working in coordination with a supervisory software tool In this paper we discuss the potential ap.docx

working in coordination with a supervisory software tool In this paper we discuss the potential ap.docx

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workingincoordinationwithasupervisorysoftwaretoolInthispaperwediscussthepotentialap

FireGrid:

Ane-infrastructurefornext-generationemergencyresponsesupport  OriginalResearchArticle

JournalofParallelandDistributedComputing,Volume70,Issue11,November2010,Pages1128-1141

LiangxiuHan,StephenPotter,GeorgeBeckett,GavinPringle,StephenWelch,Sung-HanKoo,GerhardWickler,AsifUsmani,JoséL.Torero,AustinTate

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Researchhighlights

►Demonstrationofinfrastructureforurgentemergencyresponsedecisionsupport.►Asimulationmodelinfersincidentstatethatisinterpretedbyknowledgereasoning.►Densesensornetworksprovidelivedataforsteeringsimulationsinrealtime.►TheintegrationofGridandHPCprovidesrequisitecomputationalpower.►AItechniquesrationalizeandpresentcomplexsimulationresultsinaconcisemanner.

287

Onthenatureofsupportincomputer-supportedcollaborativelearningusinggStudy–January17,2009  OriginalResearchArticle

ComputersinHumanBehavior,Volume26,Issue5,September2010,Pages835-839

PhilipC.Abrami

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AbstractAbstract|ReferencesReferences

Abstract

TheauthorsofthearticlesinthisspecialissueofComputersinHumanBehaviorexplorethenatureofsupportingStudy,acomputer-supportedcollaborativelearning（CSCL）environment,especiallyfromtheperspectiveofthetheoryofself-regulation[e.g.,Zimmerman,B.J.（2000）.Attainmentofself-regulation:

Asocialcognitiveperspective.InM.Boekaerts,P.Pintrich,&M.Zeidner（Eds.）,Handbookofself-regulation,researchandapplications（pp.13–39）.Orlando,FL:

AcademicPress].Tocommentcriticallyonthesystematicandcomprehensiveresearchthiscollectionofarticlesrepresentsisadauntingtask.Therefore,Iwanttobeginbyinsuringthatthereaderhastheappropriateimpressionofthequalityandimportanceofthecollectionofstudiesandthetoolitself.

ArticleOutline

1.Commentsonthearticles

2.Commentsonlearnerneedsandwants

3.Concludingsuggestions

References

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288

Optimisationbaseddesignofadistrictenergysystemforaneco-townintheUnitedKingdom  OriginalResearchArticle

Energy,Volume36,Issue2,February2011,Pages1292-1308

C.Weber,N.Shah

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AbstractAbstract|Figures/TablesFigures/Tables|ReferencesReferences

Abstract

ThereductionofCO2emissionslinkedwithhumanactivities（mainlyenergyservicesandtransport）,togetherwiththeincreaseduseofrenewableenergies,remainhighprioritiesonvariouspoliticalagendas.However,consideringtheincreasedconsumptionofenergyservices（especiallyelectricity）,andthestochasticnatureofsomeofthemostpromisingrenewableenergies（windforinstance）,thechallengeistofindtheoptimalmixoftechnologiesthatwillprovidetheenergyservices,withoutincreasingtheCO2emissions,butnonethelessensuringreliabilityofsupply.ThefocusofthispaperistopresenttheDESDOPtool,basedonmixedintegerlinearoptimisationtechnics,thathelpsgivinginsightintheoptimalmixoftechnologiesthatwillsimultaneouslyhelpdecreasetheemissionswhileatthesametimeguaranteeresilienceofsupply.Theresultsshowthatwhileitisnotyetpossibletoavoidelectricityfromthegridcompletely（hencenuclearorfossilfuel）,CO2reductionsupto20%,atnoextracostscomparedtothebusiness-as-usualcase,areeasilyachievable.

ArticleOutline

Nomenclature

1.Introduction

2.Descriptionofthetool

2.1.Objectivefunction

2.2.Costfunctions

2.3.Energybalanceateachnode

2.4.Locationofthecentralisedtechnologies

2.5.Energybalanceattheplantnode

2.6.Energycascade

2.7.Networkconfiguration

2.8.Designsizeofthedistributedtechnologies

2.9.Designsizeofthecentralisedtechnologies

2.10.Partloadoperationofthecentralisedtechnologies

3.Modelsofthetechnologies

3.1.Heatpump

3.2.Combinedheatandpower

3.3.Windturbines

3.4.PVcells

3.5.Solarthermalcollectors

3.6.Boilers

4.Descriptionofthetestcase

5.Assumptions

6.Results

6.1.RestrictionsonCO2emissions

6.2.PVpricedecrease

6.3.Stochasticwindconditionsandlesswind

6.4.Higherheatingdemands

6.5.Electricitystorage

7.Conclusionsandfuturework

Acknowledgements

Appendix.Consumptionprofiles

References

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Researchhighlights

►Mixedintegerlinearoptimisationtechniquesareapowerfultooltodesignandoptimisedistrictenergysystems.►Integratedenergyconversionsystems（especiallycombinationofCHPsandheat-pumps）allowCO2reductionsforenergyservicesofatleast20%atnoextra-costscomparedtobusiness-as-usual（gridandboiler）.►Whilethegrid（hencenuclearand/orfossilfuels）cannotbeavoidedaslongaselectricitystoragedoesn’tcomeofage,thecriticismofanti-windlobbyistsregardingtheineffectivenessofwindpowercouldnotbeverified.

289

Anempiricalstudyofinstructoradoptionofweb-basedlearningsystems  OriginalResearchArticle

Computers&Education,Volume53,Issue3,November2009,Pages761-774

Wei-TsongWang,Chun-ChiehWang

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Abstract

Foryears,web-basedlearningsystemshavebeenwidelyemployedinbotheducationalandnon-educationalinstitutions.Althoughweb-basedlearningsystemsareemergingasausefultoolforfacilitatingteachingandlearningactivities,thenumberofusersisnotincreasingasfastasexpected.Thisstudydevelopsanintegratedmodelofinstructoradoptionofweb-basedlearningsystemsbyincorporatingexistingliteratureandmultipleempiricallyverifiedtheories,includingthetechnologyacceptancemodelandDeLoneandMcLean’sinformationsystemsuccessmodel.Surveydatacollectedfrom268universityinstructorswereexaminedusingstructuralequationmodelingtoverifytheproposedtheoreticalmodel.Theresearchresultsfurtherilluminatethefactorsthatexplainandpredicttheinstructoradoptionofweb-basedlearningsystems.Implicationsofthisstudyarealsodiscussed.

ArticleOutline

1.Introduction

2.Literaturereview

2.1.Web-basedlearningsystems

2.2.Instructors’adoptionofweb-basedlearningsystems

2.3.Userintentiontheory

2.4.Informationsystemsuccessmodel

3.Researchmodelandhypotheses

3.1.Overviewoftheproposedresearchmodel

3.2.Theinformationsystemdimension

3.3.Thepsychologicaldimension

3.4.Theuserbehaviordimension

4.Researchmethod

4.1.Developmentofinstruments

4.2.Datacollection

4.3.Demographicsanddescriptivestatistics

5.Dataanalysisandresults

5.1.Measurementmodel

5.2.Structuralmodel

6.Discussion

7.Conclusion

Acknowledgements

AppendixA.Appendix

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290

SupportingmobilityinanIMS-basedP2PIPTVservice:

Aproactivecontexttransfermechanism  OriginalResearchArticle

ComputerCommunications,Volume33,Issue14,1September2010,Pages1736-1751

IvanVidal,JaimeGarcia-Reinoso,AntoniodelaOliva,AlexBikfalvi,IgnacioSoto

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Abstract

Inrecentyears,IPTVhasreceivedanincreasingamountofinterestfromtheindustry,commercialprovidersandtheresearchcommunity,alike.Inthiscontext,standardizationbodies,suchasETSIandITU-T,arespecifyingthearchitectureofIPTVsystemsbasedonIPmulticast.AninterestingalternativetosupporttheIPTVservicedeliveryreliesonthePeer-to-Peer（P2P）paradigmtodistributeandpushthestreamingefforttowardsthenetworkedge.However,whileP2PIPTVwasstudiedinfixedaccesstechnologies,therehasbeenlittleattentionpaidtotheimplicationsarisinginmobileenvironments.Oneoftheseinvolvestheservicehandoverwhentheusermovestoadifferentnetwork.ByanalyzingpreviousworkfromtheperspectiveofanIPTVservice,weconcludedthataproactiveapproachisnecessaryforthehandlingofinter-networkhandovers.Inthispaper,weproposeanewgeneralhandovermechanismfortheIPMultimediaSubsystem（IMS）,whilestudyingitsapplicabilitytoaP2PIPTVservice.Oursolution,calledproactivecontexttransferservice,incorporatestheexistingIEEE802.21technologyinordertominimizethehandoverdelay.Theproposalisvalidatedbycomparingitagainstsolutionsderivedfrompreviouswork.

ArticleOutline

1.Introduction

2.BackgroundontheIMS-basedP2PIPTVservice

2.1.TheIPMultimediaSubsystem

2.2.P2PstreaminginIMS

3.EnablingseamlessmobilityintheP2PIPTVservice

3.1.BufferingpacketswhenroaminginIMS

3.2.AlternativesforUEmobilityinanIMS-basedIPTVservice

3.2.1.SIPmobility

3.2.2.OptimisedSIPmobility

3.2.3.MobileIPandIMS

4.Proactivecontexttransferservice

4.1.Initializingthecontexttransferservice

4.2.Transferringthecontext

5.DelayanalysisformobilestreaminginIMS

5.1.SIPmobilitydelay

5.2.SIPcontexttransfer

5.3.MobileIP

5.3.1.P-CSCFinthehomenetwork

5.3.2.P-CSCFinthevisitednetwork

5.4.PCTSAS

5.4.1.DelaywithoutMIP

5.4.2.DelaywithMIP

5.5.Summaryofthedelays

5.6.Recoveryphaseduration

6.Conclusions

Acknowledgements

References

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291

Process,practiceandpriorities–keylessonsl