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  • Open Access

    ARTICLE

    Research on Metaverse Security and Forensics

    Guangjun Liang1,2,3, Jianfang Xin4,*, Qun Wang1,2, Xueli Ni1,2,3, Xiangmin Guo1,2,3, Pu Chen1

    CMC-Computers, Materials & Continua, Vol.77, No.1, pp. 799-825, 2023, DOI:10.32604/cmc.2023.038403

    Abstract As a subversive concept, the metaverse has recently attracted widespread attention around the world and has set off a wave of enthusiasm in academic, industrial, and investment circles. However, while the metaverse brings unprecedented opportunities for transformation to human society, it also contains related risks. Metaverse is a digital living space with information infrastructure, interoperability system, content production system, and value settlement system as the underlying structure in which the inner core is to connect real residents through applications and identities. Through social incentives and governance rules, the metaverse reflects the digital migration of human society. This article will conduct… More >

  • Open Access

    ARTICLE

    Deep Pyramidal Residual Network for Indoor-Outdoor Activity Recognition Based on Wearable Sensor

    Sakorn Mekruksavanich1, Narit Hnoohom2, Anuchit Jitpattanakul3,4,*

    Intelligent Automation & Soft Computing, Vol.37, No.3, pp. 2669-2686, 2023, DOI:10.32604/iasc.2023.038549

    Abstract Recognition of human activity is one of the most exciting aspects of time-series classification, with substantial practical and theoretical implications. Recent evidence indicates that activity recognition from wearable sensors is an effective technique for tracking elderly adults and children in indoor and outdoor environments. Consequently, researchers have demonstrated considerable passion for developing cutting-edge deep learning systems capable of exploiting unprocessed sensor data from wearable devices and generating practical decision assistance in many contexts. This study provides a deep learning-based approach for recognizing indoor and outdoor movement utilizing an enhanced deep pyramidal residual model called SenPyramidNet and motion information from wearable… More >

  • Open Access

    PROCEEDINGS

    Rate Effect of Adhesive Wear Due to Asperity Plowing

    Jianqiao Hu1,2,*, Hengxu Song1, Xiaoming Liu1,2

    The International Conference on Computational & Experimental Engineering and Sciences, Vol.26, No.1, pp. 1-1, 2023, DOI:10.32604/icces.2023.010554

    Abstract Material wear between contact surfaces with relatively sliding can be related to the failure of elevated asperities at small scales. The asperity wear depends on various factors, including material properties, interfacial adhesion, and friction velocity. In this study, using a series of materials characterized by the modified coarse-grained potentials, we studied the rate effect of adhesive wear at the asperity level over a wide range of plowing conditions. The results showed that increasing plowing velocity leads to the transition of the wear mechanism from plasticity-induced asperity smoothing to the formation of fractured debris and thus breaks down the Archard wear… More >

  • Open Access

    PROCEEDINGS

    Rate Effect of Adhesive Wear due to Asperity Plowing

    Jianqiao Hu1,2,*, Hengxu Song1, Xiaoming Liu1,2

    The International Conference on Computational & Experimental Engineering and Sciences, Vol.25, No.3, pp. 1-1, 2023, DOI:10.32604/icces.2023.010554

    Abstract Material wear between contact surfaces with relatively sliding can be related to the failure of elevated asperities at small scales. The asperity wear depends on various factors, including material properties, interfacial adhesion, and friction velocity. In this study, using a series of materials characterized by the modified coarse-grained potentials, we studied the rate effect of adhesive wear at the asperity level over a wide range of plowing conditions. The results showed that increasing plowing velocity leads to the transition of the wear mechanism from plasticity-induced asperity smoothing to the formation of fractured debris and thus breaks down the Archard wear… More >

  • Open Access

    ARTICLE

    Microstructural Dependence of Friction and Wear Behavior in Biological Shells

    Xin Wang1,3, Ying Yan1,3, Hongmei Ji1,3,*, Xiaowu Li1,2,*

    Journal of Renewable Materials, Vol.11, No.8, pp. 3297-3308, 2023, DOI:10.32604/jrm.2023.027066

    Abstract As an essential renewable mineral resource, mollusk shells can be used as handicrafts, building materials, adsorbents, etc. However, there are few reports on the wear resistance of their structures. The Vicker’s hardness and friction, and wear resistance of different microstructures in mollusk shells were comparatively studied in the present work. The hardness of prismatic structures is lower than that of cross-lamellar and nacreous structures. However, the experimental results of sliding tests indicate that the prismatic structure exhibits the best anti-wear ability compared with foliated, crossed-lamellar, and nacreous structures. The anti-wear and hardness do not present a positive correlation, as the… More > Graphic Abstract

    Microstructural Dependence of Friction and Wear Behavior in Biological Shells

  • Open Access

    ARTICLE

    A Double-Compensation-Based Federated Learning Scheme for Data Privacy Protection in a Social IoT Scenario

    Junqi Guo1,2, Qingyun Xiong1,*, Minghui Yang1, Ziyun Zhao1

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

    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 delay and data heterogeneity problems.… More >

  • Open Access

    ARTICLE

    Higher Order OAM Mode Generation Using Wearable Antenna for 5G NR Bands

    Shehab Khan Noor1, Arif Mawardi Ismail1, Mohd Najib Mohd Yasin1,*, 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

    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 was simulated, analyzed, fabricated, and… More >

  • Open Access

    ARTICLE

    A Model for Helmet-Wearing Detection of Non-Motor Drivers Based on YOLOv5s

    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

    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 the network to get more… More >

  • Open Access

    ARTICLE

    Improved Transient Search Optimization with Machine Learning Based Behavior Recognition on Body Sensor Data

    Baraa Wasfi Salim1, Bzar Khidir Hussan2, Zainab Salih Ageed3, Subhi R. M. Zeebaree4,*

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

    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 ITSOML-BR technique collects data from… More >

  • Open Access

    ARTICLE

    Non-Contact Physiological Measurement System for Wearing Masks During the Epidemic

    Shu-Yin Chiang*, Dong-Ye Wu

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

    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 rate, and forehead temperature for… More >

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