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Pa.terns of bra.n injuries a.socia.ed with ma.illofa.ia. fra.tures a.d its fa.e in emergency Egyptia. polytra.ma.pa.ients

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Chinese Journa. of Tra.ma.ology 2018年第5期21卷 287-292页

作者： a.el Ha.ed elba.h doaa a. el-sayed a.med E. a.ou-Zeid Gha.a.K. elha.a.y Depa.tment of Emergency Medicine Faculty of Medicine Suez Canal University Ismailia Egypt

Purpose： Ma.illofa.ia. injuries a.e commonly encountered in the pra.tice of emergency medicine. More tha. 50% of pa.ients with these injuries ha.e multisystem tra.ma.tha. requires coordina.ed ma.a.e- ment between emergency physicia.s a.d surgica. specia.ists in ora. a.d ma.illofa.ia. surgery, otola.- yngology, pla.tic surgery, ophtha.mology, a.d tra.ma.surgery. The a.m of this study is to identify the pa.terns of bra.n injuries a.socia.ed with ma.illofa.ia. tra.ma.a.d its outcome. Methods： This descriptive study （cross-sectiona.） wa. ca.ried out a.ong 90 polytra.ma.pa.ients with ma.illofa.ia. fra.tures a.tending the Emergency Depa.tment a. Suez Ca.a. university Hospita. a.d fulfilling our inclusion a.d exclusion criteria. Results： This study demonstra.es the rela.ion between type of ma.illofa.ia. fra.ture a.d type of tra.- ma.ic bra.n injuries in which the ma.ority of pa.ients with epidura. hemorrha.e presented with mid fa.e fra.tures （60%）, while the minority of them presented with upper a.d lower fa.e fra.tures （20% for ea.h of them）. The ma.ority of pa.ients with subdura. hemorrha.e were a.socia.ed with mid fa.e fra.tures （75%）, the ma.ority of pa.ients with bra.n contusions a.socia.ed with mid fa.e fra.tures （75%）, a.d a.l of the pa.ients presented by pneumocepha.us were a.socia.ed with mid fa.e fra.tures （100%）. Conclusion： The results of this study confirm the va.ue of quick dia.nosis a.d ea.ly intervention, which is funda.enta. to prevent morbidity a. well a. morta.ity especia.ly with rega.ds to prevention of tra.ma.ic bra.n injury a. even a.short dura.ion of hvpoxia.a.d edema.will lea. to significa.t perma.ent neurologica. deficits.

关键词： Ma.illofa.ia. fra.tures Bra.n injuries Outcome

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Optimiza.ion Ensemble Weights Model for Wind Foreca.ting System

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Computers, Ma.eria.s & Continua 2022年第11期73卷 2619-2635页

作者： a.el a.i a.hussa. el-sayed M.el-kena.y Hussa. Na.ser a.Eisa.M.el-Sa.D sayed a.Wa.d doaa Sa.i Kha.a.a Depa.tment of Computer Sciences College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityRiyadh11671Saudi Arabia Depa.tment of Communica.ions a.d electronics Delta Higher Institute of Engineering and TechnologyMansoura35111Egypt Fa.ulty of a.tificia. Intelligence Delta University for Science and TechnologyMansoura35712Egypt electrica. Engineering Depa.tment Faculty of EngineeringMansoura UniversityMansoura35516Egypt Delta.Higher Institute of Engineering a.d Technology(DHIET) Mansoura35111Egypt Depa.tment of electrica. Engineering Faculty of Engineering at ShoubraBenha UniversityCairo11629Egypt Fa.ulty of Engineering Delta University for Science and TechnologyGamasaMansoura11152Egypt

Effective technology for wind direction foreca.ting ca. be rea.ized using the recent a.va.ces in ma.hine ***,the sta.ility a.d sa.ety of power systems a.e expected to be significa.tly ***,the unsta.le a.d unpredicta.le qua.ities of the wind predict the wind direction a.cha.lenging *** pa.er proposes a.pra.tica. foreca.ting a.proa.h ba.ed on the weighted ensemble of ma.hine lea.ning *** weighted ensemble is optimized using a.wha.e optimiza.ion a.gorithm guided by pa.ticle swa.m optimiza.ion(PSO-Guided WOa..The proposed optimized weighted ensemble predicts the wind direction given a.set of input *** conducted experiments employed the wind power foreca.ting da.a.et,freely a.a.la.le on Ka.gle a.d developed to predict the regula. power genera.ion a. seven wind fa.ms over forty-eight *** recorded results of the conducted experiments empha.ize the effectiveness of the proposed ensemble in a.hieving a.cura.e predictions of the wind *** a.dition,a.compa.ison is esta.lished between the proposed optimized ensemble a.d other competing optimized ensembles to prove its ***,sta.istica. a.a.ysis using one-wa. a.a.ysis of va.ia.ce(a.OVa.a.d Wilcoxon’s ra.k-sum a.e provided ba.ed on the recorded results to confirm the excellent a.cura.y a.hieved by the proposed optimized weighted ensemble.

关键词： Guided Wha.e Optimiza.ion a.gorithm(Guided WOa. foreca.ting ma.hine lea.ning weighted ensemble model wind direction

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Novel Optimized Fea.ure Selection Using Meta.euristics a.plied to Physica. Benchma.k Da.a.ets

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Computers, Ma.eria.s & Continua 2023年第2期74卷 4027-4041页

作者： doaa Sa.i Kha.a.a.el-sayed M.el-kena.y Fa.wa.a.rowa.s Sunil Kuma. a.delha.eed Ibra.im a.dela.iz a.a.delha.id Depa.tment of Computer Sciences College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Depa.tment of Communica.ions a.d electronics Delta Higher Institute of Engineering and TechnologyMansoura35111Egypt School of Computer Science University of Petroleum and Energy StudiesDehradun248001India Computer Engineering a.d Control Systems Depa.tment Faculty of EngineeringMansoura UniversityMansoura35516Egypt Depa.tment of Computer Science Faculty of Computer and Information SciencesAin Shams UniversityCairo11566Egypt Depa.tment of Computer Science College of Computing and Information TechnologyShaqra University11961Saudi Arabia

In da.a.mining a.d ma.hine lea.ning,fea.ure selection is a.critica. pa.t of the process of selecting the optima. subset of fea.ures ba.ed on the ta.get *** a.e 2n potentia. fea.ure subsets for every n fea.ures in a.da.a.et,ma.ing it difficult to pick the best set of fea.ures using sta.da.d ***,in this resea.ch,a.new meta.euristics-ba.ed fea.ure selection technique ba.ed on a. a.a.tive squirrel sea.ch optimiza.ion a.gorithm(a.SOa.ha. been *** using meta.euristics to pick fea.ures,it is common for the selection of fea.ures to va.y a.ross runs,which ca. lea. to *** of this,we used the a.a.tive squirrel sea.ch to ba.a.ce explora.ion a.d exploita.ion duties more evenly in the optimiza.ion *** the selection of the best subset of fea.ures,we recommend using the bina.y a.SOa.sea.ch stra.egy we developed *** to the suggested a.proa.h,the number of fea.ures picked is reduced while ma.imizing cla.sifica.ion a.cura.y.a.ten-fea.ure da.a.et from the University of Ca.ifornia.Irvine(UCI)repository wa. used to test the proposed method’s performa.ce *** other sta.e-of-the-a.t a.proa.hes,including bina.y grey wolf optimiza.ion(bGWO),bina.y hybrid grey wolf a.d pa.ticle swa.m optimiza.ion(bGWO-PSO),bPSO,bina.y stocha.tic fra.ta. sea.ch(bSFS),bina.y wha.e optimiza.ion a.gorithm(bWOa.,bina.y modified grey wolf optimiza.ion(bMGWO),bina.y multiverse optimiza.ion(bMVO),bina.y bowerbird optimiza.ion(bSBO),bina.y hybrid GWO a.d genetic a.gorithm 4028 CMC,2023,vol.74,no.2(bGWO-Ga.,bina.y firefly a.gorithm(bFa.,a.d *** results confirm the superiority a.d effectiveness of the proposed a.gorithm for solving the problem of fea.ure selection.

关键词： Meta.euristics a.a.tive squirrel sea.ch a.gorithm optimiza.ion methods bina.y optimizer

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Urba. electric Vehicle Cha.ging Sta.ion Pla.ement Optimiza.ion with Gra.la. Goose Optimiza.ion Voting Cla.sifier

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Computers, Ma.eria.s & Continua 2024年第7期80卷 1163-1177页

作者： a.el a.i a.hussa. doaa Sa.i Kha.a.a.el-sayed M.el-kena.y Ma.wa.M.Eid a.delha.eed Ibra.im Depa.tment of Computer Sciences College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Depa.tment of Communica.ions a.d electronics Delta Higher Institute for Engineering and TechnologyMansoura35511Egypt Fa.ulty of a.tificia. Intelligence Delta University for Science and TechnologyMansoura35712Egypt Computer Engineering a.d Control Systems Depa.tment Faculty of EngineeringMansoura UniversityMansoura35516Egypt

To reduce the nega.ive effects tha. conventiona. modes of tra.sporta.ion ha.e on the environment,resea.chers a.e working to increa.e the use of electric *** dema.d for environmenta.ly friendly tra.sporta.ion ma. be ha.pered by obsta.les such a. a.restricted ra.ge a.d extended ra.es of *** esta.lishment of urba. cha.ging infra.tructure tha. includes both fa.t a.d ultra.fa.t termina.s is essentia. to a.dress this ***,the powering of these termina.s presents cha.lenges beca.se of the high energy requirements,whichma. influence the qua.ity of *** the ma.imum hourly ca.a.ity of ea.h sta.ion ba.ed on its geogra.hic loca.ion is necessa.y to a.rive a. a. a.cura.e estima.ion of the resources required for cha.ging *** is vita. to do a. a.a.ysis of specific regiona. tra.fic pa.terns,such a. roa. networks,route deta.ls,junction density,a.d economic zones,ra.her tha. ma.ing a.bitra.y conclusions a.out tra.fic *** vehicle tra.fic is simula.ed using this da.a.a.d other va.ia.les,it is possible to detect limits in the design of the current tra.fic engineering ***,the bina.y gra.la. goose optimiza.ion(bGGO)a.gorithm is utilized for the purpose of fea.ure ***,the gra.la. goose optimiza.ion(GGO)a.gorithm is utilized a. a.voting cla.sifier a. a.decision a.gorithm to a.loca.e dema.d to cha.ging sta.ions while ta.ing into considera.ion the cost va.ia.le of tra.fic *** on the results of the a.a.ysis of va.ia.ce(a.OVa.,a.comprehensive summa.y of the components tha. contribute to the observed va.ia.ility in the da.a.et is *** results of the Wilcoxon Signed Ra.k Test compa.e the a.tua. media. a.cura.y va.ues of severa. different a.gorithms,such a. the voting GGO a.gorithm,the voting grey wolf optimiza.ion a.gorithm(GWO),the voting wha.e optimiza.ion a.gorithm(WOa.,the voting pa.ticle swa.m optimiza.ion(PSO),the voting firefly a.gorithm(Fa.,a.d the voting genetic a.gori

关键词： electric vehicle gra.la. goose optimiza.ion meta.euristics optimiza.ion ma.hine lea.ning

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Optimized Weighted Ensemble Using Dipper Throa.ed Optimiza.ion a.gorithm in Meta.a.eria. a.tenna

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Computers, Ma.eria.s & Continua 2022年第12期73卷 5771-5788页

作者： doaa Sa.i Kha.a.a.el-sayed M.el-kena.y Fa.en Kha.id Ka.im Sa.eer a.shetewi a.delha.eed Ibra.im a.dela.iz a.bdelha.id Depa.tment of Computer Sciences College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Depa.tment of Communica.ions a.d electronics Delta Higher Institute of Engineering and TechnologyMansoura35111Egypt Fa.ulty of a.tificia. Intelligence Delta University for Science and TechnologyMansoura35712Egypt Genera. Informa.ion Technology Depa.tment Ministry of DefenseThe Executive AffairsExcellence Services DirectorateRiyadh11564Saudi Arabia Computer Engineering a.d Control Systems Depa.tment Faculty of EngineeringMansoura UniversityMansoura35516Egypt Depa.tment of Computer Science Faculty of Computer and Information SciencesAin Shams UniversityCairo11566Egypt Depa.tment of Computer Science College of Computing and Information TechnologyShaqra University11961Saudi Arabia

Meta.a.eria. a.tenna. a.e a.type of a.tenna.tha. uses meta.a.eria. to enha.ce *** ba.dwidth restriction a.socia.ed with sma.l a.tenna. ca. be solved using meta.a.eria. *** lea.ning is ga.ning popula.ity a. a.wa. to improve solutions in a.ra.ge of *** lea.ning a.proa.hes a.e currently a.big pa.t of current resea.ch,a.d they’re likely to be huge in the *** model utilized determines the a.cura.y of the prediction in la.ge *** goa. of this pa.er is to develop a. optimized ensemble model for foreca.ting the meta.a.eria. a.tenna.s ba.dwidth a.d *** ba.ic models employed in the developed ensemble a.e Support Vector Regression(SVR),K-Nea.estRegression(KNR),Multi-La.er Perceptron(MLP),Decision Trees(DT),a.d Ra.dom Forest(RF).The percenta.es of contribution of these models in the ensemble model a.e weighted a.d optimized using the dipper throa.ed optimiza.ion(DTO)*** choose the best fea.ures from the da.a.et,the bina.y(bDTO)a.gorithm is *** proposed ensemble model is compa.ed to the ba.e models a.d results a.e recorded a.d a.a.yzed *** a.dition,two other ensembles a.e incorpora.ed in the conducted experiments for *** ensembles a.e a.era.e ensemble a.d K-nea.est neighbors(KNN)-ba.ed *** compa.ison is performed in terms of eleven eva.ua.ion *** eva.ua.ion results confirmed the superiority of the proposed model when compa.ed with the ba.ic models a.d the other ensemble models.

关键词： Meta.a.eria. a.tenna dipper throa.ed optimiza.ion fea.ure selection pa.a.eters prediction

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Dipper Throa.ed Optimiza.ion for Detecting Bla.k-Hole a.ta.ks inMa.ETs

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Computers, Ma.eria.s & Continua 2023年第1期74卷 1905-1921页

作者： Reem a.ka.hel el-sayed M.el-kena.y a.dela.iz a.a.delha.id a.delha.eed Ibra.im Mosta.a.a.ota.eb doaa Sa.i Kha.a.a Depa.tment of Informa.ion Technology College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Depa.tment of Communica.ions a.d electronics Delta Higher Institute of Engineering and TechnologyMansoura35111Egypt Fa.ulty of a.tificia. Intelligence Delta University for Science and TechnologyMansoura35712Egypt Depa.tment of Computer Science Faculty of Computer and Information SciencesAin Shams UniversityCairo11566Egypt Depa.tment of Computer Science College of Computing and Information TechnologyShaqra University11961Saudi Arabia Computer Engineering a.d Control Systems Depa.tment Faculty of EngineeringMansoura UniversityMansoura35516Egypt Depa.tment of System Progra.ming South Ural State UniversityChelyabinsk454080Russia Depa.tment of Computer Sciences College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia

In terms of security a.d priva.y,mobile a.-hoc network(Ma.ET)continues to be in dema.d for a.ditiona. deba.e a.d *** more Ma.ET a.plica.ions become da.a.oriented,implementing a.secure a.d relia.le da.a.tra.sfer protocol becomes a.ma.or concern in the ***,Ma.ET’s la.k of infra.tructure,unpredicta.le topology,a.d restricted resources,a. well a. the la.k of a.previously permitted trust rela.ionship a.ong connected nodes,contribute to the a.ta.k detection burden.a.novel detection a.proa.h is presented in this pa.er to cla.sify pa.sive a.d a.tive bla.k-hole *** proposed a.proa.h is ba.ed on the dipper throa.ed optimiza.ion(DTO)a.gorithm,which presents a.pla.sible pa.h out of multiple pa.hs for sta.istics tra.smission to boost Ma.ETs’qua.ity of service.a.group of selected pa.ket fea.ures will then be weighed by the DTO-ba.ed multi-la.er perceptron(DTO-MLP),a.d these fea.ures a.e collected from nodes using the Low Energy a.a.tive Clustering Hiera.chica.(LEa.H)clustering *** is a.powerful cla.sifier a.d the DTO weight optimiza.ion method ha. a.significa.t impa.t on improving the cla.sifica.ion process by strengthening the weights of key fea.ures while suppressing the weights ofminor *** hybridmethod is prima.ily designed to comba. a.tive bla.k-hole *** the LEa.H clustering pha.e,however,ca. a.so detect pa.sive bla.k-hole *** effect of mobility va.ia.ion on detection error a.d routing overhea. is explored a.d eva.ua.ed using the suggested *** diverse mobility situa.ions,the results demonstra.e up to 97%detection a.cura.y a.d fa.ter execution ***,the suggested a.proa.h uses a. a.justa.le threshold va.ue to ma.e a.correct conclusion rega.ding whether a.node is ma.icious or benign.

关键词： Bla.k-hole a.ta.k mobile a.-hoc network optimiza.ion dipper throa.ed optimiza.ion

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a.Synergistic Multi-a.tribute Decision-Ma.ing Method for Educa.iona. Institutions Eva.ua.ion Using Simila.ity Mea.ures of Possibility Pytha.orea. Fuzzy Hypersoft Sets

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Computer Modeling in Engineering & Sciences 2025年第1期142卷 501-530页

作者： Khura. a.i Kha. Sa.a.Mubeen Ishfa. a.iqe Ur Ra.ma. Sa.wa.el-Morsy Depa.tment of Ma.hema.ics University of SargodhaSargodha40100Pakistan Depa.tment of Ma.hema.ics University of Management and TechnologyLahore54000Pakistan Depa.tment of Ma.hema.ics College of ScienceQassim UniversityBuraydah51452Saudi Arabia

Due to the numerous va.ia.les to ta.e into a.count a. well a. the inherent a.biguity a.d uncerta.nty,eva.ua.ing educa.iona. institutions ca. be *** concept of a.possibility Pytha.orea. fuzzy hypersoft set(pPyFHSS)is more flexible in this rega.d tha. other theoretica. fuzzy set-like models,even though some a.tempts ha.e been ma.e in the litera.ure to a.dress such *** study investiga.es the elementa.y notions of pPyFHSS including its set-theoretic opera.ions union,intersection,complement,OR-a.d *** results rela.ed to these opera.ions a.e a.so modified for ***,the simila.ity mea.ures between pPyFHSSs a.e formula.ed with the a.sista.ce of numerica. exa.ples a.d ***,a. intelligent decision-a.sisted mecha.ism is developed with the proposa. of a.robust a.gorithm ba.ed on simila.ity mea.ures for solving multi-a.tribute decision-ma.ing(Ma.M)problems.a.ca.e study tha. helps the decision-ma.ers a.sess the best educa.iona. institution is discussed to va.ida.e the suggested *** a.gorithmic results a.e compa.ed with the most pertinent model to eva.ua.e the a.a.ta.ility of pPyFHSS,a. it genera.izes the cla.sica. possibility fuzzy set-like theoretica. ***,while considering significa.t eva.ua.ing fa.tors,the flexibility of pPyFHSS is observed through structura. compa.ison.

关键词： Hypersoft set Pytha.orea. fuzzy hypersoft set computa.iona. complexity multi-a.tribute decision-ma.ing optimiza.ion simila.ity mea.ures uncerta.nty

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Foreca.ting Energy Consumption Using a.Novel Hybrid Dipper Throa.ed Optimiza.ion a.d Stocha.tic Fra.ta. Sea.ch a.gorithm

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Intelligent a.toma.ion & Soft Computing 2023年第8期37卷 2117-2132页

作者： doaa Sa.i Kha.a.a.el-sayed M.el-kena.y a.el a.i a.hussa. Ma.wa.M.Eid Depa.tment of Computer Sciences College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Depa.tment of Communica.ions a.d electronics Delta Higher Institute of Engineering and TechnologyMansoura35111Egypt Fa.ulty of a.tificia. Intelligence Delta University for Science and TechnologyMansouraEgypt

The a.cura.e prediction of energy consumption ha. effective role in decision ma.ing a.d risk ma.a.ement for individua.s a.d ***,the a.cura.e prediction ca. be rea.ized using the recent a.va.ces in ma.hine lea.ning a.d predictive *** resea.ch proposes a.novel a.proa.h for energy consumption foreca.ting ba.ed on a.new optimiza.ion a.gorithm a.d a.new foreca.ting model consisting of a.set of long short-term memory(LSTM)*** proposed optimiza.ion a.gorithm is used to optimize the pa.a.eters of the LSTM-ba.ed model to boost its foreca.ting *** optimiza.ion a.gorithm is ba.ed on the recently emerged dipper-throa.ed optimiza.ion(DTO)a.d stocha.tic fra.ta. sea.ch(SFS)a.go-rithm a.d is referred to a. dyna.ic *** prove the effectiveness a.d superiority of the proposed a.proa.h,five sta.da.d benchma.k a.gorithms,na.ely,stocha.tic fra.ta. sea.ch(SFS),dipper throa.ed optimiza.ion(DTO),wha.e optimiza.ion a.gorithm(WOa.,pa.ticle swa.m optimiza.ion(PSO),a.d grey wolf optimiza.ion(GWO),a.e used to optimize the pa.a.eters of the LSTM-ba.ed model,a.d the results a.e compa.ed with tha. of the proposed *** results show tha. the proposed DDTOSFS+LSTM ca. a.cura.ely foreca.t the energy consumption with root mea. squa.e error RMSE of 0.00013,which is the best a.ong the recorded results of the other *** a.dition,sta.istica. experiments a.e conducted to prove the sta.istica. difference of the proposed *** results of these tests confirmed the expected outcomes.

关键词： Stocha.tic fra.ta. sea.ch dipper throa.ed optimiza.ion energy consumption long short-term memory prediction models

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Therma. explosion of a.rea.tive ga. mixture a. consta.t pressure for non-uniform a.d uniform tempera.ure systems

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Defence Technology（防务技术） 2022年第10期18卷 1842-1851页

作者： Sa.d a.el-sayed Mecha.ica. Power Engineering Dept.Za.a.ig University ZagazigAlshrkiaEgypt

In this study,the a.proxima.e a.d exa.t solutions for the sta.iona.y-sta.e of the solids model with neglecting rea.ta.t consumption for both non-uniform a.d uniform tempera.ure systems were a.plied on ga. ignition under a.consta.t pressure *** critica.ity conditions for a.sla.,a. infinite cylinder,a.d a.sphere a.e determined a.d discussed using dimensionless tempera.ures under consta.t a.bient a.d surfa.e tempera.ures for a.non-uniform tempera.ure *** solution for a.Semenov model with convection hea. loss wa. a.so *** solution of the Semenov problem for consta.t volume or density a. a.solid a.d consta.t pressure were *** critica. pa.a.eterδis ca.cula.ed a.d compa.ed with those of Fra.k-Ka.enetskii solution *** va.ida.ion of the ca.cula.ed ignition tempera.ures with other exa.t solution a.d experimenta. results were *** rela.ion between critica. pa.a.eters form Semenov a.d *** solution wa. introduced.

关键词： Therma. explosion a.proxima.e solution Critica. conditions Distributed a.d uniform tempera.ure systems

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Tra.sfer Lea.ning for Chest X-ra.s Dia.nosis Using Dipper Throa.ed a.gorithm

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Computers, Ma.eria.s & Continua 2022年第11期73卷 2371-2387页

作者： Hussa. Na.ser a.Eisa.el-sayed M.el-kena.y a.el a.i a.hussa. Moha.ed Sa.er a.dela.iz a.a.delha.id doaa Sa.i Kha.a.a Depa.tment of Computer Sciences College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityRiyadh11671Saudi Arabia Depa.tment of Communica.ions a.d electronics Delta Higher Institute of Engineering and TechnologyMansoura35111Egypt Fa.ulty of a.tificia. Intelligence Delta University for Science and TechnologyMansoura35712Egypt electronics a.d Communica.ions Engineering Depa.tment Faculty of EngineeringDelta University for Science and TechnologyMansoura35712Egypt Depa.tment of Computer Science Faculty of Computer and Information SciencesAin Shams UniversityCairo11566Egypt Depa.tment of Computer Science College of Computing and Information TechnologyShaqra University11961Saudi Arabia

Most children a.d elderly people worldwide die from pneumonia.which is a.conta.ious illness tha. ca.ses lung *** dia.nosing pneumonia.from chest X-ra. ima.es,ma.y deep lea.ning models ha.e been put *** goa. of this resea.ch is to develop a. effective a.d strong a.proa.h for detecting a.d ca.egorizing pneumonia.*** va.ying the deep lea.ning a.proa.h,three pre-tra.ned models,GoogLeNet,ResNet18,a.d DenseNet121,a.e employed in this resea.ch to extra.t the ma.n fea.ures of pneumonia.a.d norma. *** a.dition,the bina.y dipper throa.ed optimiza.ion(DTO)a.gorithm is utilized to select the most significa.t fea.ures,which a.e then fed to the K-nea.est neighbor(KNN)cla.sifier for getting the fina. cla.sifica.ion *** gua.a.tee the best performa.ce of KNN,its ma.n pa.a.eter(K)is optimized using the continuous DTO *** test the proposed a.proa.h,six eva.ua.ion metrics were employed na.ely,positive a.d nega.ive predictive va.ues,a.cura.y,specificity,sensitivity,a.d ***,the proposed a.proa.h is compa.ed with other tra.itiona. a.proa.hes,a.d the findings confirmed the superiority of the proposed a.proa.h in terms of a.l the eva.ua.ion *** minimum a.cura.y a.hieved by the proposed a.proa.h is(98.5%),a.d the ma.imum a.cura.y is(99.8%)when different test ca.es a.e included in the eva.ua.ion experiments.

关键词： Meta.euristic pneumonia dipper throa.ed optimiza.ion KNN

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