Orthogonal drawings of graphs with vertex and edge labels.docx

Orthogonal drawings of graphs with vertex and edge labels.docx

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Orthogonaldrawingsofgraphswithvertexandedgelabels

MagneticResonanceImaging,Volume21,Issue10,December2003,Pages1175-1189

G.Garreffa,M.Carnì,G.Gualniera,G.B.Ricci,L.Bozzao,D.DeCarli,P.Morasso,P.Pantano,C.Colonnese,V.Roma,BMaraviglia

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737

Edgeenhancementbylocaldeconvolution  OriginalResearchArticle

PatternRecognition,Volume38,Issue5,May2005,Pages661-672

O.Laligant,F.Truchetet,A.Dupasquier

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AbstractAbstract|Figures/TablesFigures/Tables|ReferencesReferences

Abstract

Inthispaperanewapproachforblurredimagerestorationispresented.Ouralgorithmisbasedonhumanvisionwhichzoomsbackandforthintheimageinordertoidentifyglobalstructuresordetails.Deconvolutionparametersareestimatedbyanedgedetectionandcorrespondtotheonesofachosenedgedetectionmodel.Thesegmentationisobtainedbymergingmultiscaleinformationprovidedbymultiscaleedgedetection.TheedgedetectionisachievedbyusingaderivativeapproachfollowingageneralizationofCanny–Derichefiltering.Thismultiscaleanalysisperformsanefficientedgedetectioninnoisyblurredimages.Themergingleadstothebestlocalrepresentationofedgeinformationacrossscales.Thealgorithmdealswithamixed（coarse-to-fine/fine-to-coarse）approachandsearchesforcandidateedgepointsthroughthescales.Edgecharacteristicsareestimatedbythemergingalgorithmforthechosenmodel.Scale,directionandamplitudeinformationsallowalocaldeconvolutionoftheoriginalimage.Thenoiseproblemisnotconsideredinthisworksinceitdoesnotdisturbtheprocess.Resultsshowthatthismethodallowsnon-uniformlyblurredimagerestoration.Animplementationofthewholealgorithminanintelligentcamera（DSP）hasbeenperformed.

ArticleOutline

1.Introduction

2.Edgedetection

2.1.Edgemodel

2.2.Edgedetector

2.3.Responsesandperformancesofthedetectors

2.3.1.Response

2.3.2.Edgelocalization

2.3.3.Signaltonoisecriterion

2.4.Strategyforrestoration

3.Edgeimagerepresentation

3.1.Multiscaleedgedetection

3.2.Influenceofaneighboredge

3.3.Merging

4.Restoration

4.1.Modelparametersestimate

4.2.Deconvolution

4.3.Results

5.Conclusion

AppendixA.Responseofthedetectorstotheedgemodel

AppendixB.Localization

AppendixC.Signalovernoiseratio

AppendixD.Scaleofthedetectorsformaximuminlocalization

References

Vitae

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738

Algorithmsforoptimalmulti-resolutionquantization  OriginalResearchArticle

JournalofAlgorithms,Volume50,Issue1,January2004,Pages1-22

SorinaDumitrescu,XiaolinWu

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AbstractAbstract|ReferencesReferences

Abstract

Multi-resolutionquantizationisawayofconstructingaprogressivelyrefinabledescriptionofa discreterandomvariable.Theunderlyingdiscreteoptimizationproblemistominimizeanexpecteddistortionoverallrefinementlevelsweightedbytheprobabilityorimportanceofthedescriptionsofdifferentresolutions.Thisresearchismotivatedbytheapplicationofmultimediacommunicationsviavariable-ratechannels.WeproposeanO（rN2）timeandO（N2logN）spacealgorithmtodesignaminimum-distortionquantizerofrlevelsforarandomvariabledrawnfromanalphabetofsize N.Itisshownthatforaverylargeclassofdistortionmeasurestheobjectivefunctionofoptimalmulti-resolutionquantizationsatisfiestheconvexMongeproperty.TheefficiencyoftheproposedalgorithmhingesontheconvexMongeproperty.Butouralgorithmissimpler（eventhoughofthesameasymptoticcomplexity）thanthewell-knownSMAWKfastmatrixsearchtechnique,whichisthebestexistingsolutiontothequantizationproblem.Forexponentialrandomvariablesourapproachleadstoasolutionofevenlowercomplexity:

O（rN）timeandO（NlogN）space,whichoutperformsalltheknownalgorithmsforoptimalquantizationinbothmulti-andsingle-resolutioncases.Wealsogeneralizethemulti-resolutionquantizationproblemtoagraphproblem,forwhichouralgorithmoffersanefficientsolution.

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739

Theeffectsofstatic,dynamicandfatiguebehavioronthree-dimensionalshapeoptimizationofhipprosthesisbyfiniteelementmethod  OriginalResearchArticle

Materials&Design,Volume28,Issue8,2007,Pages2269-2277

OguzKayabasi,BulentEkici

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Abstract

Thefiniteelementmethod,oneofthemostadvancedsimulationtechniquesinsolidmechanics,isusedfororthopedicbiomechanics.Itisusedasatoolforthedesignandanalysisoftotaljointreplacementandotherorthopedicdevices.Thedesignofhipjointprosthesesisacomplexprocessthatrequirescloseco-operationbetweenengineersandsurgeons.Todesignhighlydurableprosthesesonehastotakeintoaccountthenaturalprocessesoccurringinthebone.Oneofthemostimportantfactorsintheimplantdesignistoreducestressonthefemurandthebone-cement.Thepurposeofthisstudyistoinvestigatethebehaviorofnewlydesignedimplantsunderbodyweightloadduringstumblingbyparametricmodeling.Twodifferentimplantmaterialshavebeenselectedtostudyappropriatematerialandfatigueliferesistant.Intheparametricdesign,theprosthesisfunctionalrequirementisthatthelockingofstemtothefemurheadusingcementshouldbestrongenoughtoprecludeunlockingduringthelifetimeofapatientandtopreventslidingoftheimplantintothebone-cement.

Inthefiniteelementanalysis,physicalinteractionsamongjointsaresimulatedbycontactalgorithms.Thefemur–bone-cementinterfaceandthebone-cement–implantinterfacesurfacetosurfacecontactalgorithmsofANSYSwereusedforimplicitstaticanalysis.Threestem-cementinterfaceconditionsareconsidered:

completelybonded,debondedwithcoefficientoffriction0,anddebondedwithcoefficientoffriction0.2.Intheanalysis,aviscoelasticmaterialmodelisutilizedforbone-cement.Numericalshapeoptimizationisappliedtotheprosthesis.

TheresultsoffiniteelementsimulationsarecomparedwithCharnley’simplantresultsandappropriatematerialfortheimplantisproposed.Thebeststemshapesfulfillingthedesiredfunctionalrequirementsarechosenforthedesign.Thesefindingscanformabaseforfurtherresearchsuchastheoptimumdesignofbone-implanthipprosthesis.

ArticleOutline

1.Introduction

2.Methods,geometricandfiniteelementmodeling

2.1.Methods

2.2.Parametricandgeometricmodeling

2.3.Finiteelementmodeling

3.Results

4.Conclusion

References

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Assistingconceptualdesignofbuildingstructuresbyaninteractivedescriptionlogicbasedplanner  OriginalResearchArticle

AdvancedEngineeringInformatics,Volume17,Issue1,January2003,Pages41-57

MichaelEisfeld,RaimarScherer

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AbstractAbstract|Figures/TablesFigures/Tables|ReferencesReferences

Abstract

Designingstructuralconfigurationsfortoday'sbuildingstructuresisachallengingengineeringactivitythatneedstobesupported.Existingsystemsoftencannotsupporttheengineerindesigningastructuralconfigurationwitharobustgloballoadtransfer.Inthispaper,wediscussaninteractiveplanningalgorithmthatassiststheengineerintheconceptualdesigntaskbyknowledgeaboutstructure.Centraltoourapproachistheuseofadaptedinferenceservicesofadescriptionlogicreasonerthatcontrolsthegloballoadtransferofthestructuralconfigurationunderdevelopmentandthedesignprocessontheirevaluationresults.Weintroducetheexpressivedescriptionlogiclanguage

−torepresentstructuralknowledgeacquiredfrompractitioners.Ahierarchicalplanninglanguageontopofitusedforrepresentingthedynamicdesignprocess.

ArticleOutline

1.Introduction

2.Problemformulation

3.Computationalconceptualdesigntask

3.1.Thelanguage

andthereasoningservicesforconceptualdesignsupport

3.2.Theplanninglanguageon

3.3.InteractivealgorithmConEd

4.Detailedexample

5.Relatedwork

6.Conclusions

Acknowledgements

References

Vitae

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741

Amarscommunicationconstellationforhumanexplorationandnetworkscience  OriginalResearchArticle

AdvancesinSpaceResearch,Volume45,Issue1,4January2010,Pages183-199

FrancescoCastellini,AndreaSimonetto,RobertoMartini,MichèleLavagna

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Abstract

ThispaperanalysesthepossibilityofexploitingasmallspacecraftsconstellationaroundMarstoensureacompleteandcontinuouscoverageoftheplanet,forthepurposeofsupportingfuturehumanandroboticoperationsandtakingadvantageofopticaltransmissiontechniques.Thestudyforeseessuchacommunicationsmissiontobeimplementedatleastafter2020andahighdata-raterequirementisimposedforthereturnofhugescientificdatafrommassiveroboticexplorationortoallowvideotransmissionsfromapossiblehumanoutpost.

Inaddition,theset-upofacommunicationconstellationaroundMarswouldgivetheopportunityofexploitingthismulti-platforminfrastructuretoperformnetworkscience,thatwouldlargely