universal mobile telecommunications system networks.docx
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universal mobile telecommunications system networks.docx
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universalmobiletelecommunicationssystemnetworks
CDMAmobilecommunicationsystembasedonrepeaterequipment OriginalResearchArticle
TheJournalofChinaUniversitiesofPostsandTelecommunications
multipleaccessschemeusingspatialandwaveformsignatures OriginalResearchArticle
SignalProcessing
Caractérisationdel’activitécérébraleauditiverecueillieenchampélectromagnétiqueémispardestéléphonesportablesCharacterizationofauditorycerebralactivityrecordedunderelectromagneticfieldinducedbymobilephones OriginalResearchArticle
ITBM-RBM
Cetarticletraitedel’influencedeschampsradio-électriquesémisparlestéléphonesportablessurl’activitécérébralehumaine.Notretravailestréalisésurlesystèmeauditifàpartirdurecueildepotentielsévoquésauditifs(PEA)àlasurfaceduscalpdesujetssainsetdepatientsépileptiques.LeprotocolepermetdecomparerlesPEAenregistrésavecousansexpositionauxradiofréquences.Lesstimulisontdeuxsonspursetunsimulateurdecommunicationpermetdecontrôlerlapuissancedesradiofréquencesémises.Pourobteniruneréférenceettenircompteduphénomèned’accoutumance,uneexpériencefictivesansémissionderadiofréquences,diteséanceplacebo,estégalementconsidérée.Notreétudeconsisteàmettreenœuvredesmesuresfiablesquisoientrévélatricesdecertainschangementsoudecertainesconstancesdanslessignauxenregistrés.Ellessontfondéessurlesamplitudesetleslatencesdel’ondeN100,lescoefficientsdecorrélationcalculésentresignauxmoyens,ainsiqueceuxcalculésentrelesspectresdecessignaux.Lesmesuresproposéesetfondéessurlesparamètresprécédentsprennentencomptelephénomèned’accoutumance.Lesvariationsdesamplitudesetdeslatencesdel’ondeN100mettentenévidenceundysfonctionnementcognitifattribuableauxradiofréquences.Unediminutiondeslatenceschezlessujetssainspeutêtredueàunemeilleuresynchronisationneuronaleouàuneffetthermique.Chezlespatientsépileptiques,unallongementdeceslatencespeutêtreimputableàunealtérationdelavoieafférente.Unedifférenceentrelescoefficientsdecorrélationcalculésentresignauxainsiqu’unedifférenceentrelescoefficientsdecorrélationcalculésentrelesspectresdessignauxplaceboetexpérimentauxtraduisentuneffetdesradiofréquencesquiinduitunedésorganisationneuronaledontl’incidenceréellesurl’activitécérébralen’estpasprouvée.
Abstract
Thispaperdealswiththestudyoftheinfluenceofradiofrequencyfieldsemittedbymobilephonesonhumancerebralactivity.Ourworkiscarriedoutontheauditorysystemusingauditoryevokedpotentials(AEPs)recordedonthescalpofhealthyhumansandepilepticpatients.TheprotocolallowstocomparetheAEPsrecordedwithorwithoutexposure.Thestimuliaretwopuretonesandacommunicationsimulatorthatallowstocontrolthepowerofradiofrequencyfields.Togetareferenceandtotakeintoaccountthehabituation,afictitiousexperimentwithoutradiofrequencyemission,namedplacebo,isalsoconsidered.Inthispaper,somemeasuresareinvestigatedtodetectapossibledifferenceduetoradiofrequencyfields.TheyconcerntheamplitudesandthelatenciesoftheN100wave,thecorrelationcoefficientscomputedbetweenaveragedsignals,aswellasthecorrelationcoefficientsbetweenspectraofaveragedAEPs.Theproposedmeasuresarebasedonthepreviousparameterstakingintoaccountthehabituation.TheN100amplitudesandlatencyvariationsunderlineacognitivedysfunctionattributabletoradiofrequencies.Forthehealthysubjects,thelatencydiminutionisduetoabetterneuronalsynchronizationorathermaleffect.Fortheepilepticpatients,thelatencyextensioncanbecausedbyanafferenttractalteration.Adifferenceinthecorrelationcoefficientscomputedbetweensignalsaswellasthatinthecorrelationcoefficientscalculatedbetweenthespectraoftheplaceboandexperimentalsignalsshowsaneffectoftheradiofrequencieswhichinducesaneuronaldisorganizationwhoserealincidenceonthecerebralactivityisnotproved.
ArticleOutline
1.Introduction
2.Protocole
3.Méthode
3.1.FiltragedesPEA
3.2.Sélectiondesélectrodes
3.3.Paramètresétudiés
3.3.1.Amplitudedel’ondeN100
3.3.2.Latencedel’ondeN100
3.3.3.CoefficientsdecorrélationentrePEA
3.3.4.Coefficientsdecorrélationentrespectres
3.4.Méthodologie
4.Résultats
4.1.VariationsdesamplitudesΔAmpN100MAX–OFF
4.1.1.Sujetssains
4.1.2.Patientsépileptiques
4.2.VariationsdeslatencesΔLatN100MAX–OFF
4.2.1.Sujetssains
4.2.2.Patientsépileptiques
4.3.CoefficientsdecorrélationentrePEA
4.3.1.Sujetssains
4.3.2.Patientsépileptiques
4.4.Coefficientsdecorrélationentrespectres
4.4.1.Sujetssains
4.4.2.Patientsépileptiques
5.Discussion
6.Conclusions
Remerciements
Annexe1.TestsignédeWilcoxon
Bibliographie
GSM900 MHzelectromagneticfieldsaffectscerebralcytochromecoxidaseactivity
Toxicology
VBRtrafficinbroadbandwirelesslocalcommunication OriginalResearchArticle
ComputerCommunications
multi-criteriadecisionmakingapproachtoevaluatemobilephonealternatives OriginalResearchArticle
ComputerStandards&Interfaces
RadiofrequencychannelmodelingforproximitynetworksontheMartiansurface OriginalResearchArticle
ComputerNetworks
NeXtgeneration/dynamicspectrumaccess/cognitiveradiowirelessnetworks:
Asurvey OriginalResearchArticle
ComputerNetworks
Today’swirelessnetworksarecharacterizedbyafixedspectrumassignmentpolicy.However,alargeportionoftheassignedspectrumisusedsporadicallyandgeographicalvariationsintheutilizationofassignedspectrumrangesfrom15%to85%withahighvarianceintime.Thelimitedavailablespectrumandtheinefficiencyinthespectrumusagenecessitateanewcommunicationparadigmtoexploittheexistingwirelessspectrumopportunistically.ThisnewnetworkingparadigmisreferredtoasNeXtGeneration(xG)NetworksaswellasDynamicSpectrumAccess(DSA)andcognitiveradionetworks.ThetermxGnetworksisusedthroughoutthepaper.ThenovelfunctionalitiesandcurrentresearchchallengesofthexGnetworksareexplainedindetail.Morespecifically,abriefoverviewofthecognitiveradiotechnologyisprovidedandthexGnetworkarchitectureisintroduced.Moreover,thexGnetworkfunctionssuchasspectrummanagement,spectrummobilityandspectrumsharingareexplainedindetail.Theinfluenceofthesefunctionsontheperformanceoftheupperlayerprotocolssuchasroutingandtransportareinvestigatedandopenresearchissuesintheseareasarealsooutlined.Finally,thecross-layerdesignchallengesinxGnetworksarediscussed.
ArticleOutline
1.Introduction
2.Cognitiveradio
2.1.Physicalarchitectureofthecognitiveradio
2.2.Cognitivecapability
2.3.Reconfigurability
3.ThexGnetworkarchitecture
3.1.xGnetworkfunctions
3.1.1.xGnetworkonlicensedband
3.1.2.xGnetworkonunlicensedband
3.2.xGnetworkapplications
3.3.Existingarchitectures
4.Spectrumsensing
4.1.Transmitterdetection(non-cooperativedetection)
4.1.1.Matchedfilterdetection
4.1.2.Energydetection
4.1.3.Cyclostationaryfeaturedetection
4.2.Cooperativedetection
4.3.Interference-baseddetection
4.4.Spectrumsensingchallenges
5.Spectrummanagement
5.1.Spectrumanalysis
5.2.Spectrumdecision
5.3.Spectrummanagementchallenges
6.Spectrummobility
6.1.Spectrumhandoff
6.2.SpectrummobilitychallengesinxGnetworks
7.Spectrumsharing
7.1.Overviewofspectrumsharingtechniques
7.2.Inter-networkspectrumsharing
7.2.1.Centralizedinter-networkspectrumsharing
7.2.2.Distributedinter-networkspectrumsharing
7.3.Intra-networkspectrumsharing
7.3.1.Cooperativeintra-networkspectrumsharing
7.3.2.Non-cooperativeintra-networkspectrumsharing
7.4.Spectrumsharingchallenges
7.4.1.Commoncontrolchannel(CCC)
7.4.2.Dynamicradiorange
7.4.3.Spectrumunit
8.Upperlayerissues
8.1.Routingchallenges
8.2.Transportlayerchallenges
9.Cross-layerdesign
9.1.Cross-layerchallengesinspectrummanagement
9.2.Cross-layerchallengesinspectrumhandoff
9.3.Cross-layerchallengesinspectrumsharing
9.4.Cross-layerchallengesinupperlayers
10.Conclusions
References
Vitae
Managementofused&end-of-lifemobilephonesinKorea:
Areview ReviewArticle
Resources,ConservationandRecycling
Cognitivefeedbackhasbeenknowntobeusefulinprovidingdecisionmakerswithinsightsforenhancementofthemodelingprocess.Thispaperproposesadesignmethodologytoembedfunctionalitiesthatintegratecognitivefeedbackinacomputer-baseddecisionsupportenvironment.Fromasystemdynamicsperspective,thispaperproposesfivetypesofinformationcuescapableofprovidingcognitivefeedbacksupportattheindividual,interpersonalandcollectivelevels.DSStoolsarealsoidentifiedtodelivertheseinformationcuestotheusers.Theproposedapproachhasbeensuccessfullyappliedintheconstructionofadecisionmodelusingsystemdynamicstoforecastthedemandforcellulartelecommunicationsuptotheyear2005forVietnam.Lessonslearnedfromourmodelsuggestthatcognitivefeedbackisanappropriateapproachtobuildingacomputer-basedcognitiveaid.
networkforprecisionviticulture:
TheNAVsystem OriginalResearchArticle
ComputersandElectronicsinAgriculture
Forreal-timewirelesscommunicationinindustrialcontrol,surveillanceandinventorytracking,weproposeRT-Link,atime-synchronizedlinkprotocol.RT-Linkprovidespredictablelifetimeforbattery-operatedembeddednodes,boundedend-to-enddelayacrossmultiplehops,andcollision-freeopera
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