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Titlebook: Advanced Hybrid Information Processing; 4th EAI Internationa Shuai Liu,Liyun Xia Conference proceedings 2021 ICST Institute for Computer Sc

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期刊全稱Advanced Hybrid Information Processing
期刊簡(jiǎn)稱4th EAI Internationa
影響因子2023Shuai Liu,Liyun Xia
視頻videohttp://file.papertrans.cn/146/145653/145653.mp4
學(xué)科分類Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engi
圖書(shū)封面Titlebook: Advanced Hybrid Information Processing; 4th EAI Internationa Shuai Liu,Liyun Xia Conference proceedings 2021 ICST Institute for Computer Sc
影響因子This two-volume set constitutes the post-conference proceedings of the 4th EAI International Conference on Advanced Hybrid Information Processing, ADHIP 2020, held in Binzhou, China, in September 2020. Due to COVID-19 the conference was held virtually.. The 89 papers presented were selected from 190 submissions and focus on theory and application of hybrid information processing technology for smarter and more effective research and application. The theme of ADHIP 2020 was “Industrial applications of aspects with big data”.. The papers are named in topical sections as follows: Industrial application of multi-modal information processing; Industrialized big data processing; Industrial automation and intelligent control; Visual information processing..
Pindex Conference proceedings 2021
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書(shū)目名稱Advanced Hybrid Information Processing影響因子(影響力)




書(shū)目名稱Advanced Hybrid Information Processing影響因子(影響力)學(xué)科排名




書(shū)目名稱Advanced Hybrid Information Processing網(wǎng)絡(luò)公開(kāi)度




書(shū)目名稱Advanced Hybrid Information Processing網(wǎng)絡(luò)公開(kāi)度學(xué)科排名




書(shū)目名稱Advanced Hybrid Information Processing被引頻次




書(shū)目名稱Advanced Hybrid Information Processing被引頻次學(xué)科排名




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書(shū)目名稱Advanced Hybrid Information Processing年度引用學(xué)科排名




書(shū)目名稱Advanced Hybrid Information Processing讀者反饋




書(shū)目名稱Advanced Hybrid Information Processing讀者反饋學(xué)科排名




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https://doi.org/10.1007/978-3-658-33829-9esults show that, compared with other localization methods, the positioning accuracy of this method is significantly improved, and the localization time of radio frequency signal in wireless sensor networks is shortened.
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Intensivbehandlung in der Chirurgie,me and accuracy of the monitoring method are analyzed experimentally. It is found that the monitoring method can control the delay time within 0.2?s and the monitoring error rate is low. It can be seen that the monitoring algorithm has high performance.
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https://doi.org/10.1007/978-3-642-20473-9ying function of the data is realized, and the capacity ratio of the monitoring data is calculated. Finally, the intelligent upgrading system of the real-time monitoring data expansion capacity is realized.
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Traitement conservateur sans oncoplastie,l results prove the effectiveness of the urban air quality monitoring system based on big data and drone. Applying the system to actual monitoring is beneficial to better analysis of the atmospheric environment and better maintenance of the atmospheric environment.
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