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  • Open Access

    REVIEW

    Explainable Rules and Heuristics in AI Algorithm Recommendation Approaches—A Systematic Literature Review and Mapping Study

    Francisco José García-Peñalvo*, Andrea Vázquez-Ingelmo, Alicia García-Holgado

    CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.2, pp. 1023-1051, 2023, DOI:10.32604/cmes.2023.023897

    Abstract The exponential use of artificial intelligence (AI) to solve and automated complex tasks has catapulted its popularity generating some challenges that need to be addressed. While AI is a powerful means to discover interesting patterns and obtain predictive models, the use of these algorithms comes with a great responsibility, as an incomplete or unbalanced set of training data or an unproper interpretation of the models’ outcomes could result in misleading conclusions that ultimately could become very dangerous. For these reasons, it is important to rely on expert knowledge when applying these methods. However, not every user can count on this… More > Graphic Abstract

    Explainable Rules and Heuristics in AI Algorithm Recommendation Approaches—A Systematic Literature Review and Mapping Study

  • Open Access

    REVIEW

    Cervical cancer situation in Malaysia: A systematic literature review

    WAN AZANI MUSTAFA1,2,*, AFIQAH HALIM2, MOHD WAFI NASRUDIN2, KHAIRUL SHAKIR AB RAHMAN3

    BIOCELL, Vol.46, No.2, pp. 367-381, 2022, DOI:10.32604/biocell.2022.016814

    Abstract Cervix cancer is one of Malaysia’s most significant cancers for women (around 12.9%, with an age-standardised incidence rate of 19.7 per 100,000). It was higher than other Asian, West, and even worldwide nations. The National Strategic Plan for Cancer Control Program 2016–2020 (Health Ministry) was presented to minimize cancer and mortality. The high incidence of cervical cancer in Malaysia is mainly due to women’s insufficient knowledge about its prevention and importance. Compared with traditional literature reviews, the systemic analysis provides many advantages. A clearer review process, a more prominent field of study, and essential priorities that can manage research bias… More >

  • Open Access

    REVIEW

    Economical Requirements Elicitation Techniques During COVID-19: A Systematic Literature Review

    Tauqeer ul Amin1,*, Basit Shahzad1, Fazal-e-Amin2, Muhammad Shoaib2

    CMC-Computers, Materials & Continua, Vol.67, No.2, pp. 2665-2680, 2021, DOI:10.32604/cmc.2021.013263

    Abstract Requirements elicitation is a fundamental phase of software development in which an analyst discovers the needs of different stakeholders and transforms them into requirements. This phase is cost- and time-intensive, and a project may fail if there are excessive costs and schedule overruns. COVID-19 has affected the software industry by reducing interactions between developers and customers. Such a lack of interaction is a key reason for the failure of software projects. Projects can also fail when customers do not know precisely what they want. Furthermore, selecting the unsuitable elicitation technique can also cause project failure. The present study, therefore, aimed… More >

  • Open Access

    ARTICLE

    Predicting Concrete Compressive Strength Using Deep Convolutional Neural Network Based on Image Characteristics

    Sanghyo Lee1, Yonghan Ahn2, Ha Young Kim3, *

    CMC-Computers, Materials & Continua, Vol.65, No.1, pp. 1-17, 2020, DOI:10.32604/cmc.2020.011104

    Abstract In this study, we examined the efficacy of a deep convolutional neural network (DCNN) in recognizing concrete surface images and predicting the compressive strength of concrete. A digital single-lens reflex (DSLR) camera and microscope were simultaneously used to obtain concrete surface images used as the input data for the DCNN. Thereafter, training, validation, and testing of the DCNNs were performed based on the DSLR camera and microscope image data. Results of the analysis indicated that the DCNN employing DSLR image data achieved a relatively higher accuracy. The accuracy of the DSLR-derived image data was attributed to the relatively wider range… More >

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