简介：

简介：

简介：

简介：Thepurposeofthisstudywastounderstandtheeffectofimplementingmultipleintelligence(MI)-basedinstructiononthesciencelearningmotivationandlearningachievementof7thgradejuniorhighstudents.Thisquasi-experimentalresearchstudyutilizedquestionnairesandtestsofsciencelearningmotivationandlearningachievement,andexaminedcollecteddatathroughuseofthestatisticalpackageforthesocialsciences(SPSS).Ananalysisofcovariance(ANCOVA)andat-testwereperformedinordertoexplorethedifferencesbetweenthesciencelearningmotivationsandlearningachievementsoftheexperimentalgroup(N=39),whoweresubjectedtoteachingbasedonMItheory,andthecontrolgroup(N=36),whoweresubjectedtotraditionallectures.Theresultsofthestudyshowthat,afterimplementingMI-basedinstruction,thestudentsintheexperimentalgroupsignificantlyoutperformedthoseinthecontrolgroupintermsofsciencelearningmotivation,sciencelearningvalue,andactivelearningstrategies,whilethestudentswithlowlearningachievementshowinganimprovementintheirlearningattitudethatallowedthemtodevelopapositivelearningattitudetowardbiologyclassesandraisedtheirclassparticipationandpreferenceforbiologyclasses.

简介：无

简介：

简介：TheNewEnglishcurriculumcriteriasuggestteachingEnglishgrammarbasedonthestudents’cognitivecharacteristicsandemotionalneeds,helpingthemdiscovertherulesandencouragingthemtomasterthegrammarbyusingit.Butduetothelimitedtimeinalesson,manyEnglishteachersadoptasimpleapproachtoteachgrammar,inwhichstudentsarerequiredtomemorizetherulesfirstandthenpracticealot.Thisapproachiseffec-

简介：

简介：Ahandgesturerecognitionmethodispresentedforhuman-computerinteraction,whichisbasedonfingertiplocalization.First,handgestureissegmentedfromthebackgroundbasedonskincolorcharacteristics.Second,featurevectorsareselectedwithequalintervalsontheboundaryofthegesture,andthengestures'lengthnormalizationisaccomplished.Third,thefingertippositionsaredeterminedbythefeaturevectors'parameters,andanglesoffeaturevectorsarenormalized.Finallythegesturesareclassifiedbysupportvectormachine.Theexperimentalresultsdemonstratethattheproposedmethodcanrecognize9gestureswithanaccuracyof94.1%.

简介：Thispaperproposesanewfacialbeautificationmethodusingfacialrejuvenationbasedontheageevolution.Traditionalfacialbeautificationmethodsonlyfocusonthecolorofskinanddeformationanddothetransformationbasedonanexperimentalstandardofbeauty.Ourmethodachievesthebeautyeffectbymakingfacialimagelooksyounger,whichisdifferentfromtraditionalmethodsandismorereasonablethanthem.Firstly,wedecomposetheimageintodifferentlayersandgetadetaillayer.Secondly,wegetanage-relatedparameter:thestandarddeviationoftheGaussiandistributionthatthedetaillayerfollows,andthesupportvectormachine(SVM)regressionisusedtofitafunctionabouttheageandthestandarddeviation.Thirdly,weusethisfunctiontoestimatetheageofinputimageandgenerateanewdetaillayerwithanewstandarddeviationwhichiscalculatedbydecreasingtheage.Lastly,wecombinetheoriginallayersandthenewdetaillayertogetanewfaceimage.Experimentalresultsshowthatthisalgorithmcanmakefacialimagebecomemorebeautifulbyfacialrejuvenation.Theproposedmethodopensupanewwayaboutfacialbeautification,andtherearegreatpotentialsforapplications.

简介：当数字地为一艘轮船建模时，参数评价的精确性是批评的。有限制的一个参数评价方法被开发，基于变化方法。在变化方法的性能函数和限制方程被分析系统的输入和输出方程构造。参数评价的问题被转变成最少的广场评价的一个问题。参数评价方程被分析以便基于Lagrange增加操作员得到参数的一个优化评价。模拟结果证明这个方法比传统的最少的广场评价好，当识别参数时，生产更高的精确。它在象系统鉴定和参数评价那样的申请的区域有很重要的实际价值。关键词最少的广场评价-参数评价-变化方法-限制基础条款：不到资助号码2009由海军设备部门基础支持了(189)。我皮脂腺囊瘤史在1982出生了。他是在海军海底的学院的一个讲师，中国。他的当前的研究兴趣是海底的航行。

简介：

简介：

简介：ＦｕｚｚｙＥｎｔｒｏｐｙＢａｓｅｄＣｏｍｂｉｎｅｄＬｅａｒｎｉｎｇＡｌｇｏｒｉｔｈｍｆｏｒＮｅｕｒａｌＮｅｔｗｏｒｋｓ￥ＭｉｎＹａｏ（Ｄｅｐｔ．ｏｆＣｏｍｐｕｔｅｒＳｃｉｅｎｃｅ，ＨａｎｇｚｈｏｕＵｎｉｖｅｒｓｉｔｙ，Ｈａｎｇｚｈｏｕ３１００２８，Ｐ...

简介：

简介：Thispaperpresentsanapplicationofiterativelearningcontrol(ILC)techniquetothevoltagecontrolofsolidoxidefuelcell(SOFC)stack.Tomeetthedemandsofthecontrolsystemdesign,anautoregressivemodelwithexogenousinput(ARX)isestablished.Firstly,byregulatingthevariationofthehydrogenflowrateproportionaltothatofthecurrent,thefuelutilizationoftheSOFCiskeptwithinitsadmissiblerange.Then,basedontheARXmodel,threekindsofILCcontrollers,i.e.P-,PI-andPD-typearedesignedtokeepthevoltageatadesiredlevel.SimulationresultsdemonstratethepotentialoftheARXmodelappliedtothecontroloftheSOFC,andprovetheexcellenceoftheILCcontrollersforthevoltagecontroloftheSOFC.

简介：

简介：专家知识广泛地被用来改进遥远地察觉到的分类精确性。通常，专家分类系统主要取决于DEM和一些题目的地图。在象素水平的空间关系信息通常被介绍进专家分类。因为地理目标被发现关系空间地依赖到某个度，在象素的空间关系信息的通常使用的基本单位极大地限制了空间信息的效率。寻找算法的一位基于补丁的邻居被建议实现专家分类。同类的光谱的联合起来，补丁，在空间目标被用作基本单位补丁鈥?关系信息的颗粒度，和不同类型通过寻找的一位空间邻居被获得算法。然后邻居信息和DEM数据被增加进专家分类系统并且过去常修改原始分类错误。在这，情况，沼泽地的分类精确性，草地和农田显然被改进。在这个工作，当水抽取方法的基础目标，和不同类型被测试在高精确性得到结果，水被使用。

简介：Utilizingdatafromcontrolledseismicsourcestoimagethesubsurfacestructuresandinvertthephysicalpropertiesofthesubsurfacemediaisamajoreffortinexplorationgeophysics.Denseseismicrecordswithhighsignal-to-noiseratio(SNR)andhighfidelityhelpsinproducinghighqualityimagingresults.Therefore,seismicdatadenoisingandmissingtracesreconstructionaresignificantforseismicdataprocessing.Traditionaldenoisingandinterpolationmethodsrarelyoccasionedrelyonnoiselevelestimations,thusrequiringheavymanualworktodealwithrecordsandtheselectionofoptimalparameters.Weproposeasimultaneousdenoisingandinterpolationmethodbasedondeeplearning.Fornoisyrecordswithmissingtraces,weadoptaniterativealternatingoptimizationstrategyandseparatetheobjectivefunctionofthedatarestoringproblemintotwosub-problems.Theseismicrecordscanbereconstructedbysolvingaleast-squareproblemandapplyingasetofpre-traineddenoisingmodelsalternativelyanditeratively.Wedemonstratethismethodwithsyntheticandfielddata.

简介：ItseemsthatthewritingofarticlesInEnglishIsextremelyuneasyforstudentsofsecondfan－guaaelearning．AuditIsdifficultInatleastthreeaspects：l．ThestudentsnndItbardtochoose‘enougll’wordsorphrasesorexpressionstocomposea‘good’writing．