Two different clay levels at mean depths of about 2 and 4 m depth have been imaged.docx

Two different clay levels at mean depths of about 2 and 4 m depth have been imaged.docx

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Twodifferentclaylevelsatmeandepthsofabout2and4mdepthhavebeenimaged

Titan'ssurfaceat2.2-cmwavelengthimagedbytheCassiniRADARradiometer:

Calibrationandfirstresults  OriginalResearchArticle

Icarus,Volume200,Issue1,March2009,Pages222-239

M.A.Janssen,R.D.Lorenz,R.West,F.Paganelli,R.M.Lopes,R.L.Kirk,C.Elachi,S.D.Wall,W.T.K.Johnson,Y.Anderson,R.A.Boehmer,P.Callahan,Y.Gim,G.A.Hamilton,K.D.Kelleher,L.Roth,B.Stiles,A.LeGallandtheCassiniRadarTeam

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AbstractAbstract|Figures/TablesFigures/Tables|ReferencesReferences

Abstract

ThefirstcomprehensivecalibrationandmappingofthethermalmicrowaveemissionfromTitan'ssurfaceisreportedbasedonradiometricdataobtainedat2.2-cmwavelengthbythepassiveradiometerincludedintheCassiniRadarinstrument.Thedatareportedwereaccumulatedfrom69separateobservationalsegmentsinTitanpassesfromTa（October2004）throughT30（May2007）andincludeemissionfrom94%ofTitan'ssurface.Theyarediverseinthekeyobservingparametersofemissionangle,polarization,andspatialresolution,andtheirreductionintocalibratedglobalmosaicmapsinvolvedseveralsteps.Analysisofthepolarimetryobtainedatlowtomoderateresolution（50+km）enabledintegrationoftheradiometryintoasinglemosaicoftheequivalentbrightnesstemperatureatnormalincidencewitharelativeprecisionofabout1K.TheHuygensprobemeasurementofTitan'ssurfacetemperatureandradiometryobtainedonTitan'sdunefieldsallowedustoinferanabsolutecalibrationestimatedtobeaccuratetoalevelapproaching1K.Theresultsprovideevidenceforasurfacethatiscomplexandvariedonlargescales.Theradiometryprimarilyconstrainsphysicalpropertiesofthesurface,whereweseestrongevidenceforsubsurface（volume）scatteringasadominantmechanismthatdeterminestheemissivity,withthepossibilityofafluffyorgraded-densitysurfacelayerinmanyregions.Theresultsareconsistentwith,butnotnecessarilydefinitiveofasurfacecompositionresultingfromtheslowdepositionandprocessingoforganiccompoundsfromtheatmosphere.

ArticleOutline

1.Introduction

2.TheCassiniradiometer

2.1.Description

2.2.Calibration

2.2.1.Beamcalibration

2.2.2.Relativegaincalibration

3.Observationsandinitialcalibration

4.MappingTitan

4.1.Summary

4.2.Emissionmodel

4.3.Dielectricmosaic

4.4.Brightnesstemperaturemosaic

4.5.Mosaicuncertainties

4.6.Absolutecalibration

5.Discussion

6.Conclusions

Acknowledgements

References

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Analysisofunderwatermammalvocalisationsusingtime–frequency-phasetracker  OriginalResearchArticle

AppliedAcoustics,Volume71,Issue11,November2010,Pages1070-1080

CornelIoana,CédricGervaise,YannStéphan,JerômeI.Mars

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Abstract

Oneofthemostchallengingapplicationsoftime–frequencyrepresentationsdealswiththeanalysisofthesignalissuedfromnaturalenvironment.Recently,theinterestforpassiveunderwatercontextincreased,basicallyduetotherichinformationcarriedoutbythenaturalsignals.Takenintoaccountthenon-linearmulti-componenttime–frequencybehaviourofsuchsignals,theiranalysisisachallengingproblem.

Inthiscontext,theanalysisofunderwatermammal’swhistlesisaimedtoextract,accuratelyandadaptively,theirmaintime–frequencycomponents.Inthispaper,wedefineatime–frequency-phasetrackerwhichiscomposedofthreesteps.Thefirstoneconsistsofmodellingtheshort-timesegmentsofthevocalizationbyasetofthirdorderpolynomialphasemodulations.Thesecondstepconsistsinthefusionoflocalpolynomialphasemodulationsaccordingtoalocalphasecontinuitycriterion.Finally,inthethirdstep,thedetectedtime–frequencytrackisusedtodesignthetime–frequencyfilter,inchargeofextractingthesamplescorrespondingtothedetectedtrack.Thisprocedureistheniterateduntilallcomponentofinterestareextracted.

TestsprovidedforrealisticscenariosandrealdatatakeninBayofBiscayatSeptember2009containingwhistlesofcommondolphinDelphinusdelphisillustratethepotentialandthebenefitsoftheproposedapproach.

ArticleOutline

1.Introduction

2.Time–frequency-phasetracker

2.1.Step1:

shorttimeanalysis

2.2.Step2:

selectionandfusion

2.3.Step3:

componentextraction

3.Resultsonrealdata

4.Conclusion

Acknowledgements

References

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Optimizationofpressbendformingpathofaircraftintegralpanel  OriginalResearchArticle

TransactionsofNonferrousMetalsSocietyofChina,Volume20,Issue2,February2010,Pages294-301

YuYAN,MinWAN,Hai-boWANG,LinHUANG

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Abstract

Inordertodesignthepressbendformingpathofaircraftintegralpanels,anoveloptimizationmethodwasproposed,whichintegratesFEMequivalentmodelbasedonpreviousstudy,theartificialneuralnetworkresponsesurface,andthegeneticalgorithm.First,amulti-steppressbendformingFEMequivalentmodelwasestablished,withwhichtheFEMexperimentsdesignedwithTaguchimethodwereperformed.Then,theBPneuralnetworkresponsesurfacewasdevelopedwiththesampledatafromtheFEMexperiments.Furthermore,geneticalgorithmwasappliedwiththeneuralnetworkresponsesurfaceastheobjectivefunction.Finally,verificationwascarriedoutonasimplecurvaturegrid-typestiffenedpanel.Theformingerrorofthepanelformedwiththeoptimalpathisonly0.09839andthecalculatingefficiencyhasbeenimprovedby77%.Therefore,thisnoveloptimizationmethodisquiteefficientandindispensableforthepressbendformingpathdesigning.

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Erratumto“Failureanalysisofbrazedairpassagesofanaircraftfuelsystem[EngineeringFailureAnalysis,Volume17,Issue6,September2010,Pages1495–1499]”  

EngineeringFailureAnalysis,Volume18,Issue1,January2011,Page531

A.R.Etemadi,P.Behjati,H.R.MadaahHosseini,A.H.Kokabi

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AbstractAbstract

Abstract

Airpassagesofanaircraftfuelsystemaremanufacturedfrom4130steeltubesbrazedusingBNi-4fillermetal.Itwasobservedthatbrazedtubesleakafterflyingabout100 h.Inthiscasestudy,microscopytechniquesandhardnessmeasurementswereemployedtoidentifytherootcauseofthisfailure.Itwasfoundthatwidejointclearancepromotesbrittlephasesatthejointcenterlinewhichcanactascracknucleationsitesunderthermalexpansionandmisalignmentstresses.Basedontheobtainedresults,jointclearancewasreducedtooptimumvalue.Thisreductionprohibitedtheoccurrenceofleakageandsolvedtheproblem.

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Decorrelatingwirelesssensornetworktraffictoinhibittrafficanalysisattacks  OriginalResearchArticle

PervasiveandMobileComputing,Volume2,Issue2,April2006,Pages159-186

JingDeng,RichardHan,ShivakantMishra

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Abstract

Typicalpackettrafficinasensornetworkrevealspronouncedpatternsthatallowanadversaryanalyzingpackettraffictodeducethelocationofabasestation.Oncediscovered,thebasestationcanbedestroyed,renderingtheentiresensornetworkinoperative,sinceabasestationisacentralpointofdatacollectionandhencefailure.Thispaperinvestigatesasuiteofdecorrelationcountermeasuresaimedatdisguisingthelocationofabasestationagainsttrafficanalysisattacks.Asetofbasiccountermeasuresisdescribed,includinghop-by-hopreencryptionofthepackettochangeitsappearance,impositionofauniformpacketsendingrate,andremovalofcorrelationbetweenapacket’sreceipttimeanditsforwardingtime.Moresophisticatedcountermeasuresaredescribedthatintroducerandomnessintothepathtakenbyapacket.Packetsmayalsoforkintomultiplefakepathstofurtherconfuseanadversary.Atechniqueisintroducedtocreatemultiplerandomareasofhighcommunicationactivitycalledhotspotstodeceiveanadversaryastothetruelocationofthebasestation.Theeffectivenessofthesecountermeasuresagainsttrafficanalysisattacksisdemonstratedanalyticallyandviasimulationusingthreeevaluationcriteria:

totalentropyofthenetwork,totaloverhead/energyconsumed,andtheabilitytofrustrateheuristic-basedsearchtechniquestolocateabasestation.

ArticleOutline

1.Introduction

2.Networktrafficandthreatmodel

3.Basicdecorrelationcountermeasures

3.1.Hiddenpacketdestinationaddress

3.2.Decorrelatingpacketsendingtimes

3.3.Controllingpacketsendingrates

3.4.Limitations

4.Inhibitingtrafficanalysisattackswithrandomizedtraffic

4.1.Multi-parentroutingscheme

4.2.Randomwalk

4.3.Fractalpropagation

4.3.1.Fractalpropagationwithdifferentforkingprobabilities

4.3.2.Enforcedfractalpropagation

4.4.Nodecompromises

4.5.Simulationresultsandsummary

5.Evaluation

5.1.Evaluationcriteria

5.2.Messageoverheadofratecontrolmechanism

5.3.Effectivenessandcostofrandomizedtraffictechniques

5.4.Effectivenessofprandpf

6.Relatedwork

7.Futurework

8.Conclusion

Acknowledgements

References

Vitae

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