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  • Open Access

    ARTICLE

    LSDA-APF: A Local Obstacle Avoidance Algorithm for Unmanned Surface Vehicles Based on 5G Communication Environment

    Xiaoli Li, Tongtong Jiao#, Jinfeng Ma, Dongxing Duan, Shengbin Liang#,*

    CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.1, pp. 595-617, 2024, DOI:10.32604/cmes.2023.029367

    Abstract In view of the complex marine environment of navigation, especially in the case of multiple static and dynamic obstacles, the traditional obstacle avoidance algorithms applied to unmanned surface vehicles (USV) are prone to fall into the trap of local optimization. Therefore, this paper proposes an improved artificial potential field (APF) algorithm, which uses 5G communication technology to communicate between the USV and the control center. The algorithm introduces the USV discrimination mechanism to avoid the USV falling into local optimization when the USV encounter different obstacles in different scenarios. Considering the various scenarios between the USV and other dynamic obstacles… More > Graphic Abstract

    LSDA-APF: A Local Obstacle Avoidance Algorithm for Unmanned Surface Vehicles Based on 5G Communication Environment

  • Open Access

    ARTICLE

    PanopticUAV: Panoptic Segmentation of UAV Images for Marine Environment Monitoring

    Yuling Dou1, Fengqin Yao1, Xiandong Wang1, Liang Qu2, Long Chen3, Zhiwei Xu4, Laihui Ding4, Leon Bevan Bullock1, Guoqiang Zhong1, Shengke Wang1,*

    CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.1, pp. 1001-1014, 2024, DOI:10.32604/cmes.2023.027764

    Abstract UAV marine monitoring plays an essential role in marine environmental protection because of its flexibility and convenience, low cost and convenient maintenance. In marine environmental monitoring, the similarity between objects such as oil spill and sea surface, Spartina alterniflora and algae is high, and the effect of the general segmentation algorithm is poor, which brings new challenges to the segmentation of UAV marine images. Panoramic segmentation can do object detection and semantic segmentation at the same time, which can well solve the polymorphism problem of objects in UAV ocean images. Currently, there are few studies on UAV marine image recognition… More >

  • Open Access

    REVIEW

    Embracing the Future: AI and ML Transforming Urban Environments in Smart Cities

    Gagan Deep*, Jyoti Verma

    Journal on Artificial Intelligence, Vol.5, pp. 57-73, 2023, DOI:10.32604/jai.2023.043329

    Abstract This research explores the increasing importance of Artificial Intelligence (AI) and Machine Learning (ML) with relation to smart cities. It discusses the AI and ML’s ability to revolutionize various aspects of urban environments, including infrastructure, governance, public safety, and sustainability. The research presents the definition and characteristics of smart cities, highlighting the key components and technologies driving initiatives for smart cities. The methodology employed in this study involved a comprehensive review of relevant literature, research papers, and reports on the subject of AI and ML in smart cities. Various sources were consulted to gather information on the integration of AI… More >

  • Open Access

    REVIEW

    Study of Intelligent Approaches to Identify Impact of Environmental Temperature on Ultrasonic GWs Based SHM: A Review

    Saqlain Abbas1,2,*, Zulkarnain Abbas3, Xiaotong Tu4, Yanping Zhu2

    Journal on Artificial Intelligence, Vol.5, pp. 43-56, 2023, DOI:10.32604/jai.2023.040948

    Abstract Structural health monitoring (SHM) is considered an effective approach to analyze the efficient working of several mechanical components. For this purpose, ultrasonic guided waves can cover long-distance and assess large infrastructures in just a single test using a small number of transducers. However, the working of the SHM mechanism can be affected by some sources of variations (i.e., environmental). To improve the final results of ultrasonic guided wave inspections, it is necessary to highlight and attenuate these environmental variations. The loading parameters, temperature and humidity have been recognized as the core environmental sources of variations that affect the SHM sensing… More >

  • Open Access

    REVIEW

    Progress in research on tumor microenvironment-based spatial omics technologies

    FANGMEI XIE1,#, NAITE XI1,#, ZEPING HAN1,#, WENFENG LUO1, JIAN SHEN1, JINGGENG LUO2, XINGKUI TANG2, TING PANG1, YUBING LV1, JIABING LIANG1, LIYIN LIAO1, HAOYU ZHANG1, YONG JIANG1, YUGUANG LI3,*, JINHUA HE1,*

    Oncology Research, Vol.31, No.6, pp. 877-885, 2023, DOI:10.32604/or.2023.029494

    Abstract Spatial omics technology integrates the concept of space into omics research and retains the spatial information of tissues or organs while obtaining molecular information. It is characterized by the ability to visualize changes in molecular information and yields intuitive and vivid visual results. Spatial omics technologies include spatial transcriptomics, spatial proteomics, spatial metabolomics, and other technologies, the most widely used of which are spatial transcriptomics and spatial proteomics. The tumor microenvironment refers to the surrounding microenvironment in which tumor cells exist, including the surrounding blood vessels, immune cells, fibroblasts, bone marrow-derived inflammatory cells, various signaling molecules, and extracellular matrix. A… More >

  • Open Access

    PROCEEDINGS

    Integrated Calculation of Acoustic Radiation and Propagation of Underwater Elastic Structures Based on the Simple Source Boundary Integral Equation

    Lingwen Jiang1, Mingsong Zou2,*

    The International Conference on Computational & Experimental Engineering and Sciences, Vol.27, No.2, pp. 1-1, 2023, DOI:10.32604/icces.2023.09669

    Abstract Acoustic radiation and propagation characteristics of underwater elastic structures are an organic whole, which should be considered comprehensively. Based on the three-dimensional sono-elasticity theory of ships, the integrated calculation method of acoustic radiation and propagation in ocean environment is realized by using the simple source boundary integral equation. The correctness and accuracy of the method are verified by a series of examples. Based on the domestic supercomputer platform, the parallel transformation of the algorithm is completed, and the two-level multi-core parallel is realized, which greatly improves the computing efficiency. The application of acoustic radiation calculation in composite structures is carried… More >

  • Open Access

    ARTICLE

    Deep Learning Model for Big Data Classification in Apache Spark Environment

    T. M. Nithya1,*, R. Umanesan2, T. Kalavathidevi3, C. Selvarathi4, A. Kavitha5

    Intelligent Automation & Soft Computing, Vol.37, No.3, pp. 2537-2547, 2023, DOI:10.32604/iasc.2022.028804

    Abstract Big data analytics is a popular research topic due to its applicability in various real time applications. The recent advent of machine learning and deep learning models can be applied to analyze big data with better performance. Since big data involves numerous features and necessitates high computational time, feature selection methodologies using metaheuristic optimization algorithms can be adopted to choose optimum set of features and thereby improves the overall classification performance. This study proposes a new sigmoid butterfly optimization method with an optimum gated recurrent unit (SBOA-OGRU) model for big data classification in Apache Spark. The SBOA-OGRU technique involves the… More >

  • Open Access

    ARTICLE

    Explainable Artificial Intelligence-Based Model Drift Detection Applicable to Unsupervised Environments

    Yongsoo Lee, Yeeun Lee, Eungyu Lee, Taejin Lee*

    CMC-Computers, Materials & Continua, Vol.76, No.2, pp. 1701-1719, 2023, DOI:10.32604/cmc.2023.040235

    Abstract Cybersecurity increasingly relies on machine learning (ML) models to respond to and detect attacks. However, the rapidly changing data environment makes model life-cycle management after deployment essential. Real-time detection of drift signals from various threats is fundamental for effectively managing deployed models. However, detecting drift in unsupervised environments can be challenging. This study introduces a novel approach leveraging Shapley additive explanations (SHAP), a widely recognized explainability technique in ML, to address drift detection in unsupervised settings. The proposed method incorporates a range of plots and statistical techniques to enhance drift detection reliability and introduces a drift suspicion metric that considers… More >

  • Open Access

    ARTICLE

    A Lightweight ABE Security Protection Scheme in Cloud Environment Based on Attribute Weight

    Lihong Guo*, Jie Yang, Haitao Wu

    CMC-Computers, Materials & Continua, Vol.76, No.2, pp. 1929-1946, 2023, DOI:10.32604/cmc.2023.039170

    Abstract Attribute-based encryption (ABE) is a technique used to encrypt data, it has the flexibility of access control, high security, and resistance to collusion attacks, and especially it is used in cloud security protection. However, a large number of bilinear mappings are used in ABE, and the calculation of bilinear pairing is time-consuming. So there is the problem of low efficiency. On the other hand, the decryption key is not uniquely associated with personal identification information, if the decryption key is maliciously sold, ABE is unable to achieve accountability for the user. In practical applications, shared message requires hierarchical sharing in… More >

  • Open Access

    PROCEEDINGS

    Hydrogels with Brain Tissue-Like Mechanical Properties in Complex Environments

    Jingyu Wang1,#, Yongrou Zhang4,#, Zuyue Lei1, Junqi Wang1, Yangming Zhao1, Taolin Sun3,*, Zhenyu Jiang1, Licheng Zhou1, Zejia Liu1, Yiping Liu1, Bao Yang1, Liqun Tang1,2,*

    The International Conference on Computational & Experimental Engineering and Sciences, Vol.25, No.4, pp. 1-1, 2023, DOI:10.32604/icces.2022.08829

    Abstract In surgical training applications and experimental research, brain tissues immersed in cerebrospinal fluid often involve very complex deformation and strain rate effects, which affects their reliability and stability. Thus, it is indispensable to develop a high-fidelity human brain tissue simulant material as a physical surrogate model to understand their mechanical behavior, such as traumatic brain injury (TBI). However, the reported simulant materials have not yet been able to compare and satisfy the above two mechanical properties. Here, we developed a novel composite hydrogel with brain tissue-like mechanical properties and investigated their mechanical behavior in a solution environment. The results demonstrate… More >

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