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Frequency offset estimation is an important module in the synchronisation of underwater acoustic (UWA) orthogonal frequency division multiplexing (OFDM) systems. Different ways are used for carrier frequency offset (CFO) estimation such as maximum likelihood based on a cyclic prefix. In this paper, the Zadoff-Chu (ZC) sequences are used for OFDM synchronisation in underwater communications. The normalised carrier frequency offset can be estimated using the ZC cross-correlation between the primary synchronisation signal and the corresponding local signal, which causes large complexity. The ZC sequences have a time centre symmetric property, and thus the autocorrelation of the received primary synchronisation signal can be used for frequency offset estimation. In this paper, we propose a modified algorithm with low complexity for frequency offset estimation. Simulation results demonstrate that the proposed algorithm can estimate the frequency offset accurately with simple implementation in comparison with the traditional methods. [ABSTRACT FROM AUTHOR]

In this paper, we propose a method for predicting the distributions of people's trajectories on the road network throughout a city. Specifically, we predict the number of people who will move from one area to another, their probable trajectories, and the corresponding likelihoods of those trajectories in the near future, such as within an hour. With this prediction, we will identify the hot road segments where potential traffic jams might occur and reveal the formation of those traffic jams. Accurate predictions of human trajectories at a city level in real time is challenging due to the uncertainty of people's spatial and temporal mobility patterns, the complexity of a city level's road network, and the scale of the data. To address these challenges, this paper proposes a method which includes several major components: (1) a model for predicting movements between neighboring areas, which combines both latent and explicit features that may influence the movements; (2) different methods to estimate corresponding flow trajectory distributions in the road network; (3) a MapReduce-based distributed algorithm to simulate large-scale trajectory distributions under real-time constraints. We conducted two case studies with taxi data collected from Beijing and New York City and systematically evaluated our method. [ABSTRACT FROM AUTHOR]

Purpose This paper aims to represent an improved whale optimization algorithm (WOA) based on a Lévy flight trajectory and called the LWOA algorithm to solve engineering optimization problems. The LWOA makes the WOA faster, more robust and significantly enhances the WOA. In the LWOA, the Lévy flight trajectory enhances the capability of jumping out of the local optima and is helpful for smoothly balancing exploration and exploitation of the WOA. It has been successfully applied to five standard engineering optimization problems. The simulation results of the classical engineering design problems and real application exhibit the superiority of the LWOA algorithm in solving challenging problems with constrained and unknown search spaces when compared to the basic WOA algorithm or other available solutions.Design/methodology/approach In this paper, an improved WOA based on a Lévy flight trajectory and called the LWOA algorithm is represented to solve engineering optimization problems.Findings It has been successfully applied to five standard engineering optimization problems. The simulation results of the classical engineering design problems and real application exhibit the superiority of the LWOA algorithm in solving challenging problems with constrained and unknown search spaces when compared to the basic WOA algorithm or other available solutions.Originality value An improved WOA based on a Lévy flight trajectory and called the LWOA algorithm is first proposed. [ABSTRACT FROM AUTHOR]

Random packing of spheres inside fractal collectors of dimension 2 < d < 3 is studied numerically using Random Sequential Adsorption (RSA) algorithm. The paper focuses mainly on the measurement of random packing saturation limit. Additionally, scaling properties of density autocorrelations in the obtained packing are analyzed. The RSA kinetics coefficients are also measured. Obtained results allow to test phenomenological relation between random packing saturation density and collector dimension. Additionally, performed simulations together with previously obtained results confirm that, in general, the known dimensional relations are obeyed by systems having non-integer dimension, at least for d < 3. [ABSTRACT FROM AUTHOR]

The stochastic integral ensuring the Newton-Leibnitz chain rule is essential in stochastic energetics. Marcus canonical integral has this property and can be understood as the Wong-Zakai type smoothing limit when the driving process is non-Gaussian. However, this important concept seems not well-known for physicists. In this paper, we discuss Marcus integral for non-Gaussian processes and its computation in the context of stochastic energetics. We give a comprehensive introduction to Marcus integral and compare three equivalent definitions in the literature. We introduce the exact pathwise simulation algorithm and give the error analysis. We show how to compute the thermodynamic quantities based on the pathwise simulation algorithm. We highlight the information hidden in the Marcus mapping, which plays the key role in determining thermodynamic quantities. We further propose the tau-leaping algorithm, which advance the process with deterministic time steps when tau-leaping condition is satisfied. The numerical experiments and its efficiency analysis show that it is very promising. [ABSTRACT FROM AUTHOR]

The spatial direct method with gradient-based diffusion is an accelerated stochastic reaction-diffusion simulation algorithm that treats diffusive transfers between neighboring subvolumes based on concentration gradients. This recent method achieved a marked improvement in simulation speed and reduction in the number of time-steps required to complete a simulation run, compared with the exact algorithm, by sampling only the net diffusion events, instead of sampling all diffusion events. Although the spatial direct method with gradient-based diffusion gives accurate means of simulation ensembles, its gradient-based diffusion strategy results in reduced fluctuations in populations of diffusive species. In this paper, we present a new improved algorithm that is able to anticipate all possible microscopic fluctuations due to diffusive transfers in the system and incorporate this information to retain the same degree of fluctuations in populations of diffusing species as the exact algorithm. The new algorithm also provides a capability to set the desired level of fluctuation per diffusing species, which facilitates adjusting the balance between the degree of exactness in simulation results and the simulation speed. We present numerical results that illustrate the recovery of fluctuations together with the accuracy and efficiency of the new algorithm. [ABSTRACT FROM AUTHOR]

In biochemical reaction systems dominated by delays, the simulation speed of the stochastic simulation algorithm depends on the size of the wait queue. As a result, it is important to control the size of the wait queue to improve the efficiency of the simulation. An improved accelerated delay stochastic simulation algorithm for biochemical reaction systems with delays, termed the improved delay-leaping algorithm, is proposed in this paper. The update method for the wait queue is effective in reducing the size of the queue as well as shortening the storage and access time, thereby accelerating the simulation speed. Numerical simulation on two examples indicates that this method not only obtains a more significant efficiency compared with the existing methods, but also can be widely applied in biochemical reaction systems with delays. [ABSTRACT FROM AUTHOR]

The stochastic simulation algorithm was introduced by Gillespie and in a different form by Kurtz. There have been many attempts at accelerating the algorithm without deviating from the behavior of the simulated system. The crux of the explicit τ-leaping procedure is the use of Poisson random variables to approximate the number of occurrences of each type of reaction event during a carefully selected time period, τ. This method is acceptable providing the leap condition, that no propensity function changes 'significantly' during any time-step, is met. Using this method there is a possibility that species numbers can, artificially, become negative. Several recent papers have demonstrated methods that avoid this situation. One such method classifies, as critical, those reactions in danger of sending species populations negative. At most, one of these critical reactions is allowed to occur in the next time-step. We argue that the criticality of a reactant species and its dependent reaction channels should be related to the probability of the species number becoming negative. This way only reactions that, if fired, produce a high probability of driving a reactant population negative are labeled critical. The number of firings of more reaction channels can be approximated using Poisson random variables thus speeding up the simulation while maintaining the accuracy. In implementing this revised method of criticality selection we make use of the probability distribution from which the random variable describing the change in species number is drawn. We give several numerical examples to demonstrate the effectiveness of our new method. [ABSTRACT FROM AUTHOR]

In this paper a new algorithm is presented that improves the efficiency of Wang and Landau algorithm or density of states (DOS) Monte Carlo simulations by employing rejected states. The algorithm is shown to have a performance superior to that of the original Wang-Landau [F. Wang and D. P. Landau, Phys. Rev. Lett. 86, 2050 (2001)] algorithm and the more recent configurational temperature DOS algorithm. The performance of the method is illustrated in the context of results for the Lennard-Jones fluid. [ABSTRACT FROM AUTHOR]

In this paper, we establish a framework for enabling ultra-reliable and low-latency communications in the control and non-payload communications (CNPC) links of the unmanned aerial vehicle (UAV) communication systems. We first derive the available range of the CNPC links between UAVs and a ground control station. The available range is defined as the maximal horizontal communication distance within which the round-trip delay and the overall packet loss probability can be ensured with a required probability. To exploit the macro-diversity gain of the distributed multi-antenna systems (DAS) and the array gain of the centralized multi-antenna systems (CAS), we consider a modified DAS (M-DAS), where the ground control station is equipped with the distributed access points (APs), and each AP can have multiple antennas. We then show that the available range can be maximized by judiciously optimizing the altitude of UAVs, the duration of the uplink and downlink phases, and the antenna configuration. To solve the non-convex problem, we propose an algorithm that can converge to the optimal solution in DAS and CAS, and then extend it into more general M-DAS. The simulation and numerical results validate our analysis and show that the available range of M-DAS can be significantly larger than those of the DAS and CAS. [ABSTRACT FROM AUTHOR]

Highlights • Descriptions of the experimental tests of two large-size RC containment specimens. • Descriptions of CSMM-based shell element for simulation of RC shell-type structures. • Nonlinear FE analysis of the RC containments using CSMM-based shell element. • Discussions and comparisons of experimental outcomes and analytical results. Abstract The nuclear containment structure is one of the most important infrastructure systems ensuring the safety of a nuclear power plant. The structural behavior of a cylindrical containment structure made of reinforced concrete (RC) with large dimensions and numerous rebars is complex and difficult to predict. The complex behavior of the RC containment structure has been investigated in an international collaboration project between the National Center for Research on Earthquake Engineering (NCREE) in Taipei, Taiwan and the University of Houston (UH), Houston, Texas. At NCREE two 1/13 scaled cylindrical RC containment specimens were tested under reversed cyclic loads [1]. At UH, a finite element simulation of the two tested specimens was developed using a finite element analysis (FEA) program SCS [2]. In the program, a new shell element, the so-called CSMM-based shell element, was developed based on the Cyclic Softened Membrane Model [3] and the formulation of an 8-node Serendipity curved shell element [4] with a multi-layer approach [5]. The UH simulated seismic behavior was close to the NCREE experimental results. This paper presents the theoretical development of the FEA program SCS and the comparisons of its predictions with the experimental structural behavior of the two RC containment specimens. This simulation model and the FEA program are excellent tools to develop effective performance-based design provisions. [ABSTRACT FROM AUTHOR]

We describe in this paper the experimental procedure, the data treatment and the quantification of the black body correction: an experimental approach to compensate for scattering and systematic biases in quantitative neutron imaging based on experimental data. The correction algorithm is based on two steps; estimation of the scattering component and correction using an enhanced normalization formula. The method incorporates correction terms into the image normalization procedure, which usually only includes open beam and dark current images (open beam correction). Our aim is to show its efficiency and reproducibility: we detail the data treatment procedures and quantitatively investigate the effect of the correction. Its implementation is included within the open source CT reconstruction software MuhRec. The performance of the proposed algorithm is demonstrated using simulated and experimental CT datasets acquired at the ICON and NEUTRA beamlines at the Paul Scherrer Institut. [ABSTRACT FROM AUTHOR]

Particle-based methods based on material models using spheres can provide good approximations for many physical phenomena at both the micro and macroscales. The point of departure for the simulations, in general, is a dense arrangement of spherical particles (sphere pack) inside a given container. For generic domains, the generation of a sphere pack may be complex and time-consuming, especially if the pack must comply with a prescribed sphere size distribution and the stability requirements of the simulation. The primary goal of this paper is to present an efficient algorithm that is capable of producing packs with millions of spheres following a statistical sphere size distribution inside complex arbitrary domains. This algorithm uses a new strategy to ensure that the sphere size distribution is preserved even when large particles are rejected in the growing process. The paper also presents numerical results that enable an evaluation of the proposed algorithm. [ABSTRACT FROM AUTHOR]

In this paper, we discuss the structure and performance of the maximum entropy temperature-emissivity separation (MaxEnTES) algorithm for assessing land temperature and emissivity from thermal infrared hyperspectral images. This procedure derives the emissivity spectrum and the temperature of the target adopting the maximum entropy (MaxEnt) estimation approach. The main advantage of the MaxEnt statistical inference is the absence of any external hypothesis, which is, instead, the main critical point characterizing any other temperature-emissivity separation (TES) algorithm. The MaxEnTES algorithm carries out the TES task adopting a modified version of the subgradient Shor's r-algorithm adopted for numerical optimization of a MaxEnt objective function. For this purpose, we have utilized the C/C++ Solvopt code from the University of Gratz to develop a practical data processing implementation. In this paper, we discuss the mathematical structure of the MaxEnTES algorithm and analyze its performance in depth using numerical simulations and remote sensing Multispectral Infrared/Visible Imaging Spectrometer images. We show that the MaxEnTES algorithm provides improved accuracy for temperature and emissivity estimation, lowering the standard estimation error to a fraction of degree Kelvin. In agreement with previous investigations, we find that the estimation accuracy grows when increasing the number of available spectral channels. The systematic errors affecting the temperature estimates (e.g., bias) are thoroughly evaluated. We prove that the MaxEnTES algorithm retrieves the correct shape of the target emissivity spectrum even in presence of a significant temperature estimation error. [ABSTRACT FROM PUBLISHER]

This paper studies the complexity of distributed construction of purely additive spanners in the CONGEST model. We describe algorithms for building such spanners in several cases. Because of the need to simultaneously make decisions at far apart locations, the algorithms use additional mechanisms compared to their sequential counterparts. We complement our algorithms with a lower bound on the number of rounds required for computing pairwise spanners. The standard reductions from set-disjointness and equality seem unsuitable for this task because no specific edge needs to be removed from the graph. Instead, to obtain our lower bound, we define a new communication complexity problem that reduces to computing a sparse spanner, and prove a lower bound on its communication complexity. This technique significantly extends the current toolbox used for obtaining lower bounds for the CONGEST model, and we believe it may find additional applications. [ABSTRACT FROM AUTHOR]

In this paper a simple four-point, in terms of time, but eight-value in total, identification method has been developed for the second-order linear Nomoto steering model. The algorithm intrinsically uses the zigzag test data in that it inherited some principles of the well-known procedure for the first-order model, from which it is essentially derived. The performance evaluation was then conducted with both simulated and real data. However, the results of these early, unprecedented efforts are far from satisfactory. Some potential sources of difficulties have been discussed. This calls for further research and improvement in order to provide a practical application of the method. [ABSTRACT FROM AUTHOR]

Interactive rigid body simulation is an important part of many modern computer tools, which no authoring tool nor game engine can do without. Such high-performance computer tools open up new possibilities for changing how designers, engineers, modelers and animators work with their design problems. This paper is a self contained state-of-the-art report on the physics, the models, the numerical methods and the algorithms used in interactive rigid body simulation all of which have evolved and matured over the past 20 years. Furthermore, the paper communicates the mathematical and theoretical details in a pedagogical manner. This paper is not only a stake in the sand on what has been done, it also seeks to give the reader deeper insights to help guide their future research. [ABSTRACT FROM AUTHOR]

Abstract: The system of equations arising in finite element simulations of components made of ferroelectroelastic materials is non-linear if the loading is sufficiently high. The Newton–Raphson method represents a widely used iterative technique to solve this system of non-linear equations. However, if the scalar potential formulation is utilised, convergence difficulties may occur. This circumstance can be primarily attributed to the specific form of the non-linear response of typical ferroelectroelastic materials being subjected to electrical loading. The present paper is devoted to modifications of the Newton–Raphson method, which are capable of improving the convergence behaviour experienced in the finite element iteration. We extend an existing modification to the fully coupled, ferroelectroelastic case. Additionally, a new modification of the Newton–Raphson method is proposed. This method applies an iteration algorithm, which is virtually equivalent to the iteration algorithm of the unmodified Newton–Raphson method combined with the vector potential formulation. An important feature of both modifications is that they are applied on the integration point level. Therefore, the global non-linear finite element iteration scheme remains unchanged. Finally, the practicability of the modifications discussed in the paper is shown in a numerical example. [Copyright &y& Elsevier]

This paper is concerned with accurate and efficient numerical methods for solving viscous and nonviscous wave problems. The paper first introduces a new second-order PR-ADI like scheme. For an efficient simulation, the scheme is also extended to a highorder compact PRADI likemethod. Both of themhave the advantages of unconditional stability, less impact of the perturbing terms on the accuracy, and being convenient to compute the boundary values of the intermediates. Besides this, the compact scheme has high-order accuracy and costs less in computational time. Numerical results are presented to show the accuracy and efficiency of the new algorithms. [ABSTRACT FROM AUTHOR]

Generating synthetic baseline populations is a fundamental step of agent-based modeling and simulation, which is growing fast in a wide range of socio-economic areas including transportation planning research. Traditionally, in many commercial and non-commercial microsimulation systems, the iterative proportional fitting (IPF) procedure has been used for creating the joint distribution of individuals when combining a reference joint distribution with target marginal distributions. Although IPF is simple, computationally efficient, and rigorously founded, it is unclear whether IPF well preserves the dependence structure of the reference joint table sufficiently when fitting it to target margins. In this paper, a novel method is proposed based on the copula concept in order to provide an alternative approach to the problem that IPF resolves. The dependency characteristic measures were computed and the results from the proposed method and IPF were compared. In most test cases, the proposed method outperformed IPF in preserving the dependence structure of the reference joint distribution. [ABSTRACT FROM AUTHOR]

Abstract: High strength thin-walled rectangular concrete-filled steel tubular (CFST) slender beam-columns under eccentric loading may undergo local and overall buckling. The modeling of the interaction between local and overall buckling is highly complicated. There is relatively little numerical study on the interaction buckling of high strength thin-walled rectangular CFST slender beam-columns. This paper presents a new numerical model for simulating the nonlinear inelastic behavior of uniaxially loaded high strength thin-walled rectangular CFST slender beam-columns with local buckling effects. The cross-section strengths of CFST beam-columns are modeled using the fiber element method. The progressive local and post-local buckling of thin steel tube walls under stress gradients is simulated by gradually redistributing normal stresses within the steel tube walls. New efficient Müller''s method algorithms are developed to iterate the neutral axis depth in the cross-sectional analysis and to adjust the curvature at the columns ends in the axial load–moment interaction strength analysis of a slender beam-column to satisfy equilibrium conditions. Analysis procedures for determining the load–deflection and axial load–moment interaction curves for high strength thin-walled rectangular CFST slender beam-columns incorporating progressive local bucking and initial geometric imperfections are presented. The new numerical model developed is shown to be efficient for predicting axial load–deflection and axial load–moment interaction curves for high strength thin-walled rectangular CFST slender beam-columns. The verification of the numerical model and parametric studies is given in a companion paper. [Copyright &y& Elsevier]

In this paper, the noise reduction property of type-2 fuzzy logic (FL) systems (FLSs) (T2FLSs) that use a novel type-2 fuzzy membership function is studied. The proposed type-2 membership function has certain values on both ends of the support and the kernel and some uncertain values for the other values of the support. The parameter tuning rules of a T2FLS that uses such a membership function are derived using the gradient descend learning algorithm. There exist a number of papers in the literature that claim that the performance of T2FLSs is better than type-1 FLSs under noisy conditions, and the claim is tried to be justified by simulation studies only for some specific systems. In this paper, a simpler T2FLS is considered with the novel membership function proposed in which the effect of input noise in the rule base is shown numerically in a general way. The proposed type-2 fuzzy neuro structure is tested on different input–output data sets, and it is shown that the T2FLS with the proposed novel membership function has better noise reduction property when compared to the type-1 counterparts. [ABSTRACT FROM AUTHOR]

Abstract: The unique behavior of shape memory alloys derives from its ability of phase transformation instead of slip. A reason for the phase transformation is the microstructural occurrence and amount of different variants for the multi-variant- and detwinned-martensite dependent on the stress state as well as preferred directions in textured materials. The model presented in this paper enables to take into account all martensitic variants in different orientated grains. The main focus of this paper is the numerical implementation of a known, but advanced model with a projected Newton algorithm and a residual including only two vectors of unknowns. Additionally the texture of a pseudoelastic NiTi wire is measured and the orientations and their weight/size are implemented. Finally in a finite element example the superelastic behavior of a stent with different stress states at different locations is investigated. [Copyright &y& Elsevier]

This paper presents a new algorithm for the control of a snake-like robot with passive joints and active wheels. Each segment has four autonomously driven and steered wheels. The algorithm approximates the ideal solution in which all wheels on a segment have the same centre of curvature with wheel speeds, providing cooperative redundancy. Each hitch point joining segments traverses the same path, which is determined by an operator, prescribing the path curvature and front hitch speed. The numerical algorithm developed in this paper is simulation tested against a previously derived analytical solution for a predetermined path. Further simulations are carried out to show the effects of changing curvature and front hitch speed on hitch path, wheel angles and wheel speeds for a one, two and three segment robot. [ABSTRACT FROM AUTHOR]

Abstract: Recently, block-sparse signals, whose nonzero coefficients appearing in blocks, have received much attention. A corresponding block-based orthogonal greedy algorithm (OGA) was proved by Eldar to successfully recover ideal noiseless block-sparse signals under a certain condition on block-coherence. In this paper, the stability problem of block OGA used to recover the noisy block-sparse signals is studied and the corresponding approximation bounds are derived. The theoretical bounds presented in this paper are more general and are proven to include those reported by Donoho and Tseng. Numerical experimental results are presented to support the validity and correctness of theoretical derivation. The simulation results also show that in the noisy case, the block OGA can be proved to achieve better reconstruction performance than the OGA when the conventional sparse signals are represented in block-sparse forms. [Copyright &y& Elsevier]

Interpolation or mapping of data from a given real array to data from a virtual array of more suitable geometry is well known in array signal processing. This operation allows arrays of any geometry to be used with fast direction-of-arrival (DOA) estimators designed for linear arrays. In an earlier companion paper [21], a first-order condition for zero DOA bias under such mapping was derived and was also used to construct a design algorithm for the mapping matrix that minimized the DOA estimate bias. This bias-minimizing theory is now extended to minimize not only bias, but also to consider finite sample effects due to noise and reduce the DOA mean-square error (MSE). An analytical first-order expression for mapped DOA MSE is derived, and a design algorithm for the transformation matrix that minimizes this MSE is proposed. Generally, DOA MSE is not reduced by minimizing the size of the mapping errors but instead by rotating these errors and the associated noise subspace into optimal directions relative to a certain gradient of the DOA estimator criterion function. The analytical MSE expression and the design algorithm are supported by simulations that show not only conspicuous MSE improvements in relevant scenarios, but also a more robust preprocessing for low signal-to-noise ratios (SNRs) as compared with the pure bias-minimizing design developed in the previous paper. [ABSTRACT FROM AUTHOR]

We introduce a fast error-free tracking method applicable to sequences of two and three dimensional images. The core idea is to use Quadtree (resp. Octree) data structures for representing the spatial discretization of an image in two (resp. three) spatial dimensions. This representation enables one to merge into large computational cells the regions that can be faithfully described with such a coarse representation, thus significantly reducing the total number of degrees of freedom that are processed, without compromising accuracy. This encoding is particularly effective in the case of algorithms based on moving fronts, since the adaptive refinement provides a natural means to focus the processing resources on information near the moving front. In this paper, we use an existing contour based tracker and reformulate it to the case of Quad-/Oc-tree data structures. Relevant mathematical assumptions and derivations are presented for this purpose. We then demonstrate that, on standard bio-medical image sequences, a speed up of 5X is easily achieved in 2D and about 10X in 3D. [ABSTRACT FROM AUTHOR]

In space communication environments, most studies in delay tolerant networks (DTNs) adopt experimental approaches and they have shown that the utilization efficiency of link bandwidth can be affected by changing packet sizes at the bundle layer and the convergence layer. However, the lack of theoretical work makes it difficult to find the optimal packet sizes in general scenarios. In this paper, we focus on this important issue by performing a theoretical analysis to solve the packet size optimization problems in both one-hop and multihop DTNs. As our analysis is based on the widely used DTN architecture with Bundle Protocol (BP) and Licklider Transmission Protocol (LTP), the theoretical results can be applied to any DTN scenario using this architecture. We formulate packet size optimization problems in DTNs as nonconvex optimization problems. Furthermore, a goodput enhancement algorithm (GEA) is also proposed to find the optimal packet sizes in order to maximize goodput in DTNs. We conduct numerical analysis as well as simulations to validate our theoretical analysis and study the factors that determine the optimal packet sizes for BP and LTP. Numerical results show that GEA achieves significant performance improvement compared with schemes where packet size optimization on BP and LTP is not jointly considered. [ABSTRACT FROM PUBLISHER]

In this paper, we combine two techniques together, i.e., the fast Fourier transform-twofold subspace-based optimization method (FFT-TSOM) and multiplicative regularization (MR) to solve inverse scattering problems. When applying MR to the objective function in the FFT-TSOM, the new method is referred to as MR-FFT-TSOM. In MR-FFT-TSOM, a new stable and effective strategy of regularization has been proposed. MR-FFT-TSOM inherits not only the advantages of the FFT-TSOM, i.e., lower computational complexity than the TSOM, better stability of the inversion procedure, and better robustness against noise compared with the SOM, but also the edge-preserving ability from the MR. In addition, a more relaxed condition of choosing the number of current bases being used in the optimization can be obtained compared with the FFT-TSOM. Particularly, MR-FFT-TSOM has even better robustness against noise compared with the FFT-TSOM and multiplicative regularized contrast source inversion (MR-CSI). Numerical simulations including both inversion of synthetic data and experimental data from the Fresnel data set validate the efficacy of the proposed algorithm. [ABSTRACT FROM PUBLISHER]

The aim of this paper is to establish the existence, uniqueness and asymptotic behaviour of a strong regular solution for a class of nonlinear equations of reaction–diffusion nonlocal type with moving boundaries: u t - a ∫ Ω t u ( x , t ) dx u xx = f ( x , t ) , ( x , t ) ∈ Q t , u ( α ( t ) , t ) = u ( β ( t ) , t ) = 0 , t > 0 , u ( x , 0 ) = u 0 ( x ) , x ∈ Ω 0 = ] α ( 0 ) , β ( 0 ) [ , where Q t is a bounded non-cylindrical domain defined by Q t = ( x , t ) ∈ R 2 : α ( t ) < x < β ( t ) , for all 0 < t < T . Moreover, we study the properties of the solution and implement a numerical algorithm based on the Moving Finite Element Method (MFEM) with polynomial approximations of any degree, to solve this class of problems. Some numerical tests are investigated to evaluate the performance of our Matlab code based on the MFEM and illustrate the exponential decay of the solution. [ABSTRACT FROM AUTHOR]

In this paper we consider lifetime distributions called EB-Max distribution and EB-Min. In the conditions of the Poisson's Limit Theorem it is shown that EB-Max distribution may be approximated by its analogous called EP-Max lifetime distribution and EB-Min distribution may be approximated by its analogous EP-Min lifetime distribution. Further, as example, two methods are provided to simulate pseudo random number for EB-Min distribution and we apply EM algorithm to estimate parameters of EB-Min distribution. An example with real data is also presented and the proposed simulation algorithms where implemented in Maple. [ABSTRACT FROM AUTHOR]

In the fourth generation or next generation networks, services of non-real-time variable bit rate (NRT-VBR) and best effort (BE) will dominate over 85% of the total traffic in the networks. In this paper, we study the power saving mechanism of NRT-VBR and BE services for mobile handsets (MHs) to prolong their battery lifetime (i.e., the sustained operation duration) in the fourth generation networks. Because the priority of NRT-VBR and BE is lower than that of real-time VBR (RT-VBR) or guaranteed bit rate (GBR) services, we investigate an extended sleep mode for lower priority services (e.g., NRT-VBR and BE) in an MH to conserve the energy. The extended sleep mode is used when the MH wakes up from the sleep mode but it cannot obtain the bandwidth from base station (BS). The proposed mechanism, named extra power saving scheme (EPSS), uses the Markovian queuing model to estimate the extended sleep duration to let MHs conserve their battery energy when the networks traffic is congested. To study the performance of EPSS, an accurate analysis model of energy is presented and validated by taking a series of simulations. Numerical experiments show that EPSS can achieve 43% extra energy conservation at most when downlink resource is saturated. We conclude that the energy of MHs can be conserved further by applying EPSS when the traffic load is saturated. The effect of energy saving becomes more obvious when the portion of NRT-VBR and BE services is greater than that of RT-VBR and GBR services. [ABSTRACT FROM AUTHOR]

Numerical modeling and simulation of clay brick masonry infilled in a reinforced concrete frame (RC frame) subjected to blast loading has been presented in this paper. The pressure loading generated in blast shock has been applied on the masonry and the reinforced concrete frame and time history analysis has been made using ABAQUS finite element software package. The slip and separation at the joints of RC frame and masonry occurring during blast loading due to large difference in their stiffness has been modeled using contact algorithm. The study of the infilled brick masonry has been carried out with elasto-plastic strain hardening model using Mohr-Coulomb yield and failure criterion and contact algorithm for modeling contact behaviour at the interface of masonry wall and RC frame. The non-linearity in RC beam/column has been modelled using concrete damaged plasticity model. The parameters for non-linear finite element modeling of masonry have been experimentally determined. In order to gain confidence in the analysis, the proposed constitutive models have been validated with available experimental results on infilled masonry walls. The parametric study has been made for surface blast of 100 kg TNT at a detonation distance 20, 30 and 40 m for 340 mm and 235 mm thick masonry walls with three grades of mortar infilled in a RC frame. The effect of variation of contact friction between mortar and RC elements on the behaviour of masonry walls has also been studied. [ABSTRACT FROM AUTHOR]

An efficient connection scheme for the stable incorporation of several instructive finite-difference time-domain (FDTD) computing models in the non-standard (NS)-FDTD method is proposed in this paper. Based on a straightforward formulation, the novel technique achieves an optimal FDTD/NS-FDTD connection via an interlayer region. Subsequently, the proposed concept is extended to a robust subgrid algorithm for the 3-D NS-FDTD method through the perfectly matched layer condition to decrease the total computational burden. The merits of the combined methodology are numerically validated by diverse applications, such as wire antennas and microwave devices. [ABSTRACT FROM AUTHOR]

Highlights: [•] The paper presents a new method for microscopic egress analysis in case of fire. [•] It considers occupant’s characteristics, building properties and env. conditions. [•] The egress analysis is integrated into the BIM environment. [•] An integrated model-based numerical fire simulation is deployed for env. conditions. [•] A wayfinding algorithm permanently calculates and evaluates the potential ways. [Copyright &y& Elsevier]

As Dempster-Shafer theory spreads in different application fields, and as mass functions are involved in more and more complex systems, the need for algorithms randomly generating mass functions arises. Such algorithms can be used, for instance, to evaluate some statistical properties or to simulate the uncertainty in some systems (e.g., data base content, training sets). As such random generation is often perceived as secondary, most of the proposed algorithms use straightforward procedures whose sample statistical properties can be difficult to characterize. Thus, although such algorithms produce randomly generated mass functions, they do not always produce what could be expected from them (for example, uniform sampling in the set of all possible mass functions). In this paper, we briefly review some well-known algorithms, explaining why their statistical properties are hard to characterize. We then provide relatively simple algorithms and procedures to perform efficient random generation of mass functions whose sampling properties are controlled. [ABSTRACT FROM AUTHOR]

This paper demonstrates the use of asynchronous maximum-likelihood (ML) detection to improve the detection performance of coded servo repeatable run out data. A suboptimal ML algorithm based on an absolute value metric is presented. This paper compares the performance of the ML algorithms with an asynchronous bit by bit (BBB) detection algorithm. Simulation results quantify the performance improvement over the BBB algorithm. A gain correction algorithm is also proposed to allow the asynchronous ML detection performance to be less sensitive to gain errors. The efficacy of the gain correction algorithm is quantified via simulations. [ABSTRACT FROM AUTHOR]

Abstract: This paper presents a method for the identification of loads applied to a structure, using the concept of response transmissibility. The authors propose to perform the identification of the loads in two steps: the first identifies the number of forces and their location using an algorithm of “search for number and position”, based on the response transmissibility concept; the second step consists of the reconstruction of the load vector. To carry out the first step, a complete description of the structure in terms of degrees-of-freedom will be assumed and a numerical model (usually a finite element one) is built. In order to perform the identification of the number of forces and their location, the proposed algorithm combines both the dynamic responses experimentally measured and the transmissibility matrices obtained from the numerical model. The regeneration of the load vector is achieved during the second step, once the number of loads and their location are known, combining the dynamic responses obtained experimentally with the transmissibility matrix from the numerical model. A series of simulated and experimental results on a free–free beam are presented to illustrate the procedure. [Copyright &y& Elsevier]

Abstract: In this paper, we propose a novel scheme for optical information hiding (encryption) of two-dimensional images by combining image scrambling techniques in fractional Fourier domains. The image is initially randomly shifted using the jigsaw transform algorithm, and then a pixel scrambling technique based on the Arnold transform (ART) is applied. The scrambled image is then encrypted in a randomly chosen fractional Fourier domain. These processes can then be iteratively repeated. The parameters of the architecture, including the jigsaw permutation indices, Arnold frequencies, and fractional Fourier orders, form a very large key space enhancing the security level of the proposed encryption system. Optical implementations are discussed as numerical implementation algorithms. Numerical simulation results are presented to demonstrate the system''s flexibility and robustness. [Copyright &y& Elsevier]

Abstract: This paper addresses pattern classification in dynamical systems, where the underlying algorithms are formulated in the symbolic domain and the patterns are constructed from symbol strings as probabilistic finite state automata (PFSA) with (possibly) diverse algebraic structures. A combination of Dirichlet and multinomial distributions is used to model the uncertainties due to the (finite-length) string approximation of symbol sequences in both training and testing phases of pattern classification. The classifier algorithm follows the structure of a Bayes model and has been validated on a simulation test bed. The results of numerical simulation are presented for several examples. [Copyright &y& Elsevier]

In this paper, the response of two-dimensional framed structures made of rectangular cells to the sudden removal of columns is studied. A simulation algorithm based on the discrete-element method is employed, where the structural elements are represented by elasto-plastic Euler-Bernoulli beams with elongation-rotation failure threshold. The effect of structural cell slenderness and of topological hierarchy on the dynamic residual strength after damage is investigated. Topologically hierarchical frames have a primary structure made of a few massive elements, while homogeneous frames are made of many thin elements. It is also shown how depends on the activated collapse mechanisms, which are determined by the mechanical hierarchy between beams and columns, i.e., by their relative strength and stiffness. Finally, principles of robustness-oriented capacity design that seem to be in contrast to the conventional antiseismic capacity design are addressed. [ABSTRACT FROM AUTHOR]

In this paper, a full scale cold model of 500 t/d entrained-flowgasifier by two-stage oxygen was used to analyze the distributioncharacteristics of the aerodynamic field in the gasifier. The realizable k–ε turbulent model was adopted to simulatethe three-dimensional turbulent flow field with the SIMPLE (semi-implicitmethod for pressure-linked equations) algorithm for the gasifier.The effects of side injecting velocity, position, number of nozzles,and group mode on aerodynamic field distributions were analyzed. Theresults show that the numerical simulation data are well-matched withthe experiment data. The simulated results are acceptable and canpresent a foundation for the future design, assessment, and furtheroptimization of the entrained-flow gasifier by two-stage oxygen. [ABSTRACT FROM AUTHOR]

In this paper, we present a new centralised algorithm to detect and resolve generalised deadlock in distributed systems. The initiator of this algorithm induces a directed spanning tree by diffusing the probe messages among its dependent processes. It then collects replies that carry the dependency information of the dependent process to determine a deadlock. Moreover, the initiator of this algorithm performs reduction once it receives a reply from an active process unlike the existing algorithms. Hence, it terminates the execution when it detects a deadlock without waiting for termination detection. We have asserted the correctness of the algorithm formally. It has a worst-case time complexity of d+2 time units, message complexity of e+2n messages and message size of O(n), where n is the number of nodes, e is the number of edges and d is the diameter in the wait-for graph. The performance of the proposed algorithm is compared with that of the existing centralised algorithms in terms of deadlock duration, message traffic and message size using simulation. Numerical results reveal that the performance of the proposed algorithm is equal or better than that of the existing algorithms. [ABSTRACT FROM PUBLISHER]

This paper presents an automatic process for fabrication-oriented design of custom-shaped rubber balloons. We cast computational balloon design as an inverse problem: given a target shape, we compute an optimal balloon that, when inflated, approximates the target as closely as possible. To solve this problem numerically, we propose a novel physics-driven shape optimization method, which combines physical simulation of inflatable elastic membranes with a dedicated constrained optimization algorithm. We validate our approach by fabricating balloons designed with our method and comparing their inflated shapes to the results predicted by simulation. An extensive set of manufactured sample balloons demonstrates the shape diversity that can be achieved by our method. [ABSTRACT FROM AUTHOR]

Abstract: This paper presents a statistical algorithm for classification of faults on power transmission lines. The proposed algorithm is based upon the wavelet transform of three phase currents measured at the sending end of a line and the Classification and Regression Tree (CART) method, a commonly available statistical method. Wavelet transform of current signal provides hidden information of a fault situation as an input to CART algorithm, which is used to classify different types of faults. The proposed technique is simulated using MATLAB/SIMULINK software and it is tested upon the data created with the fault analysis of the 400kV sample transmission line considering wide variations in the operating conditions. The classification results are also compared with the results obtained using back propagation neural network. [Copyright &y& Elsevier]