the whole period of sample to study the changes of stock market fluctuation and financial risk it is found that the empirical results verified the validity of r

invasion percolation and critical transient in the barabasi model of human dynamics we introduce an exact probabilistic description for l 2 of the barabasi model for the dynamics of a list of l tasks this permits us to study the problem out of the stationary state and to solve explicitly the extremal limit case where a critical behavior for the waiting time distribution is observed this behavior deviates at any finite time from that of the stationary state we study also the characteristic relaxation time for finite time deviations from stationarity in all cases showing that it diverges in the extremal limit confirming that these deviations are important at all time doi 10 1103 physrevlett 98 208701

generalized autoregressive conditional heteroskedasticity a natural generalization of the arch autoregressive conditional heteroskedastic process introduced in engle 1982 to allow for past conditional variances in the current conditional variance equation is proposed stationarity conditions and autocorrelation structure for this new class of parametric models are derived maximum likelihood estimation and testing are also considered finally an empirical example relating to the uncertainty of the inflation rate is presented

multifractal detrended fluctuation analysis of sheep livestock prices in origin abstract the multifractal detrended fluctuation analysis mf dfa is used to verify whether or not the returns of time series of prices paid to farmers in original markets can be described by the multifractal approach by way of example 5 weekly time series of prices of different breeds slaughter weight and market differentiation from 2000 to 2012 are analyzed results obtained from the multifractal parameters and multifractal spectra show that the price series of livestock products are of a multifractal nature the hurst exponent shows that these time series are stationary signals some of which exhibit long memory merino milk fed in seville and segurena paschal in jaen short memory merino paschal in cordoba and segurena milk fed in jaen or even are close to an uncorrelated signals merino paschal in seville mf dfa is able to discern the different underlying dynamics that play an important role in different types of sheep livestock markets such as degree and source of multifractality in addition the main source of multifractality of these time series is due to the broadness of the probability function instead of the long range correlation properties between small and large fluctuations which play a clearly secondary role

conservative rezoning algorithm for generalized two dimensional meshes a method is presented for transferring a conserved quantity q from one generalized mesh to another when the volumetric density of q is uniform within each cell of the original mesh

scaling in the norwegian stock market the main objective of this paper is to investigate the validity of the much used assumptions that stock market returns follow a random walk and are normally distributed for this purpose the concepts of chaos theory and fractals are applied two independent models are used to examine price variations in the norwegian and us stock markets the first model used is the range over standard deviation or r s statistic which tests for persistence or antipersistence in the time series both the norwegian and us stock markets show significant persistence caused by long run memory components in the series in addition an average non periodic cycle of four years is found for the us stock market these results are not consistent with the random walk assumption the second model investigates the distributional scaling behaviour of the high frequency price variations in the norwegian stock market the results show a remarkable constant scaling behaviour between different time intervals this means that there is no intrinsic time scale for the dynamics of stock price variations the relationship can be expressed through a scaling exponent describing the development of the distributions as the time scale changes this description may be important when constructing or improving pricing models such that they coincide more closely with the observed market behaviour the empirical distributions of high frequency price variations for the norwegian stock market is then compared to the levy stable distribution with the relevant scaling exponent found by using the r s and distributional scaling analysis good agreement is found between the levy profile and the empirical distribution for price variations less than 6 standard deviations covering almost three orders of magnitude in the data for probabilities larger than 6 standard deviations there seem to be an exponential fall off from the levy profile in the tails which indicates that the second moment may be finite

fast dynamic grid deformation based on delaunay graph mapping a simple and efficient dynamic grid deformation technique is proposed for computing unsteady flow problems with geometrical deformation relative body movement or shape changes due to aerodynamic optimisation and fluid structure interaction a delaunay graph of the solution domain is first generated which can be moved easily during the geometric dynamic deformation even for very large distortion a one to one mapping between the delaunay graph and the computational grid is maintained during the movement therefore the new computational grid after the dynamic movement can be generated efficiently through the mapping while maintaining the primary qualities of the grid while most dynamic grid deformation techniques are iterative based on the spring analogy the present method is non iterative and much more efficient on the other hand in comparison with dynamic grid techniques based on transfinite interpolation for structured grids it offers both geometric and cell topology flexibility which is crucial for many unsteady flow problems involving geometric deformation and relative motions the method is demonstrated through some typical unsteady flow test cases including a pitching aerofoil in a fixed domain boundary relative movement between multi element aerofoils due to flap deployment for high lift a deformable sphere in a fixed cube and a three dimensional flexible wing with large deformation

godunov type method on non structured meshes for three dimensional moving boundary problems abstract this paper presents a numerical method for the computation of compressible flows in domains whose boundaries move in a well defined predictable manner the method uses the space time formulation by godunov while the discretization is conducted on non structured tetrahedral meshes using roe s approximate riemann solver an implicit time stepping and a muscl type interpolation the computation of the geometrical parameters required to take into account the movement of the boundaries is described examples including the calculation of the flow in the cylinder of an internal combustion engine illustrates the possibilities of the method

dynamic unstructured method for flows past multiple objects in relative motion a new methodology is developed to simulate unsteady flows about objects in relative motion and compute the trajectory of their motion as determined by this flowfield the method couples the fluid dynamics and rigid body dynamics equations to capture the time dependent interference between stationary and moving boundaries the unsteady compressible inviscid euler equations are solved on dynamic unstructured grids by an explicit finite volume upwind method for efficiency the grid adaptation is perfomed within a window around the moving object the eulerian equations of the rigid body dynamics are solved by a runge kutta method in a noninertial frame of reference this dynamic unstructured flow solver is validated by computing the flow past a sinusoidally pitching airfoil and comparing these results with the experimental data the trajectory code is tested by computing the six degree of freedom trajectory of a store separating from a wing using the experimentally determined force and moment fields then comparing with the experimental trajectory finally the overall methodology is used for two two dimensional examples the flow past a pitching and plunging airfoil and the free call of a store after separation from a wing section

an accelerated fully coupled parallel 3d hybrid finite volume fluid structure interaction scheme abstract in this paper we propose a fast parallel 3d fully coupled partitioned hybrid unstructured finite volume fluid structure interaction fsi scheme spatial discretisation is effected via a vertex centred finite volume method where a hybrid nodal elemental strain procedure is employed for the solid in the interest of accuracy for the incompressible fluid a split step algorithm is presented which allows the entire fluid solid system to be solved in a fully implicit yet matrix free manner the algorithm combines a preconditioned gmres solver for implicit integration of pressures with dual timestepping on the momentum equations thereby allowing strong coupling of the system to occur through the inner solver iterations further acceleration is provided at little additional cost by applying lu sgs relaxation to the viscous and advective terms the solver is parallelised for distributed memory systems using mpi and its scaling efficiency evaluated the developed modelling technology is evaluated by application to two 3d fsi problems the advanced matrix free solvers achieve reductions in overall cpu time of up to 50 times while preserving close to linear parallel computing scaling using up to 128 cpus for the problems considered

multifractal description of stock price index fluctuation using a quadratic function fitting abstract in order to obtain a quantitative multifractal characterization of the stock price index the multifractal spectrum of shanghai stock price index time series in 2005 was investigated and the multifractal spectrum was fitted using a quadratic function a sliding window of 240 frequency data in 5 trading days was used to investigate the stock price index fluctuation the multifractal parameters and coefficients in each window were obtained by fitting the local multifractal spectrum using a quadratic function it is found that when the stock price index fluctuates sharply a strong variability is clearly characterized by the multifractal parameters and the quadratic function coefficients this has led to a better understanding of complex stock markets

higher order time integration schemes for aeroelastic applications on unstructured meshes efficient techniques for computational aeroelasticity on unstructured meshes are investigated these include the formulation of a fourth order implicit runge kutta time integration scheme a third order backward difference time integration scheme and a second order backward difference time integration scheme for the coupled system of flow and structural equations strong coupling between the flow solution and structural equations is maintained by fully converging the fully coupled system at each time step or stage the time integration schemes are constructed such that discrete conservation is maintained in the flow solution in the presence of dynamically deforming meshes by verifying the discrete geometric conservation law efficient multigrid solution techniques are devised for solving both the governing flow equations and the mesh motion equations using the same agglomerated coarse levels for both problems the flutter boundary prediction of the agard 445 6 wing is used to demonstrate the accuracy and efficiency of these techniques as well as the sensitivity of flutter boundary prediction to time step size and temporal errors

adjoint based airfoil optimization with adaptive isogeometric discontinuous galerkin method abstract in this work an adjoint based airfoil shape optimization algorithm is developed based on the adaptive isogeometric discontinuous galerkin method for compressible euler equations to investigate the significance of each design variable of airfoil b spline parameterization we first parameterize the airfoil by b spline curve approximation with some control points viewed as design variables and build the b spline representation of the flow field with the curve to apply the goal oriented h adaptive isogeometric dg method for flow solution then we compute and employ the discrete adjoint solutions for both multi target error estimation in adaptive mesh refinement with the isogeometric nature not only all the geometrical cells but also the numerical basis functions can be analytically expressed by the design variables indicating that the numerical solutions and objective could be differentiable with respect to those variables consequently the gradient is totally computed in an accurate approach and the sensitivity analysis is thus improved by reducing the spatial discretization error and introducing the analytical expression of derivative to reveal the key parameters for optimization in an intuitive and efficient manner although the sqp optimization algorithm is adopted in the paper the given accurate gradient can be applied to any gradient based optimization algorithm the proposed algorithm is demonstrated on rae2822 airfoil with inviscid transonic flow where the shape is optimized to minimize the drag coefficient at a constrained lift and airfoil area the numerical results show that the drag is much more sensitive to the design variables near the tailing edge at the beginning but sensitivity is reduced when optimal

memory and burstiness in dynamic networks a discrete time random process is described which can generate bursty sequences of events a bernoulli process where the probability of an event occurring at time t is given by a fixed probability x is modified to include a memory effect where the event probability is increased proportionally to the number of events that occurred within a given amount of time preceding t for small values of x the interevent time distribution follows a power law with exponent 2 x we consider a dynamic network where each node forms and breaks connections according to this process the value of x for each node depends on the fitness distribution x from which it is drawn we find exact solutions for the expectation of the degree distribution for a variety of possible fitness distributions and for both cases where the memory effect either is or is not present this work can potentially lead to methods to uncover hidden fitness distributions from fast changing temporal network data such as online social communications and fmri scans

scaling characteristics in aftershock sequence of earthquake abstract the possible scale invariant behavior and the clustering characteristics in aftershock sequence of chi chi taiwan main earthquake asccme that occurred in 1999 9 20 17 47 were investigated by means of some statistical tools histogram spectral analysis and fractal theory the examined data were constructed from the aftershocks that occurred at the locations defined at longitude 120 1 121 3 and latitude 23 3 24 5 during the 1999 9 20 17 47 1999 9 24 08 13 period it was found that the aftershock sequence exhibited the characteristic right skewed frequency distribution and could be well described with the lognormal distribution long term memory and the possibility of scale invariance were first roughly identified through the analysis of autocorrelation and power spectrum respectively scale invariance was clearly revealed with the aid of box counting method and the box dimension was shown to be a decreasing function of the threshold magnitude level i e the weak and intense regions scaled differently to verify the existence of multifractal characteristics the aftershock sequence was transferred into a useful compact form through the multifractal formalism namely the q q and f plots the analysis confirmed the existence of multifractal characteristics in the examined aftershock sequence the origin of both the pronounced right skewness and multifractal phenomena in aftershock sequence might be interpreted in terms of the multiplicative cascade process of the stress in the earth s crust a simple two scale cantor set with unequal scales and weights was then used to fit the calculated q q plot this model fitted remarkably well the entire spectrum of scaling exponents of the examined asccme

an advancing front delaunay triangulation algorithm designed for robustness abstract a new algorithm is described for generating an unstructured mesh about an arbitrary two dimensional configuration mesh points are generated automatically by the algorithm in a manner which ensures a smooth variation of elements and the resulting triangulation constitutes the delaunay triangulation of these points the algorithm combines the mathematical elegance and efficiency of delaunay triangulation algorithms with the desirable point placement features boundary integrity and robustness that are traditionally associated with advancing front type mesh generation strategies the method offers increased robustness over previous algorithms in that it cannot fail regardless of the initial boundary point distribution and the prescribed cell size distribution throughout the flow field

multifractal properties of chinese stock market in shanghai abstract 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

impact of interactions on human dynamics abstract queueing theory has been recently proposed as a framework to model the heavy tailed statistics of human activity patterns the main predictions are the existence of a power law distribution for the interevent time of human actions and two decay exponents 1 and 3 2 current models lack however a key aspect of human dynamics i e several tasks require or are determined by interactions between individuals here we introduce a minimal queueing model of human dynamics that already takes into account human human interactions to achieve large scale simulations we obtain a coarse grained version of the model allowing us to reach large interevent times and reliable scaling exponents estimations using this we show that the interevent distribution of interacting tasks exhibit the scaling exponents 2 3 2 and a series of numerable values between 3 2 and 1 this work demonstrates that within the context of queueing models of human dynamics interactions change the exponent of the power law distributed interevent times beyond the study of human dynamics these results are relevant to systems where the event of interest consists of the simultaneous occurrence of two or more events

an understanding of human dynamics in urban subway traffic from the maximum entropy principle abstract we studied the distribution of entry time interval in beijing subway traffic by analyzing the smart card transaction data and then deduced the probability distribution function of entry time interval based on the maximum entropy principle both theoretical derivation and data statistics indicated that the entry time interval obeys power law distribution with an exponential cutoff in addition we pointed out the constraint conditions for the distribution form and discussed how the constraints affect the distribution function it is speculated that for bursts and heavy tails in human dynamics when the fitted power exponent is less than 1 0 it cannot be a pure power law distribution but with an exponential cutoff which may be ignored in the previous studies

multifractal geometry in stock market time series it has been recently noticed that time series of returns in stock markets are of multifractal multiscaling character in that context multifractality has been always evidenced by its statistical signature i e the scaling exponents associated to a related variable however a direct geometrical framework much more revealing about the underlying dynamics is possible in this paper we present the techniques allowing the multifractal decomposition we will show that there exists a particular fractal component the most singular manifold msm which contains the relevant information about the dynamics of the series it is possible to reconstruct the series at a given precision from the msm we analyze the dynamics of the msm which shows revealing features about the evolution of this type of series