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  • Open Access

    PROCEEDINGS

    Dynamic Behaviors after Droplet Impact onto Liquid Surface

    Kazuhiko Kakuda1,*, Asuka Iizumi1

    The International Conference on Computational & Experimental Engineering and Sciences, Vol.24, No.1, pp. 1-5, 2022, DOI:10.32604/icces.2022.08695

    Abstract In this paper, we present the dynamic behaviors of crown formation, central jet, and secondary droplets generated with droplet impact onto a liquid surface by using experimental and computational approaches. In our experiment, the dynamic behaviors after a droplet impact are recorded using a high-speed camera with appropriate resolution and exposure time. On the other hand, we simulate numerically the similar behaviors using the VOF (volume of fluid) solver in the OpenFOAM. As a fluid field, we consider the multiphase flows with free surfaces based on incompressible Navier-Stokes equations in the software codes. Some qualitative comparisons between the experimental and… More >

  • Open Access

    ARTICLE

    An Optimized Transfer Learning Model Based Kidney Stone Classification

    S. Devi Mahalakshmi*

    Computer Systems Science and Engineering, Vol.44, No.2, pp. 1387-1395, 2023, DOI:10.32604/csse.2023.027610

    Abstract The kidney is an important organ of humans to purify the blood. The healthy function of the kidney is always essential to balance the salt, potassium and pH levels in the blood. Recently, the failure of kidneys happens easily to human beings due to their lifestyle, eating habits and diabetes diseases. Early prediction of kidney stones is compulsory for timely treatment. Image processing-based diagnosis approaches provide a greater success rate than other detection approaches. In this work, proposed a kidney stone classification method based on optimized Transfer Learning(TL). The Deep Convolutional Neural Network (DCNN) models of DenseNet169, MobileNetv2 and GoogleNet… More >

  • Open Access

    ARTICLE

    Cellulose Nanocrystal from Washingtonia Fibre and Its Characterization

    Mohammad Jawaid1, Lau Kia Kian1, Hassan Fouad2, Ramzi Khiari3,4,5,*, Othman Y. Alothman6, Mohamed Hashem7

    Journal of Renewable Materials, Vol.10, No.6, pp. 1459-1470, 2022, DOI:10.32604/jrm.2022.018415

    Abstract Cellulose nanocrystal (CNC) is a biomaterial derived from plant lignocellulosic components, widely applied in various industrial fields. Concurrently, with the growth of awareness in developing green nanomaterial, the explored Washingtonia fibre could be alternative biomass for obtaining CNC products. In the present work, different acid concentrations of 5%, 15%, and 25% hydrochloric solutions were employed to produce CNCs from Washingtonia fibre. With the chemical treatments, the yield of the CNC product was successfully retained at 21.6%−25.1%. Individually separated and needle-shaped CNC particles could be observed under the microscopic viewing with the increased acid concentrations. From elemental analysis, a relatively pure… More > Graphic Abstract

    Cellulose Nanocrystal from <i>Washingtonia</i> Fibre and Its Characterization

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