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Arabic Sentiment a.alysis of Users’ Opinions of Governmental Mobile Applications

Computers, Materials & Continua 2022年第9期72卷 4675-4689页

作者： mohammed Hadwan mohammed a.al-hagery mohammed al-Sarem Faisal Saeed Department of Information Technology College of ComputerQassim UniversityBuraydah51452Saudi Arabia Department of Computer Science College of Applied SciencesTaiz UniversityTaizYemen Inteligent a.alytic Group College of ComputerQassim UniversityBuraydah51452Saudi Arabia Department of Computer Science College of ComputerQassim UniversityBuraydah51452Saudi Arabia College of Computer Science and Engineering Taibah UniversityMedina42353Saudi Arabia Institute for Artificial Intelligence and Big Data Universiti Malaysia KelantanPengkalan ChepaKota Bharu16100KelantanMalaysia

Different types of pandemics that have appeared from time to time have changed many aspects of daily *** governments encourage their citizens to use certain applications to help control the spread of disease and to deliver other services during *** Saudi government has launched several mobile apps to control the pandemic and have made these apps available through Google Play and the app store.A huge number of reviews are written daily by users to express their opinions,which include significant information to improve these *** manual processing and extracting of information from users’reviews is an extremely difficult and time-consuming ***,the use of intelligent methods is necessary to a.alyse users’reviews and extract issues that can help in improving these *** research aims to support the efforts made by the Saudi government for its citizens and residents by a.alysing the opinions of people in Saudi Arabia that can be found as reviews on Google Play and the app store using sentiment a.alysis and machine learning *** the best of our knowledge,this is the first study to explore users’opinions about governmental apps in Saudi *** findings of this a.alysis will help government officers make the right decisions to improve the quality of the provided services and help application developers improve these applications by fixing potential issues that cannot be identified during application testing phases.A new dataset used for this research includes 8000 user reviews gathered from social media,Google Play and the app *** methods are applied to the dataset,and the results show that the k nearest neighbourhood(KNN)method generates the highest accuracy compared to other implemented methods.

关键词： Arabic sentiment a.alysis software quality user satisfaction improving online governmental services machine learning intelligent systems mobile app

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A Hybrid Neural Network and Box-Jenkins Models for Time Series Forecasting

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Computers, Materials & Continua 2022年第3期70卷 4829-4845页

作者： Mohammad Hadwan Basheer M.al-Ma.aleh Fuad N.al-Badani Rehan Ullah Khan mohammed a.al-hagery Department of Information Technology College of ComputerQassim UniversityBuraydahSaudi Arabia Department of Computer Science College of Applied SciencesTaiz UniversityTaizYemen Intelligent a.alytics Group(IAG) College of ComputerQassim UniversityBuraydahSaudi Arabia Faculty of Computer Sciences and Information Systems Thamar UniversityThamarYemen Faculty of Administration Science Ibb UniversityIbbYemen Department of Computer Science College of ComputerQassim UniversityBuraydahSaudi Arabia

Time series forecasting plays a significant role in numerous applications,including but not limited to,industrial planning,water consumption,medical domains,exchange rates and consumer price *** main problem is insufficient forecasting *** present study proposes a hybrid forecastingmethods to address this *** proposed method includes three *** first model is based on the autoregressive integrated moving average(ARIMA)statistical model;the second model is a back propagation neural network(BPNN)with adaptive slope and momentum parameters;and the thirdmodel is a hybridization between ARIMA and BPNN(ARIMA/BPNN)and artificial neural networks and ARIMA(ARIMA/ANN)to gain the benefits of linear and *** forecasting models proposed in this study are used to predict the indices of the consumer price index(CPI),and predict the expected number of cancer patients in the Ibb Province in *** standard measures used to evaluate the proposed method include(i)mean square error,(ii)mean absolute error,(iii)root mean square error,and(iv)mean absolute percentage *** on the computational results,the improvement rate of forecasting the CPI dataset was 5%,71%,and 4%for ARIMA/BPNN model,ARIMA/ANN model,and BPNN model respectively;while the result for cancer patients’dataset was 7%,200%,and 19%for ARIMA/BPNNmodel,ARIMA/ANN model,and BPNNmodel ***,it is obvious that the proposed method reduced the randomness degree,and the alterations affected the time series with data *** ARIMA/ANN model outperformed each of its components when it was applied separately in terms of increasing the accuracy of forecasting and decreasing the overall errors of forecasting.

关键词： Hybrid model forecasting non-linear data time series models cancer patients neural networks box-jenkins consumer price index

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An Efficient Scheme for Interference Mitigation in 6G-IoT Wireless Networks

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Computers, Materials & Continua 2021年第12期69卷 3889-3902页

作者： Fahd N.al-Wesabi Imran Khan Nadhem Nemri mohammed a.al-hagery Huda G.Iskander Quang Ngoc Nguyen Babar Shah Ki-Il Kim Department of Computer Science King Khalid UniversityMuhayel AseerKSA Department of Electrical Engineering University of Engineering and TechnologyPeshawarPakistan Department of Information Systems King Khalid UniversityMayahel AseerKSA Department of Computer Science College of ComputerQassim UniversitySaudi Arabia Faculty of Computer and IT Sana’a UniversitySana’aYemen Department of Communications and Computer Engineering Faculty of Science and EngineeringWaseda UniversityShinjuku-kuTokyo169-0051Japan College of Technological Innovation Zayed UniversityAbu DhabiUAE Department of Computer Science and Engineering Chungnam National UniversityDaejeon34134Korea

The Internet of Things(IoT)is the fourth technological revolution in the global information industry after computers,the Internet,and mobile communication *** combines radio-frequency identification devices,infrared sensors,global positioning systems,and various other *** sensing equipment is connected via the Internet,thus forming a vast *** these physical devices are connected to the Internet,the user terminal can be extended and expanded to exchange information,communicate with anything,and carry out identification,positioning,tracking,monitoring,and triggering of corresponding events on each device in the *** real life,the IoT has a wide range of applications,covering many fields,such as smart homes,smart logistics,fine agriculture and animal husbandry,national defense,and *** of the most significant factors in wireless channels is interference,which degrades the system *** the existing QR decomposition-based signal detection method is an emerging topic because of its low complexity,it does not solve the problem of poor detection ***,this study proposes a maximumlikelihood-based QR decomposition *** main idea is to estimate the initial level of detection using the maximum likelihood principle,and then the other layer is detected using a reliable *** optimal candidate is selected from the feedback by deploying the candidate points in an unreliable *** results show that the proposed algorithm effectively reduces the interference and propagation error compared with the algorithms reported in the literature.

关键词： 6G networks internet of things resource allocation optimization

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Identification of Tuberculosis and Coronavirus Patients Using Hybrid Deep Learning Models

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Computers, Materials & Continua 2023年第7期76卷 881-894页

作者： mohammed a.al Ghamdi Computer Science Department Umm Al-Qura UniversityMakkah City24243Saudi Arabia

Considerable resources,technology,and efforts are being utilized worldwide to eradicate the *** certain measures taken to prevent the further spread of the disease have been successful,efforts to completely wipe out the coronavirus have been *** patients have symptoms similar to those of chest Tuberculosis(TB)or pneumonia *** tuberculosis and coronavirus are similar because both diseases affect the lungs,cause coughing and produce an irregular respiratory *** diseases can be confirmed through X-ray *** is a difficult task to diagnose COVID-19,as coronavirus testing kits are neither excessively available nor very *** addition,specially trained staff and specialized equipment in medical laboratories are needed to carry out a coronavirus ***,most of the staff is not fully trained,and several laboratories do not have special equipment to perform a coronavirus ***,hospitals and medical staff are under stress to meet necessary *** of the time,these staffs confuse the tuberculosis or pneumonia patient with a coronavirus patient,as these patients present similar *** meet the above challenges,a comprehensive solution based on a deep learning model has been proposed to distinguish COVID-19 patients from either tuberculosis patients or healthy *** framework contains a fusion of Visual Geometry Group from Oxford(VGG16)and Residual Network(ResNet18)algorithms as VGG16 contains robust convolutional layers,and Resnet18 is a good *** proposed model outperforms other machine learning and deep learning models as more than 94%accuracy for multiclass identification has been achieved.

关键词： Tuberculosis coronavirus X-ray deep learning VGG16 and ResNet18

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Unveiling the impact:COVID-19's influence on bacterial resistance in the Kingdom of Bahrain

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World Journal of Virology 2025年第1期14卷 83-98页

作者： Nermin K Saeed Safiya K almusawi Noor a.albalooshi mohammed al-Beltagi Medical Microbiology Section Department of PathologySalmaniya Medical ComplexGovernmental HospitalsManama 12Bahrain Medical Microbiology Section Department of PathologyRoyal College of Surgeons in Ireland-Medical University of BahrainBusaiteen 15503MuharraqBahrain Department of Paediatrics Faculty of MedicineTanta UniversityTanta 31511AlghrabiaEgypt Department of Pediatric University Medical CenterKing Abdulla Medical CityArabian Gulf UniversityManama 26671AlgharbiaBahrain

BACKGROUND Antibiotic resistance is a growing global health threat,and understanding local trends in bacterial isolates and their susceptibility patterns is crucial for effective infection control and antimicrobial *** coronavirus disease 2019(COVID-19)pandemic has introduced additional complexities,potentially influencing these *** To a.alyze trends in bacterial isolates and their antibiotic susceptibility patterns at Salmaniya Medical Complex from 2018 to 2023,with a specific focus on the impact of the COVID-19 pandemic on these *** A retrospective a.alysis of microbiological data was conducted,covering the period from 2018 to *** study included key bacterial pathogens such as Escherichia coli(***),Klebsiella pneumoniae,Acinetobacter baumannii,Pseudomonas aeruginosa,and Staphylococcus aureus,among *** antibiotic susceptibility profiles of these isolates were assessed using standard laboratory *** contextualize the findings,the findings were compared with similar studies from other regions,including China,India,Romania,Saudi Arabia,the United Arab Emirates,Malaysia,and United *** The study revealed fluctuating trends in the prevalence of bacterial isolates,with notable changes during the COVID-19 *** example,a significant increase in the prevalence of Staphylococcus aureus was observed during the pandemic years,while the prevalence of *** showed a more variable *** resistance rates varied among the different pathogens,with a concerning rise in resistance to commonly used antibiotics,particularly among Klebsiella pneumoniae and ***,the study identified an alarming increase in the prevalence of multidrug-resistant(MDR)strains,especially within Klebsiella pneumoniae and *** *** impact of the COVID-19 pandemic on these trends was evident,with shifts in the frequency,resistance patterns,and the emergence of MDR bacteria among several key ***

关键词： Multidrug-resistant organisms Antibiotic susceptibility COVID-19 pandemic Antimicrobial stewardship Bacterial isolates Salmaniya Medical Complex Bahrain

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Network Quality Assessment in Heterogeneous Wireless Settings: An Optimization Approach

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Computers, Materials & Continua 2022年第4期71卷 439-455页

作者： Sultan H.almotiri mohammed a.al Ghamdi Computer Science Department College of Computer and Information ScienceUmm AlQura UniversityMakkahKingdom of Saudi Arabia

The identification of an effective network which can efficiently meet the service requirements of the target,while maintaining ultimate performance at an increased level is significant and challenging in a fully interconnected wireless *** wrong selection can contribute to unwanted situations like frustrated users,slow service,traffic congestion issues,missed and/or interrupted calls,and wastefulness of precious network *** schemes estimate the handoff need and cause the network screening process by a single *** strategies are not effective enough because traffic characteristics,user expectations,network terminology and other essential device metrics are not taken into *** article describes an intelligent computing technique based on Multiple-Criteria Decision-Making(MCDM)approach developed based on integrated Fuzzy AHP-TOPSIS which ensures flexible usability and maximizes the experience of end-users in miscellaneous wireless *** different components the handover need is assessed and the desired network is ***,fuzzy sets provide effective solutions to address decision making problems where experts counter uncertainty to make a *** proposed research endeavor will support designers and developers to identify,select and prioritize best attributes for ensuring flexible usability in miscellaneous wireless *** results of this research endeavor depict that this proposed computational procedure would be the most conversant mechanism for determining the usability and experience of end-users.

关键词： Wireless sensor networks fuzzy logic AHP-TOPSIS miscellaneous network intelligent computing techniques

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A Systematic Literature Review of Deep Learning algorithms for Segmentation of the COVID-19 Infection

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Computers, Materials & Continua 2023年第6期75卷 5717-5742页

作者： Shroog alshomrani Muhammad Arif mohammed a.al Ghamdi Department of Computer Science College of Computer and Information SciencesUmm AlQura UniversityMakkah24231Saudi Arabia

Coronavirus has infected more than 753 million people,ranging in severity from one person to another,where more than six million infected people died ***-aided diagnostic(CAD)with artificial intelligence(AI)showed outstanding performance in effectively diagnosing this virus in *** tomography is a complementary diagnostic tool to clarify the damage of COVID-19 in the lungs even before symptoms appear in *** paper conducts a systematic literature review of deep learning methods for classifying the segmentation of COVID-19 infection in the *** used the methodology of systematic reviews and meta-a.alyses(PRISMA)flow *** research aims to systematically a.alyze the supervised deep learning methods,open resource datasets,data augmentation methods,and loss functions used for various segment shapes of COVID-19 infection from computerized tomography(CT)chest *** have selected 56 primary studies relevant to the topic of the *** have compared different aspects of the algorithms used to segment infected areas in the CT *** to deep learning in the segmentation of infected areas still need to be developed to predict smaller regions of infection at the beginning of their appearance.

关键词： COVID-19 segmentation chest CT images deep learning systematic review 2D and 3D supervised deep learning

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Synthesis and optimization of high surface area mesoporous date palm fiber-based nanostructured powder activated carbon for aluminum removal

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Chinese Journal of Chemical Engineering 2021年第4期34卷 472-484页

作者： alfarooq O.Basheer Marlia M.Hanafiah mohammed Abdulhakim alsaadi Y.al-Douri Abbas a.al-Raad Department of Earth Sciences and Environment Faculty of Science and TechnologyUniversiti Kebangsaan Malaysia43600 BangiSelangorMalaysia Centre for Tropical Climate Change System Institute of Climate ChangeUniversiti Kebangsaan MalaysiaBangi 43600SelangorMalaysia Nanotechnology and Ca.alysis Research Center(NANOCAT) University of Malaya50603 Kuala LumpurMalaysia National Chair of Materials Science and Metallurgy University ofNizwa611 NizawaOman University Research Center Cihan University SulaimaniyaSulaymaniyah 46002Iraq Department of Mechatronics Engineering Faculty of Engineering and Natural SciencesBahcesehir University34349 BesiktasIstanbulTurkey

Date palm fiber(DPF)derived from agrowaste was utilized as a new precursor for the optimized synthesis of a costeffective,nanostructured,powderactivated carbon(nPAC)for aluminum(al3+)removal from aqueous solutions using carbonization,KOH activation,response surface methodology(RSM)and central composite design(CCD).The optimum synthesis condition,activation temperature,time and impregnation ratio were found to be 650℃,1.09 hour and 1:1,***,the optimum conditions for removal were 99.5%and 9.958 mgg 1 in regard to uptake *** optimum conditions of nPAC was a.alyzed and characterized using XRD,FTIR,FESEM,BET,TGA and Zeta ***,the adsorption of the al3+conditions was optimized with an integrated RSMCCD experimental *** results revealed that the adsorption kinetics data was well fitted by the pseudosecond order model,whereas the adsorption isotherm data was best represented by the Freundlich isotherm *** activated carbon indicated that DPF can serve as a costeffective precursor adsorbent for al^(3+)removal.

关键词： Agricultural waste Nanocomposites Wastewater treatment Industrial applications

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Decoding molecular mechanisms:brain aging and alzheimer's disease

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Neural Regeneration Research 2025年第8期20卷 2279-2299页

作者： Mahnoor Hayat Rafay ali Syed Hammad Qaiser Mohammad Uzair Khalid al-Regaiey Roaa Khallaf Lubna Abdullah mohammed albassam Imdad Kaleem Xueyi Wang Ran Wang Mehwish SBhatti Shahid Bashir Atta-ur-Rahman School of Applied Biosciences(ASAB) National University of Sciences and Technology(NUST)IslamabadPakistan Department of Biotechnology Quaid-i-Azam UniversityIslamabadPakistan Department of Biological Sciences Faculty of Basic&Applied SciencesInternational Islamic University Islamabad(IIUI)IslamabadPakistan Department of Bioengineering King Fahd University of Petroleum and MineralsDhahranSaudi Arabia Department of Physiology College of MedicineKing Saud UniversityRiyadhSaudi Arabia Department of Neurology Neuroscience CenterKing Fahad Specialist HospitalDammamSaudi Arabia Department of Mental Health Neuroscience CenterKing Fahad Specialist HospitalDammamSaudi Arabia Department of Biosciences Commission on Science and Technology for Sustainable Development in the South(COMSATS University)IslamabadPakistan Department of Psychiatry The First Hospital of Hebei Medical UniversityShijiazhuangHebei ProvinceChina Mental Health Institute of Hebei Medical University ShijiazhuangHebei ProvinceChina Department of Neurobiology and Behavior University of CaliforniaIrvineCAUSA Neuroscience Center King Fahad Specialist Hospital DammamDammamSaudi Arabia

The complex morphological,anatomical,physiological,and chemical mechanisms within the aging brain have been the hot topic of research for *** aging process alters the brain structure that affects functions and cognitions,but the worsening of such processes contributes to the pathogenesis of neurodegenerative disorders,such as alzheimer's *** these observable,mild morphological shifts,significant functional modifications in neurotransmission and neuronal activity critically influence the aging *** these changes is important for maintaining cognitive health,especially given the increasing prevalence of age-related conditions that affect *** review aims to explore the age-induced changes in brain plasticity and molecular processes,differentiating normal aging from the pathogenesis of alzheimer's disease,thereby providing insights into predicting the risk of dementia,particularly alzheimer's disease.

关键词： alzheimer’s disease brain aging cognitive health dementia molecular mechanisms neuronal activity neuroplasticity neurotransmission

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Coati Optimization-Based Energy Efficient Routing Protocol for Unmanned Aerial Vehicle Communication

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Computers, Materials & Continua 2023年第6期75卷 4805-4820页

作者： Hanan Abdullah Mengash Hamed alqahtani mohammed Maray Mohamed K.Nour Radwa Marzouk mohammed Abdullah al-hagery Heba Mohsen Mesfer al Duhayyim Department of Information Systems College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Information Systems College of Computer ScienceCenter of Artificial Intelligence and Unit of CybersecurityKing Khalid UniversityAbha62529Saudi Arabia Department of Information Systems College of Computer ScienceKing Khalid UniversityAbha62529Saudi Arabia Department of Computer Sciences College of Computing and Information SystemsUmm Al-Qura UniversityMecca24382Saudi Arabia Department of Computer Science College of ComputerQassim UniversityBuraydah52571Saudi Arabia Department of Computer Science Faculty of Computers and Information TechnologyFuture University in EgyptNew Cairo11835Egypt Department of Computer Science College of Sciences and Humanities-AflajPrince Sattam bin Abdulaziz UniversityAl-Kharj16278Saudi Arabia

With the flexible deployment and high mobility of Unmanned Aerial Vehicles(UAVs)in an open environment,they have generated con-siderable attention in military and civil applications intending to enable ubiquitous connectivity and foster agile *** difficulty stems from features other than mobile ad-hoc network(MANET),namely aerial mobility in three-dimensional space and often changing *** the UAV network,a single node serves as a forwarding,transmitting,and receiving node at the same ***,the communication path is multi-hop,and routing significantly affects the network’s performance.A lot of effort should be invested in performance a.alysis for selecting the optimum routing *** this motivation,this study modelled a new Coati Optimization algorithm-based Energy-Efficient Routing Process for Unmanned Aerial Vehicle Communication(COAER-UAVC)*** presented COAER-UAVC technique establishes effective routes for communication between the *** is primarily based on the coati characteristics in nature:if attacking and hunting iguanas and escaping from ***,the presented COAER-UAVC technique concentrates on the design of fitness functions to minimize energy utilization and communication delay.A varied group of simulations was performed to depict the optimum performance of the COAER-UAVC *** experimental results verified that the COAER-UAVC technique had assured improved performance over other approaches.

关键词： Artificial intelligence unmanned aerial vehicle data communication routing protocol energy efficiency

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