models of social networks based on social distance attachment we propose a class of models of social network formation based on a mathematical abstraction of the concept of social distance social distance attachment is represented by the tendency of peers to establish acquaintances via a decreasing function of the relative distance in a representative social space we derive analytical results corroborated by extensive numerical simulations showing that the model reproduces the main statistical characteristics of real social networks large clustering coefficient positive degree correlations and the emergence of a hierarchy of communities the model is confronted with the social network formed by people that shares confidential information using the pretty good privacy pgp encryption algorithm the so called web of trust of pgp

a new fitness estimation strategy for particle swarm optimization particle swarm optimization pso is a global metaheuristic that has been proved to be very powerful for optimizing a wide range of problems however pso requires a large number of fitness evaluations to find acceptable optimal or sub optimal solutions if one single evaluation of the objective function is computationally expensive the computational cost for the whole optimization run will become prohibitive fespso a new fitness estimation strategy is proposed for particle swarm optimization to reduce the number of fitness evaluations thereby reducing the computational cost different from most existing approaches which either construct an approximate model using data or utilize the idea of fitness inheritance fespso estimates the fitness of a particle based on its positional relationship with other particles more precisely once the fitness of a particle is known either estimated or evaluated using the original objective function the fitness of its closest neighboring particle will be estimated by the proposed estimation formula if the fitness of its closest neighboring particle has not been evaluated using the original objective function the minimum of all estimated fitness values on this position will be adopted in case of more than one particle is located at the same position the fitness of only one of them needs to be evaluated or estimated the performance of the proposed algorithm is examined on eight benchmark problems and the experimental results show that the proposed algorithm is easy to implement effective and highly competitive

applications of the direct trefftz boundary element method to the free vibration problem of a membrane in this paper the direct trefftz method is applied to solve the free vibration problem of a membrane in the direct trefftz method there exists no spurious eigenvalue however an ill posed nature of numerical instability encountered in the direct trefftz method requires some treatments the tikhonov s regularization method and generalized singular value decomposition method are used to deal with such an ill posed problem numerical results show the validity of the current approach

applications of the generalized singular value decomposition method on the eigenproblem using the incomplete boundary element formulation in this paper four incomplete boundary element formulations including the real part singular boundary element the real part hypersingular boundary element the imaginary part boundary element and the plane wave element methods are used to solve the free vibration problem among these incomplete boundary element formulations the real part singular and the hypersingular boundary elements are of the singular type and the other two are of the regular type when the incomplete formulation is used the spurious eigensolution may be encountered an auxiliary system whose boundary conditions are linearly independent of those of the original system is required in the proposed method in order to eliminate the spurious eigensolution a mathematical proof is given to show that the spurious eigensolution will appear in both the original and auxiliary systems as a result one can eliminate spurious eigensolution by means of the generalized singular value decomposition method in addition to the spurious eigensolution problem the regular boundary element formulation further suffers ill conditioned behaviors in the problem solver it is explained analytically using a circular domain why ill conditioned behaviors exist two main ill conditioned problems are the numerical instability of solution and the nonexistence of solution to solve the numerical instability of solution problem existing in these proposed regular formulations the tikhonov s regularization technique is used to improve the condition number of the leading coefficient matrix further the generalized singular value decomposition method is used to eliminate spurious eigensolutions numerical examples are given to verify the performance of these proposed methods and the results match the analytical values well

finding community structure in networks using the eigenvectors of matrices we consider the problem of detecting communities or modules in networks groups of vertices with a higher than average density of edges connecting them previous work indicates that a robust approach to this problem is the maximization of the benefit function known as modularity over possible divisions of a network here we show that this maximization process can be written in terms of the eigenspectrum of a matrix we call the modularity matrix which plays a role in community detection similar to that played by the graph laplacian in graph partitioning calculations this result leads us to a number of possible algorithms for detecting community structure as well as several other results including a spectral measure of bipartite structure in networks and a centrality measure that identifies vertices that occupy central positions within the communities to which they belong the algorithms and measures proposed are illustrated with applications to a variety of real world complex networks

h control of linear singularly perturbed systems with small state delay an infinite horizon h state feedback control problem for singularly perturbed linear systems with a small state delay is considered an asymptotic solution of the hybrid system of riccati type algebraic ordinary differential and partial differential equations with deviating arguments associated with this problem is constructed based on this asymptotic solution conditions for the existence of a solution of the original h problem independent of the singular perturbation parameter are derived a simplified controller with parameter independent gain matrices solving the original problem for all sufficiently small values of this parameter is obtained an illustrative example is presented

normalized cuts and image segmentation we propose a novel approach for solving the perceptual grouping problem in vision rather than focusing on local features and their consistencies in the image data our approach aims at extracting the global impression of an image we treat image segmentation as a graph partitioning problem and propose a novel global criterion the normalized cut for segmenting the graph the normalized cut criterion measures both the total dissimilarity between the different groups as well as the total similarity within the groups we show that an efficient computational technique based on a generalized eigenvalue problem can be used to optimize this criterion we applied this approach to segmenting static images as well as motion sequences and found the results to be very encouraging

on the analysis of prismatic beams using first order warping functions abstract a one dimensional theory for isotropic homogeneous beams with a general cross section is developed that utilizes both deformations in the cross section plane and warping out of the cross section plane where these deformation functions are known from saint venant s elasticity solutions for bending and flexure of a prismatic beam first order warping functions in contrast to existing technical beam theories which assume that local cross section deformations and some stresses can be neglected the present theory makes no assumption the finite element model is developed using the resulting differential equations along with a partially weak form formulation full three dimensional constitutive equations are used solutions are found using the finite element method numerical results which are presented for a wide variety of loadings and boundary conditions show that the calculated stresses and displacements are in excellent agreement with existing elasticity solutions

levy walks in random scattering and growth of waves random spatial wave scattering and stochastic wave growth are studied where one or both of the random processes can be described by a levy walk this analysis extends previous work on randomly growing and scattering waves where both the random processes are modeled by gaussian diffusive statistics both random spatial scattering and stochastic wave growth modeled by levy walks are studied separately together and in combination with gaussian processes transmission coefficients lasing thresholds and energy densities in the medium are obtained for the different permutations

free vibration analysis of membranes using wave type base functions the free vibration analysis of general convex polygonal membranes is carried out the selected based functions for the analysis are wave type functions which propagate in one direction and vary sinusoidally in the other direction the key feature of the present technique is to use the base functions that satisfy the governing differential equation exactly so that only the boundary conditions need to be satisfied if base functions are not chosen carefully the dependence problem of the base functions may occur and a technique to select independent base functions is suggested

brief paper h control for fast sampling discrete time singularly perturbed systems this paper is concerned with the h control problem via state feedback for fast sampling discrete time singularly perturbed systems a new h controller design method is given in terms of solutions to linear matrix inequalities lmis which eliminates the regularity restrictions attached to the riccati based solution a method for evaluating the upper bound of singular perturbation parameter e with meeting a prescribed h performance bound requirement is also given furthermore the results are extended to robust controller design for fast sampling discrete time singularly perturbed systems with polytopic uncertainties numerical examples are given to illustrate the validity of the proposed methods

benchmark graphs for testing community detection algorithms community structure is one of the most important features of real networks and reveals the internal organization of the nodes many algorithms have been proposed but the crucial issue of testing i e the question of how good an algorithm is with respect to others is still open standard tests include the analysis of simple artificial graphs with a built in community structure that the algorithm has to recover however the special graphs adopted in actual tests have a structure that does not reflect the real properties of nodes and communities found in real networks here we introduce a class of benchmark graphs that account for the heterogeneity in the distributions of node degrees and of community sizes we use this benchmark to test two popular methods of community detection modularity optimization and potts model clustering the results show that the benchmark poses a much more severe test to algorithms than standard benchmarks revealing limits that may not be apparent at a first analysis

application of symmetric indirect trefftz method to free vibration problems in 2d a symmetric indirect trefftz method is developed to solve the free vibration problem of a 2d membrane it is proved that in this approach the spurious eigensolution exists and an auxiliary matrix is constructed to help extraction of the spurious solution using the generalized singular value decomposition in addition to the spurious eigensolution this regular formulation suffers from its ill posed nature i e the numerical instability in order to deal with the numerical instability the tikhonov s regularization method in conjunction with the generalized singular value decomposition is suggested the proposed approach has some merits when compared with other regular boundary element formulations reported so far namely the capacity of representing eigenmodes and the ability to deal with a multiply connected domain of genus 1 several numerical examples are demonstrated to show the validity of the current approach copyright 2003 john wiley sons ltd

topology optimization of beam cross sections abstract perhaps this paper reports the first successful applications of the topology optimization in the design of thin walled beam sections in particular topologically different thin walled beam cross sections can be obtained by the present approach which is very useful in identifying the direction and location of stiffeners in formulating the topology optimization problems a simple power law is used for the relation between the density of an element with a hole and the mechanical properties of the element the sensitivity of the torsional rigidity is obtained by developing a finite element model of a st venant torsion problem and the euler beam theory is used for the sensitivity analysis of the bending rigidities

hybrid harmony search particle swarm optimization with global dimension selection this study presents a hybrid harmony search particle swarm optimization with global dimension selection hhspso gds for improving the performance of particle swarm optimization pso in hhspso gds a new global velocity updating strategy is introduced to enhance the neighborhood region search of the current best solution and to get a better trade off between convergence rate and robustness additionally a dynamic non linear decreased inertia weight is utilized to balance the global exploration and local exploitation moreover the best worst improvisation mechanism of harmony search hs is implanted in the hhspso gds algorithm and a global dimension selection is employed in the improvisation process which can effectively accelerate convergence global best information sharing strategy is developed to link the two layer exploration frames pso and hs finally a comprehensive experimental study is conducted on a large number of benchmark functions the experimental results reveal that hhspso gds performs better in terms of the quality of solution convergence rate robustness and scalability compared to various state of the art psos and other meta heuristic search algorithms

a decentralized quantum inspired particle swarm optimization algorithm with cellular structured population this paper proposes a decentralized form of quantum inspired particle swarm optimization qpso with cellular structured population called cqpso for keeping the population diversity and balancing the global and local search the cqpso is further improved by re designing the local attractor in the sub population called cqpso lbest in order to accelerate the diffusion of the best solution and thus enhance the performance of cqpso the particles in cqpso and cqpso lbest are distributed in a two dimensional 2d grid and only allowed to interact with their neighbors according to the specified neighborhood which plays a role in exploiting the search space inside the neighborhood the overlapping particles work for delivering the information among the nearest neighborhoods acting as exploring the search space with diffusion of solutions during the evolutionary process theoretical studies are made to analyze the global convergence of cpso and cqpso lbest based on the theory of probabilistic metric space we systematically investigate the performance of cqpso lbest on 42 benchmark functions with different properties including unimodal multimodal separated shifted rotated noisy and mis scaled and compare with a set of pso variants with different topologies and swarm based evolutionary algorithms eas the experimental results demonstrate the better performance of cqpso lbest moreover two real world problems which are two dimensional 2d iir digital filter design and economic dispatch ed problem from power systems area are used to evaluate cqpso lbest and the experimental results verified the advantages of cqpso lbest

spectral and dynamical properties in classes of sparse networks with mesoscopic inhomogeneities we study structure eigenvalue spectra and random walk dynamics in a wide class of networks with subgraphs modules at mesoscopic scale the networks are grown within the model with three parameters controlling the number of modules their internal structure as scale free and correlated subgraphs and the topology of connecting network within the exhaustive spectral analysis for both the adjacency matrix and the normalized laplacian matrix we identify the spectral properties which characterize the mesoscopic structure of sparse cyclic graphs and trees the minimally connected nodes the clustering and the average connectivity affect the central part of the spectrum the number of distinct modules leads to an extra peak at the lower part of the laplacian spectrum in cyclic graphs such a peak does not occur in the case of topologically distinct tree subgraphs connected on a tree whereas the associated eigenvectors remain localized on the subgraphs both in trees and cyclic graphs we also find a characteristic pattern of periodic localization along the chains on the tree for the eigenvector components associated with the largest eigenvalue lambda l 2 of the laplacian further differences between the cyclic modular graphs and trees are found by the statistics of random walks return times and hitting patterns at nodes on these graphs the distribution of first return times averaged over all nodes exhibits a stretched exponential tail with the exponent sigma approximately 1 3 for trees and sigma approximately 2 3 for cyclic graphs which is independent of their mesoscopic and global structure

fourier series for polygonal plate bending a very large plate element abstract in this study we developed an edge function approach using the fourier series for boundary value problems on polygonal domains the method was then applied to classical plate bending problems in subsequent work this method has been extended to the moderate rotation equations for a shallow shell preliminary results indicate that the stability of a curved surface plays an important role in the morphogenesis of plants for a polygonal plate with a convex domain the levy type solutions for each edge serve as a set of fundamental functions the set is complete and each member satisfies the equation exactly the problem is solved by superimposing the solution functions and matching the fourier harmonics of the prescribed boundary conditions the process is much like the boundary element method bem except that the unknowns are the amplitudes of fourier harmonics rather than the weightings of individual point sources an extra harmonic is added so that corner boundary conditions can be treated more efficiently by this approach a convex polygon is one element nonconvex domains however are divided into convex subdomains with appropriate continuity conditions at the interfaces in this method similar to the boundary integral method no mesh generation is involved the number of elements and the degrees of freedom is significantly smaller than in the finite element or finite difference methods the advantage over boundary elements is that the matrices are generally well conditioned and the approach is readily extended to the shallow shells

an algorithm for solving the singularly perturbed h algebraic riccati equation abstract the algebraic riccati equation of singularly perturbed h linear quadratic optimal control problems is decoupled into two completely independent reduced order pure slow and pure fast h algebraic riccati equations even though the algebraic riccati equations obtained are nonsymmetric they are efficiently solved in terms of lyapunov iterations by using the newton method the presented algorithm can be used for h parallel filtering and regulation of systems displaying two time scale dynamics

acoustical cavity excitation a tutorial exposition is given of cavity excitations and it is shown that relatively simple analytical solutions for the excitation of acoustic fields in cavities with lossy walls can be obtained for a broad class of such cavities the standard analytic procedure whereby one expresses the acoustic field as a sum over the eigenmodes of the cavity is reviewed and its limitations are pointed out an alternate procedure is to seek to make use of green s functions depending on a single coordinate and to not express such green s functions as sums over eigenfunctions instead one expresses the green s function as a closed form function that has a discontinuous slope at the value of the coordinate corresponding to the source location although the class of cavities for which this approach is possible is limited it is sufficiently broad to be of intrinsic interest and the results may be helpful to those seeking benchmark solutions and analytic insight displayed examples are for cavities whose shapes are spheres and cylinders with interior monopole dipole line and distributed sources the formulation yields simple expressions for the total power absorbed by the cavity walls

a modified fourier series method for the torsion analysis of bars with multiply connected cross sections a modified fourier series method is proposed for the torsion analysis of prismatic bars with multiply connected cross sections the key feature in the present approach is the combined use of polynomials and fourier series solutions unlike in the existing approaches which use the fourier series only the replacement of the zeroth harmonic terms in the fourier series solutions by carefully selected polynomials resolves the major problem of functional dependence which the direct fourier series method may pose the polynomials and fourier series solutions are selected to satisfy the governing equation exactly so that the numerical calculation is minimal the effectiveness and generality of the present method is verified through numerical examples

an asymmetric indirect trefftz method for solving free vibration problems in this paper a new asymmetric indirect trefftz method aitm has been developed to solve free vibration problems the proposed method is categorized into a regular type of boundary element methods bems such that no singular or hypersingular integration is necessary however like other regular bems the proposed approach encounters the numerical instability as the number of elements increases to deal with such an ill posed behavior tikhonov s regularization method in conjunction with the generalized singular value decomposition gsvd is adopted it is proved that the degeneracy of the proposed indirect trefftz method has the same mathematical structure as the direct trefftz method thus no special effort should be paid in programming besides such an equivalency indicates that the current method does not have spurious eigensolutions furthermore the proposed approach can easily treat a multiply connected domain of genus 1 as shown in fig 1 due to its indirect nature the present approach can also represent the mode shapes within its own mathematical formulations several numerical examples are given to show the validity of the proposed approach

h optimal control for singularly perturbed systems part i perfect state measurements we study the h optimal control of singularly perturbed linear systems under perfect state measurements for both finite and infinite horizons using a differential game theoretic approach we show that as the singular perturbation parameter approaches zero the optimal disturbance attenuation level for the full order system under a quadratic performance index converges to a value that is bounded above by the maximum of the optimal disturbance attenuation levels for the slow and fast subsystems under appropriate slow and fast quadratic cost functions furthermore we construct a composite controller based on the solution of the slow and fast games which guarantees a desired achievable performance level for the full order plant as approaches zero a slow controller however is not generally robust in this sense but still under some conditions which are delineated in the paper the fast dynamics can be totally ignored the paper also studies optimality when the controller includes a feedforward term in the disturbance and presents some numerical examples to illustrate the theoretical results

finding community structure in very large networks the discovery and analysis of community structure in networks is a topic of considerable recent interest within the physics community but most methods proposed so far are unsuitable for very large networks because of their computational cost here we present a hierarchical agglomeration algorithm for detecting community structure which is faster than many competing algorithms its running time on a network with n vertices and m edges is o md phantom rule 0 2em 0ex mathrm log phantom rule 0 2em 0ex n where d is the depth of the dendrogram describing the community structure many real world networks are sparse and hierarchical with m ensuremath sim n and d ensuremath sim mathrm log phantom rule 0 2em 0ex n in which case our algorithm runs in essentially linear time o n phantom rule 0 2em 0ex mathrm log 2 phantom rule 0 2em 0ex n as an example of the application of this algorithm we use it to analyze a network of items for sale on the web site of a large on line retailer items in the network being linked if they are frequently purchased by the same buyer the network has more than 400 000 vertices and 2 ifmmode times else texttimes fi 10 6 edges we show that our algorithm can extract meaningful communities from this network revealing large scale patterns present in the purchasing habits of customers

approximate normalized cuts without eigen decomposition most traditional weighted graph clustering algorithms are solved by spectral method which is only suitable for small scale datasets because of the high space and time complexity how to reduce the computational complexity of graph cut clustering to process the massive complex data has become a challenging problem to overcome this problem we design an approximate normalized cuts algorithm without eigen decomposition for large scale clustering on the one hand the space requirement of normalized cut is decreased by sampling a few data points to infer the global features of dataset instead of using the whole affinity matrix on the other hand the graph cut clustering procedure is accelerated in an iterative way that using the approximate weighted kernel k means to optimize the objective function of normalized cut which avoids the direct eigen decomposition of laplacian matrix we also analyze the approximation error of the proposed algorithm and compare it with other state of the arts clustering algorithms on several benchmark datasets the experimental results demonstrate that our method can efficiently do the clustering when the number of data objects exceeds tens of thousands

an improved 1 1 evolutionary algorithm for k median clustering problem with performance guarantee abstract evolutionary algorithms eas have been widely studied in numerical experiments and successfully applied in practice however most existing eas are designed without a theoretical analysis for their performance guarantee in this paper we define a fitness function to guide the well known 1 1 evolutionary algorithm called 1 1 ea to optimize the np hard k median problem we prove that the 1 1 ea can obtain a performance guarantee of 5 for k median problem in polynomial expected runtime o m n 2 d m a x if all distances between data points and cluster centers are integers where m and n are respectively the cardinalities of the data set and cluster center set and d m a x denotes the largest distance between data points and cluster centers to tackle the general case that the distances between data points and cluster centers are real number we propose an improved 1 1 ea which employs a distance scaling scheme during the evolutionary process our rigorous theoretical analysis shows that the improved 1 1 ea obtains a performance guarantee of 5 e in expected runtime o e 1 m n 2 log m d m a x where e 0 is a constant this study reveals that an appropriate scaling scheme can help eas to obtain a constant performance guarantee in polynomial expected runtime and provides insights into design eas for some np hard problems in addition we conduct experiment to compare the efficiency of the improved 1 1 ea with three clustering algorithms on optimizing three uci datasets

infinite horizon differential games of singularly perturbed systems a unified approach nified approach which is valid for both standard and nonstandard singularly perturbed systems is presented to achieve the composite approximation of the full order linear feedback saddle point solution it is proved that such a composite approximation forms an o e near saddle point equilibrium of the full order game and the resulting value is email protected 2 over or below the exact value of the full order game depending on the given game parameter

greedy discrete particle swarm optimization for large scale social network clustering social computing is a new paradigm for information and communication technology social network analysis is one of the theoretical underpinnings of social computing community structure detection is believed to be an effective tool for social network analysis uncovering community structures in social networks can be regarded as clustering optimization problems because social networks are characterized by dynamics and huge volumes of data conventional nature inspired optimization algorithms encounter serious challenges when applied to solving large scale social network clustering optimization problems in this study we put forward a novel particle swarm optimization algorithm to reveal community structures in social networks the particle statuses are redefined under a discrete scenario the status updating rules are reconsidered based on the network topology a greedy strategy is designed to drive particles to a promising region to this end a greedy discrete particle swarm optimization framework for large scale social network clustering is suggested to determine the performance of the algorithm extensive experiments on both synthetic and real world social networks are carried out we also compare the proposed algorithm with several state of the art network community clustering methods the experimental results demonstrate that the proposed method is effective and promising for social network clustering

identification of overlapping community structure in complex networks using fuzzy c means clustering abstract identification of overlapping communities clusters in a complex network is a general problem in data mining of network data sets in this paper we devise a novel algorithm to identify overlapping communities in complex networks by the combination of a new modularity function based on generalizing ng s q function an approximation mapping of network nodes into euclidean space and fuzzy c means clustering experimental results indicate that the new algorithm is efficient at detecting both good clusterings and the appropriate number of clusters

linear quadratic zero sum differential games for generalized state space systems in this note we consider linear quadratic zero sum differential games for generalized state space systems it is well known that a unique linear feedback saddle point solution can exist in the game of state space systems however for the generalized state space system we show that the game admits uncountably many linear feedback saddle point solutions sufficient conditions for the existence of linear feedback saddlepoint solutions are found a constructive method is given to find these linear feedback saddle point solutions a simple example is included to illustrate the nonuniqueness of the linear feedback saddle point solutions

applications of waveguide type base functions for the eigenproblems of two dimensional cavities an acoustic modal analysis technique useful for two dimensional cavities of general shapes is developed as an extension of the technique developed earlier by kim and kang j acoust soc am 99 2938 2946 1996 for the modal analysis of convex membranes both neumann and dirichlet problems can be solved with the present choice of cosinusoidally varying waveguide type functions instead of sinusoidally varying waveguide type functions adopted earlier j acoust soc am 99 2938 2946 1996 a cavity subdivision technique for general nonconvex cavities overcomes the limitation of the earlier technique useful only for convex cavities successful applications of the present technique are demonstrated in some practical two dimensional cavity problems the present technique is potentially a very efficient technique in handling higher eigenmodes

fuzzy queries processing based on intuitionistic fuzzy social relational networks in this paper we propose fuzzy queries processing techniques based on the proposed intuitionistic fuzzy social relational network ifsrn model which contain positive relationships neutral relationships and negative relationships between actors where the degrees of relationship between actors are represented by intuitionistic fuzzy values ifvs the proposed fuzzy queries processing techniques based on the proposed ifsrn model are more flexible than the ones of yager s fuzzy social relational network fsrn model due to the fact that the system can get the degrees of truth and the degrees of false of fuzzy queries respectively whereas the fuzzy queries processing techniques based on yager s fuzzy social relational network fsrn model only can get the degrees of truth of fuzzy queries

large scale evolutionary optimization using cooperative coevolution evolutionary algorithms eas have been applied with success to many numerical and combinatorial optimization problems in recent years however they often lose their effectiveness and advantages when applied to large and complex problems e g those with high dimensions although cooperative coevolution has been proposed as a promising framework for tackling high dimensional optimization problems only limited studies were reported by decomposing a high dimensional problem into single variables dimensions such methods of decomposition often failed to solve nonseparable problems for which tight interactions exist among different decision variables in this paper we propose a new cooperative coevolution framework that is capable of optimizing large scale nonseparable problems a random grouping scheme and adaptive weighting are introduced in problem decomposition and coevolution instead of conventional evolutionary algorithms a novel differential evolution algorithm is adopted theoretical analysis is presented in this paper to show why and how the new framework can be effective for optimizing large nonseparable problems extensive computational studies are also carried out to evaluate the performance of newly proposed algorithm on a large number of benchmark functions with up to 1000 dimensions the results show clearly that our framework and algorithm are effective as well as efficient for large scale evolutionary optimisation problems we are unaware of any other evolutionary algorithms that can optimize 1000 dimension nonseparable problems as effectively and efficiently as we have done

influence maximization in social networks based on discrete particle swarm optimization influence maximization in social networks aims to find a small group of individuals which have maximal influence cascades in this study an optimization model based on a local influence criterion is established for the influence maximization problem the local influence criterion can provide a reliable estimation for the influence propagations in independent and weighted cascade models a discrete particle swarm optimization algorithm is then proposed to optimize the local influence criterion the representations and update rules for the particles are redefined in the proposed algorithm moreover a degree based heuristic initialization strategy and a network specific local search strategy are introduced to speed up the convergence experimental results on four real world social networks demonstrate the effectiveness and efficiency of the proposed algorithm for influence maximization

free vibration analysis of arbitrarily shaped plates with clamped edges using wave type functions the basic idea related to the non dimensional dynamic influence green s function defined in an infinite membrane has been applied to the free vibration analysis of arbitrarily shaped plates with clamped edges another non dimensional dynamic influence function newly defined in the paper exactly satisfies the governing homogeneous differential equations of plates and is regular in the entire domain the proposed method uses the boundary discretization scheme similar to that of the boundary element method but does not require any interpolation function between the nodes distributed along the boundary as a result the method has a significant advantage in its simplicity and accuracy although the method uses no interpolation function it gives very accurate eigenvalues and mode shapes compared with the exact solutions or fem results it should be also noted that particular attention is given to reduce the size of the system matrix whose determinant equation yields eigenvalues and to overcome the functional dependence problem of the non dimensional dynamic influence functions

discrete particle swarm optimization for high order graph matching high order graph matching aims at establishing correspondences between two sets of feature points using high order constraints it is usually formulated as an np hard problem of maximizing an objective function this paper introduces a discrete particle swarm optimization algorithm for resolving high order graph matching problems which incorporates several re defined operations a problem specific initialization method based on heuristic information and a problem specific local search procedure the proposed algorithm is evaluated on both synthetic and real world datasets its outstanding performance is validated in comparison with three state of the art approaches