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Search Results (5)
  • Open Access

    REVIEW

    Emerging Trends in Damage Tolerance Assessment: A Review of Smart Materials and Self-Repairable Structures

    Ali Akbar Firoozi1,*, Ali Asghar Firoozi2

    Structural Durability & Health Monitoring, Vol.18, No.1, pp. 1-18, 2024, DOI:10.32604/sdhm.2023.044573

    Abstract The discipline of damage tolerance assessment has experienced significant advancements due to the emergence of smart materials and self-repairable structures. This review offers a comprehensive look into both traditional and innovative methodologies employed in damage tolerance assessment. After a detailed exploration of damage tolerance concepts and their historical progression, the review juxtaposes the proven techniques of damage assessment with the cutting-edge innovations brought about by smart materials and self-repairable structures. The subsequent sections delve into the synergistic integration of smart materials with self-repairable structures, marking a pivotal stride in damage tolerance by establishing an autonomous system for immediate damage identification… More >

  • Open Access

    Time-Efficient Blockchain Framework for Improved Data Transmission in Autonomous Systems

    Abdulrahman M. Abdulghani, Wilbur L. Walters, Khalid H. Abed*

    Journal of Blockchain and Intelligent Computing, Vol.1, pp. 1-13, 2023, DOI:10.32604/jbic.2023.041340

    Abstract Blockchain technology is increasingly used to design trustworthy and reliable platforms for sharing information in a plethora of industries. It is a decentralized system that acts as an immutable record for storing data. It has the potential to disrupt a range of fields that rely on data, including autonomous systems like Unmanned Aerial Vehicles (UAVs). In this paper, we propose a framework based on blockchain and distributed ledger technology to improve transmission time and provide a secured and trusted method for UAVs to transfer data to the consumer efficiently while maintaining data reliability. The results show that our framework enables… More >

  • Open Access

    ARTICLE

    Lightweight Network Ensemble Architecture for Environmental Perception on the Autonomous System

    Yingpeng Dai1, Junzheng Wang1, Jing Li1,*, Lingfeng Meng2, Songfeng Wang2,*

    CMES-Computer Modeling in Engineering & Sciences, Vol.134, No.1, pp. 135-156, 2023, DOI:10.32604/cmes.2022.021525

    Abstract It is important for the autonomous system to understand environmental information. For the autonomous system, it is desirable to have a strong generalization ability to deal with different complex environmental information, as well as have high accuracy and quick inference speed. Network ensemble architecture is a good choice to improve network performance. However, it is unsuitable for real-time applications on the autonomous system. To tackle this problem, a new neural network ensemble named partial-shared ensemble network (PSENet) is presented. PSENet changes network ensemble architecture from parallel architecture to scatter architecture and merges multiple component networks together to accelerate the inference… More >

  • Open Access

    ARTICLE

    Autonomous Unmanned Aerial Vehicles Based Decision Support System for Weed Management

    Ashit Kumar Dutta1,*, Yasser Albagory2, Abdul Rahaman Wahab Sait3, Ismail Mohamed Keshta1

    CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 899-915, 2022, DOI:10.32604/cmc.2022.026783

    Abstract Recently, autonomous systems become a hot research topic among industrialists and academicians due to their applicability in different domains such as healthcare, agriculture, industrial automation, etc. Among the interesting applications of autonomous systems, their applicability in agricultural sector becomes significant. Autonomous unmanned aerial vehicles (UAVs) can be used for suitable site-specific weed management (SSWM) to improve crop productivity. In spite of substantial advancements in UAV based data collection systems, automated weed detection still remains a tedious task owing to the high resemblance of weeds to the crops. The recently developed deep learning (DL) models have exhibited effective performance in several… More >

  • Open Access

    ARTICLE

    Evaluating the Topology Coverage of BGP Monitors

    Shen Su1, Zhihong Tian1, Jing Qiu1, *, Yu Jiang1, *, Yanbin Sun1, Mohan Li1, Dunqiu Fan2, Haining Yu3

    CMC-Computers, Materials & Continua, Vol.62, No.3, pp. 1397-1412, 2020, DOI:10.32604/cmc.2020.06319

    Abstract BGP monitors are currently the main data resource of AS-level topology measurement, and the integrity of measurement result is limited to the location of such BGP monitors. However, there is currently no work to conduct a comprehensive study of the range of measurement results for a single BGP monitor. In this paper, we take the first step to describe the observed topology of each BGP monitor. To that end, we first investigate the construction and theoretical up-limit of the measured topology of a BGP monitor based on the valley-free model, then we evaluate the individual parts of the measured topology… More >

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