main results achieved in the COST 271 Action concerning in particular.docx

main results achieved in the COST 271 Action concerning in particular.docx

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mainresultsachievedintheCOST271Actionconcerninginparticular

Designingfastsynchronizationmethodsforchaoticsystems.►Robustifyingsecurecommunicationsystemsinbothtimeandfrequencydomains.►Augmentingsynchronizationwithparameteridentificationforchaoticsystems.►Resistingintruderattacksbasedonreturnmapsandfilteringtechniques.►Transmittinganalogand/ordigitalsignalsinanoisypubliccommunicationchannel.

338

OpticalDopplertomographybasedonafieldprogrammablegatearray  OriginalResearchArticle

BiomedicalSignalProcessingandControl,Volume3,Issue1,January2008,Pages102-106

HenningEngelbrechtLarsen,RonnieThorupNilsson,LarsThrane,FinnPedersen,ThomasMartiniJørgensen,PeterE.Andersen

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339

Bsoft:

Imageprocessingandmolecularmodelingforelectronmicroscopy  OriginalResearchArticle

JournalofStructuralBiology,Volume157,Issue1,January2007,Pages3-18

J.BernardHeymann,DavidM.Belnap

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AbstractAbstract|Figures/TablesFigures/Tables|ReferencesReferences

Abstract

Bsoftisasoftwarepackagewrittenforimageprocessingofelectronmicrographs,interpretationofreconstructions,molecularmodeling,andgeneralimageprocessing.Thecodeismodularizedtoallowforrapidtestinganddeploymentofnewprocessingalgorithms,whilealsoprovidingsufficientinfrastructuretodealwithmanyfileformatsandparametricdata.Thedesignisdeliberatelyopentoallowinterchangeofinformationwithotherimageandmolecularprocessingsoftwarethroughastandardparameterfile（currentlyatext-basedencodingofparametersintheSTARformat）anditssupportofmultipleimageandmolecularformats.Italsoallowsshellscriptingofprocessesandallowssubtaskstobedistributedacrossmultiplecomputersforconcurrentprocessing.Bsofthasundergonemanymodificationsandadvancementssinceitsinitialrelease[Heymann,J.B.,2001.Bsoft:

imageandmolecularprocessinginelectronmicroscopy.J.Struct.Biol.133,156–169].Muchoftheemphasisisonsingleparticleanalysisandtomography,andsufficientfunctionalityisavailableinthepackagetosupportmostneededoperationsforthesetechniques.Thekeygraphicaluserinterfaceistheprogrambshow,whichdisplaysanimageandisusedformanyinteractivepurposessuchasfittingthecontrasttransferfunctionorpickingparticles.Bsoftalsooffersvarioustoolstomanipulateatomicstructuresandtorefinethefitofaknownmolecularstructuretoadensityinareconstruction.

ArticleOutline

1.Introduction

2.Generalimageprocessingprograms

3.TheconceptofworkflowinBsoft

3.1.Readyaccesstotheprimarydata,images,regardlessofformat

3.2.Adheringtoastandardsetofconventions

3.3.Aparameterexchangemechanism

3.4.Flexibleandaccessibledistributedprocessing

4.Micrographandreconstructionparameters

5.Singleparticleanalysis

5.1.MicrographassessmentandCTFfitting

5.2.Particlepicking

5.3.Particleorientationdetermination

5.4.Particlereconstruction

5.5.Initialreferencemaps

5.6.Handednessdetermination

5.7.Multipleparticleanalysis

5.8.Reconstructionmodification

5.9.Reconstructioninterpretation

6.Tomography

6.1.Preparationfortomographicalignment

6.2.Tomographicalignmentusingfiducialmarkers

6.3.Tomogramreconstructionanddenoising

6.4.Three-dimensionalsingleparticleanalysis

7.Molecularmodeling

8.Othertechniques

8.1.Helicalprocessing

8.2.Diffractionanalysis

8.3.Atomicforcemicroscopy

9.Associatedpackages

9.1.PFT2andEM3DR2

9.2.Radonpackage

10.Conclusion

10.1.TheBsoftpackage

10.2.Interchangebetweenpackages

Acknowledgements

AppendixA.ThecontrasttransferfunctioninBsoft

References

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340

Speedestimationofvectorcontrolledsquirrelcageasynchronousmotorwithartificialneuralnetworks  OriginalResearchArticle

EnergyConversionandManagement,Volume52,Issue1,January2011,Pages675-686

YukselOguz,MehmetDede

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341

Aknowledge-basedevolutionaryassistanttosoftwaredevelopmentprojectscheduling  OriginalResearchArticle

ExpertSystemswithApplications,Volume38,Issue7,July2011,Pages8403-8413

VirginiaYannibelli,AnalíaAmandi

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Abstract

Theschedulingofsoftwaredevelopmentprojectsisacentral,non-trivialandcostlytaskforsoftwarecompanies.Thistaskisnotexemptoferroneousdecisionscausedbyhumanlimitationsinherenttoprojectmanagers.Inthispaper,weproposeaknowledge-basedevolutionaryapproachwiththeaimofassistingtoprojectmanagersattheearlystageofschedulingsoftwareprojects.Givenasoftwareprojecttobescheduled,theapproachautomaticallydesignsfeasibleschedulesfortheproject,andevaluateseachdesignedscheduleaccordingtoanoptimizationobjectivethatispriorityformanagersatthementionedstage.Ourobjectiveistoassignthemosteffectivesetofemployeestoeachprojectactivity.Forthisreason,theevaluationofdesignedschedulesinourapproachisdevelopedbasedonavailableknowledgeaboutthecompetenceoftheemployeesinvolvedineachschedule.Thisknowledgearisesfromhistoricalinformationabouttheparticipationoftheemployeesinalreadyexecutedprojects.Inordertoevaluatetheperformanceofourevolutionaryapproach,wepresentcomputationalexperimentsdevelopedovereightdifferentsetsofprobleminstances.Theobtainedresultsarepromisingsincethisapproachhasreachedanoptimallevelofeffectivityonsevenoftheeightmentionedsets,andahighlevelofeffectivityontheremainingset.

ArticleOutline

1.Introduction

2.Problemdescription

2.1.Problemexample

3.Aknowledge-basedgeneticalgorithm

3.1.Representationorencodingofsolutions

3.1.1.Decodingofsolutions

3.2.Initialpopulation

3.3.Fitnessfunction

3.4.Selection

3.5.Crossover

3.5.1.Crossoveroperationforactivitylists

3.5.2.Crossoveroperationforassignedresourceslists

3.6.Mutation

3.6.1.Mutationoperationforactivitylists

3.6.2.Mutationoperationforassignedresourceslists

4.Computationalexperiments

5.Relatedworks

6.Conclusions

References

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Researchhighlights

►Weaddresstheproblemofschedulingasoftwaredevelopmentproject.►Objectiveconsidered:

toassignthemosteffectivesetofemployeestoeachactivity.►Tosolvetheproblem,weproposeaknowledge-basedevolutionaryapproach.►Theeffectivityoftheemployeesisestimatedbasedonavailablehistoricalknowledge.►Theapproachhasreachedexcellentresultsoneightdifferentprobleminstancesets.

342

Amodelfordevelopmentofoptimizedfeederroutesandcoordinatedschedules—Ageneticalgorithmsapproach  OriginalResearchArticle

TransportPolicy,Volume13,Issue5,September2006,Pages413-425

PrabhatShrivastava,MargaretO’Mahony

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Abstract

Manyattemptshavebeenmadetosolvebusroutenetworkdesignproblemsbysplittingitintwostages,oneforroutingandtheotherforscheduling.Someresearchershavemadeattemptstosolvenetworkdesignproblemsusingnon-traditionaloptimizationtechniquesalso,butnotmuchhasbeendoneonmodellingcoordinatedoperationsinvolvingtransfersfromonemodetoanother.Inthisresearch,feederroutesandfrequenciesleadingtoschedulecoordinationoffeederbuseswithmaintransitaredevelopedsimultaneouslyusinggeneticalgorithms.Thecoordinatedschedulesoffeederbusesaredeterminedfortheexistinggivenschedulesofmaintransit.Thusthedevelopedfeederroutesandschedulesarecomplementarytoeachother.AsacasestudytheDunLaoghaireDublinAreaRapidTransit（DART）（heavyrailsuburbanservice）stationofDublininIrelandisselected.FinallytheoutcomeoftheresearchisageneratedfeederroutenetworkforfeederbusesandcoordinatedschedulesoffeederbusesfortheexistingschedulesofDARTattheselectedstation.Theresultsoftheproposedmodelindicateimprovedloadfactorsondevelopedroutesandalsotheoverallloadfactorisalsoimprovedconsiderablyascomparedtotheauthors’earliermodel.

ArticleOutline

1.Introduction

1.1.Literaturereviewandobjectiveofstudy

1.2.Detailsofstudyarea

2.Datacollectionandanalysis

3.Modelfordevelopmentofoptimizedfeederroutesandcoordinatedschedules

3.1.Objectivefunction,constraintsandpenalties

3.1.1.Objectivefunction

3.2.Stepsinvolvedfordevelopmentofmodel

3.3.ApplicationofGAformodeldevelopment

3.3.1.OverviewofGAs

3.3.2.Implementationofgeneticalgorithms

4.Resultsanddiscussion

5.Conclusions

References

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343

DesignofcontentsforICTliteracyin-servicetrainingofteachersinKorea  OriginalResearchArticle

Computers&Education,Volume51,Issue4,December2008,Pages1683-1706

JongHyeKim,SoonYoungJung,WonGyuLee

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Abstract

TheimportanceofICTliteracyeducationforstudentsandteachersintheinformationsocietycannotbeov