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Carbonate rocks resistivity determination using dual and triple porosity conductivity models

Petroleum 2020年第1期6卷 35-42页

作者： Zeeshan Tariq Mohamed mahmoud Hasan al-Youssef Mohammad Rasheed Khan Department of Petroleum Engineering King Fahd University of Petroleum&MineralsDhahran31261Saudi Arabia

The rocks may be classified as Archie rocks or Non-Archie rocks,depending on the link between pore structure and resistivity of the *** carbonate rocks,keeping this factor in view,the applicability of Archie's law tends to be unreasonable and employing Archie's equation will ultimately lead to inaccurate estimates of the water *** investigators have reported models that forms a link between laboratory results and field well logs to determine water saturation in intricate pore *** case of complex systems,Archie's law fails to correctly define the resistivity-index *** addition,it is imperative to carry out investigations at lower saturation values in order to elaborate the non-Archie *** brings the dual and triple porosity conductivity models into the *** these models are essential in defining the considerable changes of the resistivity-index curves,both qualitatively and *** linkage between the two models is depicted electrically in series or in ***,it is possible to have a combination of the two *** a result,the experimental results can be modeled accurately using least *** work presents two models to determine water saturation in carbonate rocks,containing dual and triple porosity *** study also investigates the impact of different influential parameters such as saturation exponents,conductivity ratios,and pore volume fraction of each network systems,on the new ***,the effect of each parameter is individually studied and the sensitivity analysis on the RI curves is produced.A new approach to apply these models is also explained which requires the use of NMR log,mercury injection capillary pressure(MICP)measurement,and simple plotting techniques to determine the water *** proposed new models help petrophysicists to estimate water saturation in Non-Archie rocks,containing double and triple porosity network systems.

关键词： Dual porosity Triple porosity Carbonate rocks Water saturation models

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Intelligent Forensic Investigation Using Optimal Stacked Autoencoder for Critical Industrial Infrastructures

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Computers, Materials & Continua 2022年第8期72卷 2275-2289页

作者： Abdullah S.al-Malaise al-Ghamdi mahmoud Ragab F.J.alsolami Hani Choudhry Ibrahim Rizqallah alzahrani Information Systems Department Faculty of Computing and Information Technology King Abdulaziz UniversityJeddah21589Saudi Arabia Information Technology Department Faculty of Computing and Information TechnologyKing Abdulaziz UniversityJeddah21589Saudi Arabia Centre of Artificial Intelligence for Precision Medicines King Abdulaziz UniversityJeddah21589Saudi Arabia Mathematics Department Faculty of ScienceAl-Azhar UniversityNaser City11884CairoEgypt Computer Science Department Faculty of Computing and Information Technology King Abdulaziz UniversityJeddah21589Saudi Arabia Biochemistry Department Faculty of ScienceKing Abdulaziz UniversityJeddah21589Saudi Arabia Computer Science and Engineering Department College of Computer Science and EngineeringUniversity of Hafr Al BatinAl JamiahHafar Al Batin39524Saudi Arabia

Industrial Control Systems(ICS)can be employed on the industrial processes in order to reduce the manual labor and handle the complicated industrial system processes as well as communicate *** of Things(IoT)integrates numerous sets of sensors and devices via a data network enabling independent *** incorporation of the IoT in the industrial sector leads to the design of Industrial Internet of Things(IIoT),which find use in water distribution system,power plants,*** the IIoT is susceptible to different kinds of attacks due to the utilization of Internet connection,an effective forensic investigation process becomes *** study offers the design of an intelligent forensic investigation using optimal stacked autoencoder for critical industrial *** proposed strategy involves the design of manta ray foraging optimization(MRFO)based feature selection with optimal stacked autoencoder(OSAE)model,named MFROFS-OSAE *** primary objective of the MFROFS-OSAE technique is to determine the presence of abnormal events in critical industrial ***-OSAE approach involves several subprocesses namely data gathering,data handling,feature selection,classification,and parameter ***,the MRFO based feature selection approach is designed for the optimal selection of feature ***,the OSAE based classifier is derived to detect abnormal events and the parameter tuning process is carried out via the coyote optimization algorithm(COA).The performance validation of the MFROFS-OSAE technique takes place using the benchmark dataset and the experimental results reported the betterment of the MFROFS-OSAE technique over the recent approaches interms of different measures.

关键词： Industrial control systems internet of things artificial intelligence feature selection deep learning

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Optimized Artificial Neural Network Techniques to Improve Cybersecurity of Higher Education Institution

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Computers, Materials & Continua 2022年第8期72卷 3385-3399页

作者： Abdullah Saad al-Malaise al-Ghamdi mahmoud Ragab Maha Farouk S.Sabir Ahmed Elhassanein Ashraf A.Gouda Information Systems Department Faculty of Computing and Information Technology King Abdulaziz UniversityJeddah21589Saudi Arabia Information Technology Department Faculty of Computing and Information TechnologyKing Abdulaziz UniversityJeddah21589Saudi Arabia Centre of Artificial Intelligence for Precision Medicines King Abdulaziz UniversityJeddah21589Saudi Arabia Mathematics Department Faculty of ScienceAl-Azhar UniversityNaser City11884CairoEgypt Mathematics Department College of ScienceUniversity of BishaBishaSaudi Arabia Mathematics Department Faculty of ScienceDamanhour UniversityDamanhourEgypt

Education acts as an important part of economic growth and improvement in human *** educational sectors have transformed a lot in recent days,and Information and Communication Technology(ICT)is an effective part of the education *** every action in university and college,right from the process fromcounselling to admissions and fee deposits has been *** records,quiz,evaluation,mark,and grade submissions involved the utilization of the ***,security is essential to accomplish cybersecurity in higher security institutions(HEIs).In this view,this study develops an Automated Outlier Detection for CyberSecurity in Higher Education Institutions(AOD-CSHEI)*** AOD-CSHEI technique intends to determine the presence of intrusions or attacks in the *** AOD-CSHEI technique initially performs data pre-processing in two stages namely data conversion and class *** addition,the Adaptive Synthetic(ADASYN)technique is exploited for the removal of outliers in the ***,the sparrow search algorithm(SSA)with deep neural network(DNN)model is used for the classification of data into the existence or absence of intrusions in the HEIs ***,the SSA is utilized to effectually adjust the hyper parameters of the DNN *** order to showcase the enhanced performance of the AOD-CSHEI technique,a set of simulations take place on three benchmark datasets and the results reported the enhanced efficiency of the AOD-CSHEI technique over its compared methods with higher accuracy of 0.9997.

关键词： Higher security institutions intrusion detection system artificial intelligence deep neural network hyperparameter tuning deep learning

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Intelligent Firefly algorithm Deep Transfer Learning Based COVID-19 Monitoring System

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Computers, Materials & Continua 2023年第2期74卷 2889-2903页

作者： mahmoud Ragab Mohammed W.al-Rabia Sami Saeed Binyamin Ahmed A.aldarmahi Information Technology Department Faculty of Computing and Information TechnologyKing Abdulaziz UniversityJeddah 21589Saudi Arabia Centre for Artificial Intelligence in Precision Medicines King Abdulaziz UniversityJeddah 21589Saudi Arabia Mathematics Department Faculty of ScienceAl-Azhar UniversityNaser City 11884CairoEgypt Department of Medical Microbiology and Parasitology Faculty of MedicineKing Abdulaziz UniversityJeddah 21589Saudi Arabia Health Promotion Center King Abdulaziz UniversityJeddah 21589Saudi Arabia Computer and Information Technology Department The Applied CollegeKing Abdulaziz UniversityJeddah 21589Saudi Arabia Basic Science Department College of Science and Health ProfessionsKing Saud Bin Abdulaziz University for Health SciencesJeddah 21423Saudi Arabia King Abdullah International Medical Research Center Ministry of National Guard-Health AffairsJeddah 21423Saudi Arabia

With the increasing and rapid growth rate of COVID-19 cases,the healthcare scheme of several developed countries have reached the point of *** important and critical steps in fighting against COVID-19 is powerful screening of diseased patients,in such a way that positive patient can be treated and isolated.A chest radiology image-based diagnosis scheme might have several benefits over traditional *** accomplishment of artificial intelligence(AI)based techniques in automated diagnoses in the healthcare sector and rapid increase in COVID-19 cases have demanded the requirement of AI based automated diagnosis and recognition *** study develops an Intelligent Firefly algorithm Deep Transfer Learning Based COVID-19Monitoring System(IFFA-DTLMS).The proposed IFFADTLMSmodelmajorly aims at identifying and categorizing the occurrence of COVID19 on chest *** attain this,the presented IFFA-DTLMS model primarily applies densely connected networks(DenseNet121)model to generate a collection of feature *** addition,the firefly algorithm(FFA)is applied for the hyper parameter optimization of DenseNet121 ***,autoencoder-long short term memory(AE-LSTM)model is exploited for the classification and identification of *** ensuring the enhanced performance of the IFFA-DTLMS model,a wide-ranging experiments were performed and the results are reviewed under distinctive *** experimental value reports the betterment of IFFA-DTLMS model over recent approaches.

关键词： COVID-19 artificial intelligence intelligent systems deep learning decision making

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Assessing effects of deficit irrigation techniques on water productivity of tomato for subsurface drip irrigation system

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International Journal of Agricultural and Biological Engineering 2018年第4期11卷 156-167页

作者： mahmoud S Hashem Tarek Zin El-Abedin Hussein M al-Ghobari Agricultural Engineering Department College of Food and Agriculture SciencesKing Saud UniversityRiyadh 11451Saudi Arabia Agricultural Engineering Research Institute(AEnRI) Agricultural Research CenterGizaEgypt Agricultural Engineering Department College of AgricultureAlexandria UniversityAlexandriaEgypt

Water resources are subjected to ever-increasing supply constraints due to extensive agricultural water demand for irrigated ***,water-saving irrigation strategies need to be *** present study was conducted to explore the possibilities of using regulated deficit irrigation(RDI)and partial root zone drying irrigation(PRD)methods as water-saving irrigation techniques for subsurface *** objective of this study are to assess the effects of RDI and PRD irrigation on the water productivity of vegetable crops(tomato)under SSD systems in arid climatic conditions,and to compare the responses of tomato crops to PRD,RDI,and FI under an SSD system in terms of productivity,crop quality,and the amount of water *** field experiment was conducted during the fall 2014-2015 and 2015-2016 seasons in an experimental field located on an educational farm owned by the Faculty of Food and Agriculture Sciences Department,King Saud University,Riyadh,Kingdom of Saudi *** area of 102.7 m^(2)(13 m×7.9 m)was allocated for the experiment to manage three treatments:RDI,PRD,and full irrigation(FI).The RDI and PRD treatments received 70%of the irrigation water volume of *** was replicated three *** most important results indicated that the soil water content(SWC)for the RDI and PRD treatments was lower than that of the FI *** had the highest stomatal conductance values(gs),while PRD had the lowest stomatal conductance *** photosynthetic rate(A_(n))was lower under RDI and PRD compared to ***,there was no significant change in A_(n) between treatments for most readings taken during both time periods,which means that the water saving treatments(PRD and RDI)did not affect the net photosynthesis rate,thereby enhancing irrigation water use efficiency(IWUE)under DI *** water-saving irrigation techniques decreased transpiration rate(T)compared to the FI *** values of the abscisic acid(ABA)contents were higher

关键词： full irrigation(FI) regulated deficit irrigation(RDI) partial root zone drying(PRD) irrigation water use efficiency(IWUE)

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An Intelligent Hazardous Waste Detection and Classification Model Using Ensemble Learning Techniques

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Computers, Materials & Continua 2023年第2期74卷 3315-3332页

作者： Mesfer al Duhayyim Saud S.alotaibi Shaha al-Otaibi Fahd N.al-Wesabi mahmoud Othman Ishfaq Yaseen Mohammed Rizwanullah Abdelwahed Motwakel Department of Computer Science College of Sciences and Humanities-AflajPrince Sattam bin Abdulaziz UniversitySaudi Arabia Department of Information Systems College of Computing and Information SystemUmm Al-Qura UniversitySaudi Arabia Department of Information Systems College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Computer Science College of Science and Arts at MuhayelKing Khalid UniversityMuhayel AseerSaudi Arabia Department of Computer Science Faculty of Computers and Information TechnologyFuture University in EgyptNew Cairo11835Egypt Department of Computer and Self Development Preparatory Year DeanshipPrince Sattam bin Abdulaziz UniversityAlKharjSaudi Arabia

Proper waste management models using recent technologies like computer vision,machine learning(ML),and deep learning(DL)are needed to effectively handle the massive quantity of increasing ***,waste classification becomes a crucial topic which helps to categorize waste into hazardous or non-hazardous ones and thereby assist in the decision making of the waste management *** study concentrates on the design of hazardous waste detection and classification using ensemble learning(HWDC-EL)technique to reduce toxicity and improve human *** goal of the HWDC-EL technique is to detect the multiple classes of wastes,particularly hazardous and non-hazardous *** HWDC-EL technique involves the ensemble of three feature extractors using Model Averaging technique namely discrete local binary patterns(DLBP),EfficientNet,and *** addition,the flower pollination algorithm(FPA)based hyperparameter optimizers are used to optimally adjust the parameters involved in the EfficientNet and DenseNet121 ***,a weighted voting-based ensemble classifier is derived using three machine learning algorithms namely support vector machine(SVM),extreme learning machine(ELM),and gradient boosting tree(GBT).The performance of the HWDC-EL technique is tested using a benchmark Garbage dataset and it obtains a maximum accuracy of 98.85%.

关键词： Hazardous waste image classification ensemble learning deep learning intelligent models human health weighted voting model

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Examination of Pine Wilt Epidemic Model through Efficient algorithm

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Computers, Materials & Continua 2022年第6期71卷 5293-5310页

作者： ali Raza Emad E.mahmoud A.M.al-Bugami Dumitru Baleanu Muhammad Rafiq Muhammad Mohsin Muneerah al Nuwairan Department of Mathematics Govt.Maulana Zafar Ali Khan Graduate College WazirabadPunjab Higher Education Department(PHED)Lahore54000Pakistan Department of Mathematics College of ScienceTaif UniversityTaif21944Saudi Arabia Department of Mathematics Cankaya UniversityBalgatAnkara06530Turkey Department of Medical Research China Medical UniversityTaichung40402Taiwan Department of Mathematics Faculty of SciencesUniversity of Central PunjabLahore54600Pakistan Department of Mathematics Technische Universitat Chemnitz6209111Germany Department of Mathematics and Statistics King Faisal UniversityAl Ahsa31982Saudi Arabia

Pine wilt is a dramatic disease that kills infected trees within a few weeks to a few *** cause is the pathogen Pinewood *** plant-parasitic nematodes are attached to plant roots,but pinewood nematodes are found in the tops of *** kill the tree by feeding the cells around the resin *** modeling of a pine wilt disease is based on six compartments,including three for plants(susceptible trees,exposed trees,and infected trees)and the other for the beetles(susceptible beetles,exposed beetles,and infected beetles).The deterministic modeling,along with subpopulations,is based on Law of mass *** stability of the model along with equilibria is studied *** authentication of analytical results is examined through well-known computer methods like Non-standard finite difference(NSFD)and the model’s feasible properties(positivity,boundedness,and dynamical consistency).In the end,comparison analysis shows the effectiveness of the NSFD algorithm.

关键词： Pine wilt disease modeling NSFD algorithm linearization of NSFD algorithm results

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Modeling CO_(2) Emission of Middle Eastern Countries Using Intelligent Methods

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Computers, Materials & Continua 2021年第12期69卷 3767-3781页

作者： Mamdouh El Haj Assad Ibrahim Mahariq Zaher al Barakeh mahmoud Khasawneh Mohammad ali Amooie Sustainable and Renewable Energy Engineering Department University of SharjahPO Box 27272SharjahUAE College of Engineering and Technology American University of the Middle EastKuwait Department of Mechanical and Industrial Engineering Louisiana State UniversityUSA

CO_(2) emission is considerably dependent on energy consumption and on share of energy sources as well as on the extent of economic ***,these factors must be considered for CO_(2) emission prediction for seven middle eastern countries including Iran,Kuwait,United Arab Emirates,Turkey,Saudi Arabia,Iraq and *** order to propose a predictive model,a Multilayer Perceptron Artificial Neural Network(MLP ANN)is *** transfer functions including logsig,tansig and radial basis functions are utilized in the hidden layer of the ***,various numbers of neurons are applied in the structure of the *** is revealed that using MLP ANN makes it possible to accurately predict CO_(2) emission of these *** addition,it is concluded that using logsig transfer function leads to the highest accuracy with minimum value of mean squared error(MSE)which is followed by the networks with radial basis and tansig transfer *** R-squared of the networks with logsig,radial basis and tansig transfer functions are 0.9998,0.9997 and 0.9996,***,comparison of the proposed model with a similar study,considered five countries in the same region,reveals higher accuracy in term of MSE.

关键词： CO_(2)emission artificial neural network middle eastern countries transfer function

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A Drones Optimal Path Planning Based on Swarm Intelligence algorithms

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Computers, Materials & Continua 2022年第7期72卷 365-380页

作者： mahmoud Ragab ali altalbe Abdullah Saad al-Malaise alGhamdi SAbdel-khalek Rashid A.Saeed Information Technology Department Faculty of Computing and Information TechnologyKing Abdulaziz UniversityJeddah 21589Saudi Arabia Center of Artificial Intelligence for Precision Medicines King Abdulaziz UniversityJeddah 21589Saudi Arabia Information Systems Department Faculty of Computing and Information TechnologyKing Abdulaziz UniversityJeddah 21589Saudi Arabia Department of Mathematics Faculty of ScienceAl-Azhar UniversityNaser City 11884CairoEgypt Department of Mathematics Faculty of ScienceTaif UniversityTaifSaudi Arabia Department of Mathematics Faculty of ScienceSohag UniversitySohagEgypt Department of Computer Engineering College of Computers and Information TechnologyTaif UniversityTaifSaudi Arabia

The smart city comprises various interlinked elements which communicate data and offers urban life to *** Aerial Vehicles(UAV)or drones were commonly employed in different application areas like agriculture,logistics,and *** improving the drone flying safety and quality of services,a significant solution is for designing the Internet of Drones(IoD)where the drones are utilized to gather data and people communicate to the drones of a specific flying region using the mobile devices is for constructing the Internet-of-Drones,where the drones were utilized for collecting the data,and communicate with *** addition,the SIRSS-CIoD technique derives a tuna swarm algorithm-based clustering(TSA-C)technique to choose cluster heads(CHs)and organize clusters in IoV ***,the SIRSS-CIoD technique involves the design of a biogeography-based optimization(BBO)technique to an optimum route selection(RS)*** design of clustering and routing techniques for IoD networks in smart cities shows the novelty of the study.A wide range of experimental analyses is carried out and the comparative study highlighted the improved performance of the SIRSS-CIoD technique over the other approaches.

关键词： Drones smart city swarm intelligence route selection internet of drones networking

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Spontaneous bacterial peritonitis:risk factors and causative organisms

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Asian Pacific Journal of Tropical Medicine 2009年第6期2卷 52-58页

作者： mahmoud M al-Bendary mahmoud Abdel-Aziz Waleed A al-Sherbeeny Raghda El-Sayed Farag Abdel-Hady El-Gilany Mohammad Hosam Eldeen Zaghloul Tropical Medicine Unit Community Medicine DepartmentCollege of MedicineMansoura UniversityEgypt Clinical Pathology Department College of MedicineMansoura UniversityEgypt

Objective:To determine the prevalent pathogens responsible for spontaneous bacterial peritonitis(SBP) and their sensitivity pattern,to test the efficiency of different culture techniques in microbial isolation,and to study the diagnostic predictors of such ***:One hundred eight SBP episodes from 92 adult patients were compared to 88 cirrhotic ascites patients cross - matched with age and sex without *** fluid was subjected to cytological,biochemical examination and culture on both conventional and blood culture bottles at the bedside for bacterial identification and antimicrobial susceptibility ***:The prevalence of SBP was 25.02%.Logistic regression analysis revealed that;previous SBP episode,low ascitic fluid protein levels, high serum creatinine and low serum albumin levels were the independent significant predictors of *** forty - five per cent of SBP episodes were detected by conventional culture compared to 73.15%by modified technique with a significant *** - negative bacteria were the cause of SBP in 46(58.23%) culture positive *** coli and Staphylococcus aureus were the most commonly detected organisms. Resistance to different antibiotics was ***:Culture of ascitic fluid in blood culture bottles at bedside increases the sensitivity of SBP *** is a recent increase in Gram - positive pathogen with emergence of multidrug *** recent changes may have an impact on guidelines for management and treatment of SBP in our locality.

关键词： Spontaneous bacterial peritonitis Paracentesis Bedside inoculation Blood bottle culture

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