Haytham A. Ali^1,2,*, 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 >

Qiuqin Yang¹, Linfang Li¹, Ming-Xing Luo^1,*, Xiaojun Wang²

CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 1863-1877, 2022, DOI:10.32604/cmc.2022.027120

Abstract In real communication systems, secure and low-energy transmit scheme is very important. So far, most of schemes focus on secure transmit in special scenarios. In this paper, our goal is to propose a secure protocol in wireless networks involved various factors including artificial noise (AN), the imperfect receiver and imperfect channel state information (CSI) of eavesdropper, weight of beamforming (BF) vector, cooperative jammers (CJ), multiple receivers, and multiple eavesdroppers, and the analysis shows that the protocol can reduce the transmission power, and at the same time the safe reachability rate is greater than our pre-defined value, and the analysis results… More >

Wujie Hu¹, Gonglin Yuan^{1, *}, Hongtruong Pham²

CMC-Computers, Materials & Continua, Vol.62, No.2, pp. 787-800, 2020, DOI:10.32604/cmc.2020.02993

Abstract It is well known that Newton and quasi-Newton algorithms are effective to small and medium scale smooth problems because they take full use of corresponding gradient function’s information but fail to solve nonsmooth problems. The perfect algorithm stems from concept of ‘bundle’ successfully addresses both smooth and nonsmooth complex problems, but it is regrettable that it is merely effective to small and medium optimization models since it needs to store and update relevant information of parameter’s bundle. The conjugate gradient algorithm is effective both large-scale smooth and nonsmooth optimization model since its simplicity that utilizes objective function’s information and the… More >

S. Tangaramvong¹, F. Tin-Loi¹

CMES-Computer Modeling in Engineering & Sciences, Vol.42, No.3, pp. 217-256, 2009, DOI:10.3970/cmes.2009.042.217

Abstract Classical limit analysis is extended to include the effects of 2nd-order geometric and material nonlinearities, as well as the inclusion of limited ductility constraints. For the class of frame structures considered, the material constitutive model adopted can simultaneously accommodate the effects of combined axial and flexural force as well as local softening instability through the use of piecewise linearized yield surfaces. The main feature of the approach developed is to compute, in a single step, an upper bound to the maximum load. Corresponding displacements and stresses can be obtained as a by-product of the analysis. The problem is formulated as… More >

Sifan Long¹, Ming Zhao^2,*, Xinfu He³

CMC-Computers, Materials & Continua, Vol.58, No.3, pp. 727-760, 2019, DOI:10.32604/cmc.2019.04454

Abstract With the development of society and the exhaustion of fossil energy, researcher need to identify new alternative energy sources. Nuclear energy is a very good choice, but the key to the successful application of nuclear technology is determined primarily by the behavior of nuclear materials in reactors. Therefore, we studied the radiation performance of the fusion material reduced activation ferritic/martensitic (RAFM) steel. The main novelty of this paper are the statistical analysis of RAFM steel data sets through related statistical analysis and the formula derivation of the gradient descent method (GDM) which combines the gradient descent search strategy of the… More >