R. S. Tuan¹

Molecular & Cellular Biomechanics, Vol.3, No.4, pp. 229-230, 2006, DOI:10.32604/mcb.2006.003.229

Abstract This article has no abstract. More >

A. Frangi¹, L. Ghezzi, P. Faure-Ragani²

CMES-Computer Modeling in Engineering & Sciences, Vol.15, No.1, pp. 41-48, 2006, DOI:10.3970/cmes.2006.015.041

Abstract Three dimensional magneto-mechanical problems at low frequency are addressed by means of a coupled fast Boundary Element - Finite Element approach with total scalar potential and focusing especially on the issue of global force calculation on movable ferromagnetic parts. The differentiation of co-energy in this framework and the use of Maxwell tensor are critically discussed and the intrinsic links are put in evidence. Three examples of academic and industrial applications are employed for validation. More >

Kenji Tsuruta¹

The International Conference on Computational & Experimental Engineering and Sciences, Vol.13, No.3, pp. 63-64, 2009, DOI:10.3970/icces.2009.013.063

Abstract Unique properties in artificially designed new materials are demonstrated via multiple-scale computational techniques. A density-functional/classical molecular-dynamics method is employed to investigate segregation dynamics of dopants in nanostructured ceramics/semiconductors. We also develop a classical electromagnetic simulation algorithm combining with an electronic-structure calculation for analysis on optical properties of meta-materials. We demonstrate that these novel algorithms are highly optimized for ultra-scale parallel computers. More >

Ewa Głowińska*, Janusz Datta, Paulina Parcheta and Natalia Kaźmierczak

Journal of Renewable Materials, Vol.6, No.7, pp. 680-687, 2018, DOI:10.32604/JRM.2018.00003

Abstract The aim of this work was to investigate the influence of Spirulina (Spirulina platensis) as a natural filler on the curing characterization, morphology and mechanical, thermomechanical and thermal properties of natural rubber (NR) based composites. Spirulina was introduced into NR mixture in amount of 0 phr, 10 phr and 30 phr. The vulcanization process was carried out at the determined process condition by using hydraulic press at optimum vulcanization time (t90). It was noticed that Spirulina affected on the reduction of t90, and scorch time (t2) of the NR mixtures. Obtained vulcanizates were subjected to the number of tests e.g.… More >

Z. D. Han¹, S. N. Atluri¹

CMES-Computer Modeling in Engineering & Sciences, Vol.6, No.2, pp. 169-188, 2004, DOI:10.3970/cmes.2004.006.169

Abstract Three different truly Meshless Local Petrov-Galerkin (MLPG) methods are developed for solving 3D elasto-static problems. Using the general MLPG concept, these methods are derived through the local weak forms of the equilibrium equations, by using different test functions, namely, the Heaviside function, the Dirac delta function, and the fundamental solutions. The one with the use of the fundamental solutions is based on the local unsymmetric weak form (LUSWF), which is equivalent to the local boundary integral equations (LBIE) of the elasto-statics. Simple formulations are derived for the LBIEs in which only weakly-singular integrals are included for a simple numerical implementation.… More >

Alamelu Manghai T.M.¹, Jegadeeshwaran R², Sugumaran V.³

Structural Durability & Health Monitoring, Vol.11, No.1, pp. 43-67, 2017, DOI:10.3970/sdhm.2017.012.043

Abstract Diagnosis is the recognition of the nature and cause of a certain phenomenon. It is generally used to determine cause and effect of a problem. Machine fault diagnosis is a field of finding faults arising in machines. To identify the most probable faults leading to failure, many methods are used for data collection, including vibration monitoring, thermal imaging, oil particle analysis, etc. Then these data are processed using methods like spectral analysis, wavelet analysis, wavelet transform, short-term Fourier transform, high-resolution spectral analysis, waveform analysis, etc., The results of this analysis are used in a root cause failure analysis in order… More >

Tak-Sing Wong^*, Branden Brough^†, Chih-Ming Ho^∗,‡

Molecular & Cellular Biomechanics, Vol.6, No.1, pp. 1-56, 2009, DOI:10.3970/mcb.2009.006.001

Abstract Mimicking nature's approach in creating devices with similar functional complexity is one of the ultimate goals of scientists and engineers. The remarkable elegance of these naturally evolved structures originates from bottom-up self-assembly processes. The seamless integration of top-down fabrication and bottom-up synthesis is the challenge for achieving intricate artificial systems. In this paper, technologies necessary for guided bottom-up assembly such as molecular manipulation, molecular binding, and the self assembling of molecules will be reviewed. In addition, the current progress of synthesizing mechanical devices through top-down and bottom-up approaches will be discussed. More >

S.R.K. Vedula¹, T.S. Lim², P.J. Kausalya³, W. Hunziker³, G. Rajagopal², C.T. Lim^1,4

Molecular & Cellular Biomechanics, Vol.2, No.3, pp. 105-124, 2005, DOI:10.3970/mcb.2005.002.105

Abstract Cell-cell adhesion is an extremely important phenomenon as it influences several biologically important processes such as inflammation, cell migration, proliferation, differentiation and even cancer metastasis. Furthermore, proteins involved in cell-cell adhesion are also important from the perspective of facilitating better drug delivery across epithelia. The adhesion forces imparted by proteins involved in cell-cell adhesion have been the focus of research for sometime. However, with the advent of nanotechnological techniques such as the atomic force microscopy (AFM), we can now quantitatively probe these adhesion forces not only at the cellular but also molecular level. Here, we review the structure and function… More >

Hao Wu¹, Qi Liu^{2, 3, *}, Xiaodong Liu⁴

CMC-Computers, Materials & Continua, Vol.60, No.2, pp. 575-597, 2019, DOI:10.32604/cmc.2019.03595

Abstract Deep learning technology has brought great impetus to artificial intelligence, especially in the fields of image processing, pattern and object recognition in recent years. Present proposed artificial neural networks and optimization skills have effectively achieved large-scale deep learnt neural networks showing better performance with deeper depth and wider width of networks. With the efforts in the present deep learning approaches, factors, e.g., network structures, training methods and training data sets are playing critical roles in improving the performance of networks. In this paper, deep learning models in recent years are summarized and compared with detailed discussion of several typical networks… More >

Xiaoying Zhuang^1,2,*, Shuai Zhou^3,4

CMC-Computers, Materials & Continua, Vol.59, No.1, pp. 57-77, 2019, DOI:10.32604/cmc.2019.04589

Abstract Advances in machine learning (ML) methods are important in industrial engineering and attract great attention in recent years. However, a comprehensive comparative study of the most advanced ML algorithms is lacking. Six integrated ML approaches for the crack repairing capacity of the bacteria-based self-healing concrete are proposed and compared. Six ML algorithms, including the Support Vector Regression (SVR), Decision Tree Regression (DTR), Gradient Boosting Regression (GBR), Artificial Neural Network (ANN), Bayesian Ridge Regression (BRR) and Kernel Ridge Regression (KRR), are adopted for the relationship modeling to predict crack closure percentage (CCP). Particle Swarm Optimization (PSO) is used for the hyper-parameters… More >