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Titlebook: Activity and Behavior Computing; Md Atiqur Rahman Ahad,Sozo Inoue,Kaori Fujinami Book 2021 The Editor(s) (if applicable) and The Author(s)

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21#
發(fā)表于 2025-3-25 06:08:51 | 只看該作者
,Notwendigkeit von ?Messen in der Maschine“,uite challenging. Fortunately, there exist technologies that promote physical activity. Nonetheless, almost all of these technologies only target a narrow set of physical exercises (e.g., either running or physical workouts but not both) and are only applicable either in indoor or in outdoor environ
22#
發(fā)表于 2025-3-25 09:44:42 | 只看該作者
,Notwendigkeit von ?Messen in der Maschine“,ntil now. Thus, a bottom-up approach is recommended: citizens role should change from consumers to prosumers, to (co-)decision-makers regarding energy-related behaviour, and to co-investors in the new energy infrastructure. However behavioural change is difficult to realize in face of the ‘knowledge
23#
發(fā)表于 2025-3-25 13:20:30 | 只看該作者
Md Atiqur Rahman Ahad,Sozo Inoue,Kaori FujinamiPresents the latest research in the field of activity and behavior computing.Gathers extended versions of selected papers presented at ABC 2020, held in Kitakyushu, Japan on August 26 – 29, 2020.Serve
24#
發(fā)表于 2025-3-25 19:10:54 | 只看該作者
25#
發(fā)表于 2025-3-25 23:18:22 | 只看該作者
26#
發(fā)表于 2025-3-26 02:28:51 | 只看該作者
27#
發(fā)表于 2025-3-26 05:37:12 | 只看該作者
https://doi.org/10.1007/978-3-8349-6500-4 activities—sitting, standing and lying down—we find that 95% of the reconstructed gyroscope data is within an error of [?7.25;+7.46] ., while 95% of the reconstructed accelerometer data was contained within [?96.1;+72.9] .. However, when we introduce more movement by including data collected while
28#
發(fā)表于 2025-3-26 11:44:39 | 只看該作者
29#
發(fā)表于 2025-3-26 16:12:44 | 只看該作者
,Grundlagen automatisierter überwachung,h operates with extracted features, which drastically reduces the amount of stored and processed data and enables deployment on less powerful and potentially wearable devices. We show that this technique can be used to improve the classification performance of a classifier trained to recognise locom
30#
發(fā)表于 2025-3-26 19:54:07 | 只看該作者
Schlussfolgerungen und Ausblick,cision of an algorithm for automatic IC and TO detection is evaluated on the basis of root mean square error (RMSE) and intraclass correlation coefficient (ICC). The RMSE of the TO detection was 1.22%, and that of the IC was 1.40%. The ICC of the TO detection was 0.7011, and that of the IC was 0.772
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