简介：Deduplication通常在两个企业存储系统和云存储被使用了。克服性能挑战为选择恢复deduplication系统的操作，solid-state-drive-based(即，基于SSD)读的缓存能为由缓冲加快被部署流行动态地恢复内容。不幸地，经常的数据更改由古典缓存计划导致了(例如，LRU和LFU)显著地弄短SSD一生当在SSD减慢I/O进程时。处理这个问题，我们建议新解决方案砍缓存极大地由扩大比例象I/O性能一样改进SSD的write耐久性长期流行(砍)在写进基于SSD的缓存的数据之中的数据。砍缓存保留很长时间在SSD缓存砍数据减少的时期缓存代替的数字。而且，它在deduplication集装箱阻止不得人心或不必要的数据被写进SSD缓存。我们在一个原型deduplication系统实现了砍缓存评估它的性能。我们的试验性的结果显示砍缓存弄短潜伏选择与仅仅deduplicated数据的5.56%能力以小基于SSD的缓存的成本由37.3%的一般水准恢复。重要地，砍缓存由9.77的一个因素改进SSD一生。砍缓存为一个成本效率的基于SSD的读的缓存解决方案提供到的证据表演增加性能选择为deduplication恢复系统。

简介：Thehumanvisionsystemcanreconstructa3Dobjecteasilyfromsingle2Dlinedrawingsevenifthehiddenlinesoftheobjectareinvisible.Now,therearemanymethodshaveemulatedthisability,butwhenthehiddenlinesoftheobjectareinvisible,thesemethodscannotreconstructacomplete3Dobject.Therefore,weputforwardanewalgorithmtosettlethishardproblem.Ourapproachconsistsoftwosteps:(1)infertheinvisibleverticesandedgestocompletethelinedrawing,(2)proposeavertex-basedoptimizationmethodtoreconstructa3Dobject.

简介：Inthefieldofmedicalimaging,thetraditionallocalbinarypattern(LBP)anditsimprovedalgorithmsareoftensensitivetonoise.TraditionalLBPsaresolelybasedonthesignalinformationfromlocaldifferences,andthebinaryquantizationmethodoversimplifiesthelocaltexturefeatureswhiledisregardingtheimaginginformationfromtheconcaveconvexregionsbetweenthehigh-orderpixelsandtheneighboringsamplingpoints.Therefore,weproposeanimprovedDerivedMeanCompleteLocalBinaryPattern(DM_CLBP)algorithmbasedonhigh-orderderivatives.IntheDM_CLBPmethod,thegreyvalueofasinglepixelisreplacedbythemeangreyvalueoftherectangularareablock,andthedifferencebetweenpixelvaluesintheareaisobtainedusingthesecond-orderdifferentiationmethod.Basedonthecalculationconceptofthecompletelocalbinarypattern(CLBP)algorithm,thecascadesignsandmagnitudesofthetwocomponentsareencodedandrecombinedinDM_CLBPusingauniformpattern.TheresultsfromtheexperimentsshowedthattheproposedDM_CLBPdescriptorsachievedaclassificationaccuracyof94.4%.ComparedwithLBPandotherimprovedalgorithms,theDM_CLBPalgorithmpresentedinthisstudycaneffectivelydifferentiatebetweenlesionareasandnormalareasinthyroidMR,(magneticresonance)imagesandshowstheimprovedaccuracyofareaclassification.

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