Zikun Li¹, Jing Tang¹, Xiaobao Tian¹, Qingyuan Wang¹, Wentao Jiang¹, Haidong Fan^1,*

The International Conference on Computational & Experimental Engineering and Sciences, Vol.25, No.2, pp. 1-1, 2023, DOI:10.32604/icces.2023.09968

Abstract Magnesium is a lightweight structural metal but the industrial application is limited by its poor intrinsic ductility. Pyramidal dislocations are believed to be responsible for the ductility enhancement whereas the dislocation plasticity of magnesium was not well studied, especially the pyramidal dislocations. In this work, molecular dynamics simulations were performed to investigate the pyramidal disloation behaviors including the decomposition of pyramidal dislocations on both pyramidal-I and pyramidal-II planes and the interactions between themselves and other dislocations in Mg. The pyramidal-I dislocations are decomposed into and dislocations under shear stress at 0-400K, which all reside on basal plane.… More >

Mohamed Abdulsalam¹, Jiling Feng^1,*

The International Conference on Computational & Experimental Engineering and Sciences, Vol.25, No.2, pp. 1-1, 2023, DOI:10.32604/icces.2023.09884

Abstract Atherosclerosis developed in the arterial wall is the major cause of cardiovascular events such as stroke and heart failure. Atherosclerosis, also referred to as arterial plaque can be classified as stable, unstable, and vulnerable plaque. In terms of the features of compositions and structures, atherosclerosis also can be classified as calcified plaque, the plaque with a lipid core, and plaque with a thin fibrous cap. It is expected that the compositions, structures, and mechanical properties of the plaques interrelate with each other. The correlations between the compositions, structure, and mechanical properties are expected to characterize the nature of the rupture… More >

John Freddy Gelves-Díaz^1,*, Ludovic Dorkis², Richard Monroy-Sepúlveda¹, Sandra Rozo-Rincón¹, Yebrail Alexis Romero-Arcos¹

Journal of Renewable Materials, Vol.11, No.10, pp. 3769-3787, 2023, DOI:10.32604/jrm.2023.029270

Abstract Secondary lignocellulosic biomass has proved to be useful as an energy source through its oxidation by means of combustion processes. In accordance with the above, in this paper, we wanted to study the ash from urban pruning residues that are generated in cities in the Neotropics. Species such as Licania tomentosa, Azadirachta indica, Ficus benjamina, Terminalia catappa, Leucaena leucocephala, Prosopis juliflora and Pithecellobium dulce were selected because they have been previously studied and showed potential for thermal energy generation. These materials were calcined in an oxidizing atmosphere and characterized by X-ray diffraction and fluorescence, scanning electron microscopy with microchemistry, BET… More > Graphic Abstract

Wangpeng He^1,*, Yue Zhou¹, Xiaoya Guo², Deshun Hu¹, Junjie Ye³

CMES-Computer Modeling in Engineering & Sciences, Vol.137, No.3, pp. 2495-2511, 2023, DOI:10.32604/cmes.2023.027896

Abstract In today’s world, smart electric vehicles are deeply integrated with smart energy, smart transportation and smart cities. In electric vehicles (EVs), owing to the harsh working conditions, mechanical parts are prone to fatigue damages, which endanger the driving safety of EVs. The practice has proved that the identification of periodic impact characteristics (PICs) can effectively indicate mechanical faults. This paper proposes a novel model-based approach for intelligent fault diagnosis of mechanical transmission train in EVs. The essential idea of this approach lies in the fusion of statistical information and model information from a dynamic process. In the algorithm, a novel… More >

Xinfei Li², Xiaolan Xie^1,2,*, Yigang Tang², Qiang Guo^1,2

Computer Systems Science and Engineering, Vol.47, No.2, pp. 2707-2724, 2023, DOI:10.32604/csse.2023.037351

Abstract Predicting the usage of container cloud resources has always been an important and challenging problem in improving the performance of cloud resource clusters. We proposed an integrated prediction method of stacking container cloud resources based on variational modal decomposition (VMD)-Permutation entropy (PE) and long short-term memory (LSTM) neural network to solve the prediction difficulties caused by the non-stationarity and volatility of resource data. The variational modal decomposition algorithm decomposes the time series data of cloud resources to obtain intrinsic mode function and residual components, which solves the signal decomposition algorithm’s end-effect and modal confusion problems. The permutation entropy is used… More >

Jiaojiao Yuan¹, Su Tuo¹, Yangyang Liu¹, Jing He¹, Shao-Hwa Hu¹, Junling Tu^2,*

Journal of Renewable Materials, Vol.11, No.8, pp. 3371-3385, 2023, DOI:10.32604/jrm.2023.028046

Abstract

Due to the existence of poly-hydroxyl structures, the temperature may have an effect on the thermal stability of oleuropein for its applications. In the current study, the thermal decomposition process and kinetics behavior of oleuropein from the olive resource were researched by thermogravimetric theoretical analysis methods and non-isothermal kinetics simulation. The results of thermogravimetry analysis showed the whole thermal decomposition process of oleuropein involved two stages, with 21.22% of residue. It was also revealed that high heating rates of more than 20 K min⁻¹ led to significant thermal hysteresis and inhibited the whole thermal decomposition behavior of oleuropein. Moreover, an… More > Graphic Abstract

Loc Vu-Quoc^1,*, Alexander Humer²

CMES-Computer Modeling in Engineering & Sciences, Vol.137, No.2, pp. 1069-1343, 2023, DOI:10.32604/cmes.2023.028130

Abstract Three recent breakthroughs due to AI in arts and science serve as motivation: An award winning digital image, protein folding, fast matrix multiplication. Many recent developments in artificial neural networks, particularly deep learning (DL), applied and relevant to computational mechanics (solid, fluids, finite-element technology) are reviewed in detail. Both hybrid and pure machine learning (ML) methods are discussed. Hybrid methods combine traditional PDE discretizations with ML methods either (1) to help model complex nonlinear constitutive relations, (2) to nonlinearly reduce the model order for efficient simulation (turbulence), or (3) to accelerate the simulation by predicting certain components in the traditional… More >

Yu-Ming Chu¹, Saima Rashid^2,*, Shazia Karim³, Anam Sultan²

CMES-Computer Modeling in Engineering & Sciences, Vol.137, No.2, pp. 1573-1611, 2023, DOI:10.32604/cmes.2023.027724

Abstract The fractional-order Boussinesq equations (FBSQe) are investigated in this work to see if they can effectively improve the situation where the shallow water equation cannot directly handle the dispersion wave. The fuzzy forms of analytical FBSQe solutions are first derived using the Adomian decomposition method. It also occurs on the sea floor as opposed to at the functionality. A set of dynamical partial differential equations (PDEs) in this article exemplify an unconfined aquifer flow implication. This methodology can accurately simulate climatological intrinsic waves, so the ripples are spread across a large demographic zone. The Aboodh transform merged with the mechanism… More >

Yong Cheng¹, Zexuan Yang^2,*, Wenjie Zhang^3,4, Ling Yang⁵, Jun Wang¹, Tingzhao Guan¹

Intelligent Automation & Soft Computing, Vol.37, No.2, pp. 1469-1482, 2023, DOI:10.32604/iasc.2023.038251

Abstract The numerous photos captured by low-price Internet of Things (IoT) sensors are frequently affected by meteorological factors, especially rainfall. It causes varying sizes of white streaks on the image, destroying the image texture and ruining the performance of the outdoor computer vision system. Existing methods utilise training with pairs of images, which is difficult to cover all scenes and leads to domain gaps. In addition, the network structures adopt deep learning to map rain images to rain-free images, failing to use prior knowledge effectively. To solve these problems, we introduce a single image derain model in edge computing that combines… More >

Kali Gurkahraman^1,*, Rukiye Karakis², Hidayet Takci¹

Computer Systems Science and Engineering, Vol.47, No.1, pp. 55-77, 2023, DOI:10.32604/csse.2023.037798

Abstract This study aimed to deal with three challenges: robustness, imperceptibility, and capacity in the image watermarking field. To reach a high capacity, a novel similarity-based edge detection algorithm was developed that finds more edge points than traditional techniques. The colored watermark image was created by inserting a randomly generated message on the edge points detected by this algorithm. To ensure robustness and imperceptibility, watermark and cover images were combined in the high-frequency subbands using Discrete Wavelet Transform and Singular Value Decomposition. In the watermarking stage, the watermark image was weighted by the adaptive scaling factor calculated by the standard deviation… More >