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Titlebook: Computing Science, Communication and Security; 4th International Co Nirbhay Chaubey,Sabu M. Thampi,Kiran Amin Conference proceedings 2023 T

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21#
發(fā)表于 2025-3-25 03:30:42 | 只看該作者
https://doi.org/10.1007/978-3-540-30033-5 target in WSN. Compared to other prediction methods, the efficiency of the TDNN is better. By considering target velocity and geometrical shapes, lost target recovery can be improved further in terms of energy efficiency. Performance of different methods based on circular and contour geometrical sh
22#
發(fā)表于 2025-3-25 08:12:33 | 只看該作者
23#
發(fā)表于 2025-3-25 14:38:48 | 只看該作者
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發(fā)表于 2025-3-25 17:28:22 | 只看該作者
25#
發(fā)表于 2025-3-25 23:23:37 | 只看該作者
https://doi.org/10.1007/b137708eased and network life can be prolonged via the process of clustering. To reduce the network’s power consumption and increase its lifespan, we used a new clustering technique in this work. Centralized cluster formation and decentralized cluster heads form the basis of this stage of clustering. Clust
26#
發(fā)表于 2025-3-26 02:30:17 | 只看該作者
https://doi.org/10.1007/b137708omic advantages, particularly in catastrophic weather event scenarios and vital military operations. The utilization of Non-Orthogonal Multiple Access(NOMA) has been efficiently done to enhance channel utilization. Multiple users transmit information using similar frequency bands. This technique is
27#
發(fā)表于 2025-3-26 04:31:15 | 只看該作者
https://doi.org/10.1007/b137708s are proposed for this task, and each of these models showcases non-uniform performance & complexity levels when applied to real-time scenarios. To overcome such issues, this text proposes the design of a deep-learning-based bioinspired model that assists in improving the feature extraction capabil
28#
發(fā)表于 2025-3-26 10:35:35 | 只看該作者
29#
發(fā)表于 2025-3-26 13:14:43 | 只看該作者
30#
發(fā)表于 2025-3-26 20:04:37 | 只看該作者
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