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  • Open Access

    ARTICLE

    Estimating the Impact of COVID-19 Pandemic on the Research Community in the Kingdom of Saudi Arabia

    Abdulaziz Attaallah1, Masood Ahmad2, Adil Hussain Seh2, Alka Agrawal2, Rajeev Kumar2,3,*, Raees Ahmad Khan2

    CMES-Computer Modeling in Engineering & Sciences, Vol.126, No.1, pp. 419-436, 2021, DOI:10.32604/cmes.2021.014263

    Abstract Ever since its outbreak in Wuhan, COVID-19 has cloaked the entire world in a pall of despondency and uncertainty. The present study describes the exploratory analysis of all COVID cases in Saudi Arabia. Besides, the study has executed the forecasting model for predicting the possible number of COVID-19 cases in Saudi Arabia till a defined period. Towards this intent, the study analyzed different age groups of patients (child, adult, elderly) who were affected by COVID-19. The analysis was done city-wise and also included the number of recoveries recorded in different cities. Furthermore, the study also discusses the impact of COVID-19… More >

  • Open Access

    ARTICLE

    Real-Time Analysis of COVID-19 Pandemic on Most Populated Countries Worldwide

    Meenu Gupta1, Rachna Jain2, Akash Gupta2,*, Kunal Jain2

    CMES-Computer Modeling in Engineering & Sciences, Vol.125, No.3, pp. 943-965, 2020, DOI:10.32604/cmes.2020.012467

    Abstract The spread of the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) has already taken on pandemic extents, inuencing even more than 200 nations in a couple of months. Although, regulation measures in China have decreased new cases by over 98%, this decrease is not the situation everywhere, and most of the countries still have been affected by it. The objective of this research work is to make a comparative analysis of the top 5 most populated countries namely United States, India, China, Pakistan and Indonesia, from 1st January 2020 to 31st July 2020. This research work also targets to predict… More >

  • Open Access

    ARTICLE

    Predictive Models for Cumulative Confirmed COVID-19 Cases by Day in Southeast Asia

    Yupaporn Areepong1, Rapin Sunthornwat2,*

    CMES-Computer Modeling in Engineering & Sciences, Vol.125, No.3, pp. 927-942, 2020, DOI:10.32604/cmes.2020.012323

    Abstract Coronavirus disease 2019 outbreak has spread as a pandemic since the end of year 2019. This situation has been causing a lot of problems of human beings such as economic problems, health problems. The forecasting of the number of infectious people is required by the authorities of all countries including Southeast Asian countries to make a decision and control the outbreak. This research is to investigate the suitable forecasting model for the number of infectious people in Southeast Asian countries. A comparison of forecasting models between logistic growth curve which is symmetric and Gompertz growth curve which is asymmetric based… More >

  • Open Access

    ARTICLE

    Investigation of Coronavirus Deposition in Realistic Human Nasal Cavity and Impact of Social Distancing to Contain COVID-19: A Computational Fluid Dynamic Approach

    Mohammad Zuber1, John Valerian Corda1, Milad Ahmadi2, B. Satish Shenoy1, Irfan Anjum Badruddin3,*, Ali E. Anqi3, Kamarul Arifin Ahmad4, S. M. Abdul Khader5, Leslie Lewis6, Mohammad Anas Khan7, Sarfaraz Kamangar3

    CMES-Computer Modeling in Engineering & Sciences, Vol.125, No.3, pp. 1185-1199, 2020, DOI:10.32604/cmes.2020.015015

    Abstract The novel coronavirus responsible for COVID-19 has spread to several countries within a considerably short period. The virus gets deposited in the human nasal cavity and moves to the lungs that might be fatal. As per safety guidelines by the World Health Organization (WHO), social distancing has emerged as one of the major factors to avoid the spread of infection. However, different guidelines are being followed across the countries with regards to what should be the safe distance. Thus, the current work is an attempt to understand the virus deposition pattern in the realistic human nasal cavity and also to… More >

  • Open Access

    ARTICLE

    Modelling the Effect of Self-Immunity and the Impacts of Asymptomatic and Symptomatic Individuals on COVID-19 Outbreak

    M. H. A. Biswas1,*, M. A. Islam1, S. Akter2, S. Mandal2, M. S. Khatun1, S. A. Samad1, A. K. Paul1, M. R. Khatun1

    CMES-Computer Modeling in Engineering & Sciences, Vol.125, No.3, pp. 1033-1060, 2020, DOI:10.32604/cmes.2020.012792

    Abstract COVID-19 is one of the most highly infectious diseases ever emerged and caused by newly discovered severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). It has already led the entire world to health and economic crisis. It has invaded the whole universe all most every way. The present study demonstrates with a nine mutually exclusive compartmental model on transmission dynamics of this pandemic disease (COVID-19), with special focus on the transmissibility of symptomatic and asymptomatic infection from susceptible individuals. Herein, the compartmental model has been investigated with mathematical analysis and computer simulations in order to understand the dynamics of COVID-19 transmission.… More >

  • Open Access

    ARTICLE

    SEIHCRD Model for COVID-19 Spread Scenarios, Disease Predictions and Estimates the Basic Reproduction Number, Case Fatality Rate, Hospital, and ICU Beds Requirement

    Avaneesh Singh*, Manish Kumar Bajpai

    CMES-Computer Modeling in Engineering & Sciences, Vol.125, No.3, pp. 991-1031, 2020, DOI:10.32604/cmes.2020.012503

    Abstract We have proposed a new mathematical method, the SEIHCRD model, which has an excellent potential to predict the incidence of COVID-19 diseases. Our proposed SEIHCRD model is an extension of the SEIR model. Three-compartments have added death, hospitalized, and critical, which improves the basic understanding of disease spread and results. We have studied COVID-19 cases of six countries, where the impact of this disease in the highest are Brazil, India, Italy, Spain, the United Kingdom, and the United States. After estimating model parameters based on available clinical data, the model will propagate and forecast dynamic evolution. The model calculates the… More >

  • Open Access

    ARTICLE

    Study of Non-Pharmacological Interventions on COVID-19 Spread

    Avaneesh Singh*, Saroj Kumar Chandra, Manish Kumar Bajpai

    CMES-Computer Modeling in Engineering & Sciences, Vol.125, No.3, pp. 967-990, 2020, DOI:10.32604/cmes.2020.011601

    Abstract COVID-19 disease has emerged as one of the life threatening threat to the society. A novel beta coronavirus causes it. It began as unidentified pneumonia of unknown etiology in Wuhan City, Hubei province in China emerged in December 2019. No vaccine has been produced till now. Mathematical models are used to study the impact of different measures used to decrease pandemic. Mathematical models have been designed to estimate the numbers of spreaders in different scenarios in the present manuscript. In the present manuscript, three different mathematical models have been proposed with different scenarios, such as screening, quarantine, and NPIs, to… More >

  • Open Access

    ARTICLE

    Prediction of Proteins Associated with COVID-19 Based Ligand Designing and Molecular Modeling

    Majid Monajjemi1,*, Rahim Esmkhani2, Fatemeh Mollaamin1, Sara Shahriari3

    CMES-Computer Modeling in Engineering & Sciences, Vol.125, No.3, pp. 907-926, 2020, DOI:10.32604/cmes.2020.012846

    Abstract Current understanding about how the virus that causes COVID-19 spreads is largely based on what is known about similar coronaviruses. Some of the Natural products are suitable drugs against SARS-CoV-2 main protease. For recognizing a strong inhibitor, we have accomplished docking studies on the major virus protease with 4 natural product species as anti COVID-19 (SARS-CoV-2), namely “Vidarabine”, “Cytarabine”, “Gemcitabine” and “Matrine” which have been extracted from Gillan’s leaves plants. These are known as Chuchaq, Trshvash, Cote-Couto and Khlvash in Iran. Among these four studied compounds, Cytarabine appears as a suitable compound with high effectiveness inhibitors to this protease. Finally… More >

  • Open Access

    ARTICLE

    How Can Lean Manufacturing Lead the Manufacturing Sector during Health Pandemics Such as COVID 19: A Multi Response Optimization Framework

    Abdallah Ali Abdallah*

    CMC-Computers, Materials & Continua, Vol.66, No.2, pp. 1397-1410, 2021, DOI:10.32604/cmc.2020.013733

    Abstract Lean manufacturing has been used for the last few decades as a process and performance improvement tool. Initially known as Toyota production system (TPS), lean is now used in almost all service and manufacturing sectors to deliver favorable results such as decreased operational cost, increased customer satisfaction, decreased cycle time, and enhanced profits. During the coronavirus disease (COVID 19) pandemic, the manufacturing sector struggled immensely and could not function well even after lockdown was eased in many countries. Many companies found out there are not ready to conform with new regulations made by authorities in many countries. This paper proposes… More >

  • Open Access

    ARTICLE

    A Deep-CNN Crowd Counting Model for Enforcing Social Distancing during COVID19 Pandemic: Application to Saudi Arabia’s Public Places

    Salma Kammoun Jarraya1,2,*, Maha Hamdan Alotibi1,3, Manar Salamah Ali1

    CMC-Computers, Materials & Continua, Vol.66, No.2, pp. 1315-1328, 2021, DOI:10.32604/cmc.2020.013522

    Abstract With the emergence of the COVID19 virus in late 2019 and the declaration that the virus is a worldwide pandemic, health organizations and governments have begun to implement severe health precautions to reduce the spread of the virus and preserve human lives. The enforcement of social distancing at work environments and public areas is one of these obligatory precautions. Crowd management is one of the effective measures for social distancing. By reducing the social contacts of individuals, the spread of the disease will be immensely reduced. In this paper, a model for crowd counting in public places of high and… More >

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