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  • Open Access

    ARTICLE

    A Computational Analysis to Burgers Huxley Equation

    Muhammad Saqib1, Muhammad Shoaib Arif2,*, Shahid Hasnain3, Daoud S. Mashat4

    CMC-Computers, Materials & Continua, Vol.67, No.2, pp. 2161-2183, 2021, DOI:10.32604/cmc.2021.014507 - 05 February 2021

    Abstract The efficiency of solving computationally partial differential equations can be profoundly highlighted by the creation of precise, higher-order compact numerical scheme that results in truly outstanding accuracy at a given cost. The objective of this article is to develop a highly accurate novel algorithm for two dimensional non-linear Burgers Huxley (BH) equations. The proposed compact numerical scheme is found to be free of superiors approximate oscillations across discontinuities, and in a smooth flow region, it efficiently obtained a high-order accuracy. In particular, two classes of higher-order compact finite difference schemes are taken into account and… More >

  • Open Access

    ARTICLE

    Deep Learning and Holt-Trend Algorithms for Predicting Covid-19 Pandemic

    Theyazn H. H. Aldhyani1,*, Melfi Alrasheed2, Mosleh Hmoud Al-Adaileh3, Ahmed Abdullah Alqarni4, Mohammed Y. Alzahrani4, Ahmed H. Alahmadi5

    CMC-Computers, Materials & Continua, Vol.67, No.2, pp. 2141-2160, 2021, DOI:10.32604/cmc.2021.014498 - 05 February 2021

    Abstract The Covid-19 epidemic poses a serious public health threat to the world, where people with little or no pre-existing human immunity can be more vulnerable to its effects. Thus, developing surveillance systems for predicting the Covid-19 pandemic at an early stage could save millions of lives. In this study, a deep learning algorithm and a Holt-trend model are proposed to predict the coronavirus. The Long-Short Term Memory (LSTM) and Holt-trend algorithms were applied to predict confirmed numbers and death cases. The real time data used has been collected from the World Health Organization (WHO). In… More >

  • Open Access

    ARTICLE

    Analyzing COVID-19 Impact on the Researchers Productivity through Their Perceptions

    Syeda Javeria Shoukat1, Humaira Afzal2, Muhammad Rafiq Mufti3, Muhammad Khalid Sohail4, Dost Muhammad Khan5, Nadeem Akhtar5, Shahid Hussain6,*, Mansoor Ahmed1

    CMC-Computers, Materials & Continua, Vol.67, No.2, pp. 1835-1847, 2021, DOI:10.32604/cmc.2021.014397 - 05 February 2021

    Abstract Context: Since the end of 2019, the COVID-19 pandemic had a worst impact on world’s economy, healthcare, and education. There are several aspects where the impact of COVID-19 could be visualized. Among these, one aspect is the productivity of researcher, which plays a significant role in the success of an organization. Problem: There are several factors that could be aligned with the researcher’s productivity of each domain and whose analysis through researcher’s feedback could be beneficial for decision makers in terms of their decision making and implementation of mitigation plans for the success of an organization. Method:More >

  • Open Access

    REVIEW

    Automated Test Case Generation from Requirements: A Systematic Literature Review

    Ahmad Mustafa1, Wan M. N. Wan-Kadir1, Noraini Ibrahim1, Muhammad Arif Shah3,*, Muhammad Younas2, Atif Khan4, Mahdi Zareei5, Faisal Alanazi6

    CMC-Computers, Materials & Continua, Vol.67, No.2, pp. 1819-1833, 2021, DOI:10.32604/cmc.2021.014391 - 05 February 2021

    Abstract Software testing is an important and cost intensive activity in software development. The major contribution in cost is due to test case generations. Requirement-based testing is an approach in which test cases are derivative from requirements without considering the implementation’s internal structure. Requirement-based testing includes functional and nonfunctional requirements. The objective of this study is to explore the approaches that generate test cases from requirements. A systematic literature review based on two research questions and extensive quality assessment criteria includes studies. The study identifies 30 primary studies from 410 studies spanned from 2000 to 2018.… More >

  • Open Access

    ARTICLE

    Technology Landscape for Epidemiological Prediction and Diagnosis of COVID-19

    Siddhant Banyal1, Rinky Dwivedi2, Koyel Datta Gupta2, Deepak Kumar Sharma3,*, Fadi Al-Turjman4, Leonardo Mostarda5

    CMC-Computers, Materials & Continua, Vol.67, No.2, pp. 1679-1696, 2021, DOI:10.32604/cmc.2021.014387 - 05 February 2021

    Abstract The COVID-19 outbreak initiated from the Chinese city of Wuhan and eventually affected almost every nation around the globe. From China, the disease started spreading to the rest of the world. After China, Italy became the next epicentre of the virus and witnessed a very high death toll. Soon nations like the USA became severely hit by SARS-CoV-2 virus. The World Health Organisation, on 11th March 2020, declared COVID-19 a pandemic. To combat the epidemic, the nations from every corner of the world has instituted various policies like physical distancing, isolation of infected population and… More >

  • Open Access

    ARTICLE

    Machine Learning-Enabled Power Scheduling in IoT-Based Smart Cities

    Nabeela Awan1, Salman Khan2, Mohammad Khalid Imam Rahmani3, Muhammad Tahir3, Nur Alam MD4,*, Ryan Alturki5, Ihsan Ullah6

    CMC-Computers, Materials & Continua, Vol.67, No.2, pp. 2449-2462, 2021, DOI:10.32604/cmc.2021.014386 - 05 February 2021

    Abstract Recent advancements in hardware and communication technologies have enabled worldwide interconnection using the internet of things (IoT). The IoT is the backbone of smart city applications such as smart grids and green energy management. In smart cities, the IoT devices are used for linking power, price, energy, and demand information for smart homes and home energy management (HEM) in the smart grids. In complex smart grid-connected systems, power scheduling and secure dispatch of information are the main research challenge. These challenges can be resolved through various machine learning techniques and data analytics. In this paper,… More >

  • Open Access

    ARTICLE

    COVID-19 Public Sentiment Insights: A Text Mining Approach to the Gulf Countries

    Saleh Albahli1, Ahmad Algsham1, Shamsulhaq Aeraj1, Muath Alsaeed1, Muath Alrashed1, Hafiz Tayyab Rauf2,*, Muhammad Arif3, Mazin Abed Mohammed4

    CMC-Computers, Materials & Continua, Vol.67, No.2, pp. 1613-1627, 2021, DOI:10.32604/cmc.2021.014265 - 05 February 2021

    Abstract Social media has been the primary source of information from mainstream news agencies due to the large number of users posting their feedback. The COVID-19 outbreak did not only bring a virus with it but it also brought fear and uncertainty along with inaccurate and misinformation spread on social media platforms. This phenomenon caused a state of panic among people. Different studies were conducted to stop the spread of fake news to help people cope with the situation. In this paper, a semantic analysis of three levels (negative, neutral, and positive) is used to gauge… More >

  • Open Access

    ARTICLE

    Modeling the COVID-19 Pandemic Dynamics in Iran and China

    Jin Zhao1, Zubair Ahmad2,*, Zahra Almaspoor2

    CMC-Computers, Materials & Continua, Vol.67, No.2, pp. 2111-2122, 2021, DOI:10.32604/cmc.2021.014259 - 05 February 2021

    Abstract The epidemic outbreak COVID-19 was first detected in the Wuhan city of China and then spread worldwide. It is of great interest to the researchers for its high rate of infection spread and its significant number of fatalities. A detailed scientific analysis of this phenomenon is yet to come. However, it is of interest of governments and other responsible institutions to have the right facts and figures to take every possible necessary action such as an arrangement of the appropriate quarantine activities, estimation of the required number of places in hospitals, assessment of the level… More >

  • Open Access

    ARTICLE

    Rayleigh Waves Propagation in an Infinite Rotating Thermoelastic Cylinder

    A. M. Farhan1,2,*

    CMC-Computers, Materials & Continua, Vol.67, No.2, pp. 2515-2525, 2021, DOI:10.32604/cmc.2021.014255 - 05 February 2021

    Abstract In this paper, we investigated the inuence of rotating half-space on the propagation of Rayleigh waves in a homogeneous isotropic, generalized thermo-elastic body, subject to the boundary conditions that the surface is traction free. In addition, it is subject to insulating thermal conduction. A general solution is obtained by using Lame’ potential’s and Hankel transform. The dispersion equations has been derived separately for two types of Rayleigh wave propagation properties by solving the equations of motion with appropriate boundary conditions. It is observed that the rotation, frequency and r exert some influence in the homogeneous… More >

  • Open Access

    ARTICLE

    Social Media and Stock Market Prediction: A Big Data Approach

    Mazhar Javed Awan1,2,*, Mohd Shafry Mohd Rahim2, Haitham Nobanee3,4,5, Ashna Munawar2, Awais Yasin6, Azlan Mohd Zain 7

    CMC-Computers, Materials & Continua, Vol.67, No.2, pp. 2569-2583, 2021, DOI:10.32604/cmc.2021.014253 - 05 February 2021

    Abstract Big data is the collection of large datasets from traditional and digital sources to identify trends and patterns. The quantity and variety of computer data are growing exponentially for many reasons. For example, retailers are building vast databases of customer sales activity. Organizations are working on logistics financial services, and public social media are sharing a vast quantity of sentiments related to sales price and products. Challenges of big data include volume and variety in both structured and unstructured data. In this paper, we implemented several machine learning models through Spark MLlib using PySpark, which More >

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