Shimaa M. Amer¹, Ashraf A. M. Khalaf², Amr H. Hussein^3,4, Salman A. Alqahtani⁵, Mostafa H. Dahshan⁶, Hossam M. Kassem^3,4,*

CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.3, pp. 2749-2767, 2024, DOI:10.32604/cmes.2023.029138 - 15 December 2023

Abstract Side lobe level reduction (SLL) of antenna arrays significantly enhances the signal-to-interference ratio and improves the quality of service (QOS) in recent and future wireless communication systems starting from 5G up to 7G. Furthermore, it improves the array gain and directivity, increasing the detection range and angular resolution of radar systems. This study proposes two highly efficient SLL reduction techniques. These techniques are based on the hybridization between either the single convolution or the double convolution algorithms and the genetic algorithm (GA) to develop the Conv/GA and DConv/GA, respectively. The convolution process determines the element’s… More >

Shiyang Song^1,*, Tongxin Han²

FDMP-Fluid Dynamics & Materials Processing, Vol.20, No.1, pp. 127-145, 2024, DOI:10.32604/fdmp.2023.030137 - 08 November 2023

Abstract Aiming to mitigate the aerodynamic lift force imbalance between pantograph strips, which exacerbates wear and affects the current collection performance of the pantograph-catenary system, a study has been conducted to support the beam deflector optimization using a combination of experimental measurements and computational fluid dynamics (CFD) simulations. The results demonstrate that the size, position, and installation orientation of the wind deflectors significantly influence the amount of force compensation. They also indicate that the front strip deflectors should be installed downwards and the rear strip deflectors upwards, thereby forming a “π” shape. Moreover, the lift force More >

Baofeng Ji^1,2,3,4,*, Yifan Liu^1,2,3,4, Tingpeng Li¹, Ling Xing², Weixing Wang², Shahid Mumtaz⁵, Xiaolong Shang⁶, Wanying Liu², Congzheng Han⁴

CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.1, pp. 679-689, 2024, DOI:10.32604/cmes.2023.028667 - 22 September 2023

Abstract With the development of information technology, more and more devices are connected to the Internet through wireless communication to complete data interconnection. Due to the broadcast characteristics of wireless channels, wireless networks have suffered more and more malicious attacks. Physical layer security has received extensive attention from industry and academia. MIMO is considered to be one of the most important technologies related to physical layer security. Through beamforming technology, messages can be transmitted to legitimate users in an offset direction that is as orthogonal as possible to the interference channel to ensure the reception SINR… More >

Zhongming Hu^1,*, Leilei Chen¹, Delei Yang¹, Jichao Zhang¹, Youyang Xin¹

The International Conference on Computational & Experimental Engineering and Sciences, Vol.27, No.4, pp. 1-3, 2023, DOI:10.32604/icces.2023.09340

Abstract Functionally graded materials (FGMs), a kind of composite materials, were proposed to satisfy the requirements of thermal barrier materials initially [1-3]. Compared with traditional composites, the microstructure and mechanical characteristics of FGMs change continuously which make them present excellent performance in deformation resistance or toughness under extreme mechanical and thermal loadings [4]. Therefore, FGMs have been paid much attention and experienced rapid developments in the last decade. Nowadays, various structural components manufactured by FGMs have been used in extensive applications, such as aerospace, bioengineering, nuclear industries, civil constructions etc. [5-7]
While, FG Euler-Bernoulli beams maybe… More >

Jebran Khan¹, Kashif Ahmad², Kyung-Ah Sohn^1,3,*

Computer Systems Science and Engineering, Vol.47, No.3, pp. 2869-2894, 2023, DOI:10.32604/csse.2023.040159 - 09 November 2023

Abstract In recent years, the growing popularity of social media platforms has led to several interesting natural language processing (NLP) applications. However, these social media-based NLP applications are subject to different types of adversarial attacks due to the vulnerabilities of machine learning (ML) and NLP techniques. This work presents a new low-level adversarial attack recipe inspired by textual variations in online social media communication. These variations are generated to convey the message using out-of-vocabulary words based on visual and phonetic similarities of characters and words in the shortest possible form. The intuition of the proposed scheme… More >

Libo Xie¹, Xue Wang¹, Luxiang Liu^2,*, Chunmei Xu¹, Yongdun Xie², Hongchun Xiong², Xinchun Han³, Mu Guo¹

Phyton-International Journal of Experimental Botany, Vol.92, No.11, pp. 2947-2964, 2023, DOI:10.32604/phyton.2023.042919 - 24 October 2023

Abstract Hot pepper (Capsicum annuum L.) is consumed as one of the oldest domesticated crops all over the world. Although mutation breeding using radiation has been performed in hot peppers, little is known about the comparative analysis of mutagenic effects at the molecular level by ion beam irradiation. To comprehend the response mechanism of hot pepper to the ion beam, we used a mutant with favorable economic characteristics induced by lithium-ion beam irradiation to investigate the biological effects. The results indicated that the lithium-ion beam had a positive effect on important agronomic traits, particularly yield unit, but… More >

Hang Meng^1,*, Jiaxing Wu¹, Guangxing Wu¹, Kai Long¹

The International Conference on Computational & Experimental Engineering and Sciences, Vol.27, No.2, pp. 1-1, 2023, DOI:10.32604/icces.2023.09685

Abstract Wind energy is one of the most promising renewable energies in the world. To generate more electricity, the wind turbines are getting larger and larger in recent decades [1]. With the wind turbine size growing, the length of the blade is getting slender. The large deflections of slender wind turbine blade will inevitably lead to geometric nonlinearities [2], e.g. nonlinear coupling between torsion and deflection, which complicates the governing equations of motion. To simplify the solution of the nonlinear equations, in the current research, a novel finite-difference method was proposed to solve the nonlinear equations… More >

Chun Sha^1,*, Chaohui Yue², Wenchen Wang³

Structural Durability & Health Monitoring, Vol.17, No.5, pp. 369-381, 2023, DOI:10.32604/sdhm.2023.027948 - 07 September 2023

Abstract Convolution neural networks in deep learning can solve the problem of damage identification based on vibration acceleration. By combining multiple 1D DenseNet submodels, a new ensemble learning method is proposed to improve identification accuracy. 1D DenseNet is built using standard 1D CNN and DenseNet basic blocks, and the acceleration data obtained from multiple sampling points is brought into the 1D DenseNet training to generate submodels after offset sampling. When using submodels for damage identification, the voting method ideas in ensemble learning are used to vote on the results of each submodel, and then vote centrally. More >

Zeyuan Zhou¹, Ming Yu¹, Zaixing Huang^1,*

The International Conference on Computational & Experimental Engineering and Sciences, Vol.26, No.4, pp. 1-1, 2023, DOI:10.32604/icces.2023.09135

Abstract Peridynamics (PD) is a reformulation of the classical continuum mechanics. Its core consists in that a weighted integral of relative displacement over a spatial domain is used instead of the spatial derivative of displacement in governing equations of deformation. Based on an improved technique of exerting traction on boundary surface, an improved peridynamic motion equation has been proposed within the framework of the peridynamic(PD) theory. It is more natural and easier to deal with boundary conditions for the elastic deformation and fracture analysis. Under the enhancement effect in the constructed transfer functions of boundary traction,… More >

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 - 26 June 2023

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… More >