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Evaluating the resilience of the bottom-up method used to detect and benchmark the smartness of university campuses

机译:评估自下而上的方法的弹性,该方法可用于检测和确定大学校园的智能水平

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A new method to perform a bottom-up extraction and benchmark of the perceived multilevel smartness of complex ecosystems has been recently described and applied to territories and learning ecosystems like university campuses and schools. In this paper we study the resilience of our method by comparing and integrating the data collected in several European Campuses during two different academic years, 2014-15 and 2015-16. The overall results are: a) a more adequate and robust definition of the orthogonal multidimensional space of representation of the smartness, and b) the definition of a procedure to identify data that exhibits a limited level of trust.
机译:最近已经描述了一种执行自下而上的提取和对复杂生态系统的感知多级智能进行基准测试的新方法,并将其应用于领土和学习型生态系统,例如大学校园和学校。在本文中,我们通过比较和整合2014-15和2015-16两个不同学年在多个欧洲校区收集的数据来研究我们方法的弹性。总体结果是:a)对智能表示的正交多维空间的更充分,更健壮的定义,以及b)识别具有有限信任级别的数据的过程的定义。

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