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  • Open Access

    ARTICLE

    X-ray Image-Based COVID-19 Patient Detection Using Machine Learning-Based Techniques

    Shabana Habib1, Saleh Alyahya2, Aizaz Ahmed3, Muhammad Islam2,*, Sheroz Khan2, Ishrat Khan4, Muhammad Kamil5

    Computer Systems Science and Engineering, Vol.43, No.2, pp. 671-682, 2022, DOI:10.32604/csse.2022.021812

    Abstract In early December 2019, the city of Wuhan, China, reported an outbreak of coronavirus disease (COVID-19), caused by a novel severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2). On January 30, 2020, the World Health Organization (WHO) declared the outbreak a global pandemic crisis. In the face of the COVID-19 pandemic, the most important step has been the effective diagnosis and monitoring of infected patients. Identifying COVID-19 using Machine Learning (ML) technologies can help the health care unit through assistive diagnostic suggestions, which can reduce the health unit's burden to a certain extent. This paper investigates the possibilities of ML techniques in… More >

  • Open Access

    REVIEW

    Review of Research Advances in CFD Techniques for the Simulation of Urban Wind Environments

    Pengfei Ju1,2,*, Mingrui Li3,4, Jingying Wang3,4

    FDMP-Fluid Dynamics & Materials Processing, Vol.18, No.2, pp. 449-462, 2022, DOI:10.32604/fdmp.2022.018035

    Abstract

    Computational fluid dynamics (CFD) has become the main method for the prediction of the properties of the external wind environment in cities and other urban contexts. A review is presented of the existing literature in terms of boundary conditions, building models, computational domains, computational grids, and turbulence models. Some specific issues, such as the accuracy/computational cost ratio and the exploitation of existing empirical correlations, are also examined.

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  • Open Access

    ARTICLE

    Fuzzy Based Latent Dirichlet Allocation for Intrusion Detection in Cloud Using ML

    S. Ranjithkumar1,*, S. Chenthur Pandian2

    CMC-Computers, Materials & Continua, Vol.70, No.3, pp. 4261-4277, 2022, DOI:10.32604/cmc.2022.019031

    Abstract The growth of cloud in modern technology is drastic by provisioning services to various industries where data security is considered to be common issue that influences the intrusion detection system (IDS). IDS are considered as an essential factor to fulfill security requirements. Recently, there are diverse Machine Learning (ML) approaches that are used for modeling effectual IDS. Most IDS are based on ML techniques and categorized as supervised and unsupervised. However, IDS with supervised learning is based on labeled data. This is considered as a common drawback and it fails to identify the attack patterns. Similarly, unsupervised learning fails to… More >

  • Open Access

    ARTICLE

    Roughsets-based Approach for Predicting Battery Life in IoT

    Rajesh Kaluri1, Dharmendra Singh Rajput1, Qin Xin2,*, Kuruva Lakshmanna1, Sweta Bhattacharya1, Thippa Reddy Gadekallu1, Praveen Kumar Reddy Maddikunta1

    Intelligent Automation & Soft Computing, Vol.27, No.2, pp. 453-469, 2021, DOI:10.32604/iasc.2021.014369

    Abstract Internet of Things (IoT) and related applications have successfully contributed towards enhancing the value of life in this planet. The advanced wireless sensor networks and its revolutionary computational capabilities have enabled various IoT applications become the next frontier, touching almost all domains of life. With this enormous progress, energy optimization has also become a primary concern with the need to attend to green technologies. The present study focuses on the predictions pertinent to the sustainability of battery life in IoT frameworks in the marine environment. The data used is a publicly available dataset collected from the Chicago district beach water.… More >

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