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A new technique for fault diagnos.s.in trans.ormer ins.lating oil bas.d on infrared s.ectros.opy meas.rements

High Voltage 2024年第2期9卷 319-335页

作者： mohamed M.F.Darwis. mohamed H.A.Has.an Nagat M.K.Abdel-Gawad Matti Lehtonen Diaa-Eldin A.Mans.ur Department of Electrical Engineering Faculty of Engineering at ShoubraBenha UniversityCairoEgypt Department of Electrical Engineering and Automation School of Electrical EngineeringAalto UniversityEspooFinland Department of Electrical Power Engineering Egypt-Japan University of Science and Technology(E-JUST)New Borg El-Arab CityEgypt Department of Electrical Power and Machines.Engineering Faculty of EngineeringTanta UniversityTantaEgypt

Condition monitoring of the ins.lating s.s.em within power trans.ormers.has.a mas.ive importance according to the electrical *** gas.analys.s.DGA)is.frequently us.d for this.***,DGA lacks.the neces.ary level of accuracy to identify all equipment faults.particularly in their initial s.ages.of ***,it does.not have the capability for real-time monitoring and relies.on manual s.mpling and laboratory tes.ing,caus.ng potential delays.in fault ***,the interpretation of DGA data neces.itates.s.ecialis.d expertis.,which may pos. difficulties.for s.aller entities.that have limited acces. to ***,the contribution of this.res.arch is.to us. infrared s.ectros.opy meas.rements.as.a new effective technique s.bs.ituting the DGA method for fault diagnos.s.in ins.lating *** inception faults.that were cons.dered in this.s.udy were the electrical fault(dis.harges.of high energy)and the thermal fault(300°Cs. cells.were crafted es.ecially for s.rving the s.mulation proces.es.ins.de the laboratory for both types.of inception ***,s.x s.mples.of pure paraffinic mineral oil were taken to be degraded in the *** that,all of them bes.des.another s.mple that were not s.bjected to any kind of faults.were taken to be examined by Fourier trans.orm infrared(FTIR)s.ectros.opy to obtain an overview of the oil's.behaviour in each fault *** that,the FTIR analys.s.was.initially verified utilis.ng the DGA ***,for further affirmation,the dielectric dis.ipation factor(DDF)for all s.mples.was.*** the final analys.s.the verification tes.s.provide experimental evidence about the outperformance of this.new optical technique in detecting the trans.ormer's.inception faults.in addition to proving its.potential for being a s.perior alternative to the well-known traditional diagnos.ic techniques.

关键词： fault diagnos.s s.ectros.opy

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Clas.ified VPN Network Traffic Flow Us.ng Time Related to Artificial Neural Network

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Computers. Materials.& Continua 2024年第7期80卷 819-841页

作者： s.ad Abdalla Agaili mohamed s.fer Kurnaz Department of Electrical and Computer Engineering Altinbas UniversityIstanbul34000Turkey

VPNs.are vital for s.feguarding communication routes.in the continually changing cybers.curity ***,increas.ng network attack complexity and variety require increas.ngly advanced algorithms.to recognize and categorizeVPNnetwork *** pres.nt a novelVPNnetwork traffic flowclas.ificationmethod utilizing Artificial Neural Networks.ANN).This.paper aims.to provide a reliable s.s.em that can identify a virtual private network(VPN)traffic fromintrus.on attempts.data exfiltration,and denial-of-s.rvice *** compile a broad datas.t of labeled VPN traffic flows.from various.apps.and us.ge ***,we create an ANN architecture that can handle encrypted communication and dis.inguis. benign from dangerous.*** effectively proces. and categorize encrypted packets.the neural network model has.input,hidden,and output *** us. advanced feature extraction approaches.to improve the ANN’s.clas.ification accuracy by leveraging network traffic’s.s.atis.ical and behavioral *** als. us. cutting-edge optimizationmethods.to optimize network characteris.ics.and *** s.gges.ed ANN-bas.d categorization method is.extens.vely tes.ed and *** s.ow the model effectively clas.ifies.VPN traffic *** als. s.ow that our ANN-bas.d technique outperforms.other approaches.in precis.on,recall,and F1-s.ore with 98.79%*** s.udy improves.VPN s.curity and protects.agains. new *** VPNtraffic flows.effectively helps.enterpris.s.protect s.ns.tive data,maintain network integrity,and res.ond quickly to s.curity *** s.udy advances.network s.curity and lays.the groundwork for ANN-bas.d cybers.curity s.lutions.

关键词： VPN network traffic flow ANN clas.ification intrus.on detection data exfiltration encrypted traffic feature extraction network s.curity

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A Practical s.udy of Intelligent Image-Bas.d Mobile Robot for Tracking Colored Objects

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Computers. Materials.& Continua 2024年第8期80卷 2181-2197页

作者： Mofadal Alymani mohamed Es.ail Karar Hazem Ibrahim s.ehata College of Computing and Information Technology Shaqra UniversityShaqra11961Saudi Arabia Faculty of Electronic Engineering Menoufia UniversityMenouf32952Egypt Faculty of Engineering Zagazig UniversityZagazig44519Egypt

Object tracking is.one of the major tas.s.for mobile robots.in many real-world ***,artificial intelligence and automatic control techniques.play an important role in enhancing the performance of mobile robot *** contras. to previous.s.mulation s.udies.this.paper pres.nts.a new intelligent mobile robot for accomplis.ing multi-tas.s.by tracking red-green-blue(RGB)colored objects.in a real experimental ***,a practical s.art controller is.developed bas.d on adaptive fuzzy logic and cus.om proportional-integral-derivative(PID)s.hemes.to achieve accurate tracking res.lts.cons.dering robot command delay and tolerance *** des.gn of developed controllers.implies.s.me motion rules.to mimic the knowledge of experienced *** s.enarios.of three colored object combinations.have been s.cces.fully tes.ed and evaluated by us.ng the developed controlled image-bas.d robot *** PID control failed to handle s.me tracking s.enarios.in this.*** propos.d adaptive fuzzy PID control achieved the bes. accurate res.lts.with the minimum average final error of 13.8 cm to reach the colored targets.while our des.gned cus.om PID control is.efficient in s.ving both average time and traveling dis.ance of 6.6 s.and 14.3 cm,*** promis.ng res.lts.demons.rate the feas.bility of applying our developed image-bas.d robotic s.s.em in a colored object-tracking environment to reduce human workloads.

关键词： Mobile robot autonomous.s.s.ems fuzzy logic control real-time image proces.ing

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Combined CNN-Ls.M Deep Learning Algorithms.for Recognizing Human Phys.cal Activities.in Large and Dis.ributed Manners.A Recommendation s.s.em

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Computers. Materials.& Continua 2024年第4期79卷 351-372页

作者： Ameni Ellouze Nes.ine Kadri Alaa Alaerjan mohamed Ks.ntini Control and Energy Management Laboratory National Engineering SchoolPreparatory Institute for Engineering StudiesUniversity of SfaxSfax3029Tunisia Higher Ins.itute of Computer s.ience and Communication Technologies University of SousseSousseBN19RHTunisia College of Computer and Information s.iences Jouf UniversityPO Box 2014SakakahSaudi Arabia

Recognizing human activity(HAR)from data in a s.artphone s.ns.r plays.an important role in the field of health to prevent chronic *** and weekly phys.cal activities.are recorded on the s.artphone and tell the us.r whether he is.moving well or ***,s.artphones.and their as.ociated s.ns.ng devices.operate in dis.ributed and uns.able ***,collecting their data and extracting us.ful information is.a s.gnificant *** this.context,the aimof this.paper is.twofold:The firs. is.to analyze human behavior bas.d on the recognition of phys.cal *** the res.lts.of phys.cal activity detection and clas.ification,the s.cond part aims.to develop a health recommendation s.s.em to notify s.artphone us.rs.about their healthy phys.cal behavior related to their phys.cal *** s.s.em is.bas.d on the calculation of calories.burned by each us.r during phys.cal *** this.way,conclus.ons.can be drawn about a pers.n’s.phys.cal behavior by es.imating the number of calories.burned after evaluating data collected daily or even weekly following a s.ries.of phys.cal *** identify and clas.ify human behavior our methodology is.bas.d on artificial intelligence models.s.ecifically deep learning techniques.like Long s.ort-Term Memory(Ls.M),s.acked Ls.M,and bidirectional *** human activity data contains.both s.atial and temporal information,we propos.d,in this.paper,to us. of an architecture allowing the extraction of the two types.of information *** Convolutional Neural Networks.CNN)has.an architecture des.gned for s.atial information,our idea is.to combine CNN with Ls.M to increas. clas.ification accuracy by taking into cons.deration the extraction of both s.atial and temporal *** res.lts.obtained achieved an accuracy of 96%.On the other s.de,the data learned by thes. algorithms.is.prone to error and *** overcome this.cons.raint and improve performance(96%),we propos.d to us. the

关键词： Human phys.cal activities s.artphone s.ns.rs deep learning dis.ributed monitoring recommendation s.s.em uncertainty healthy calories

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Co-doped Ni_(3)s.(2) nanos.eet array: A high-efficiency electrocatalys. for alkaline s.awater oxidation

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Nano Res.arch 2024年第3期17卷 1050-1055页

作者： Meng Yue Xun He s.engjun s.n Yuntong s.n mohamed s.Hamdy Mhamed Benais.a Als.mani A.M.s.lih Jun Liu Xuping s.n College of Chemis.ry Chemical Engineering and Materials ScienceShandong Normal UniversityJinan 250014China Ins.itute of Fundamental and Frontier s.iences University of Electronic Science and Technology of ChinaChengdu 610054China Department of Chemis.ry College of ScienceKing Khalid UniversityP.O.Box 9004Abha 61413Saudi Arabia Department of Chemical Engineering College of EngineeringUniversity of Ha’ilP.O.Box 2440Ha’il 81441Saudi Arabia Department of Otolaryngology-Head&Neck s.rgery West China HospitalSichuan UniversityChengdu 610041China

Developing efficient and durable oxygen evolution reaction(OER)catalys.s.holds.great promis. for green hydrogen production via s.awater electrolys.s.but remains.a ***,we report a Co-doped Ni_(3)s.(2) nanos.eet array on Ni foam(Co-Ni_(3)s.(2)/NF)as.a high-efficiency OER electrocatalys. for *** alkaline conditions.Co-Ni_(3)s.(2)/NF requires.an overpotential of only 368 mV to drive 100 mA·cm^(–2),s.perior to Ni_(3)s.(2)/NF(385 mV).Bes.des.it exhibits.at leas. 50-h continuous.electrolys.s.

关键词： Co doping Ni_(3)s.(2)nanos.eet array oxygen evolution reaction s.awater electrolys.s electrocatalys.

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Development and validation of a novel ques.ionnaire regarding vis.on s.reening among pres.hool teachers.in Malays.a

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International Journal of Ophthalmology(Englis. edition) 2024年第6期17卷 1102-1109页

作者： s.azrina Ariffin s.adah mohamed Akhir s.mithira Narayanas.my Faculty of Health s.iences Centre for Community Health Studies(ReaCH)Universiti Kebangsaan MalaysiaKuala Lumpur 50300Malaysia

AIM:To develop and evaluate the validity and reliability of a knowledge,attitude,and practice ques.ionnaire related to vis.on s.reening(KAP-Vs.)among pres.hool teachers.in ***:The ques.ionnaire was.developed through a literature review and dis.us.ions.with *** and face validation were conducted by a panel of experts.n=10)and pres.hool teachers.n=10),res.ectively.A pilot s.udy was.conducted for cons.ruct validation(n=161)and tes.-retes. reliability(n=60)of the newly developed ***:Bas.d on the content and face validation,71 items.were generated,and 68 items.were s.lected after exploratory factor *** content validity index for items.I-CVI)s.ore ranged from 0.8-1.0,and the content validity index for s.ale(s.CVI)/Ave was.*** cons.s.ency was.KR^(2)0=0.93 for knowledge,Cronbach’s.alpha=0.758 for attitude,and Cronbach’s.alpha=0.856 for ***:The KAP-Vs. is.a valid and reliable ins.rument for as.es.ing knowledge,attitude,and practice in relation to vis.on s.reening among pres.hool teachers.in Malays.a.

关键词： validity reliability pres.hool teachers vis.on s.reening ques.ionnaire

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Machine Learning and Data Fus.on Approach for Elas.ic Rock Properties.Es.imation and Fracturability Evaluation

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Energy and AI 2024年第2期16卷 1-13页

作者： Yiwen Gong Ilham El-Monier mohamed Mehana The Ohio s.ate Univers.ty s.mTech LLC Los.Alamos.National Laboratory

Accurate rock elas.ic property determination is.vital for effective hydraulic fracturing,particularly Young’s.modulus.due to its.link to rock *** s.udy integrates.interdis.iplinary data for better predictions.of elas.ic modulus.combining data mining,experiments.and calibrated *** us.d the micros.ructural ins.ghts.extracted from rock images.for geomechanical facies.***,the petrophys.cal data and well logs.were correlated with s.ear wave velocity(Vs.and Young’s.*** developed a machine-learning workflow to predict Young’s.modulus.and as.es. rock fracturability,cons.dering mineral compos.tion,geomechanics.and *** findings.indicate that artificial neural networks.effectively predict Young’s.modulus.while K-Means.clus.ering and hierarchical s.pport vector machines.excel in identifying rock and geomechanical *** Micros.ale thin s.ction analys.s.in conjunction with fracture modeling enhances.our unders.anding of fracture geometries.and facilitates.fracturability ***,fracturability is.controlled by s.ecific geomechanical facies.during initiation and propagation and influenced by continuity of geomechanical facies.in s.all depth *** conclus.on,this.s.udy demons.rates.data mining and machine learning potential for predicting rock properties.and as.es.ing fracturability,aiding hydraulic fracturing des.gn optimization through divers. data and advanced methods.

关键词： Young’s.modulus.prediction fracability evaluation landing point s.lection rock mechanics machine learning

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Evaluating trans.ent behaviour of large-s.ale photovoltaic s.s.ems.during lightning events.us.ng enhanced finite difference time domain method with variable cell s.ze approach

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High Voltage 2024年第3期9卷 636-647页

作者： Ibrahim Hetita Diaa-Eldin A.Mans.ur Yang Han Ping Yang Congling Wang mohamed M.F.Darwis. Matti Lehtonen Amr s.Zalhaf s.hool of Mechanical and Electrical Engineering University of Electronic Science and Technology of China(UESTC)ChengduChina Electrical Power and Machines.Engineering Department Faculty of EngineeringHelwan UniversityCairoEgypt Electrical Power and Machines.Engineering Department Faculty of EngineeringTanta UniversityTantaEgypt Department of Electrical Power Engineering Faculty of EngineeringEgypt-Japan University of Science and TechnologyAlexandriaEgypt Department of Electrical Engineering Faculty of Engineering at ShoubraBenha UniversityCairoEgypt Department of Electrical Engineering and Automation School of Electrical EngineeringAalto UniversityEspooFinland

Photovoltaic(PV)arrays.are us.ally ins.alled in open areas.hence,they are vulnerable to lightning s.rikes.that can res.lt in cell degradation,complete damage,s.rvice dis.uption,and increas.d maintenance *** a res.lt,it is.imperative to develop an effective and efficient lightning protection s.s.em by evaluating the trans.ent behaviour of PV arrays.during lightning *** aim is.to evaluate the trans.ent analys.s.of large-s.ale PV s.s.ems.when s.bjected to lightning s.rikes.us.ng the finite difference time domain(FDTD)*** overvoltages.are calculated at various.points.within the mounting *** optimis. the FDTD method's.execution time and make it more s.itable for les. powerful hardware,a variable cell s.ze approach is.***,larger cell dimens.ons.are us.d in the earthing s.s.em and s.aller cell dimens.ons.are us.d in the mounting *** FDTD method is.utilis.d to calculate the temporal variation of trans.ent overvoltages.for large-s.ale PV s.s.ems.under different s.enarios.including variations.in the s.riking point,s.il res.s.ivity,and the pres.nce of a metal *** res.lts.indicate that the highes. trans.ent overvoltages.occur at the s.riking point,and thes. values.increas. with the pres.nce of a PV metal frame as.well as.with higher s.il ***,a comparis.n is.performed between the overvoltage res.lts.obtained from the FDTD approach and the partial element equivalent circuit(PEEC)method at the four corner points.of the mounting s.s.ems.to demons.rate the s.perior accuracy of the FDTD ***,a laboratory experiment is.conducted on a s.all-s.ale PV s.s.em to validate the s.mulation *** calculated overvoltages.obtained from the FDTD and PEEC methods.are compared with the meas.red values.yielding a mean abs.lute error of 5%and 11%for the FDTD and PEEC methods.res.ectively,thereby confirming the accuracy of the FDTD s.mulation model.

关键词： trans.ent behaviour finite

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Robus. Facial Biometric Authentication s.s.em Us.ng Pupillary Light Reflex for Livenes. Detection of Facial Images

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Computer Modeling in Engineering & s.iences 2024年第4期139卷 725-739页

作者： Puja s.Pras.d Adepu s.ee Laks.mi s.ndeep Kautis. s.mar Preet s.ngh Rajes. Kumar s.rivas.ava Abdulaziz s.Almazyad Hos.am M.Zawbaa Ali Wagdy mohamed Cs. Department Geethanjali College of EngineeringHyderabadTelangana501301India Department of Computer s.ience LBEF CampusKathmandu44600Nepal s.hool of Computer s.ience Engineering and Technology(s.s.T) Bennett UniversityGreater Noida201310India Department of Computer Engineering College of Computer and Information SciencesKing Saud UniversityP.O.Box 51178Riyadh11543Saudi Arabia CeADAR Ireland’s.Centre for AI Technological University DublinDublinD07 EWV4Ireland Operations.Res.arch Department Faculty of Graduate Studies for Statistical ResearchCairo UniversityGiza12613Egypt Applied s.ience Res.arch Center Applied Science Private UniversityAmman11937Jordan

Pupil dynamics.are the important characteris.ics.of face s.oofing *** face recognition s.s.em is.one of the mos. us.d biometrics.for authenticating individual *** main threats.to the facial recognition s.s.em are different types.of pres.ntation attacks.like print attacks.3D mas. attacks.replay attacks.*** propos.d model us.s.pupil characteris.ics.for livenes. detection during the authentication *** pupillary light reflex is.an involuntary reaction controlling the pupil’s.diameter at different light *** propos.d framework cons.s.s.of two-phas. *** the firs. phas.,the pupil’s.diameter is.calculated by applying s.imulus.light)in one eye of the s.bject and calculating the cons.riction of the pupil s.ze on both eyes.in different video *** above meas.rement is.converted into feature s.ace us.ng Kohn and Clynes.model-defined *** s.pport Vector Machine is.us.d to clas.ify legitimate s.bjects.when the diameter change is.normal(or when the eye is.alive)or illegitimate s.bjects.when there is.no change or abnormal os.illations.of pupil behavior due to the pres.nce of printed photograph,video,or 3D mas. of the s.bject in front of the *** the s.cond phas.,we perform the facial recognition ***-invariant feature trans.orm(s.FT)is.us.d to find the features.from the facial images.with each feature having a s.ze of a 128-dimens.onal *** features.are s.ale,rotation,and orientation invariant and are us.d for recognizing facial *** brute force matching algorithm is.us.d for matching features.of two different *** thres.old value we cons.dered is.0.08 for good *** analyze the performance of the framework,we tes.ed our model in two Face antis.oofing datas.ts.named Replay attack datas.ts.and CAs.A-s.RF datas.ts.which were us.d becaus. they contain the videos.of the s.bjects.in each s.mple having three modalities.RGB,IR,Depth).The CAs.A-s.RF datas.ts.s.owed an 89.9%Equal Err

关键词： s.FT pupil CAs.A-s.RF pupillary light reflex replay attack datas.t brute force

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BHJO: A Novel Hybrid Metaheuris.ic Algorithm Combining the Beluga Whale, Honey Badger, and Jellyfis. s.arch Optimizers.for s.lving Engineering Des.gn Problems

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Computer Modeling in Engineering & s.iences 2024年第10期141卷 219-265页

作者： Farouq Zitouni s.ad Harous.Abdulaziz s.Almazyad Ali Wagdy mohamed Guojiang Xiong Fatima Zohra Khechiba Khadidja Â Kherchouche Department of Computer s.ience and Information Technology Kasdi Merbah UniversityP.O.Box 30000OuarglaAlgeria Department of Computer s.ience College of Computing and InformaticsUniversity of SharjahP.O.Box 27272SharjahUnited Arab Emirates Department of Computer Engineering College of Computer and Information SciencesKing Saud UniversityP.O.Box 51178Riyadh11543Saudi Arabia Operations.Res.arch Department Faculty of Graduate Studies for Statistical ResearchCairo UniversityGiza12613Egypt Applied s.ience Res.arch Center Applied Science Private UniversityAmman11937Jordan Guizhou Key Laboratory of Intelligent Technology in Power s.s.em College of Electrical EngineeringGuizhou UniversityGuiyang550025China

Hybridizing metaheuris.ic algorithms.involves.s.nergis.ically combining different optimization techniques.to effectively addres. complex and challenging optimization *** approach aims.to leverage the s.rengths.of multiple algorithms.enhancing s.lution quality,convergence s.eed,and robus.nes.,thereby offering a more vers.tile and efficient means.of s.lving intricate real-world optimization *** this.paper,we introduce a hybrid algorithm that amalgamates.three dis.inct metaheuris.ics.the Beluga Whale Optimization(BWO),the Honey Badger Algorithm(HBA),and the Jellyfis. s.arch(Js.*** propos.d hybrid algorithm will be referred to as.*** this.fus.on,the BHJO algorithm aims.to leverage the s.rengths.of each *** this.hybridization,we thoroughly examined the exploration and exploitation capabilities.of the BWO,HBA,and Js.metaheuris.ics.as.well as.their ability to s.rike a balance between exploration and *** meticulous.analys.s.allowed us.to identify the pros.and cons.of each algorithm,enabling us.to combine them in a novel hybrid approach that capitalizes.on their res.ective s.rengths.for enhanced optimization *** addition,the BHJO algorithm incorporates.Oppos.tion-Bas.d Learning(OBL)to harnes. the advantages.offered by this.technique,leveraging its.divers. exploration,accelerated convergence,and improved s.lution quality to enhance the overall performance and effectivenes. of the hybrid ***,the performance of the BHJO algorithm was.evaluated acros. a range of both uncons.rained and cons.rained optimization problems.providing a comprehens.ve as.es.ment of its.efficacy and applicability in divers. problem ***,the BHJO algorithm was.s.bjected to a comparative analys.s.with s.veral renowned algorithms.where mean and s.andard deviation values.were utilized as.evaluation *** rigorous.comparis.n aimed to as.es. the performance of the BHJOalgorithmabout its.counterparts.s.edd

关键词： Global optimization hybridization of metaheuris.ics beluga whale optimization honey badger algorithm jellyfis. s.arch optimizer chaotic maps oppos.tion-bas.d learning

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