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  • Open Access

    PROCEEDINGS

    Experimental Study of the Electrical Resistance of Graphene OxideReinforced Cement-Based Composites with Notch or Rebar

    Yangao Hu1,*

    The International Conference on Computational & Experimental Engineering and Sciences, Vol.27, No.3, pp. 1-1, 2023, DOI:10.32604/icces.2023.09773

    Abstract This paper investigates the effects of graphene oxide (GO), notch depth, rebar, and load on the resistivity of cement paste and mortar. The electrical conductivity of GO/cement composite reaches its maximum value when the GO content is 0.03%, which is approximately 50% higher compared to the composite without GO. The resistivity of GO/cement composite shows significant changes with increasing load from 0 to 40 kN. The gauge factor for compressive loading varies from about 26 to 73 for different GO contents. Moreover, the resistivity variation with the notch depth in GO/cement is found to be much greater than that in… More >

  • Open Access

    ARTICLE

    Research on Transmission Line Tower Tilting and Foundation State Monitoring Technology Based on Multi-Sensor Cooperative Detection and Correction

    Guangxin Zhang1, Minghui Liu2, Shichao Cheng3, Minzhen Wang1,*, Changshun Zhao4, Hongdan Zhao5, Gaiming Zhong1

    Energy Engineering, Vol.121, No.1, pp. 169-185, 2024, DOI:10.32604/ee.2023.027907

    Abstract The transmission line tower will be affected by bad weather and artificial subsidence caused by the foundation and other factors in the power transmission. The tower’s tilt and severe deformation will cause the building to collapse. Many small changes caused the tower’s collapse, but the early staff often could not intuitively notice the changes in the tower’s state. In the current tower online monitoring system, terminal equipment often needs to replace batteries frequently due to premature exhaustion of power. According to the need for real-time measurement of power line tower, this research designed a real-time monitoring device monitoring the transmission… More >

  • Open Access

    ARTICLE

    Internet of Things Based Smart Irrigation System Using ESP WROOM 32

    Krish R. Mehta, K. Jayant Naidu, Madhav Baheti, Dev Parmar, A. Sharmila*

    Journal on Internet of Things, Vol.5, pp. 45-55, 2023, DOI:10.32604/jiot.2023.043102

    Abstract Farming has been the most prominent and fundamental activity for generations. As the population has been multiplying exponentially, the demand for agricultural yield is growing relentlessly. Such high demand in production through traditional farming methodologies often falls short in terms of efficiency due to the limitations of manual labour. In the era of digitization, smart agricultural solutions have been emerging through the windows of Internet of Things and Artificial Intelligence to improve resource management, optimize the process of farming and enhance the yield of crops, hence, ensuring sustainable growth of the increasing production. By implementing modern technologies in the field… More >

  • Open Access

    ARTICLE

    Adaptive Multi-Feature Fusion for Vehicle Micro-Motor Noise Recognition Considering Auditory Perception

    Ting Zhao1, Weiping Ding1, Haibo Huang1, Yudong Wu1,2,*

    Sound & Vibration, Vol.57, pp. 133-153, 2023, DOI:10.32604/sv.2023.044203

    Abstract The deployment of vehicle micro-motors has witnessed an expansion owing to the progression in electrification and intelligent technologies. However, some micro-motors may exhibit design deficiencies, component wear, assembly errors, and other imperfections that may arise during the design or manufacturing phases. Consequently, these micro-motors might generate anomalous noises during their operation, consequently exerting a substantial adverse influence on the overall comfort of drivers and passengers. Automobile micro-motors exhibit a diverse array of structural variations, consequently leading to the manifestation of a multitude of distinctive auditory irregularities. To address the identification of diverse forms of abnormal noise, this research presents a… More > Graphic Abstract

    Adaptive Multi-Feature Fusion for Vehicle Micro-Motor Noise Recognition Considering Auditory Perception

  • Open Access

    ARTICLE

    Privacy Enhanced Mobile User Authentication Method Using Motion Sensors

    Chunlin Xiong1,2, Zhengqiu Weng3,4,*, Jia Liu1, Liang Gu2, Fayez Alqahtani5, Amr Gafar6, Pradip Kumar Sharma7

    CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.3, pp. 3013-3032, 2024, DOI:10.32604/cmes.2023.031088

    Abstract With the development of hardware devices and the upgrading of smartphones, a large number of users save privacy-related information in mobile devices, mainly smartphones, which puts forward higher demands on the protection of mobile users’ privacy information. At present, mobile user authentication methods based on human-computer interaction have been extensively studied due to their advantages of high precision and non-perception, but there are still shortcomings such as low data collection efficiency, untrustworthy participating nodes, and lack of practicability. To this end, this paper proposes a privacy-enhanced mobile user authentication method with motion sensors, which mainly includes: (1) Construct a smart… More >

  • Open Access

    REVIEW

    An Insight Survey on Sensor Errors and Fault Detection Techniques in Smart Spaces

    Sheetal Sharma1,2, Kamali Gupta1, Deepali Gupta1, Shalli Rani1,*, Gaurav Dhiman3,4,5,6,7,*

    CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.3, pp. 2029-2059, 2024, DOI:10.32604/cmes.2023.029997

    Abstract The widespread adoption of the Internet of Things (IoT) has transformed various sectors globally, making them more intelligent and connected. However, this advancement comes with challenges related to the effectiveness of IoT devices. These devices, present in offices, homes, industries, and more, need constant monitoring to ensure their proper functionality. The success of smart systems relies on their seamless operation and ability to handle faults. Sensors, crucial components of these systems, gather data and contribute to their functionality. Therefore, sensor faults can compromise the system’s reliability and undermine the trustworthiness of smart environments. To address these concerns, various techniques and… More > Graphic Abstract

    An Insight Survey on Sensor Errors and Fault Detection Techniques in Smart Spaces

  • Open Access

    ARTICLE

    An Optimal Node Localization in WSN Based on Siege Whale Optimization Algorithm

    Thi-Kien Dao1, Trong-The Nguyen1,2,*

    CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.3, pp. 2201-2237, 2024, DOI:10.32604/cmes.2023.029880

    Abstract Localization or positioning scheme in Wireless sensor networks (WSNs) is one of the most challenging and fundamental operations in various monitoring or tracking applications because the network deploys a large area and allocates the acquired location information to unknown devices. The metaheuristic approach is one of the most advantageous ways to deal with this challenging issue and overcome the disadvantages of the traditional methods that often suffer from computational time problems and small network deployment scale. This study proposes an enhanced whale optimization algorithm that is an advanced metaheuristic algorithm based on the siege mechanism (SWOA) for node localization in… More >

  • Open Access

    ARTICLE

    Force Sensitive Resistors-Based Real-Time Posture Detection System Using Machine Learning Algorithms

    Arsal Javaid1, Areeb Abbas1, Jehangir Arshad1, Mohammad Khalid Imam Rahmani2,*, Sohaib Tahir Chauhdary3, Mujtaba Hussain Jaffery1, Abdulbasid S. Banga2,*

    CMC-Computers, Materials & Continua, Vol.77, No.2, pp. 1795-1814, 2023, DOI:10.32604/cmc.2023.044140

    Abstract To detect the improper sitting posture of a person sitting on a chair, a posture detection system using machine learning classification has been proposed in this work. The addressed problem correlates to the third Sustainable Development Goal (SDG), ensuring healthy lives and promoting well-being for all ages, as specified by the World Health Organization (WHO). An improper sitting position can be fatal if one sits for a long time in the wrong position, and it can be dangerous for ulcers and lower spine discomfort. This novel study includes a practical implementation of a cushion consisting of a grid of 3… More >

  • Open Access

    ARTICLE

    Flexible Global Aggregation and Dynamic Client Selection for Federated Learning in Internet of Vehicles

    Tariq Qayyum1, Zouheir Trabelsi1,*, Asadullah Tariq1, Muhammad Ali2, Kadhim Hayawi3, Irfan Ud Din4

    CMC-Computers, Materials & Continua, Vol.77, No.2, pp. 1739-1757, 2023, DOI:10.32604/cmc.2023.043684

    Abstract Federated Learning (FL) enables collaborative and privacy-preserving training of machine learning models within the Internet of Vehicles (IoV) realm. While FL effectively tackles privacy concerns, it also imposes significant resource requirements. In traditional FL, trained models are transmitted to a central server for global aggregation, typically in the cloud. This approach often leads to network congestion and bandwidth limitations when numerous devices communicate with the same server. The need for Flexible Global Aggregation and Dynamic Client Selection in FL for the IoV arises from the inherent characteristics of IoV environments. These include diverse and distributed data sources, varying data quality,… More >

  • Open Access

    ARTICLE

    Adaptive Deep Learning Model to Enhance Smart Greenhouse Agriculture

    Medhat A. Tawfeek1,2, Nacim Yanes3,4, Leila Jamel5,*, Ghadah Aldehim5, Mahmood A. Mahmood1,6

    CMC-Computers, Materials & Continua, Vol.77, No.2, pp. 2545-2564, 2023, DOI:10.32604/cmc.2023.042179

    Abstract The trend towards smart greenhouses stems from various factors, including a lack of agricultural land area owing to population concentration and housing construction on agricultural land, as well as water shortages. This study proposes building a full farming adaptation model that depends on current sensor readings and available datasets from different agricultural research centers. The proposed model uses a one-dimensional convolutional neural network (CNN) deep learning model to control the growth of strategic crops, including cucumber, pepper, tomato, and bean. The proposed model uses the Internet of Things (IoT) to collect data on agricultural operations and then uses this data… More >

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