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派博传思国际中心 »期刊书目

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Titlebook: Edge Computing and IoT: Systems, Management and Security; Second EAI Internati Kaishun Wu,Lu Wang,Yanjiao Chen Conference proceedings 2022

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发表于 2025-3-21 16:08:17 | 显示全部楼层 |阅读模式
书目名称Edge Computing and IoT: Systems, Management and Security
副标题Second EAI Internati
编辑Kaishun Wu,Lu Wang,Yanjiao Chen
视频video
丛书名称Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engi
图书封面Titlebook: Edge Computing and IoT: Systems, Management and Security; Second EAI Internati Kaishun Wu,Lu Wang,Yanjiao Chen Conference proceedings 2022
描述This book constitutes the refereed post-conference proceedings of the 2nd International Conference on Edge Computing and IoT, ICECI 2021, held in December 2021 in Shenzhen, China. Due to COVID-19 pandemic the conference was held virtually. The explosion of the big data generated by ubiquitous edge devices motivates the emergence of applying machine learning systems for edge computing and Internet of Things (IoT) services. Machine learning techniques are delivering a promising solution to the industry for building IoT systems and to make innovation at a rapid pace. The 12 full papers of ICECI 2021 were selected from 26 submissions and present results and ideas in the area of edge computing and IoT.
出版日期Conference proceedings 2022
关键词artificial intelligence; communication channels (information theory); communication systems; computer h
版次1
doihttps://doi.org/10.1007/978-3-031-04231-7
isbn_softcover978-3-031-04230-0
isbn_ebook978-3-031-04231-7Series ISSN 1867-8211 Series E-ISSN 1867-822X
issn_series 1867-8211
copyrightICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering 2022
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Matching with Externalities for Device Assignment in IoT Sharding Blockchaints of devices, we consider the matching model with externalities. We propose an algorithm to find a stable matching and prove its convergence and stability. The simulation results indicate that the algorithm converges efficiently. Besides, the proposed algorithm has better performance than random as
MIRTH
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hermitage
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Intelligent Vocal Training Assistant System build this system, we constructed a vowel data set classified by degree vocal cords closure, including the wearable sensors and mobile phone microphones we used. We compared the performance of the traditional vocalization pattern classification method and the convolutional neural network method we
Adornment
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Wearable-Based Human Emotion Inference System object and implement an emotion recognition to explore deep context innovatively. The experimental results show that MW-Emotion has a recognition accuracy of 85.1% for person-dependent mode. The framework uses the method that different types of data are effectively fused through signal processing.
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Children‘s Play and Learning in Brazilmaximize the overall benefit. Finally, this paper verifies the proposed carbon-trading mechanism for private car through simulation design, and the results show that carbon-trading mechanism for private cars driven by green transition designed in this paper is feasible. It can play a certain role in
congenial
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