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  • Open Access


    A Novel Heuristic Algorithm for the Modeling and Risk Assessment of the COVID-19 Pandemic Phenomenon

    Panagiotis G. Asteris1,*, Maria G. Douvika1, Chrysoula A. Karamani1, Athanasia D. Skentou1, Katerina Chlichlia2, Liborio Cavaleri3, Tryfon Daras4, Danial J. Armaghani5, Theoklis E. Zaoutis6

    CMES-Computer Modeling in Engineering & Sciences, Vol.125, No.2, pp. 815-828, 2020, DOI:10.32604/cmes.2020.013280

    Abstract The modeling and risk assessment of a pandemic phenomenon such as COVID-19 is an important and complicated issue in epidemiology, and such an attempt is of great interest for public health decision-making. To this end, in the present study, based on a recent heuristic algorithm proposed by the authors, the time evolution of COVID-19 is investigated for six different countries/states, namely New York, California, USA, Iran, Sweden and UK. The number of COVID-19-related deaths is used to develop the proposed heuristic model as it is believed that the predicted number of daily deaths in each country/state includes information about the… More >

  • Open Access


    A Classification–Detection Approach of COVID-19 Based on Chest X-ray and CT by Using Keras Pre-Trained Deep Learning Models

    Xing Deng1,2, Haijian Shao1,2,*, Liang Shi3, Xia Wang4,5, Tongling Xie6

    CMES-Computer Modeling in Engineering & Sciences, Vol.125, No.2, pp. 579-596, 2020, DOI:10.32604/cmes.2020.011920

    Abstract The Coronavirus Disease 2019 (COVID-19) is wreaking havoc around the world, bring out that the enormous pressure on national health and medical staff systems. One of the most effective and critical steps in the fight against COVID-19, is to examine the patient’s lungs based on the Chest X-ray and CT generated by radiation imaging. In this paper, five keras-related deep learning models: ResNet50, InceptionResNetV2, Xception, transfer learning and pre-trained VGGNet16 is applied to formulate an classification–detection approaches of COVID-19. Two benchmark methods SVM (Support Vector Machine), CNN (Convolutional Neural Networks) are provided to compare with the classification–detection approaches based on… More >

  • Open Access


    Impact of the COVID-19 Pandemic on Health-Related Concerns, Quality of Life and Psychological Adjustment in Young Adults with Congenital Heart Disease

    Flavia M. Wehrle1,2,3, Markus A. Landolt3,4,5, Beatrice Latal1,3, Sarah Rometsch6, Matthias Greutmann7,*

    Congenital Heart Disease, Vol.15, No.5, pp. 301-308, 2020, DOI:10.32604/CHD.2020.013078

    Abstract Background: The risk for a severe disease course in case of infection with SARS-CoV-2 in young adults with congenital heart disease is largely unknown, potentially leading to uncertainty and anxiety among affected patients. This study aims to investigate health-related concerns, health-related quality of life and psychological adjustment in patients with congenital heart disease compared to healthy peers during the COVID-19 pandemic. Methods: One-hundred patients with congenital heart disease and 50 controls (M = 29.7, SD = 3.8 years) were recruited. They completed an online survey including the assessment of health-related concerns regarding COVID-19, the 12-item Short Form Health Survey and… More >

  • Open Access


    Topp-Leone Odd Fréchet Generated Family of Distributions with Applications to COVID-19 Data Sets

    Sanaa Al-Marzouki1, Farrukh Jamal2, Christophe Chesneau3,*, Mohammed Elgarhy4

    CMES-Computer Modeling in Engineering & Sciences, Vol.125, No.1, pp. 437-458, 2020, DOI:10.32604/cmes.2020.011521

    Abstract Recent studies have pointed out the potential of the odd Fréchet family (or class) of continuous distributions in fitting data of all kinds. In this article, we propose an extension of this family through the so-called “Topp-Leone strategy”, aiming to improve its overall flexibility by adding a shape parameter. The main objective is to offer original distributions with modifiable properties, from which adaptive and pliant statistical models can be derived. For the new family, these aspects are illustrated by the means of comprehensive mathematical and numerical results. In particular, we emphasize a special distribution with three parameters based on the… More >

  • Open Access


    IoMT-Based Smart Monitoring Hierarchical Fuzzy Inference System for Diagnosis of COVID-19

    Tahir Abbas Khan1, Sagheer Abbas1, Allah Ditta2, Muhammad Adnan Khan3, *, Hani Alquhayz4, Areej Fatima3, Muhammad Farhan Khan5

    CMC-Computers, Materials & Continua, Vol.65, No.3, pp. 2591-2605, 2020, DOI:10.32604/cmc.2020.011892

    Abstract The prediction of human diseases, particularly COVID-19, is an extremely challenging task not only for medical experts but also for the technologists supporting them in diagnosis and treatment. To deal with the prediction and diagnosis of COVID-19, we propose an Internet of Medical Things-based Smart Monitoring Hierarchical Mamdani Fuzzy Inference System (IoMTSM-HMFIS). The proposed system determines the various factors like fever, cough, complete blood count, respiratory rate, Ct-chest, Erythrocyte sedimentation rate and C-reactive protein, family history, and antibody detection (lgG) that are directly involved in COVID-19. The expert system has two input variables in layer 1, and seven input variables… More >

  • Open Access


    Awareness as the Most Effective Measure to Mitigate the Spread of COVID-19 in Nigeria

    Isa Abdullahi Baba1, *, Dumitru Baleanu2, 3

    CMC-Computers, Materials & Continua, Vol.65, No.3, pp. 1945-1957, 2020, DOI:10.32604/cmc.2020.011508

    Abstract A mathematical model consisting of a system of four nonlinear ordinary differential equations is constructed. Our aim is to study the dynamics of the spread of COVID-19 in Nigeria and to show the effectiveness of awareness and the need for relevant authorities to engage themselves more in enlightening people on the significance of the available control measures in mitigating the spread of the disease. Two equilibrium solutions; Disease free equilibrium and Endemic equilibrium solutions were calculated and their global stability analysis was carried out. Basic reproduction ratio ( More >

  • Open Access


    Validating the Correct Wearing of Protection Mask by Taking a Selfie: Design of a Mobile Application “CheckYourMask” to Limit the Spread of COVID-19

    Karim Hammoudi1,2,*, Adnane Cabani3, Halim Benhabiles4, Mahmoud Melkemi1,2

    CMES-Computer Modeling in Engineering & Sciences, Vol.124, No.3, pp. 1049-1059, 2020, DOI:10.32604/cmes.2020.011663

    Abstract In a context of a virus that is transmissive by sputtering, wearing masks appear necessary to protect the wearer and to limit the propagation of the disease. Currently, we are facing the 2019–2020 coronavirus pandemic. Coronavirus disease 2019 (COVID-19) is an infectious disease with first symptoms similar to the flu. The symptom of COVID-19 was reported first in China and very quickly spreads to the rest of the world. The COVID-19 contagiousness is known to be high by comparison with the flu. In this paper, we propose a design of a mobile application for permitting everyone having a smartphone and… More >

  • Open Access


    Case Study: Spark GPU-Enabled Framework to Control COVID-19 Spread Using Cell-Phone Spatio-Temporal Data

    Hussein Shahata Abdallah1, *, Mohamed H. Khafagy1, Fatma A. Omara2

    CMC-Computers, Materials & Continua, Vol.65, No.2, pp. 1303-1320, 2020, DOI:10.32604/cmc.2020.011313

    Abstract Nowadays, the world is fighting a dangerous form of Coronavirus that represents an emerging pandemic. Since its early appearance in China Wuhan city, many countries undertook several strict regulations including lockdowns and social distancing measures. Unfortunately, these procedures have badly impacted the world economy. Detecting and isolating positive/probable virus infected cases using a tree tracking mechanism constitutes a backbone for containing and resisting such fast spreading disease. For helping this hard effort, this research presents an innovative case study based on big data processing techniques to build a complete tracking system able to identify the central areas of infected/suspected people,… More >

  • Open Access


    Cogitation on the Mental Health Service System during the COVID-19 Outbreak in China

    Jie Zhong1,*, Fumin Fan2, Yixing Liu1

    International Journal of Mental Health Promotion, Vol.22, No.3, pp. 199-202, 2020, DOI:10.32604/IJMHP.2020.011559

    Abstract The spread of the novel coronavirus disease (COVID-19) in China from December 2019 to April 2020 caused serious social panic and other psychological problems among the Chinese public. Thus, reducing the public panic of and the long-term adverse psychological effects on individuals and society resulting from the epidemic became the priority task for mental health professionals in China. Based on the experiences in providing mental health services during SARS outbreak, the perspectives and strategies for targeted mental health services are reported. Furthermore, the cogitation on the problems with mental health services in China during the outbreak of COVID-19 are discussed. More >

  • Open Access


    The Impact of COVID-19 on Spanish Health Professionals: A Description of Physical and Psychological Effects

    Mònica Cunill1, Maria Aymerich1, Bernat-Carles Serdà2,*, Josefina Patiño-Masó3

    International Journal of Mental Health Promotion, Vol.22, No.3, pp. 185-198, 2020, DOI:10.32604/IJMHP.2020.011615

    Abstract Aim: To describe the physical and psychological symptoms in healthcare workers caring for COVID-19 patients. Methods: Cross-sectional descriptive study design. A sample of 1,452 participants was collected. Sociodemographic data were recorded. Symptoms of anxiety were screened with Generalized Anxiety Disorder (GAD-7), symptoms of depression were measured with the Patient Health Questionnaire (PHQ-9), and finally physical symptoms were measured using the Patient Health Questionnaire (PHQ-15). Percentages, means and standard deviations, the one-way and two-way ANOVA test, the Chi square test and Pearson’s correlation coefficient were all calculated. The level of significance was (p < 0.05). Results: Medium levels of anxiety (range,… More >

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