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  • Open Access


    Quantification of Urban Sprawl for Past-To-Future in Abha City, Saudi Arabia

    Saeed AlQadhi1, Javed Mallick1,*, Swapan Talukdar2, Ahmed Ali Bindajam3, Ahmed Ali A. Shohan3, Shahfahad4

    CMES-Computer Modeling in Engineering & Sciences, Vol.129, No.2, pp. 755-786, 2021, DOI:10.32604/cmes.2021.016640

    Abstract Given that many cities in Saudi Arabia have been observing rapid urbanization since the 1990s, scarce studies on the spatial pattern of urban expansion in Saudi Arabia have been conducted. Therefore, the present study investigates the evidence of land use and land cover (LULC) dynamics and urban sprawl in Abha City of Saudi Arabia, which has been experiencing rapid urbanization, from the past to the future using novel and sophisticated methods. The SVM classifier was used in this study to classify the LULC maps for 1990, 2000, and 2018. The LULC dynamics between 1990–2000, 2000–2018, and 1990–2018 have been analyzed… More >

  • Open Access


    Data-Fusion for Epidemiological Analysis of Covid-19 Variants in UAE

    Anoud Bani-Hani1,*, Anaïs Lavorel2, Newel Bessadet3

    CMC-Computers, Materials & Continua, Vol.68, No.3, pp. 3895-3913, 2021, DOI:10.32604/cmc.2021.015355

    Abstract Since December 2019, a new pandemic has appeared causing a considerable negative global impact. The SARS-CoV-2 first emerged from China and transformed to a global pandemic within a short time. The virus was further observed to be spreading rapidly and mutating at a fast pace, with over 5,775 distinct variations of the virus observed globally (at the time of submitting this paper). Extensive research has been ongoing worldwide in order to get a better understanding of its behaviour, influence and more importantly, ways for reducing its impact. Data analytics has been playing a pivotal role in this research to obtain… More >

  • Open Access


    Prediction of COVID-19 Pandemic Spread in Kingdom of Saudi Arabia

    Abdulaziz Attaallah1, Sabita Khatri2, Mohd Nadeem2, Syed Anas Ansar2, Abhishek Kumar Pandey2, Alka Agrawal2,*

    Computer Systems Science and Engineering, Vol.37, No.3, pp. 313-329, 2021, DOI:10.32604/csse.2021.014933

    Abstract A significant increase in the number of coronavirus cases can easily be noticed in most of the countries around the world. Inspite of the consistent preventive initiatives being taken to contain the spread of this virus, the unabated increase in the cases is both alarming and intriguing. The role of mathematical models in predicting and estimating the spread of the virus, and identifying various preventive factors dependencies has been found important and effective in most of the previous pandemics like Severe Acute Respiratory Syndrome (SARS) 2003. In this research work, authors have proposed the Susceptible-Infectected-Removed (SIR) model variation in order… More >

  • Open Access


    Analyzing the Implications of COVID-19 Pandemic: Saudi Arabian Perspective

    Shakeel Ahmed*, Abdulaziz Alhumam

    Intelligent Automation & Soft Computing, Vol.27, No.3, pp. 835-851, 2021, DOI:10.32604/iasc.2021.015789

    Abstract Most of the patients diagnosed with COVID-19 pandemic usually suffer from mild-to-serious respiratory illness and become stable without any specific care. In fact, in some countries like India the mortality rate is as low. Those who are amongst the most vulnerable groups are the elderly and the ones with chronic ailments like diabetes, heart ailments, and respiratory ailments. However, apart from the impact on the physical health of the patients, this disease has had a more debilitating affect on the mental as well as emotional well-being of the people. Due to continuous watching and protection programs to fight the pandemic,… More >

  • Open Access


    Modelling the Psychological Impact of COVID-19 in Saudi Arabia Using Machine Learning

    Mohammed A. Aleid1, Khaled A. Z. Alyamani2, Mohieddine Rahmouni2,3, Theyazn H. H. Aldhyani2,*, Nizar Alsharif4, Mohammed Y. Alzahrani4

    CMC-Computers, Materials & Continua, Vol.67, No.2, pp. 2029-2047, 2021, DOI:10.32604/cmc.2021.014873

    Abstract This article aims to assess health habits, safety behaviors, and anxiety factors in the community during the novel coronavirus disease (COVID-19) pandemic in Saudi Arabia based on primary data collected through a questionnaire with 320 respondents. In other words, this paper aims to provide empirical insights into the correlation and the correspondence between socio-demographic factors (gender, nationality, age, citizenship factors, income, and education), and psycho-behavioral effects on individuals in response to the emergence of this new pandemic. To focus on the interaction between these variables and their effects, we suggest different methods of analysis, comprising regression trees and support vector… More >

  • Open Access


    Soil Properties for Earthen Building Construction in Najran City, Saudi Arabia

    Yaser Khaled Al-Sakkaf1, Gamil M. S. Abdullah2,*

    CMC-Computers, Materials & Continua, Vol.67, No.1, pp. 127-140, 2021, DOI:10.32604/cmc.2021.014438

    Abstract Earth is the most common and important building material used in the construction industry, since it is found in almost every country in the world. Modern earthen construction is alive and well, and is spread over an enormous geographical area. This technique utilizes various earthen materials and numerous methods, and features many benefits for both construction in general and buildings in particular. Najran, a city located in the south of Saudi Arabia, is distinguished by its heritage of earthen architecture, which displays many advantages and a marvelous variety of types and exterior designs. Many weaknesses of the material, however, along… More >

  • Open Access


    Artificial Neural Networks for Prediction of COVID-19 in Saudi Arabia

    Nawaf N. Hamadneh1, Waqar A. Khan2, Waqar Ashraf3, Samer H. Atawneh4, Ilyas Khan5,*, Bandar N. Hamadneh6

    CMC-Computers, Materials & Continua, Vol.66, No.3, pp. 2787-2796, 2021, DOI:10.32604/cmc.2021.013228

    Abstract In this study, we have proposed an artificial neural network (ANN) model to estimate and forecast the number of confirmed and recovered cases of COVID-19 in the upcoming days until September 17, 2020. The proposed model is based on the existing data (training data) published in the Saudi Arabia Coronavirus disease (COVID-19) situation—Demographics. The Prey-Predator algorithm is employed for the training. Multilayer perceptron neural network (MLPNN) is used in this study. To improve the performance of MLPNN, we determined the parameters of MLPNN using the prey-predator algorithm (PPA). The proposed model is called the MLPNN–PPA. The performance of the proposed… More >

  • Open Access


    Estimating the Impact of COVID-19 Pandemic on the Research Community in the Kingdom of Saudi Arabia

    Abdulaziz Attaallah1, Masood Ahmad2, Adil Hussain Seh2, Alka Agrawal2, Rajeev Kumar2,3,*, Raees Ahmad Khan2

    CMES-Computer Modeling in Engineering & Sciences, Vol.126, No.1, pp. 419-436, 2021, DOI:10.32604/cmes.2021.014263

    Abstract Ever since its outbreak in Wuhan, COVID-19 has cloaked the entire world in a pall of despondency and uncertainty. The present study describes the exploratory analysis of all COVID cases in Saudi Arabia. Besides, the study has executed the forecasting model for predicting the possible number of COVID-19 cases in Saudi Arabia till a defined period. Towards this intent, the study analyzed different age groups of patients (child, adult, elderly) who were affected by COVID-19. The analysis was done city-wise and also included the number of recoveries recorded in different cities. Furthermore, the study also discusses the impact of COVID-19… More >

  • Open Access


    A Deep-CNN Crowd Counting Model for Enforcing Social Distancing during COVID19 Pandemic: Application to Saudi Arabia’s Public Places

    Salma Kammoun Jarraya1,2,*, Maha Hamdan Alotibi1,3, Manar Salamah Ali1

    CMC-Computers, Materials & Continua, Vol.66, No.2, pp. 1315-1328, 2021, DOI:10.32604/cmc.2020.013522

    Abstract With the emergence of the COVID19 virus in late 2019 and the declaration that the virus is a worldwide pandemic, health organizations and governments have begun to implement severe health precautions to reduce the spread of the virus and preserve human lives. The enforcement of social distancing at work environments and public areas is one of these obligatory precautions. Crowd management is one of the effective measures for social distancing. By reducing the social contacts of individuals, the spread of the disease will be immensely reduced. In this paper, a model for crowd counting in public places of high and… More >

  • Open Access


    Fuzzy Based Decision Making Approach for Evaluating the Severity of COVID-19 Pandemic in Cities of Kingdom of Saudi Arabia

    Abdullah Baz1,*, Hosam Alhakami2

    CMC-Computers, Materials & Continua, Vol.66, No.2, pp. 1155-1174, 2021, DOI:10.32604/cmc.2020.013215

    Abstract The World Health Organization declared COVID-19 a pandemic on March 11, 2020 stating that it is a worldwide danger and requires imminent preventive strategies to minimise the loss of lives. COVID-19 has now affected millions across 211 countries in the world and the numbers continue to rise. The information discharged by the WHO till June 15, 2020 reports 8,063,990 cases of COVID-19. As the world thinks about the lethal malady for which there is yet no immunization or a predefined course of drug, the nations are relentlessly working at the most ideal preventive systems to contain the infection. The Kingdom… More >

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