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  • Open Access


    Optimization of Head Cluster Selection in WSN by Human-Based Optimization Techniques

    Hajer Faris1, Musaria Karim Mahmood2, Osama Ahmad Alomari3,*, Ashraf Elnagar4

    CMC-Computers, Materials & Continua, Vol.72, No.3, pp. 5643-5661, 2022, DOI:10.32604/cmc.2022.026228

    Abstract Wireless sensor networks (WSNs) are characterized by their ability to monitor physical or chemical phenomena in a static or dynamic location by collecting data, and transmit it in a collaborative manner to one or more processing centers wirelessly using a routing protocol. Energy dissipation is one of the most challenging issues due to the limited power supply at the sensor node. All routing protocols are large consumers of energy, as they represent the main source of energy cost through data exchange operation. Cluster-based hierarchical routing algorithms are known for their good performance in energy conservation during active data exchange in… More >

  • Open Access


    A Novel Deep Learning Based Healthcare Model for COVID-19 Pandemic Stress Analysis

    Ankur Dumka1, Parag Verma2, Rajesh Singh3, Anil Kumar Bisht4, Divya Anand5,6,*, Hani Moaiteq Aljahdali7, Irene Delgado Noya6,8, Silvia Aparicio Obregon6,9

    CMC-Computers, Materials & Continua, Vol.72, No.3, pp. 6029-6044, 2022, DOI:10.32604/cmc.2022.024698

    Abstract Coronavirus (COVID-19) has impacted nearly every person across the globe either in terms of losses of life or as of lockdown. The current coronavirus (COVID-19) pandemic is a rare/special situation where people can express their feelings on Internet-based social networks. Social media is emerging as the biggest platform in recent years where people spend most of their time expressing themselves and their emotions. This research is based on gathering data from Twitter and analyzing the behavior of the people during the COVID-19 lockdown. The research is based on the logic expressed by people in this perspective and emotions for the… More >

  • Open Access


    Numerical Analysis of Blood Flow through COVID-19 Infected Arteries

    Anupam Krishnan1, Anjana P. Anantharaman2,*

    Molecular & Cellular Biomechanics, Vol.19, No.2, pp. 77-88, 2022, DOI:10.32604/mcb.2022.018369

    Abstract Computational Fluid Dynamics has become relevant in the study of hemodynamics, where clinical results are challenging to obtain. This paper discusses a 2-Dimensional transient blood flow analysis through an arterial bifurcation for patients infected with the Coronavirus. The geometry considered is an arterial bifurcation with main stem diameter 3 mm and two outlets. The left outlet (smaller) has a diameter of 1.5 mm and the right outlet (larger), 2 mm. The length of the main stem, left branch and right branch are fixed at 35 mm, 20 mm and 25 mm respectively. Viscosity change that occurs in the blood leads… More >

  • Open Access


    Perceived Stress and Coping Styles among the General Population in Saudi Arabia during COVID-19 Pandemic

    Waleed A. Alghamdi1,2, Sami H. Alzahrani3, Saeed S. Shaaban1,*, Naseem A. Alhujaili2

    International Journal of Mental Health Promotion, Vol.24, No.3, pp. 361-373, 2022, DOI:10.32604/ijmhp.2022.017685

    Abstract This article examines the stress levels, coping responses, and influence of adaptive and maladaptive coping styles on stress in Saudi Arabia during the COVID-19 pandemic. An online cross-sectional survey was distributed to the attendees of a pandemic-related awareness webinars. The questionnaire assessed demographic and clinical characteristics, coping strategies (the brief COPE inventory), and stress levels (the Perceived Stress Scale). A multivariate linear regression analysis was conducted to assess the predictors of stress. The highest adaptive and maladaptive coping styles were reported for religion and self-distraction. Certain groups were independently more vulnerable to experience stress, including young- and middle-aged adults, females,… More >

  • Open Access


    Stochastic Epidemic Model of Covid-19 via the Reservoir-People Transmission Network

    Kazem Nouri1,*, Milad Fahimi1, Leila Torkzadeh1, Dumitru Baleanu2,3

    CMC-Computers, Materials & Continua, Vol.72, No.1, pp. 1495-1514, 2022, DOI:10.32604/cmc.2022.024406

    Abstract The novel Coronavirus COVID-19 emerged in Wuhan, China in December 2019. COVID-19 has rapidly spread among human populations and other mammals. The outbreak of COVID-19 has become a global challenge. Mathematical models of epidemiological systems enable studying and predicting the potential spread of disease. Modeling and predicting the evolution of COVID-19 epidemics in near real-time is a scientific challenge, this requires a deep understanding of the dynamics of pandemics and the possibility that the diffusion process can be completely random. In this paper, we develop and analyze a model to simulate the Coronavirus transmission dynamics based on Reservoir-People transmission network.… More >

  • Open Access


    Pandemic Analysis and Prediction of COVID-19 Using Gaussian Doubling Times

    Saleh Albahli1,*, Farman Hassan2, Ali Javed2,3, Aun Irtaza2,4

    CMC-Computers, Materials & Continua, Vol.72, No.1, pp. 833-849, 2022, DOI:10.32604/cmc.2022.024267

    Abstract COVID-19 has become a pandemic, with cases all over the world, with widespread disruption in some countries, such as Italy, US, India, South Korea, and Japan. Early and reliable detection of COVID-19 is mandatory to control the spread of infection. Moreover, prediction of COVID-19 spread in near future is also crucial to better plan for the disease control. For this purpose, we proposed a robust framework for the analysis, prediction, and detection of COVID-19. We make reliable estimates on key pandemic parameters and make predictions on the point of inflection and possible washout time for various countries around the world.… More >

  • Open Access


    Investigation of SARS-CoV-2 Main Protease Potential Inhibitory Activities of Some Natural Antiviral Compounds Via Molecular Docking and Dynamics Approaches

    Nada M. Mostafa1,5,#, Muhammad I. Ismail2,#, Amr M. El-Araby3, Dina M. Bahgat1, Ahmed M. Elissawy1,5, Ahmed M. Mostafa4, Omayma A. Eldahshan1,5,*, Abdel Nasser B. Singab1,5,*

    Phyton-International Journal of Experimental Botany, Vol.91, No.5, pp. 1089-1104, 2022, DOI:10.32604/phyton.2022.018239

    Abstract Coronaviruses caused an outbreak pandemic disease characterized by a severe acute respiratory distress syndrome leading to the infection of more than 200 million patients and the death of more than 4 million individuals. The primary treatment is either supportive or symptomatic. Natural products have an important role in the development of various drugs. Thus, screening of natural compounds with reported antiviral activities can lead to the discovery of potential inhibitory entities against coronaviruses. In the current study, an in-silico molecular docking experiment was conducted on the effects of some of these natural antiviral phytoconstituents, (e.g., procyanidin B2, theaflavin, quercetin, ellagic… More >

  • Open Access


    COVID-19 Lockdown in India: An Experimental Study on Promoting Mental Wellness Using a Chatbot during the Coronavirus

    V. P. Harshini Raji*, P. Uma Maheswari

    International Journal of Mental Health Promotion, Vol.24, No.2, pp. 189-205, 2022, DOI:10.32604/ijmhp.2022.011865

    Abstract India imposed the largest lockdown in the world in response to fight the spread of the Novel Coronavirus disease (COVID-19) from 19 March till 31 May 2020. The onset of the pandemic left the general public feeling psychosocially distressed, helpless, and anxious. The researcher developed a Messenger supported Chatbot, based on the broaden and build model, to cater to the healthy general public to promote positivity and mental well-being. 31 participants between 22 and 45 years old consensually took a pre-test, Chatbot intervention, and post-test. The Chatbot provided guided activities out of which positive affirmations, meditation, and exercises were mostly… More >

  • Open Access


    Coronavirus Detection Using Two Step-AS Clustering and Ensemble Neural Network Model

    Ahmed Hamza Osman*

    CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 6307-6331, 2022, DOI:10.32604/cmc.2022.024145

    Abstract This study presents a model of computer-aided intelligence capable of automatically detecting positive COVID-19 instances for use in regular medical applications. The proposed model is based on an Ensemble boosting Neural Network architecture and can automatically detect discriminatory features on chest X-ray images through Two Step-As clustering algorithm with rich filter families, abstraction and weight-sharing properties. In contrast to the generally used transformational learning approach, the proposed model was trained before and after clustering. The compilation procedure divides the datasets samples and categories into numerous sub-samples and subcategories and then assigns new group labels to each new group, with each… More >

  • Open Access


    Structure Preserving Algorithm for Fractional Order Mathematical Model of COVID-19

    Zafar Iqbal1,2, Muhammad Aziz-ur Rehman1, Nauman Ahmed1,2, Ali Raza3,4, Muhammad Rafiq5, Ilyas Khan6,*, Kottakkaran Sooppy Nisar7

    CMC-Computers, Materials & Continua, Vol.71, No.2, pp. 2141-2157, 2022, DOI:10.32604/cmc.2022.013906

    Abstract In this article, a brief biological structure and some basic properties of COVID-19 are described. A classical integer order model is modified and converted into a fractional order model with as order of the fractional derivative. Moreover, a valued structure preserving the numerical design, coined as Grunwald–Letnikov non-standard finite difference scheme, is developed for the fractional COVID-19 model. Taking into account the importance of the positivity and boundedness of the state variables, some productive results have been proved to ensure these essential features. Stability of the model at a corona free and a corona existing equilibrium points is investigated on… More >

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