Allocation of Resources to Innovation Transfer Projects within the Multinational Enterprise.docx

Allocation of Resources to Innovation Transfer Projects within the Multinational Enterprise.docx

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AllocationofResourcestoInnovationTransferProjectswithintheMultinationalEnterprise

Greycomprehensivecorrelationemployedtodeterminetheproductioncharacteristics.►Greyclusteringassessmentadoptedtoassessthesystemfunctionalrequirements.►CasestudiesfocusingontheprocessenterprisesinsouthwestChinaareillustrated.

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Fabricationofoff-axisasphericsurfacesusingaslowtoolservo  OriginalResearchArticle

InternationalJournalofMachineToolsandManufacture,Volume51,Issue5,May2011,Pages404-410

Z.Q.Yin,Y.F.Dai,S.Y.Li,C.L.Guan,G.P.Tie

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AbstractAbstract|Figures/TablesFigures/Tables|ReferencesReferences

Abstract

Off-axisasphericsurfaceshavebeenwidelyappliedinopticalsystems,butitisdifficulttofabricatethiskindofopticalsurfacewithhighquality.Slowtoolservoisoneofthemethodsforturningoff-axisasphericsurfaceson-axis,whichhavealargetravelrangewithoutanadditionaldevice.Thispaperpresentsatheoreticalandexperimentalinvestigationonthe3Dsurfacegenerationinsinglepointdiamondtuningusingslowtoolservo.Theformerrorofoff-axisparaboloidcausedbytoolcenteringerrorisanalyzedandverifiedbycuttingexperiment.

ArticleOutline

1.Introduction

2.Toolpathinslowtoolservocutting

2.1.Cuttingstrategies

2.2.Interpolationforslowtoolservo

2.3.Toolpathgeneration

3.3Dsurfacegeneration

4.Formerrorcausedbytoolcenteringerror

5.Experiments

6.Conclusions

Acknowledgements

References

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13

AServoSystemControlwithTime-varyingandNonlinearLoadConditionsUsingType-2TSKFuzzyNeuralSystem  OriginalResearchArticle

AppliedSoftComputing,InPress,AcceptedManuscript,Availableonline4April2011

ErdalKayacan,YesimOniz,AyseCiselAras,OkyayKaynak,RahibAbiyev

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AbstractAbstract

Abstract

Atype-2Takagi-Sugeno-Kangfuzzyneuralsystemisproposedanditsparameterupdaterulesarederivedusingfuzzyclusteringandgradientlearningalgorithms.Theproposedtype-2fuzzyneuralsystemisusedforthecontrolandtheidentificationofareal-timeservosystem.Fuzzyc-meansclusteringalgorithmisusedtodeterminetheinitialplacesofthemembershipfunctionstoensurethatthegradientdescentalgorithmusedafterwardsconvergesinashortertime.Anumberofdifferentloadconditionsincludingnonlinearandtime-varyingonesareusedtoinvestigatetheperformanceoftheproposedcontrolalgorithm.Thecontrolstructurehastheabilitytoregulatetheservosystemwithreducedoscillationswhencomparedwiththeresultsofitstype-1counterpartaroundthesetpointsignalinthepresenceofloaddisturbances.

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14

Miseenplacedelaventilationautoasservie  

MédecineduSommeil,Volume8,Issue1,January-March2011,Pages39-46

C.Philippe,F.Viau

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Résumé

Laventilationautoasservie（VAA）estunmodeventilatoirequiassocieuneaideinspiratoirevariableetunepressionexpiratoirefixeouautopilotée.Cetteaideinspiratoirevariecycleàcycleenfonctiondelaventilationmesuréechezlepatient.Elleaétéinitialementconçuepourcorrigerlarespirationpériodiquedespatientsprésentantuneinsuffisancecardiaque（IC）congestivestable,soustraitementmédicaloptimal.Aujourd’hui,sesindicationssesontélargiesauxSAScentrauxnormo-hypocapniques,mêmesileniveaudepreuvedesonefficacitéànormaliserl’indexd’apnées/hypopnéesestplusfaible.Lorsdel’instaurationd’uneVAAoudemodificationsdespressions,lespatientsinsuffisantscardiaques,etced’autantplusquel’ICestsévère,doiventbénéficierd’unesurveillancecliniqueettensionnelleparticulière.Commetouteventilation,lechoixdumasqueetlagestiondesfuitesdoiventêtreminutieux,lespressionsdedébutdetraitementdoiventpermettrelemeilleurconfortpossible.Lesmodificationsdesautresparamètresnécessitentuneanalysefinedestracéspoly（somno）graphiquesetdesdonnées« machine ».Lapersistanced’anomaliesobstructivesseragéréeparl’augmentationdelapressionexpiratoire.Pourcelled’anomaliescentrales,ilfautsavoirêtrepatient.Lesmodificationsdesbornesdel’aideinspiratoire,et/ouunemodificationdelafréquencerespiratoiredesécuritépeuventêtreproposées.

Summary

Adaptiveservo-ventilation（ASV）isanoveltherapythatprovidesinspiratorypressuresupportsuperimposedonfixedorautomaticpositiveexpiratorypressure.Thisinspiratorypressureismodifiedcyclebycycleaccordingtothepatient'sventilation.ItwasinitiallyconceivedtocorrecttheCheyne-Stokesrespirationinpatientswithstablecardiacfailureandreceivingoptimalmedicaltreatment.Today,indicationswidenedineucapnic/hypocapnicsleepcentralapnea,evenifthelevelofproofofitsefficiencytonormalizetheapnea/hypopneaindexisweaker.DuringtheinstitutionofanASVormodificationsofthepressures,HFpatients,anditespeciallyiftheHFissevere,havetobenefitfromaclinicalsupervisionandarterielpressuremonitoring.Asanyventilation,thechoiceofthemaskandthemanagementoftheleaksmustbemeticulous;thebeginningpressureshavetoallowthebestcomfort.Themodificationsoftheotherparametersrequireafineanalysisofpoly（somno）graphicdataandsoftware.Thepersistenceofobstructiveabnormalitieswillbemanagedbytheincreaseoftheexpiratorypressure.Forthecentralabnormalities,itisnecessarytobepatient.Themodificationsoftheinspiratorypressuresupportlimitsandoramodificationofthebackupratecanbeproposed.

ArticleOutline

Introduction

Définitions

Indications

Syndromed’apnéesdusommeilcentraldel’insuffisantcardiaque

Syndromed’apnéesdusommeilcentralchezunpatientprésentantdesantécédentsneurologiques

Syndromed’apnéesdusommeilcomplexes

Syndromed’apnéesdusommeilcentraldespatientsprenantdesopioïdes:

Syndromed’apnéesdusommeilcentralidiopathique

Algorithmesdesappareilsdeventilationautoasservie

AutoSetCS®（Resmed）

BiPAPautoSVAdvanced®

LaSOMNOventCR®

Miseenrouted’untraitementparventilationautoasservie

Conclusion

Conflitd’intérêt

References

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15

Governmentprogramscanimprovelocallabormarkets:

EvidencefromStateEnterpriseZones,FederalEmpowermentZonesandFederalEnterpriseCommunity  OriginalResearchArticle

JournalofPublicEconomics,Volume95,Issues7-8,August2011,Pages779-797

JohnC.Ham,CharlesSwenson,Ayşeİmrohoroğlu,HeonjaeSong

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Abstract

Federalandstategovernmentsspendwelloverabilliondollarsayearonprogramsthatencourageemploymentdevelopmentindisadvantagedlabormarketsthroughtheuseofsubsidiesandtaxcredits.InthispaperweuseanestimationapproachthatisvalidunderrelativelyweakassumptionstomeasuretheimpactofStateEnterpriseZones（ENTZs）,FederalEmpowermentZones（EMPZs）,andFederalEnterpriseCommunity（ENTC）programsonlocallabormarkets.Wefindthatallthreeprogramshavepositive,statisticallysignificant,impactsonlocallabormarketsintermsoftheunemploymentrate,thepovertyrate,thefractionwithwageandsalaryincome,andemployment.Further,theeffectsofEMPZandENTCdesignationareconsiderablylargerthantheimpactofENTZdesignation.Wefindthatourestimatesarerobusttoallowingforaregressiontothemeaneffect.Wealsofindthattherearepositive,butstatisticallyinsignificant,spillovereffectstoneighboringCensustractsofeachoftheseprograms.Thusourpositiveestimatesoftheseprogramimpactsdonotsimplyrepresentatransferfromthenearestnon-treatedCensustracttothetreatedCensustract.Ourresultsarenoteworthyforseveralreasons.First,ourstudyisthefirsttojointlylookatthesethreeprograms,thusallowingpolicymakerstocomparetheimpactsoftheseprograms.Second,ourpaper,alongwithaconcurrentstudybyNeumarkandKolko（2008）,isthefirsttocarryouttheestimationaccountingforoverlapbetweentheprograms.Third,ourestimationstrategyisvalidunderweakerassumptionsthanthosemadeinmanypreviousstudies;weconsiderthreecomparisongroupsandletthedatadeterminetheappropriategroup.Fourth,inspiteofourconservativeestimationstrategy,bylookingatnationaleffectswithdisaggregateddata,weshowthatENTZdesignationgenerallyhasapositiveeffectonthelocallabormarket,whilemostpreviousresearchonENTZs,muchofwhichusedmoregeographicallyaggregateddatatolookatstate-specificeffects,didnotfindanysignificantimpacts.Fifth,wenotethatthereislittleornopreviousworkonENTCs.Overall,ourresultsstronglysupporttheefficacyoftheselabormarketinterventions.

ArticleOutline

1.Introduction

2.Abriefdescriptionofenterprisezones,empowermentzones,andenterprisecommunities

2.1.EnterpriseZones（ENTZs）

2.2.EmpowermentZones（EMPZs）andEnterpriseCommunities（ENTCs）

3.Econometricapproach

3.1.Overview

3.2.Ourbasespecification;usingthenearestNENTZasacomparisonforanENTZ

3.2.1.Estimatinganaveragenationaleffect

3.2.2.Estimatingstate-specificaverageeffects

3.3.Amorerestrictive,butpotentiallymoreefficient,estimator

3.4.TheHec