Yen-Jen Lai¹, I-Ling Chang^1,*

The International Conference on Computational & Experimental Engineering and Sciences, Vol.31, No.1, pp. 1-1, 2024, DOI:10.32604/icces.2024.012918

Abstract Biomechanical research reveals that the geometric shapes and dynamic behaviors of organ tissues play a pivotal role in determining their mechanical properties. Recent advancements in time-correlated imaging technologies, such as Computed Tomography (4D-CT) and Magnetic Resonance Imaging (4D-MRI), have enabled the non-invasive capture of both geometric data and dynamic information over time. However, the manual segmentation of these extensive datasets proves to be laborious and expensive. This study introduces an automated workflow designed for image segmentation and classification within 4D-CT scans, with a specific focus on the bone structures surrounding the Trapeziometacarpal (TMC) joint in More >

Weixiang Peng¹, Hortense Le Ferrand^1,2,*

The International Conference on Computational & Experimental Engineering and Sciences, Vol.31, No.1, pp. 1-2, 2024, DOI:10.32604/icces.2024.011119

Abstract Natural structural materials have undergone extensive evolution, resulting in intricate microstructural designs over billions of years. These designs have given rise to a diverse array of hierarchical microstructures that exhibit exceptional performance in terms of strength, resilience, toughness, and adaptability [1]. Among these natural microstructures, the microplatelet-based brick-and-mortar arrangement found in the nacreous layers of seashells has been the subject of extensive study. Additionally, more complex microstructural alignments exist, and these mineral orientations showcase varying properties, such as the shrinkage deformations. Inspired by the observed expansion deformation characteristics in nature, this study delves into the… More >

Keke Zhou, Guoqiang Zheng^*, Huihui Zhai, Xiangshuai Lv, Weizhen Zhang

CMC-Computers, Materials & Continua, Vol.81, No.2, pp. 2571-2585, 2024, DOI:10.32604/cmc.2024.056863 - 18 November 2024

Abstract Distracted driving remains a primary factor in traffic accidents and poses a significant obstacle to advancing driver assistance technologies. Improving the accuracy of distracted driving can greatly reduce the occurrence of traffic accidents, thereby providing a guarantee for the safety of drivers. However, detecting distracted driving behaviors remains challenging in real-world scenarios with complex backgrounds, varying target scales, and different resolutions. Addressing the low detection accuracy of existing vehicle distraction detection algorithms and considering practical application scenarios, this paper proposes an improved vehicle distraction detection algorithm based on YOLOv5. The algorithm integrates Attention-based Intra-scale Feature… More >

Xi Li^1,2, Yuxin Li², Zhenhua Xiao^3,*, Zhenghua Huang¹, Lianying Zou¹

CMC-Computers, Materials & Continua, Vol.81, No.2, pp. 3325-3349, 2024, DOI:10.32604/cmc.2024.056464 - 18 November 2024

Abstract Human pose estimation is a critical research area in the field of computer vision, playing a significant role in applications such as human-computer interaction, behavior analysis, and action recognition. In this paper, we propose a U-shaped keypoint detection network (DAUNet) based on an improved ResNet subsampling structure and spatial grouping mechanism. This network addresses key challenges in traditional methods, such as information loss, large network redundancy, and insufficient sensitivity to low-resolution features. DAUNet is composed of three main components. First, we introduce an improved BottleNeck block that employs partial convolution and strip pooling to reduce… More >

Kaituo Jiao¹, Dongxu Han^2,*, Bo Yu²

The International Conference on Computational & Experimental Engineering and Sciences, Vol.30, No.1, pp. 1-3, 2024, DOI:10.32604/icces.2024.011520

Abstract Motivated by the fractures being very thin compared to the size of rock matrix, utilizing the non-conforming grid is an efficient approach to simulate fluid flow in fractured porous media. The embedded discrete fracture model (EDFM) is the typical one that using the conforming grid and modelled based on the finite volume method (FVM) framework. The EDFM maintains advantages of mass conservation and low computational complexity, but it cannot characterize blocking fractures and has a low accuracy on the mass exchange between fractures and matrix [1]. In our previous work [2], we developed the enriched-EDFM… More >

Taher Armaghani¹, Lioua Kolsi², Najiyah Safwa Khashi’ie^3,*, Ahmed Muhammed Rashad⁴, Muhammed Ahmed Mansour⁵, Taha Salah⁶, Aboulbaba Eladeb⁷

CMES-Computer Modeling in Engineering & Sciences, Vol.141, No.3, pp. 2225-2251, 2024, DOI:10.32604/cmes.2024.056676 - 31 October 2024

Abstract In this paper, the unsteady magnetohydrodynamic (MHD)-radiation-natural convection of a hybrid nanofluid within a U-shaped wavy porous cavity is investigated. This problem has relevant applications in optimizing thermal management systems in electronic devices, solar energy collectors, and other industrial applications where efficient heat transfer is very important. The study is based on the application of a numerical approach using the Finite Difference Method (FDM) for the resolution of the governing equations, which incorporates the Rosseland approximation for thermal radiation and the Darcy-Brinkman-Forchheimer model for porous media. It was found that the increase of Hartmann number… More >

Winston Wai Shing Ma¹, Lei Zhang^2,3, Junhao Ding¹, Shuo Qu¹, Xu Song^1,*, Michael Yu Wang^4,*

The International Conference on Computational & Experimental Engineering and Sciences, Vol.29, No.2, pp. 1-1, 2024, DOI:10.32604/icces.2024.011319

Abstract Elastically isotropic open-cell lattice metamaterials exhibit identical elastic properties along arbitrary directions, and are ideal candidates for applications with unknown primary loading directions. Their open-cell properties are preferred for additive manufacturing processes and multifunctional applications requiring mass and heat transfer. This presentation focuses on the design, simulation, fabrication, and experimental tests of elastically isotropic open-cell lattice metamaterials with superior stiffness. First, a family of elastically isotropic truss lattices are analytically devised through combining elementary cubic lattices with contrary elastic anisotropy. The proposed stretching-dominated truss lattices can reach nearly 1/3 of the Hashin-Shtrikman upper bounds at… More >

Zheng Wu¹, Pai Liu¹, Zhan Kang¹, Yiqiang Wang^1,*

The International Conference on Computational & Experimental Engineering and Sciences, Vol.29, No.2, pp. 1-2, 2024, DOI:10.32604/icces.2024.011044

Abstract Honeycomb sandwich structures (HSSs) consist of lightweight cores arranged in periodic polygons [1] between two face sheets. They are widely used in the aerospace industry due to their lightweight but superior strength [2] and energy absorption [3]. As extremely high temperatures might be applied, the sandwich structures may suffer from thermal buckling failure [4] due to thin face walls [5]. This paper designs a new type of HSSs for pursuing optimal thermal buckling strength. The design idea is to replace the vertical straight walls in the honeycomb cores with curved walls. An optimization problem is… More >

Zhimin Chen¹, Bo Yu², Yujie Chen^2,*, Xufei Yang², Jianqin Zhu³, Wei Lu⁴, Weihua Cai^1,*

The International Conference on Computational & Experimental Engineering and Sciences, Vol.29, No.4, pp. 1-1, 2024, DOI:10.32604/icces.2024.012525

Abstract The laminated cooling configuration offers significant advantages in enhancing the cooling effectiveness, prolonging the service life, and enhancing the reliability of turbine blades. It stands as one of the key development directions for the cooling structure of next-generation turbine blades. Numerous scholars have conducted extensive research on laminated cooling, which has been widely applied in the aviation industry. With the continuous rise in turbine inlet temperatures, there is a growing need to further enhance the cooling performance of the blades. Therefore, this study proposes the utilization of a shaped film hole to enhance the overall… More >

Aniqua Nusrat Zereen¹, Abir Das², Jia Uddin^3,*

CMC-Computers, Materials & Continua, Vol.80, No.3, pp. 3463-3484, 2024, DOI:10.32604/cmc.2024.054886 - 12 September 2024

Abstract Machine fault diagnostics are essential for industrial operations, and advancements in machine learning have significantly advanced these systems by providing accurate predictions and expedited solutions. Machine learning models, especially those utilizing complex algorithms like deep learning, have demonstrated major potential in extracting important information from large operational datasets. Despite their efficiency, machine learning models face challenges, making Explainable AI (XAI) crucial for improving their understandability and fine-tuning. The importance of feature contribution and selection using XAI in the diagnosis of machine faults is examined in this study. The technique is applied to evaluate different machine-learning More >