Agentbased platform to support the execution of parallel tasksNeural Networks.docx
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Agentbased platform to support the execution of parallel tasksNeural Networks.docx
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AgentbasedplatformtosupporttheexecutionofparalleltasksNeuralNetworks
SNAP:
ADSStoanalyzenetworkservicepricingforstatenetworks
DecisionSupportSystems,Volume50,Issue1,December2010,Pages347-359
JongsawasChongwatpol,RameshSharda
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PetaAshworth,NaomiBoughen,MelissaMayhew,FrancesMillar
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ResearchonService-OrientedSBAsupportingenvironment OriginalResearchArticle
SimulationModellingPracticeandTheory,Volume17,Issue5,May2009,Pages979-989
NiLi,XiaoyuanPeng
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116
MiningtheR&Dinnovationperformanceprocessesforhigh-techfirmsbasedonroughsettheory OriginalResearchArticle
Technovation,Volume30,Issues7-8,July-August2010,Pages447-458
Chun-HsienWang,Yang-ChiehChin,Gwo-HshiungTzeng
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AbstractAbstract|Figures/TablesFigures/Tables|ReferencesReferences
Abstract
Theresearchanddevelopment(R&D)innovationoffirmscontinuestobeviewedasanimportantsourceofcompetitiveadvantagetoacademicsandpractitioners.ToexploreandextracttheR&Dinnovationdecisionrules,itisimportanttounderstandhowtheR&Dinnovationrule-baseworks.However,manystudieshavenotyetadequatelyinducedandextractedthedecisionruleofR&Dinnovationandperformancebasedonthecharacteristicsandcomponentsoftheoriginaldataratherthanonpost-determinationmodels.Theanalysisofthisstudyisgroundedinthetaxonomyofinduction-relatedactivitiesusingaroughsettheoryapproachorrule-baseddecision-makingtechniquetoinferR&DinnovationdecisionrulesandmodelslinkingR&Dinnovationtosalesgrowth.Therulesdevelopedusingroughsettheorycanbedirectlytranslatedintoapath-dependentflownetworktoinferdecisionpathsandparameters.Theflownetworkgraphandcause-and-effectrelationshipofdecisionrulesareheavilyexploitedinR&Dinnovationcharacteristics.Inaddition,anempiricalcaseofR&DinnovationperformancewillbeillustratedtoshowthattheroughsetsmodelandtheflownetworkgraphareusefulandefficienttoolsforbuildingR&Dinnovationdecisionrulesandprovidingpredictions.WewillthenillustratethatintegratingtheflownetworkgraphwithroughsettheorycanfullyreflectthecharacteristicsofR&Dinnovation,and,throughtheestablishedmodel,wecanobtainamorereasonableresultthanwithartificialinfluence.
ArticleOutline
1.Introduction
2.ReviewofpriorstudiesonR&Defforts
3.Roughsettheoryandflownetworkgraphalgorithm
3.1.Basicconceptsofroughset
3.2.Indiscernibility
3.3.Approximationsofsets
3.4.Attributesreductionsandcore
3.5.Decisionrulesextraction
3.6.Thecausal-and-effectofdecisionrulesbasedonflownetworkgraph
4.Anempiricalcaseofhigh-technologyfirms
4.1.Selectionvariablesanddata
4.2.Therules-basedpredictionofR&Dinnovationcharacteristics
4.3.Thecausal-and-effectflownetworkgraph
5.Conclusionsandremarks
Acknowledgements
References
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117
Impactof3Gandbeyondtechnologydevelopmentandpricingonmobiledataserviceprovisioning,usageanddiffusion OriginalResearchArticle
TelematicsandInformatics,Volume27,Issue3,August2010,Pages269-282
JarmoHarno
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Abstract
Thisstudyinvestigatesthethirdgenerationmobiletelecommunicationsystems(3G)diffusionchallengesinthesituationwherelarge-scalemobiledataserviceusagehasnotyetbrokenthrough.ThepaperfirstanalyzesincumbentmobileoperatorbusinessprospectsinalargeWestern-Europeancountry.Theresultssuggestthatrolloutofthemostadvancedavailable3Gtechnologiespaybackthroughincreaseddataserviceusageandrevenuesinthesituationofdecliningvoicerevenues.Inthemainbodyofthestudywediscussdifferentpricingmodelsanddemonstratethattheflatratepricingofdataservices,supplementedwithcertainconditions,supportsthelarge-scaletake-upofmobiledataservices.Itbooststheusageofmobiledataservicesandprovidesacompetitiveandsustainablebusinessmodelfortheoperatorsandothermarketactorsatthesametime.Ourmodelingindicatesfurthermore,thatflatratemodel,combinedwithopenaccess,givesbetterincentivestorollouthigh-speedmobiletechnologiestotheruralareas,thanthetraffic-basedcharging.
ArticleOutline
1.Introduction
2.Resultsfromthebasecasemodeling
3.Flatratepricingmodelforopenmobiledataaccess
3.1.Pricingmodeloptimality
3.2.Marketdevelopmentandthebroadbandinvestmentincentiveproblem
4.Quantitativecomparisonbetweenthebasiccaseandtheflatrateopenaccessmodel
4.1.Datatrafficdevelopmentandrelatedcostsintheflatrateapproach
4.2.Servicediffusionandrevenuedevelopmentintheflatrateapproach
4.3.Comparisonofthemodelingresultsofthebasiccaseandtheflatrateapproach
5.Incentivesforadvancedmobiletechnologyrolloutforruralareas
6.Finalremarks
Acknowledgements
References
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118
Technologyreadinessandriskassessments:
Anewapproach OriginalResearchArticle
ActaAstronautica,Volume65,Issues9-10,November-December2009,Pages1208-1215
JohnC.Mankins
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Abstract
Systemsthatdependupontheapplicationofnewtechnologiesinevitablyfacethreemajorchallengesduringdevelopment:
performance,scheduleandbudget.Technologyresearchanddevelopment(R&D)programsaretypicallyadvocatedbasedonargumentthattheseinvestmentswillsubstantiallyreducetheuncertaintyinallthreeofthesedimensionsofprojectmanagement.However,ifearlyR&Disimplementedpoorly,thenthenewsystemdevelopmentsthatplantoemploytheresultingadvancedtechnologieswillsufferfromcostoverruns,scheduledelaysandthesteadyerosionofinitialperformanceobjectives.Itisoftencriticalforseniormanagementtobeabletodeterminewhichofthesetwopathsismorelikely—andtorespondaccordingly.Thechallengeforsystemandtechnologymanagersistobeabletomakeclear,well-documentedassessmentsoftechnologyreadinessandrisks,andtodosoatkeypointsinthelifecycleoftheprogram.
Severalapproacheshavebeenusedtoevaluatetechnologymaturityandriskinordertobetteranticipatelatersystemdevelopmentrisks.The“technologyreadinesslevels”(TRLs),developedbyNASA,areonediscipline-independent,programmaticfigureofmerit(FOM)thatallowsmoreeffectiveassessmentof,andcommunicationregardingthematurityofnewtechnologies.Anotherbroadlyusedmanagementtoolisofthe“riskmatrix”,whichdependsuponagraphicalrepresentationofuncertaintyandconsequences.However,forthemostpartthesevariousmethodologieshavehadnoexplicitinterrelationship.
ThispaperwillexaminepastusesofcurrentmethodstoimproveR&Doutcomesandwillhighlightsomeofthelimitationsthatcanarise.Inthiscontext,anewconceptfortheintegrationoftheTRLmethodology,andtheconceptofthe“riskmatrix”willbedescribed.Thepaperwillconcludewithobservationsconcerningprospectivefuturedirectionsfortheimportantnewconceptofintegrated“technologyreadinessandriskassessments”.
ArticleOutline
1.Introduction
2.Theidealapproach
3.Technologydevelopmentcontext
4.Anintegratedtechnologyreadinessandriskassessmentapproach:
figuresofmerit
5.Anintegratedtechnologyreadinessandriskassessmentapproach:
anintegratedriskmatrix
6.HowmightthisnewTRRAapproachbeapplied?
7.Selectedspecialconsiderations
8.Summary
References
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119
TowardsclimateadaptationandcoastalgovernanceinIreland:
Integratedarchitectureforeffectivemanagement?
OriginalResearchArticle
MarinePolicy,InPress,CorrectedProof,Availableonline15February2011
MariaFalaleeva,CathalO'Mahony,StefanGray,MargaretDesmond,JeremyGault,ValerieCummins
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Abstract
Coastalenvironmentsaresusceptibletoarangeofimpactsarisingfrommediumandlong-termclimatechange.However,asIreland'spopulationandindustrialcentresareconcentratedincoastallocations,Ireland'scoastalcommunitieswillbeparticularlyvulnerabletotheimpactsofclimatechange.Therefore,makingthebestuseofexistingknowledgetoinformtheestablishmentofgovernancestructurescapableoffacilitatingthemeasuresandactionswhichmaysoonberequiredisanationalimperative.Coastalcommunitiesworldwidehaveturnedtointegratedcoastalzonemanagement(ICZM)asaprocesstodeliversustainabledevelopment.ThispaperexploreshowexperiencegainedfromICZMimplementationcanbeharnessedtoinformthedevelopmentandimplementationofclimateadaptationpolicies,withap
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