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已有 21842 次阅读 2013-9-22 09:04 |个人分类:复杂网络|系统分类:论文交流| 文章

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Diversity of individual mobility patterns and emergence of aggregated scaling laws

Xiao-Yong Yan, Xiao-Pu Han, Bing-Hong Wang & Tao Zhou

Scientific Reports 3, Article number: 2678 doi:10.1038/srep02678

Uncovering human mobility patterns is of fundamental importance to the understanding of epidemic spreading, urban transportation and other socioeconomic dynamics embodying spatiality and human travel. According to the direct travel diaries of volunteers, we show the absence of scaling properties in the displacement distribution at the individual level,while the aggregated displacement distribution follows a power law with an exponential cutoff. Given the constraint on total travelling cost, this aggregated scaling law can be analytically predicted by the mixture nature of human travel under the principle of maximum entropy. A direct corollary of such theory is that the displacement distribution of a single mode of transportation should follow an exponential law, which also gets supportive evidences in known data. We thus conclude that the travelling cost shapes the displacement distribution at the aggregated level.










Efficient Learning Strategy of Chinese Characters Based on Network Approach

Xiaoyong Yan, Ying Fan, Zengru Di, Shlomo Havlin, Jinshan Wu

PLoS ONE 8(8): e69745. doi:10.1371/journal.pone.0069745


We develop an efficient learning strategy of Chinese characters based on the network of the hierarchical structural relations between Chinese characters. A more efficient strategy is that of learning the same number of useful Chinese characters in less effort or time. We construct a node-weighted network of Chinese characters, where character usage frequencies are used as node weights. Using this hierarchical node-weighted network, we propose a new learning method, the distributed node weight (DNW) strategy, which is based on a new measure of nodes' importance that considers both the weight of the nodes and its location in the network hierarchical structure. Chinese character learning strategies, particularly their learning order, are analyzed as dynamical processes over the network. We compare the efficiency of three theoretical learning methods and two commonly used methods from mainstream Chinese textbooks, one for Chinese elementary school students and the other for students learning Chinese as a second language. We find that the DNW method significantly outperforms the others, implying that the efficiency of current learning methods of major textbooks can be greatly improved.


详细介绍请看我之前的博文:《一篇论文被BBC Future报道



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