Numerical algorithm for triphasic model of charged and hydrated soft tissues

 This paper devises an efficient numerical algorithm for solving a two-dimensional triphasic model of charged and hydrated soft tissue by using the radial basis functions. The proposed numerical method is applied directly as a simple meshless collocation algorithm to approximate the solution of the governing system of continuity, momentum, and constitutive equations for the triphasic model. Since there is no requirement on meshing, the method can easily be applied to solve problems under complicated geometry. For verification, numerical simulations of stress, strain, and fluid flow patterns for a plane strain and an axisymmetric mechano-electrochemical coupling model with real synovial joint are given respectively. Classical domain decomposition technique is also combined successfully with the proposed method for solving large scale problems with numerical verification given in solving the axisymmetric case. Received 20 November 2001 / Accepted 28 November 2001     

Filter and Embedded Feature Selection Methods to Meet Big Data Visualization Challenges

This study focuses on meeting the challenges of big data visualization by using of data reduction methods based the feature selection methods. To reduce the volume of big data and minimize model training time (Tt) while maintaining data quality. We contributed to meeting the challenges of big data visualization using the embedded method based “Select from model (SFM)” method by using “Random forest Importance algorithm (RFI)” and comparing it with the filter method by using “Select percentile (SP)” method based chi square “Chi2” tool for selecting the most important features, which are then fed into a classification process using the logistic regression (LR) algorithm and the k-nearest neighbor (KNN) algorithm. Thus, the classification accuracy (AC) performance of LR is also compared to the KNN approach in python on eight data sets to see which method produces the best rating when feature selection methods are applied. Consequently, the study concluded that the feature selection methods have a significant impact on the analysis and visualization of the data after removing the repetitive data and the data that do not affect the goal. After making several comparisons, the study suggests (SFMLR) using SFM based on RFI algorithm for feature selection, with LR algorithm for data classify. The proposal proved its efficacy by comparing its results with recent literature.     

Estimating mixtures of truncated exponentials in hybrid bayesian networks

The MTE (Mixture of Truncated Exponentials) model allows to deal with Bayesian networks containing discrete and continuous variables simultaneously. This model offers an alternative to discretisation, since standard algorithms to compute the posterior probabilities in the network, in principle designed for discrete variables, can be directly applied over MTE models. In this paper, we study the problem of estimating these models from data. We propose an iterative algorithm based on least squares approximation. The performance of the algorithm is tested both with artificial and actual data. This work has been supported by the Spanish Ministry of Education and Science and the European Funds for Regional Development, through projects TIC2001-2973-C05-01,02 and by UAL-CAJAMAR, project E-729/01     

An efficient multi‐layer planar 3D fracture growth algorithm using a fixed mesh approach

We present a planar three‐dimensional (3D) fracture growth simulator, based on a displacement discontinuity (DD) method for multi‐layer elasticity problems. The method uses a fixed mesh approach, with rectangular panel elements to represent the planar fracture surface. Special fracture tip logic is included that allows a tip element to be partially fractured in the tip region. The fracture perimeter is modelled in a piece‐wise linear manner. The algorithm can model any number of interacting fractures that are restricted to lie on a single planar surface, located orthogonal to any number of parallel layers. The multiple layers are treated using a Fourier transform (FT) approach that provides a numerical Green's function for the DD scheme. The layers are assumed to be fully bonded together. Any fracture growth rule can be postulated for the algorithm. We demonstrate this approach on a number of test problems to verify its accuracy and efficiency, before showing some more general results. Copyright © 2001 John Wiley & Sons, Ltd.     

Extracting surface impedance model parameters of a high-temperature superconductor from experimental characteristics of a microstrip resonator

We describe a method for extracting the model parameters of a high-temperature superconductor (HTSC) film from experimental resonance characteristics of a microstrip resonator. The method is based on a correct phenomenological model of the surface impedance of an HTSC film and the exact calculation of the microstrip resonator characteristics. The procedure of extracting the model parameters from experimental data is realized by using a genetic algorithm. Based on the models described, a special program implementing this mathematical algorithm was written, which allows the HTSC model parameters to be determined from experimental data.     

Parallelization in time for thermo‐viscoplastic problems in extrusion of aluminium

The ParaReal algorithm (C.R. Acad. Sci. Paris 2001; 332 :1–6) is a parallel approach for solving numerically systems of ordinary differential equations by exploiting parallelism across the steps of the numerical integrator. The method performs well for dissipative problems and problems of fluid–structure interaction (Int. J. Numer. Methods Engng 2003; 58 :1397–1434). We consider here a convergence analysis for the method and we report the performance achieved from the parallelization of a Stokes/Navier–Stokes code via the ParaReal algorithm. Copyright © 2009 John Wiley & Sons, Ltd.     

Modelling crack growth by level sets in the extended finite element method

An algorithm which couples the level set method (LSM) with the extended finite element method (X‐FEM) to model crack growth is described. The level set method is used to represent the crack location, including the location of crack tips. The extended finite element method is used to compute the stress and displacement fields necessary for determining the rate of crack growth. This combined method requires no remeshing as the crack progresses, making the algorithm very efficient. The combination of these methods has a tremendous potential for a wide range of applications. Numerical examples are presented to demonstrate the accuracy of the combined methods. Copyright © 2001 John Wiley & Sons, Ltd.     

An implicit algorithm using explicit correctors for the kinematic hardening model with multiple back stresses

This paper presents an efficient mathematical algorithm for a class of non‐linear kinematic hardening models with multiple back stresses, as an extension of the implicit integration algorithm for a single back stress hardening model. Explicit formulations for general three‐dimensional stress states as well as plane stress and plane strain are given. The new formulation is implemented in a general‐purpose finite element code, ABAQUS, and is verified by comparison with the existing formulation for the single back‐stress constitutive model. Comparison is also made with the experimental results obtained from a plate containing a circular hole subjected to cyclic loading, demonstrating the validity of new method. Copyright © 2001 John Wiley & Sons, Ltd.     

Semi-empirical correction algorithm for AC-9 measurements in a coccolithophore bloom

Values for the coefficients of absorption (a) and attenuation (c) obtained from AC-9 measurements in coccolithophore blooms do not provide satisfactory inputs for radiance transfer models. We have therefore modified the standard AC-9 scattering correction algorithm by including an extra term, F(lambda, lambda(r)), which allows for possible wavelength dependence in the scattering phase function. We estimated the magnitude of F(lambda, lambda(r)), which is unity in the standard algorithm, by adjusting the absorption and scattering values in Hydrolight radiance transfer calculations until the depth profiles of downward irradiance (E(d)) and upward radiance (L(u)) matched those measured in situ. The modified algorithm was tested with data from a phytoplankton bloom dominated by the coccolithophore Emiliania huxleyi, which occurred in the western English Channel in May 2001. In this paper, we only have sufficient data to adequately constrain the radiance transfer model in one wave band centered on 488 ma. A single value of F(lambda, lambda(r)) = 1.4 was found to produce satisfactory agreement between modeled and observed profiles at four widely spaced stations within the bloom. Measurements of the ratio of backscattering (b(b)) to total scattering (b) showed significant wavelength dependence at these stations.     

Dynamic survival analysis for non-Markovian epidemic models

We present a new method for analysing stochastic epidemic models under minimal assumptions. The method, dubbed dynamic survival analysis (DSA), is based on a simple yet powerful observation, namely that population-level mean-field trajectories described by a system of partial differential equations may also approximate individual-level times of infection and recovery. This idea gives rise to a certain non-Markovian agent-based model and provides an agent-level likelihood function for a random sample of infection and/or recovery times. Extensive numerical analyses on both synthetic and real epidemic data from foot-and-mouth disease in the UK (2001) and COVID-19 in India (2020) show good accuracy and confirm the method’s versatility in likelihood-based parameter estimation. The accompanying software package gives prospective users a practical tool for modelling, analysing and interpreting epidemic data with the help of the DSA approach.     

Nonlinear quantum optical computing via measurement

Abstract

We show how the measurement induced model of quantum computation proposed by Raussendorf and Briegel (2001, Phys. Rev. Letts., 86, 5188) can be adapted to a nonlinear optical interaction. This optical implementation requires a Kerr nonlinearity, a single photon source, a single photon detector and fast feed forward. Although nondeterministic optical quantum information proposals such as that suggested by KLM (2001, Nature, 409, 46) do not require a Kerr nonlinearity they do require complex reconfigurable optical networks. The proposal in this paper has the benefit of a single static optical layout with fixed device parameters, where the algorithm is defined by the final measurement procedure.     

Point interpolation collocation method for the solution of partial differential equations

This paper presents a truly meshless method for solving partial differential equations based on point interpolation collocation method (PICM). This method is different from the previous Galerkin-based point interpolation method (PIM) investigated in the papers [G.R. Liu, (2002), mesh free methods, Moving beyond the Finite Element Method, CRC Press. G.R. Liu, Y.T. Gu, A point interpolation method for two-dimension solids, Int J Numer Methods Eng, 50, 937–951, 2001. G.R. Liu, Y.T. Gu, A matrix triangularization algorithm for point interpolation method, in Proceedings Asia-Pacific Vibration Conference, Bangchun Weng Ed., November, Hangzhou, People's Republic of China, 2001a, 1151–1154. 1–3.], because it is based on collocation scheme. In the paper, polynomial basis functions have been used. In addition, Hermite-type interpolations called as inconsistent PIM has been adopted to solve PDEs with Neumann boundary conditions so that the accuracy of the solution can be improved. Several examples were numerically analysed. These examples were applied to solve 1D and 2D partial differential equations including linear and non-linear in order to test the accuracy and efficiency of the presented method based on polynomial basis functions. The h-convergence rates were computed for the PICM based on different model of regular and irregular nodes. The results obtained by polynomial PICM show the presented schemes possess a considerable perfect stability and good numerical accuracy even for scattered models while matrix triangularization algorithm (MTA) adopted in the computed procedure.     

Reflectance recovery for airborne sensor images of 3D scenes

An airborne sensor measures the radiance spectrum, which is dependent on the spectral reflectance of the ground material, the orientation of the material surface, and the atmospheric and illumination conditions. We present an algorithm to estimate the surface spectral reflectance, given the sensor radiance spectrum corresponding to a single pixel. The algorithm uses a nonlinear physics-based image formation model. A low-dimensional linear subspace model is used for the reflectance spectra. The solar radiance, sky radiance, and path-scattered radiance are dependent on the environmental conditions and viewing geometry, and this interdependence is considered by using a coupled-subspace model for these spectra. The algorithm uses the Levenberg-Marquardt method to estimate the subspace model parameters. We have applied the algorithm to a large set of synthetic and real data.     

Bayesian Nonmetric Successive Categories Multidimensional Scaling

A Bayesian nonmetric successive categories multidimensional scaling (MDS) method is proposed. The proposed method can be seen as a Bayesian alternative to the maximum likelihood multidimensional successive scaling method proposed by Takane (1981), or as a nonmetric extension of Bayesian metric MDS by Oh and Raftery (2001). The model has a graded-response type measurement model part and a latent metric MDS part. All the parameters are jointly estimated using a Markov chain Monte Carlo (MCMC) estimation technique. Moreover, WinBUGS/OpenBUGS code for the proposed methodology is also given to aid applied researchers. The proposed method is illustrated through the analysis of empirical two-mode three-way similarity data.

     

基于粒子群算法的6自由度机械臂动力学模型参数辨识

提出了基于粒子群优化(PSO)算法的工业机器人动力学参数辨识方法。首先利用改进的牛顿-欧拉方法,建立考虑关节摩擦的机械臂线性动力学模型,然后引入PSO算法,建立基于PSO算法的估计未知动力学参数的算法,最后以UR工业机器人为实验对象,通过设计激励轨迹,激励工业机器人关节运动,并对关节运动参数进行采样,实现UR工业机器人的动力学参数估计,并根据力矩预测精度验证动力学模型。实验证明了所提出算法辨识工业机器人动力学模型参数的准确性和有效性。     

Estimating parameters of a stochastic cell invasion model with fluorescent cell cycle labelling using approximate Bayesian computation

We develop a parameter estimation method based on approximate Bayesian computation (ABC) for a stochastic cell invasion model using fluorescent cell cycle labelling with proliferation, migration and crowding effects. Previously, inference has been performed on a deterministic version of the model fitted to cell density data, and not all parameters were identifiable. Considering the stochastic model allows us to harness more features of experimental data, including cell trajectories and cell count data, which we show overcomes the parameter identifiability problem. We demonstrate that, while difficult to collect, cell trajectory data can provide more information about the parameters of the cell invasion model. To handle the intractability of the likelihood function of the stochastic model, we use an efficient ABC algorithm based on sequential Monte Carlo. Rcpp and MATLAB implementations of the simulation model and ABC algorithm used in this study are available at https://github.com/michaelcarr-stats/FUCCI.     

Estimation of dispersion effects from robust design experiments with censored response data

A method is presented for estimating dispersion effects (DE) from robust design experiments (RDE) with control and noise factors involving censored response data. This method is developed to discern the significance of DE from RDE and the method aims at analyzing a multi‐level/multi‐factor experiment. This method imputes censored data by a regression based imputation technique, assuming that the distribution of lifetime before and after censoring is identical. This method also models the residuals to identify important DE, assuming that the distribution of the observed random variables of the model is the same with or without censored response data. Finally, the method is demonstrated through a numerical example. Copyright © 2001 John Wiley & Sons, Ltd.     

Exact analysis of a discrete material three-station one-buffer merge system with unreliable machines

In this paper, a model of a discrete material flow line consisting of three unreliable machines and one buffer of limited capacity is analysed. A similar system, but with continuous flow of material was examined by Helber and Mehrtens (2001) and Tan (2001). In our system it is assumed that the buffer has two immediate preceding machines, performing the same operations and one immediate succeeding machine that receives material from the buffer. For the case where the buffer reaches its own capacity, one of the two preceding machines has priority over the other to dispose its processed part into the buffer. Processing times are assumed to be deterministic and identical for all machines and are taken as the time unit. Geometrically distributed operation dependent failures at the machines are assumed. All possible transition equations for the examined model are derived and a recursive algorithm that generates the transition matrix for any value N of the storage level is developed. Once the transition matrix is known the performance measures of the model under consideration can be easily evaluated. This model may be used as a building block in a decomposition method to evaluate large production systems with split/merge operations (for example, flow lines with quality inspections and rework loops).     

Density implications of shift compensation postprocessing in holographic storage systems

We investigate the effect of data page misregistration, and its subsequent correction in postprocessing, on the storage density of holographic data storage systems. A numerical simulation is used to obtain the bit-error rate as a function of hologram aperture, page misregistration, pixel fill factors, and Gaussian additive intensity noise. Postprocessing of simulated data pages is performed by a nonlinear pixel shift compensation algorithm [Opt. Lett. 26, 542 (2001)]. The performance of this algorithm is analyzed in the presence of noise by determining the achievable areal density. The impact of inaccurate measurements of page misregistration is also investigated. Results show that the shift-compensation algorithm can provide almost complete immunity to page misregistration, although at some penalty to the baseline areal density offered by a system with zero tolerance to misalignment.