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    npb4go: NonParametric Bayes for Going-Out behavior

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    npb4go, a nonparametric Bayesian software for modeling going-out behavior written by Matlab, detects one’s own rhythm or patterns of going out behavior from home / away log. As well as rhythm extraction, predicting one’s future presence using the extracted models is also performed. Technical details are in our paper at Pervasive 2012 [1]. This software should be used freely. To encourage free use, the library is licensed under the very liberal open-source MIT License.

    References

    [1] S. Tominaga, M. Shimosaka, R. Fukui, and T. Sato: A Unified Framework for Modeling and Predicting Going-Out Behavior. In: J. Kay, P. Lukowicz, H. Tokuda, P. Olivier, A. Kruger, (eds.) Pervasive 2012. LNCS, vol. 7319, pp. 73 — 90, Springer, Heidelberg (2012)

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    Recent News

    • Presenting our paper on Exploiting Periodic UWB CIRs for Robust Activity Recognition with Attention-aware Multi-level Wavelet at PerCom2025 2025/02/15
    • Presenting our paper on revealing Universities’ Atmosphere from Visitor Interests has been presented at IEEE BigData 2024 2024/12/16
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    • Presenting our paper on efficient Bluetooth beacon deployment for campus-scale crowd density monitoring application at UbiComp2023 2023/10/05

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