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  • Open Access


    Smart Quarantine Environment Privacy through IoT Gadgets Using Blockchain

    Nitish Pathak1, Shams Tabrez Siddiqui2, Anjani Kumar Singha3, Heba G Mohamed4, Shabana Urooj4,*, Abhinandan R Patil5

    Intelligent Automation & Soft Computing, Vol.35, No.3, pp. 3021-3036, 2023, DOI:10.32604/iasc.2023.029053

    Abstract The coronavirus, formerly known as COVID-19, has caused massive global disasters. As a precaution, most governments imposed quarantine periods ranging from months to years and postponed significant financial obligations. Furthermore, governments around the world have used cutting-edge technologies to track citizens’ activity. Thousands of sensors were connected to IoT (Internet of Things) devices to monitor the catastrophic eruption with billions of connected devices that use these novel tools and apps, privacy and security issues regarding data transmission and memory space abound. In this study, we suggest a blockchain-based methodology for safeguarding data in the billions of devices and sensors connected… More >

  • Open Access


    A Method for Detecting Non-Mask Wearers Based on Regression Analysis

    Dokyung Hwang1, Hyeonmin Ro1, Naejoung Kwak2, Jinsang Hwang3, Dongju Kim1,*

    CMC-Computers, Materials & Continua, Vol.72, No.3, pp. 4411-4431, 2022, DOI:10.32604/cmc.2022.025378

    Abstract A novel practical and universal method of mask-wearing detection has been proposed to prevent viral respiratory infections. The proposed method quickly and accurately detects mask and facial regions using well-trained You Only Look Once (YOLO) detector, then applies image coordinates of the detected bounding box (bbox). First, the data that is used to train our model is collected under various circumstances such as light disturbances, distances, time variations, and different climate conditions. It also contains various mask types to detect in general and universal application of the model. To detect mask-wearing status, it is important to detect facial and mask… More >

  • Open Access


    A Novel COVID-19 Prediction Model with Optimal Control Rates

    Ashraf Ahmed1, Yousef AbuHour2,*, Ammar El-Hassan1

    Intelligent Automation & Soft Computing, Vol.32, No.2, pp. 979-990, 2022, DOI:10.32604/iasc.2022.020726

    Abstract The Corona (COVID-19) epidemic has triggered interest in many fields of technology, medicine, science, and politics. Most of the mathematical research in this area focused on analyzing the dynamics of the spread of the virus. In this article, after a review of some current methodologies, a non-linear system of differential equations is developed to model the spread of COVID-19. In order to consider a wide spectrum of scenarios, we propose a susceptible-exposed-infected-quarantined-recovered (SEIQRS)-model which was analyzed to determine threshold conditions for its stability, and the number of infected cases that is an infected person will transmit on a virus to,… More >

  • Open Access


    Is Social Distancing, and Quarantine Effective in Restricting COVID-19 Outbreak? Statistical Evidences from Wuhan, China

    Salman A. Cheema1, Tanveer Kifayat2, Abdu R. Rahman2, Umair Khan3, A. Zaib4, Ilyas Khan5,*, Kottakkaran Sooppy Nisar6

    CMC-Computers, Materials & Continua, Vol.66, No.2, pp. 1977-1985, 2021, DOI:10.32604/cmc.2020.012096

    Abstract The flow of novel coronavirus (COVID-19) has affected almost every aspect of human life around the globe. Being the emerging ground and early sufferer of the virus, Wuhan city-data remains a case of multifold significance. Further, it is of notable importance to explore the impact of unique and unprecedented public health response of Chinese authorities—the extreme lockdown of the city. In this research, we investigate the statistical nature of the viral transmission concerning social distancing, extreme quarantine, and robust lockdown interventions. We observed highly convincing and statistically significant evidences in favor of quarantine and social distancing approaches. These findings might… More >

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