简介:诺基亚手机第一代型号是:2110、8110、3810等,由于体积较大和功能较少已退出市场;第二代主要型号是:6110、5110、8810、6150等机型,也是由于体积较大功能较少市场上已较少使用;第三代常见机型为:8210、8250、8850、3310等,即DCT3(第三代数字核心技术)系列手机,由于功能较多,价格低廉,社会上拥有相当的数量;第四代机型以3510、6100、6310、6510、6610、7210、8310、8910等的DCT4(第四代数字核心技术)系列手机,它们功能齐全,外观新颖,有的具有彩屏、彩信、拍照和摄像等多种时尚功能。下面就谈一谈DCT3系列手机的维修:
简介:Byusingthecenterprojectionimagesequencetoestimate3-Dmotionparameters,oneneedstoknowthecorrespondingrelationshipbetweenthefeatureofmotionobjectinspaceandtheprojectioncoordinateonimageplane.Inordertoavoidusingtherelationshipoffeaturecorrespondence,thetensoranalysismethodintheaffinetransformationsystemispresented,andthesimulationdataofexperimentalresultsaregiven.
简介:Thispaperpresentsahandheld3Dvision-basedscannerforsmallobjectsbyusingKinect.Itisdifferentfromthepreviouscolor-glove-basedapproacheswhichrequiresegmentingthetargetobject.First,weeliminatethenoisesandtheoutlierscausedbyholdinghands.Second,weapplyKinect-fusionalgorithmandtruncatedsigneddistancefunction(TSDF)torepresent3Dsurfaces.Third,weproposeamodifiedintegrationstrategytoeliminatethehandeffect.Fourth,wetakeadvantageoftheparallelcomputationofGPUsforreal-timeoperation.Themajorcontributionsofthispaperare(1)theregistrationprecisionisimproved,(2)theofflineamendmentandloopclosureoperationarenotrequired,and(3)concave3Dobjectreconstructionisfeasible.IndexTermsHandheld3Dscanning,Kinect-fusion,Truncatedsigneddistancefunction(TSDF).1.IntroductionRecently,thesensor-based3Dmodelreconstructionmethodshavebeenproposed[1].Thesensordeviceshavedifferentpropertiessothatthe3Dreconstructionalgorithmsvaryaccordingly.Thecommonlyusedsensordevicesaretime-of-flight(ToF)cameras[2]-[4],laserscanners[5],andstructuredlightscanners[6],[7].Lasershavegainedareputationforaccuracy;however,caremustbetakentouseeye-safelaserswhenoperatinginproximitytohumans.Foraninteractivesystem,thestructuredlightscannerwhichisbasicallyapassivevision-basedsensordeviceissuperiorbecauseitprovidesa2DdepthimageperframeandismoreaccuratethanthatofaToFcamera.Here,wepresentareal-time3DscannerusingthedepthimagescapturedbyKinect.
简介:Micro-structures3-Dprofilemeasurementisanimportantmeasurementcontentforresearchonmicro-machiningandcharacterizationofmicro-dimension.Inthispaper,anewmethodinvolved2-Dstructuretemplate,whichguidesphaseunwrapping,isproposedbasedonphase-shiftingmicroscopicinterferometry.Itisfitnotonlyforstaticmeasurement,butalsofordynamicmeasurement,especiallyformotionofMEMSdevices.3-Dprofileofactivecombofmicro-resonatorisobtainedbyusingthemethod.Thetheoreticprecisioninout-of-planedirectionisbetterthan0.5nm.Thein-planetheoreticprecisioninmicro-structuresisbetterthan0.5μm.Butattheedgeofmicro-structures,itisonthelevelofmicrometermainlycausedbyimpreciseedgeanalysis.Finally,itsdisadvantagesandthefollowingdevelopmentarediscussed.
简介:Organicmultiplequantumwells(OMQWs)consistingofalternatinglayersoforganicmaterialshavebeenfabricatedfromtris(8-hdroxyquinoline)aluminum(Alq)and2-(4-biphenylyl)-5-(4-tertbutylphenyl)-1,3,3-oxadiazole(PBD)byamultisource-typehigh-vacuumorganicmoleculardeposition.Fromthesmall-angleX-raydiffractionpatternsofAlq/PBDOMQWs,aperiodicallylayeredstructureisconfirmedthroughtheentirestack.TheAlqlayerthicknessintheOMQWswasvariedfrom1nmto4nm.Fromtheopticalaborption,photoluminescenceandelectroluminescencemeasurements,itisfoundthattheexcitonenergyshiftstohigherenergywithdecreasingAlqlayerthickness,ThechangesoftheexcitonenergycouldbeinterpretedastheconfinementeffectsofexcitonintheAlqthinlayers.Narrowingoftheemissionspectrumhasalsobeenobservedfortheelectroluminescentdevices(ELDs)withtheOMQWsstructureatroomtemperature.
简介:Satisfactoryresultscannotbeobtainedwhenthreedimensional(3D)targetswithcomplexmaneuveringcharacteristicsaretrackedbythecommonlyusedtwo-dimensionalcoordinatedturn(2DCT)model.Toaddresstheproblemof3Dtargettrackingwithstrongmaneuverability,onthebasisofthemodifiedthree-dimensionalvariableturn(3DVT)model,anadaptivetrackingalgorithmisproposedbycombiningwiththecubatureKalmanfilter(CKF)inthispaper.Throughideologyofreal-timeidentification,theparametersofthemodelarechangedtoadjustthestatetransitionmatrixandthestatenoisecovariancematrix.Therefore,statesofthetargetarematchedinreal-timetoachievethepurposeofadaptivetracking.Finally,foursimulationsareanalyzedindifferentsettingsbytheMonteCarlomethod.Allresultsshowthattheproposedalgorithmcanupdateparametersofthemodelandidentifymotioncharacteristicsinreal-timewhentargetstrackingalsohasabettertrackingaccuracy.