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Titlebook: Advanced Network Technologies and Intelligent Computing; Third International Anshul Verma,Pradeepika Verma,Isaac Woungang Conference proce

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31#
發(fā)表于 2025-3-26 22:17:54 | 只看該作者
32#
發(fā)表于 2025-3-27 03:50:40 | 只看該作者
Tree Topologies and Node Covers for Efficient Communication in Wireless Sensor Networkstree-based networks and the exact values of the node and edge covers for trees such as n-centipedes, paths, stars, spike trees and banana trees are determined. Furthermore, a use case of node cover within WSNs is presented in the context of disaster response and emergency management in earthquake early warning systems.
33#
發(fā)表于 2025-3-27 08:07:28 | 只看該作者
1865-0929 onference on Advanced Network Technologies and Intelligent Computing, ANTIC 2023, held in Varanasi, India, during December 20-22, 2023...The 87 full papers and 11 short papers included in this book were carefully reviewed and selected from 487 submissions. The conference papers are organized in topi
34#
發(fā)表于 2025-3-27 10:06:27 | 只看該作者
Reduced Competitive Ratio of?Sparse Semi-oblivious Routing Using Social Spider Algorithmn improving the competitive ratio of sparse semi-oblivious routing. Through proficiently responding to changes in traffic patterns with our path selections, we have opened up a road to more streamlined routing strategies. Our breakthrough lies in the mastery of SSA’s capabilities..Empirical evidence
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發(fā)表于 2025-3-27 14:27:06 | 只看該作者
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發(fā)表于 2025-3-27 20:48:41 | 只看該作者
IoT Based Safety Monitoring and Communication System for Underground Coal Minesing real-time data collection and analysis, the system can promptly identify dangerous gas levels or adverse environmental conditions. Consequently, the system will issue timely alerts and notifications to workers and supervisors, enabling swift responses and evacuation procedures in the event of es
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發(fā)表于 2025-3-28 01:55:09 | 只看該作者
Enhancing Network Security: A Hybrid Approach for?Detection and?Mitigation of?Distributed Denial-of-on abilities of 1D Convolutional Neural Networks (CNNs) with the classification skills of Random Forest (RF) and Multi-layer Perceptron (MLP) classifiers. Using the CIC-DDoS2019 dataset, we perform multiclass classification of various DDoS attacks and conduct a comparative analysis of evaluation met
38#
發(fā)表于 2025-3-28 05:06:55 | 只看該作者
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發(fā)表于 2025-3-28 06:19:29 | 只看該作者
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發(fā)表于 2025-3-28 13:03:10 | 只看該作者
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