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  • Open Access

    ARTICLE

    Modern Mobile Malware Detection Framework Using Machine Learning and Random Forest Algorithm

    Mohammad Ababneh*, Ayat Al-Droos, Ammar El-Hassan

    Computer Systems Science and Engineering, Vol.48, No.5, pp. 1171-1191, 2024, DOI:10.32604/csse.2024.052875 - 13 September 2024

    Abstract With the high level of proliferation of connected mobile devices, the risk of intrusion becomes higher. Artificial Intelligence (AI) and Machine Learning (ML) algorithms started to feature in protection software and showed effective results. These algorithms are nonetheless hindered by the lack of rich datasets and compounded by the appearance of new categories of malware such that the race between attackers’ malware, especially with the assistance of Artificial Intelligence tools and protection solutions makes these systems and frameworks lose effectiveness quickly. In this article, we present a framework for mobile malware detection based on a… More >

  • Open Access

    ARTICLE

    An active RUNX1-ID1/ID3 axis governs differentiation and chemoresistance of cancer stem cell population in epithelial ovarian cancer cells

    AJIT C. DHADVE1,2, PRITHA RAY1,2

    BIOCELL, Vol.46, No.1, pp. 75-86, 2022, DOI:10.32604/biocell.2022.016346 - 28 September 2021

    Abstract Progression, relapse, and therapy resistance are the most challenging features of cancer therapy that have been postulated to be driven by Cancer Stem Cell (CSC) population. This enigmatic subpopulation of cancer cells has therefore emerged as promising therapeutic candidate. We earlier reported enrichment of CSC-like side population (SP) with increasing resistance towards Cisplatin and Paclitaxel either alone or in combination in epithelial ovarian cancer (EOC) cells. This SP population is a small proportion of the total population of cancer cells characterised with high expression of drug transporters, a unique feature of stem cells and thereby… More >

  • Open Access

    ARTICLE

    Intelligent Decision Support System for COVID-19 Empowered with Deep Learning

    Shahan Yamin Siddiqui1,2, Sagheer Abbas1, Muhammad Adnan Khan3,*, Iftikhar Naseer4, Tehreem Masood4, Khalid Masood Khan3, Mohammed A. Al Ghamdi5, Sultan H. Almotiri5

    CMC-Computers, Materials & Continua, Vol.66, No.2, pp. 1719-1732, 2021, DOI:10.32604/cmc.2020.012585 - 26 November 2020

    Abstract The prompt spread of Coronavirus (COVID-19) subsequently adorns a big threat to the people around the globe. The evolving and the perpetually diagnosis of coronavirus has become a critical challenge for the healthcare sector. Drastically increase of COVID-19 has rendered the necessity to detect the people who are more likely to get infected. Lately, the testing kits for COVID-19 are not available to deal it with required proficiency, along with-it countries have been widely hit by the COVID-19 disruption. To keep in view the need of hour asks for an automatic diagnosis system for early… More >

  • Open Access

    ARTICLE

    Reduced Expression of Jumonji AT-Rich Interactive Domain 2 (JARID2) in Glioma Inhibits Tumor Growth In Vitro and In Vivo

    Zhenjiang Li*1, Chenyang Xu*1, Ming Gao*, Bingqian Ding*, Xinting Wei, Nan Ji

    Oncology Research, Vol.25, No.3, pp. 365-372, 2017, DOI:10.3727/096504016X14738135889976

    Abstract Jumonji AT-rich interactive domain 2 (JARID2) is a member of the Jumonji family of proteins and has been proposed as an oncogene in several types of human cancer. However, the role of JARID2 in human glioma has not yet been understood. The present study was designed to determine the roles of JARID2 in the proliferation and migration in human glioma cells and the growth of glioma cells in nude mice. Our data indicate that JARID2 is upregulated in human glioma tissues and cell lines. Knockdown of JARID2 obviously inhibits the proliferation of U87MG cells and More >

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