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  • Open Access

    ARTICLE

    Potential Inhibitory Effect of Vitamins Against COVID-19

    Kashaf Junaid1,*, Sumera Qasim2, Humaira Yasmeen3, Hasan Ejaz1, Abdullah Alsrhani1, Muhammad Ikram Ullah1, Fahad Ahmad4, Abdul Rehman5

    CMC-Computers, Materials & Continua, Vol.66, No.1, pp. 707-714, 2021, DOI:10.32604/cmc.2020.012976

    Abstract Coronavirus disease 2019 (COVID-19) is a current pandemic that has affected more than 195 countries worldwide. In this severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic, when treatment strategies are not yet clear and vaccines are not available, vitamins are an excellent choice to protect against this viral infection. The rationale behind this study was to examine the inhibitory effect of vitamins B, C, and D against the main protease of SARSCoV-2 and angiotensin-converting enzyme 2 (ACE2), which have critical rolesin the immune system. Molecular docking, performed by using MOE-Dock of the Chemical Computing Group, was used to understand the… More >

  • Open Access

    ARTICLE

    Analysis of the Smart Player’s Impact on the Success of a Team Empowered with Machine Learning

    Muhammad Adnan Khan1,*, Mubashar Habib1, Shazia Saqib1, Tahir Alyas1, Khalid Masood Khan1, Mohammed A. Al Ghamdi2, Sultan H. Almotiri2

    CMC-Computers, Materials & Continua, Vol.66, No.1, pp. 691-706, 2021, DOI:10.32604/cmc.2020.012542

    Abstract The innovation and development in data science have an impact in all trades of life. The commercialization of sport has encouraged players, coaches, and other concerns to use technology to be in better position than r their opponents. In the past, the focus was on improved training techniques for better physical performance. These days, sports analytics identify the patterns in the performance and highlight strengths and weaknesses of potential players. Sports analytics not only predict the performance of players in the near future but it also performs predictive modeling for a particular behavior of a player in the past. The… More >

  • Open Access

    ARTICLE

    Analysis of Convective Transport of Temperature-Dependent Viscosity for Non-Newtonian Erying Powell Fluid: A Numerical Approach

    Ahlam Aljabali1, Abdul Rahman Mohd Kasim1,*, Nur Syamilah Arifin2, Sharena Mohamad Isa3, Noor Amalina Nisa Ariffin1

    CMC-Computers, Materials & Continua, Vol.66, No.1, pp. 675-689, 2021, DOI:10.32604/cmc.2020.012334

    Abstract Non-Newtonian is a type of fluid that does not comply with the viscosity under the Law of Newton and is being widely used in industrial applications. These include those related to chemical industries, cosmetics manufacturing, pharmaceutical field, food processing, as well as oil and gas activities. The inability of the conventional equations of Navier–Stokes to accurately depict rheological behavior for certain fluids led to an emergence study for non-Newtonian fluids’ models. In line with this, a mathematical model of forced convective flow on non-Newtonian Eyring Powell fluid under temperature-dependent viscosity (TDV) circumstance is formulated. The fluid model is embedded with… More >

  • Open Access

    ARTICLE

    The Effect of Surface Pit Treatment on Fretting Fatigue Crack Initiation

    Qingming Deng1,2, Xiaochun Yin1, Magd Abdel Wahab3,4,*

    CMC-Computers, Materials & Continua, Vol.66, No.1, pp. 659-673, 2021, DOI:10.32604/cmc.2020.012878

    Abstract This paper analyses the effect of surface treatment on fretting fatigue specimen by numerical simulations using Finite Element Analysis. The processed specimen refers to artificially adding a cylindrical pit to its contact surface. Then, the contact radius between the pad and the specimen is controlled by adjusting the radius of the pit. The stress distribution and slip amplitude of the contact surface under different contact geometries are compared. The critical plane approach is used to predict the crack initiation life and to evaluate the effect of processed specimen on its fretting fatigue performance. Both crack initiation life and angle can… More >

  • Open Access

    ARTICLE

    Resampling Factor Estimation via Dual-Stream Convolutional Neural Network

    Shangjun Luo1, Junwei Luo1, Wei Lu1,*, Yanmei Fang1, Jinhua Zeng2, Shaopei Shi2, Yue Zhang3,4

    CMC-Computers, Materials & Continua, Vol.66, No.1, pp. 647-657, 2021, DOI:10.32604/cmc.2020.012869

    Abstract The estimation of image resampling factors is an important problem in image forensics. Among all the resampling factor estimation methods, spectrumbased methods are one of the most widely used methods and have attracted a lot of research interest. However, because of inherent ambiguity, spectrum-based methods fail to discriminate upscale and downscale operations without any prior information. In general, the application of resampling leaves detectable traces in both spatial domain and frequency domain of a resampled image. Firstly, the resampling process will introduce correlations between neighboring pixels. In this case, a set of periodic pixels that are correlated to their neighbors… More >

  • Open Access

    ARTICLE

    A Framework for Systematic Classification of Assets for Security Testing

    Sadeeq Jan1,*, Omer Bin Tauqeer1, Fazal Qudus Khan2, George Tsaramirsis2, Awais Ahmad3, Iftikhar Ahmad4, Imran Maqsood5, Niamat Ullah6

    CMC-Computers, Materials & Continua, Vol.66, No.1, pp. 631-645, 2021, DOI:10.32604/cmc.2020.012831

    Abstract Over the last decade, a significant increase has been observed in the use of web-based Information systems that process sensitive information, e.g., personal, financial, medical. With this increased use, the security of such systems became a crucial aspect to ensure safety, integrity and authenticity of the data. To achieve the objectives of data safety, security testing is performed. However, with growth and diversity of information systems, it is challenging to apply security testing for each and every system. Therefore, it is important to classify the assets based on their required level of security using an appropriate technique. In this paper,… More >

  • Open Access

    ARTICLE

    Recommender Systems Based on Tensor Decomposition

    Zhoubao Sun1,*, Xiaodong Zhang1, Haoyuan Li1, Yan Xiao2, Haifeng Guo3

    CMC-Computers, Materials & Continua, Vol.66, No.1, pp. 621-630, 2021, DOI:10.32604/cmc.2020.012593

    Abstract Recommender system is an effective tool to solve the problems of information overload. The traditional recommender systems, especially the collaborative filtering ones, only consider the two factors of users and items. While social networks contain abundant social information, such as tags, places and times. Researches show that the social information has a great impact on recommendation results. Tags not only describe the characteristics of items, but also reflect the interests and characteristics of users. Since the traditional recommender systems cannot parse multi-dimensional information, in this paper, a tensor decomposition model based on tag regularization is proposed which incorporates social information… More >

  • Open Access

    ARTICLE

    FogMed: A Fog-Based Framework for Disease Prognosis Based Medical Sensor Data Streams

    Le Sun1,*, Qiandi Yu1, Dandan Peng1, Sudha Subramani2, Xuyang Wang1

    CMC-Computers, Materials & Continua, Vol.66, No.1, pp. 603-619, 2021, DOI:10.32604/cmc.2020.012515

    Abstract Recently, an increasing number of works start investigating the combination of fog computing and electronic health (ehealth) applications. However, there are still numerous unresolved issues worth to be explored. For instance, there is a lack of investigation on the disease prediction in fog environment and only limited studies show, how the Quality of Service (QoS) levels of fog services and the data stream mining techniques influence each other to improve the disease prediction performance (e.g., accuracy and time efficiency). To address these issues, we propose a fog-based framework for disease prediction based on Medical sensor data streams, named FogMed. This… More >

  • Open Access

    ARTICLE

    Smart Healthcare Using Data-Driven Prediction of Immunization Defaulters in Expanded Program on Immunization (EPI)

    Sadaf Qazi1, Muhammad Usman1, Azhar Mahmood1, Aaqif Afzaal Abbasi2, Muhammad Attique3, Yunyoung Nam4,*

    CMC-Computers, Materials & Continua, Vol.66, No.1, pp. 589-602, 2021, DOI:10.32604/cmc.2020.012507

    Abstract Immunization is a noteworthy and proven tool for eliminating lifethreating infectious diseases, child mortality and morbidity. Expanded Program on Immunization (EPI) is a nation-wide program in Pakistan to implement immunization activities, however the coverage is quite low despite the accessibility of free vaccination. This study proposes a defaulter prediction model for accurate identification of defaulters. Our proposed framework classifies defaulters at five different stages: defaulter, partially high, partially medium, partially low, and unvaccinated to reinforce targeted interventions by accurately predicting children at high risk of defaulting from the immunization schedule. Different machine learning algorithms are applied on Pakistan Demographic and… More >

  • Open Access

    ARTICLE

    Effects of Combined Heat and Mass Transfer on Entropy Generation due to MHD Nanofluid Flow over a Rotating Frame

    F. Mabood1, T. A. Yusuf2, A. M. Rashad3, W. A. Khan4,*, Hossam A. Nabwey5,6

    CMC-Computers, Materials & Continua, Vol.66, No.1, pp. 575-587, 2021, DOI:10.32604/cmc.2020.012505

    Abstract The current investigation aims to explore the combined effects of heat and mass transfer on free convection of Sodium alginate-Fe3O4 based Brinkmann type nanofluid flow over a vertical rotating frame. The Tiwari and Das nanofluid model is employed to examine the effects of dimensionless numbers, including Grashof, Eckert, and Schmidt numbers and governing parameters like solid volume fraction of nanoparticles, Hall current, magnetic field, viscous dissipation, and the chemical reaction on the physical quantities. The dimensionless nonlinear partial differential equations are solved using a finite difference method known as Runge-Kutta Fehlberg (RKF-45) method. The variation of dimensionless velocity, temperature, concentration,… More >

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