Huiru Zhao¹, Manyu Yao^1,*, Zhenqi Bai¹, Yue Zhang², Zhihua Ding³, Zhenda Hu⁴

Energy Engineering, Vol.120, No.10, pp. 2211-2231, 2023, DOI:10.32604/ee.2023.029371 - 28 September 2023

Abstract As an essential infrastructure, the rural power grid is vital in promoting agricultural and rural carbon sequestration and improving rural energy electrification. It is necessary to carry out in-depth research on its comprehensive efficiency. Based on the requirements of “double carbon” and rural revitalization strategy for the rural Power Grid, this paper focuses on the modernization and low-carbon transformation of the rural Power Grid. It constructs an input-output index system for the investment efficiency of the rural Power Grid in China under the new situation. It uses the primary data of the rural Power Grid… More >

Zoran Gligorić, Miloš Gligorić^*, Igor Miljanović, Suzana Lutovac, Aleksandar Milutinović

CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.1, pp. 955-979, 2023, DOI:10.32604/cmes.2023.025021 - 05 January 2023

Abstract Information about the relative importance of each criterion or the weights of criteria can have a significant influence on the ultimate rank of alternatives. Accordingly, assessing the weights of criteria is a very important task in solving multi-criteria decision-making problems. Three methods are commonly used for assessing the weights of criteria: objective, subjective, and integrated methods. In this study, an objective approach is proposed to assess the weights of criteria, called SPC method (Symmetry Point of Criterion). This point enriches the criterion so that it is balanced and easy to implement in the process of… More > Graphic Abstract

Rehman Ullah Khan^1,*, Woei Sheng Wong¹, Insaf Ullah², Fahad Algarni³, Muhammad Inam Ul Haq⁴, Mohamad Hardyman bin Barawi¹, Muhammad Asghar Khan²

CMC-Computers, Materials & Continua, Vol.71, No.2, pp. 2755-2772, 2022, DOI:10.32604/cmc.2022.022471 - 07 December 2021

Abstract The deaf-mutes population is constantly feeling helpless when others do not understand them and vice versa. To fill this gap, this study implements a CNN-based neural network, Convolutional Based Attention Module (CBAM), to recognise Malaysian Sign Language (MSL) in videos recognition. This study has created 2071 videos for 19 dynamic signs. Two different experiments were conducted for dynamic signs, using CBAM-3DResNet implementing ‘Within Blocks’ and ‘Before Classifier’ methods. Various metrics such as the accuracy, loss, precision, recall, F1-score, confusion matrix, and training time were recorded to evaluate the models’ efficiency. Results showed that CBAM-ResNet models More >