Abhishek Kumar Pandey¹, Jehad F. Al-Amri², Ahmad F. Subahi³, Rajeev Kumar^4,*, Raees Ahmad Khan¹

Computer Systems Science and Engineering, Vol.41, No.3, pp. 959-974, 2022, DOI:10.32604/csse.2022.021443

Abstract The outbreak of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2 virus or COVID-19) disease was declared pandemic by the World Health Organization (WHO) on March 11, 2020. COVID-19 has already affected more than 211 nations. In such a bleak scenario, it becomes imperative to analyze and identify those regions in Saudi Arabia that are at high risk. A preemptive study done in the context of predicting the possible COVID-19 hotspots would facilitate in the implementation of prompt and targeted countermeasures against SARS-CoV-2, thus saving many lives. Working towards this intent, the present study adopts a… More >

Abdulwahab Ali Almazroi¹, Raja Sher Afgun Usmani^2,*

Intelligent Automation & Soft Computing, Vol.32, No.1, pp. 389-400, 2022, DOI:10.32604/iasc.2022.020588

Abstract COVID-19 pandemic has affected more than 144 million people and spread to over 200 countries. The prediction of COVID-19 behaviour and trend is crucial to prevent its spreading. Kingdom of Saudi Arabia (KSA) is Asia’s fifth largest country, and it hosts the two holiest cities of the Islamic world. KSA hosts millions of pilgrims every year, and it is of great importance to predict the COVID-19 spread to organize these religious activities and bring life to normality in KSA. This study proposes four tree-based ensemble methods to predict the COVID-19 daily new cases in KSA.… More >

Saeed AlQadhi¹, Javed Mallick^1,*, 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,… More >

Anoud Bani-Hani^1,*, 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… More >

Abdulaziz Attaallah¹, Sabita Khatri², Mohd Nadeem², Syed Anas Ansar², Abhishek Kumar Pandey², Alka Agrawal^2,*

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… More >

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… More >

Mohammed A. Aleid¹, Khaled A. Z. Alyamani², Mohieddine Rahmouni^2,3, Theyazn H. H. Aldhyani^2,*, 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… More >

Yaser Khaled Al-Sakkaf¹, Gamil M. S. Abdullah^2,*

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… More >

Nawaf N. Hamadneh¹, Waqar A. Khan², Waqar Ashraf³, Samer H. Atawneh⁴, Ilyas Khan^5,*, 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. More >

Abdulaziz Attaallah¹, Masood Ahmad², Adil Hussain Seh², Alka Agrawal², Rajeev Kumar^2,3,*, 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… More >