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  • Open Access

    ARTICLE

    SDH-FCOS: An Efficient Neural Network for Defect Detection in Urban Underground Pipelines

    Bin Zhou, Bo Li*, Wenfei Lan, Congwen Tian, Wei Yao

    CMC-Computers, Materials & Continua, Vol.78, No.1, pp. 633-652, 2024, DOI:10.32604/cmc.2023.046667 - 30 January 2024

    Abstract Urban underground pipelines are an important infrastructure in cities, and timely investigation of problems in underground pipelines can help ensure the normal operation of cities. Owing to the growing demand for defect detection in urban underground pipelines, this study developed an improved defect detection method for urban underground pipelines based on fully convolutional one-stage object detector (FCOS), called spatial pyramid pooling-fast (SPPF) feature fusion and dual detection heads based on FCOS (SDH-FCOS) model. This study improved the feature fusion component of the model network based on FCOS, introduced an SPPF network structure behind the last… More >

  • Open Access

    ARTICLE

    Graph Ranked Clustering Based Biomedical Text Summarization Using Top k Similarity

    Supriya Gupta*, Aakanksha Sharaff, Naresh Kumar Nagwani

    Computer Systems Science and Engineering, Vol.45, No.3, pp. 2333-2349, 2023, DOI:10.32604/csse.2023.030385 - 21 December 2022

    Abstract Text Summarization models facilitate biomedical clinicians and researchers in acquiring informative data from enormous domain-specific literature within less time and effort. Evaluating and selecting the most informative sentences from biomedical articles is always challenging. This study aims to develop a dual-mode biomedical text summarization model to achieve enhanced coverage and information. The research also includes checking the fitment of appropriate graph ranking techniques for improved performance of the summarization model. The input biomedical text is mapped as a graph where meaningful sentences are evaluated as the central node and the critical associations between them. The… More >

  • Open Access

    ARTICLE

    GrCol-PPFL: User-Based Group Collaborative Federated Learning Privacy Protection Framework

    Jieren Cheng1, Zhenhao Liu1,*, Yiming Shi1, Ping Luo1,2, Victor S. Sheng3

    CMC-Computers, Materials & Continua, Vol.74, No.1, pp. 1923-1939, 2023, DOI:10.32604/cmc.2023.032758 - 22 September 2022

    Abstract With the increasing number of smart devices and the development of machine learning technology, the value of users’ personal data is becoming more and more important. Based on the premise of protecting users’ personal privacy data, federated learning (FL) uses data stored on edge devices to realize training tasks by contributing training model parameters without revealing the original data. However, since FL can still leak the user's original data by exchanging gradient information. The existing privacy protection strategy will increase the uplink time due to encryption measures. It is a huge challenge in terms of… More >

  • Open Access

    ARTICLE

    A Suitable Active Control for Suppression the Vibrations of a Cantilever Beam

    Y. A. Amer1, A. T. EL-Sayed2, M. N. Abd EL-Salam3,*

    Sound & Vibration, Vol.56, No.2, pp. 89-104, 2022, DOI:10.32604/sv.2022.011838 - 25 March 2022

    Abstract In our consideration, a comparison between four different types of controllers for suppression the vibrations of the cantilever beam excited by an external force is carried out. Those four types are the linear velocity feedback control, the cubic velocity feedback control, the non-linear saturation controller (NSC) and the positive position feedback (PPF) controller. The suitable type is the PPF controller for suppression the vibrations of the cantilever beam. The approximate solution obtained up to the first approximation by using the multiple scale method. The PPF controller effectiveness is studied on the system. We used frequency-response More >

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