Junqi Guo^1,2, Qingyun Xiong^1,*, Minghui Yang¹, Ziyun Zhao¹

CMC-Computers, Materials & Continua, Vol.76, No.1, pp. 827-848, 2023, DOI:10.32604/cmc.2023.036450 - 08 June 2023

Abstract Nowadays, smart wearable devices are used widely in the Social Internet of Things (IoT), which record human physiological data in real time. To protect the data privacy of smart devices, researchers pay more attention to federated learning. Although the data leakage problem is somewhat solved, a new challenge has emerged. Asynchronous federated learning shortens the convergence time, while it has time delay and data heterogeneity problems. Both of the two problems harm the accuracy. To overcome these issues, we propose an asynchronous federated learning scheme based on double compensation to solve the problem of time… More >

Shehab Khan Noor¹, Arif Mawardi Ismail¹, Mohd Najib Mohd Yasin^1,*, Mohamed Nasrun Osman¹, Thennarasan Sabapathy¹, Shakhirul Mat Salleh², Ping Jack Soh³, Ali Hanafiah Rambe⁴, Nurulazlina Ramli⁵

Computer Systems Science and Engineering, Vol.47, No.1, pp. 537-551, 2023, DOI:10.32604/csse.2023.037381 - 26 May 2023

Abstract This paper presents a flexible and wearable textile array antenna designed to generate Orbital Angular Momentum (OAM) waves with Mode +2 at 3.5 GHz (3.4 to 3.6 GHz) of the sub-6 GHz fifth-generation (5G) New Radio (NR) band. The proposed antenna is based on a uniform circular array of eight microstrip patch antennas on a felt textile substrate. In contrast to previous works involving the use of rigid substrates to generate OAM waves, this work explored the use of flexible substrates to generate OAM waves for the first time. Other than that, the proposed antenna… More >

Hongyu Lin, Feng Jiang^*, Yu Jiang, Huiyin Luo, Jian Yao, Jiaxin Liu

CMC-Computers, Materials & Continua, Vol.75, No.3, pp. 5321-5336, 2023, DOI:10.32604/cmc.2023.036893 - 29 April 2023

Abstract Detecting non-motor drivers’ helmets has significant implications for traffic control. Currently, most helmet detection methods are susceptible to the complex background and need more accuracy and better robustness of small object detection, which are unsuitable for practical application scenarios. Therefore, this paper proposes a new helmet-wearing detection algorithm based on the You Only Look Once version 5 (YOLOv5). First, the Dilated convolution In Coordinate Attention (DICA) layer is added to the backbone network. DICA combines the coordinated attention mechanism with atrous convolution to replace the original convolution layer, which can increase the perceptual field of… More >

Baraa Wasfi Salim¹, Bzar Khidir Hussan², Zainab Salih Ageed³, Subhi R. M. Zeebaree^4,*

CMC-Computers, Materials & Continua, Vol.75, No.2, pp. 4593-4609, 2023, DOI:10.32604/cmc.2023.037514 - 31 March 2023

Abstract Recently, human healthcare from body sensor data has gained considerable interest from a wide variety of human-computer communication and pattern analysis research owing to their real-time applications namely smart healthcare systems. Even though there are various forms of utilizing distributed sensors to monitor the behavior of people and vital signs, physical human action recognition (HAR) through body sensors gives useful information about the lifestyle and functionality of an individual. This article concentrates on the design of an Improved Transient Search Optimization with Machine Learning based Behavior Recognition (ITSOML-BR) technique using body sensor data. The presented… More >

Shu-Yin Chiang^*, Dong-Ye Wu

CMC-Computers, Materials & Continua, Vol.75, No.2, pp. 2509-2526, 2023, DOI:10.32604/cmc.2023.036466 - 31 March 2023

Abstract Physiological signals indicate a person’s physical and mental state at any given time. Accordingly, many studies extract physiological signals from the human body with non-contact methods, and most of them require facial feature points. However, under COVID-19, wearing a mask has become a must in many places, so how non-contact physiological information measurements can still be performed correctly even when a mask covers the facial information has become a focus of research. In this study, RGB and thermal infrared cameras were used to execute non-contact physiological information measurement systems for heart rate, blood pressure, respiratory… More >

Narit Hnoohom¹, Sakorn Mekruksavanich², Anuchit Jitpattanakul^3,4,*

Intelligent Automation & Soft Computing, Vol.36, No.3, pp. 3371-3385, 2023, DOI:10.32604/iasc.2023.036551 - 15 March 2023

Abstract Falls are the contributing factor to both fatal and nonfatal injuries in the elderly. Therefore, pre-impact fall detection, which identifies a fall before the body collides with the floor, would be essential. Recently, researchers have turned their attention from post-impact fall detection to pre-impact fall detection. Pre-impact fall detection solutions typically use either a threshold-based or machine learning-based approach, although the threshold value would be difficult to accurately determine in threshold-based methods. Moreover, while additional features could sometimes assist in categorizing falls and non-falls more precisely, the estimated determination of the significant features would be… More >

Xingyu Liang¹, Xiaoyu Gu¹, Myint Myint Paing Hsu², Yuhang He¹, Rongzhuo Zhang¹, Conghui Cai³, Zheng Wang^1,*

Journal of Renewable Materials, Vol.11, No.5, pp. 2333-2344, 2023, DOI:10.32604/jrm.2023.026137 - 13 February 2023

Abstract In order to improve the fire resistance, water resistance and wear resistance of ordinary plywood products in the wood processing industry, three composite structures of plywood products S1, S2 and S3 were designed in this paper, and a reasonable production process was proposed. Through the physical and mechanical properties and fire resistance testing and technical and economic analysis, the applicability of composite plywood was evaluated. The results of the study showed that the physical mechanics of the three kinds of composite structure plywood met the standard requirements, and their fire resistance was far better than… More >

Ying Wang^*, Zheng Yan, Yangyang Wu

CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.2, pp. 1339-1370, 2023, DOI:10.32604/cmes.2023.025830 - 06 February 2023

Abstract In this paper, a numerical model of fretting fatigue analysis of cable wire and the fretting fatigue damage constitutive model considering the multi-axis effect were established, and the user material subroutine UMAT was written. Then, the constitutive model of wear morphology evolution of cable wire and the constitutive model of pitting evolution considering the mechanical-electrochemical effect were established, respectively. The corresponding subroutines UMESHMOTION_Wear and UMESHMOTION_Wear_Corrosion were written, and the fretting fatigue life was further predicted. The results show that the numerical simulation life obtained by the program in this paper has the same trend as… More > Graphic Abstract

A. S. M. Sharifuzzaman Sagar¹, Taein Kim¹, Soyoung Park¹, Hee Seh Lee², Hyung Seok Kim^1,*

CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 1941-1961, 2023, DOI:10.32604/cmc.2023.035360 - 06 February 2023

Abstract Relative positioning is one of the important techniques in collaborative robotics, autonomous vehicles, and virtual/augmented reality (VR/AR) applications. Recently, ultra-wideband (UWB) has been utilized to calculate relative position as it does not require a line of sight compared to a camera to calculate the range between two objects with centimeter-level accuracy. However, the single UWB range measurement cannot provide the relative position and attitude of any device in three dimensions (3D) because of lacking bearing information. In this paper, we have proposed a UWB-IMU fusion-based relative position system to provide accurate relative position and attitude… More >

Sakorn Mekruksavanich¹, Anuchit Jitpattanakul^2,*

Intelligent Automation & Soft Computing, Vol.36, No.2, pp. 2111-2128, 2023, DOI:10.32604/iasc.2023.033542 - 05 January 2023

Abstract The automated evaluation and analysis of employee behavior in an Industry 4.0-compliant manufacturing firm are vital for the rapid and accurate diagnosis of work performance, particularly during the training of a new worker. Various techniques for identifying and detecting worker performance in industrial applications are based on computer vision techniques. Despite widespread computer vision-based approaches, it is challenging to develop technologies that assist the automated monitoring of worker actions at external working sites where camera deployment is problematic. Through the use of wearable inertial sensors, we propose a deep learning method for automatically recognizing the… More >