S. MATHIVANAN^*, R. MOHAN, RAMES C PANDA, P. BALACHANDER¹

Journal of Polymer Materials, Vol.39, No.3-4, pp. 195-204, 2022, DOI:10.32381/JPM.2022.39.3-4.2

Abstract Optimum-designed footwear with polyurethane (PU) material for comfort is an important requirement for obese. Investigations on compressive behavior of varied designed footwear using 120 D PU material have been carried out. The energy absorption primarily depends on heel height, slope angle and load applied or body mass index of obese. Statistical analysis has been used to formulate the prediction of absorbed energy wherein a heel height of 30 mm with 20-degree angle provides optimum value with the incorporation of 120 D PU material. A coefficientof-determination (R² ) value of 0.9406 confirms the suitability of the statistical More >

Ali Hanafiah Rambe¹, Muzammil Jusoh^2,3, Samir Salem Al-Bawri^4,5,*, Mahmoud A. Abdelghany^6,7

CMC-Computers, Materials & Continua, Vol.73, No.3, pp. 5575-5587, 2022, DOI:10.32604/cmc.2022.030902 - 28 July 2022

Abstract This paper proposed integrating the communication system on the garment, which can be utilized to detect breast cancer at an early stage by using an ultra-wideband (UWB) wearable antenna. Breast cancer is an abnormal cell that is located in the breast tissue. Early detection of breast cancer plays an important role, and it helps in the long term for all women. The proposed UWB wearable antenna successfully operates at 3.1–10.6 GHz under an acceptable reflection coefficient of −10 dB. The fabricated wearable antenna was made from Shieldit Super and felt both conductive and nonconductive wearable More >

Jiacheng Qian¹, Chenqi Zou¹, Mengyan Zang^1,*, Shunhua Chen^2,3,*, Makoto Tsubokura⁴

CMES-Computer Modeling in Engineering & Sciences, Vol.133, No.2, pp. 251-280, 2022, DOI:10.32604/cmes.2022.020738 - 21 July 2022

Abstract The stone chip resistance performance of automotive coatings has attracted increasing attention in academic and industrial communities. Even though traditional gravelometer tests can be used to evaluate stone chip resistance of automotive coatings, such experiment-based methods suffer from poor repeatability and high cost. The main purpose of this work is to develop a CFD-DEM-wear coupling method to accurately and efficiently simulate stone chip behavior of automotive coatings in a gravelometer test. To achieve this end, an approach coupling an unresolved computational fluid dynamics (CFD) method and a discrete element method (DEM) are employed to account… More >

Jingyu Dai^1,*, Hongyu Dai², Yutong Xie³, T. Indumathi⁴

Journal of Renewable Materials, Vol.10, No.11, pp. 2717-2728, 2022, DOI:10.32604/jrm.2022.019735 - 29 June 2022

Abstract In order to promote the application of clean energy technology in clothing and promote the integration of industrial development and artificial intelligence wearable technology, this study elaborates the energy application characteristics of intelligent wearable products at home and abroad and its application in different fields, aiming at the current research status of wearable technology in the field of textile and clothing. The wearable distributed generation technology is classified, and a creative clothing design for detecting climate temperature is designed. Based on the monitoring of body temperature, the changes in clothing pattern color can reflect people’s More >

Yiming Zhao^1,2, Hongsheng Zhao³, Zhili Wei⁴, Jie Yuan¹, Jie Jian¹, Fankai Kong¹, Haojiang Xie¹, Xingliang Xiong^1,2,*

Journal of Renewable Materials, Vol.10, No.11, pp. 2729-2746, 2022, DOI:10.32604/jrm.2022.019721 - 29 June 2022

Abstract The flexible wearable sensors with excellent stretchability, high sensitivity and good biocompatibility are signifi- cantly required for continuously physical condition tracking in health management and rehabilitation monitoring. Herein, we present a high-performance wearable sensor. The sensor is prepared with nanocomposite hydrogel by using silk fibroin (SF), polyacrylamide (PAM), polydopamine (PDA) and graphene oxide (GO). It can be used to monitor body motions (including large-scale and small-scale motions) as well as human electrophysiological (ECG) signals with high sensitivity, wide sensing range, and fast response time. Therefore, the proposed sensor is promising in the fields of rehabilitation, More >

Sakorn Mekruksavanich¹, Anuchit Jitpattanakul^2,*

Intelligent Automation & Soft Computing, Vol.34, No.3, pp. 1907-1925, 2022, DOI:10.32604/iasc.2022.027233 - 25 May 2022

Abstract Numerous learning-based techniques for effective human activity recognition (HAR) have recently been developed. Wearable inertial sensors are critical for HAR studies to characterize sport-related activities. Smart wearables are now ubiquitous and can benefit people of all ages. HAR investigations typically involve sensor-based evaluation. Sport-related activities are unpredictable and have historically been classified as complex, with conventional machine learning (ML) algorithms applied to resolve HAR issues. The efficiency of machine learning techniques in categorizing data is limited by the human-crafted feature extraction procedure. A deep learning model named MBiGRU (multimodal bidirectional gated recurrent unit) neural network More >

Yazeed Yasin Ghadi¹, Mouazma Batool², Munkhjargal Gochoo³, Suliman A. Alsuhibany⁴, Tamara al Shloul⁵, Ahmad Jalal², Jeongmin Park^6,*

CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 1037-1053, 2022, DOI:10.32604/cmc.2022.027422 - 18 May 2022

Abstract Over the last decade, there is a surge of attention in establishing ambient assisted living (AAL) solutions to assist individuals live independently. With a social and economic perspective, the demographic shift toward an elderly population has brought new challenges to today’s society. AAL can offer a variety of solutions for increasing people’s quality of life, allowing them to live healthier and more independently for longer. In this paper, we have proposed a novel AAL solution using a hybrid bidirectional long-term and short-term memory networks (BiLSTM) and convolutional neural network (CNN) classifier. We first pre-processed the… More >

Yanman Li¹, Jun Zhang¹, Yang Hu¹, Yingnan Zhao^2,*, Yi Cao³

Computer Systems Science and Engineering, Vol.43, No.3, pp. 1219-1230, 2022, DOI:10.32604/csse.2022.028224 - 09 May 2022

Abstract Safety helmet-wearing detection is an essential part of the intelligent monitoring system. To improve the speed and accuracy of detection, especially small targets and occluded objects, it presents a novel and efficient detector model. The underlying core algorithm of this model adopts the YOLOv5 (You Only Look Once version 5) network with the best comprehensive detection performance. It is improved by adding an attention mechanism, a CIoU (Complete Intersection Over Union) Loss function, and the Mish activation function. First, it applies the attention mechanism in the feature extraction. The network can learn the weight of… More >

Dokyung Hwang¹, Hyeonmin Ro¹, Naejoung Kwak², Jinsang Hwang³, Dongju Kim^1,*

CMC-Computers, Materials & Continua, Vol.72, No.3, pp. 4411-4431, 2022, DOI:10.32604/cmc.2022.025378 - 21 April 2022

Abstract A novel practical and universal method of mask-wearing detection has been proposed to prevent viral respiratory infections. The proposed method quickly and accurately detects mask and facial regions using well-trained You Only Look Once (YOLO) detector, then applies image coordinates of the detected bounding box (bbox). First, the data that is used to train our model is collected under various circumstances such as light disturbances, distances, time variations, and different climate conditions. It also contains various mask types to detect in general and universal application of the model. To detect mask-wearing status, it is important… More >

Wei Chen¹, Mi Liu^1,*, Xuhong Zhou², Jiandong Pan³, Haozhi Tan⁴

CMC-Computers, Materials & Continua, Vol.72, No.2, pp. 3159-3174, 2022, DOI:10.32604/cmc.2022.026664 - 29 March 2022

Abstract In construction, it is important to check whether workers wear safety helmets in real time. We proposed using an unmanned aerial vehicle (UAV) to monitor construction workers in real time. As the small target of aerial photography poses challenges to safety-helmet-wearing detection, we proposed an improved YOLOv4 model to detect the helmet-wearing condition in aerial photography: (1) By increasing the dimension of the effective feature layer of the backbone network, the model's receptive field is reduced, and the utilization rate of fine-grained features is improved. (2) By introducing the cross stage partial (CSP) structure into… More >