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Titlebook: Betriebswirtschaftliches Probleml?sungsverhalten; Theoretische überleg Egbert Kahle Book 1973 Betriebswirtschaftlicher Verlag Dr. Th. Gable

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樓主: 劉興旺
21#
發(fā)表于 2025-3-25 05:30:30 | 只看該作者
22#
發(fā)表于 2025-3-25 09:25:01 | 只看該作者
23#
發(fā)表于 2025-3-25 12:12:21 | 只看該作者
Maixdock Based Driver Drowsiness Detection System Using CNNwn as drowsy driving. To categorize sleepiness signs like breathing and squinting deep learning has been used in this study. Yolo design training was done using example pictures. To categorize sleepiness signs like blinking and breathing, this study employs the Convolutional Neural Network (CNN). Th
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發(fā)表于 2025-3-25 16:20:39 | 只看該作者
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發(fā)表于 2025-3-25 20:50:31 | 只看該作者
26#
發(fā)表于 2025-3-26 02:16:12 | 只看該作者
Modernizing of the Rail Transport Curriculum and Study Process,nd the development of rail transport infrastructure are safety (control and command systems of rail traffic), opening the rail transport market to competition and improving the interoperability. A holistic approach to these issues will certainly help to solve the complex problems, but more attention
27#
發(fā)表于 2025-3-26 08:03:57 | 只看該作者
28#
發(fā)表于 2025-3-26 08:31:51 | 只看該作者
Scaling of Noise and Constructive Aspects of Fluctuationsng the symmetries and invariances of the system. By means of this methodology, it is possible to predict diverse physical manifestations of the cooperative behavior between noise and input signal, as for instance, stochastic resonance and stochastic multiresonance.
29#
發(fā)表于 2025-3-26 15:36:04 | 只看該作者
Michael J. V. White,Andrew Grieve) dynamic bundling remains superior in this context, (2) it does not require a full lookahead strategy, and (3) it dramatically reduces the cost of solving problems at the phase transition while yielding a bundle of multiple, robust solutions.
30#
發(fā)表于 2025-3-26 19:41:53 | 只看該作者
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