简介：许多图象分割解决方案是基于问题的。医药图象在感兴趣的目标之中有很类似的灰水平和质地。因此，尽管有研究，自从最后几十年起，做，医药图象分割要求改进。我们设计一个自我学习的框架从计算断层摄影术(CT)图象同时提取兴趣的几个目标。我们的分割方法有基于加强学习的一个学习阶段(RL)系统。每个RL代理人研究一幅输入图象的一幅特别亚图象在它为每个目标发现合适的价值。RL系统是由状态，行动和报酬定义。我们在亚图象为每个状态定义一些行动。报酬功能为RL代理人的每个行动计算报酬。最后，从发现兴趣目标的所有状态，珍贵信息将在Q矩阵被存储，最后的结果能在类似的图象的分割被使用。头部的CT图象的试验性的结果超过95%表明了分割精确性。

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简介：AninformationtheorymethodisproposedtotesttheGrangercausalityandcontemporaneousconditionalindependenceinGrangercausalitygraphmodels.Inthegraphs,thevertexsetdenotesthecomponentseriesofthemultivariatetimeseries,andthedirectededgesdenotecausaldependence,whiletheundirectededgesreflecttheinstantaneousdependence.Thepresenceoftheedgesismeasuredbyastatisticsbasedonconditionalmutualinformationandtestedbyapermutationprocedure.Furthermore,fortheexistedrelations,astatisticsbasedonthedifferencebetweengeneralconditionalmutualinformationandlinearconditionalmutualinformationisproposedtotestthenonlinearity.Thesignificanceofthenonlinearteststatisticsisdeterminedbyabootstrapmethodbasedonsurrogatedata.Weinvestigatethefinitesamplebehavioroftheprocedurethroughsimulationtimeserieswithdifferentdependencestructures,includinglinearandnonlinearrelations.

简介：E—Learning作为一种新的教学与学习模式给英语教学带来了深刻的变革，英语教师要适应这种变革．就必须了解E—Learning的特征。明确英语教师在E—Learning教育中的新角色，才能适应E—Leaming时代的要求。

简介：象建议，当模特儿的话题，和医药诊断一样的许多机器学习和数据采矿(MLDM)问题能在由两部组成的图上作为计算被建模。然而，很分布式的图平行系统对在这的唯一的特征忘却图和存在的联机图划分算法通常在网络通讯上象重要压力一样引起顶点的过多的复制。这篇文章识别为分布式的MLDM处理划分由两部组成的图的挑战和机会并且建议BiGraph，划分算法的一套由两部组成面向的图。BiGraph力量观察象数据在导出一套最佳的图的顶点的二个子集之间缩放划分导致最小的顶点复制和网络通讯的算法的顶点，区别计算负担和imbalanced的扭曲的分发那样。BiGraph在PowerGraph上被实现了并且被显示有表演增加直到17.75X(从1.16X)为四个典型MLDM算法，由于减少直到80%顶点复制，并且直到96%网络交通。

简介：Eveninclasseswhichstressoralpractice,theexplicitteachingofgrammarstillhasaroletoplay.EvelynDomanexplainswhyandpresentssomepracticalactivitieswhichintegrategrammarteachingwithcommunicativetasksinthegrammaticalconsciousness-raisingapproach.IntroductionTheroleofgrammarintheforeignlanguageclassroomhasbeendebatedbothlongandhard.Theoriesaboutteachinggrammarhavecoveredallrangesofthespectrum,goingfromplayingamajorroletobasicallyplayingnoroleatall.Today,CommunicativeLanguageTeaching(CLT)istheforerunnerintheTESL/TEFLcommunity.Yet,evenwithintheCLTframework,thecontroversyovertheteachingofgrammarcontinues.Manypeoplestillassertthatgrammarbegivenitsplace.Itooamamongthesepeople,especiallyinEFLenvironments,suchasinmypreviousteachingsituationsinSouthKorea.

简介：and evaluating the success of a particular strategy. They have an executive function. In O’Malley and Chamot framework of learning strategies,Oxford’s taxonomy fails to make a distinction between strategies directed at learning the L2 and those directed at using it (Ellis). The last problem is that compensation strategies are considered as a direct type of learning strategies rather than one type of production strategies,cognitive and social/affective. They grounded the study of learning strategies within the information-processing model of learning developed by Anderson. Metacognitive strategies involve consciously directing one’s efforts into the learning task. These strategies are higher order executive skills that may entail planning learning

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简介：模式经由确定的学习理论当模特儿和识别在这篇论文被介绍的为心电图(ECG)的一个方法。而不是认识到ECG表明beat-to-beat，包含很多心跳的每个ECG信号被认出。方法完全基于时间的特征(即，动力学)ECG模式，它包含ECG模式的完全的信息。一个动态模特儿被雇用表明方法，它能够产生合成ECG信号。基于动态模型，方法在下列二个阶段被显示出：鉴定(训练)阶段和识别(测试)分阶段执行。在鉴定阶段，ECG模式的动力学精确地被建模并且通过确定的学习表示了为经常的RBF神经重量。在识别阶段，当模特儿的结果被用于ECG模式识别。建议方法的主要特征是ECG模式的动力学精确地被当模特儿并且被用于ECG模式识别。用Physikalisch-TechnischeBundesanstalt(PTB)数据库的试验性的研究被包括表明途径的有效性。

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简介：IntroductionExtensiveReading,asthenameindicates,isaguideforstudentsintothevastseaofknowledge.Readingdemonstratestostudentsthatthereisnoendinlearningknowledge.However,readingandlanguagelearningbasedontextbooksisfarfromenoughbecausetheknowledgefromthemistoonarrow,thevocabularyistoolimitedandthecontentsarenotcurrentenoughinthesetimesofinformationexchange.Throughoutmyteachingexperiments,Ihavefoundthatnewspaperclippingscanbecomeaverygoodwaytobringmorebenefitstostudents’learningthanIexpected.Itcanbroadenthestudents’horizons,

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