Effects of the upper atmosphere on terrestrial and Earthspace communications Final results of the文档格式.docx

Effects of the upper atmosphere on terrestrial and Earthspace communications Final results of the文档格式.docx

《Effects of the upper atmosphere on terrestrial and Earthspace communications Final results of the文档格式.docx》由会员分享，可在线阅读，更多相关《Effects of the upper atmosphere on terrestrial and Earthspace communications Final results of the文档格式.docx（27页珍藏版）》请在冰豆网上搜索。

Relatedarticles 

Relatedreferenceworkarticles 

Purchase

$31.50

327

TransformdomaintechniqueforwindowingtheDCTandDST 

JournaloftheFranklinInstitute,Volume339,Issue1,January2002,Pages111-120

B.G.Sherlock,Y.P.Kakad

328

EffectsoftheupperatmosphereonterrestrialandEarth–spacecommunications:

FinalresultsoftheEUCOST271Action 

AdvancesinSpaceResearch,Volume37,Issue6,2006,Pages1223-1228

B.Zolesi,Lj.R.Cander

Closepreview 

AbstractAbstract|Figures/TablesFigures/Tables|ReferencesReferences

Abstract

Project“EffectsoftheUpperAtmosphereonTerrestrialandEarth–SpaceCommunications（EACOSs）”wasinauguratedasafour-year271ActionintheTelecommunicationsandInformationScienceandTechnologydomainoftheEUCOST（Co-operationintheFieldofScientificandTechnicalResearch）inOctober2000.ItfollowedtwoprevioussuccessfulActionsCOST238onPRIME（PredictionandRetrospectiveIonosphericModellingoverEurope）andCOST251onIITS（ImprovedQualityofServiceinIonosphericTelecommunicationSystemsPlanningandOperation）.TheCOST271Action（EACOS）hasbeenorientedtowards:

（i）collectionofnewionosphericandplasmasphericdatafornow-castingandforecastingpurposes,（ii）developmentofmethodsandalgorithmstopredictandtominimisetheeffectsofplasmaspheric–ionosphericperturbationsandvariationsoncommunications;

（iii）performstudiesthatinfluencethetechnicaldevelopmentandtheimplementationofnewcommunicationservices,particularlyfortheGNSSandotheradvancedEarth–spaceandsatellite-to-satelliteapplications;

and（iv）disseminationandcorrelationofresults,ideasandinformationwhichwillprovideavaluablesupporttoEuropeanresearchcentresandindustry.

ThispaperreviewsthemainresultsachievedintheCOST271Actionconcerninginparticulararangeoftheionosphericspaceweatherissues,specifically:

now-casting,forecastingandwarningtools,methodsandsupportingdatabasesforionosphericpropagationprediction;

totalelectroncontentvariationsandtheiruseinthereconstructionofplasmaspheric–ionosphericstructuresasakeyparameterfornavigationerrorinGNSSapplicationsandeffectsofplanetaryandgravitywavesandgradientsoftheelectrondensityonterrestrialandsatellitecommunications.

ArticleOutline

1.Introduction

2.MainresultsofCOST271Action

3.MIERS:

mitigationofionosphericeffectsonradiosystems

4.Conclusions

References

329

Asimulationmodelofgearskiving 

JournalofMaterialsProcessingTechnology,Volume146,Issue2,28February2004,Pages213-220

A.Antoniadis,N.Vidakis,N.Bilalis

Thekeycomponentsindemandingtransmissionchainsaredoubtlesslypremiumwelldesignedandproperlyfabricatedgears.Thedesiredgearqualityisperformed,throughthreemanufacturingstages,i.e.theroughcutting,theheattreatmentandthefinishingprocess.Oneofthemostadoptedmethodsingearfinishingisavariationofhobbing,theso-calledgearskivingorhardhobbing.Aseverycuttingprocessbasedontherollingprinciple,gearskivingisanexceptionalmultiparametricandcomplicatedmethod,whichcanandmustbefullyoptimized.Thispaperillustratesaninvolvedalgorithmthatsimulatesrigorouslytheskivingprocessandyieldsdata,suchasthedimensionsofthenon-deformedchipsandconsequentlythecuttingforcecomponents.Thisalgorithmissupportedbyacomputercodethatofferstheaforementionedparameters,withtheaidofauser-friendlygraphicalinterface,builtmodularandobjectoriented.Bearinginmindthatgearskivingisafinishinggearcuttingprocess,thedevelopedsoftwareinitiallyperformsthesimulationofthegearcutting,inordertodeterminethecuttingboundaryconditions.Theaimofthisresearchworkistointerpretquantitativelycuttingphenomenarelatedtothecourseofthecuttingforcecomponentsandisextendabletopredictthewearprogressofcomplexandexpensivecuttingtools.Inthisway,theoptimizationofthecuttingprocessisenabled.

2.Gearskivingfeaturesandsimulationstrategy

3.Determinationofthechipdimensionswiththeaidofhardcutprofiles

4.Coordinatesystems

5.Determinationofchipformationingearskiving

6.Cuttingforcecomponentsdeterminationandcomparisonbetweenanalyticalandexperimentalresults

7.Conclusions

$37.95

330

Open-hardwaree-puckLinuxextensionboardforexperimentalswarmroboticsresearch 

MicroprocessorsandMicrosystems,Volume35,Issue1,February2011,Pages60-67

WenguoLiu,AlanF.T.Winfield

InthispaperwedescribetheimplementationofaLinuxextensionboardforthee-puckeducationalmobilerobot,designedtoenhancethecomputation,memoryandnetworkingperformanceoftherobotatverylowcost.Theextensionboardisbasedona32-bitARM9microprocessorandprovideswirelessnetworksupport.TheARM9extensionboardrunsinparallelwiththedsPICmicroprocessoronthee-puckmotherboardwithcommunicationbetweenthetwoviaanSPIbus.Theextensionboardisdesignedtohandlecomputationallyintensiveimageprocessing,wirelesscommunicationandhigh-levelintelligentrobotcontrolalgorithms,whilethedsPIChandleslow-levelsensorinterfacing,dataprocessingandmotorcontrol.TheextensionboardrunsanembeddedLinuxoperatingsystem,alongwithaDebian-basedportoftherootfilesystemstoredinaMicroSDcard.Theextendede-puckrobotplatformrequiresminimalefforttointegratethewell-knownopen-sourcerobotcontrolframeworkPlayerand,whenplacedwithinaTCP/IPnetworkedinfrastructure,providesapowerfulandflexibleplatformforexperimentalswarmroboticsresearch.

2.Hardware

2.1.Microcontrollerunit

2.2.Memory

2.3.Low-leveldebugginginterfaces

3.Linuxoperatingsystem

3.1.Bootsequence

3.2.Rootfilesystem

3.3.Devicedrivers

4.Softwareinterfaces

4.1.SPIcommunicationprotocolsconsideration

4.2.Robotprogrammer’sAPI

4.3.Playerserversupport

5.Implementation,evaluationandinfrastructure

5.1.Performanceevaluationandlimitations

5.2.Swarmroboticsinfrastructure

6.Opensourcematerials

Acknowledgements

Vitae

$35.95

331

MissingdataanalysiswithfuzzyC-Means:

Astudyofitsapplicationinapsychologicalscenario 

ExpertSystemswithApplications,Volume38,Issue6,June2011,Pages6793-6797

AlessandroG.DiNuovo

Inscientificresearch,andparticularlyinpsychologicalstudies,dataforsomevariablesinthedatabasetobeanalyzedmaywellbemissing.Ifnotdealtwithinthecorrectway,themissingvaluesmayweakenorevencompromisethevalidityofresearchintothedatabase,especiallyifitisasmallone.Inthispaperweintroducethemostcommonsolutionstothisproblemofferedbythemostpopularstatisticalsoftwareandatechniquebasedonthemostfamousfuzzyclusteringalgorithm:

FuzzyC-Means（FCM）.Thenwecomparethesemethodologiesinordertohighlightthepeculiarcharacteristicsofeachsolution.Thecomparisonwasmadeinapsychologicalresearchenvironment,usingadatabaseofin-patientswhohaveadiagnosisofmentalretardation.Theresultsdemonstratethatcompletiontechniques,andinparticulartheonebasedonFCM,leadtoeffectivedataimputation,avoidingthedeletionofelementswithmissingdata,whichdiminishesthepoweroftheresearch.

2.Methodsformissingdataanalysis

3.MissingdataimputationwithFCM

4.Empiricalresults

4.1.Thedatabase

4.2.Accuracycomparisonofmissingdataimputationtechniques

4.3.FCM-OCSapplication:

apoweranalysis

5.Conclusion

$41.95

Researchhighlights

►Missingdatamustbehandledincorrectwayinordertodonotcomprimisethevalidityofresearch.►Completationtechniquescanleadtoeffectivedataimputationinordertopreservethepoweroftheresearchresults.►ComparisonresultsinapsychologicalscenariodemonstratethatextentionstoFuzzyC-Meansclusteringcanaccuratelycompletedatasetswithmissingvalues.

332

ParLeS:

Softwareforchemometricanalysisofspectroscopicdata 

ChemometricsandIntelligentLaboratorySystems,Volume90,Issue1,15January2008,Pages72-83

RaphaelA.ViscarraRossel

Relatedrefer