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Researchhighlights

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

287

Onthenatureofsupportincomputer-supportedcollaborativelearningusinggStudy–January17,2009 

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

$19.95

288

Optimisationbaseddesignofadistrictenergysystemforaneco-townintheUnitedKingdom 

Energy,Volume36,Issue2,February2011,Pages1292-1308

C.Weber,N.Shah

AbstractAbstract|Figures/TablesFigures/Tables|ReferencesReferences

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

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

$35.95

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

289

Anempiricalstudyofinstructoradoptionofweb-basedlearningsystems 

Computers&

Education,Volume53,Issue3,November2009,Pages761-774

Wei-TsongWang,Chun-ChiehWang

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

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

AppendixA.Appendix

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290

SupportingmobilityinanIMS-basedP2PIPTVservice:

Aproactivecontexttransfermechanism 

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

IvanVidal,JaimeGarcia-Reinoso,AntoniodelaOliva,AlexBikfalvi,IgnacioSoto

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.

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

291

Process,practiceandpriorities–keylessonsl