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Computer Modeling in Engineering & Sciences
Tech Science Press
Computer Modeling in Engineering & Sciences

Tech Science Press

1526-1492

Computer Modeling in Engineering & Sciences/Journal Computer Modeling in Engineering & Sciences
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    Prediction of Proteins Associated with COVID-19 Based Ligand Designing and Molecular Modeling

    Shahriari, SaraMonajjemi, MajidEsmkhani, RahimMollaamin, Fatemeh...
    20页
    查看更多>>摘要：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 by this work we present a method on the Computational Prediction of Protein Structure Associated with COVID-19 Based Ligand Design and Molecular Modeling. By this investigation, auto dock software (iGEM-DOCK) has been used and via this tool, the suitable receptors can be distinguished in whole COVID-19 component structures for forming a complex. "iGEMDOCK" is suitable to define the binding site quickly. With docking simulation and NMR investigation, we have demonstrated these compounds exhibit a suitable binding energy around 9 Kcal/mol with various ligand proteins modes in the binding to COVID-19 viruses. However, these data need further evaluation for repurposing these drugs against COVID-19 viruses, in both vivo & vitro.
      原文链接:
    • NSTL
    • Tech Science Press

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

    Areepong, YupapornSunthornwat, Rapin
    16页
    查看更多>>摘要：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 on the maximum of Coefficient of Determination and the minimum of Root Mean Squared Percentage Error is also proposed. The estimation of parameters of the forecasting models is evaluated by the least square method. In addition, spreading of the outbreak is estimated by the derivative of the number of cumulative cases. The findings show that Gompertz growth curve is a suitable forecasting model for Indonesia, Philippines, and Malaysia and logistic growth curve suits the other countries in South Asia.
      原文链接:
    • NSTL
    • Tech Science Press

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

    Gupta, MeenuJain, RachnaGupta, AkashJain, Kunal...
    23页
    查看更多>>摘要：The spread of the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) has already taken on pandemic extents, influencing 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 an increase in the number of deaths and total infected cases in these five countries. In our research, the performance of the proposed framework is determined by using three Machine Learning (ML) regression algorithms namely Linear Regression (LR), Support Vector Regression (SVR), and Random Forest (RF) Regression. The proposed model is also validated upon the infected and death cases of further dates. The performance of these three algorithms is compared using the Root Mean Square Error (RMSE) metrics. Random Forest algorithm shows best performance as compared to other proposed algorithms, with the lowest RMSE value in the prediction of total infected and total deaths cases for all the top five most populated countries.
      原文链接:
    • NSTL
    • Tech Science Press

    Study of Non-Pharmacological Interventions on COVID-19 Spread

    Singh, AvaneeshChandra, Saroj KumarBajpai, Manish Kumar
    24页
    查看更多>>摘要：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 estimate the number of virus spreaders. The analysis shows that the numbers of COVID-19 patients will be more without screening the peoples coming from other countries. Since every people suffering from COVID-19 disease are spreaders. The screening and quarantine with NPIs have been implemented to study their impact on the spreaders. It has been found that NPI measures can reduce the number of spreaders. The NPI measures reduce the spread function's growth and provide decision makers more time to prepare with in dealing with the disease.
      原文链接:
    • NSTL
    • Tech Science Press

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

    Singh, AvaneeshBajpai, Manish Kumar
    41页
    查看更多>>摘要：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 Basic reproduction number over time using logistic regression and the Case fatality rate based on the selected countries' age-category scenario. The model calculates two types of Case fatality rate one is CFR daily, and the other is total CFR. The proposed model estimates the approximate time when the disease is at its peak and the approximate time when death cases rarely occur and calculate how much hospital beds and ICU beds will be needed in the peak days of infection. The SEIHCRD model outperforms the classic ARX model and the ARIMA model. RMSE, MAPE, and R squared matrices are used to evaluate results and are graphically represented using Taylor and Target diagrams. The result shows RMSE has improved by 56%-74%, and MAPE has a 53%-89% improvement in prediction accuracy.
      原文链接:
    • NSTL
    • Tech Science Press

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

    Biswas, M. H. A.Islam, M. A.Akter, S.Mandal, S....
    28页
    查看更多>>摘要：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. Initially, mathematical analysis of the model has been carried out in broadly by illustrating some well-known methods including exactness, equilibrium and stability analysis in terms of basic reproduction number. We investigate the sensitivity of the model with respect to the variation of the parameters' values. Furthermore, computer simulations are performed to illustrate the results. Our analysis reveals that the death rate from coronavirus disease increases as the infection rate increases, whereas infection rate extensively decreases with the increase of quarantined individuals. The quarantined individuals also lead to increase the concentration of recovered individuals. However, the infection rate of COVID-19 increases more surprisingly as the rate of asymptomatic individuals increases than that of the symptomatic individuals. Moreover, the infection rate decreases significantly due to increase of self-immunity rate.
      原文链接:
    • NSTL
    • Tech Science Press

    Performance of Geometric Multigrid Method for Two-Dimensional Burgers' Equations with Non-Orthogonal, Structured Curvilinear Grids

    Zanatta, Daiane CristinaArak, Luciano KiyoshiVillela Pinto, Marcio AugustoFernandoMoro, Diego...
    21页
    查看更多>>摘要：This paper seeks to develop an efficient multigrid algorithm for solving the Burgers problem with the use of non-orthogonal structured curvilinear grids in L-shaped geometry. For this, the differential equations were discretized by Finite Volume Method (FVM) with second-order approximation scheme and deferred correction. Moreover, the algebraic method and the differential method were used to generate the non-orthogonal structured curvilinear grids. Furthermore, the influence of some parameters of geometric multigrid method, as well as lexicographical Gauss-Seidel (Lex-GS), eta-line Gauss-Seidel (eta-line-GS), Modified Strongly Implicit (MSI) and modified incomplete LU decomposition (MILU) solvers on the Central Processing Unit (CPU) time was investigated. Therefore, several parameters of multigrid method and solvers were tested for the problem, with the use of non-orthogonal structured curvilinear grids and multigrid method, resulting in an algorithm with the combination that achieved the best results and CPU time. The geometric multigrid method with Full Approximation Scheme (FAS), V-cycle and standard coarsening ratio for this problem were utilized. This article shows how to calculate the coordinates transformation metrics in the coarser grids. Results show that the MSI and MILU solvers are the most efficient. Moreover, the MSI solver is faster than MILU for both grids generators; and the solutions are more accurate for the Burgers problem with grids generated using elliptic equations.
      原文链接:
    • NSTL
    • Tech Science Press

    ALCencryption: A Secure and Efficient Algorithm for Medical Image Encryption

    Ge, Jiao
    18页
    查看更多>>摘要：With the rapid development of medical informatization and the popularization of digital imaging equipment, DICOM images contain the personal privacy of patients, and there are security risks in the process of storage and transmission, so it needs to be encrypted. In order to solve the security problem of medical images on mobile devices, a safe and efficient medical image encryption algorithm called ALCencryption is designed. The algorithm first analyzes the medical image and distinguishes the color image from the gray image. For gray images, the improved Arnold map is used to scramble them according to the optimal number of iterations, and then the diffusion is realized by the Logistic and Chebyshev map cross-diffusion algorithm. The color image is encrypted by cross-diffusion algorithm of double chaotic map. Security and efficiency analysis show that the ALCencryption algorithm has the characteristics of small neighboring pixels, large key space, strong key sensitivity, high safety and short encryption time. It is suitable for medical image encryption of mobile devices with high real-time requirements.
      原文链接:
    • NSTL
    • Tech Science Press

    An Anonymous Authentication Scheme with Controllable Linkability for Vehicle Sensor Networks

    Yang, ZhengZhou, YoushengChen, LvjunZhao, Xiaofeng...
    18页
    查看更多>>摘要：Vehicle sensor networks (VSN) play an increasingly important part in smart city, due to the interconnectivity of the infrastructure. However similar to other wireless communications, vehicle sensor networks are susceptible to a broad range of attacks. In addition to ensuring security for both data-at-rest and data-in-transit, it is essential to preserve the privacy of data and users in vehicle sensor networks. Many existing authentication schemes for vehicle sensor networks are generally not designed to also preserve the privacy between the user and service provider (e.g., mining user data to provide personalized services without infringing on user privacy). Controllable linkability can be used to facilitate an involved entity with the right linking key to determine whether two messages were generated by the same sender, while preserving the anonymity of the signer. Such a functionality is very useful to provide personalized services. Thus, in this paper, a threshold authentication scheme with anonymity and controllable linkability for vehicle sensor networks is constructed, and its security is analyzed under the random oracle model.
      原文链接:
    • NSTL
    • Tech Science Press

    Thermal Analysis of MHD Non-Newtonian Nanofluids over a Porous Media

    Ejaz, AsadAbbas, ImranNawaz, YasirArif, Muhammad Shoaib...
    16页
    查看更多>>摘要：In the present research, Tiwari and Das model are used for the impact of a magnetic field on non-Newtonian nanofluid flow in the presence of injection and suction. The PDEs are converted into ordinary differential equations (ODEs) using the similarity method. The obtained ordinary differential equations are solved numerically using shooting method along with RK-4. Part of the present study uses nanoparticles (NPs) like TiO2 and Al2O3 and sodium carboxymethyl cellulose (CMC/water) is considered as a base fluid (BF). This study is conducted to find the influence of nanoparticles, Prandtl number, and magnetic field on velocity and temperature profile, however, the Nusselt number and coefficient of skin friction parameters are also presented in detail with the variation of nanoparticles and parameters. The obtained results of the present study are presented using MATLAB. In addition to these, some simulations of partial differential equations are also shown using software for graphing surface plots of velocity profile and streamlines along with surface plots and isothermal contours of the temperature profile.
      原文链接:
    • NSTL
    • Tech Science Press