a new method for adding a parameter to a family of distributions with application to the exponential and weibull families summary a new way of introducing a parameter to expand a family of distributions is introduced and applied to yield a new two parameter extension of the exponential distribution which may serve as a competitor to such commonly used two parameter families of life distributions as the weibull gamma and lognormal distributions in addition the general method is applied to yield a new three parameter weibull distribution families expanded using the method introduced here have the property that the minimum of a geometric number of independent random variables with common distribution in the family has a distribution again in the family bivariate versions are also considered

an 0 n 2 5 fault identification algorithm for diagnosable systems consider a system composed of n independent processors each of which tests a subset of the others it is assumed that at most tp of these processors are permanently faulty and that the outcome of a test is reliable if and only if the processor which performed the test is fault free such a system is said to be tp diagnosable if given any complete collection of test results the set of faulty processors can be uniquely identified in this paper it is shown that tp diagnosable systems due to their robust interconnection structure possess heretofore unknown graph theoretic properties relative to vertex cover sets and maximum matchings an 0 n2 5 algorithm is given which exploits these properties to identify the set of faulty processors in a tp diagnosable system the algorithm is shown to be correct complete not based on any conjecture and superior to any other known fault identification algorithm for the general class of tp diagnosable systems

on 3 extra connectivity and 3 extra edge connectivity of folded hypercubes given a graph mbi g and a non negative integer g the g extra connectivity resp g extra edge connectivity of mbi g is the minimum cardinality of a set of vertices resp edges in mbi g if it exists whose deletion disconnects mbi g and leaves each remaining component with more than g vertices this study shows that the 3 extra connectivity resp 3 extra edge connectivity of an mbi n dimensional folded hypercube is 4 n 5 for n geq 6 resp 4 n 4 for n geq 5 this study also provides an upper bound for the g extra connectivity on folded hypercubes for g geq 6

a semiparametric estimation procedure of dependence parameters in multivariate families of distributions summary this paper investigates the properties of a semiparametric method for estimating the dependence parameters in a family of multivariate distributions the proposed estimator obtained as a solution of a pseudo likelihood equation is shown to be consistent asymptotically normal and fully efficient at independence a natural estimator of its asymptotic variance is proved to be consistent comparisons are made with alternative semiparametric estimators in the special case of clayton s model for association in bivariate data

reliability analysis of data center networks based on precise and imprecise diagnosis strategies abstract fault tolerance and reliability are the crucial issues for data center networks dcns both the g extra conditional diagnosis g ecd precise strategy and the t k diagnosis imprecise strategy play essential role in the reliability of networks for the data center network based on dcell structure d m n we prove that 1 the g ecd of d m n under the mm model is g 1 m n 1 with n 4 m 3 and 1 g min n 4 m 2 2 d m n is k 1 m 1 n k diagnosable under the mm model with n 2 m 2 and 0 k n 1 furthermore for n server dcn we propose the first t k diagnosis algorithm on d m n under the mm model namely t k d m n diag with o n log n time complexity comparing with the traditional t diagnosable algorithm by ziwich and duarte 2016 11 on d m n the t k d m n diag can identify the number of faulty vertices is almost k times larger than the t diagnosable algorithm where the time complexity of t diagnosable algorithm is about o n log n 3 these results provide a quantitative analysis for the reliability and availability evaluation of a large scale dcn

road traffic noise shielding by vegetation belts of limited depth abstract road traffic noise propagation through a vegetation belt of limited depth 15 m containing periodically arranged trees along a road is numerically assessed by means of 3d finite difference time domain fdtd calculations the computational cost is reduced by only modeling a representative strip of the planting scheme and assuming periodic extension by applying mirror planes with increasing tree stem diameter and decreasing spacing traffic noise insertion loss is predicted to be more pronounced for each planting scheme considered simple cubic rectangular triangular and face centered cubic for rectangular schemes the spacing parallel to the road axis is predicted to be the determining parameter for the acoustic performance significant noise reduction is predicted to occur for a tree spacing of less than 3 m and a tree stem diameter of more than 0 11 m this positive effect comes on top of the increase in ground effect near 3 dba for a light vehicle at 70 km h when compared to sound propagation over grassland the noise reducing effect of the forest floor and the optimized tree belt arrangement are found to be of similar importance in the calculations performed the effect of shrubs with typical above ground biomass is estimated to be at maximum 2 dba in the uniform scattering approach applied for a light vehicle at 70 km h downward scattering from tree crowns is predicted to be smaller than 1 dba for a light vehicle at 70 km h for various distributions of scattering elements representing the tree crown the effect of the presence of tree stems shrubs and tree crowns is predicted to be approximately additive inducing some pseudo randomness in stem center location tree diameter and omitting a limited number of rows with trees seem to hardly affect the insertion loss these predictions suggest that practically achievable vegetation belts can compete to the noise reducing performance of a classical thin noise barrier on grassland with a height of 1 1 5 m in a non refracting atmosphere

on reliability of the folded hypercubes in this paper we explore the 2 extra connectivity and 2 extra edge connectivity of the folded hypercube fq n we show that k 2 fq n 3n 2 for n 8 and l 2 fq n 3n 1 for n 5 that is for n 8 resp n 5 at least 3n 2 vertices resp 3n 1 edges of fq n are removed to get a disconnected graph that contains no isolated vertices resp edges when the folded hypercube is used to model the topological structure of a large scale parallel processing system these results can provide more accurate measurements for reliability and fault tolerance of the system

hamiltonian connectivity and strongly hamiltonian laceability of folded hypercubes in this paper we analyze a hypercube like structure called the folded hypercube which is basically a standard hypercube with some extra links established between its nodes we first show that the n dimensional folded hypercube is bipartite when n is odd we also show that the n dimensional folded hypercube is strongly hamiltonian laceable when n is odd and is hamiltonian connected when n 1 or n 2 is even

vorticity and entropy boundary conditions for acoustical finite difference time domain simulations in this paper a time domain numerical model for describing the presence of vorticity and entropy boundary layers is introduced the boundary model can be inserted in acoustic time domain models such as the finite difference time domain fdtd model for studying the acoustic behavior of high quality resonator structures the main focus in deriving the model is on numerical efficiency boundary layer theory is reviewed to obtain a three dimensional formulation of its influence on fdtd equations that must be applied in boundary discretization cells the dependence that is encountered is approximated in time domain in such a way that no numerical convolution is required although this approximation is rather inaccurate it is sufficient for most applications and introduces almost no extra computational effort several numerical examples illustrate the applicability of the model

pancyclicity and bipancyclicity of conditional faulty folded hypercubes a graph is said to be pancyclic if it contains cycles of every length from its girth to its order inclusive and a bipartite graph is said to be bipancyclic if it contains cycles of every even length from its girth to its order the pancyclicity or the bipancyclicity of a given network is an important factor in determining whether the network s topology can simulate rings of various lengths an n dimensional folded hypercube fq n is an attractive variant of an n dimensional hypercube q n that is obtained by establishing some extra edges between the vertices of q n fq n for any odd n is known to be bipartite in this paper we explore the pancyclicity and bipancyclicity of fq n for any fq n n 2 with at most 2n 3 faulty edges where each vertex is incident to at least two fault free edges we prove that there exists a fault free cycle of every even length from 4 to 2 n and when n 2 is even we prove there also exists a fault free cycle of every odd length from n 1 to 2 n 1 the result is optimal with respect to the number of faulty edges tolerated

acoustical finite difference time domain simulations of subwavelength geometries accurate simulation of wave propagation around subwavelength geometries using standard finite difference time domain fdtd techniques require a fine spatial and temporal sampling resulting in high computational costs in this paper an extension to this standard fdtd technique is proposed by means of quasi stationary solutions on a subwavelength scale the fdtd equations in the region near the subwavelength geometry are extended with some correction terms of which the magnitude is extracted from the quasi stationary pressure distribution around these geometries these pressure distributions can be calculated from the laplace equation using this new technique fdtd simulations can be based on a more coarse grid thus reducing computational cost considerably the accuracy of this technique is mainly determined by the accuracy of the laplace solutions this technique was tested with success on the simulation of resonators it was also shown that the new fdtd equations can be extended to include viscosity ef

multivariate archimedean copulas d monotone functions and l1 norm symmetric distributions it is shown that a necessary and sufficient condition for an archimedean copula generator to generate a d dimensional copula is that the generator is a d monotone function the class of d dimensional archimedean copulas is shown to coincide with the class of survival copulas of d dimensional l 1 norm symmetric distributions that place no point mass at the origin the d monotone archimedean copula generators may be characterized using a little known integral transform of williamson duke math j 23 1956 189 207 in an analogous manner to the well known bernstein widder characterization of completely monotone generators in terms of the laplace transform these insights allow the construction of new archimedean copula families and provide a general solution to the problem of sampling multivariate archimedean copulas they also yield useful expressions for the d dimensional kendall function and kendall s rank correlation coefficients and facilitate the derivation of results on the existence of densities and the description of singular components for archimedean copulas the existence of a sharp lower bound for archimedean copulas with respect to the positive lower orthant dependence ordering is shown

the g good neighbor conditional diagnosability of hypercube under pmc model abstract processor fault diagnosis plays an important role in multiprocessor systems for reliable computing and the diagnosability of many well known networks has been explored for example hypercubes crossed cubes mobius cubes and twisted cubes of dimension n all have diagnosability n the conditional diagnosability of n dimensional hypercube q n is proved to be 4 n 2 1 under the pmc model in this paper we study the g good neighbor conditional diagnosability of q n under the pmc model and show that it is 2 g n g 2 g 1 for 0 g n 3 the g good neighbor conditional diagnosability of q n is several times larger than the classical diagnosability

time domain wave equations for lossy media obeying a frequency power law for attenuation described by a slowly varying power law function of frequency 0 y classical lossy time domain wave equations exist only for the restricted cases where y 0 or y 2 for the frequently occurring practical situation in which attenuation is much smaller than the wave number a lossy dispersion characteristic is derived that has the desired attenuation general power law dependence in order to obtain the corresponding time domain lossy wave equation time domain loss operators similar in function to existing derivative operators are developed through the use of generalized functions three forms of lossy wave equations are found depending on whether y is an even or odd integer or a noninteger a time domain expression of causality analogous in function to the kramers kronig relations in the frequency domain is used to derive the causal wave equations final causal versions of the time domain wave equations are obtained even for the cases where y 1 which according to the paley wiener th

generation of fdtd subcell equations by means of reduced order modeling adapted finite difference time domain fdtd update equations exist for a number of objects that are smaller than the grid step such as wires and thin slots we provide a technique that automatically generates new fdtd update equations for small objects our presentation focusses on 2d fdtd we start from the fdtd equations in a fine grid where the time derivative is not discretised this yields a large state space model that is drastically reduced with a reduced order modeling technique the reduced state space model is then translated into new fdtd update equations that can be used in an fdtd simulation in the same way as the existing update equations for wires and thin slots this technique is applied to a number of numerical problems showing the accuracy and versatility of the proposed method

a family of bivariate distributions generated by the bivariate bernoulli distribution abstract if x 1 x 2 is a sequence of independent bernoulli random variables the number of successes in the first n trials has a binomial distribution and the number of failures before the rth success has a negative binomial distribution from both the binomial and the negative binomial distributions the poisson distribution is obtainable as a limit moreover gamma distributions integer shape parameters are limits of negative binomial distributions and the normal distribution is a limit of negative binomial poisson and gamma distributions these basic facts from elementary probability have natural extensions to two dimensions because there is a unique natural bivariate bernoulli distribution in this article such extensions yielding a family of bivariate distributions are obtained and studied

families of multivariate distributions abstract for many years there has been an interest in families of bivariate distributions with marginals as parameters genest and mackay 1986a b showed that several such families that appear in the literature can be derived by a unified method a similar conclusion is obtained in this article through the use of mixture models these models might be regarded as multivariate proportional hazards models with random constants of proportionality the mixture models are useful for two purposes first they make some properties of the derived distributions more transparent the positive dependency property of association is sometimes exposed and a method for simulation of data from the distributions is suggested but the mixture models also allow derivation of several new families of bivariate distributions with marginals as parameters and they indicate obvious multivariate extensions some of the new families of bivariate distributions given in this article extend known distributions by adding a parameter

the diagnosability of the matching composition network under the comparison diagnosis model the classical problem of diagnosability is discussed widely and the diagnosability of many well known networks has been explored we consider the diagnosability of a family of networks called the matching composition network mcn a perfect matching connects two components the diagnosability of mcn under the comparison model is shown to be one larger than that of the component provided some connectivity constraints are satisfied applying our result the diagnosability of the hypercube qn the crossed cube cq sub n the twisted cube tq sub n and the mobius cube mq sub n can all proven to be n for n spl ges 4 in particular we show that the diagnosability of the four dimensional hypercube q sub 4 is 4 which is not previously known

modeling of the seat dip effect using the finite difference time domain method in this paper the use of the finite difference time domain technique for the modeling of the seat dip effect in concert halls is demonstrated the linear time domain acoustic partial differential equations are discretized using a finite difference technique the second order accurate differencing scheme is time space centered and the velocity and pressure are solved on an interlaced mesh first and second order mur absorbing boundary conditions originally formulated for electromagnetic problems are adapted to the acoustics case and used to truncate the numerical grid the technique is first verified by comparing the numerical results to the analytic solution of a simple point source results from computer simulations of the seat dip phenomena are compared with the findings of previous studies where measurements had been made on scale models and in real concert halls the computer model successfully predicts the effects associated with the source receiver distance the height of the receiver and the h

stochastic comparisons of series and parallel systems with dependent heterogeneous extended exponential components under archimedean copula abstract in this paper we discuss the usual stochastic star and convex transform orders of both series and parallel systems comprising heterogeneous and dependent extended exponential components under archimedean copula sufficient conditions are established for the star ordering between the lifetimes of series and parallel systems consisting of such dependent components under certain conditions on the archimedean copula and the parameters we also discuss convex transform order between the series and parallel systems these results generalize some existing results in the literature to the case of dependent components as well as to a general family of component lifetime distributions

on g extra conditional diagnosability of hierarchical cubic networks abstract connectivity and diagnosability are important parameters in measuring the fault tolerance and reliability of interconnection networks given a graph g and a non negative integer g the g extra connectivity of g denoted by g g is the minimum cardinality of a set of vertices of g if it exists whose deletion disconnects g and every remaining component has more than g vertices the g extra conditional diagnosability t g g of a graph g is the maximum value of t such that g is g extra conditional t diagnosable the n dimensional hierarchical cubic network h c n n was proposed by ghose and desai 12 as a hypercube based topology while preserving its attractive features for n 5 we first determine g h c n n for 0 g n 1 then establish t g h c n n under the pmc model for 0 g n 1 and t g h c n n under the mm model for 0 g n 1 3 respectively

on g extra conditional diagnosability of hypercubes and folded hypercubes abstract diagnosability of a multiprocessor system is one important study topic which plays an important role in measuring of the reliability of multiprocessor systems in the work of zhang et al in 2016 they proposed a new measure for fault diagnosis of systems namely g extra conditional diagnosability it is defined as the diagnosability of a multiprocessor system under the assumption that every fault free component contains more than g vertices which can measure the reliability of interconnection networks in heterogeneous environments more accurately than traditional diagnosability as two kind of favorable topology structures of interconnection networks the n dimensional hypercubes q n and folded hypercubes f q n have many good properties in this paper we investigate their g extra conditional diagnosability and show that a the g extra conditional diagnosability of q n is g 1 n g c g 2 for n 5 and 1 g n 1 4 under the mm model b the g extra conditional diagnosability of f q n is g 1 n c g 2 1 for n 9 and 1 g n 4 under the mm model

a new extension of weibull distribution properties and different methods of estimation abstract the weibull distribution has been generalized by many authors in recent years here we introduce a new generalization of the weibull distribution called alpha logarithmic transformed weibull distribution that provides better fits than some of its known generalizations the proposed distribution contains weibull exponential logarithmic transformed exponential and logarithmic transformed weibull distributions as special cases our main focus is the estimation from frequentist point of view of the unknown parameters along with some mathematical properties of the new model the proposed distribution accommodates monotonically increasing decreasing bathtub and unimodal and then bathtub shape hazard rates so it turns out to be quite flexible for analyzing non negative real life data we briefly describe different frequentist approaches namely maximum likelihood estimators percentile based estimators least squares estimators weighted least squares estimators maximum product of spacings estimators and compare them using extensive numerical simulations monte carlo simulations are performed to compare the performances of the proposed methods of estimation for both small and large samples the potentiality of the distribution is analyzed by means of two real data sets

on g extra connectivity of folded hypercubes let g be a connected graph and g a non negative integer the g extra connectivity of g is the minimum cardinality of a set of vertices in g if it exists whose deletion disconnects g and leaves each remaining component with more than g vertices in several recent publications the g extra connectivity of an n dimensional folded hypercube was determined for g 3 and some specific n see for example chang tsai and hsieh 2014 4 in this paper an extension of the above results to all 0 g n 1 and n 7 is presented

fault tolerant path embedding in folded hypercubes with both node and edge faults the folded hypercube fq n is a well known variation of the hypercube structure fq n is superior to q n in many measurements such as diameter fault diameter connectivity and so on let email protected fq n resp email protected fq n denote the set of faulty nodes resp faulty edges in fq n in the case that all nodes in fq n are fault free it has been shown that fq n contains a fault free path of length 2 n 1 resp 2 n 2 between any two nodes of odd resp even distance if email protected fq n n 1 where n 1 is odd and fq n contains a fault free path of length 2 n 1 between any two nodes if email protected fq n n 2 where n 2 is even in this paper we extend the above result to obtain two further properties which consider both node and edge faults as follows 1 fq n contains a fault free path of length at least 2 n 2 email protected fq n 1 resp 2 n 2 email protected fq n 2 between any two fault free nodes of odd resp even distance if email protected fq n email protected fq n n 1 where n 1 is odd 2 fq n contains a fault free path of length at least 2 n 2 email protected fq n 1 between any two fault free nodes if email protected fq n email protected fq n n 2 where n 2 is even

numerical model for moderately nonlinear sound propagation in three dimensional structures a three dimensional numerical model is presented that is capable of handling moderately nonlinear sound propagation the model is based on a finite difference time domain fdtd discretization of a set of equations that approximate the navier stokes equations and that include molecular relaxation processes the mathematical model and numerical discretization focus on compatibility with earlier linear fdtd models in this way combining both models in a single simulation is trivial and optimum efficiency is obtained for acoustic propagation a staggered grid is used for the discretization nonlinear effects heat conduction and damping are treated to a lower order of accuracy two examples illustrate the use of the model the first example is the nonlinear resonance of a finite length duct typical waveform steepening and frequency shift broadening and skewing of the resonance peak that are also observed in experiments are found the second example is a tuned reactive muffler installed on a duct the dec