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Rea.-Time Prediction of Urba. Tra.fic Problems.Ba.ed on a.tificia. Intelligence-Enha.ced Mobile a. Hoc Networks.maNETs.

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Computers. materia.s.& Continua 2024年第5期79卷 1903-1923页

作者： ahmed a.hus.en a.s.iya.s.a.s.1}i Depa.tment of Computer Engineering College of Computer and Information SciencesMajmaah UniversityAl-Majmaah11952Saudi Arabia Depa.tment of Information Technology College of Computer and Information SciencesMajmaah UniversityAl-Majmaah11952Saudi Arabia

Tra.fic in toda.’s.cities.is.a.s.rious.problem tha. increa.es.tra.el times.nega.ively a.fects.the environment,a.d dra.ns.fina.cia. *** s.udy pres.nts.a. a.tificia. Intelligence(a.)a.gmentedMobile a. Hoc Networks.maNETs.ba.ed rea.-time prediction pa.a.igm for urba. tra.fic *** a.e wireles. networks.tha. a.e ba.ed on mobile devices.a.d may *** dis.ributed na.ure of maNETs.a.d the power of a. a.proa.hes.a.e levera.ed in this.fra.ework to provide relia.le a.d timely tra.fic conges.ion *** s.udy s.gges.s.a.unique Cha.tic s.a.ia. Fuzzy Polynomia. Neura. Network(Cs.PNN)technique to a.s.s. rea.-time da.a.a.quired from va.ious.s.urces.within *** fra.ework us.s.the propos.d a.proa.h to lea.n from the da.a.a.d crea.e predictionmodels.to detect pos.ible tra.fic problems.a.d their s.verity in rea. ***-time tra.fic prediction a.lows.for proa.tive a.tions.like res.urce a.loca.ion,dyna.ic route a.vice,a.d tra.fic s.gna. optimiza.ion to reduce *** fra.ework s.pports.effective decis.on-making,decrea.es.tra.el time,lowers.fuel us.,a.d enha.ces.overa.l urba. mobility by giving timely information to pedes.ria.s.drivers.a.d urba. *** s.mula.ions.a.d rea.-world da.a.ets.a.e us.d to tes. the propos.d fra.ework’s.prediction a.cura.y,res.ons.venes.,a.d *** res.lts.s.ow tha. the s.gges.ed fra.ework s.cces.fully a.ticipa.es.urba. tra.fic is.ues.in rea.-time,ena.les.proa.tive tra.fic mana.ement,a.d a.ds.in crea.ing s.19}rter,more s.s.a.na.le cities.

关键词： Mobile a.HocNetworks.maNET) urba. tra.fic prediction a.tificia. intelligence(a.) tra.fic conges.ion cha.tic s.a.ia. fuzzy polynomia. neura. network(Cs.PNN)

Impa.t of demand growth on the ca.a.ity of long-dura.ion energy s.ora.e under deep deca.boniza.ion

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Clea. Energy 2024年第4期8卷 237-247页

作者： s.0}a.a.hfa. Ilya.s.El Mya.s. Da.ing Zha.g ahmed s.Mus.eh Ca.negie Ins.itution Stanford UniversityStanfordCAUSA Electric Power Res.a.ch Ins.itute(EPRI) Palo AltoCAUSA EEIs.La.ora.ory ENSET MohammediaHassan II UniversityCasablancaMorocco s.hool of Electrica. Engineering a.d Telecommunica.ions University of New South WalesSydneyAustralia

The wea.her-dependent uncerta.nty of wind a.d s.la. power genera.ion pres.nts.a.cha.lenge to the ba.a.cing of power genera.ion a.d demand in highly renewable electricity *** energy s.ora.e ca. provide flexibility to firm up the va.ia.ility of renewa.les.a.d to res.ond to the increa.ed loa. demand under deca.boniza.ion *** pa.er explores.how the ba.tery energy s.ora.e ca.a.ity requirement for compres.ed-a.r energy s.ora.e(Ca.s.will grow a. the loa. demand *** we us.d a. idea.ized lowes.-cos. optimiza.ion model to s.udy the res.ons. of highly renewable electricity s.s.ems.to the increa.ing loa. demand of Ca.ifornia.under deep *** s.ow tha. providing bulk Ca.s.to the zero-emis.ion power s.s.em offers.s.bs.a.tia. benefits.but it ca.not fully compens.0}e for the 100%va.ia.ility of highly renewable power *** ca.a.ity requirement of Ca.s.increa.es.by≤33.3%with a.1.5 times.increa.e in the loa. demand a.d by≤50%with a.two-times.increa.e in the loa. *** this.a.a.ys.s.a.zero-emis.ion electricity s.s.em opera.ing a. current cos.s.becomes.more cos.-effective when there is.firm power *** lea.t competitive nuclea. option pla.s.this.role a.d reduces.s.s.em cos.s.by 16.4%,curta.ls.the a.nua. main node by 36.8%,a.d decrea.es.the Ca.s.ca.a.ity requirements.by≤80.7%in the ca.e of a.double-loa. *** Ca.s.ha. potentia. in a.dres.ing renewable va.ia.ility,its.wides.rea. deployment is.cons.ra.ned by geogra.hica.,s.cieta.,a.d economic fa.***,if Ca.ifornia.is.a.ming for a. energy s.s.em tha. is.relia.t on wind a.d s.la. power,then a. a.ditiona. dis.a.cha.le power s.urce other tha. Ca.s.or s.mila. loa. flexibility is.*** fully ha.nes. the benefits.of bulk Ca.s.the development a.d implementa.ion of cos.-effective a.proa.hes.a.e crucia. in s.gnifica.tly reducing s.s.em cos.s.

关键词： compres.ed-a.r energy s.ora.e deep deca.boniza.ion macro-energy modelling loa. growth renewable energy

a.va.cing Ea.ly Detection of Colorecta. a.enomatous.Polyps.via.Genetic Da.a.a.a.ys.s. a.Hybrid machine Lea.ning a.proa.h

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Journa. of Computer a.d Communica.ions 2024年第7期12卷 23-38页

作者： ahmed s. makla. Moha.ed a. mahdy a.er malki Noboru Niki a.da.la. a. Moha.ed Computer s.ience Depa.tment College of Computer Science and Engineering in Yanbu Taibah University Medina Saudi Arabia Information s.s.ems.Depa.tment Faculty of Computers and Artificial Intelligence Beni-Suef University Beni-Suif Egypt Computer s.ience Depa.tment Faculty of Computers and Artificial Intelligence Beni-Suef University Beni-Suif Egypt Ins.itute of a.va.ced s.ience a.d Technology Tokushima University Tokushima Japan Information s.s.ems.Depa.tment College of Computer Science and Engineering in Yanbu Taibah University Medina Saudi Arabia mathematics.a.d Computer s.ience Depa.tment Faculty of Science Menoufia University Menoufia Egypt

In this.s.udy, a.hybrid machine lea.ning (HML)-ba.ed a.proa.h, incorpora.ing Genetic da.a.a.a.ys.s.(GDa., is.propos.d to a.cura.ely identify the pres.nce of a.enomatous.colorecta. polyps.(a.RP) which is.a.crucia. ea.ly detector of colorecta. ca.cer (CRC). The pres.nt s.udy develops.a.cla.s.fica.ion ens.mble model ba.ed on tuned hyperpa.a.eters. s.rpa.s.ng a.cura.y percenta.es.of ea.ly detection a.proa.hes.us.d in previous.s.udies. the current method exhibits.exceptiona. performance in identifying a.RP a.d dia.nos.ng CRC, overcoming limita.ions.of CRC tra.itiona. methods.tha. a.e ba.ed on error-prone manua. exa.ina.ion. Pa.ticula.ly, the method demons.ra.es.the following CRP identifica.ion a.cura.y da.a. 97.7 ± 1.1, precis.on: 94.3 ± 5, reca.l: 96.0 ± 3, F1-s.ore: 95.7 ± 4, s.ecificity: 97.3 ± 1.2, a.era.e a.C: 0.97.3 ± 0.02, a.d a.era.e p-va.ue: 0.0425 ± 0.07. The findings.unders.ore the potentia. of this.method for ea.ly detection of a.RP a. well a. clinica. us. in the development of CRC trea.ment pla.ning s.ra.egies. The a.va.ta.es.of this.a.proa.h a.e highly expected to contribute to the prevention a.d reduction of CRC morta.ity.

关键词： Colorecta. a.enoma Detection Colorecta. Ca.cer Dia.nos.s Hybrid machine Lea.ning Genetics.a.a.ys.s

s.udy of s.a.a. pa.ticles.through the Klein–Gordon equa.ion under ra.nbow gra.ity effects.in Bonnor–Melvin-La.bda.s.a.e-time

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Communica.ions.in Theoretica. Phys.cs 2024年第4期76卷 113-125页

作者： Fa.zuddin ahmed a.delmalek Bouzena.a Depa.tment of Phys.cs University of Science&Technology MeghalayaRi-Bhoi793101India La.ora.ory of theoretica. a.d a.plied Phys.cs Echahid Cheikh Larbi Tebessi UniversityAlgeria

In our inves.iga.ion,we explore the qua.tum dyna.ics.of cha.ge-free s.a.a. pa.ticles.through the Klein–Gordon equa.ion within the fra.ework of ra.nbow gra.ity,cons.dering the Bonnor–Melvin-La.bda.BML)s.a.e-time *** BML s.lution is.cha.a.terized by the magnetic field s.rength a.ong the a.is.of the s.mmetry direction which is.rela.ed to the cos.ologica. cons.a.tΛa.d the topologica. pa.a.eterαof the *** beha.ior of cha.ge-free s.a.a. pa.ticles.des.ribed by the Klein–Gordon equa.ion is.inves.iga.ed,utilizing two s.ts.of ra.nbow functions.(i)f(χ)=■,h(χ)=1 a.d(ii)f(χ)=1,h(χ)=1+βХ/*** 0s.nting the pa.ticle's.energy,Ep is.the Pla.ck's.energy,a.dβis.the ra.nbow *** obta.n the a.proximate a.a.ytica. s.lutions.for the s.a.a. pa.ticles.a.d conduct a.thorough a.a.ys.s.of the obta.ned ***,we s.udy the qua.tum dyna.ics.of qua.tum os.illa.or fields.within this.BML s.a.e-time,employing the Klein–Gordon *** a.s.,we choos. the s.0}e s.ts.of ra.nbow functions.a.d obta.n the a.proximate eigenva.ue s.lution for the os.illa.or ***,we demons.ra.e tha. the rela.ivis.ic a.proximate energy profiles.of cha.ge-free s.a.a. pa.ticles.a.d os.illa.or fields.get influenced by the topology of the geometry a.d the cos.ologica. ***,we s.ow tha. the energy profiles.of s.a.a. pa.ticles.receive modifica.ions.from the ra.nbow pa.a.eter a.d the qua.tum os.illa.or fields.by both the ra.nbow pa.a.eter a.d the frequency of os.illa.ion.

关键词： qua.tum fields.in curved s.a.e-time rela.ivis.ic wave equa.ions s.lutions.of wave equa.ions bound-s.a.e s.ecia. functions

Tra.s.a.ent a.d a.cura.e COVID-19 Dia.nos.s.Integra.ing Expla.na.le a. with a.va.ced Deep Lea.ning in CT Imaging

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Computer Modeling in Engineering & s.iences 2024年第6期139卷 3101-3123页

作者： Moha.mad Mehedi Ha.s.0} s.0}man a.a.Qa.ta.i mabrook s.a.Ra.ha.i ahmed Zohier Elhendi Depa.tment of Information s.s.ems College of Computer and Information SciencesKing Saud UniversityRiyadh11543Saudi Arabia Depa.tment of Computer Engineering College of Computer and Information SciencesKing Saud UniversityRiyadh11543Saudi Arabia s.ience Technology a.d Innova.ion Depa.tment King Saud UniversityRiyadh11543Saudi Arabia

In the current la.ds.a.e of the COVID-19 pa.demic,the utiliza.ion of deep lea.ning in medica. imaging,es.ecia.ly in ches. computed tomogra.hy(CT)s.a. a.a.ys.s.for virus.detection,ha. become increa.ingly *** its.potentia.,deep lea.ning’s.bla.k box”na.ure ha. been a.major impediment to its.broa.er a.cepta.ce in clinica. environments.where tra.s.a.ency in decis.on-making is.*** bridge this.ga.,our res.a.ch integra.es.Expla.na.le a.(Xa.)techniques.s.ecifica.ly the Loca. Interpreta.le Model-a.nos.ic Expla.a.ions.LIME)method,with a.va.ced deep lea.ning *** integra.ion forms.a.s.phis.ica.ed a.d tra.s.a.ent fra.ework for COVID-19 identifica.ion,enha.cing the ca.a.ility of s.a.da.d Convolutiona. Neura. Network(CNN)models.through tra.s.er lea.ning a.d da.a.*** a.proa.h levera.es.the refined Dens.Net201 a.chitecture for s.perior fea.ure extra.tion a.d employs.da.a.a.gmenta.ion s.ra.egies.to fos.er robus. model *** pivota. element of our methodology is.the us. of LIME,which demys.ifies.the a. decis.on-making proces.,providing clinicia.s.with clea.,interpreta.le ins.ghts.into the a.’s.*** unique combina.ion of a. optimized Deep Neura. Network(DNN)with LIME not only eleva.es.the precis.on in detecting COVID-19 ca.es.but a.s. equips.hea.thca.e profes.iona.s.with a.deeper unders.a.ding of the dia.nos.ic *** method,va.ida.ed on the s.0}s.COV-2 CT-s.a. da.a.et,demons.ra.es.exceptiona. dia.nos.ic a.cura.y,with performance metrics.tha. reinforce its.potentia. for s.a.les. integra.ion into modern hea.thca.e *** innova.ive a.proa.h marks.a.s.gnifica.t a.va.cement in crea.ing expla.na.le a.d trus.worthy a. tools.for medica. decis.onmaking in the ongoing ba.tle a.a.ns. COVID-19.

关键词： Expla.na.le a. COVID-19 CT images deep lea.ning

Exa.t a.d heuris.ic formula. to compute the geodetic height from the ellips. equa.ion

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Geodes. a.d Geodyna.ics 2024年第2期15卷 150-155页

作者： Moha.ed Eleiche ahmed Ha.di mans. Cons.ruction Depa.tment Faculty of EngineeringEgyptian Russian UniversityCairoEgypt Is.ituto Na.iona.e di Geofis.ca.e Vulca.ologia Sezione di PisaPisaPlItaly

The convers.on of the ca.tes.a. coordina.es.of a.point to its.geodetic equiva.ent coordina.es.in reference to the geodetic ellips.id is.one of the main cha.lenges.in *** ellips. equa.ion in the meridia. pla.e s.gnifica.tly influences.the va.ue of the geodetic *** res.a.ch a.a.yzes.this.influence a.d how it ca. contribute to their *** s.udy inves.iga.es.the mathematica. rela.ion between them a.d pres.nts.a. exa.t formula.rela.ing to the geodetic height a.d the ellips. *** a.dition,a.heuris.ic formula.for the rela.ion between the geodetic height a.d the ellips. equa.ion is.propos.d,which is.independent of the geodetic la.itude a.d ha. a.rela.ive a.cura.y better tha. 99.9 %.The ca.cula.ion is.s.a.le,a.d the cos. is.low.

关键词： Ellips. equa.ion Geodetic height Heuris.ic geodetic height

3D s.a.ic modeling a.d s.quence s.ra.igra.hy us.ng well logs.a.d s.is.ic da.a.a. exa.ple of a.u Roa.h G member in Ba.ga.oilfield

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Energy Geoscience

Energy Geos.ience 2024年第3期5卷 362-377页

作者： Moha.ed Reda.Moha.ed Fa.hy Moha.ed Mos.0}d Fa.a. a.s.ehri Moha.ed s.ahmed Geology Depa.tment Faculty of ScienceAl-Azhar UniversityP.O.Box 11884Nasr CityCairoEgypt a.dulla. a.rus.a.d Cha.r for Ea.th s.ience Remote s.ns.ng Res.a.ch Geology and Geophysics DepartmentCollege of ScienceKing Saud UniversityRiyadh11451Saudi Arabia

This.res.a.ch us.s.both three-dimens.ona.(3D)modeling a.d geologic well control to piece ba.k together the a.chitectura. pa.ts.of the La.e Creta.eous.*** goa. is.to figure out the s.zes.directions.loca.ions.a.d controls.of the la.ers.of the fluvia. s.0}ds.one *** s.ra.igra.hy is.es.entia. for 3D res.rvoir modeling a.d petroleum geology unders.a.ding in the Ba.ga.*** purpos. of this.work is.to crea.e a.s.a.ic model tha. s.ows.the la.ers.a.d fa.ies.dis.ribution in the res.rvoir *** will us. da.a.from nine well logs.a.d 22 s.is.ic lines.ca.ibra.ed by the a.u Roa.h G Member res.rvoir core interva.s.to a.complis. *** petrophys.ca. s.udy dis.overed three pa.ts.in the a.u Roa.h G Member res.rvoir rock:cha.nel fill tha. is.a.fected by tides.cha.nel fill tha. is.domina.ed by tides.intertida. s.0}ds.,a.d cha.nel top with lenticula. bedded *** model's.findings.point to the exis.ence of a. NNW-oriented s.0}d body,which could be a.prime loca.ion to produce *** origina. oil in pla.e(OOIP)is.a.out 3,438,279 s.ock Ta.k Ba.rels.s.B),a.d the oil res.rve rea.hes.up to 1,031,484(s.B).s.quence s.ra.igra.hic a.a.ys.s.us.ng s.is.ic a.d well log information(s.)revea.s.tha. the Upper Creta.eous.a./G res.rvoir of the Ba.ga.field is.cha.a.terized by third-a.d fourth-order s.ra.igra.hic s.quences.which a.e cons.ra.ned by three maximum Flooding s.rfa.es.MFs.a.d two s.quence *** integra.ion of the derived geologica. model a.d s.quence s.ra.igra.hic res.lts.ca. lower future extra.tion ris. by identifying the loca.ions.a.d trends.of the geologic fa.ies.with the neces.a.y petrophys.ca. properties.for the hydroca.bon a.cumula.ions.

关键词： Three-dimens.ona. res.rvoir modeling s.quence s.ra.igra.hy Res.rvoir cha.a.teriza.ion a.u Roa.h res.rvoir a.u Gha.a.ig Ba.in

s.curity a.a.ys.s.in s.2}rt a.riculture: Ins.ghts.from a.Cyber-Phys.ca. s.s.em a.plica.ion

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Computers. materia.s.& Continua 2024年第6期79卷 4781-4803页

作者： ahmed Redha.mahlous College of Computer a.d Information s.iences Prince Sultan UniversityRiyadh11586Saudia Arabia

s.0}rt a.riculture modifies.tra.itiona. fa.ming pra.tices.a.d offers.innova.ive a.proa.hes.to boos. production a.d s.s.a.na.ility by levera.ing contempora.y *** toda.’s.world where technology is.everything,thes. technologies.a.e utilized to s.rea.line regula. ta.ks.a.d procedures.in a.riculture,one of the la.ges. a.d mos. s.gnifica.t indus.ries.in every *** res.a.ch pa.er s.a.ds.out from exis.ing litera.ure on s.0}rt a.riculture s.curity by providing a.comprehens.ve a.a.ys.s.a.d exa.ina.ion of s.curity is.ues.within s.0}rt a.riculture *** into three main s.ctions.s.curity a.a.ys.s.s.s.em a.chitecture a.d des.gn a.d ris. a.s.s.ment of Cyber-Phys.ca. s.s.ems.CPs.a.plica.ions.the s.udy delves.into va.ious.elements.crucia. for s.0}rt fa.ming,s.ch a. da.a.s.urces.infra.tructure components.communica.ion protocols.a.d the roles.of different s.a.eholders.s.ch a. fa.mers.a.ricultura. s.ientis.s.a.d res.a.chers.technology providers.government a.encies.cons.mers.a.d many *** contra.t to ea.lier res.a.ch,this.work a.a.yzes.the res.lience of s.0}rt a.riculture s.s.ems.us.ng a.proa.hes.s.ch a. threa. modeling,penetra.ion tes.ing,a.d vulnera.ility *** dis.overies.highlight the concerns.connected to uns.cured communica.ion protocols.pos.ible threa.s.from malevolent a.tors.a.d vulnera.ilities.in IoT ***,the s.udy s.gges.s.enha.cements.for CPs.a.plica.ions.s.ch a. s.rong a.ces. controls.intrus.on detection s.s.ems.a.d encryption *** a.dition,ris. a.s.s.ment techniques.a.e a.plied to prioritize mitiga.ion ta.tics.a.d detect potentia. ha.a.ds.a.dres.ing is.ues.like da.a.brea.hes.s.s.em outa.es.a.d a.tomated fa.ming proces. *** res.a.ch s.ts.its.lf a.a.t even more by pres.nting a.prototype CPs.a.plica.ion tha. makes.us. of a.digita. tempera.ure *** a.plica.ion was.firs. crea.ed us.ng a.Tinkerca. s.mula.or a.d then us.ng a.tua. ha.dware with a.duino *** CPs.a.plica.ion’s.defens.s.a.a.ns. p

关键词： s.0}rt a.riculture cyber-phys.ca. s.s.em IoT s.curity tempera.ure s.ns.r threa.s vulnera.ilities

The La.bert-G Fa.ily:Properties.Inference,a.d a.plica.ions

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Computer Modeling in Engineering & s.iences 2024年第7期140卷 513-536页

作者： Ja.0}l N.a. a.ba.i ahmed Z.a.ify Ba.r a.ns.ya. Mus.a.a.s.s.a.0} a.counting Depa.tment Ashur UniversityBaghdad10011Iraq Depa.tment of s.a.is.ics Mathematics and InsuranceBenha UniversityBenha13511Egypt Depa.tment of mana.ement Information s.s.ems.a.d Production mana.ement College of Business and EconomicsQassim UniversityBuraydah51452Saudi Arabia Depa.tment of Ba.ic s.iences Common First Year(CFY)King Saud UniversityRiyadh11362Saudi Arabia Depa.tment of mathematics.a.d s.a.is.ics Osim Higher Institute of Administrative ScienceOsim12961Egypt

This.s.udy propos.s.a.new flexible fa.ily of dis.ributions.ca.led the La.bert-G *** La.bert fa.ily is.very flexible a.d exhibits.des.ra.le *** three-pa.a.eter s.ecia. s.b-models.provide a.l s.gnifica.tmonotonic a.d non-monotonic fa.lure ra.es.a.s.ecia. s.b-model of the La.bert fa.ily ca.led the La.bert-Lomax(LL)dis.ribution is.*** expres.ions.for the LL s.a.is.ica. properties.a.e *** of the LL dis.ribution a.e a.dres.ed mathematica.ly ba.ed on its.ha.a.d *** es.imation of the LL pa.a.eters.is.dis.us.ed us.ng s.x es.imation *** performance of this.es.imation method is.explored through s.mula.ion *** us.fulnes. a.d flexibility of the LL dis.ribution a.e demons.ra.ed empirica.ly us.ng two rea.-life da.a.*** LL model better fits.the exponentia.ed Lomax,invers. power Lomax,Lomax-Ra.leigh,power Lomax,a.d Lomax dis.ributions.

关键词： La.bert function Lomax dis.ribution maximum likelihood ha.a.d function s.a.is.ica. model s.mula.ion