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    Evaluation and optimization of carbon emission for federal edge intelligence network by Peng ZHANG, Yong XIAO, Jiwei HU, Liang LIAO, Jianxin LYU, Zegang BAI

    Published 2024-03-01
    “…In recent years, the continuous evolution of communication technology has led to a significant increase in energy consumption.With the widespread application and deep deployment of artificial intelligence (AI) technology and algorithms in telecommunication networks, the network architecture and technological evolution of network intelligent will pose even more severe challenges to the energy efficiency and emission reduction of future 6G.Federated edge intelligence (FEI), based on edge computing and distributed federated machine learning, has been widely acknowledged as one of the key pathway for implementing network native intelligence.However, evaluating and optimizing the comprehensive carbon emissions of federated edge intelligence networks remains a significant challenge.To address this issue, a framework and a method for assessing the carbon emissions of federated edge intelligence networks were proposed.Subsequently, three carbon emission optimization schemes for FEI networks were presented, including dynamic energy trading (DET), dynamic task allocation (DTA), and dynamic energy trading and task allocation (DETA).Finally, by utilizing a simulation network built on real hardware and employing real-world carbon intensity datasets, FEI networks lifecycle carbon emission experiments were conducted.The experimental results demonstrate that all three optimization schemes significantly reduce the carbon emissions of FEI networks under different scenarios and constraints.This provides a basis for the sustainable development of next-generation intelligent communication networks and the realization of low-carbon 6G networks.…”
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  2. 2

    FedDyH: A Multi-Policy with GA Optimization Framework for Dynamic Heterogeneous Federated Learning by Xuhua Zhao, Yongming Zheng, Jiaxiang Wan, Yehong Li, Donglin Zhu, Zhenyu Xu, Huijuan Lu

    Published 2025-03-01
    “…Prior to this work, few studies have explored the use of optimization algorithms for hyperparameter tuning in federated learning. …”
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    Federated learning system on autonomous vehicles for lane segmentation by Mohab M. Eid Kishawy, Mohamed T. Abd El-Hafez, Retaj Yousri, M. Saeed Darweesh

    Published 2024-10-01
    “…However, one of the bottlenecks of this evolution is providing data that contains different scenarios and scenes to improve the models without exposing the privacy and security of the edge vehicles. …”
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    The Evolution of Ophthalmological Healthcare System in Premature Children by A. V. Tereshhenko, I. G. Trifanenkova, M. S. Tereshhenkova, Yu. A. Yudina, S. V. Isaev, P. L. Volodin, N. N. Yudina, A. A. Vydrina, Yu. A. Sidorova, E. V. Erohina, V. V. Shaulov

    Published 2018-07-01
    “…The purpose is to analyze the stages of ophthalmological healthcare system’s evolution in premature children on the basis of Kaluga branch of FGAU «MNTK “Eye Microsurgery” named after acad. …”
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    STUDY REGARDING CERVIDAE EVOLUTION, IN GIURGIU COUNTY, BETWEEN 2006 - 2015 by Marius MAFTEI, Elena Narcisa POGURSCHI, Iulian VLAD, Lucia NISTOR

    Published 2017-01-01
    “…This is just a partial study for an ample research regarding evolution of species from Cervidae family in Romania. …”
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    A privacy-preserved horizontal federated learning for malignant glioma tumour detection using distributed data-silos. by Shagun Sharma, Kalpna Guleria, Ayush Dogra, Deepali Gupta, Sapna Juneja, Swati Kumari, Ali Nauman

    Published 2025-01-01
    “…Therefore, in the proposed work, a distributed and privacy-preserved horizontal federated learning-based malignant glioma disease detection model has been developed by employing 5 and 10 different clients' architectures in independent and identically distributed (IID) and non-IID distributions. …”
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    Path and Practice of Gap Management in National Parks: A Comparison Between China and the US and Inspirations Therefrom by Yun MA, Siyuan HE

    Published 2025-02-01
    “…In the US, the management of “gap” in federal lands is in alignment with the evolution of historical land policies, which gives birth to “inholding” — non-federal lands surrounded by federally owned territories. …”
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