nonequilibrium processes driven lattice gases interface dynamics and quenched disorder effects on density profiles and currents properties of the one dimensional totally asymmetric simple exclusion process tasep and their connection with the dynamical scaling of moving interfaces described by a kardar parisi zhang equation are investigated with periodic boundary conditions scaling of interface widths the latter defined via a discrete occupation number to height mapping gives the exponents alpha 0 500 5 z 1 52 3 beta 0 33 1 with open boundaries results are as follows i in the maximal current phase the exponents are the same as for the periodic case and in agreement with recent bethe ansatz results ii in the low density phase curve collapse can be found to a rather good extent with alpha 0 497 3 z 1 20 5 beta 0 41 2 which is apparently at variance with the bethe ansatz prediction z 0 iii on the coexistence line between low and high density phases alpha 0 99 1 z 2 10 5 beta 0 47 2 in relatively good agreement with the bethe ansatz prediction z 2 from a mean field continuum formulation a characteristic relaxation time related to kinematic wave propagation and having an effective exponent z 1 is shown to be the limiting slow process for the low density phase which accounts for the above mentioned discrepancy with bethe ansatz results for tasep with quenched bond disorder interface width scaling gives alpha 1 05 5 z 1 7 1 beta 0 62 7 from a direct analytic approach to steady state properties of tasep with quenched disorder closed form expressions for the piecewise shape of averaged density profiles are given as well as rather restrictive bounds on currents all these are substantiated in numerical simulations

the crossover phenomena in surface growth models with height dependent noise abstract in this paper we consider several known growth processes with height dependent noise this type of noise is interesting from a theoretical standpoint for example it paves the way to the derivation of the exact height distribution of the kpz equation through the hopf cole transformation in addition it may have implications for experimental growth processes using numerical methods we observe that adding such a noise to different growth processes can change their universality class or ruin the scaling laws in the case of mullins herring equation a two fold cross over is observed

the dynamic stiffness matrix of two dimensional elements application to kirchhoff s plate continuous elements this paper describes a procedure for building the dynamic stiffness matrix of two dimensional elements with free edge boundary conditions the dynamic stiffness matrix is the basis of the continuous element method then the formulation is used to build a kirchhoff rectangular plate element gorman s method of boundary condition decomposition and levy s series are used to obtain the strong solution of the elementary problem a symbolic computation software partially performs the construction of the dynamic stiffness matrix from this solution the performances of the element are evaluated from comparisons with harmonic responses of plates obtained by the finite element method

interface depinning in a disordered medium numerical results abstract we propose a lattice model to study the dynamics of a driven interface in a medium with random pinning forces the critical exponents characterizing the depinning transition are determined numerically in 1 1 and 2 1 dimensions our findings are compared with recent numerical and analytical results for a langevin equation with quenched noise which is expected to be in the same universality class

relaxation properties of 1 1 dimensional driven interfaces in disordered media we use the kardar parisi zhang equation with quenched noise in order to study the relaxation properties of driven interfaces in disordered media for 0 this equation belongs to the directed percolation depinning universality class and for 0 it belongs to the quenched edwards wilkinson universality class we study the fourier transform of the two time autocorrelation function of the interface height ck t t these functions depend on the difference of times t t in the steady state regime we find a two step relaxation decay in this regime for both universality classes the long time tail can be fitted by a stretched exponential function where the exponent depends on the universality class the relaxation time and the wavelength of the fourier transform where the two step relaxation is lost are related to the length of the pinned regions the stretched exponential relaxation is caused by the existence of pinned regions which is a direct consequence of the quenched noise

oslo model hyperuniformity and the quenched edwards wilkinson model we present simulations of the one dimensional oslo rice pile model in which the critical height at each site is randomly reset after each toppling we use the fact that the stationary state of this sand pile model is hyperuniform to reach system of sizes 10 7 most previous simulations were seriously flawed by important finite size corrections we find that all critical exponents have values consistent with simple rationals 4 3 for the correlation length exponent d 9 4 for the fractal dimension of avalanche clusters and z 10 7 for the dynamical exponent in addition we relate the hyperuniformity exponent to the correlation length exponent finally we discuss the relationship with the quenched edwards wilkinson model where we find in particular that the local roughness exponent is loc 1

kinetic roughening global quantities and fluctuation dissipation relations abstract growth processes and interface fluctuations can be studied through the properties of global quantities we here discuss a global quantity that not only captures better the roughness of an interface than the widely studied surface width but that is also directly conjugate to an experimentally accessible parameter thereby allowing us to study in a consistent way the global response of the system to a global change of external conditions exploiting the full analyticity of the linear edwards wilkinson and mullins herring equations we study in detail various two time functions related to that quantity this quantity fulfills the fluctuation dissipation theorem when considering steady state equilibrium fluctuations

on the automaton representation of the edwards wilkinson model with quenched disorder we reinvestigate the automaton version of an edwards wilkinson type model with quenched disorder introduced recently by leschhorn leschhorn physica a 195 1993 324 in interface dimensions d 1 2 3 at the depinning transition our numerical results suggest that the dynamic exponent z has a d independent value z 32 while the roughness exponent has the value 4 d 3

svdd based pattern denoising the support vector data description svdd is one of the best known one class support vector learning methods in which one tries the strategy of using balls defined on the feature space in order to distinguish a set of normal data from all other possible abnormal objects the major concern of this letter is to extend the main idea of svdd to pattern denoising combining the geodesic projection to the spherical decision boundary resulting from the svdd together with solving the preimage problem we propose a new method for pattern denoising we first solve svdd for the training data and then for each noisy test pattern obtain its denoised feature by moving its feature vector along the geodesic on the manifold to the nearest decision boundary of the svdd ball finally we find the location of the denoised pattern by obtaining the pre image of the denoised feature the applicability of the proposed method is illustrated by a number of toy and real world data sets

dynamic stiffness matrix development and free vibration analysis of a moving beam abstract the dynamic stiffness matrix of a moving bernoulli euler beam is developed and used to investigate its free flexural vibration characteristics in order to develop the dynamic stiffness matrix it is necessary to derive and solve the governing differential equation of motion of the moving beam in closed analytical form the solution is then used to obtain the general expressions for both responses and loads boundary conditions are applied to determine the constants in the general solution leading to the formation of the frequency dependent dynamic stiffness matrix of the moving beam relating the amplitudes of the harmonically varying loads to those of the corresponding responses the application of the resulting dynamic stiffness matrix using the wittrick williams algorithm is demonstrated by some illustrative examples numerical results for both simply supported and fixed fixed end conditions of the beam are discussed and wherever possible some are compared with those available in the literature

support vector clustering we present a novel clustering method using the approach of support vector machines data points are mapped by means of a gaussian kernel to a high dimensional feature space where we search for the minimal enclosing sphere this sphere when mapped back to data space can separate into several components each enclosing a separate cluster of points we present a simple algorithm for identifying these clusters the width of the gaussian kernel controls the scale at which the data is probed while the soft margin constant helps coping with outliers and overlapping clusters the structure of a dataset is explored by varying the two parameters maintaining a minimal number of support vectors to assure smooth cluster boundaries we demonstrate the performance of our algorithm on several datasets

dynamic behaviour of structures in large frequency range by continuous element methods abstract the continuous element method is presented in the context of the harmonic response of beam assemblies a general formulation is described from the displacement solution of the elementary problem a direct computation of elementary dynamic stiffness matrices is presented in the present formulation distributed loadings are taken into account in the case of more complex geometries for which many coupling phenomena occur an explicit formulation is no more conceivable in this case a numerical approach is presented this approach allows an algorithmic computation of exact dynamic stiffness matrices this method called numerical continuous element allows one to consider the coupled vibrations of curved beams and those of helical beams the validation of this numerical method is achieved by comparisons with the harmonic response of various beams obtained by a finite element approach finally a comparison between eigenfrequencies obtained experimentally and numerically for a straight beam and a helical beam has been made to evaluate the performances of the method

interface growth with competing surface currents the authors examine the dynamics of interface growth under the combined influence of a stabilizing and a destabilizing surface current in 1 1 dimensions it has been shown that the surface is weakly stabilized if a newly deposited particle can move locally to maximize the total number of nearest neighbour contacts with the surface curvature driven current the introduction of a weak destabilizing surface tension term results in an almost periodic grooved surface the width of the surface grows linearly in time and does not reach a steady state it appears that such a formation cannot be described by a continuous langevin equation

free vibration of rotating tapered beams using the dynamic stiffness method abstract the free bending vibration of rotating tapered beams is investigated by using the dynamic stiffness method the range of problems considered includes beams for which the depth and or width of the cross section vary linearly along the length first the governing differential equation of motion of the rotating tapered beam in free flap bending vibration is derived for the most general case using hamilton s principle allowing for the effects of centrifugal stiffening an arbitrary outboard force and the hub radius term for harmonic oscillation the differential equation is solved for bending displacement by applying the frobenius method of series solution the expressions for bending rotation shear force and bending moment at any cross section of the beam are also obtained in explicit analytical form then the dynamic stiffness matrix is developed by relating the amplitudes of forces and moments to those of the displacements and rotations at the ends of the harmonically vibrating tapered beam next the wittrick williams algorithm is used as a solution technique to the resulting dynamic stiffness matrix to compute the natural frequencies and mode shapes of some illustrative examples a parametric study is carried out to demonstrate the effects of rotational speed taper ratio and hub radius on the results which are discussed and compared with the published ones finally some conclusions are drawn

boundary element analysis of anisotropic kirchhoff plates in this paper the radial integration method is used to obtain a boundary element formulation without any domain integral for general anisotropic plate bending problems two integral equations are used and the unknown variables are assumed to be constant along each boundary element the domain integral which arises from a transversely applied load is exactly transformed into a boundary integral by a radial integration technique uniformly and linearly distributed loads are considered several computational examples concerning orthotropic and general anisotropic plate bending problems are presented the results show good agreement with analytical and finite element results available in the literature

renormalization of stochastic lattice models basic formulation we describe a general method for the multiscale analysis of stochastic lattice models beginning with a lattice langevin formulation of site fluctuations we derive stochastic partial differential equations by regularizing the transition rules of the model subsequent coarse graining is accomplished by calculating renormalization group rg trajectories from initial conditions determined by the regularized atomistic models the rg trajectories correspond to hierarchies of continuum equations describing lattice models over expanding length and time scales these continuum equations retain a quantitative connection over different scales as well as to the underlying atomistic dynamics this provides a systematic method for the derivation of continuum equations from the transition rules of lattice models for any length and time scales as an illustration we consider the one dimensional 1d wolf villain wv model europhys lett 13 389 1990 the rg analysis of this model which we develop in detail is generic and can be applied to a wide range of conservative lattice models the rg trajectory of the 1d wv model shows a complex crossover sequence of linear and nonlinear stochastic differential equations which is in excellent agreement with kinetic monte carlo simulations of this model we conclude by discussing possible applications of the multiscale method described here to other nonequilibrium systems

dynamic stiffness formulation for free orthotropic plates this paper presents a procedure for developing the dynamic stiffness matrix of a free orthotropic kirchhoff plate the dynamic stiffness matrix is computed for free edge boundary conditions of the plate that allow assembly procedures the method is based on a strong formulation of kirchhoff plate equations and series solutions taking advantage of the symmetry and gorman type decomposition of the free boundary conditions the performances of the so called dynamic stiffness method dsm are evaluated by comparing the harmonic responses of an orthotropic kirchhoff plate with those obtained from the finite element method using four noded quadrilateral elements

the pre image problem in kernel methods in this paper we address the problem of finding the pre image of a feature vector in the feature space induced by a kernel this is of central importance in some kernel applications such as on using kernel principal component analysis pca for image denoising unlike the traditional method in which relies on nonlinear optimization our proposed method directly finds the location of the pre image based on distance constraints in the feature space it is noniterative involves only linear algebra and does not suffer from numerical instability or local minimum problems evaluations on performing kernel pca and kernel clustering on the usps data set show much improved performance

dynamic pattern denoising method using multi basin system with kernels in this paper we propose a novel pattern denoising method that utilizes the topological property of a support that describes the distribution of normal patterns to denoise noisy patterns the method first trains a support function which captures the domain of normal patterns and then construct a so called multi basin system associated with the trained support function by moving noisy patterns along the trajectories of the multi basin system noise is removed while the pattern recovers its normality the denoised pattern is obtained when the noisy pattern arrives at the attracting manifold generated by a set of normal patterns and this is the most similar normal pattern with the noisy pattern in the topological sense through simulations on some toy dataset and real image datasets we show that the proposed framework effectively removes the noise while preserving the information contained in the noisy pattern

adapting to unknown smoothness via wavelet shrinkage abstract we attempt to recover a function of unknown smoothness from noisy sampled data we introduce a procedure sureshrink that suppresses noise by thresholding the empirical wavelet coefficients the thresholding is adaptive a threshold level is assigned to each dyadic resolution level by the principle of minimizing the stein unbiased estimate of risk sure for threshold estimates the computational effort of the overall procedure is order n log n as a function of the sample size n sureshrink is smoothness adaptive if the unknown function contains jumps then the reconstruction essentially does also if the unknown function has a smooth piece then the reconstruction is essentially as smooth as the mother wavelet will allow the procedure is in a sense optimally smoothness adaptive it is near minimax simultaneously over a whole interval of the besov scale the size of this interval depends on the choice of mother wavelet we know from a previous paper by the authors that traditional smoot

cusps self organization and absorbing states elastic interfaces embedded in quenched random media exhibit metastability and stick slip dynamics these nontrivial dynamical features have been shown to be associated with cusp singularities of the coarse grained disorder correlator here we show that annealed systems with many absorbing states and a conservation law but no quenched disorder exhibit identical cusps on the other hand similar nonconserved systems in the directed percolation class are also shown to exhibit cusps but of a different type these results are obtained both by a recent method to explicitly measure disorder correlators and by defining an alternative new protocol inspired by self organized criticality which opens the door to easily accessible experimental realizations

generalized survival in equilibrium step fluctuations we investigate the dynamics of a generalized survival probability s t r defined with respect to an arbitrary reference level r rather than the average in equilibrium step fluctuations the exponential decay at large time scales of the generalized survival probability is numerically analyzed s t r is shown to exhibit simple scaling behavior as a function of system size l sampling time ensuremath delta t and the reference level r the generalized survival time scale ensuremath tau s r associated with s t r is shown to decay exponentially as a function of r

the surface statistics of a granular aggregate the problem of the surface fluctuations in a settled granular material is posed a simple model is given which describes the process by which a particle settles and comes to rest on the existing surface of the packing and from this a set of langevin equations for the fourier modes of the surface are derived these equations imply that the fourier amplitudes behave like the velocities of a set of independent brownian particles we show that this results in logarithmically divergent surface fluctuations if the flux of particles onto the surface is random the divergence being removed by a more accurate description of the settling material for example by having the granules fall through a sieve

extreme fluctuations in stochastic network coordination with time delays we study the effects of uniform time delays on the extreme fluctuations in stochastic synchronization and coordination problems with linear couplings in complex networks we obtain the average size of the fluctuations at the nodes from the behavior of the underlying modes of the network we then obtain the scaling behavior of the extreme fluctuations with system size as well as the distribution of the extremes on complex networks and compare them to those on regular one dimensional lattices for large complex networks when the delay is not too close to the critical one fluctuations at the nodes effectively decouple and the limit distributions converge to the fisher tippett gumbel density in contrast fluctuations in low dimensional spatial graphs are strongly correlated and the limit distribution of the extremes is the airy density finally we also explore the effects of nonlinear couplings on the stability and on the extremes of the synchronization landscapes

dimensional crossover and universal roughness distributions in barkhausen noise we investigate the dimensional crossover of scaling properties of avalanches domain wall jumps in a single interface model used for the description of barkhausen noise in disordered magnets by varying the transverse aspect ratio a l y l x of simulated samples the system dimensionality changes from two to three we find that perturbing away from d 2 is a relevant field the exponent tau characterizing the power law scaling of avalanche distributions varies between 1 06 1 for d 2 and 1 275 15 for d 3 according to a crossover function f x x identical with l 1x phi a with phi 0 95 3 we discuss the possible relevance of our results to the interpretation of thin film measurements of barkhausen noise we also study the probability distributions of interface roughness sampled among successive equilibrium configurations in the barkhausen noise regime attempts to fit our data to the class of universality distributions associated to 1 f alpha noise give alpha approximately 1 1 1 for d 2 and 3 provided that suitable boundary conditions are used in the latter case

fast support vector data descriptions for novelty detection support vector data description svdd has become a very attractive kernel method due to its good results in many novelty detection problems however the decision function of svdd is expressed in terms of the kernel expansion which results in a run time complexity linear in the number of support vectors for applications where fast real time response is needed how to speed up the decision function is crucial this paper aims at dealing with the issue of reducing the testing time complexity of svdd a method called fast svdd f svdd is proposed unlike the traditional methods which all try to compress a kernel expansion into one with fewer terms the proposed f svdd directly finds the preimage of a feature vector and then uses a simple relationship between this feature vector and the svdd sphere center to re express the center with a single vector the decision function of f svdd contains only one kernel term and thus the decision boundary of f svdd is only spherical in the original space hence the run time complexity of the f svdd decision function is no longer linear in the support vectors but is a constant no matter how large the training set size is in this paper we also propose a novel direct preimage finding method which is noniterative and involves no free parameters the unique preimage can be obtained in real time by the proposed direct method without taking trial and error for demonstration several real world data sets and a large scale data set the extended mit face data set are used in experiments in addition a practical industry example regarding liquid crystal display micro defect inspection is also used to compare the applicability of svdd and our proposed f svdd when faced with mass data input the results are very encouraging

wavelet transforms in a critical interface model for barkhausen noise we discuss the application of wavelet transforms to a critical interface model which is known to provide a good description of barkhausen noise in soft ferromagnets the two dimensional version of the model one dimensional interface is considered mainly in the adiabatic limit of very slow driving on length scales shorter than a crossover length which grows with the strength of the surface tension the effective interface roughness exponent zeta is approximately 1 20 close to the expected value for the universality class of the quenched edwards wilkinson model we find that the waiting times between avalanches are fully uncorrelated as the wavelet transform of their autocorrelations scales as white noise similarly detrended size size correlations give a white noise wavelet transform consideration of finite driving rates still deep within the intermittent regime shows the wavelet transform of correlations scaling as 1 f 1 5 for intermediate frequencies this behavior is ascribed to intra avalanche correlations

an introduction to kernel based learning algorithms this paper provides an introduction to support vector machines kernel fisher discriminant analysis and kernel principal component analysis as examples for successful kernel based learning methods we first give a short background about vapnik chervonenkis theory and kernel feature spaces and then proceed to kernel based learning in supervised and unsupervised scenarios including practical and algorithmic considerations we illustrate the usefulness of kernel algorithms by discussing applications such as optical character recognition and dna analysis

estimating the support of a high dimensional distribution suppose you are given some data set drawn from an underlying probability distribution p and you want to estimate a simple subset s of input space such that the probability that a test point drawn from p lies outside of s equals some a priori specified value between 0 and 1 we propose a method to approach this problem by trying to estimate a function f that is positive on s and negative on the complement the functional form of f is given by a kernel expansion in terms of a potentially small subset of the training data it is regularized by controlling the length of the weight vector in an associated feature space the expansion coefficients are found by solving a quadratic programming problem which we do by carrying out sequential optimization over pairs of input patterns we also provide a theoretical analysis of the statistical performance of our algorithm the algorithm is a natural extension of the support vector algorithm to the case of unlabeled data

roughening of the interfaces in 1 1 dimensional two component surface growth with an admixture of random deposition we simulate competitive two component growth on a one dimensional substrate of l sites one component is a poisson type deposition that generates kardar parisi zhang kpz correlations the other is random deposition rd we derive the universal scaling function of the interface width for this model and show that the rd admixture acts as a dilatation mechanism to the fundamental time and height scales but leaves the kpz correlations intact this observation is generalized to other growth models it is shown that the flat substrate initial condition is responsible for the existence of an early nonscaling phase in the interface evolution the length of this initial phase is a nonuniversal parameter but its presence is universal we introduce a method to measure the length of this initial nonscaling phase in application to parallel and distributed computations the important consequence of the derived scaling is the existence of the upper bound for the desynchronization in a conservative update algorithm for parallel discrete event simulations it is shown that such algorithms are generally scalable in a ring communication topology

exact vibration solutions for cross ply laminated plates with two opposite edges simply supported using refined theories of variable order abstract this paper presents exact solutions for free vibration of rectangular cross ply laminated plates with at least one pair of opposite edges simply supported using refined kinematic theories of variable order exact natural frequencies are obtained using an efficient and unified formulation where the solving set of second order differential equations of motion and related boundary conditions are expressed at layer level in terms of so called fundamental nuclei having invariant properties with respect to the order of the plate theory the nuclei are then appropriately expanded according to the number of layers and the order of the theory and the resulting equations are transformed into a first order model whose solution is obtained by using the state space concept in this way the mathematical effort needed to derive analytical solutions is highly reduced both higher order equivalent single layer and layer wise theories are considered in this study comparisons with other exact solutions are presented and useful benchmark frequency results for symmetric and un symmetric cross ply laminates are provided

surface growth on percolation networks by a conserved noise restricted solid on solid growth model surface growth by the conserved noise restricted solid on solid model is investigated on diluted lattices i e on percolation networks that are embedded in two spatial dimensions the growth exponent and the roughness exponent are defined respectively by the mean square surface width via w 2 t t 2 and the mean square saturated width via w sat 2 l l 2 where l is the system size these are measured on both an infinite network and a backbone network and the results are compared with power counting predictions obtained using the fractional langevin equation while the monte carlo results on deterministic fractal substrates show excellent agreement with the predictions d h kim and j m kim phys rev e 84 011105 2011 the results on critical percolation networks deviate by 8 12 from these predictions

penalized preimage learning in kernel principal component analysis finding the preimage of a feature vector in kernel principal component analysis kpca is of crucial importance when kpca is applied in some applications such as image preprocessing since the exact preimage of a feature vector in the kernel feature space normally does not exist in the input data space an approximate preimage is learned and encouraging results have been reported in the last few years however it is still difficult to find a good estimation of preimage as estimation of preimage in kernel methods is ill posed how to guide the preimage learning for a better estimation is important and still an open problem to address this problem a penalized strategy is developed in this paper where some penalization terms are used to guide the preimage learning process to develop an efficient penalized technique we first propose a two step general framework in which a preimage is directly modeled by weighted combination of the observed samples and the weights are learned by some optimization function subject to certain constraints compared to existing techniques this would also give advantages in directly turning preimage learning into the optimization of the combination weights under this framework a penalized methodology is developed by integrating two types of penalizations first to ensure learning a well defined preimage of which each entry is not out of data range convexity constraint is imposed for learning the combination weights more insight effects of the convexity constraint are also explored second a penalized function is integrated as part of the optimization function to guide the preimage learning process particularly the weakly supervised penalty is proposed discussed and extensively evaluated along with laplacian penalty and ridge penalty it could be further interpreted that the learned preimage can preserve some kind of pointwise conditional mutual information finally kpca with preimage learning is applied on face image data sets in the aspects of facial expression normalization face image denoising recovery of missing parts from occlusion and illumination normalization experimental results show that the proposed preimage learning algorithm obtains lower mean square error mse and better visual quality of reconstructed images

input space versus feature space in kernel based methods this paper collects some ideas targeted at advancing our understanding of the feature spaces associated with support vector sv kernel functions we first discuss the geometry of feature space in particular we review what is known about the shape of the image of input space under the feature space map and how this influences the capacity of sv methods following this we describe how the metric governing the intrinsic geometry of the mapped surface can be computed in terms of the kernel using the example of the class of inhomogeneous polynomial kernels which are often used in sv pattern recognition we then discuss the connection between feature space and input space by dealing with the question of how one can given some vector in feature space find a preimage exact or approximate in input space we describe algorithms to tackle this issue and show their utility in two applications of kernel methods first we use it to reduce the computational complexity of sv decision functions second we combine it with the kernel pca algorithm thereby constructing a nonlinear statistical denoising technique which is shown to perform well on real world data