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  • Open Access


    Robust and Reusable Fuzzy Extractors from Non-Uniform Learning with Errors Problem

    Joo Woo1, Jonghyun Kim1, Jong Hwan Park2,*

    CMC-Computers, Materials & Continua, Vol.74, No.1, pp. 1985-2003, 2023, DOI:10.32604/cmc.2023.033102

    Abstract A fuzzy extractor can extract an almost uniform random string from a noisy source with enough entropy such as biometric data. To reproduce an identical key from repeated readings of biometric data, the fuzzy extractor generates a helper data and a random string from biometric data and uses the helper data to reproduce the random string from the second reading. In 2013, Fuller et al. proposed a computational fuzzy extractor based on the learning with errors problem. Their construction, however, can tolerate a sub-linear fraction of errors and has an inefficient decoding algorithm, which causes the reproducing time to increase significantly. In 2016,… More >

  • Open Access


    Artificial Intelligence Model for Software Reusability Prediction System

    R. Subha1,*, Anandakumar Haldorai1, Arulmurugan Ramu2

    Intelligent Automation & Soft Computing, Vol.35, No.3, pp. 2639-2654, 2023, DOI:10.32604/iasc.2023.028153

    Abstract The most significant invention made in recent years to serve various applications is software. Developing a faultless software system requires the software system design to be resilient. To make the software design more efficient, it is essential to assess the reusability of the components used. This paper proposes a software reusability prediction model named Flexible Random Fit (FRF) based on aging resilience for a Service Net (SN) software system. The reusability prediction model is developed based on a multilevel optimization technique based on software characteristics such as cohesion, coupling, and complexity. Metrics are obtained from the SN software system, which… More >

  • Open Access


    Reusing the Evaluations of Basis Functions in the Integration for Isogeometric Analysis

    Zijun Wu1, Shuting Wang2, Wenjun Shao3, *, Lianqing Yu1

    CMES-Computer Modeling in Engineering & Sciences, Vol.122, No.2, pp. 459-485, 2020, DOI:10.32604/cmes.2020.08697

    Abstract We propose a new approach to reuse the basis function evaluations in the numerical integration of isogeometric analysis. The concept of reusability of the basis functions is introduced according to their symmetrical, translational and proportional features on both the coarse and refined levels. Based on these features and the parametric domain regularity of each basis, we classify the bases on the original level and then reuse them on the refined level, which can reduce the time for basis calculations at integration nodes. By using the sum factorization method and the mean value theorem for the integrals, a new integration method… More >

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