排序方式： 共有71条查询结果，搜索用时 15 毫秒
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在新技术背景下,围绕培养高素质创新人才这一中心,如何进行微积分课堂教学,是值得探索与研究的问题。微积分的教学目的,不仅是要让学生掌握基本知识和方法,提高运算能力,还需要培养学生的抽象思维能力、逻辑思维能力、应用创新能力,为学习相关专业打好数学基础。微积分课堂应当成为数学文化传播的场所;微积分的教学活动应当有意识地进行数学思想的教育;微积分的教学应当与现代技术相结合,以发展学生的数学能力为重。微积分课程应当真正成为培育人才的基础课程。 相似文献
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戈玉新 《淮海工学院学报(社会科学版)》2012,10(2):109-111
高等职业教育是职业技术教育的高级阶段,是培养高等技术应用型人才的教育。针对高等职业教育的特点,通过多年数学教学,以分部积分的课堂教学为例,对有效课堂的构建问题进行了不懈的探索。 相似文献
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徐明明 《深圳大学学报(人文社会科学版)》1993,(3)
F·P·Ramsey(拉姆西)发现,应用二阶逻辑对一个有有限数目公理的科学理论T而言,T中的理论性词项可以被消除。将T的公理用Ramsey语句来代替可以保持T的所有的经验推论。狭义而言,Ramsey方法通过对理论性词项的意义存而不论,从而提供了一种处理该类词项的逻辑技巧;广义而论,Ramsey方法强调对对象之间的关系的描述,而对对象的本质的解释存而不论。本文通过比较Ramsey方法与逻辑经验主义对运算和解释的区分以及对近代科学方法论的若干思考而得到这一对Ramsey方法的广义理解。 相似文献
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给出了全微分求偏导法的证明,指出了比较系数法和全微分求偏导方法的同一性,并且给出了具体的例子. 相似文献
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Christoph Lutz Christian Pieter Hoffmann Eliane Bucher Christian Fieseler 《Information, Communication & Society》2018,21(10):1472-1492
Internet-mediated sharing is growing quickly. Millions of users around the world share personal services and possessions with others ? often complete strangers. Shared goods can amount to substantial financial and immaterial value. Despite this, little research has investigated privacy in the sharing economy. To fill this gap, we examine the sharing–privacy nexus by exploring the privacy threats associated with Internet-mediated sharing. Given the popularity of sharing services, users seem quite willing to share goods and services despite the compounded informational and physical privacy threats associated with such sharing. We develop and test a framework for analyzing the effect of privacy concerns on sharing that considers institutional and social privacy threats, trust and social-hedonic as well as monetary motives. 相似文献
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从实例出发,借助问题驱动,以微积分基本公式讲授为例进行教学设计,意在引导学生发现问题、分析问题、解决问题,从而加深对定理的理解和应用。 相似文献
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《Journal of nonparametric statistics》2012,24(1):1-15
Kernel estimators for d dimensional data are usually parametrized by either a single smoothing parameter, or d smoothing parameters corresponding to each of the coordinate directions. A generalization of each of these parameterizations is to use a d× d matrix which allows smoothing in arbitrary directions. We demonstrate that, at this level of generality, the usual error approximations and their numerical minimization can be done quite simply using matrix algebra. The minimization formulas have the practical importance that they can be applied to data-driven selection of the smoothing parameters using a ”plug-in approach. Particular attention is paid to the special case of kernel estimation of multivariate normal mixture densities where it is shown that the numerical evaluation and minimization of both asymptotic and exact mean integrated squared error can be set up in a matrix algebraic formulation which requires no numerical integration. This provides a flexible family of multivariate smoothing problems for which error analyses can be performed in a computationally simple manner. 相似文献