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Titlebook: Cloud Computing, Smart Grid and Innovative Frontiers in Telecommunications; 9th EAI Internationa Xuyun Zhang,Guanfeng Liu,Tao Huang Confere

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樓主: Exaltation
11#
發(fā)表于 2025-3-23 09:50:42 | 只看該作者
12#
發(fā)表于 2025-3-23 14:03:06 | 只看該作者
13#
發(fā)表于 2025-3-23 19:12:49 | 只看該作者
https://doi.org/10.1007/978-3-658-23210-8nteract with our environment. There is a lot of progress being made toward achieving the envisioned goals of IoT, however there are still numerous challenges to be addressed. Bluetooth low energy (BLE) and its beacons protocol have pushed forward innovations in the field of microlocation, which is a
14#
發(fā)表于 2025-3-24 02:01:14 | 只看該作者
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發(fā)表于 2025-3-24 04:05:14 | 只看該作者
Interaktion, Organisation, Gesellschaftesis methods, introduced to computer graphics, aiming to simplify virtual scene simulation and enhance the fidelity of complex scenes. Currently, the simulation algorithms applied to cloud scene, inclined to be complicated and computationally intensive. Hence, it is still a key challenge to implemen
16#
發(fā)表于 2025-3-24 09:52:27 | 只看該作者
17#
發(fā)表于 2025-3-24 11:07:54 | 只看該作者
https://doi.org/10.1007/978-3-658-23212-2popularity model based on user interest feature. Usually, traditional model that does not take into account the stability of user’s interests, which leads to the difficulty in capturing their interest. To cope with this limitation, we propose a time-sensitive and stabilized interest similarity model
18#
發(fā)表于 2025-3-24 16:51:48 | 只看該作者
19#
發(fā)表于 2025-3-24 22:50:42 | 只看該作者
Organisationen im Wirtschaftssystemis proposed. The abstract features are captured by training a CNN model with the pixels’ vectors as inputs. Based on the extracted high-level features, different classifiers will perform different outputs under the same training set, due to the different types of classifiers take on diverse characte
20#
發(fā)表于 2025-3-25 02:02:19 | 只看該作者
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