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• The improved PSO was employed to calibrating the micro-parameters. • Different combinations of micro-parameters of DEM model can be obtained. • More macro-parameters should be used to calibrate the micro-parameters of DEM model. The discrete element method (DEM) is commonly used for simulating the mechanical characteristics of rock materials; however, constructing a DEM model requires the specification of a number of microparameters. In this paper, to obtain the microparameters of the DEM model, the improved particle swarm optimization (PSO) calibration method was presented. Based on numerical simulation examples, the new approach is considered valid for calibrating the microparameters of the DEM model. Moreover, it is concluded that different sets of microparameters can be determined when few macroparameters are used, which indicates that the empirical formula between microparameters and macroparameters is not reliable. From the analysis of the numerical simulation results, it is suggested that more macroparameters should be used to calibrate the microparameters of the DEM model, and the corresponding numerical simulation results could be more reliable; otherwise, the generated numerical model may not accurately simulate the mechanical characteristics of rock materials. [ABSTRACT FROM AUTHOR]

Plant-wide oscillation detection is an important task in the maintenance of large-scale industrial control systems, owing to the fact that in an interactive multi-loop environment oscillation generated in one loop may propagate to the different parts of the plant. In such a scenario, it is required that different loops oscillating due to a common cause and hence similar frequency may be grouped together. In this paper an adaptive method for plant-wide oscillation detection based on multivariate empirical mode decomposition (MEMD) along with a grouping algorithm is proposed. The method can identify multiple oscillation groups among different variables as well as variables with random noise only. The proposed method is also applicable to both non-linear and non-stationary time series where the techniques based on the conventional Fourier analysis are prone to errors. Within each group that oscillate due to a common cause, the method can also indicate the location of the probable root cause of oscillations. The efficacy of the proposed method is established with the help of both simulation and industrial case studies. [ABSTRACT FROM AUTHOR]

Recommender systems use algorithms to provide users with product or service recommendations. Recently, these systems have been using machine learning algorithms from the field of artificial intelligence. However, choosing a suitable machine learning algorithm for a recommender system is difficult because of the number of algorithms described in the literature. Researchers and practitioners developing recommender systems are left with little information about the current approaches in algorithm usage. Moreover, the development of recommender systems using machine learning algorithms often faces problems and raises questions that must be resolved. This paper presents a systematic review of the literature that analyzes the use of machine learning algorithms in recommender systems and identifies new research opportunities. The goals of this study are to (i) identify trends in the use or research of machine learning algorithms in recommender systems; (ii) identify open questions in the use or research of machine learning algorithms; and (iii) assist new researchers to position new research activity in this domain appropriately. The results of this study identify existing classes of recommender systems, characterize adopted machine learning approaches, discuss the use of big data technologies, identify types of machine learning algorithms and their application domains, and analyzes both main and alternative performance metrics. [ABSTRACT FROM AUTHOR]

Abstract: In the framework of dependent risks it is a crucial task for risk management purposes to quantify the probability that the aggregated risk exceeds some large value . Motivated by Asmussen et al. (2011) [1] in this paper we introduce a modified Asmussen–Kroese estimator for simulation of the rare event that the aggregated risk exceeds . We show that in the framework of log-Gaussian risks our novel estimator has the best possible performance i.e., it has asymptotically vanishing relative error. For the more general class of log-elliptical risks with marginal distributions in the Gumbel max-domain of attraction we propose a modified Rojas-Nandayapa estimator of the rare events of interest, which for specific importance sampling densities has a good logarithmic performance. Our numerical results presented in this paper demonstrate the excellent performance of our novel Asmussen–Kroese algorithm. [Copyright &y& Elsevier]

Abstract: Lines of curvature are important intrinsic characteristics of a curved surface used in a wide variety of geometric analysis and processing. Although their differential attributes have been examined in detail, their global geometric distribution and topological pattern are very difficult to compute over the whole surface because of umbilical points and unstable numerical computation. No studies have yet been carried out on this problem, especially for an implicit surface. In this paper, we present a scheme for computing and visualizing the lines of curvature defined on an implicit surface. A key structure is introduced, conveying significant structure information about lines of curvature to facilitate their investigation, rather than computing their whole net. Our current framework is confined to a collection of manageable structures, consisting of algorithms to locate some seed umbilical points, to compute the lines of curvature through them, and finally to assemble this structure. The numerical implementations are provided in detail and a novel evaluation function measuring the violation of umbilical points in an implicit surface, i.e. indicating how much a point is to be umbilical, is also presented. This paper is the continuation of [Che, W.J., Paul, J.-C., Zhang, X.P., 2007. Lines of curvature and umbilical points for implicit surfaces. Computer Aided Geometric Design 24 (7), 395–409]. [Copyright &y& Elsevier]

This paper presents a mesoscale analysis approach to investigate the dynamic response of the sand particulate system. Firstly, a 3D mesoscopic model is developed considering the randomness of sand particles in shape and distribution. Secondly, we put forward an analysis approach to model the mechanical behavior of dry sand under static and dynamic loadings. Simulations are conducted to validate the numerical model and the analysis approach. A good agreement is attained comparing with test data. The presented 3D model can realistically model the grain-level response of the dry sand particulate system under high strain rate loadings. Finally, applications are carried out in the domain of projectile penetration into the sand particulate system. The contact and friction between sand particles are taken into account using the contact algorithm. The effects of mesoscopic configurations (porosity, particle size, contact and friction coefficients) of the specimen are discussed numerically. Simulations focusing on the stress wave propagation, projectile penetration depth and instability are conducted. Results show that impact velocity of projectile is also an important factor for penetration behavior. Porosity, particle size and friction coefficients affect ballistic instability significantly. [ABSTRACT FROM AUTHOR]

In this paper, we present numerical and experimental study on beam steering with liquid-crystal optical phased array (LC-OPA) by means of stochastic parallel gradient descent (SPGD) algorithm. The numerical simulation, which is mainly based on the evolution of power-in-bucket (PIB), indicates that the beam steering strategy with LC-OPA is relatively robust, and the algorithm performs well most of the time. The results also reveal that the performance of SPGD algorithm is influenced by the order of Zernike polynomials, the radius of bucket and the steering angle. The order of Zernike polynomials and the radius of bucket are optimized to improve the accuracy and convergence of the algorithm. In a proof-of-concept experiment, the feasibility of the beam steering strategy with LC-OPA is demonstrated. [ABSTRACT FROM AUTHOR]

In this paper, an optimal nonlinear feedback guidance algorithm with complex state and control constraints is developed for Mars powered decent. The analysis of the optimal control problem for Mars powered descent is undertaken firstly. Then based on the real-time sampling optimal feedback control theory, the Mars powered descent guidance (PDG) algorithm is designed and analysed. A practical method is also proposed to solve the problem of the initialization of the PDG algorithm. Numerical simulations are performed to evaluate the effectiveness of the proposed PDG algorithm. The effects of the sampling period and the prediction errors on landing errors are studied in the numerical simulations. The fuel consumption performances of the proposed PDG algorithm and the Apollo guidance algorithm are also studied and compared. The simulation results show that the less fuel consumption is obtained with the proposed PDG algorithm. Monte Carlo simulation verifies the high landing precision of the proposed PDG algorithm. [ABSTRACT FROM AUTHOR]

Abstract: In this paper, we design and analyze a Newton-like blind equalization algorithm for the APSK system. Specifically, we exploit the principle of minimum entropy deconvolution and derive a blind equalization cost function for APSK signals and optimize it using Newton׳s method. We study and evaluate the steady-state excess mean square error performance of the proposed algorithm using the concept of energy conservation. Numerical results depict a significant performance enhancement for the proposed scheme over well established blind equalization algorithms. Further, the analytical excess mean square error of the proposed algorithm is verified with computer simulations and is found to be in good conformation. [Copyright &y& Elsevier]

Abstract: Rapid advances in sensor technology and wireless communications have led to the development of wireless sensor networks (WSNs). However, the sensor nodes in WSNs have a finite lifetime since it is often impractical, or even impossible, to recharge their batteries once they have been deployed. When the energy of a sensor node has been fully consumed, it can play no further role within the WSNs. In an attempt to prolong the lifetime of WSNs, various schemes have been proposed. This paper proposed a lifetime-extension under uniform distribution (LEUD) scheme which not only prolongs the lifetime of WSNs, but also optimizes its performance by maximizing the total number of active regions within the networks. To evaluate the effectiveness of our scheme, we chose three uniform distribution algorithms with LEUD to analyze and compared the performance of our scheme. Numerical simulations are performed which demonstrate that when the deployed sensor nodes have an equal initial energy and are distributed uniformly within the networks, LEUD provides an improved networks performance. [Copyright &y& Elsevier]

Abstract: In this paper, new integration methods for stiff ordinary differential equations (ODEs) are developed. Following the idea of quantization-based integration (QBI), i.e., replacing the time discretization by state quantization, the proposed algorithms generalize the idea of linearly implicit algorithms. Also, the implementation of the new algorithms in a DEVS simulation tool is discussed. The efficiency of these new methods is verified by comparing their performance in the simulation of two benchmark problems with that of other numerical stiff ODE solvers. In particular, the advantages of these new algorithms for the simulation of electronic circuits are demonstrated. [Copyright &y& Elsevier]

Abstract: In a numerical simulation using the finite element method, the mesh has to be fine enough to guarantee the accuracy of the solution. However, a uniformly fine mesh will usually imply a more expensive computation. Mesh adaptation offers an effective compromise, combining a fine mesh with a low computational cost. The h-refinement consists in sub-dividing some meshes, where necessary due to numerical analysis. Some difficulties occur at the interface between two zones with different levels of refinement, if a conformal mesh is required. To maintain the compatibility, the refinement is performed by specific operations. These operations are simple, using triangles or tetrahedra, but are much more complex with a hexahedral mesh. This paper deals with conformal mesh refinement with hexahedra. A new method, which implies the use of tetrahedra and pyramids to connect the zones of different levels of refinement, is proposed. The details of the algorithm used to generate those meshes are presented. This new technique allows h-refinement to be used in numerical simulations based on hexahedra with a conformal finite element method. Finally, some numerical applications show the relevance of this technique in mechanical computation. [Copyright &y& Elsevier]

Abstract: We revisit in this paper the theory of axisymmetric vortex rings in an ideal fluid. The boundary separating the vortex ring from the external (potential) flow is assumed of elliptic shape. For a given distribution of vorticity in the vortex core, we theoretically put into evidence the critical parameter for the existence of non-trivial solutions, thus confirming the numerical observation of Durst et al. [ZAMP 32 (1981) 156]. A sharp estimation of the critical threshold is analytically derived. Theoretical predictions are confirmed by numerical simulations using finite elements. A new numerical algorithm is presented and shown to display better performances compared to previous published algorithms using finite differences. The convergence of the iterative algorithm is proved using the theory of elliptic partial differential equations with discontinuous nonlinearities. [Copyright &y& Elsevier]

Abstract: In this paper, we present a max-plus algebraic modeling and control approach for cyclically operated high-throughput screening plants. In previous work an algorithm has been developed to determine the globally optimal solution of the cyclic scheduling problem. The obtained optimal schedule is modeled in a max-plus algebraic framework. The max-plus algebraic model can then be used to generate appropriate control actions to handle unexpected deviations from the predetermined cyclic operation during runtime. [Copyright &y& Elsevier]

Abstract: Feature statistics normalization in the cepstral domain is one of the most performing approaches for robust automaticspeech and speaker recognition in noisy acoustic scenarios: feature coefficients are normalized by using suitable linear or nonlinear transformations in order to match the noisy speech statistics to the clean speech one. Histogram equalization (HEQ) belongs to such a category of algorithms and has proved to be effective on purpose and therefore taken here as reference. In this paper the presence of multi-channel acoustic channels is used to enhance the statistics modeling capabilities of the HEQ algorithm, by exploiting the availability of multiple noisy speech occurrences, with the aim of maximizing the effectiveness of the cepstra normalization process. Computer simulations based on the Aurora 2 database in speech and speaker recognition scenarios have shown that a significant recognition improvement with respect to the single-channel counterpart and other multi-channel techniques can be achieved confirming the effectiveness of the idea. The proposed algorithmic configuration has also been combined with the kernel estimation technique in order to further improve the speech recognition performances. [Copyright &y& Elsevier]

Abstract: The accuracy of the nonlinear one-dimensional (1-D) equations of pressure and flow wave propagation in Voigt-type visco-elastic arteries was tested against measurements in a well-defined experimental 1:1 replica of the 37 largest conduit arteries in the human systemic circulation. The parameters required by the numerical algorithm were directly measured in the in vitro setup and no data fitting was involved. The inclusion of wall visco-elasticity in the numerical model reduced the underdamped high-frequency oscillations obtained using a purely elastic tube law, especially in peripheral vessels, which was previously reported in this paper [Matthys et al., 2007. Pulse wave propagation in a model human arterial network: Assessment of 1-D numerical simulations against in vitro measurements. J. Biomech. 40, 3476–3486]. In comparison to the purely elastic model, visco-elasticity significantly reduced the average relative root-mean-square errors between numerical and experimental waveforms over the 70 locations measured in the in vitro model: from 3.0% to 2.5% for pressure and from 15.7% to 10.8% for the flow rate. In the frequency domain, average relative errors between numerical and experimental amplitudes from the 5th to the 20th harmonic decreased from 0.7% to 0.5% for pressure and from 7.0% to 3.3% for the flow rate. These results provide additional support for the use of 1-D reduced modelling to accurately simulate clinically relevant problems at a reasonable computational cost. [Copyright &y& Elsevier]

Abstract: This paper describes a numerical procedure for the blank shape design of thin metallic parts obtained by stamping. The objective is to determine the initial blank shape knowing the geometry of the desired 3D CAD part. The numerical procedure consists of two stages: At first, an estimation of the initial blank shape is given using the one step inverse approach (IA). Then, update of the blank shape is continued by iterations combining optimization algorithms and finite element analysis (FEA). The numerical procedure for the blank shape design is tested in the case of an industrial stamping process where the part is formed using a manual press without blank-holder. The proposed numerical procedure can provide very quickly the optimal blank shape in a few iterations. [Copyright &y& Elsevier]

Abstract: Computer modeling of radiation deep penetration problems is historically based on the discrete ordinates (S N) formulation. For efficiency reasons, besides accuracy, coarse-mesh spatial discretization is desirable. The spectral Green''s function (SGF) methods form a class of accurate coarse-mesh numerical methods as they use polynomial approximations only for the node-edge transverse leakage terms; the scattering source terms are treated analytically in the numerical algorithm. Therefore, algebraic work and the computational algorithms of the spectral nodal methods are rather complicated. To alleviate this negative feature, we offer in this paper a composite spatial grid SGF nodal method for the numerical solution of one-speed deep penetration S N problems with isotropic scattering in X,Y geometry. This method uses a rectangular coarse spatial grid, that is coincident with the material region distribution within the shielding structure. We first transverse integrate the S N equations separately in the x- and y-coordinate directions inside each material region, and then we introduce flat approximations for the transverse leakage terms. Furthermore, we use a fine spatial grid to discretize each set of “one-dimensional”S N nodal equations. As the spatial directions are coupled by the transverse leakage terms, we use an explicit alternate direction technique to converge the numerical solution. In order to verify the offered method''s accuracy, we present numerical results for typical model problems. Moreover, we compare the computing performance of this method with the conventional SGF-constant nodal method. [Copyright &y& Elsevier]

Abstract: We introduce new criteria for model discrimination and use these and existing criteria to evaluate standard orthogonal designs. We show that the capability of orthogonal designs for model discrimination is surprisingly varied. In fact, for specified sample sizes, number of factors, and model spaces, many orthogonal designs are not model discriminating by the definition given in this paper, while others in the same class of orthogonal designs are. We also use these criteria to construct optimal two-level model-discriminating designs for screening experiments. The efficacy of these designs is studied, both in terms of estimation efficiency and discrimination success. Simulation studies indicate that the constructed designs result in substantively higher likelihoods of identifying the correct model. [Copyright &y& Elsevier]

Abstract: Mid-frequency response analysis often faces computational difficulties when a conventional modal approach is used for a finite element linear system. In this paper, the computational burden is relieved by frequency sweep algorithm or mode acceleration method for a reduced-order system constructed by algebraic substructuring, a variant of model order reduction. The two methods are compared with the help of numerical experiments and their computational complexity. As demonstrated by the finite element simulations, in which proportional damping is assumed, of a turbo-prop aircraft and a ring resonator, the frequency sweep algorithm for reduced-order systems shows the best performance among all considered numerical solutions, including the conventional approach. [Copyright &y& Elsevier]

Abstract: Phase control may substantially increase the power absorption in point-absorber wave energy converters. This study deals with validation of dynamic models and latching control algorithms for an oscillating water column (OWC) inside a fixed vertical tube of small circular cross-section by small-scale testing. The paper describes experimental and numerical results for the system''s dynamics, using simple and practical latching control techniques that do not require the prediction of waves or wave forces, and which will be relevant to any type of point-absorbing devices. In the experimental set-up, the upper end of the tube was equipped with an outlet duct and a shut-off valve, which could be controlled to give a latching of the inner free surface movement. The pressure drop through the open valve is used as a simplified measure of the energy extraction. The control was realized by using the real-time measurement signals for the inner and outer surface displacement. A mathematical model of the system was established and applied in numerical simulation. In the case the OWC''s diameter is much smaller than the wavelength and the wave amplitude much smaller than the draft, the free surface movement inside the tube can be described as an oscillating weightless piston. For this hydrodynamic problem an analytical solution is known. In addition, the mathematical model includes the effects of viscous flow losses, the air compressibility inside the chamber and the pressure drop across the valve. Experimental results were used to calibrate some of the model parameters, and the total model was formulated as a coupled system of six non-linear, first-order differential equations. Time-domain integration was used to simulate the system in order to test the control strategies and compare with experimental results. [Copyright &y& Elsevier]

In this paper, we present a new approach of-spline curve fitting to a set of ordered points, which is motivated by an insight that properly selected points called dominant points can play an important role in producing better curve approximation. The proposed approach takes four main steps: parameterization, dominant point selection, knot placement, and least-squares minimization. The approach is substantially different from the conventional approaches in knot placement and dominant point selection. In the knot placement, the knots are determined by averaging the parameter values of the dominant points, which basically transforms-spline curve fitting into the problem of dominant point selection. We describe the properties of the knot placement including the property of local modification useful for adaptive curve refinement. We also present an algorithm for dominant point selection based on the adaptive refinement paradigm. The approach adaptively refines a-spline curve by selecting fewer dominant points at flat regions but more at complex regions. For the same number of control points, the proposed approach can generate a-spline curve with less deviation than the conventional approaches. When adopted in error-bounded curve approximation, it can generate a-spline curve with far fewer control points while satisfying the desired shape fidelity. Some experimental results demonstrate its usefulness and quality. [Copyright &y& Elsevier]

Modeling of tissue deformation is of great importance to virtual reality (VR)-based medical simulations. Considerable effort has been dedicated to the development of interactively deformable virtual tissues. In this paper, an efficient and scalable deformable model is presented for virtual-reality-based medical applications. It considers deformation as a localized force transmittal process which is governed by algorithms based on breadth-first search (BFS). The computational speed is scalable to facilitate real-time interaction by adjusting the penetration depth. Simulated annealing (SA) algorithms are developed to optimize the model parameters by using the reference data generated with the linear static finite element method (FEM). The mechanical behavior and timing performance of the model have been evaluated. The model has been applied to simulate the typical behavior of living tissues and anisotropic materials. Integration with a haptic device has also been achieved on a generic personal computer (PC) platform. The proposed technique provides a feasible solution for VR-based medical simulations and has the potential for multi-user collaborative work in virtual environment. [Copyright &y& Elsevier]