Ange Chen, Chengdong Wu^*, Chuanjiang Leng

CMC-Computers, Materials & Continua, Vol.82, No.1, pp. 173-191, 2025, DOI:10.32604/cmc.2024.059284 - 03 January 2025

Abstract Previous multi-view 3D human pose estimation methods neither correlate different human joints in each view nor model learnable correlations between the same joints in different views explicitly, meaning that skeleton structure information is not utilized and multi-view pose information is not completely fused. Moreover, existing graph convolutional operations do not consider the specificity of different joints and different views of pose information when processing skeleton graphs, making the correlation weights between nodes in the graph and their neighborhood nodes shared. Existing Graph Convolutional Networks (GCNs) cannot extract global and deep-level skeleton structure information and view… More >

Zhao-Jun Zhang¹, Wen-Wei Wang^1,2,*, Jing-Shui Zhen¹, Bo-Cheng Li¹, De-Cheng Cai¹, Yang-Yang Du¹, Hui Huang²

Structural Durability & Health Monitoring, Vol.19, No.1, pp. 105-123, 2025, DOI:10.32604/sdhm.2024.052506 - 15 November 2024

Abstract This study aimed to investigate the moment redistribution in continuous glass fiber reinforced polymer (GFRP)-concrete composite slabs caused by concrete cracking and steel bar yielding in the negative bending moment zone. An experimental bending moment redistribution test was conducted on continuous GFRP-concrete composite slabs, and a calculation method based on the conjugate beam method was proposed. The composite slabs were formed by combining GFRP profiles with a concrete layer and supported on steel beams to create two-span continuous composite slab specimens. Two methods, epoxy resin bonding, and stud connection, were used to connect the composite… More >

Guojun Chen^*, Tao Cui, Yongjie Hou, Huihui Li

CMC-Computers, Materials & Continua, Vol.81, No.3, pp. 3969-3987, 2024, DOI:10.32604/cmc.2024.056093 - 19 December 2024

Abstract Existing glass segmentation networks have high computational complexity and large memory occupation, leading to high hardware requirements and time overheads for model inference, which is not conducive to efficiency-seeking real-time tasks such as autonomous driving. The inefficiency of the models is mainly due to employing homogeneous modules to process features of different layers. These modules require computationally intensive convolutions and weight calculation branches with numerous parameters to accommodate the differences in information across layers. We propose an efficient glass segmentation network (EGSNet) based on multi-level heterogeneous architecture and boundary awareness to balance the model performance… More >

Ivan Lobzenko^1,*, Tomohito Tsuru¹, Yoshinori Shiihara², Takuya Iwashita³

The International Conference on Computational & Experimental Engineering and Sciences, Vol.32, No.2, pp. 1-1, 2024, DOI:10.32604/icces.2024.012770

Abstract Revealing the origin of the mechanical properties of metallic glasses (MG) is a long-standing problem. MGs respond to the external strain with the activation of collective atomic motion, but the triggers of such motions are not revealed yet, in contrast to the well-defined dislocations in crystals. In the present study we show that the change of atomic Von Mises stress is one of the key local parameters to indicate the stress response to a shear strain in metallic glass. Four random Cu50%Zr50% structures were prepared in first-principles molecular dynamics cooling process. Structures were then put… More >

Bosong Li¹, Jamie J. Kruzic^1,*

The International Conference on Computational & Experimental Engineering and Sciences, Vol.32, No.2, pp. 1-2, 2024, DOI:10.32604/icces.2024.011331

Abstract Additive manufacturing has made the fabrication of large-dimensioned bulk metallic glasses (BMGs) achievable; however, questions remain regarding how to control the processing parameters to obtain dense and fully amorphous BMGs with desirable mechanical properties. Here, laser powder bed fusion (LPBF) was used to produce dense and fully amorphous Zr_59.3Cu_28.8Nb_1.5Al_10.4 BMG samples from two different starting powders within a large processing window of laser powers and scanning speeds. X-ray diffraction (XRD) revealed that fully amorphous materials with high relative densities (>99%) were obtained when the LPBF energy density ranged from ~20 J/mm³ up to ~33 J/mm³ for coarse… More >

Santhanakrishnan Mamallan¹, Venkateshwaran Narayanan^1,*, Canungo Bhimarao Ragothaman²

Journal of Polymer Materials, Vol.41, No.3, pp. 105-116, 2024, DOI:10.32604/jpm.2024.056744 - 30 September 2024

Abstract Glass fabric/polymer composites are widely used in various industrial applications due to their lightweight, exceptional strength, and fatigue resistance. Graphene nanoplatelets, a recently developed type of carbon material, stand out as unique nanofillers due to their 2D quantum confinement and expansive surface area within a polymer matrix. These features make them more effective than traditional carbon nanofillers at enhancing a range of properties. In this study, 3-weight % of graphene nanoplatelets with epoxy resin were used for investigation by varying sonication durations (0, 20, 40, and 60 min) using an ultrasonic bath sonicator. The laminates More >

Ravikumar Karthikeyan, Subbiah Rajkumar^*, Balasundaram Ravi

Journal of Polymer Materials, Vol.41, No.3, pp. 131-141, 2024, DOI:10.32604/jpm.2024.055989 - 30 September 2024

Abstract In this study, the Polyamide-12 (PA-12) powdered material in the Selective Laser Sintering (SLS) process has been incorporated as the filler in the composite material to enhance its properties. The PA-12 powder has been made into a form of filament and is primarily used in the Fused Deposition Modelling (FDM) process. The PA-12 has been used with epoxy resin and glass fiber with different proportions. The characterization of materials, including the validation of the presence of PA-12 filler with epoxy, has been evidenced using Fourier Transform Infrared Spectroscopy (FTIR), Differential Scanning Calorimetry (DSC), and Thermogravimetric More >

Yusuf Olanrewaju Busari^1,2,*, Issah Sadiq Ibrahim¹, Kabir S. Ajao¹, Norliana Mohd Abbas², James Obafemi Adegbola¹, Hassan Kobe Ibrahim³, Abdallah Reghioua⁴, Yusuf Lanre Shuaib-Babata¹, Rachael Oluwatoyosi Idowu¹

Journal of Polymer Materials, Vol.41, No.3, pp. 117-129, 2024, DOI:10.32604/jpm.2024.055895 - 30 September 2024

Abstract The research paper focuses on manufacturing composite materials from waste polyethylene terephthalate (PET) reinforced with soda-lime glass to provide a lightweight, less brittle, and high rust resistance when exposed to hazardous environment. In developing nations such as Nigeria, there is a significant surge in the volume of bottled water and other packaging materials used in households, leading to a rapid accumulation of biodegradable waste, that presents concerns such as the creation of landfills and health issues. PET are thermoplastic polymer that can be melted and shaped into various objects. This study involves the incorporation of… More >

Kunkun Tong^1,#, Guchu Zou^2,#, Xin Tan^1,*, Jingyu Gong¹, Zhenyi Qi², Zhizhong Zhang¹, Yuan Xie¹, Lizhuang Ma¹

CMC-Computers, Materials & Continua, Vol.80, No.3, pp. 3421-3461, 2024, DOI:10.32604/cmc.2024.055327 - 12 September 2024

Abstract Confusing object detection (COD), such as glass, mirrors, and camouflaged objects, represents a burgeoning visual detection task centered on pinpointing and distinguishing concealed targets within intricate backgrounds, leveraging deep learning methodologies. Despite garnering increasing attention in computer vision, the focus of most existing works leans toward formulating task-specific solutions rather than delving into in-depth analyses of methodological structures. As of now, there is a notable absence of a comprehensive systematic review that focuses on recently proposed deep learning-based models for these specific tasks. To fill this gap, our study presents a pioneering review that covers… More >

Wei Chen^*, Dingdan Liu, Yue Liang

FDMP-Fluid Dynamics & Materials Processing, Vol.20, No.5, pp. 915-938, 2024, DOI:10.32604/fdmp.2024.046335 - 07 June 2024

Abstract This study focuses on the effect of ultrafine waste glass powder on cement strength, gas permeability and pore structure. Varying contents were considered, with particle sizes ranging from 2 to 20 μm. Moreover, alkali activation was considered to ameliorate the reactivity and cementitious properties, which were assessed by using scanning electron microscopy (SEM), energy-dispersive X-ray spectroscopy (EDS), and specific surface area pore size distribution analysis. According to the results, without the addition of alkali activators, the performance of glass powder mortar decreases as the amount of glass powder increases, affecting various aspects such as strength… More >