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

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Computers, Materials & Continua 2021年第5期67卷 2029-2047页

作者： mohammed A.Aleid Khaled A.Z.Alyamani Mohieddine Rahmouni Theyazn H.H.Aldhyani Nizar Alsharif mohammed y.alzahrani College of Education King Faisal UniversityAl-Ahsa31982Saudi Arabia Community College in Abqaiq King Faisal UniversityAl-Ahsa31982Saudi Arabia Department of Economics and Quantitative Methods ESSECTUniversity of TunisTunisTunisia Department of Computer Engineering and Science Al-Baha UniversityAl-BahahSaudi Arabia

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 *** other words,this paper aims to provide empirical insights into the correlation and the correspondence between sociodemographic factors(gender,nationality,age,citizenship factors,income,and education),and psycho-behavioral effects on individuals in response to the emergence of this new *** focus on the interaction between these variables and their effects,we suggest different methods of analysis,comprising regression trees and support vector machine regression(SVMR)*** to the regression tree results,the age variable plays a predominant role in health habits,safety behaviors,and *** health habit index,which focuses on the extent of behavioral change toward the commitment to use the health and protection methods,is highly affected by gender and age *** average monthly income is also a relevant factor but has contrasting effects during the COVID-19 pandemic *** results of the SVMR model reveal a strong positive effect of income,with R^(2) values of 99.59%,99.93%and 99.88%corresponding to health habits,safety behaviors,and anxiety.

关键词： COVID-19 health habits safety behaviors anxiety support vector machine regression regression trees

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

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Computers, Materials & Continua 2021年第5期67卷 2141-2160页

作者： Theyazn H.H.Aldhyani Melfi Alrasheed Mosleh Hmoud Al-Adaileh Ahmed Abdullah Alqarni mohammed y.alzahrani Ahmed H.Alahmadi Community College of Abqaiq King Faisal UniversityAl HofufSaudi Arabia Department of Quantitative Methods School of BusinessKing Faisal UniversityAl HofufSaudi Arabia Deanship of E-Learning and Distance Education King Faisal UniversityAl HofufSaudi Arabia Department of Computer Sciences and Information Technology Albaha UniversityAl BahahSaudi Arabia Department of Computer Science and Information Taibah UniversityMadinahKingdom of Saudi Arabia

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 ***,developing surveillance systems for predicting the Covid-19 pandemic at an early stage could save millions of *** this study,a deep learning algorithm and a Holt-trend model are proposed to predict the *** Long-Short Term Memory(LSTM)and Holttrend algorithms were applied to predict confirmed numbers and death *** real time data used has been collected from theWorld Health Organization(WHO).In the proposed research,we have considered three countries to test the proposed model,namely Saudi Arabia,Spain and *** results suggest that the LSTM models show better performance in predicting the cases of coronavirus *** measure performance Mean squared Error(MSE),Root Mean Squared Error(RMSE),Mean error and correlation are employed to estimate the results of the proposed *** empirical results of the LSTM,using the correlation metrics,are 99.94%,99.94%and 99.91%in predicting the number of confirmed cases in the three *** far as the results of the LSTM model in predicting the number of death of Covid-19,they are 99.86%,98.876%and 99.16%with respect to Saudi Arabia,Italy and Spain ***,the experiment’s results of the Holt-Trend model in predicting the number of confirmed cases of Covid-19,using the correlation metrics,are 99.06%,99.96%and 99.94%,whereas the results of the Holt-Trend model in predicting the number of death cases are 99.80%,99.96%and 99.94%with respect to the Saudi Arabia,Italy and Spain *** empirical results indicate the efficient performance of the presented model in predicting the number of confirmed and death cases of Covid-19 in these *** findings provide better insights regarding the future of Covid-19 this pandemic in *** results were obtained by applying time series models,which

关键词： Deep learning algorithm holt-trend prediction Covid-19 machine learning

Human-Animal Affective Robot Touch Classification Using Deep Neural Network

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Computer Systems Science & Engineering 2021年第7期38卷 25-37页

作者： mohammed Ibrahim Ahmed Al-mashhadani Theyazn H.H.Aldhyani Mosleh Hmoud Al-Adhaileh Alwi M.Bamhdi mohammed y.alzahrani Fawaz Waselallah Alsaade Hasan Alkahtani AL-Iraqia University College of EducationComputer DepartmentBaghdadIraq Community College of Abqaiq King Faisal UniversityAl-AhsaSaudi Arabia Deanship of E-learning and Distance Education King Faisal UniversityAl-AhsaSaudi Arabia UMM Al-Qura University College of ComputingMakkahSaudi Arabia Department of Computer Sciences and Information Technology Albaha UniversityAl BahaSaudi Arabia College of Computer Science and Information Technology King Faisal UniversityAl-AhsaSaudi Arabia

Touch gesture recognition is an important aspect in human-robot interaction,as it makes such interaction effective and *** novelty of this study is the development of a system that recognizes human-animal affective robot touch(HAART)using a deep learning *** proposed system was used for touch gesture recognition based on a dataset provided by the Recognition of the Touch Gestures Challenge *** dataset was tested with numerous subjects performing different HAART gestures;each touch was performed on a robotic animal covered by a pressure sensor skin.A convolutional neural network algorithm is proposed to implement the touch recognition system from row inputs of the sensor *** leave-one-subject-out cross-validation method was used to validate and evaluate the proposed system.A comparative analysis between the results of the proposed system and the state-of-the-art performance is *** show that the proposed system could recognize the gestures in almost real time(after acquiring the minimum number of frames).According to the results of the leave-one-subject-out cross-validation method,the proposed algorithm could achieve a classification accuracy of 83.2%.It was also superior compared with existing systems in terms of classification ratio,touch recognition time,and data preprocessing on the same ***,the proposed system can be used in a wide range of real applications,such as image recognition,natural language recognition,and video clip classification.

关键词： Touch gesture recognition touch gesture classification deep learning

The User Analysis of Amazon Using Artificial Intelligence at Customer Churn

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Journal of Data Analysis and Information Processing 2024年第1期12卷 40-48页

作者： mohammed Ali alzahrani Information Technology Department Computing and ICT Faculty Taif University Taif Saudi Arabia

Customer churns remains a key focus in this research, using artificial intelligence-based technique of machine learning. Research is based on the feature-based analysis four main features were used that are selected on the basis of our customer churn to deduct the meaning full analysis of the data set. Data-set is taken from the Kaggle that is about the fine food review having more than half a million records in it. This research remains on feature based analysis that is further concluded using confusion matrix. In this research we are using confusion matrix to conclude the customer churn results. Such specific analysis helps e-commerce business for real time growth in their specific products focusing more sales and to analyze which product is getting outage. Moreover, after applying the techniques, Support Vector Machine and K-Nearest Neighbour perform better than the random forest in this particular scenario. Using confusion matrix for obtaining the results three things are obtained that are precision, recall and accuracy. The result explains feature-based analysis on fine food reviews, Amazon at customer churn Support Vector Machine performed better as in overall comparison.

关键词： Customer Churn Machine Learning Amazon Fine Food Reviews Data Science Artificial Intelligence

Oral candidiasis and potential risk factors among disabled and nondisabled in Al-Baha region, Saudi Arabia

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World Journal of Clinical Cases 2024年第27期12卷 6077-6086页

作者： Abdullah Ali H alzahrani Nagesh Bhat Pankaj Kukreja Eltayeb mohammed Alhassan Abdallah Ibrahim A Mudawi Faisal A alzahrani Mohammad A Albanghali Department of Dental Health Faculty of Applied Medical SciencesAl-Baha UniversityAl Bahah 65731Saudi Arabia Department of Preventive Dental Sciences School of DentistryAlBaha UniversityAl Bahah 65731Saudi Arabia Department of Biomedical Dental Sciences School of DentistryAlBaha UniversityAl Bahah 65731Saudi Arabia Department of Medical Services General Administration Public SecurityThe Saudi Ministry of InteriorRiyadh 11235Saudi Arabia Department of Public Health Faculty of Applied Medical SciencesAl-Baha UniversityAl Bahah 65731Saudi Arabia

BACKGROUND Oral candidiasis(OC)is an oral health disease that could influence patients’oral health quality of *** To estimate prevalence of OC among disabled and non-disabled individuals and its potential risk factors in the Al-Baha region,Saudi *** An observational cross-sectional study was carried out among 148 disabled and non-disabled *** technique of concentrated oral rinse employing the Sabouraud Dextrose Agar medium accompanied with 0.05%chloramphenicol was conducted to assess and isolate *** examination using the World Health Organization guidelines was conducted to examine participants’oral hea-lth status.A pre-designed questionnaire was also used to evaluate sociodemo-graphic,medical history,and oral hygiene habits of the studied *** Out of 148 participants(n=57,38%)had colonized *** of the studied population had visible Candida ***,Candida was found in the oral rinses without the subject presenting any lesions or issues caused by Candida(asymptomatic colonization).The most common prevalent OC among participants were Candida albicans,Candida glabrata,Candida dubliniensis,Candida krusei,Candida tropicalis,and Candida parapsilosis(n=35,61%;n=8,14%;n=6,10%;n=5,9%;n=2,4%;and n=1,2%)***,smoking,poor plaque,and gingival status were key potential risk factors that significantly associated with candida’s density and presence(P=0.001,P=0.001,P=0.01,and P=0.01)*** status had no statistically significant effect on presence and density of *** The prevalence of OC is almost third of the studied population;thus,may provoke a need to develop preventive strategies to reduce the OC rate and establish solid treatment plans.

关键词： Oral health Candida Oral candidiasis Dental public health Disabled Disability Risk factors Epidemiology

The Impact of Simulation Education on Self-Efficacy in Pre-Registration Nursing Students

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Open Journal of Nursing 2024年第1期14卷 51-76页

作者： Ahmed A. Hakami Aisha Hussin Rabie Sultan Ghormallah M. alzahrani Faisal mohammed Alnakhilan Khalid Awaidhalharbi College of Nursing Umm Al-Qura University Makkah Saudi Arabia Al-Noor Specialist Hospital Makkah Saudi Arabia (MOH) Ministry of Health King Fahad Hospital Al Baha Saudi Arabia (MOH) Ministry of Health Eradah Complex Riyadh Saudi Arabia King Salman Medical City Al Madinah Saudi Arabia

This literature review primarily aims to explore and synthesise the previous studies in simulation education research conducted over the past five years related to the effects of simulation training on the self-efficacy of undergraduate pre-registration nursing students. The second aim of this study is to explore additional outcome variables that were examined in the previous studies. Five electronic databases were searched systematically. These databases were MEDLINE, CINAHL Plus, Scopus, Embase and PsycINFO. The PICO model was employed to identify the search terms, with a thesaurus being used to provide synonyms. Reference lists of relevant articles were examined and hand searches of journals were also undertaken. The quality of each study was assessed using the Simulation Research Rubric (SRR). A total of 11 studies were included. All studies explored the impact of simulation education on undergraduate pre-registration nursing. Six studies explored nursing students’ competence and performance and two papers examined their critical thinking. Problem solving, learning motivation, communication skills and knowledge acquisition were examined once. The majority of studies indicated that simulation training has a positive impact on pre-registration nursing students’ self-efficacy and other outcome variables. Furthermore, the study results indicate that simulation training is more dependable than traditional training, and students were extremely satisfied with the simulation training. However, most of the studies included in this review had several gaps, including study design, sample size and dissimilarities between the scales used. Further research with large samples, reliable and valid instruments, and outcomes measures (such as critical thinking and transferability of skills) is required to provide better insight into the effectiveness of simulation in undergraduate nursing education. .

关键词： Simulation Education Self-Efficacy Pre-Registration Nursing Students Clinical Skills Undergraduate Nursing Education Teaching Techniques Decision-Making

Prevalence and associated factors of clubfoot in the eastern province of Saudi Arabia: A hospital-based study

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World Journal of Orthopedics 2024年第7期15卷 635-641页

作者： Ammar K Alomran Bandar A alzahrani Bader S Alanazi mohammed A Alharbi Loay M Bojubara Eman M Alyaseen Department of Orthopedic College of MedicineImam Abdulrahman bin Faisal UniversityDammam 34212Saudi Arabia College of Medicine Imam Abdulrahman bin Faisal UniversityDammam 34212Saudi Arabia College of Medicine Arabian Gulf UniversityManama 329Bahrain

BACKGROUND Clubfoot,or congenital talipes equinovarus,is a widely recognized cause of disability and congenital deformity worldwide,which significantly impacts the quality of *** management of clubfoot requires long-term,multidiscip-linary *** is important to understand how common this condition is in order to assess its impact on the ***,few studies have investigated the prevalence of clubfoot in Saudi *** To determine the prevalence of clubfoot in Saudi Arabia via the patient population at King Fahad University Hospital(KFUH).METHODS This was a retrospective study conducted at one of the largest hospitals in the country and located in one of the most densely populated of the administrative *** Of the 7792 births between 2015 to 2023 that were included in the analysis,42 patients were diagnosed with clubfoot,resulting in a prevalence of 5.3 per 1000 live births at *** The observed prevalence of clubfoot was significantly higher than both global and local estimates,indicating a substantial burden in the study population.

关键词： Clubfoot Talipes equinovarus Congenital talipes equinovarus Prevalence Saudi Arabia

Modeling of Combined Economic and Emission Dispatch Using Improved Sand Cat Optimization Algorithm

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Computers, Materials & Continua 2023年第6期75卷 6145-6160页

作者： Fadwa Alrowais Jaber S.alzahrani Radwa Marzouk Abdullah Mohamed Gouse Pasha mohammed Department of Computer Sciences College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Industrial Engineering College of Engineering at AlqunfudahUmm Al-Qura UniversityMecca24382Saudi Arabia Research Centre Future University in EgyptNew Cairo11845Egypt Department of Computer and Self Development Preparatory Year DeanshipPrince Sattam bin Abdulaziz UniversityAlKharjSaudi Arabia

Combined Economic and Emission Dispatch(CEED)task forms multi-objective optimization problems to be resolved to minimize emission and fuel *** disadvantage of the conventional method is its incapability to avoid falling in local optimal,particularly when handling nonlinear and complex *** have recently received considerable attention due to their enhanced capacity to prevent local optimal solutions in addressing all the optimization problems as a black ***,this paper focuses on the design of an improved sand cat optimization algorithm based CEED(ISCOA-CEED)*** ISCOA-CEED technique majorly concen-trates on reducing fuel costs and the emission of generation ***,the presented ISCOA-CEED technique transforms the equality constraints of the CEED issue into inequality ***,the improved sand cat optimization algorithm(ISCOA)is derived from the integration of tra-ditional SCOA with the Levy Flight(LF)*** last,the ISCOA-CEED technique is applied to solve a series of 6 and 11 generators in the CEED *** experimental validation of the ISCOA-CEED technique ensured the enhanced performance of the presented ISCOA-CEED technique over other recent approaches.

关键词： Economic and emission dispatch multi-objective optimization metaheuristics fuel cost minimization sand cat optimization

Improved Multileader Optimization with Shadow Encryption for Medical Images in IoT Environment

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Computers, Materials & Continua 2023年第2期74卷 3133-3149页

作者： Mesfer Al Duhayyim mohammed Maray Ayman Qahmash Fatma S.Alrayes Nuha Alshuqayran Jaber S.alzahrani mohammed Alghamdi Abdullah Mohamed Department of Computer Science College of Sciences and Humanities-AflajPrince Sattam Bin Abdulaziz UniversitySaudi Arabia Department of Information Systems College of Computer ScienceKing Khalid UniversityAbhaSaudi Arabia Department of Information Systems College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityP.O.Box 84428Riyadh 11671Saudi Arabia Department of Information Systems College of Computer and Information SciencesImam Mohammad Ibn Saud Islamic UniversitySaudi Arabia Department of Industrial Engineering College of Engineering at AlqunfudahUmm Al-Qura UniversitySaudi Arabia Department of Information and Technology Systems College of Computer Science and EngineeringUniversity of JeddahJeddahSaudi Arabia Research Centre Future University in EgyptNew Cairo11845Egypt

Nowadays,security plays an important role in Internet of Things(IoT)environment especially in medical services’domains like disease prediction and medical data *** healthcare sector,huge volumes of data are generated on a daily basis,owing to the involvement of advanced health care *** general terms,health care images are highly sensitive to alterations due to which any modifications in its content can result in faulty *** the same time,it is also significant to maintain the delicate contents of health care images during reconstruction ***,an encryption system is required in order to raise the privacy and security of healthcare data by not leaking any sensitive *** current study introduces Improved Multileader Optimization with Shadow Image Encryption for Medical Image Security(IMLOSIE-MIS)technique for IoT *** aim of the proposed IMLOSIE-MIS model is to accomplish security by generating shadows and encrypting them *** do so,the presented IMLOSIE-MIS model initially generates a set of shadows for every input medical ***,shadow image encryption process takes place with the help of Multileader Optimization(MLO)withHomomorphic Encryption(IMLO-HE)technique,where the optimal keys are generated with the help of MLO *** the receiver side,decryption process is initially carried out and shadow image reconstruction process is *** experimentation analysis was carried out on medical images and the results inferred that the proposed IMLOSIE-MIS model is an excellent performer compared to other *** comparison study outcomes demonstrate that IMLOSIE-MIS model is robust and offers high security in IoT-enabled healthcare environment.

关键词： Medical image security image encryption shadow images homomorphic encryption optimal key generation