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  • Open Access

    ARTICLE

    Privacy-Preserving and Lightweight V2I and V2V Authentication Protocol Using Blockchain Technology

    Muhammad Imran Ghafoor1, Awad Bin Naeem2,*, Biswaranjan Senapati3, Md. Sakiul Islam Sudman4, Satyabrata Pradhan5, Debabrata Das6, Friban Almeida6, Hesham A. Sakr7

    Intelligent Automation & Soft Computing, Vol.39, No.5, pp. 783-803, 2024, DOI:10.32604/iasc.2024.050819 - 31 October 2024

    Abstract The confidentiality of pseudonymous authentication and secure data transmission is essential for the protection of information and mitigating risks posed by compromised vehicles. The Internet of Vehicles has meaningful applications, enabling connected and autonomous vehicles to interact with infrastructure, sensors, computing nodes, humans, and fellow vehicles. Vehicular hoc networks play an essential role in enhancing driving efficiency and safety by reducing traffic congestion while adhering to cryptographic security standards. This paper introduces a privacy-preserving Vehicle-to-Infrastructure authentication, utilizing encryption and the Moore curve. The proposed approach enables a vehicle to deduce the planned itinerary of Roadside More >

  • Open Access

    ARTICLE

    Research on the Microstructure Construction Technology of Fully Degraded Polymer Vascular Stent Based on Electric Field Driven 3D Printing

    Yanpu Chao1,*, Fulai Cao1, Hao Yi2,3,*, Shuai Lu1, Yaohui Li1, Hui Cen1

    FDMP-Fluid Dynamics & Materials Processing, Vol.20, No.11, pp. 2489-2508, 2024, DOI:10.32604/fdmp.2024.051962 - 28 October 2024

    Abstract The so-called fourth-generation biodegradable vascular stent has become a research hotspot in the field of bio-engineering because of its good degradation ability and drug-loading characteristics. However, the preparation of polymer-degraded vascular stents is affected by known problem such as poor process flexibility, low forming accuracy, large diameter wall thickness, limited complex pore structure, weak mechanical properties of radial support and high process cost. In this study, a deposition technique based on a high-voltage electric-field-driven continuous rotating jet is proposed to fabricate fully degraded polymer vascular stents. The experimental results show that, due to the rotation… More > Graphic Abstract

    Research on the Microstructure Construction Technology of Fully Degraded Polymer Vascular Stent Based on Electric Field Driven 3D Printing

  • Open Access

    ARTICLE

    Implementation of a Nesting Repair Technology for Transportation Pipeline Repair

    Yijun Gao1,2, Yong Wang1,*, Qing Na1, Jiawei Zhang1, Aixiang Wu1

    FDMP-Fluid Dynamics & Materials Processing, Vol.20, No.11, pp. 2443-2458, 2024, DOI:10.32604/fdmp.2024.051385 - 28 October 2024

    Abstract Filling methods in the mining industry can maximize the recovery of mineral resources and protect the underground and surface environments. In recent years, such methods have been widely used in metal mines where pipeline transportation typically plays a decisive role in the safety and stability of the entire filling system. Because the filling slurry contains a large percentage of solid coarse particles, the involved pipeline is typically eroded and often damaged during such a process. A possible solution is the so-called nesting repair technology. In the present study, nesting a 127 mm outer diameter pipeline… More >

  • Open Access

    ARTICLE

    Optimizing Internet of Things Device Security with a Globalized Firefly Optimization Algorithm for Attack Detection

    Arkan Kh Shakr Sabonchi*

    Journal on Artificial Intelligence, Vol.6, pp. 301-322, 2024, DOI:10.32604/jai.2024.056552 - 18 October 2024

    Abstract The phenomenal increase in device connectivity is making the signaling and resource-based operational integrity of networks at the node level increasingly prone to distributed denial of service (DDoS) attacks. The current growth rate in the number of Internet of Things (IoT) attacks executed at the time of exchanging data over the Internet represents massive security hazards to IoT devices. In this regard, the present study proposes a new hybrid optimization technique that combines the firefly optimization algorithm with global searches for use in attack detection on IoT devices. We preprocessed two datasets, CICIDS and UNSW-NB15,… More >

  • Open Access

    ARTICLE

    LQTTrack: Multi-Object Tracking by Focusing on Low-Quality Targets Association

    Suya Li1, Ying Cao1,*, Hengyi Ren2, Dongsheng Zhu3, Xin Xie1

    CMC-Computers, Materials & Continua, Vol.81, No.1, pp. 1449-1470, 2024, DOI:10.32604/cmc.2024.056824 - 15 October 2024

    Abstract Multi-object tracking (MOT) has seen rapid improvements in recent years. However, frequent occlusion remains a significant challenge in MOT, as it can cause targets to become smaller or disappear entirely, resulting in low-quality targets, leading to trajectory interruptions and reduced tracking performance. Different from some existing methods, which discarded the low-quality targets or ignored low-quality target attributes. LQTTrack, with a low-quality association strategy (LQA), is proposed to pay more attention to low-quality targets. In the association scheme of LQTTrack, firstly, multi-scale feature fusion of FPN (MSFF-FPN) is utilized to enrich the feature information and assist… More >

  • Open Access

    ARTICLE

    Mural Anomaly Region Detection Algorithm Based on Hyperspectral Multiscale Residual Attention Network

    Bolin Guo1,2, Shi Qiu1,*, Pengchang Zhang1, Xingjia Tang3

    CMC-Computers, Materials & Continua, Vol.81, No.1, pp. 1809-1833, 2024, DOI:10.32604/cmc.2024.056706 - 15 October 2024

    Abstract Mural paintings hold significant historical information and possess substantial artistic and cultural value. However, murals are inevitably damaged by natural environmental factors such as wind and sunlight, as well as by human activities. For this reason, the study of damaged areas is crucial for mural restoration. These damaged regions differ significantly from undamaged areas and can be considered abnormal targets. Traditional manual visual processing lacks strong characterization capabilities and is prone to omissions and false detections. Hyperspectral imaging can reflect the material properties more effectively than visual characterization methods. Thus, this study employs hyperspectral imaging… More >

  • Open Access

    ARTICLE

    Research on Defect Detection of Wind Turbine Blades Based on Morphology and Improved Otsu Algorithm Using Infrared Images

    Shuang Kang1, Yinchao He1,2, Wenwen Li1,*, Sen Liu2

    CMC-Computers, Materials & Continua, Vol.81, No.1, pp. 933-949, 2024, DOI:10.32604/cmc.2024.056614 - 15 October 2024

    Abstract To address the issues of low accuracy and high false positive rate in traditional Otsu algorithm for defect detection on infrared images of wind turbine blades (WTB), this paper proposes a technique that combines morphological image enhancement with an improved Otsu algorithm. First, mathematical morphology’s differential multi-scale white and black top-hat operations are applied to enhance the image. The algorithm employs entropy as the objective function to guide the iteration process of image enhancement, selecting appropriate structural element scales to execute differential multi-scale white and black top-hat transformations, effectively enhancing the detail features of defect… More >

  • Open Access

    ARTICLE

    Adversarial Defense Technology for Small Infrared Targets

    Tongan Yu1, Yali Xue1,*, Yiming He1, Shan Cui2, Jun Hong2

    CMC-Computers, Materials & Continua, Vol.81, No.1, pp. 1235-1250, 2024, DOI:10.32604/cmc.2024.056075 - 15 October 2024

    Abstract With the rapid development of deep learning-based detection algorithms, deep learning is widely used in the field of infrared small target detection. However, well-designed adversarial samples can fool human visual perception, directly causing a serious decline in the detection quality of the recognition model. In this paper, an adversarial defense technology for small infrared targets is proposed to improve model robustness. The adversarial samples with strong migration can not only improve the generalization of defense technology, but also save the training cost. Therefore, this study adopts the concept of maximizing multidimensional feature distortion, applying noise… More >

  • Open Access

    ARTICLE

    Industrial Fusion Cascade Detection of Solder Joint

    Chunyuan Li1,2,3, Peng Zhang1,2,3, Shuangming Wang4, Lie Liu4, Mingquan Shi2,*

    CMC-Computers, Materials & Continua, Vol.81, No.1, pp. 1197-1214, 2024, DOI:10.32604/cmc.2024.055893 - 15 October 2024

    Abstract With the remarkable advancements in machine vision research and its ever-expanding applications, scholars have increasingly focused on harnessing various vision methodologies within the industrial realm. Specifically, detecting vehicle floor welding points poses unique challenges, including high operational costs and limited portability in practical settings. To address these challenges, this paper innovatively integrates template matching and the Faster RCNN algorithm, presenting an industrial fusion cascaded solder joint detection algorithm that seamlessly blends template matching with deep learning techniques. This algorithm meticulously weights and fuses the optimized features of both methodologies, enhancing the overall detection capabilities. Furthermore,… More >

  • Open Access

    ARTICLE

    Cross-Target Stance Detection with Sentiments-Aware Hierarchical Attention Network

    Kelan Ren, Facheng Yan, Honghua Chen, Wen Jiang, Bin Wei, Mingshu Zhang*

    CMC-Computers, Materials & Continua, Vol.81, No.1, pp. 789-807, 2024, DOI:10.32604/cmc.2024.055624 - 15 October 2024

    Abstract The task of cross-target stance detection faces significant challenges due to the lack of additional background information in emerging knowledge domains and the colloquial nature of language patterns. Traditional stance detection methods often struggle with understanding limited context and have insufficient generalization across diverse sentiments and semantic structures. This paper focuses on effectively mining and utilizing sentiment-semantics knowledge for stance knowledge transfer and proposes a sentiment-aware hierarchical attention network (SentiHAN) for cross-target stance detection. SentiHAN introduces an improved hierarchical attention network designed to maximize the use of high-level representations of targets and texts at various… More > Graphic Abstract

    Cross-Target Stance Detection with Sentiments-Aware Hierarchical Attention Network

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