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简介：在航空测量，主要因素是地面波动。然而，大多数为航空测量设计使用的外部航空测量软件不考虑地面波动影响。因此，设计结果有比较randomicity和“差距”被期望。一个航空测量设计系统被与DEM数据分析地面波动影响到设计结果开发以便前面的重叠和方面重叠能根据块地面波动被认为正当遇见说明或标准。这个系统设计的数据与真实的飞数据相比。结果证明使用DEM在航空测量设计帮助能保证设计结果更好适合真实地面。

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简介：客观：为胫骨的intramedullarynails.Methods的远侧的锁住评估帮助thecomputer的汽车框架航行系统的临床的可行性和效果：系统的硬件部件与一个监视器包括了一台PC计算机，汽车机械立体声战术的定位立方的框架，脚持有者和起作用的本地化仪器。特殊航行软件能被用于X光检查fluoroscopic图象和工具的real-timecontrolling航行的登记。近胫骨、腓骨的破裂的21个案例被对待，关上的intramedullary钉其6在中间第三包含了，12在里面中间、更低第三，3在里面降低第三。涉及锁住的过程的C手臂排列和登记时间，fluoroscopic时间和钻的时间被记录。unreamed或铰大的胫骨的钉子的尺寸从8/300-11/330。结果：除了1的所有远侧的洞成功地被锁。在41个锁的洞(21.95%)中的9个里，练习小点摸了没有钉子和临床的后果的损坏，锁洞的运河。荧光检查时间每一些螺丝钉是2.23s±0.31s。结论:为远侧的锁住的帮助计算机的汽车框架航行系统很好被设计，对容易操作并且不在过程期间需要另外的仪器。发达系统使医生能精确用就一些校准计算机的X光线照相术的图象在整个解剖遨游外科的仪器。X光暴露的全部的时间能显著地每过程被减少。

简介：Objective:ToevaluateHighResolutionComputerTomography(HRCT)inthediagnosisofexternalearcanalcholesteatoma.Methods:Inthisretrospectivestudy,HRCTsof27patientswithexternalearcanalcholesteatomawerereviewed.Thechangesintheexternalearcanal,tympanicmembrane(TM),scutum,tympanumandmastoidweremeasuredandcategorized.Results:Fourteenpatientsshowednoormilddestructionintheexternalearcanal(stageIgroup).Eightpatientshadobviousenlargementintheexternalearcanal(stageIIgroup)butshowedlimiteddestructionsofthemastoidboneandnodamageofthetympanums.Fivepatientshadseriousdestructionofthemastoidboneanddamageofthetympanum(stageIIIgroup).AllpatientsinthestageIIIgroupshowedacompressionofmanubriumsandTMs,with3havingdamagesonossicularchain.BonedestructionoftheverticalsectionoffacialnervecanalwasdiscoveredinonecaseinthestageIIIgroup.Conclusion:HRCTcanprovidedetailinformationabouttheextentofexternalearcanalcholesteatoma.Suchinformationcanbeusedtoidentifyspecialsituationswithseriouscomplicationsandtodifferentiateexternalearcanalcholesteatomafrommiddleearcholesteatoma.

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简介：都市快速生产着高楼快车，也快速生产着人们内心的压力、寂寞与孤独。面对相识的人不肯吐露内心所想，却要通过冰冷的机器来传达信息，这也许是第一个发明这部机器的人始料未及的吧……

简介：Doyouevercalllongdistancefromapayphone?

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简介：AbstractBackground:Diagnoses of Skin diseases are frequently delayed in China due to lack of dermatologists. A deep learning-based diagnosis supporting system can facilitate pre-screening patients to prioritize dermatologists’ efforts. We aimed to evaluate the classification sensitivity and specificity of deep learning models to classify skin tumors and psoriasis for Chinese population with a modest number of dermoscopic images.Methods:We developed a convolutional neural network (CNN) based on two datasets from a consecutive series of patients who underwent the dermoscopy in the clinic of the Department of Dermatology, Peking Union Medical College Hospital, between 2016 and 2018, prospectively. In order to evaluate the feasibility of the algorithm, we used two datasets. Dataset I consisted of 7192 dermoscopic images for a multi-class model to differentiate three most common skin tumors and other diseases. Dataset II consisted of 3115 dermoscopic images for a two-class model to classify psoriasis from other inflammatory diseases. We compared the performance of CNN with 164 dermatologists in a reader study with 130 dermoscopic images. The experts’ consensus was used as the reference standard except for the cases of basal cell carcinoma (BCC), which were all confirmed by histopathology.Results:The accuracies of multi-class and two-class models were 81.49% ± 0.88% and 77.02% ± 1.81%, respectively. In the reader study, for the multi-class tasks, the diagnosis sensitivity and specificity of 164 dermatologists were 0.770 and 0.962 for BCC, 0.807 and 0.897 for melanocytic nevus, 0.624 and 0.976 for seborrheic keratosis, 0.939 and 0.875 for the "others" group, respectively; the diagnosis sensitivity and specificity of multi-class CNN were 0.800 and 1.000 for BCC, 0.800 and 0.840 for melanocytic nevus, 0.850 and 0.940 for seborrheic keratosis, 0.750 and 0.940 for the "others" group, respectively. For the two-class tasks, the sensitivity and specificity of dermatologists and CNN for classifying psoriasis were 0.872 and 0.838, 1.000 and 0.605, respectively. Both the dermatologists and CNN achieved at least moderate consistency with the reference standard, and there was no significant difference in Kappa coefficients between them (P > 0.05).Conclusions:The performance of CNN developed with relatively modest number of dermoscopic images of skin tumors and psoriasis for Chinese population is comparable with 164 dermatologists. These two models could be used for screening in patients suspected with skin tumors and psoriasis respectively in primary care hospital.

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简介：ispaperestablishesaformalmodelforhybriddiagnosis,novelfeaturesincluding:(1)Itprovidesaunifiedtheoreticalframeworkforutilizingdevicemodelsandheuristicsindiagnosis,whichnaturallyintegratesalltheimportantcomponentsofdiagnosis-thestructuralandbehavioraldescriptionofdevices,faultmodes,thelowerandupperfaultbounds,faultpossibilitiesandheuristicrules-intoadiagnosticsystem.Devicemodelspredictoutputsfrominputs,heuristicrulesinferthepossibilitiesofcertaincomponentsbeingfaultyfromsymptons,andyetthecombinationofbothconstrainseachotherforustoreducethehypothesisspace.(2)Itpresentsatypicalwayofmodelingbehaviorofdevices,towhichthekeyistheintroductionofI-Ofunctionswithindefiniteinputs/outputs.(3)Itcaneasilybeimplementedoveraforware-chaininginferenceengine.

简介：Inthepastyear,productscapableofturningnonstopspeechintotexthaveenteredthecommercialmarketplace.ViaVoicefromIBMCorp.isoneinstance,andNaturallySpeakingfromDragonSystemsInc.…,isanother.BothsystemsconsistofsoftwarewrittenforIBM-compatiblePCswithWindows95orNT,

简介：Thearcsprayingprocessisdividedintotwostages:thefirststageisatomization-sprayingstream(ASS)andthesecondoneissprayingdeposition(SD).Thenstudystatusisdescribedofbothstages'physicalmodelandcorrespondingcontrolling-equation.Basedontheanalysisofstudystatus,theconclusionasfollowsisgot.TheheatandmasstransfermodelswithtwoorthreedimensionsinASSstageshouldbeestablishedtofardeeplyanalysesthedynamicalandthermalbehavioroftheoverheatdroplet.Thestatisticslawofoverheateddropletsshouldbefurtherstudiedbyconnectingsimulationwithexperiments.MorepropervalidationexperimentsshouldbedesignedforflatteningsimulationtomodifythemodelsinSDstage.