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Titlebook: Advanced Multimedia and Ubiquitous Engineering; MUE/FutureTech 2018 James J. Park,Vincenzo Loia,Gangman Yi Conference proceedings 2019 Spri

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期刊全稱Advanced Multimedia and Ubiquitous Engineering
期刊簡稱MUE/FutureTech 2018
影響因子2023James J. Park,Vincenzo Loia,Gangman Yi
視頻videohttp://file.papertrans.cn/147/146011/146011.mp4
學(xué)科分類Lecture Notes in Electrical Engineering
圖書封面Titlebook: Advanced Multimedia and Ubiquitous Engineering; MUE/FutureTech 2018 James J. Park,Vincenzo Loia,Gangman Yi Conference proceedings 2019 Spri
影響因子.This book presents the combined proceedings of the 12th International Conference on Multimedia and Ubiquitous Engineering (MUE 2018) and the 13th International Conference on Future Information Technology (Future Tech 2018), both held in Salerno, Italy, April 23 - 25, 2018...The aim of these two meetings was to promote discussion and interaction among academics, researchers and professionals in the field of ubiquitous computing technologies...These proceedings reflect the state of the art in the development of computational methods, involving theory, algorithms, numerical simulation, error and uncertainty analysis and novel applications of new processing techniques in engineering, science, and other disciplines related to ubiquitous computing..
Pindex Conference proceedings 2019
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Nicola J. Corbett,Nigel M. Hooper advantage of agent-based model to simulate the evolution of online social network after privacy leaked. Our result shows the service providers are almost certain to sell some personal data. If users are very attention to their privacy, the service providers more likely sell all the data.
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1876-1100 e 13th International Conference on Future Information Technology (Future Tech 2018), both held in Salerno, Italy, April 23 - 25, 2018...The aim of these two meetings was to promote discussion and interaction among academics, researchers and professionals in the field of ubiquitous computing technolo
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https://doi.org/10.1007/978-94-009-1271-7stics of traffic flow, we divid holiday traffic flow into regular and fluctuant parts. The regular flow is predicted by Long Short-term Memory Model, and the fluctuant flow is forecasted by fluctuation coefficient method. This method can overcome the shortage of historical data, and the effectiveness of this method is verified by the experiments.
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