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  • Open Access

    REVIEW

    A Survey on Sensor- and Communication-Based Issues of Autonomous UAVs

    Pavlo Mykytyn1,2,*, Marcin Brzozowski1, Zoya Dyka1,2, Peter Langendoerfer1,2

    CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.2, pp. 1019-1050, 2024, DOI:10.32604/cmes.2023.029075

    Abstract The application field for Unmanned Aerial Vehicle (UAV) technology and its adoption rate have been increasing steadily in the past years. Decreasing cost of commercial drones has enabled their use at a scale broader than ever before. However, increasing the complexity of UAVs and decreasing the cost, both contribute to a lack of implemented security measures and raise new security and safety concerns. For instance, the issue of implausible or tampered UAV sensor measurements is barely addressed in the current research literature and thus, requires more attention from the research community. The goal of this survey is to extensively review… More >

  • Open Access

    ARTICLE

    Computational Intelligence Driven Secure Unmanned Aerial Vehicle Image Classification in Smart City Environment

    Firas Abedi1, Hayder M. A. Ghanimi2, Abeer D. Algarni3, Naglaa F. Soliman3,*, Walid El-Shafai4,5, Ali Hashim Abbas6, Zahraa H. Kareem7, Hussein Muhi Hariz8, Ahmed Alkhayyat9

    Computer Systems Science and Engineering, Vol.47, No.3, pp. 3127-3144, 2023, DOI:10.32604/csse.2023.038959

    Abstract Computational intelligence (CI) is a group of nature-simulated computational models and processes for addressing difficult real-life problems. The CI is useful in the UAV domain as it produces efficient, precise, and rapid solutions. Besides, unmanned aerial vehicles (UAV) developed a hot research topic in the smart city environment. Despite the benefits of UAVs, security remains a major challenging issue. In addition, deep learning (DL) enabled image classification is useful for several applications such as land cover classification, smart buildings, etc. This paper proposes novel meta-heuristics with a deep learning-driven secure UAV image classification (MDLS-UAVIC) model in a smart city environment.… More >

  • Open Access

    ARTICLE

    The Effect of Lateral Offset Distance on the Aerodynamics and Fuel Economy of Vehicle Queues

    Lili Lei*, Ze Li, Haichao Zhou, Jing Wang, Wei Lin

    FDMP-Fluid Dynamics & Materials Processing, Vol.20, No.1, pp. 147-163, 2024, DOI:10.32604/fdmp.2023.030158

    Abstract The vehicle industry is always in search of breakthrough energy-saving and emission-reduction technologies. In recent years, vehicle intelligence has progressed considerably, and researchers are currently trying to take advantage of these developments. Here we consider the case of many vehicles forming a queue, i.e., vehicles traveling at a predetermined speed and distance apart. While the majority of existing studies on this subject have focused on the influence of the longitudinal vehicle spacing, vehicle speed, and the number of vehicles on aerodynamic drag and fuel economy, this study considers the lateral offset distance of the vehicle queue. The group fuel consumption… More >

  • Open Access

    ARTICLE

    Multi-Objective Prediction and Optimization of Vehicle Acoustic Package Based on ResNet Neural Network

    Yunru Wu1, Xiangbo Liu1, Haibo Huang1,2,*, Yudong Wu1, Weiping Ding1,2, Mingliang Yang1,2,*

    Sound & Vibration, Vol.57, pp. 73-95, 2023, DOI:10.32604/sv.2023.044601

    Abstract Vehicle interior noise has emerged as a crucial assessment criterion for automotive NVH (Noise, Vibration, and Harshness). When analyzing the NVH performance of the vehicle body, the traditional SEA (Statistical Energy Analysis) simulation technology is usually limited by the accuracy of the material parameters obtained during the acoustic package modeling and the limitations of the application conditions. In order to effectively solve these shortcomings, based on the analysis of the vehicle noise transmission path, a multi-level objective decomposition architecture of the interior noise at the driver’s right ear is established. Combined with the data-driven method, the ResNet neural network model… More >

  • Open Access

    ARTICLE

    Research on Human-Vehicle-Road Friendliness Based on Improved SH-GH-ADD Control

    Yangyang Bao, Mingliang Yang, Haibo Huang, Liyuan Liu, Honglin Zhu, Weiping Ding*

    Sound & Vibration, Vol.57, pp. 45-68, 2023, DOI:10.32604/sv.2023.043279

    Abstract The hub-driven virtual rail train is a novel urban transportation system that amalgamates the benefits of modern trams and buses. However, this system is plagued by issues such as decreased ride comfort and severe deformation of urban roads due to the increase in sprung mass and long-term rolling at the same position. To address these concerns and improve the human-vehicle-road friendliness of the virtual rail train, we propose an Improved Sky-Ground Hook and Acceleration-Driven Damper control (Improved SH-GH-ADD control) strategy for the semi-active suspension system. This control monitors the vibration acceleration signal of the unsprung mass in real-time and selects… More >

  • Open Access

    ARTICLE

    Traffic Sign Recognition for Autonomous Vehicle Using Optimized YOLOv7 and Convolutional Block Attention Module

    P. Kuppusamy1,*, M. Sanjay1, P. V. Deepashree1, C. Iwendi2

    CMC-Computers, Materials & Continua, Vol.77, No.1, pp. 445-466, 2023, DOI:10.32604/cmc.2023.042675

    Abstract The infrastructure and construction of roads are crucial for the economic and social development of a region, but traffic-related challenges like accidents and congestion persist. Artificial Intelligence (AI) and Machine Learning (ML) have been used in road infrastructure and construction, particularly with the Internet of Things (IoT) devices. Object detection in Computer Vision also plays a key role in improving road infrastructure and addressing traffic-related problems. This study aims to use You Only Look Once version 7 (YOLOv7), Convolutional Block Attention Module (CBAM), the most optimized object-detection algorithm, to detect and identify traffic signs, and analyze effective combinations of adaptive… More >

  • Open Access

    ARTICLE

    LSTDA: Link Stability and Transmission Delay Aware Routing Mechanism for Flying Ad-Hoc Network (FANET)

    Farman Ali1, Khalid Zaman2, Babar Shah3, Tariq Hussain4, Habib Ullah5, Altaf Hussain5, Daehan Kwak6,*

    CMC-Computers, Materials & Continua, Vol.77, No.1, pp. 963-981, 2023, DOI:10.32604/cmc.2023.040628

    Abstract The paper presents a new protocol called Link Stability and Transmission Delay Aware (LSTDA) for Flying Ad-hoc Network (FANET) with a focus on network corridors (NC). FANET consists of Unmanned Aerial Vehicles (UAVs) that face challenges in avoiding transmission loss and delay while ensuring stable communication. The proposed protocol introduces a novel link stability with network corridors priority node selection to check and ensure fair communication in the entire network. The protocol uses a Red-Black (R-B) tree to achieve maximum channel utilization and an advanced relay approach. The paper evaluates LSTDA in terms of End-to-End Delay (E2ED), Packet Delivery Ratio… More >

  • Open Access

    ARTICLE

    NPBMT: A Novel and Proficient Buffer Management Technique for Internet of Vehicle-Based DTNs

    Sikandar Khan1, Khalid Saeed1, Muhammad Faran Majeed2,*, Salman A. AlQahtani3, Khursheed Aurangzeb3, Muhammad Shahid Anwar4,*

    CMC-Computers, Materials & Continua, Vol.77, No.1, pp. 1303-1323, 2023, DOI:10.32604/cmc.2023.039697

    Abstract Delay Tolerant Networks (DTNs) have the major problem of message delay in the network due to a lack of end-to-end connectivity between the nodes, especially when the nodes are mobile. The nodes in DTNs have limited buffer storage for storing delayed messages. This instantaneous sharing of data creates a low buffer/shortage problem. Consequently, buffer congestion would occur and there would be no more space available in the buffer for the upcoming messages. To address this problem a buffer management policy is proposed named “A Novel and Proficient Buffer Management Technique (NPBMT) for the Internet of Vehicle-Based DTNs”. NPBMT combines appropriate-size… More >

  • Open Access

    ARTICLE

    Multi-Modal Scene Matching Location Algorithm Based on M2Det

    Jiwei Fan, Xiaogang Yang*, Ruitao Lu, Qingge Li, Siyu Wang

    CMC-Computers, Materials & Continua, Vol.77, No.1, pp. 1031-1052, 2023, DOI:10.32604/cmc.2023.039582

    Abstract In recent years, many visual positioning algorithms have been proposed based on computer vision and they have achieved good results. However, these algorithms have a single function, cannot perceive the environment, and have poor versatility, and there is a certain mismatch phenomenon, which affects the positioning accuracy. Therefore, this paper proposes a location algorithm that combines a target recognition algorithm with a depth feature matching algorithm to solve the problem of unmanned aerial vehicle (UAV) environment perception and multi-modal image-matching fusion location. This algorithm was based on the single-shot object detector based on multi-level feature pyramid network (M2Det) algorithm and… 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 >

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