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  • Open Access

    ARTICLE

    Improving Channel Estimation in a NOMA Modulation Environment Based on Ensemble Learning

    Lassaad K. Smirani1, Leila Jamel2,*, Latifah Almuqren2

    CMES-Computer Modeling in Engineering & Sciences, Vol.140, No.2, pp. 1315-1337, 2024, DOI:10.32604/cmes.2024.047551 - 20 May 2024

    Abstract This study presents a layered generalization ensemble model for next generation radio mobiles, focusing on supervised channel estimation approaches. Channel estimation typically involves the insertion of pilot symbols with a well-balanced rhythm and suitable layout. The model, called Stacked Generalization for Channel Estimation (SGCE), aims to enhance channel estimation performance by eliminating pilot insertion and improving throughput. The SGCE model incorporates six machine learning methods: random forest (RF), gradient boosting machine (GB), light gradient boosting machine (LGBM), support vector regression (SVR), extremely randomized tree (ERT), and extreme gradient boosting (XGB). By generating meta-data from five… More >

  • Open Access

    ARTICLE

    A New Privacy-Preserving Data Publishing Algorithm Utilizing Connectivity-Based Outlier Factor and Mondrian Techniques

    Burak Cem Kara1,2,*, Can Eyüpoğlu1

    CMC-Computers, Materials & Continua, Vol.76, No.2, pp. 1515-1535, 2023, DOI:10.32604/cmc.2023.040274 - 30 August 2023

    Abstract Developing a privacy-preserving data publishing algorithm that stops individuals from disclosing their identities while not ignoring data utility remains an important goal to achieve. Because finding the trade-off between data privacy and data utility is an NP-hard problem and also a current research area. When existing approaches are investigated, one of the most significant difficulties discovered is the presence of outlier data in the datasets. Outlier data has a negative impact on data utility. Furthermore, k-anonymity algorithms, which are commonly used in the literature, do not provide adequate protection against outlier data. In this study, a… More >

  • Open Access

    ARTICLE

    Customer Churn Prediction Framework of Inclusive Finance Based on Blockchain Smart Contract

    Fang Yu1, Wenbin Bi2, Ning Cao3,4,*, Hongjun Li1, Russell Higgs5

    Computer Systems Science and Engineering, Vol.47, No.1, pp. 1-17, 2023, DOI:10.32604/csse.2023.018349 - 26 May 2023

    Abstract In view of the fact that the prediction effect of influential financial customer churn in the Internet of Things environment is difficult to achieve the expectation, at the smart contract level of the blockchain, a customer churn prediction framework based on situational awareness and integrating customer attributes, the impact of project hotspots on customer interests, and customer satisfaction with the project has been built. This framework introduces the background factors in the financial customer environment, and further discusses the relationship between customers, the background of customers and the characteristics of pre-lost customers. The improved Singular… More >

  • Open Access

    ARTICLE

    Generalization of Advanced Encryption Standard Based on Field of Any Characteristic

    Nabilah Abughazalah1, Majid Khan2,*, Noor Munir2, Ammar S. Alanazi3, Iqtadar Hussain4,5

    CMC-Computers, Materials & Continua, Vol.73, No.3, pp. 6121-6138, 2022, DOI:10.32604/cmc.2022.031417 - 28 July 2022

    Abstract Nowadays most communications are done by utilizing digital transmission mechanisms. The security of this digital information transmitted through different communication systems is quite important. The secrecy of digital data is one of the burning topics of the digitally developed world. There exist many traditional algorithms in the literature to provide methods for robust communication. The most important and recent modern block cipher named the advanced encryption standard (AES) is one of the extensively utilized encryption schemes with binary based. AES is a succession of four fundamental steps: round key, sub-byte, shift row, and mix column.… More >

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