简介:Withtherapiddevelopmentofsiliconchiptech-nology,web-basedinstruction(WBI)andcomputer-izedadaptivetesting(CAT)willbethenewtrendsinthefieldoflanguageteachingandtesting.Weassumethatonlywhenteachingandtestingsharethesameviewaboutthenatureoflanguageandlanguagelearn-ingcantestingexerciseabeneficialbackwasheffectonteaching.However,WBIandCATprovetobebasedonoppositetheoriesoflanguageandlanguagelearn-ing.WhileWBIbelievesinconstructivism,CATcor-respondstostructuralismandbehaviorism.Thissitu-ationplaceslanguagetestersinadilemma,foriftheyfollowthetrend,testingwillgoagainstteaching.ButiftheygiveupCAT,itisverydifficulttosubstituteanothertestingsystempossessingsomanyadvantages.ThispaperillustratesindetailwhyWBIandCATaretobecomethenewtrendsinteachingandtesting,ex-plainsclearlythediscrepancybetweenWBIandCATintheoryandtheirobjectivesandfinallyattemptstoprovideasolutiontohelpthelanguagetestersoutofthedilemma.
简介:Studiedarethecontrollerdesignandbasicprinciplesofintelligentlightingnetwork.TI’sMSP430F123isusedasamaincontroller.ByusingtheZigBeemodules(Xbee/Xbee-PRO)andtheGSMmodule(SIM300C)forwirelesscommunications,thelightingcontrolisenabledtoaccesswirelessnetwork.Thissystemusesamobilephonetoachievelighton-offdirectly,whichcanaccomplishwirelesscontrolofintelligentlightinginfamilies.
简介:Basedoncurrentresearchonapplicationsofchaoticneuronnetworkforinformationprocessing,thestabilityandconvergenceofchaoticneuronnetworkareprovedfromtheviewpointofenergyfunction.Moreover,anewauto-associativematrixisdevisedforartificialneuralnetworkcomposedofchaoticneurons,thus,animprovedchaoticneuronnetworkforassociativememoryisbuiltup.Finally,theassociativerecallingprocessofthenetworkisanalyzedindetailandexplanationsofimprovementaregiven.
简介:PresidentZhaoJibinofChinaTitonggoestoJiangsutodosomesurveysandafterlisteningtotheworkingreportofJiangsuTietong,heinspectsthenetworkdevelopmentinNanjing,Suzhou,Changzhouandothercities.ZhaoJiBinemphasizesChinaTietongshouldbeonthewayof'enlargeprivatenetworkcoverageandmakegreatprogressinnetworkregionalization',makeeveryefforttolayasolid
简介:在这份报纸,我们比较了联合网络隧道编码的表演(JNCC)为多点传送当独占时,用低密度同等值支票(LDPC)的继电器网络作为隧道代码编码,Convolutional编码或(XOR)编码的网络在中间的继电器节点使用了。多点传送继电器传播是二个固定继电器节点在第二在作出贡献的传播计划的一种类型在基础收发器车站(BTS)和一双活动车站之间的端对端的传播跳跃。我们认为一个方法和二个方法多点传送评估位错误率(BER)和产量性能的情形。是否使用XOR网络在中间的继电器节点编码,被看了那,一样的传播因此在更少的时间槽变得可能产量性能能被改进。而且我们也在建议系统模型,差异和multiplexing获得在被考虑了讨论了二种可能的情形。它值得通知那BER和产量为LDPC代码完成了比对讨论的所有计划的Convolutional代码好。
简介:ThisletteranalyzesthereasonswhytheknownNeuralBackPromulgation(NBP)networklearningalgorithmhasslowerspeedandgreatersampleerror.Basedontheanalysisandexperiment,thetraininggroupdescendingEnhancedCombinationAlgorithm(ECA)isproposed.TheanalysisofthegeneralizedpropertyandsampleerrorshowsthattheECAcanheightenthestudyspeedandreduceindividualerror.
简介:Arobustdigitalreceiverbasedonamatchedfilter(MF)isproposedfortheradiofrequencyidentification(RFID)readersystemtoenhancethereliabilityofsignalprocessingintheelectronicproductcode(EPC)sensornetwork(ESN).Theperformanceoftheproposedreceiverisinvestigatedbyexaminingtheanti-collisionalgorithmintheEPCglobalClasslGeneration2protocol.Thevalidityandusefulnessaredemonstratedbybothcomputersimulationsandexperiments.Basedontheverificationresults,comparingwiththeconventionalzerocrossingdetector(ZCD)basedreceiver,theproposedreceiverisveryrobustagainststrongamplitudedistortionsandconsiderablefrequencydeviationshappeningonthebackscatteredsignalfromapassivetag.
简介:Vehielesenlistedwitheomputing,sensingandcommunicatingdevicescancreatevehicularnetworks,asubsetofcooperativesystemsinheterogeneousenvironments,aimingatimprovingsafetyandentertainmentintraffic.Invehicularnetworks,avehicle’sidentityisassociatedtoitsowner’sidentityasauniquelinkage.Therefore,itisofimportancetoprotectprivacyofvehiclesfrombeingpossiblytracked.Obviously,theprivacyprotectionmustbescalablebecauseofthehighmobilityandlargepopulationofvehicles.Inthiswork,wetakeanon-trivialsteptowardsprotectingprivacyofvehicles.Asprivacydrawspublicconcerns,wefirstlypresentprivacyimplicationsofoperationalchallengesfromthepublicpolicyperspective.Additionally,weenvisionvehicularnetworksasgeographicallypartitionedsubnetworks(cells).Eachsubnetworkmaintainsalistofpseudonyms.Eachpseudonymincludesthecell’sgeographicidandarandomnumberashostid.Beforestartingcommunication,vehiclesneedtorequestapseudonymondemandfrompseudonymserver.Inordertoimproveutilizationofpseudonyms,weaddressastochasticmodelwithtime-varyingarrivalanddeparturerates.Ourmaincontributionincludes:1)proposingascalableandeffectivealgorithmtoprotectprivacy;2)providinganalyticalresultsofprobability,varianceandexpectednumberofrequestsonpseudonymservers.Theempiricalresultsconfirmtheaccuracyofouranalyticalpredictions.