Muhammad Attique Khan¹, Abdul Majid¹, Tallha Akram², Nazar Hussain¹, Yunyoung Nam^3,*, Seifedine Kadry⁴, Shui-Hua Wang⁵, Majed Alhaisoni⁶

CMC-Computers, Materials & Continua, Vol.68, No.1, pp. 1003-1019, 2021, DOI:10.32604/cmc.2021.015541

Abstract Here, we use multi-type feature fusion and selection to predict COVID-19 infections on chest computed tomography (CT) scans. The scheme operates in four steps. Initially, we prepared a database containing COVID-19 pneumonia and normal CT scans. These images were retrieved from the Radiopaedia COVID-19 website. The images were divided into training and test sets in a ratio of 70:30. Then, multiple features were extracted from the training data. We used canonical correlation analysis to fuse the features into single vectors; this enhanced the predictive capacity. We next implemented a genetic algorithm (GA) in which an Extreme Learning Machine (ELM) served… More >

Shakeel Ahmed^*, Abdulaziz Alhumam

Intelligent Automation & Soft Computing, Vol.27, No.3, pp. 835-851, 2021, DOI:10.32604/iasc.2021.015789

Abstract Most of the patients diagnosed with COVID-19 pandemic usually suffer from mild-to-serious respiratory illness and become stable without any specific care. In fact, in some countries like India the mortality rate is as low. Those who are amongst the most vulnerable groups are the elderly and the ones with chronic ailments like diabetes, heart ailments, and respiratory ailments. However, apart from the impact on the physical health of the patients, this disease has had a more debilitating affect on the mental as well as emotional well-being of the people. Due to continuous watching and protection programs to fight the pandemic,… More >

Muhammad Saad¹, Maaz Bin Ahmad¹, Muhammad Asif^2,*, Khalid Masood², Mohammad A. Al Ghamdi³

CMC-Computers, Materials & Continua, Vol.67, No.3, pp. 3545-3562, 2021, DOI:10.32604/cmc.2021.015720

Abstract Social distancing and self-isolation management are crucial preventive measures that can save millions of lives during challenging pandemics of diseases such as the Spanish flu, swine flu, and coronavirus disease 2019 (COVID-19). This study describes the comprehensive and effective implementation of the Industrial Internet of Things and machine-to-machine technologies for social distancing and smart self-isolation management. These technologies can help prevent outbreaks of any disease that can disperse widely and develop into a pandemic. Initially, a smart wristband is proposed that incorporates Bluetooth beacon technology to facilitate the tracing and tracking of Bluetooth Low Energy beacon packets for smart contact… More >

Muhammad Farman¹, Aqeel Ahmad¹, Ali Akgül^2,*, Muhammad Umer Saleem³, Muhammad Naeem⁴, Dumitru Baleanu^5,6,7

CMC-Computers, Materials & Continua, Vol.67, No.3, pp. 3215-3227, 2021, DOI:10.32604/cmc.2021.014006

Abstract Today, coronavirus appears as a serious challenge to the whole world. Epidemiological data of coronavirus is collected through media and web sources for the purpose of analysis. New data on COVID-19 are available daily, yet information about the biological aspects of SARS-CoV-2 and epidemiological characteristics of COVID-19 remains limited, and uncertainty remains around nearly all its parameters’ values. This research provides the scientific and public health communities better resources, knowledge, and tools to improve their ability to control the infectious diseases. Using the publicly available data on the ongoing pandemic, the present study investigates the incubation period and other time… More >

Shumaila Azam¹, Nauman Ahmed^1,6, Ali Raza², Muhammad Sajid Iqbal¹, Muhammad Rafiq³, Ilyas Khan^4,*, Kottakkaran Sooppy Nisar⁵, Muhammad Ozair Ahmad¹, Zafar Iqbal^1,6

CMC-Computers, Materials & Continua, Vol.67, No.3, pp. 2933-2953, 2021, DOI:10.32604/cmc.2021.012396

Abstract Recently, the world is facing the terror of the novel corona-virus, termed as COVID-19. Various health institutes and researchers are continuously striving to control this pandemic. In this article, the SEIAR (susceptible, exposed, infected, symptomatically infected, asymptomatically infected and recovered) infection model of COVID-19 with a constant rate of advection is studied for the disease propagation. A simple model of the disease is extended to an advection model by accommodating the advection process and some appropriate parameters in the system. The continuous model is transposed into a discrete numerical model by discretizing the domains, finitely. To analyze the disease dynamics,… More >

Guanghui Lei¹, Caihong Yang^2,#, Yan Ge^3,#, Yan Zhang^2,*, Yufei Xie^4,*, Jianwen Chen², Jinyang Wu⁵

International Journal of Mental Health Promotion, Vol.23, No.1, pp. 121-140, 2021, DOI:10.32604/IJMHP.2021.013072

Abstract To explore the relationship between social support and sleep quality of community workers in Wuhan during the coronavirus disease 2019 (the COVID-19 infection epidemic), this research constructed a mediating effect model to explore the mediating psychological mechanism of social support influencing sleep quality of front-line community workers. A total of 500 front-line community workers in Wuhan were investigated. We used the perceived social support scale (PSSS), the Connor-Davidson Resilience Scale (CD-RISC), the perceived stress scale (PSS), and the Pittsburgh sleep quality index (PSQI) to measure social support, psychological resilience, perceived stress and sleep quality. Specifically, the higher the PSQI, the… More >

Sally M. Elghamrawy¹, Aboul Ella Hassnien^2,*, Vaclav Snasel³

CMC-Computers, Materials & Continua, Vol.67, No.2, pp. 2353-2371, 2021, DOI:10.32604/cmc.2021.014767

Abstract Detecting COVID-19 cases as early as possible became a critical issue that must be addressed to avoid the pandemic’s additional spread and early provide the appropriate treatment to the affected patients. This study aimed to develop a COVID-19 diagnosis and prediction (AIMDP) model that could identify patients with COVID-19 and distinguish it from other viral pneumonia signs detected in chest computed tomography (CT) scans. The proposed system uses convolutional neural networks (CNNs) as a deep learning technology to process hundreds of CT chest scan images and speeds up COVID-19 case prediction to facilitate its containment. We employed the whale optimization… More >

Jin Zhao¹, Zubair Ahmad^2,*, Zahra Almaspoor²

CMC-Computers, Materials & Continua, Vol.67, No.2, pp. 2111-2122, 2021, DOI:10.32604/cmc.2021.014259

Abstract The epidemic outbreak COVID-19 was first detected in the Wuhan city of China and then spread worldwide. It is of great interest to the researchers for its high rate of infection spread and its significant number of fatalities. A detailed scientific analysis of this phenomenon is yet to come. However, it is of interest of governments and other responsible institutions to have the right facts and figures to take every possible necessary action such as an arrangement of the appropriate quarantine activities, estimation of the required number of places in hospitals, assessment of the level of personal protection, and calculating… More >

Naveed Shahid^1,2, Dumitru Baleanu^3,4,5, Nauman Ahmed^1,2, Tahira Sumbal Shaikh⁶, Ali Raza^7,*, Muhammad Sajid Iqbal¹, Muhammad Rafiq⁸, Muhammad Aziz-ur Rehman²

CMC-Computers, Materials & Continua, Vol.67, No.2, pp. 1713-1728, 2021, DOI:10.32604/cmc.2021.014191

Abstract The novel coronavirus disease, coined as COVID-19, is a murderous and infectious disease initiated from Wuhan, China. This killer disease has taken a large number of lives around the world and its dynamics could not be controlled so far. In this article, the spatio-temporal compartmental epidemic model of the novel disease with advection and diffusion process is projected and analyzed. To counteract these types of diseases or restrict their spread, mankind depends upon mathematical modeling and medicine to reduce, alleviate, and anticipate the behavior of disease dynamics. The existence and uniqueness of the solution for the proposed system are investigated.… More >

A. S. Al-Waisy¹, Mazin Abed Mohammed¹, Shumoos Al-Fahdawi¹, M. S. Maashi², Begonya Garcia-Zapirain³, Karrar Hameed Abdulkareem⁴, S. A. Mostafa⁵, Nallapaneni Manoj Kumar⁶, Dac-Nhuong Le^7,8,*

CMC-Computers, Materials & Continua, Vol.67, No.2, pp. 2409-2429, 2021, DOI:10.32604/cmc.2021.012955

Abstract Coronavirus (COVID-19) epidemic outbreak has devastating effects on daily lives and healthcare systems worldwide. This newly recognized virus is highly transmissible, and no clinically approved vaccine or antiviral medicine is currently available. Early diagnosis of infected patients through effective screening is needed to control the rapid spread of this virus. Chest radiography imaging is an effective diagnosis tool for COVID-19 virus and follow-up. Here, a novel hybrid multimodal deep learning system for identifying COVID-19 virus in chest X-ray (CX-R) images is developed and termed as the COVID-DeepNet system to aid expert radiologists in rapid and accurate image interpretation. First, Contrast-Limited… More >