construction of nonlinear resilient boolean functions using small affine functions in this correspondence we use affine functions on a small number of variables to construct resilient functions on a large number of variables we show that by properly combining these functions it is possible to achieve high nonlinearity and high algebraic degree an important contribution of the correspondence is to show that for each order of resiliency m it is possible to find infinitely many odd and even positive integers n such that it is possible to construct maximum degree n variable m resilient functions having nonlinearity strictly greater than 2 sup n 1 2 sup spl lfloor n 2 spl rfloor we also present construction of some important functions on a small number of variables

a relaxation model for numerical approximations of the multidimensional pressureless gas dynamics system abstract relaxation models for the pressureless gas dynamics pgd equations attempt to satisfy the strictly hyperbolic conservation law in order to employ the well posed approximated riemann solvers in this study a new type of relaxation model is proposed to resolve two shortcomings of the existing relaxation models the constant propagation speed of sound and the collapse of delta shock waves in multidimensional problems the proposed model seeks a strictly hyperbolic system of equations without any special consideration for the proper values of the propagation speed of sound numerical tests showed that the proposed model can accurately describe the behavior of the pgd equations in particular the occurrence of delta shock waves and vacuum states in a multidimensional problem

decrypting a class of stream ciphers using ciphertext only pseudonoise sequences generated by linear feedback shift registers 1 with some nonlinear combining function have been proposed 2 5 for cryptographic applications as running key generators in stream ciphers in this correspondence it will be shown that the number of trials to break these ciphers can be significantly reduced by using correlation methods by comparison of computer simulations and theoretical results based on a statistical model the validity of this analysis is demonstrated rubin 6 has shown that it is computationally feasible to solve a cipher proposed by pless 2 in a known plaintext attack using as few as 15 characters here the number of ciphertext symbols is determined to perform a ciphertext only attack on the pless cipher using the correlation attack our conclusion from the analysis is that the pseudonoise generator s output sequence and the sequences generated by the linear feedback shift registers should be uncorrelated this leads to constraints for the nonlinear combining function to be used

type based random access for distributed detection over multiaccess fading channels the problem of distributed detection in a sensor network over multiaccess fading channels is considered a random access transmission scheme referred to as the type based random access tbra is proposed and analyzed error exponents of tbra under noncoherent detection are characterized with respect to the mean transmission rate and the channel coherence index for the zero mean multiaccess fading channels it is shown that there exists an optimal mean transmission rate that maximizes the detection error exponents the optimal mean transmission rate can be calculated numerically or estimated using the gaussian approximation and it gives a sensor activation strategy that achieves an optimal allocation of transmission energy to spatial and temporal domains numerical examples and simulations are used to compare tbra with the conventional centralized time division multiple access tdma scheme it is shown that for the zero mean multiaccess fading channels tbra gives substantial improvement in the low signal to noise ratio snr regime whereas for the nonzero mean fading channels tbra performs better over a wide range of snr

a spectral characterization of correlation immune combining functions it is shown that a boolean combining function f x of n variables is mth order correlation immune if and only if its walsh transform f omega vanishes for all omega with hamming weight between 1 and m inclusive this result is used to extend slightly siegenthaler s ieee trans comput vol c 34 pp 81 85 jan 1985 characterization of the algebraic normal form of correlation immune combining functions

correlation immunity of nonlinear combining functions for cryptographic applications corresp pseudonoise generators for cryptographic applications consisting of several linear feedback shift registers with a nonlinear combining function have been proposed as running key generators in stream ciphers these running key generators eau sometimes be broken by ciphertext only correlation attacks on individual subsequences a new class of combining functions is presented which provides better security against such attacks the security is quantified by the smallest number m 1 of subsequences that must be simultaneously considered in a correlation attack a necessary condition for such m th order correlation immunity is proved a recursive construction is given that permits the construction of an m th order immune combining function for n subsequences for any m and n with 1 leq m finally the trade off between the length of the linear equivalent of the nonlinear generator and the order m of its immunity against correlation attacks is considered

distributed detection in sensor networks over fading channels with multiple antennas at the fusion centre we develop new and optimal algorithms for distributed detection in sensor networks over fading channels with multiple receive antennas at the fusion centre fc sensors observe a hidden physical phenomenon over fading channels and transmit their observations using the amplify and forward scheme over fading channels to the fc which is equipped with multiple antennas we derive the optimal decision rules and the associated probabilities of detection and false alarm for three scenarios of channel state information csi availability for the most difficult case of unknown csi we develop two new algorithms to derive the optimal decision rule the first is based on a gaussian approximation method where we quantify the approximation error and its rate of convergence to a true normal distribution via a multivariate version of the berry esseen bound the second is based on a multivariate saddle point laplace approximation which is obtained via a non convex optimisation problem which is solved efficiently via bayesian expectation maximisation method we show under which system configuration which algorithm is suitable and should be used for cases where the distribution of the optimal decision rule can not be derived exactly we develop a laguerre series expansion to approximate the resulting distribution the performance of the proposed algorithms is evaluated via analytic bounds and numerical simulations we show that the detection performance of the proposed algorithms is significantly superior to a local vote decision fusion based algorithms

products of linear recurring sequences with maximum complexity conditions are derived which guarantee that products of linear recurring sequences attain maximum linear complexity it is shown that the product of any number of maximum length gf q sequences has maximum linear complexity provided only the degrees of the corresponding minimal polynomials are distinct and greater than two it is also shown that if the roots of any number of not necessarily irreducible minimal polynomials are simple and lie in extension fields of pairwise relatively prime degrees then the product of the corresponding gf q sequences attains maximum linear complexity provided only that no two roots of any minimal polynomial are linearly dependent over the groundfield gf q which is automatically satisfied when q 2 the results obtained for products are extended to arbitrary linear combinations of product sequences

self organized hydrodynamics with congestion and path formation in crowds a continuum model for self organized dynamics is numerically investigated the model describes systems of particles subject to alignment interaction and short range repulsion it consists of a non conservative hyperbolic system for the density and velocity orientation short range repulsion is included through a singular pressure which becomes infinite at the jamming density the singular limit of infinite pressure stiffness leads to phase transitions from compressible to incompressible dynamics the paper proposes an asymptotic preserving scheme which takes care of the singular pressure while preventing the breakdown of the courant friedrichs lewy cfl stability condition near congestion it relies on a relaxation approximation of the system and an elliptic formulation of the pressure equation numerical simulations of impinging clusters show the efficiency of the scheme to treat congestions a two fluid variant of the model provides a model of path formation in crowds

a model for the formation and evolution of traffic jams in this paper we establish and analyze a traffic flow model which describes the formation and dynamics of traffic jams it consists of a pressureless gas dynamics system under a maximal constraint on the density and is derived through a singular limit of the aw rascle model from this analysis we deduce the particular dynamical behavior of clusters or traffic jams defined as intervals where the density limit is reached an existence result for a generic class of initial data is proved by means of an approximation of the solution by a sequence of clusters finally numerical simulations are produced

optimal resource allocation for detection of a gaussian process using a mac in wsns we analyze a binary hypothesis testing problem built on a wireless sensor network wsn for detecting a stationary random process distributed both in space and time with a circularly symmetric complex gaussian distribution under the neyman pearson np framework using an analog scheme the sensors transmit different linear combinations of their measurements through a multiple access channel mac to reach the fusion center fc whose task is to decide whether the process is present or not considering an energy constraint on each node transmission and a limited amount of channel uses we compute the miss error exponent of the proposed scheme using large deviation theory ldt and show that the proposed strategy is asymptotically optimal when the number of sensors approaches infinity among linear orthogonal schemes we also show that the proposed scheme obtains meaningful energy saving in the low signal to noise ratio regime which is the typical scenario of wsns finally a monte carlo simulation of a 2 dimensional process in space validates the analytical results

maiorana mcfarland class degree optimization and algebraic properties in this paper we consider a subclass of the maiorana mcfarland class used in the design of resilient nonlinear boolean functions we show that these functions allow a simple modification so that resilient boolean functions of maximum algebraic degree may be generated instead of suboptimized degree in the original class preserving a high nonlinearity value immanent to the original construction method together with the degree optimization gives in many cases functions with cryptographic properties superior to all previously known construction methods this approach is then used to increase the algebraic degree of functions in the extended maiorana mcfarland mm class nonlinear resilient functions f gf 2 n rarrgf 2 m derived from linear codes we also show that in the boolean case the same subclass seems not to have an optimized algebraic immunity hence not providing a maximum resistance against algebraic attacks a theoretical analysis of the algebraic properties of extended maiorana mcfarland class indicates that this class of functions should be avoided as a filtering function in nonlinear combining generators

construction of highly nonlinear 1 resilient boolean functions with optimal algebraic immunity and provably high fast algebraic immunity in 2013 tang carlet and tang ieee tit 59 1 653 664 2013 presented two classes of boolean functions the functions in the first class are unbalanced and the functions in the second one are balanced both of those two classes of functions have high nonlinearity high algebraic degree optimal algebraic immunity and high fast algebraic immunity however they are not 1 resilient which represents a drawback for their use as filter functions in stream ciphers in this paper we first propose a large family of 1 resilient boolean functions having high lower bound on nonlinearity optimal algebraic immunity and optimal algebraic degree that is meeting the siegenthaler bound most notably we can mathematically prove that every function in n variables belonging to this family has fast algebraic immunity no less than n 6 which is the first time that an infinite family of 1 resilient functions with provably high fast algebraic immunity has been invented furthermore we exhibit a subclass of the family which has higher lower bound on nonlinearity than all the known 1 resilient functions with potentially optimal algebraic immunity and potentially high fast algebraic immunity

semi implicit extension of a godunov type scheme based on low mach number asymptotics i one dimensional flow a single scale multiple space scale asymptotic analysis provides detailed insight into the low mach number limit behavior of solutions of the compressible euler equations we use the asymptotics as a guideline for developing a low mach number extension of an explicit higher order shock capturing scheme this semi implicit scheme involves multiple pressure variables large scale differencing and averaging procedures that are discretized versions of standard operations in multiple scales asymptotic analysis advection and acoustic wave propagation are discretized explicitly and upwind and only one scalar elliptic equation is to be solved implicitly at each time step this equation is a pressure correction equation for incompressible flows when the mach number is zero in the low mach number limit the time step is restricted by a courant number based essentially on the maximum flow velocity for moderate and large mach numbers the scheme reduces to the underlying explicit higher order shock capturing algorithm

uncoded transmission is exactly optimal for a simple gaussian sensor network a single memoryless gaussian source is observed by many terminals subject to independent gaussian observation noises the terminals are linked to a fusion center via a standard gaussian multiple access channel the fusion center needs to recover the underlying gaussian source with respect to mean squared error in this correspondence a theorem of witsenhausen is shown to imply that an optimal communication strategy is uncoded transmission i e each terminal s channel input is merely a scaled version of its noisy observation

new constructions of resilient functions with strictly almost optimal nonlinearity via non overlap spectra functions abstract the design of n variable t resilient functions with strictly almost optimal sao nonlinearity 2 n 1 2 n 2 n even appears to be a rather difficult task the known construction methods commonly use a rather large number exactly i t 1 n 2 n 2 i of affine subfunctions in n 2 variables which can induce some algebraic weaknesses making these functions susceptible to certain types of guess and determine cryptanalysis and dynamic cube attacks in this paper the concept of non overlap spectra functions is introduced which essentially generalizes the idea of disjoint spectra functions on different variable spaces two general methods to obtain a large set of non overlap spectra functions are given and a new framework for designing infinite classes of resilient functions with sao nonlinearity is developed based on these unlike previous construction methods our approach employs only a few n 2 variable affine subfunctions in the design resulting in a more favourable algebraic structure it is shown that these new resilient sao functions properly include all the existing classes of resilient sao functions as a subclass moreover it is shown that the new class provides a better resistance against fast algebraic attacks than the known functions with sao nonlinearity and in addition these functions are more robust to guess and determine cryptanalysis and dynamic cube attacks

a conservative discrete compatibility constraint low mach pressure correction algorithm for time accurate simulations of variable density flows in this paper we develop the discrete compatibility constraint pressure correction algorithm for transient simulations of variable density flows at low mach numbers the constraint for the velocity field is constructed from a combination of the discrete equations of continuity and scalar e g energy transport imposing that the newly predicted state must be compatible in agreement with the equation of state this way mass and scalar conservation are guaranteed and the equation of state is exactly fulfilled at every time step for comparison reasons two other types of well known pressure correction algorithms are also used the first class denoted as continuity constraint pressure correction is based on a constraint for the velocity field that is derived solely from the continuity equation the second class denoted as analytical compatibility constraint pressure correction constructs the constraint from an analytical combination of the material derivative of the equation of state and the continuity and scalar equations the algorithms are tested for three example fluid configurations a single fluid ideal gas a two fluid inert mixture and a two fluid reacting mixture the latter is special in the sense that the equation of state is non linear and not everywhere differentiable the continuity constraint pressure correction algorithm yields unstable solutions if density ratios are high the analytical compatibility constraint pressure correction algorithm yields stable results but the predicted states do not correspond to the equation of state the discrete compatibility constraint pressure correction algorithm performs well on all test cases the simulation results are stable and exactly match the equation of state

results on highly nonlinear boolean functions with provably good immunity to fast algebraic attacks abstract in the last decade algebraic and fast algebraic attacks are regarded as the most successful attacks on lfsr based stream ciphers since the notion of algebraic immunity was introduced the properties and constructions of boolean functions with maximum algebraic immunity have been researched in a large number of papers however there are few results with respect to boolean functions with provably good immunity against fast algebraic attacks in previous literatures only carlet feng function was proven to have good immunity to fast algebraic attacks in this paper we first study a large family of highly nonlinear boolean functions in terms of the immunity to fast algebraic attacks which includes the functions of tu deng the functions of tang et al and the functions of jin et al based on a sufficient and necessary condition for measuring the immunity of boolean functions against fast algebraic attacks using bivariate polynomial representation we propose an efficient method for estimating the immunity of the functions of such family then we prove that a family of 2 k variable boolean functions including the function recently constructed by tang et al are almost perfect algebraic immune for any integer k 3 more exactly they achieve optimal algebraic immunity and almost perfect immunity to fast algebraic attacks the functions of such family are balanced and have optimal algebraic degree besides we prove a lower bound on their nonlinearity based on the work of tang et al which is better than that of carlet feng function it is also checked for 3 k 9 that the exact nonlinearity of such functions is very good which is slightly smaller than that of carlet feng function and some functions of this family even have a slightly larger nonlinearity than tang s et al function to sum up among the known functions with provably good immunity against fast algebraic attacks the functions of this family make a trade off between the exact value and the lower bound of nonlinearity

generalized lexicographic multiobjective combinatorial optimization application to cryptography this paper formalizes a family of prioritized multicriteria optimization problems and assesses the corresponding up to date known suboptimal solutions the resulting framework is then employed to characterize and search for boolean functions which are valuable for a robust symmetric mainly block cipher design the proposed optimality definitions generalize the lexicographic method by establishing an ordered sequence of multiobjective combinatorial optimization problems which in turn gathers the relative relevance of the criteria so that the optimal solutions can be obtained from a sequential application of the pareto efficiency the relationship among the different formulable problems is characterized in terms of both their respective solutions sets and computing costs since in practice only a limited set of functions can be evaluated i e are known the best known pareto efficient functions are also defined finally this framework is employed to obtain new functions having known pareto max

sticky particles and scalar conservation laws one dimensional scalar conservation laws with nondecreasing initial conditions and general fluxes are shown to be the appropriate equations to describe large systems of free particles on the real line which stick under collision with conservation of mass and momentum

the weights of the orthogonals of the extended quadratic binary goppa codes starting from results on elliptic curves and kloosterman sums over the finite field ge 2 sup t the authors determine the weights of the orthogonals of some binary linear codes the melas code of length the irreducible cyclic binary code of length 2 sup t 1 and the extended binary goppa codes defined by polynomials of degree two

exploiting product distributions to identify relevant variables of correlation immune functions a boolean function f is correlation immune if each input variable is independent of the output under the uniform distribution on inputs for example the parity function is correlation immune we consider the problem of identifying relevant variables of a correlation immune function in the presence of irrelevant variables we address this problem in two different contexts first we analyze skewing a heuristic method that was developed to improve the ability of greedy decision tree algorithms to identify relevant variables of correlation immune boolean functions given examples drawn from the uniform distribution page and ray 2003 we present theoretical results revealing both the capabilities and limitations of skewing second we explore the problem of identifying relevant variables in the product distribution choice pdc learning model a model in which the learner can choose product distributions and obtain examples from them we prove a lemma establishing a property of boolean functions that may be of independent interest using this lemma we give two new algorithms for finding relevant variables of correlation immune functions in the pdc model

correlation immune functions over finite fields we give a series of constructions of correlation immune function over finite fields we prove that f sub 2 and f sub 3 are the only finite fields f sub q with the property that every n 1 th correlation immune function in n 2 variables over f sub q is linear we also show that by choosing larger finite fields one can alleviate the tradeoff between the length of the linear equivalent and the order of correlation immunity this is useful for the design of various cryptosystems

further constructions of resilient boolean functions with very high nonlinearity one well known method of generating key stream sequences for stream ciphers is to combine the outputs of several linear feedback shift registers lfsr using a combining boolean function here we concentrate on the design of good combining boolean functions we provide resilient boolean functions with currently best known nonlinearity these functions were not known earlier and the issues related to their existence were posed as open questions in the literature some of the functions we construct here achieve the provable upper bound on nonlinearity for resilient boolean functions our technique interlinks mathematical results with classical computer search

constructions of almost optimal resilient boolean functions on large even number of variables in this paper a technique on constructing nonlinear resilient boolean functions is described by using several sets of disjoint spectra functions on a small number of variables an almost optimal resilient function on a large even number of variables can be constructed it is shown that given any m one can construct infinitely many re variable n even m resilient functions with nonlinearity 2n 1 2n 2 a large class of highly nonlinear resilient functions which were not known are obtained then one method to optimize the degree of the constructed functions is proposed last an improved version of the main construction is given

a hierarchy of heuristic based models of crowd dynamics we derive a hierarchy of kinetic and macroscopic models from a noisy variant of the heuristic behavioral individual based model of ngai et al disaster med public health prep 3 191 195 2009 where pedestrians are supposed to have constant speeds this ibm supposes that pedestrians seek the best compromise between navigation towards their target and collisions avoidance we first propose a kinetic model for the probability distribution function of pedestrians then we derive fluid models and propose three different closure relations the first two closures assume that the velocity distribution function is either a dirac delta or a von mises fisher distribution respectively the third closure results from a hydrodynamic limit associated to a local thermodynamical equilibrium we develop an analogy between this equilibrium and nash equilibria in a game theoretic framework in each case we discuss the features of the models and their suitability for practical use

linear interference cancellation in cdma based on iterative techniques for linear equation systems it has previously been shown that well known iterations for solving a set of linear equations correspond to linear interference cancellation structures here we suggest applying a block wise iteration that consists of an outer and an inner iteration the outer iteration used is the gauss seidel gs method while for the inner iteration we study direct matrix inversion the jacobi over relaxation iteration and the conjugate gradient iteration when a true inner iteration is used this approach allows for a timely derivation of the acceleration parameters required by advanced iterations the block iteration is based on a symbol level implementation which leads to the same detection delay profile for both parallel and serial structures at the expense of differences in the amount of serial processing required this is discussed in some detail and quantified for comparison the performance of the detectors is studied via computer simulations where it is found that the block approach can provide significantly faster convergence leading to improved detection delay over the simpler gs iteration the improvements are obtained at the expense of an increase in the required serial processing speed

on the construction of boolean functions with optimal algebraic immunity in this correspondence we introduce a method to construct boolean functions in any number of variables with optimal algebraic immunity remarkably all functions of this type with an odd number of variables can be obtained in this way we study some cryptographic properties such as balancedness algebraic degree of the constructed functions moreover a lower bound of the number of boolean functions with optimal algebraic immunity is given

constructions of cryptographically significant boolean functions using primitive polynomials it is known that boolean functions used in stream and block ciphers should have good cryptographic properties to resist algebraic attacks up until now there have been several constructions of boolean functions achieving optimum algebraic immunity however most of their nonlinearities are very low carlet and feng studied a class of boolean functions with optimum algebraic immunity and deduced the lower bound of its nonlinearity which is good but not very high moreover the main practical problem with this construction is that it cannot be implemented efficiently in this paper we put forward a new method to construct cryptographically significant boolean functions by using primitive polynomials and construct three infinite classes of boolean functions with good cryptographic properties balancedness optimum algebraic degree optimum algebraic immunity and a high nonlinearity

numerical simulations of the euler system with congestion constraint in this paper we study the numerical simulations for euler system with maximal density constraint this model is developed in 6 17 with the constraint introduced into the system by a singular pressure law which causes the transition of different asymptotic dynamics between different regions to overcome these difficulties we adapt and implement two asymptotic preserving ap schemes originally designed for low mach number limit 16 18 to our model these schemes work for the different dynamics and capture the transitions well several numerical tests both in one dimensional and two dimensional cases are carried out for our schemes

a unified method for computing incompressible and compressible flows in boundary fitted coordinates a unified method for computing incompressible and compressible flows with mach uniform accuracy and efficiency is described the method is equally applicable to stationary and nonstationary flows a pressure based discretisation on a staggered grid in general boundary fitted coordinates is used for the euler equations extension to navier stokes is straightforward dimensionless variables that remain finite for all mach numbers are used mach number independent accuracy and efficiency is shown by numerical experiments

comments on constructions of cryptographically significant boolean functions using primitive polynomials we show that the first of the two constructions by q wang j peng h kan and x xue ieee transactions on information theory vol 56 no 6 pp 3048 3053 2010 of boolean functions satisfying the main criteria for filter functions in stream ciphers is the same as the construction studied by k feng and the author at asiacrypt 2008 lncs 5350 pp 425 440 we observe that the bounds shown on the nonlinearities of the functions in this ieee paper are similar to those shown in the asiacrypt paper we point out that these kinds of functions can be implemented in a more efficient way than usually believed

a new attack on the filter generator the filter generator is an important building block in many stream ciphers the generator consists of a linear feedback shift register of length n that generates an m sequence of period 2n 1 filtered through a boolean function of degree d that combines bits from the shift register and creates an output bit zt at any time t the previous best attacks aimed at reconstructing the initial state from an observed keystream have essentially reduced the problem to solving a nonlinear system of d sigmai 1 d n i equations in n unknowns using techniques based on linear algebra this attack needs about d bits of keystream and the system can be solved in complexity o domega where omega can be taken to be strassen s reduction exponent omega log2 7 ap2 807 this paper describes a new algorithm that recovers the initial state of most filter generators after observing o d keystream bits with complexity o d n 2 apo d after a pre computation with complexity o d log2d 3

type based estimation over multiaccess channels we study the problem of communicating sensor readings over a gaussian multiaccess channel we focus on the scenario that each sensor observes a single random variable and transmits it using certain signaling in a shared channel the objective is the design of channel waveforms i e the signal constellation to facilitate the estimation of field parameters from the channel output we propose a communication scheme in which sensors transmit according to the type of their observations type based multiple access tbma and show that the tbma is asymptotically optimal in the limit of large number of sensors if the sensor channel gains are identical in particular we show that tbma together with a variant of the maximum likelihood estimator achieves the cramer rao bound asymptotically we then extend the asymptotic analysis of tbma to fading channels and compare the performance of tbma with other orthogonal allocation methods such as time division multiple access

an all speed roe type scheme and its asymptotic analysis of low mach number behaviour a new scheme all speed roe scheme was proposed for all speed flows compared with traditional preconditioned roe scheme all speed roe scheme changes non linear eigenvalues in the numerical dissipation terms of roe type schemes with an asymptotic analysis the low mach number behaviour of the scheme is studied theoretically in two ways in one way all speed roe scheme is regarded as finite magnification of low speed roe scheme in the low mach number limit in the other way a general form of all speed roe scheme is analyzed both ways demonstrate that all speed roe scheme has the same low mach number behaviour as the original governing equation in the continuous case which includes three important features pressure variation scales with the square of the mach number the zero order velocity field is subject to a divergence constraint and the second order pressure satisfies a poisson type equation in the case of constant entropy the analysis also leads to an unexpected conclusion that the velocity filed computed by traditional preconditioned roe scheme does not satisfy the divergence constraint as the mach number vanishes moreover the analysis explains the reason of checkerboard decoupling and shows that momentum interpolation method provides a similar mechanism as traditional preconditioned roe scheme inherently possesses to suppress checkerboard decoupling in the end general rulers for modifying non linear eigenvalues are obtained finally several numerical experiments are provided to support the theoretical analysis all speed roe scheme has a sound foundation and is expected to be widely studied and applied to all speed flow calculations

mach uniformity through the coupled pressure and temperature correction algorithm we present a new type of algorithm the coupled pressure and temperature correction algorithm it is situated in between the fully coupled and the fully segregated approach and is constructed such that mach uniform accuracy and efficiency are obtained the essential idea is the separation of the convective and the acoustic thermodynamic phenomena a convective predictor is followed by an acoustic thermodynamic corrector for a general case the corrector consists of a coupled solution of the energy and the continuity equations for both pressure and temperature corrections for the special case of an adiabatic perfect gas flow the algorithm reduces to a fully segregated method with a pressure correction equation based on the energy equation various test cases are considered which confirm that mach uniformity is obtained

fundamentals of statistical signal processing estimation theory minimum variance unbiased estimation cramer rao lower bound linear models general minimum variance unbiased estimation best linear unbiased estimators maximum likelihood estimation least squares method of moments the bayesian philosophy general bayesian estimators linear bayesian estimators kalman filters summary of estimators extension for complex data and parameters

on first order markov modeling for the rayleigh fading channel previous models for the received signal amplitude of the flat fading channel that use first order finite state markov chains are examined the stochastic properties of a proposed first order model based on these models are examined the limitations of using an information theoretic metric which is sometimes used to justify a first order markov chain as a sufficient model for very slowly fading channels are discussed a simple method of qualitatively comparing autocorrelation functions is instead proposed the usefulness of the first order markov chain in representing the flat fading channel is examined by looking at two specific problems in wireless system applications that represent two disparate cases the first case involves analysis over a short duration of time relative to the inverse of the normalized doppler frequency while the second involves analysis over a long duration of time contrary to previous reports the results indicate that first order markov chains are not generally suitable for very slowly fading channels rather first order markov chains can be suitable for very slowly fading applications which require analysis over only a short duration of time

numerical approximations of pressureless and isothermal gas dynamics we study several schemes of first or second order accuracy based on kinetic approximations to solve pressureless and isothermal gas dynamics equations the pressureless gas system is weakly hyperbolic giving rise to the formation of density concentrations known as delta shocks for the isothermal gas system the infinite speed of expansion into vacuum leads to zero timestep in the godunov method based on exact riemann solver the schemes we consider are able to bypass these difficulties they are proved to satisfy positiveness of density and discrete entropy inequalities to capture the delta shocks and to treat data with vacuum

performance analysis of likelihood based multiple access for detection over fading channels in this paper we consider the binary hypothesis testing problem using wireless sensor networks we analyze the case where sensors transmit their local log likelihood ratio llr directly to a fusion center fc using an analog transmission scheme over multiple access fading channels due to the nature of the wireless medium the fc receives a superposition of sensor transmissions the decision is made by the fc and is based on received data from the sensors in contrast to the case of identical channels and i i d observations the analog transmission of the llr over multiple access fading channels does not achieve the centralized error exponent large deviation tools are used in this paper to characterize the error exponent in the asymptotic regime when the number of sensors approaches infinity in the case of non i i d observations and non i i d fading channels chernoff bounding techniques are used to provide bounds on the error probability for a finite number of sensors when the observations and the fading channels are independent across sensors specific performance analysis is provided for detection over both i i d and spatially correlated markovian fading channels simulation results then illustrate the detector s performance

energy efficient signal detection in sensor networks using ordered transmissions signal detection is one application for which dedicated sensor networks have been proposed joint signal processing and communication design of such networks has been of great interest recently we consider new approaches where transmissions can be ordered and halted when sufficient evidence is accumulated we demonstrate that these approaches require on average fewer sensor transmissions and that the savings can be significant in cases of interest we describe a highly efficient approach which saves transmissions over either the optimum unconstrained energy approach or censoring while achieving the same error probability as these approaches the average number of transmissions saved ants is lower bounded by a quantity proportional to the number of sensors employed provided a well behaved distance measure between the sensor distributions is sufficiently large for such cases the ants over the optimum unconstrained energy approach is shown to be larger than half the number of sensors employed numerical results for a mean shift hypothesis testing problem with gaussian noise show significant savings even for smaller values of the distance measure

improving the lower bound on the maximum nonlinearity of 1 resilient boolean functions and designing functions satisfying all cryptographic criteria in this article we improve the lower bound on the maximum nonlinearity of 1 resilient boolean functions for n even by proposing a method of constructing this class of functions attaining the best nonlinearity currently known thus for the first time at least for small values of n the upper bound on nonlinearity can be reached in a deterministic manner in difference to some heuristic search methods proposed previously the nonlinearity of these functions is extremely close to the maximum nonlinearity attained by bent functions and it might be the case that this is the highest possible nonlinearity of 1 resilient functions apart from this theoretical contribution it turns out that the cryptographic properties of these functions are overall good apart from their moderate resistance to fast algebraic attacks faa this weakness is repaired by a suitable modification of the original functions giving a class of balanced functions with almost optimal resistance to faa whose nonlinearity is better than the nonlinearity of other methods

on the resistance of boolean functions against algebraic attacks using univariate polynomial representation in the past few years algebraic attacks against stream ciphers with linear feedback function have been significantly improved as a response to the new attacks the notion of algebraic immunity of a boolean function f was introduced defined as the minimum degree of the annihilators of f and f 1 an annihilator of f is a nonzero boolean function g such that f g 0 while several constructions of boolean functions with optimal algebraic immunity have been proposed there is no significant progress concerning the resistance against the so called fast algebraic attacks in this paper we provide a framework to assess the resistance of boolean functions against the new algebraic attacks including fast algebraic attacks the analysis is based on the univariate polynomial representation of boolean functions and necessary and sufficient conditions are presented for a boolean function to have optimal behavior against all the new algebraic attacks finally we introduce a new infinite family of balanced boolean functions described by their univariate polynomial representation by applying the new framework we prove that all the members of the family have optimal algebraic immunity and we efficiently evaluate their behavior against fast algebraic attacks

a front tracking method for the computations of multiphase flow direct numerical simulations of multiphase flows using a front tracking method are presented the method is based on writing one set of governing equations for the whole computational domain and treating the different phases as one fluid with variable material properties interfacial terms are accounted for by adding the appropriate sources as functions at the boundary separating the phases the unsteady navier stokes equations are solved by a conventional finite volume method on a fixed structured grid and the interface or front is tracked explicitly by connected marker points interfacial source terms such as surface tension are computed on the front and transferred to the fixed grid advection of fluid properties such as density is done by following the motion of the front the method has been implemented for fully three dimensional flows as well as for two dimensional and axisymmetric ones first the method is described for the flow of two or more isothermal phases the representation of the moving interface and its dynamic restructuring as well as the transfer of information between the moving front and the fixed grid are discussed applications and extensions of the method to homogeneous bubbly flows atomization flows with variable surface tension solidification and boiling are then presented

highly nonlinear boolean functions with optimal algebraic immunity and good behavior against fast algebraic attacks inspired by the previous work of tu and deng we propose two infinite classes of boolean functions of 2k variables where k 2 the first class contains unbalanced functions having high algebraic degree and nonlinearity the functions in the second one are balanced and have maximal algebraic degree and high nonlinearity as shown by a lower bound that we prove as a byproduct we also prove a better lower bound on the nonlinearity of the carlet feng function thanks to a combinatorial fact first conjectured by the authors and later proved by cohen and flori we are able to show that they both possess optimal algebraic immunity it is also checked that at least for numbers of variables n 16 functions in both classes have a good behavior against fast algebraic attacks compared with the known boolean functions resisting algebraic attacks and fast algebraic attacks both of them possess the highest lower bounds on nonlinearity these bounds are however not enough for ensuring a sufficient nonlinearity for allowing resistance to fast correlation attack nevertheless as for previously found functions with the same features there is a gap between the bound that we can prove and the actual values computed for bounded numbers of variables n 38 moreover these values are very good the infinite class of functions we propose in construction 2 presents among all currently known constructions the best provable tradeoff between all the important cryptographic criteria

more balanced boolean functions with optimal algebraic immunity and good nonlinearity and resistance to fast algebraic attacks in this paper three constructions of balanced boolean functions with optimal algebraic immunity are proposed it is checked that at least for small numbers of input variables these functions have good behavior against fast algebraic attacks as well other cryptographic properties such as algebraic degree and nonlinearity of the constructed functions are also analyzed lower bounds on the nonlinearity are proved which are similar to the best bounds obtained for known boolean functions resisting algebraic attacks and fast algebraic attacks moreover it is checked that for the number n of variables with 5 n 19 the proposed n variable boolean functions have in fact very good nonlinearity

algebraic immunity for cryptographically significant boolean functions analysis and construction recently algebraic attacks have received a lot of attention in the cryptographic literature it has been observed that a boolean function f used as a cryptographic primitive and interpreted as a multivariate polynomial over f sub 2 should not have low degree multiples obtained by multiplication with low degree nonzero functions in this paper we show that a boolean function having low nonlinearity is also weak against algebraic attacks and we extend this result to higher order nonlinearities next we present enumeration results on linearly independent annihilators we also study certain classes of highly nonlinear resilient boolean functions for their algebraic immunity we identify that functions having low degree subfunctions are weak in terms of algebraic immunity and we analyze some existing constructions from this viewpoint further we present a construction method to generate boolean functions on n variables with highest possible algebraic immunity spl lceil n 2 spl rceil this construction first presented at the 2005 workshop on fast software encryption fse 2005 has been the first one producing such functions these functions are obtained through a doubly indexed recursive relation we calculate their hamming weights and deduce their nonlinearities we show that they have very high algebraic degrees we express them as the sums of two functions which can be obtained from simple symmetric functions by a transformation which can be implemented with an algorithm whose complexity is linear in the number of variables we deduce a very fast way of computing the output to these functions given their input