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

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 too time-intensive, thus using a… 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

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 that of ordinary plywood. Among… 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

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 the tested one; the error… 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

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 between wearable Internet of Things… More >

Sakorn Mekruksavanich¹, Anuchit Jitpattanakul^2,*

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

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 activities of construction workers. The… More >

K. M. Monica, R. Parvathi^*

CMC-Computers, Materials & Continua, Vol.74, No.3, pp. 6229-6249, 2023, DOI:10.32604/cmc.2023.032273

Abstract Human Activity Recognition (HAR) has always been a difficult task to tackle. It is mainly used in security surveillance, human-computer interaction, and health care as an assistive or diagnostic technology in combination with other technologies such as the Internet of Things (IoT). Human Activity Recognition data can be recorded with the help of sensors, images, or smartphones. Recognizing daily routine-based human activities such as walking, standing, sitting, etc., could be a difficult statistical task to classify into categories and hence 2-dimensional Convolutional Neural Network (2D CNN) MODEL, Long Short Term Memory (LSTM) Model, Bidirectional long short-term memory (Bi-LSTM) are used… More >

Mengqi Cong^*, Yang Zhang, Yunlong Zhang, Xiao Liu, Yalin Lu, Xiaoping Li

Journal of Renewable Materials, Vol.11, No.4, pp. 1977-1989, 2023, DOI:10.32604/jrm.2023.023849

Abstract Magnesium alloy has been considered as one of the third-generation biomaterials for the regeneration and support of functional bone tissue. As a regeneration implant material with great potential applications, in-situ Mg₂Si phase reinforced Mg-6Zn cast alloy was comprehensively studied and expected to possess excellent mechanical properties via the refining and modifying of Mg₂Si reinforcements. The present study demonstrates that the primary and eutectic Mg₂Si phase can be greatly modified by the yttrium (Y) addition. The size of the primary Mg₂Si phases can be reduced to ~20 μm with an addition of 0.5 wt.% Y. This phenomenon is mainly attributed to… More > Graphic Abstract

R. Selvam^1,*, L. Ganesh Babu², Joji Thomas³, R. Prakash¹, T. Karthikeyan¹, T. Maridurai⁴

FDMP-Fluid Dynamics & Materials Processing, Vol.19, No.3, pp. 569-577, 2023, DOI:10.32604/fdmp.2022.022187

Abstract Hybrid materials collected from organic and inorganic sources, which are traditionally used as brake lining materials, generally include fly ash, cashew shell powder, phenolic resins, aluminium wool, barites, lime powder, carbon powder and copper powder. The present research focuses on the specific effects produced by fly ash and aims to provide useful indications for the replacement of asbestos due to the health hazards caused by the related fibers. Furthermore, the financial implications related to the use of large-volume use of fly ash, lime stone and cashew shell powder, readily available in most countries in the world, are also discussed. It… More > Graphic Abstract

K. Sugapriya^*, S. Omkumar

Intelligent Automation & Soft Computing, Vol.36, No.1, pp. 803-818, 2023, DOI:10.32604/iasc.2023.032163

Abstract The antenna plays an essential role in the medical industry. The short-range 5^th Generation (5G) communication can be used for seamless transmission, reception, patient monitoring, sensing and measuring various processes at high speeds. A passive Ultra Wide Band (UWB) antenna, used as a sensor in the measurement of Prothrombin Time (PT) i.e., blood clot is being proposed. The investigated micro-strip patch UWB antenna operating in the frequency range of 3.1 to 10.6 GHz consists of a circular patch with a diamond-shaped slot made of jeans substrate material with good sensing properties is accomplished by adjusting the copper thickness of the… More >

Chih-Ta Yen^1,*, Tz-Yun Chen², Un-Hung Chen³, Guo-Chang Wang³, Zong-Xian Chen³

CMC-Computers, Materials & Continua, Vol.74, No.1, pp. 83-99, 2023, DOI:10.32604/cmc.2023.032739

Abstract A system for classifying four basic table tennis strokes using wearable devices and deep learning networks is proposed in this study. The wearable device consisted of a six-axis sensor, Raspberry Pi 3, and a power bank. Multiple kernel sizes were used in convolutional neural network (CNN) to evaluate their performance for extracting features. Moreover, a multiscale CNN with two kernel sizes was used to perform feature fusion at different scales in a concatenated manner. The CNN achieved recognition of the four table tennis strokes. Experimental data were obtained from 20 research participants who wore sensors on the back of their… More >