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  • Open Access

    ARTICLE

    Regulation Relatedness Map Creation Method with Latent Semantic Analysis

    Mehmet Murat Huyut1,*, Batuhan Kocaoğlu2, Ünzile Meram3

    CMC-Computers, Materials & Continua, Vol.72, No.1, pp. 2093-2107, 2022, DOI:10.32604/cmc.2022.024190

    Abstract Regulatory authorities create a lot of legislation that must be followed. These create complex compliance requirements and time-consuming processes to find regulatory non-compliance. While the regulations establish rules in the relevant areas, recommendations and best practices for compliance are not generally mentioned. Best practices are often used to find a solution to this problem. There are numerous governance, management, and security frameworks in Information Technology (IT) area to guide businesses to run their processes at a much more mature level. Best practice maps can used to map another best practice, and users can adapt themselves by the help of this… More >

  • Open Access

    ARTICLE

    Understanding Research Trends in Android Malware Research Using Information Modelling Techniques

    Jaiteg Singh1, Tanya Gera1, Farman Ali2, Deepak Thakur1, Karamjeet Singh3, Kyung-sup Kwak4,*

    CMC-Computers, Materials & Continua, Vol.66, No.3, pp. 2655-2670, 2021, DOI:10.32604/cmc.2021.014504

    Abstract Android has been dominating the smartphone market for more than a decade and has managed to capture 87.8% of the market share. Such popularity of Android has drawn the attention of cybercriminals and malware developers. The malicious applications can steal sensitive information like contacts, read personal messages, record calls, send messages to premium-rate numbers, cause financial loss, gain access to the gallery and can access the user’s geographic location. Numerous surveys on Android security have primarily focused on types of malware attack, their propagation, and techniques to mitigate them. To the best of our knowledge, Android malware literature has never… More >

  • Open Access

    ARTICLE

    Attention-Aware Network with Latent Semantic Analysis for Clothing Invariant Gait Recognition

    Hefei Ling1, Jia Wu1, Ping Li1,*, Jialie Shen2

    CMC-Computers, Materials & Continua, Vol.60, No.3, pp. 1041-1054, 2019, DOI:10.32604/cmc.2019.05605

    Abstract Gait recognition is a complicated task due to the existence of co-factors like carrying conditions, clothing, viewpoints, and surfaces which change the appearance of gait more or less. Among those co-factors, clothing analysis is the most challenging one in the area. Conventional methods which are proposed for clothing invariant gait recognition show the body parts and the underlying relationships from them are important for gait recognition. Fortunately, attention mechanism shows dramatic performance for highlighting discriminative regions. Meanwhile, latent semantic analysis is known for the ability of capturing latent semantic variables to represent the underlying attributes and capturing the relationships from… More >

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