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ASSIGNMENT 2 :PROUDLY MALAYSIAN ART AND DESIGN NEW MALAYA / MALAYSIA – VISIT MALAYA POSTER 1930 – 1961 by Teh Jia Ying BDC 1134 Historical past of Artwork and Design Ms. Fiona Wong Sunway College Bandar Sunway , Subang Jaya , Selangor , Malaysia 31 Might 2019 Desk of Contents 1.zero Introduction …………………………………………………………………… three 1.1 […]

Kennywood We have a tendency to seek out that all of us have a objective for which we work. It’s human nature. We have a look at what others have and select that as our subsequent accomplishment. That is simply what people do. The method is rarely questioned. Most be taught this early on in […]

Most stories in mythology stay away from dark or supernatural powers. “The demonic wizards and the hideous outdated witches who haunted Europe and America, too, as much as fairly latest years, play no half in any respect in the stories.” The concepts of dark arts, if you’ll, didn’t peak the pursuits of early audiences having […]

• • • C arrie rs :- A p ath ogen in fe cte d p ers o n p osse ssin g s p eci? c in fe ctio us a gent s h ow in g n o o r m ild s ym pto m s o f c lin ic a […]

Metacognitive Studying Report # four Trainee: NANTES, CARELLE SAMANTHA S.Date: March 17, 2019 Understanding the Self/ Pag-unawa sa Sarili G E N E R A L I N S T R U C T I O N S BEFORE COMPLETING THIS ASSESSMENT, PLEASE READ ALL OF THE INSTRUCTIONS THOROUGHLY AND CAREFULLY. FOLLOW THE INSTRUCTIONS. RESPOND […]

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Psychology is the examine of the human thoughts and its habits. In psychology nurture is the issues/skills that one learns and is taught. Good and evil are two examples of what human nature can do to evolve a human. In Lord of the Flies by William Golding a gaggle of boys get stranded in an […]

LITERATURETSURVEY 1.I.TF.TAkyildizTandTI.TH.TKasimoglu,T“WirelessTsensorTandTactorTnetworks:TresearchTchallenges,”TAdTHocTNetworks. WirelessTsensorTandTactorTnetworksT(WSANs)TreferTtoTaTgroupTofTsensorsTandTactorsTlinkedTbyTwirelessTmediumTtoTperformTdistributedTsensingTandTactingTtasks.TTheTrealizationTofTwirelessTsensorTandTactorTnetworksT(WSANs)TneedsTtoTsatisfyTtheTrequirementsTintroducedTbyTtheTcoexistenceTofTsensorsTandTactors.TInTWSANs,TsensorsTgatherTinformationTaboutTtheTphysicalTworld,TwhileTactorsTtakeTdecisionsTandTthenTperformTappropriateTactionsTuponTtheTenvironment,TwhichTallowsTaTuserTtoTeffectivelyTsenseTandTactTfromTaTdistance.TInTorderTtoTprovideTeffectiveTsensingTandTacting,TcoordinationTmechanismsTareTrequiredTamongTsensorsTandTactors.TMoreover,TtoTperformTrightTandTtimelyTactions,TsensorTdataTmustTbeTvalidTatTtheTtimeTofTacting.TThisTpaperTexploresTsensor-actorTandTactor-actorTsynchronizationTandTdescribesTresearchTchallengeTforTcoordinationTandTcommunicationTproblems. 2.Y.TAkkaya,TKemalTandTMohamed,T“CoverageTandTlatencyTawareTactorTplacementTmechanismsTinTwsans,”TInternationalTJournalTofTSensorTNetworks. InTWirelessTSensorTandTActorTNetworksT(WSANs),TresponsivenessTtoTseriousTeventsTisTofTutmostTimportanceTandTthus,TminimalTlatencyTshouldTbeTexperienced.TInTaddition,TsinceTtheseTactionsTcanTbeTtakenTatTanyTspotTwithinTtheTmonitoredTarea,TtheTactorsTshouldTprovideTmaximalTcoverageTofTtheTarea.TInTthisTpaper,TweTproposeTtwoTactorTplacementTmechanismsTforTWSANs,TnamelyTCOLATandTCOCOLATthatTconsiderTbothTtheTdelayTrequirementsTofTdataTcollectionTandTtheTcoverageTofTtheTarea.TCOLATevenlyTdistributesTtheTactorsTinTtheTregionTforTmaximisedTcoverageTfirst.TActorsTthenTcollaborativelyTformTclusters.TEachTindividualTactorTrepositionsTitselfTatTaTnewTlocationTthatTenablesTminimalTlatencyTinTcollectingTdataTinTitsTcluster.TCOCOLATisTanTextensionTtoTCOLATwhichTadditionallyTenforcesTconnectivityTamongTtheTactorsTbyTassigningTappropriateTlocationsTtoTeachTactorTforTimprovedTcoverageTandTreducedTlatency.TTheTeffectivenessTofTbothTapproachesTisTevaluatedTthroughTextensiveTsimulationTexperiments. three.S.TG.TA,TH.TBozyigit,TandTF.TB.,T“Cluster-basedTcoordinationTandTroutingTframeworkTforTwirelessTsensorTandTactorTnetworks,”TWirelessTCommunicationsTandTMobileTComputing. InTWirelessTSensorTActorTNetworksT(WSAN),TsensorTnodesTperformTtheTsensingTtaskTandTactorTnodesTtakeTactionTbasedTonTtheTsensedTphenomena.TGenerally,TtheTnetworkTisTconfiguredTtoTobserveTmultipleTeventsTandTtoTreactTuponTeachTindividualTeventTaccordingly.TTimeTdelay,TenergyTefficiencyTandTreliabilityTareTthreeTimportantTaspectsTofTWSANTthatTrequireTspecialTattention.TToTensureTefficientTandTreliableToperationsTofTsuchTheterogeneousTWSAN,TnewTcommunicationTprotocolsTareTimperative. InTthisTpaper,TweTproposeTanTintegratedTcluster?basedTcoordinationTandTroutingT(CCR)TframeworkTforTWSAN,TwhoseTprimeTobjectiveTisTtoTensureTreliableTactionTwithTefficientTenergyTconsumption.TInTCCR,TsensorTnodesTareTfirstTconfiguredTtoTformTclustersTbyTtakingTintoTaccountTtheTresidualTenergyTofTnodesTandTnetworkTdensity.TOnceTtheTclustersTareTformed,Tcluster?headsTcoordinateTwithTtheTactorsTtoTformTinteractiveTregions.TTheTreliabilityTofTactionTisTaddressedTinTtermsTofTinTtimeTdataTdeliveryTtoTactorsTinTinteractiveTregionsTandTactor–actorTcoordinationTtoTmakeTsureTthatTanTactorTperformTactionTinTtheTreportedTregion.TATnovelTreal?timeTdataTaggregationT(RDA)TapproachTisTalsoTincorporatedTinTtheTframeworkTtoTconserveTenergyTbyTminimizingTtheTnumberTofTtransmissionsTandTachieveTfairness. four.F.-H.TTseng,TL.-D.TChou,TandTH.-C.TChao,T“ATsurveyTofTblackTholeTattacksTinTwirelessTmobileTadThocTnetworks,”THumanTcentricTComputingTandTInformationTSciences TheTblackTholeTattackTisToneTofTtheTwell-knownTsecurityTthreatsTinTwirelessTmobileTadThocTnetworks.TTheTintrudersTutilizeTtheTloopholeTtoTcarryToutTtheirTmaliciousTbehaviorsTbecauseTtheTrouteTdiscoveryTprocessTisTnecessaryTandTinevitable.TManyTresearchersThaveTconductedTdifferentTdetectionTtechniquesTtoTproposeTdifferentTtypesTofTdetectionTschemes.TInTthisTpaper,TweTsurveyTtheTexistingTsolutionsTandTdiscussTtheTstate-of-the-artTroutingTmethods.TWeTnotTonlyTclassifyTtheseTproposalsTintoTsingleTblackTholeTattackTandTcollaborativeTblackTholeTattackTbutTalsoTanalyzeTtheTcategoriesTofTtheseTsolutionsTandTprovideTaTcomparisonTtable.TWeTexpectTtoTfurnishTmoreTresearchersTwithTaTdetailedTworkTinTanticipation. 5.L.TK.TBysaniTandTA.TK.TTuruk,T“ATsurveyTonTselectiveTforwardingTattackTinTwirelessTsensorTnetworks,”TinTInternationalTConferenceTonTDevicesTandTCommunications. WirelessTSensorTNetwork(WSN)TisTbeingTemergedTasTaTprevailingTtechnologyTinTfutureTdueTtoTitsTwideTrangeTofTapplicationsTinTmilitaryTandTcivilianTdomains.TTheseTnetworksTareTeasilyTproneTtoTsecurityTattacks,TsinceTonceTdeployedTtheseTnetworksTareTunattendedTandTunprotected.TSomeTofTtheTinherentTfeaturesTlikeTlimitedTbatteryTandTlowTmemoryTmakesTsensorTnetworksTinfeasibleTtoTuseTconventionalTsecurityTsolutions,TwhichTneedsTcomplexTcomputationsTandThighTmemory.TThereTareTlotTofTattacksTonTtheseTnetworksTwhichTcanTbeTclassifiedTasTroutingTattacksTandTdataTtrafficTattacks.TSomeTofTtheTdataTattacksTinTsensorTnodesTareTwormhole,TblackTholeTandTselectiveTforwardingTattack.TInTaTblackTholeTattack,TcompromisedTnodeTdropsTallTtheTpacketsTforwardingTthroughTit.TATspecialTcaseTofTblackTholeTattackTisTselectiveTforwardingTattack,TwhereTcompromisedTnodeTdropsTpacketsTselectively,TwhichTmayTdeteriorateTtheTnetworkTefficiency.TInTthisTpaper,TweTdiscussedTaboutTselectiveTforwardingTattackTandTsomeTofTtheTmitigationTschemesTtoTdefendTthisTattack. 6.Z.TKarakehayov,T“UsingTrewardTtoTdetectTteamTblack-holeTattacksTinTwirelessTsensorTnetworks,”TWksp.TReal-WorldTWirelessTSensorTNetworks. WirelessTsensorTnetworksTconsistTofTautonomous,Tself-organizing,Tlow-powerTnodesTwhichTcollaborativelyTmeasureTdataTinTanTenvironmentTandTcooperateTtoTrouteTthisTdataTtoTitsTintendedTdestination.TBlackTholeTattacksTareTpotentiallyTdevastatingTattacksTonTwirelessTsensorTnetworksTinTwhichTaTmaliciousTnodeTusesTspuriousTrouteTupdatesTtoTattractTnetworkTtrafficTthatTitTthenTdrops.TWeTproposeTaTrobustTandTflexibleTattackTdetectionTschemeTthatTusesTaTwatchdogTmechanismTandTlightweightTexpertTsystemTonTeachTnodeTtoTdetectTanomaliesTinTtheTbehaviourTofTneighbouringTnodes.TUsingTthisTscheme,TevenTifTmaliciousTnodesTareTinsertedTintoTtheTnetwork,TgoodTnodesTwillTbeTableTtoTidentifyTthemTbasedTonTtheirTbehaviourTasTinferredTfromTtheirTnetworkTtraffic.TWeTexamineTtheTresource-preservingTmechanismsTofTourTsystemTusingTsimulationsTandTdemonstrateTthatTweTcanTallowTgroupsTofTnodesTtoTcollectivelyTevaluateTnetworkTtrafficTandTidentifyTattacksTwhileTrespectingTtheTlimitedThardwareTresourcesT(processing,TmemoryTandTstorage)TthatTareTtypicallyTavailableTonTwirelessTsensorTnetworkTnodes.

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