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  • Open Access

    RETRACTION

    Retraction: Marketing Model Analysis of Fashion Communication Based on the Visual Analysis of Neutrosophic Systems

    Fangyu Ye1, Xiaoshu Xu2,*, Yunfeng Zhang3, Yan Ye4, Jingyu Dai5,*
    Intelligent Automation & Soft Computing, DOI:10.32604/iasc.2023.045930
    Abstract This article has no abstract. More >

  • Open Access

    ARTICLE

    Modified Elite Opposition-Based Artificial Hummingbird Algorithm for Designing FOPID Controlled Cruise Control System

    Laith Abualigah1,2,3,4,5,6,*, Serdar Ekinci7, Davut Izci7,8, Raed Abu Zitar9
    Intelligent Automation & Soft Computing, DOI:10.32604/iasc.2023.040291
    Abstract Efficient speed controllers for dynamic driving tasks in autonomous vehicles are crucial for ensuring safety and reliability. This study proposes a novel approach for designing a fractional order proportional-integral-derivative (FOPID) controller that utilizes a modified elite opposition-based artificial hummingbird algorithm (m-AHA) for optimal parameter tuning. Our approach outperforms existing optimization techniques on benchmark functions, and we demonstrate its effectiveness in controlling cruise control systems with increased flexibility and precision. Our study contributes to the advancement of autonomous vehicle technology by introducing a novel and efficient method for FOPID controller design that can enhance the driving experience while ensuring safety and… More >

  • Open Access

    ARTICLE

    Hash Table Assisted Efficient File Level De-Duplication Scheme in SD-IoV Assisted Sensing Devices

    Ghawar Said1, Ata Ullah2, Anwar Ghani1,*, Muhammad Azeem1, Khalid Yahya3, Muhammad Bilal4, Sayed Chhattan Shah5,*
    Intelligent Automation & Soft Computing, DOI:10.32604/iasc.2023.036079
    Abstract The Internet of Things (IoT) and cloud technologies have encouraged massive data storage at central repositories. Software-defined networks (SDN) support the processing of data and restrict the transmission of duplicate values. It is necessary to use a data de-duplication mechanism to reduce communication costs and storage overhead. Existing State of the art schemes suffer from computational overhead due to deterministic or random treebased tags generation which further increases as the file size grows. This paper presents an efficient file-level de-duplication scheme (EFDS) where the cost of creating tags is reduced by employing a hash table with keyvalue pair for each… More >