Md. Munirul Hasan¹, Md Mustafizur Rahman^2,*, Mohammad Saiful Islam³, Wong Hung Chan⁴, Yasser M. Alginahi⁵, Muhammad Nomani Kabir⁶, Suraya Abu Bakar¹, Devarajan Ramasamy²

Frontiers in Heat and Mass Transfer, Vol.22, No.2, pp. 537-556, 2024, DOI:10.32604/fhmt.2024.047428 - 20 May 2024

Abstract A vehicle engine cooling system is of utmost importance to ensure that the engine operates in a safe temperature range. In most radiators that are used to cool an engine, water serves as a cooling fluid. The performance of a radiator in terms of heat transmission is significantly influenced by the incorporation of nanoparticles into the cooling water. Concentration and uniformity of nanoparticle distribution are the two major factors for the practical use of nanofluids. The shape and size of nanoparticles also have a great impact on the performance of heat transfer. Many researchers are… More > Graphic Abstract

Rashad A. Al-Jawfi^*

Intelligent Automation & Soft Computing, Vol.36, No.1, pp. 957-965, 2023, DOI:10.32604/iasc.2023.031700 - 29 September 2022

Abstract Activation functions play an essential role in converting the output of the artificial neural network into nonlinear results, since without this nonlinearity, the results of the network will be less accurate. Nonlinearity is the mission of all nonlinear functions, except for polynomials. The activation function must be differentiable for backpropagation learning. This study’s objective is to determine the best activation functions for the approximation of each fractal image. Different results have been attained using Matlab and Visual Basic programs, which indicate that the bounded function is more helpful than other functions. The non-linearity of the… More >

Walid El-Shafai^1,2,*, Amira A. Mahmoud¹, El-Sayed M. El-Rabaie¹, Taha E. Taha¹, Osama F. Zahran¹, Adel S. El-Fishawy¹, Mohammed Abd-Elnaby³, Fathi E. Abd El-Samie^1,4

CMC-Computers, Materials & Continua, Vol.70, No.3, pp. 4373-4391, 2022, DOI:10.32604/cmc.2022.019354 - 11 October 2021

Abstract Coronavirus (COVID-19) infection was initially acknowledged as a global pandemic in Wuhan in China. World Health Organization (WHO) stated that the COVID-19 is an epidemic that causes a 3.4% death rate. Chest X-Ray (CXR) and Computerized Tomography (CT) screening of infected persons are essential in diagnosis applications. There are numerous ways to identify positive COVID-19 cases. One of the fundamental ways is radiology imaging through CXR, or CT images. The comparison of CT and CXR scans revealed that CT scans are more effective in the diagnosis process due to their high quality. Hence, automated classification… More >

Kazuhiko Kakuda^1,*, Tomoyuki Enomoto¹, Shinichiro Miura²

CMES-Computer Modeling in Engineering & Sciences, Vol.118, No.1, pp. 1-14, 2019, DOI:10.31614/cmes.2019.04676

Abstract The nonlinear activation functions in the deep CNN (Convolutional Neural Network) based on fluid dynamics are presented. We propose two types of activation functions by applying the so-called parametric softsign to the negative region. We use significantly the well-known TensorFlow as the deep learning framework. The CNN architecture consists of three convolutional layers with the max-pooling and one fully-connected softmax layer. The CNN approaches are applied to three benchmark datasets, namely, MNIST, CIFAR-10, and CIFAR-100. Numerical results demonstrate the workability and the validity of the present approach through comparison with other numerical performances. More >

Tomoyuki Enomoto, Kazuhiko Kakuda, Shinichiro Miura

The International Conference on Computational & Experimental Engineering and Sciences, Vol.21, No.2, pp. 36-39, 2019, DOI:10.32604/icces.2019.05292

Abstract In this paper, the nonlinear activation functions based on fluid dynamics are presented. We propose two types of activation functions by applying the so-called parametric softsign to the negative region. We apply the activation function to CNN (Convolutional Neural Network) which performs image recognition and approaches from multiple benchmark datasets such as MNIST, CIFAR-10. Numerical results demonstrate the workability and the validity of the present approach through comparison with other numerical performances. More >