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  • Open Access


    Multiple Perspective of Multipredictor Mechanism and Multihistogram Modification for High-Fidelity Reversible Data Hiding

    Kai Gao1, Chin-Chen Chang1,*, Chia-Chen Lin2,*

    Computer Systems Science and Engineering, Vol.48, No.3, pp. 813-833, 2024, DOI:10.32604/csse.2024.038308

    Abstract Reversible data hiding is a confidential communication technique that takes advantage of image file characteristics, which allows us to hide sensitive data in image files. In this paper, we propose a novel high-fidelity reversible data hiding scheme. Based on the advantage of the multipredictor mechanism, we combine two effective prediction schemes to improve prediction accuracy. In addition, the multihistogram technique is utilized to further improve the image quality of the stego image. Moreover, a model of the grouped knapsack problem is used to speed up the search for the suitable embedding bin in each sub-histogram. More >

  • Open Access


    An Optimized Offloaded Task Execution for Smart Cities Applications

    Ahmad Naseem Alvi1, Muhammad Awais Javed1,*, Mozaherul Hoque Abul Hasanat2, Muhammad Badruddin Khan2, Abdul Khader Jilani Saudagar2, Mohammed Alkhathami2

    CMC-Computers, Materials & Continua, Vol.74, No.3, pp. 6321-6334, 2023, DOI:10.32604/cmc.2023.029913

    Abstract Wireless nodes are one of the main components in different applications that are offered in a smart city. These wireless nodes are responsible to execute multiple tasks with different priority levels. As the wireless nodes have limited processing capacity, they offload their tasks to cloud servers if the number of tasks exceeds their task processing capacity. Executing these tasks from remotely placed cloud servers causes a significant delay which is not required in sensitive task applications. This execution delay is reduced by placing fog computing nodes near these application nodes. A fog node has limited… More >

  • Open Access


    A Combinatorial Optimized Knapsack Linear Space for Information Retrieval

    Varghese S. Chooralil1, Vinodh P. Vijayan2, Biju Paul1, M. M. Anishin Raj3, B. Karthikeyan4,*, G. Manikandan4

    CMC-Computers, Materials & Continua, Vol.66, No.3, pp. 2891-2903, 2021, DOI:10.32604/cmc.2021.012796

    Abstract Key information extraction can reduce the dimensional effects while evaluating the correct preferences of users during semantic data analysis. Currently, the classifiers are used to maximize the performance of web-page recommendation in terms of precision and satisfaction. The recent method disambiguates contextual sentiment using conceptual prediction with robustness, however the conceptual prediction method is not able to yield the optimal solution. Context-dependent terms are primarily evaluated by constructing linear space of context features, presuming that if the terms come together in certain consumer-related reviews, they are semantically reliant. Moreover, the more frequently they coexist, the… More >

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