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Titlebook: Collaborative Computing: Networking, Applications and Worksharing; 16th EAI Internation Honghao Gao,Xinheng Wang,Ning Gu Conference proceed

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樓主: Remodeling
41#
發(fā)表于 2025-3-28 17:17:24 | 只看該作者
The chronic patient: damage limitation,rmation yields better results than using traditional thresholding when deciding if weaker detections are actually classed as observed or not. The experiments performed not only show that our method significantly improves the performance of CNN object detectors, but that it can be used as an efficien
42#
發(fā)表于 2025-3-28 21:17:22 | 只看該作者
https://doi.org/10.1007/978-3-319-46795-5valuation, we test the performance of matrix multiplications and a CNN model training in our system with uncoded and coded strategies. The evaluation results show that the system with code strategies perform better than with uncoded strategies on the edge devices having the problem of straggler. In
43#
發(fā)表于 2025-3-29 01:14:56 | 只看該作者
Transvestism and Transsexualism, helps to illustrate the health status of the platform-based service ecosystem from the perspective of multi-dimensional integration. Additionally, this paper analyzes the factors affecting the health of this ecosystem based on HIM. In this work, a platform-based service ecosystem simulation model i
44#
發(fā)表于 2025-3-29 05:09:39 | 只看該作者
45#
發(fā)表于 2025-3-29 08:39:31 | 只看該作者
Tobias Schiffler,Hanna M. Mües,Igor Grabovacrge number of binary variables, and the solution space will be too large to be solved directly in a multi-task scenario. Then we use dynamic programming and greedy strategy to reduce the solution space under the premise of a good solution, and propose our offline algorithm named GSPI. Then consideri
46#
發(fā)表于 2025-3-29 13:19:08 | 只看該作者
https://doi.org/10.1007/978-3-030-65599-0erformance and introduce a dynamic offloading strategy based on a probabilistic evolutionary game-theoretic framework. To validate our proposed framework, we conduct experimental case studies based on a real-world dataset of cloud edge resource locations and show that our proposed approach outperfor
47#
發(fā)表于 2025-3-29 16:40:23 | 只看該作者
48#
發(fā)表于 2025-3-29 21:51:03 | 只看該作者
WSN Coverage Optimization Based on?Two-Stage PSOoptimization performance, and gives the corresponding algorithm implement. Simulation experiments show that compared with MVFA, SPSO and OPSO algorithms, MTPSO algorithm has a better redeployment coverage performance, which fully demonstrates its effectiveness.
49#
發(fā)表于 2025-3-30 00:32:25 | 只看該作者
An Efficient and Truthful Online Incentive Mechanism for a Social Crowdsensing Networkthe network, we design a user selection algorithm and a payment determination algorithm respectively, in which payments given to participants not only depend on data qualities but also related with social influences. We theoretically prove that our mechanism achieves properties of computational effi
50#
發(fā)表于 2025-3-30 07:33:16 | 只看該作者
CPNSA: Cascade Prediction with Network Structure Attentionstructural dependency for cascade prediction of resharing. Experiments are conducted on both synthetic and real-world datasets, and the results show that our approach can effectively improve the performance of the cascade prediction of resharing.
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