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- W4300387660 abstract "Rapid advances in modern communication technology are enabling the accumulation of large-scale, high-resolution observational data of spatiotemporal movements of humans. Classification and prediction of human mobility based on the analysis of such data carry great potential in applications such as urban planning as well as being of theoretical interest. A robust theoretical framework is therefore required to study and properly understand human motion. Here we perform the eigenmode analysis of human motion data gathered from mobile communication records, which allows us to explore the scaling properties and characteristics of human motion." @default.
- W4300387660 created "2022-10-03" @default.
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- W4300387660 date "2016-01-11" @default.
- W4300387660 modified "2023-10-17" @default.
- W4300387660 title "The Eigenmode Analysis of Human Motion" @default.
- W4300387660 doi "https://doi.org/10.48550/arxiv.1603.04810" @default.
- W4300387660 hasPublicationYear "2016" @default.
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