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  • Open Access


    Toward Improved Accuracy in Quasi-Static Elastography Using Deep Learning

    Yue Mei1,2,3, Jianwei Deng1,2, Dongmei Zhao1,2, Changjiang Xiao1,2, Tianhang Wang4, Li Dong5, Xuefeng Zhu1,6,*

    CMES-Computer Modeling in Engineering & Sciences, Vol.139, No.1, pp. 911-935, 2024, DOI:10.32604/cmes.2023.043810

    Abstract Elastography is a non-invasive medical imaging technique to map the spatial variation of elastic properties of soft tissues. The quality of reconstruction results in elastography is highly sensitive to the noise induced by imaging measurements and processing. To address this issue, we propose a deep learning (DL) model based on conditional Generative Adversarial Networks (cGANs) to improve the quality of nonhomogeneous shear modulus reconstruction. To train this model, we generated a synthetic displacement field with finite element simulation under known nonhomogeneous shear modulus distribution. Both the simulated and experimental displacement fields are used to validate the proposed method. The reconstructed… More >

  • Open Access


    A Time-Varying Parameter Estimation Method for Physiological Models Based on Physical Information Neural Networks

    Jiepeng Yao1,2, Zhanjia Peng1,2, Jingjing Liu1,2, Chengxiao Fan1,2, Zhongyi Wang1,2,3, Lan Huang1,2,*

    CMES-Computer Modeling in Engineering & Sciences, Vol.137, No.3, pp. 2243-2265, 2023, DOI:10.32604/cmes.2023.028101

    Abstract In the establishment of differential equations, the determination of time-varying parameters is a difficult problem, especially for equations related to life activities. Thus, we propose a new framework named BioE-PINN based on a physical information neural network that successfully obtains the time-varying parameters of differential equations. In the proposed framework, the learnable factors and scale parameters are used to implement adaptive activation functions, and hard constraints and loss function weights are skillfully added to the neural network output to speed up the training convergence and improve the accuracy of physical information neural networks. In this paper, taking the electrophysiological differential… More >

  • Open Access


    Thermal Properties Reconstruction and Temperature Fields in Asphalt Pavements: Inverse Problem and Optimisation Algorithms

    Zhonghai Jiang1, Qian Wang1, Liangbing Zhou2,*, Chun Xiao3

    FDMP-Fluid Dynamics & Materials Processing, Vol.19, No.6, pp. 1693-1708, 2023, DOI:10.32604/fdmp.2023.025270

    Abstract A two-layer implicit difference scheme is employed in the present study to determine the temperature distribution in an asphalt pavement. The calculation of each layer only needs four iterations to achieve convergence. Furthermore, in order to improve the calculation accuracy a swarm intelligence optimization algorithm is also exploited to inversely analyze the laws by which the thermal physical parameters of the asphalt pavement materials change with temperature. Using the basic cuckoo and the gray wolf algorithms, an adaptive hybrid optimization algorithm is obtained and used to determine the relationship between the thermal diffusivity of two types of asphalt pavement materials… More >

  • Open Access


    Binary Tomography Reconstruction with Limited-Data by a Convex Level-Set Method

    Haytham A. Ali1,2,*, Hiroyuki Kudo1

    CMC-Computers, Materials & Continua, Vol.73, No.2, pp. 3741-3756, 2022, DOI:10.32604/cmc.2022.029394

    Abstract This paper proposes a new level-set-based shape recovery approach that can be applied to a wide range of binary tomography reconstructions. In this technique, we derive generic evolution equations for shape reconstruction in terms of the underlying level-set parameters. We show that using the appropriate basis function to parameterize the level-set function results in an optimization problem with a small number of parameters, which overcomes many of the problems associated with the traditional level-set approach. More concretely, in this paper, we use Gaussian functions as a basis function placed at sparse grid points to represent the parametric level-set function and… More >

  • Open Access


    A Meshless Method for Retrieving Nonlinear Large External Forces on Euler-Bernoulli Beams

    Chih-Wen Chang*

    CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 433-451, 2022, DOI:10.32604/cmc.2022.027021

    Abstract We retrieve unknown nonlinear large space-time dependent forces burdened with the vibrating nonlinear Euler-Bernoulli beams under varied boundary data, comprising two-end fixed, cantilevered, clamped-hinged, and simply supported conditions in this study. Even though some researchers used several schemes to overcome these forward problems of Euler-Bernoulli beams; however, an effective numerical algorithm to solve these inverse problems is still not available. We cope with the homogeneous boundary conditions, initial data, and final time datum for each type of nonlinear beam by employing a variety of boundary shape functions. The unknown nonlinear large external force can be recuperated via back-substitution of the… More >

  • Open Access


    A Novel Method for the Reconstruction of Road Profiles from Measured Vehicle Responses Based on the Kalman Filter Method

    Jianghui Zhu1,3, Xiaotong Chang2, Xueli Zhang2, Yutai Su2, Xu Long2,*

    CMES-Computer Modeling in Engineering & Sciences, Vol.130, No.3, pp. 1719-1735, 2022, DOI:10.32604/cmes.2022.019140

    Abstract The estimation of the disturbance input acting on a vehicle from its given responses is an inverse problem. To overcome some of the issues related to ill-posed inverse problems, this work proposes a method of reconstructing the road roughness based on the Kalman filter method. A half-car model that considers both the vehicle and equipment is established, and the joint input-state estimation method is used to identify the road profile. The capabilities of this methodology in the presence of noise are numerically demonstrated. Moreover, to reduce the influence of the driving speed on the estimation results, a method of choosing… More >

  • Open Access


    Solvability of the Nonlocal Inverse Parabolic Problem and Numerical Results

    M. J. Huntul1,*, Taki-Eddine Oussaeif2

    Computer Systems Science and Engineering, Vol.40, No.3, pp. 1109-1126, 2022, DOI:10.32604/csse.2022.020175

    Abstract In this paper, we consider the unique solvability of the inverse problem of determining the right-hand side of a parabolic equation whose leading coefficient depends on time variable under nonlocal integral overdetermination condition. We obtain sufficient conditions for the unique solvability of the inverse problem. The existence and uniqueness of the solution of the inverse parabolic problem upon the data are established using the fixed point theorem. This inverse problem appears extensively in the modelling of various phenomena in engineering and physics. For example, seismology, medicine, fusion welding, continuous casting, metallurgy, aircraft, oil and gas production during drilling and operation… More >

  • Open Access


    The Definition and Numerical Method of Final Value Problem and Arbitrary Value Problem

    Shixiong Wang1,∗, Jianhua He1, Chen Wang2, Xitong Li1

    Computer Systems Science and Engineering, Vol.33, No.5, pp. 379-387, 2018, DOI:10.32604/csse.2018.33.379

    Abstract Many Engineering Problems could be mathematically described by FinalValue Problem, which is the inverse problem of InitialValue Problem. Accordingly, the paper studies the final value problem in the field of ODE problems and analyses the differences and relations between initial and final value problems. The more general new concept of the endpoints-value problem which could describe both initial and final problems is proposed. Further, we extend the concept into inner-interval value problem and arbitrary value problem and point out that both endpoints-value problem and inner-interval value problem are special forms of arbitrary value problem. Particularly, the existence and uniqueness of… More >

  • Open Access


    Determination of Time-Dependent Coefficients for a Weakly Degenerate Heat Equation

    M. J. Huntul1, D. Lesnic2, *

    CMES-Computer Modeling in Engineering & Sciences, Vol.123, No.2, pp. 475-494, 2020, DOI:10.32604/cmes.2020.08791

    Abstract In this paper, we consider solving numerically for the first time inverse problems of determining the time-dependent thermal diffusivity coefficient for a weakly degenerate heat equation, which vanishes at the initial moment of time, and/or the convection coefficient along with the temperature for a one-dimensional parabolic equation, from some additional information about the process (the so-called over-determination conditions). Although uniquely solvable these inverse problems are still ill-posed since small changes in the input data can result in enormous changes in the output solution. The finite difference method with the Crank-Nicolson scheme combined with the nonlinear Tikhonov regularization are employed. The… More >

  • Open Access


    A Geometrical Approach to Compute Upper Limb Joint Stiffness

    Davide Piovesan1, *, Roberto Bortoletto2

    CMES-Computer Modeling in Engineering & Sciences, Vol.123, No.1, pp. 23-47, 2020, DOI:10.32604/cmes.2020.09231

    Abstract Exoskeletons are designed to control the forces exerted during the physical coupling between the human and the machine. Since the human is an active system, the control of an exoskeleton requires coordinated action between the machine and the load so to obtain a reciprocal adaptation. Humans in the control loop can be modeled as active mechanical loads whose stiffness is continuously changing. The direct measurement of human stiffness is difficult to obtain in real-time, thus posing a significant limitation to the design of wearable robotics controllers. Electromyographic (EMG) recordings can provide an indirect estimation of human muscle force and stiffness,… More >

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