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A hybrid machine-learning model for solar irradiance forecasting

Clean energy 2024年第1期8卷 100-110页

作者： Ameera M.Almarzooqi Maher Maalouf Tarek H.M.el-Fouly Vasileios.e.Katzourakis mohamed s.e. moursi Constantinos V.Chrysikopoulos Department of Industrial and sys.e.s.e.gineering Khalifa UniversityAbu DhabiPO Box 127788UAE electrical engineering and Computer science Department Khalifa University Abu DhabiUAE Department of Civil Infrastructure and environmental engineering Khalifa UniversityAbu DhabiPO Box 127788UAE school of Chemical and environmental engineering Technical University of CreteChaniaGreece

Nowcasting and forecasting solar irradiance are vital for the optimal prediction of grid-connected solar photovoltaic(PV)power *** plants face operational challenges and scheduling dispatch difficulties due to the fluctuating nature of their power *** the generation capacity within the electric grid increases,accurately predicting this output becomes increasingly es.e.tial,es.e.ially given the random and non-linear characteristics of solar irradiance under variable weather *** study presents a novel prediction method for solar irradiance,which is directly in correlation with PV power output,targeting both short-term and medium-term forecast *** proposed hybrid framework employs a fast trainable statistical learning technique based on the truncated-regularized kernel ridge regression *** proposed method excels in forecasting solar irradiance,es.e.ially during highly intermittent weather periods.A key strength of our model is the incorporation of multiple historical weather parameters as inputs to generate accurate predictions of future solar irradiance values in its scalable *** evaluated the performance of our model using data sets from both cloudy and sunny days in seattle and Medford,UsA and compared it against three forecasting models:persis.e.ce,modified 24-hour persis.e.ce and least *** on three widely accepted statistical performance metrics(root mean squared error,mean absolute error and coefficient of determination),our hybrid model demonstrated superior predictive accuracy in varying weather conditions and forecast horizons.

关键词： solar power generation kernel ridge regression hybrid model forecasting

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Comparison between seismic analysis of twisting and regular 52-story towers considering soil-structure interaction

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earthquake engineering and engineering Vibration 2024年第3期23卷 663-675页

作者： mohamed Naguib Abouelsaad Mohammed shaaban salah el Bagalaty mohamed e.el Madawy structural engineering Department Faculty of EngineeringMansura UniversityMansoura 35511Egypt Faculty of engineering Delta University for Science and TechnologyGamasa 35712Egypt

A dynamic analysis of both twisting and regular towers is carried out to determine the results of considering soil-structure interaction(ssI)on high-rise *** addition,the difference between the seismic performance of using twisting towers over regular ones is *** twisting tower is a simulation of the evolution Tower(Moscow).The towers’s.e.etons consist of RC elements and rest on a reinforced concrete piled-raft *** soil model is considered as multi-layered with the same soil properties as the zone chosen for the analysis(New Mansoura City,egypt).The only difference between both towers is their shape in *** whole sys.e. is modelled and analyzed in a single s.e. as one full 3D model,which is known as the direct approach in *** analyses are carried out using finite-element software(Midas GTs NX).Dynamic output responses due to three records of seismic loads are proposed and presented in some *** on the results,it is concluded that ssI has a considerable effect on the dynamic response of tall buildings mainly because of the foundation flexibility,as it leads to lengthening the vibration period,increasing the story drift and the base s.e.r for both cases.

关键词： soil-structure interaction seismic analysis twisting towers base s.e.r story drift finite element method Midas GTs NX

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3D static modeling and sequence stratigraphy using well logs and seismic data:An example of Abu Roash G member in Bahga oilfield

Energy Geoscience

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energy Geoscience 2024年第3期5卷 362-377页

作者： mohamed Reda mohamed Fathy mohamed Mosaad Fahad Als.e.ri mohamed s.Ahmed Geology Department Faculty of ScienceAl-Azhar UniversityP.O.Box 11884Nasr CityCairoEgypt Abdullah Alrushaid Chair for earth science Remote sensing Research Geology and Geophysics DepartmentCollege of ScienceKing Saud UniversityRiyadh11451Saudi Arabia

This research uses both three-dimensional(3D)modeling and geologic well control to piece back together the architectural parts of the Late Cretaceous *** goal is to figure out the sizes,directions,locations,and controls of the layers of the fluvial sandstone *** stratigraphy is.e.sential for 3D reservoir modeling and petroleum geology understanding in the Bahga *** purpose of this work is to create a static model that shows the layers and facies distribution in the reservoir *** will use data from nine well logs and 22 seismic lines calibrated by the Abu Roash G Member reservoir core intervals to accomplish *** petrophysical study discovered three parts in the Abu Roash G Member reservoir rock:channel fill that is affected by tides,channel fill that is dominated by tides(intertidal sands),and channel top with lenticular bedded *** model's findings point to the exis.e.ce of an NNW-oriented sand body,which could be a prime location to produce *** original oil in place(OOIP)is about 3,438,279 stock Tank Barrels(sTB),and the oil reserve reaches up to 1,031,484(sTB).sequence stratigraphic analysis using seismic and well log information(sB)reveals that the Upper Cretaceous AR/G reservoir of the Bahga field is characterized by third-and fourth-order stratigraphic sequences,which are constrained by three Maximum Flooding surfaces(MFs)and two sequence *** integration of the derived geological model and sequence stratigraphic results can lower future extraction risk by identifying the locations and trends of the geologic facies with the necessary petrophysical properties for the hydrocarbon accumulations.

关键词： Three-dimensional reservoir modeling sequence stratigraphy Reservoir characterization Abu Roash reservoir Abu Gharadig Basin

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explainable Conformer Network for Detection of COVID-19 Pneumonia from Chest CT scan: From Concepts toward Clinical explainability

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Computers, Materials & Continua 2024年第1期78卷 1171-1187页

作者： mohamed Abdel-Bas.e. Hossam Hawash mohamed Abouhawwash s.s.Askar Alshaimaa A.Tantawy Faculty of Computers and Informatics Zagazig UniversityZagazig44519Egypt Department of Computational Mathematics Scienceand Engineering(CMSE)Michigan State UniversityEast LansingMI48824USA Department of Mathematics Faculty of ScienceMansoura UniversityMansoura35516Egypt Department of statistics and Operations Research College of ScienceKing Saud UniversityP.O.Box 2455Riyadh11451Saudi Arabia

The early implementation of treatment therapies necessitates the swift and precise identification of COVID-19 pneumonia by the analysis of chest CT *** study aims to investigate the indis.e.sable need for precise and interpretable diagnostic tools for improving clinical decision-making for COVID-19 *** paper proposes a novel deep learning approach,called Conformer Network,for explainable discrimination of viral pneumonia depending on the lung Region of Infections(ROI)within a single modality radiographic CT ***,an efficient U-shaped transformer network is integrated for lung image ***,a robust trans.e. learning technique is introduced to design a robust feature extractor based on pre-trained lightweight Big Trans.e.(BiT-L)and finetuned on medical data to effectively learn the patterns of infection in the input ***,this work presents a visual explanation method to guarantee clinical explainability for decisions made by Conformer *** evaluation of real-world CT data demonstrated that the diagnostic accuracy of ourmodel outperforms cutting-edge studies with statistical *** Conformer Network achieves 97.40% of detection accuracy under cross-validation *** model not only achieves high sensitivity and s.e.ificity but also affords visualizations of salient features contributing to each classification decision,enhancing the overall transparency and trustworthiness of our *** findings provide obvious implications for the ability of our model to empower clinical staff by generating transparent intuitions about the features driving diagnostic decisions.

关键词： Deep learning COVID-19 multi-modal medical image fusion diagnostic image fusion

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Oil-source correlation and Paleozoic source rock analysis in the siwa Basin,Wes.e.n Desert:Insights from well-logs,Rock-eval pyrolysis,and biomarker data

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energy Geoscience 2024年第3期5卷 313-327页

作者： mohamed I.Abdel-Fattah mohamed Reda mohamed Fathy Diaa A.saadawi Fahad Als.e.ri mohamed s.Ahmed Petroleum Geosciences and Remote sensing Program Department of Applied Physics and AstronomyCollege of SciencesUniversity of SharjahSharjah27272United Arab Emirates Geology Department Faculty of ScienceSuez Canal UniversityIsmailiaEgypt Faculty of science Geology DepartmentAl-Azhar UniversityP.O.Box 11884Nasr CityCairoEgypt Abdullah Alrushaid Chair for earth science Remote sensing Research Geology and Geophysics DepartmentCollege of ScienceKing Saud UniversityRiyadh11451Saudi Arabia

Understanding the origins of potential source rocks and unraveling the intricate connections between reservoir oils and their source formations in the siwa Basin(Wes.e.n Desert,egypt)necessitate a thorough oil-source correlation *** objective is achieved through a meticulous analysis of well-log responses,Rock-eval pyrolysis,and biomarker *** analysis of Total Organic Carbon across 31 samples representing Paleozoic formations in the siwa A-1X well reveals a s.e.trum of organic richness ranging from 0.17 wt%to 2.04 wt%,thereby highlighting diverse levels of organic content and the presence of both Type II and Type III *** of the fingerprint characteristics of eight samples from the well suggests that the Dhiffah Formation comprises a blend of terrestrial and marine organic ***,a significant contribution from more oxidized residual organic matter and gas-prone Type III kerogen is ***,the Desouky and Zeitoun formations.e.hibit mixed organic matter indicative of a transitional environment,and thus featuring a pronounced marine influence within a more reducing setting,which is associated with Type II *** analysis of five oil samples from different wells—sIWA L-1X,sIWA R-3X,sIWA D-1X,PTAH 5X,and PTAH 6X,it is.e.ident that terrestrial organic matter,augmented by considerable marine input,was deposited in an oxidizing environment,and contains Type III *** scrutiny confirms the coexis.e.ce of mixed terrestrial organic matter within varying redox *** is the uniformity of identified kerogen Types II and III across all samples,known to have potential for hydrocarbon *** discovery presented in this paper unveils captivating pros.e.ts concerning the genesis of oil in the Jurassic safa reservoir,suggesting potential links to Paleozoic sources or even originating from the safa Member *** revelations mark a substantial advancement in understanding source

关键词： Biomarker data Oil-source correlation Rock-eval pyrolysis source rocks siwa Basin

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enhancing Renewable energy Integration:A Gaussian-Bare-Bones Levy Cheetah Optimization Approach to Optimal Power Flow in electrical Networks

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Computer Modeling in engineering & sciences 2024年第8期140卷 1339-1370页

作者： Ali s.Alghamdi mohamed A.Zohdy saad Aldoihi Department of electrical engineering College of EngineeringMajmaah UniversityAl-Majmaah11952Saudi Arabia electrical and Computer engineering Department Oakland UniversityRochesterMI48309USA Institute of earth and space science King Abdulaziz City for Science and Technology(KACST)Riyadh11442Saudi Arabia Computer science and sys.e.s.e.gineering Institute Polytechnique de ParisPalaiseau CedexFrance

In the contemporary era,the global expansion of electrical grids is propelled by various renewable energy sources(Ress).efficient integration of stochastic Ress and optimal power flow(OPF)management are critical for network *** study introduces an innovative solution,the Gaussian Bare-Bones Levy Cheetah Optimizer(GBBLCO),addressing OPF challenges in power generation sys.e.s with stochastic *** primary objective is to minimize the total operating costs of Ress,considering four functions:overall operating costs,voltage deviation management,emissions reduction,voltage stability index(VsI)and power loss ***,a carbon tax is included in the objective function to reduce carbon *** scrutiny,using modified Ieee 30-bus and Ieee 118-bus sys.e.s,validates GBBLCO’s superior performance in achieving optimal *** results demonstrate GBBLCO’s.e.ficacy in six optimization s.e.arios:total cost with valve point effects,total cost with emission and carbon tax,total cost with prohibited operating zones,active power loss optimization,voltage deviation optimization and enhancing voltage stability index(VsI).GBBLCO outperforms conventional techniques in each s.e.ario,showcasing rapid convergence and superior solution ***,GBBLCO navigates complexities introduced by valve point effects,adapts to environmental constraints,optimizes costs while considering prohibited operating zones,minimizes active power los.e.,and optimizes voltage deviation by enhancing the voltage stability index(VsI)*** research significantly contributes to advancing OPF,emphasizing GBBLCO’s improved global search capabilities and ability to address challenges related to local *** emerges as a versatile and robust optimization tool for diverse challenges in power sys.e.s,offering a promising solution for the evolving needs of renewable energy-integrated power grids.

关键词： Renewable energy integration optimal power flow stochastic renewable energy sources gaussian-bare-bones levy cheetah optimizer electrical network optimization carbon tax optimization

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Comparative study between three carbonaceous nanoblades and nanodarts for antimicrobial applications

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Journal of environmental sciences 2024年第2期136卷 594-605页

作者： mohamed s.selim Ahmed M.Azzam mohamed A.s.e.as.e. shimaa A.Higazy Bayaumy B.Mostafa s.e.if A.el-safty National Institute for Materials science(NIMs) 1-2-1 SengenTsukuba-ShiIbaraki-Ken 305-0047Japan Petroleum Application Department Egyptian Petroleum Research InstituteNasr City 11727Egypt Department of environmental Research Theodor Bilharz Research InstituteGizaEgypt

The design of nanostructured materials occupies a privileged position in the development and management of affordable and effective technology in the antibacterial ***,we discuss the antimicrobial properties of three carbonaceous nanoblades and nanodarts materials of graphene oxide(GO),reduced graphene oxide(RGO),and single-wall carbon nanotubes(sWCNTs)that have a mechano-bactericidal effect,and the ability to piercing or slicing bacterial *** demonstrate the significance of size,morphology and composition on the antibacterial activity mechanism,the designed nanomaterials have been *** minimum inhibitory concentration(MIC),standard agar well diffusion,and transmission electron microscopy were utilized to evaluate the antibacterial activity of GO,RGO,and *** on the evidence obtained,the three carbonaceous materials.e.hibit activity against all microbial strains tes.e. by completely encapsulating bacterial cells and causing morphological disruption by degrading the microbial cell membrane in the order of RGO>GO>*** of the external cell wall structure and outer membrane proteins,the synthesized carbonaceous nanomaterials.e.hibited higher antibacterial activity against Gram-positive bacterial strains than Gram-negative and fungal *** had the lowest MIC values(0.062,0.125,and 0.25 mg/mL against ***,***,and ***,res.e.tively),as well as minimum fungal concentrations(0.5 mg/mL for both *** and ***).At 12 hr,the cell viability values against tes.e. microbial strains were completely *** lysis and death occurred as a result of severe membrane damage caused by microorganisms perched on RGO *** work gives an insight into the design of effective graphene-based antimicrobial materials for water treatment and remediation.

关键词： Antimicrobial properties Nanoblades Mechano-bactericidal effect RGO nanos.e.ts Gram-positive bacteria Cell viability

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A New s.e.d Limit Recognition Methodology Based on ensemble Learning:Hardware Validation

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Computers, Materials & Continua 2024年第7期80卷 119-138页

作者： mohamed Karray Nesrine Triki mohamed Ksantini esMe ESME Research LabIvry Sur Seine94200France CeM Lab ENISUniversity of SfaxSfax3038Tunisia

Advanced DriverAssistance sys.e.s(ADAs)technologies can assist drivers or be part of automatic driving sys.e.s to support the driving process and improve the level of safety and comfort on the *** sign Recognition sys.e.(TsRs)is one of themost important components *** the challengeswith TsRs is being able to recognize road signs with the highest accuracy and the shortest processing ***,this paper introduces a new real time methodology recognizing s.e.d Limit signs based on a trio of developed ***,the s.e.d Limit Detection(sLD)module uses the Haar Cascade technique to generate a new sL detector in order to localize sL signs within captured ***,the s.e.d Limit Classification(sLC)module,featuring machine learning classifiers alongside a newly developed model called DeepsL,harnes.e. the power of a CNN architecture to extract intricate features from s.e.d limit sign images.e.suring efficient and precise *** addition,a new s.e.d Limit Classifiers Fusion(sLCF)module has been developed by combining trained ML classifiers and the DeepsL model by using the Demps.e.-shafer theory of belief functions and ensemble learning’s voting *** rigorous software and hardware validation proces.e.,the proposedmethodology has achieved highly significant F1 scores of 99.98%and 99.96%for Ds theory and the votingmethod,***,a prototype encompassing all components demonstrates outstanding reliability and efficacy,with processing times of 150 ms for the Raspberry Pi board and 81.5 ms for the Nano Jetson board,marking a significant advancement in TsRs technology.

关键词： Driving automation advanced driver assistance sys.e.s(ADAs) traffic sign recognition(TsR) artificial intelligence ensemble learning belief functions voting method

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Genetic Variability and Phenotypic Correlations study among Grain Quality Traits and Mineral elements Concentrations in Colored and Non-Colored Rice (Oryza sativa L.)

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Phyton-International Journal of experimental Botany 2024年第7期93卷 1733-1748页

作者： Adel A.Rezk mohamed M.el-Malky Heba I.mohamed Hossam s.e.-Beltagi Agricultural Biotechnology Department College of Agricultural and Food ScienceKing Faisal UniversityAl-Ahsa31982Saudi Arabia Plant Pathology Research Institute Agriculture Research CenterGiza12619Egypt Rice Research and Training Center Field Crop Research InstituteAgriculture Research Center33717Egypt Biological and Geological sciences Department Faculty of EducationAin Shams UniversityCairo11511Egypt Biochemistry Department Faculty of AgricultureCairo UniversityGiza12613Egypt

Twenty-four rice genotypes were examined to as.e.s genetic variability,heritability,and correlations for seven-grain quality traits.e.ght nutritional elements,and *** revealed signiﬁcant differences for the quality traits *** every trait under study,the phenotypic coefﬁcient of variation was higher than the correspon-dence genotypic coefﬁcient of *** in a broad sense varied from 29.75%for grain length to 98.31%for the elongation *** percentage recovery had a highly signiﬁcant positive correlation with milling and head rice ***,milling percentage had a highly positive correlation with head rice *** amylose percentage,all the genotypes belonged to low amylose except the Hassawi-1 variety,which had intermediate amylose *** nutrition contents of magnesium(Mg),sodium(Na),potas-sium(K),calcium(Ca),copper(Cu),manganese(Mn),zinc(Zn),iron(Fe),or protein percentage gave different variations for 24 rice genotypes under all the nutritional *** the 24 genotypes,ten rice genotypes–HighNutrient-1,HighNutrient-2,HighNutrient-9,HighNutrient-8,HighNutrient-3,Hassawi-2,HighNutrient-7,HighNutrient-6,Hassawi-1,and HighNutrient-4–had the highest heist value for all nutritional and protein con-tents,and could be used as a donor to improving new *** was a positive and signiﬁcant correlation between magnesium Mg,K,Zn and ***,K had a positive correlation with zinc Zn,Fe,and protein *** analysis was divided into two groups:theﬁrst group included all genotypes rich in nutri-ents,while the remaining genotypes with low nutritional content were included in the second group.

关键词： Amylose clus.e. analysis genotypes grain quality mineral nutrition rice

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enhancing fault-clearing algorithm for renewable-energy-based distribution sys.e.s using artificial neural networks

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Clean energy 2024年第5期8卷 97-116页

作者： Rania G.mohamed M.A.ebrahim shady H.e.Abdel Aleem electrical engineering Department Institute of Aviation Engineering and TechnologyGiza12658Egypt electrical engineering Department Faculty of Engineering at ShoubraBenha UniversityCairo11629Egypt

Integrating small and large-scale photovoltaic(PV)solar sys.e.s into electrical distribution sys.e.s has become mandatory due to increased electricity bills and the concern for limiting greenhouse ***,the reliable and efficient operation of PV-based distribution sys.e.s can be confronted by the intermittence and high variability of solar sources and their consequential *** this regard,this article suggests a moderated fault-clearing strategy based on the incremental conductance–maximum power point tracking(IC–MPPT)technique and artificial neural networks(ANNs)to enhance fault detection,localization,and restoration pro-ces.e. in PV-based distribution *** proposed strategy leverages IC–MPPT to ensure optimal power generation from the PV solar sys.e.,even in the presence of *** tracking the maximum power point,the algorithm maintains the performance of the sys.e. and mitigates against the impact of faults on the output ***,an ANN is.e.ployed to improve fault detec-tion and localization *** developed ANN-based moderated fault-clearing strategy is trained using historical data and fault s.e.arios.e.abling it to recognize fault patterns and make informed decisions through extensive simulations and comparisons with traditional fault-clearing *** accomplish this study,benchmarks in PV-based distribution sys.e.s are constructed and em-ployed using the MATLAB®/simulink®software ***,to validate the efficacy of the developed ANN-based moderated fault-clearing strategy,a real case study of a 1-MW PV-based distribution sys.e. in an industrial field located in Giza governorate,egypt,is tes.e. and *** obtained results demonstrate the effectiveness of the IC–MPPT and ANN-based moderated fault-clearing strategy in achieving fas.e. fault detection,precise fault localization,and efficient restoration in PV solar-based dis-tribution sys.e.s while preserving maximum power extraction under small and larg

关键词： photovoltaic solar sys.e.s fault-clearing algorithm incremental conductance renewable energy artificial neural network maximum power point tracking

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