Chein-Shan Liu^1,2

CMC-Computers, Materials & Continua, Vol.5, No.1, pp. 31-42, 2007, DOI:10.3970/cmc.2007.005.031

Abstract By using a meshless regularized integral equation method (MRIEM), the solution of elastic torsion problem of a uniform bar with arbitrary cross-section is presented by the first kind Fredholm integral equation on an artificial circle, which just encloses the bar's cross-section. The termwise separable property of kernel function allows us to obtain the semi-analytical solutions of conjugate warping function and shear stresses. A criterion is used to select the regularized parameter according to the minimum principle of Laplace equation. Numerical examples show the effectiveness of the new method in providing very accurate numerical solutions as compared with the exact ones. More >

Ramana M. Pidaparti^1,2, Evan J. Neblett²

CMC-Computers, Materials & Continua, Vol.5, No.1, pp. 1-10, 2007, DOI:10.3970/cmc.2007.005.001

Abstract A neural network (NN) model is developed for the analysis and prediction of the mapping between degradation of chemical elements and electrochemical parameters during the corrosion process. The input parameters to the neural network model are alloy composition, electrochemical parameters, and corrosion time. The output parameters are the degradation of chemical elements in AA 2024-T3 material. The NN is trained with the data obtained from Energy Dispersive X-ray Spectrometry (EDS) on corroded specimens. A very good performance of the neural network is achieved after training and validation with the experimental data. After validating the NN model, simulations were carried out… More >

Dongsheng Li^1,2, Ghazal Saheli¹, Moe Khaleel², Hamid Garmestani¹

CMC-Computers, Materials & Continua, Vol.4, No.1, pp. 31-42, 2006, DOI:10.3970/cmc.2006.004.031

Abstract A multiscale model based on statistical continuum mechanics is proposed to predict the mechanical and electrical properties of heterogeneous porous media. This model is applied within the framework of microstructure sensitive design (MSD) to guide the design of the microstructure in porous lanthanum strontium manganite (LSM) fuel cell electrode. To satisfy the property requirement and compatibility, porosity and its distribution can be adjusted under the guidance of MSD to achieve optimized microstructure. More >

D. Ballhause¹, M. König¹, B. Kröplin¹

CMC-Computers, Materials & Continua, Vol.4, No.1, pp. 21-30, 2006, DOI:10.3970/cmc.2006.004.021

Abstract The mechanical behaviour of woven fabrics is dominated by the kinematics of the constituents on the microscopic scale. Their macroscopic response usually shows non-linearities which are due to the mobility of the interlaced yarns. The major deformation mechanisms of fabrics, i.e. the crimp interchange in case of biaxial tension and the trellising motion of the yarns in case of shear, reflect the dependency of the macroscopic material behaviour on the microstructural deformation mechanisms.
We present a novel modelling approach for woven fabrics which is capable to represent directly and locally the microstructure and its kinematics at yarn level. With… More >

Thanh Q. Nguyen^1,2, Thao T. D. Nguyen³, H. Nguyen-Xuan^4,5,*, Nhi K. Ngo^1,2

CMC-Computers, Materials & Continua, Vol.61, No.1, pp. 27-53, 2019, DOI:10.32604/cmc.2019.07756

Abstract This paper presents a new approach using correlation and cross-correlation coefficients to evaluate the stiffness degradation of beams under moving load. The theoretical study of identifying defects by vibration methods showed that the traditional methods derived from the vibration measurement data have not met the needs of the actual issues. We show that the correlation coefficients allow us to evaluate the degree and the effectiveness of the defects on beams. At the same time, the cross-correlation model is the basis for determining the relative position of defects. The results of this study are experimentally conducted to confirm the relationship between… More >

Zhenqiu Xiao^1,*, Bin Yang², Desy Tjahjadi³

CMC-Computers, Materials & Continua, Vol.60, No.3, pp. 1141-1154, 2019, DOI:10.32604/cmc.2019.05638

Abstract Crowd counting is a challenging task in crowded scenes due to heavy occlusions, appearance variations and perspective distortions. Current crowd counting methods typically operate on an image patch level with overlaps, then sum over the patches to get the final count. In this paper we describe a real-time pedestrian counting framework based on a two-stage human detection algorithm. Existing works with overhead cameras is mainly based on visual tracking, and their robustness is rather limited. On the other hand, some works, which focus on improving the performances, are too complicated to be realistic. By adopting a line sampling process, a… More >

Lili He^1,2, Hongtao Bai^1,2, Dantong Ouyang^1,2, Changshuai Wang^1,2, Chong Wang^1,2,3, Yu Jiang^1,2,*

CMC-Computers, Materials & Continua, Vol.60, No.2, pp. 599-613, 2019, DOI:10.32604/cmc.2019.05928

Abstract Cloud-derived wind refers to the wind field data product reversely derived through satellite remote sensing cloud images. Satellite cloud-derived wind inversion has the characteristics of large scale, computationally intensive and long time. The most widely used cloud-derived serial--tracer cloud tracking method is the maximum cross-correlation coefficient (MCC) method. In order to overcome the efficiency bottleneck of the cloud-derived serial MCC algorithm, we proposed a parallel cloud-derived wind inversion algorithm based on GPU framework in this paper, according to the characteristics of independence between each wind vector calculation. In this algorithm, each iteration is considered as a thread of GPU cores,… More >

Fenghua Yuan¹, Qing Zhang^1,*, Xiaozhou Xia¹

CMC-Computers, Materials & Continua, Vol.58, No.3, pp. 777-793, 2019, DOI:10.32604/cmc.2019.04182

Abstract Reinforcement corrosion directly affects the mechanical behavior of reinforced concrete structures. An electric corrosion test was conducted on a reinforced concrete test specimen, and a finite element model of the reinforcement corrosion damage was established. In addition, the damage behavior of reinforced concrete under different corrosion sediment distribution characteristics and different corrosion rates was studied. It was noted that when corrosion sediments are in a “semiellipse+semicircle” distribution, the results of numerical calculation are consistent with those obtained experimentally, reflecting the damage characteristics of reinforced concrete test specimens. Further, the results showed that the distribution characteristics of corrosion sediments greatly influence… More >

Xudong Hong¹, Xiao Zheng^1,*, Jinyuan Xia¹, Linna Wei¹, Wei Xue¹

CMC-Computers, Materials & Continua, Vol.58, No.2, pp. 379-389, 2019, DOI:10.32604/cmc.2019.04059

Abstract To acquire non-ferrous metals related news from different countries’ internet, we proposed a cross-lingual non-ferrous metals related news recognition method based on CNN with a limited bilingual dictionary. Firstly, considering the lack of related language resources of non-ferrous metals, we use a limited bilingual dictionary and CCA to learn cross-lingual word vector and to represent news in different languages uniformly. Then, to improve the effect of recognition, we use a variant of the CNN to learn recognition features and construct the recognition model. The experimental results show that our proposed method acquires better results. More >

Huiyu Sun^1,*, Suzanne McIntosh¹

CMC-Computers, Materials & Continua, Vol.57, No.1, pp. 1-9, 2018, DOI:10.32604/cmc.2018.03684

Abstract The majority of big data analytics applied to transportation datasets suffer from being too domain-specific, that is, they draw conclusions for a dataset based on analytics on the same dataset. This makes models trained from one domain (e.g. taxi data) applies badly to a different domain (e.g. Uber data). To achieve accurate analyses on a new domain, substantial amounts of data must be available, which limits practical applications. To remedy this, we propose to use semi-supervised and active learning of big data to accomplish the domain adaptation task: Selectively choosing a small amount of datapoints from a new domain while… More >