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Intelligent Deep Data Analytics Based Remote Sensing Scene Classification Model

Computers, Materials & Continua 2022年第7期72卷 1921-1938页

作者： ahmed althobaiti Abdullah Alhumaidi Alotaibi Sayed Abdel-Khalek Suliman A.Alsuhibany Romany F.Mansour Department of Electrical Engineering College of EngineeringTaif UniversityP.O.Box 11099Taif21944Saudi Arabia Department of Science and Technology College of RanyahTaif UniversityP.O.Box 11099Taif21944Saudi Arabia Department of Mathematics College of ScienceP.O.Box 11099Taif UniversityTaif21944Saudi Arabia Department of Computer Science College of ComputerQassim UniversityBuraydah51452Saudi Arabia Department of Mathematics Faculty of ScienceNew Valley UniversityEl-Kharga72511Egypt

Latest advancements in the integration of camera sensors paves a way for newUnmannedAerialVehicles(UAVs)applications such as analyzing geographical(spatial)variations of earth science in mitigating harmful environmental impacts and climate *** have achieved significant attention as a remote sensing environment,which captures high-resolution images from different scenes such as land,forest fire,flooding threats,road collision,landslides,and so on to enhance data analysis and decision *** scene classification has attracted much attention in the examination of earth data captured by *** paper proposes a new multi-modal fusion based earth data classification(MMF-EDC)*** MMF-EDC technique aims to identify the patterns that exist in the earth data and classifies them into appropriate class *** MMF-EDC technique involves a fusion of histogram of gradients(HOG),local binary patterns(LBP),and residual network(ResNet)*** fusion process integrates many feature vectors and an entropy based fusion process is carried out to enhance the classification *** addition,the quantum artificial flora optimization(QAFO)algorithm is applied as a hyperparameter optimization *** AFO algorithm is inspired by the reproduction and the migration of flora helps to decide the optimal parameters of the ResNet model namely learning rate,number of hidden layers,and their number of ***,Variational Autoencoder(VAE)based classification model is applied to assign appropriate class labels for a useful set of feature *** proposedMMF-EDCmodel has been tested using UCM and WHU-RS *** proposed MMFEDC model attains exhibits promising classification results on the applied remote sensing images with the accuracy of 0.989 and 0.994 on the test UCM and WHU-RS dataset respectively.

关键词： Remote sensing unmanned aerial vehicles deep learning artificial intelligence scene classification

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Nanosecond pulse and dual-wavelength Q-switched 1.5 μm fiber laser using MAX phase Cr2TiAlC2 saturable absorber

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Optoelectronics Letters 2025年第1期21卷 7-12页

作者： ahmed Shakir AL-HITI Hiba HASSAN Department of Electrical Engineering Faculty of Engineering University of Anbar Department of Laser and Optoelectronics Engineering University of Technology-Iraq

We demonstrated a new type of MAX phase material, chromium titanium aluminum carbide（Cr2TiAlC2） polymer film, to generate a passively Q-switched erbium-doped fiber laser（EDFL）. The film thickness was measured to be around 45 μm, which was fabricated using the embedding method with polyvinyl alcohol（PVA） polymer as hoster. The saturable absorber（SA） film demonstrates a dual-wavelength passively Q-switched EDFL which operates at 1 531 nm and 1 560.19 nm, respectively. The Q-switching pulse duration could be varied from 2.46 μs to 770 ns, while the repetition rate varied from 92.76 kHz to 106.6 kHz with an increasing input pumping range from 154 mW to 300 mW. The maximum output power and pulse energy of 15.05 mW and 141.18 nJ were obtained at the maximum input power of 300 mW, respectively.

关键词： Saturable absorbers

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Vascular endothelial growth factor:a double-edged sword in the development of white matter lesions

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Neural Regeneration Research 2025年第1期20卷 191-192页

作者： Narek Manukjan Daniel Fulton Zubair ahmed WMatthijs Blankesteijn Sébastien Foulquier Department of Pharmacology and Toxicology Maastricht UniversityMaastrichtThe Netherlands CARIM-School for Cardiovascular Diseases Maastricht UniversityMaastrichtThe Netherlands Neuroscience and Ophthalmology Institute of Inflammation and AgeingUniversity of BirminghamEdgbastonBirminghamUK Centre for Trauma Sciences Research University of BirminghamEdgbastonBirminghamUK MHeNs-School for Mental Health and Neuroscience Maastricht UniversityMaastrichtThe Netherlands Department of Neurology Maastricht University Medical CenterMaastrichtThe Netherlands

As the population ages,the burden of age-related diseases becomes ***,over 55 million people suffer from dementia worldwide,with Alzheimer’s disease being the most common ***,it is becoming clearer that underlying vascular pathology such as cerebral small vessel disease(cSVD)may be a more detrimental cause for dementia(Cuadrado-Godia et al.,2018).It is estimated that 10%-30%of the elderly population and 35%-90%of all dementia patients exhibit signs of *** term cSVD refers to pathology affecting the small vessels of the brain,which can lead to lacunar cerebral infarcts,enlarged perivascular spaces,and cortical hemorrhages(Cuadrado-Godia et al.,2018).CSVD is often associated with cognitive decline,gait problems,and dementia(Cuadrado-Godia et al.,2018).

关键词： pathology becoming white

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Bio-Inspired Numerical Analysis of COVID-19 with Fuzzy Parameters

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Computers, Materials & Continua 2022年第8期72卷 3213-3229页

作者： F.M.Allehiany Fazal Dayan F.F.Al-Harbi Nesreen althobaiti Nauman ahmed Muhammad Rafiq Ali Raza Mawahib Elamin Department of Mathematical Sciences College of Applied SciencesUmm Al-Qura UniversityMakkah21955Saudi Arabia Department of Mathematics and Statistics University of LahoreLahorePakistan Department of Mathematics School of ScienceUniversity of Management and TechnologyLahorePakistan Department of Physics College of SciencePrincess Nourah Bint Abdulrahman UniversityRiyadh11671Saudi Arabia Department of Mathematics and Statistics College of ScienceTaif UniversityTaif21944Saudi Arabia Department of Mathematics Faculty of SciencesUniversity of Central PunjabLahorePakistan Department of Mathematics Govt.Maulana Zafar Ali Khan Graduate College WazirabadPunjab Higher Education Department(PHED)Lahore54000Pakistan Department of Mathematics College of Science and ArtsQassim UniversityRiyadh Al KhabraSaudi Arabia

Fuzziness or uncertainties arise due to insufficient knowledge,experimental errors,operating conditions and parameters that provide inaccurate *** concepts of susceptible,infectious and recovered are uncertain due to the different degrees in susceptibility,infectivity and recovery among the individuals of the *** differences can arise,when the population groups under the consideration having distinct habits,customs and different age groups have different degrees of resistance,*** realistic models are needed which consider these different degrees of susceptibility infectivity and recovery of the *** this paper,a Susceptible,Infected and Recovered(SIR)epidemic model with fuzzy parameters is *** infection,recovery and death rates due to the disease are considered as fuzzy *** basic reproduction number and fuzzy equilibrium points have been derived for the studied *** is then solved numerically with three different techniques,forward Euler,Runge-Kutta fourth order method(RK-4)and the nonstandard finite difference(NSFD)methods *** NSFD technique becomes more efficient and reliable among the others and preserves all the essential features of a continuous dynamical system.

关键词： Fuzzy parameters SIR model NSFD scheme fuzzy equilibrium points fuzzy stability analysis

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Dynamic Interaction Analysis of Coupled Axial-Torsional-Lateral Mechanical Vibrations in Rotary Drilling Systems

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Structural Durability & Health Monitoring 2025年第1期19卷 77-103页

作者： Sabrina Meddah Sid ahmed Tadjer Abdelhakim Idir Kong Fah Tee Mohamed Zinelabidine Doghmane Madjid Kidouche Applied Automation Laboratory Faculty of Hydrocarbons and ChemistryUniversity of BoumerdesBoumerdes35000Algeria Institute of Electrical and Electronic Engineering(IGEE) University of BoumerdesBoumerdes35000Algeria Laboratory of the Electrification of Industrial Enterprises University of BoumerdesBoumerdes35000Algeria Electrical Engineering Department Mohamed Boudiaf University of M’silaM’sila28000Algeria Department of Civil and Environmental Engineering King Fahd University of Petroleum&MineralsDhahran31261Saudi Arabia Interdisciplinary Research Center for Construction and Building Materials King Fahd University of Petroleum&Minerals(KFUPM)Dhahran31261Saudi Arabia

Maintaining the integrity and longevity of structures is essential in many industries,such as aerospace,nuclear,and *** achieve the cost-effectiveness of large-scale systems in petroleum drilling,a strong emphasis on structural durability and monitoring is *** study focuses on the mechanical vibrations that occur in rotary drilling systems,which have a substantial impact on the structural integrity of drilling *** study speciﬁcally investigates axial,torsional,and lateral vibrations,which might lead to negative consequences such as bit-bounce,chaotic whirling,and high-frequency *** events not only hinder the efﬁciency of drilling but also lead to exhaustion and harm to the system’s components since they are difﬁcult to be detected and controlled in real *** study investigates the dynamic interactions of these vibrations,speciﬁcally in their high-frequency modes,usingﬁeld data obtained from measurement while ***ﬁndings have demonstrated the effect of strong coupling between the high-frequency modes of these vibrations on drilling sys-tem *** obtained results highlight the importance of considering the interconnected impacts of these vibrations when designing and implementing robust control ***,integrating these compo-nents can increase the durability of drill bits and drill strings,as well as improve the ability to monitor and detect ***,by exploiting theseﬁndings,the assessment of structural resilience in rotary drilling systems can be ***,the study demonstrates the capacity of structural health monitoring to improve the quality,dependability,and efﬁciency of rotary drilling systems in the petroleum industry.

关键词： Rotary drilling systems mechanical vibrations structural durability dynamic interaction analysis ﬁeld data analysis

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New Trends in the Modeling of Diseases Through Computational Techniques

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Computer Systems Science & Engineering 2023年第6期45卷 2935-2951页

作者： Nesreen althobaiti Ali Raza Arooj Nasir Jan Awrejcewicz Muhammad Rafiq Nauman ahmed Witold Pawłowski Muhammad Jawaz Emad E.Mahmoud Department of Mathematics and Statistics College of ScienceTaif UniversityP.O.Box 11099Taif21944Saudi Arabia Department of Mathematics Govt.Maulana Zafar Ali Khan Graduate College WazirabadPunjab Higher Education Department(PHED)Lahore54000Pakistan Baqai Medical University Karachi75340Pakistan Shalamar Medical and Dental College Lahore54000Pakistan Department of Automation Biomechanics and MechatronicsLodz University of Technology1/15 Stefanowskiego St.90-924LodzPoland Department of Mathematics Faculty of Sciences and TechnologyUniversity of Central PunjabLahore54000Pakistan Department of Mathematics and Statistics University of LahoreLahore54590Pakistan Institute of Machine Tools and Production Engineering Lodz University of Technology1/15 Stefanowskiego St.90-537LodzPoland

The computational techniques are a set of novel problem-solving methodologies that have attracted wider attention for their excellent *** handling strategies of real-world problems are artificial neural networks(ANN),evolutionary computing(EC),and many *** estimated fifty thousand to ninety thousand new leishmaniasis cases occur annually,with only 25%to 45%reported to the World Health Organization(WHO).It remains one of the top parasitic diseases with outbreak and mortality *** 2020,more than ninety percent of new cases reported to World Health Organization(WHO)occurred in ten countries:Brazil,China,Ethiopia,Eritrea,India,Kenya,Somalia,South Sudan,Sudan,and *** transmission of visceral leishmaniasis is studied dynamically and *** study included positivity,boundedness,equilibria,reproduction number,and local stability of the model in the dynamical *** detailed methods like Runge Kutta and Euler depend on time steps and violate the physical relevance of the *** produce negative and unbounded results,so in disease dynamics,such developments have no biological significance;in other words,these results are *** the implicit nonstandard finite difference method does not depend on time step,positive,bounded,dynamic and *** the computational techniques and their results were compared using computer simulations.

关键词： Real-world problem differential equations computational techniques analysis

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Federated Learning with Blockchain Assisted Image Classification for Clustered UAV Networks

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Computers, Materials & Continua 2022年第7期72卷 1195-1212页

作者： Ibrahim Abunadi Maha M.althobaiti Fahd N.Al-Wesabi Anwer Mustafa Hilal Mohammad Medani Manar ahmed Hamza Mohammed Rizwanullah Abu Serwar Zamani Department of Information Systems Prince Sultan UniversityRafha StreetRiyadh11586Saudi Arabia Department of Computer Science College of Computing and Information TechnologyTaif UniversityTaif21944Saudi Arabia Department of Computer Science College of Science&Art at MahayilKing Khalid UniversityMuhayel Aseer62529Saudi Arabia Faculty of Computer and IT Sana’a UniversitySana’a61101Yemen Department of Computer and Self Development Prince Sattam bin Abdulaziz UniversityAl-Kharj16278Saudi Arabia Department of Information Systems College of Science&Art at MahayilKing Khalid UniversityMuhayel Aseer62529Saudi Arabia

The evolving“Industry 4.0”domain encompasses a collection of future industrial developments with cyber-physical systems(CPS),Internet of things(IoT),big data,cloud computing,***,the industrial Internet of things(IIoT)directs data from systems for monitoring and controlling the physical world to the data processing system.A major novelty of the IIoT is the unmanned aerial vehicles(UAVs),which are treated as an efficient remote sensing technique to gather data from large *** are commonly employed in the industrial sector to solve several issues and help decision *** the strict regulations leading to data privacy possibly hinder data sharing across autonomous *** learning(FL)becomes a recent advancement of machine learning(ML)which aims to protect user *** this aspect,this study designs federated learning with blockchain assisted image classification model for clustered UAV networks(FLBIC-CUAV)on IIoT *** proposed FLBIC-CUAV technique involves three major processes namely clustering,blockchain enabled secure communication and FL based image *** UAV cluster construction process,beetle swarm optimization(BSO)algorithm with three input parameters is designed to cluster the UAVs for effective *** addition,blockchain enabled secure data transmission process take place to transmit the data from UAVs to cloud ***,the cloud server uses an FL with Residual Network model to carry out the image classification process.A wide range of simulation analyses takes place for ensuring the betterment of the FLBIC-CUAV *** experimental outcomes portrayed the betterment of the FLBIC-CUAV approach over the recent state of art methods.

关键词： UAV networks clustering secure communication blockchain federated learning image classification

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Anatomical and Molecular Identification of Ornamental Plant Ficus ***

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Phyton-International Journal of Experimental Botany 2023年第5期92卷 1329-1347页

作者： Abtisam Binnoubah Rim Hamdy Osama G.Ragab ahmed M.El-Taher ahmed Abou El-Yazied Fatmah A.Safhi Hala A.Elzilal Ashwaq T.althobaiti Salha M.ALshamrani Diaa Abd El Moneim ahmed El-Banhawy Department of Botany Faculty of ScienceUniversity of SabrathaSabratha999116Libya Department of Botany Faculty of ScienceCairo UniversityGiza12111Egypt Department of Botany and Microbiology Faculty of Science(Boys Branch)Al-Azhar UniversityCairo11884Egypt Department of Agricultural Botany Faculty of AgricultureAl-Azhar UniversityCairo11884Egypt Department of Horticulture Faculty of AgricultureAin Shams UniversityCairo11566Egypt Department of Biology College of SciencePrincess Nourah bint Abdulrahman UniversityRiyadh11671Saudi Arabia Department of Science and Technology College of RanyahTaif UniversityTaif21944Saudi Arabia Department of Biology College of ScienceTaif UniversityTaif21944Saudi Arabia Department of Biology College of ScienceUniversity of JeddahJeddah21959Saudi Arabia Department of Plant Production(Genetic Branch) Faculty of Environmental Agricultural SciencesArish UniversityEl-Arish45511Egypt Department of Botany and Microbiology Faculty of ScienceSuez Canal UniversityIsmailia41522Egypt

This present study includes twelve species that represent the Ficus genus,namely;aspera,carica,tinctoria ***,hirta,hispida,neriifolia,palmata,pumila,racemosa,septica,sur,and sycomorus,belonging to the Moraceae *** species samples were collected from various locations in *** study focused on the anatomical and molecular characteristics of mature foliage *** the identification and classification of taxa are highly dependent on the anatomical features of leaves,the anatomical characteristics were recorded in the form of a comparison between the examined plants in the data *** study aims to contribute to the identification of the studied species based on the anatomical details of the matured *** characterization includes the variations in upper and lower epidermal layers that are covered by a thin or thick cuticle;the number of palisade and spongy layers;crystals;secretory elements;lithocysts;the midrib zone has parenchyma associated with mechanical tissue,vascular system,and investigation of trichomes;on the other hand,in the current study,the phylogenetic analysis was conducted by using the ITS and 5.8 S *** the analysis of all the available data,it could be stated that there is an overall agreement with the anatomical character dendrogram.

关键词： ITS trichomes leaf anatomy Ficus moraceae

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Influence of biomass density and food to microorganisms ratio on the mixed culture type I methanotrophs enriched from activated sludge

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Journal of Environmental Sciences 2018年第8期30卷 87-96页

作者： ahmed AlSayed ahmed Fergala ahmed Eldyasti Department of Civil Engineering Lassonde School of Engineering York University

Methanotrophic based process can be the remedy to offset the wastewater treatment facilities increasing energy requirements due to methanotroph＇s unique ability to integrate methane assimilation with multiple biotechnological applications like biological nitrogen removal and methanol production. Regardless of the methanotrophic process end product, the challenge to maintain stable microbial growth in the methanotrophs cultivation bioreactor at higher cell densities is one of the major obstacles facing the process upscaling. Therefore, a series of consecutive batch tests were performed to attentively investigate the biomass density influence on type I methanotrophs bacterial growth. In addition, food to microorganisms（F/M）, carbon to nitrogen（C/N） and nitrogen to microorganisms（N/M） ratio effect on the microbial activity was studied for the first time. It was clarified that the F/M ratio is the most influencing factor on the microbial growth at higher biomass densities rather than the biomass density increase, whereas C/N and N/M ratio change, while using nitrate as the nitrogen source,does not influence methanotrophs microbial growth. These study results would facilitate the scaling up of methanotrophic based biotechnology by identifying that F/M ratio as the key parameter that influences methanotrophs cultivation at high biomass densities.

关键词： Methanotrophs Wastewater treatment Food to microorganisms ratio Biomass density

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On Learning Adaptive Service Compositions

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Journal of Systems Science and Systems Engineering 2021年第4期30卷 465-481页

作者： ahmed Moustafa Department of Computer Science Nagoya Institute of TechnologyGokiso-choShowa-kuNagoyaAichi466-8555Japan Faculty of Informatics Zagazig UniversityZagazigEgypt

Service composition is an important and effective technique that enables atomic services to be combined together to forma more powerful service,i.e.,a composite *** the pervasiveness of the Internet and the proliferation of interconnected computing devices,it is essential that service composition embraces an adaptive service provisioning *** learning has emerged as a powerful tool to compose and adapt Web services in open and dynamic ***,the most common applications of reinforcement learning algorithms are relatively inefficient in their use of the interaction experience data,whichmay affect the stability of the learning process when deployed to cloud *** particular,they make just one learning update for each interaction *** paper introduces a novel approach that aims to achieve greater data efficiency by saving the experience data and using it in aggregate to make updates to the learned *** proposed approach devises an offline learning scheme for cloud service composition where the online learning task is transformed into a series of supervised learning tasks.A set of algorithms is proposed under this scheme in order to facilitate and empower efficient service composition in the cloud under various policies and different *** results of our experiments show the effectiveness of the proposed approach for composing and adapting cloud services,especially under dynamic environment settings,compared to their online learning counterparts.

关键词： Service composition reinforcement learning cloud services offline learning

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