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Time to forge ahead:The Internet of Things for healthcare

Digital Communications and Networks 2023年第1期9卷 223-235页

作者： Denzil Furtado Andre F.Gygax chien aun chan Ashley I.Bush Melbourne Dementia Research Centre&Department of Chemical Engineering University of MelbourneVIC3010Australia Faculty of Business and Economics University of MelbourneVIC3010Australia Department of Electrical and Electronic Engineering University of MelbourneVIC3010Australia Florey Institute of Neuroscience and Mental Health University of MelbourneVIC3010Australia

Situated at the intersection of technology and medicine,the Internet of Things(IoT)holds the promise of addressing some of healthcare's most pressing challenges,from medical error,to chronic drug shortages,to overburdened hospital systems,to dealing with the COVID-19 ***,despite considerable recent technological advances,the pace of successful implementation of promising IoT healthcare initiatives has been *** inspire more productive collaboration,we present here a simple—but surprisingly underrated—problemoriented approach to developing healthcare *** further assist in this effort,we reviewed the various commercial,regulatory,social/cultural,and technological factors in the development of the *** propose that fog computing—a technological paradigm wherein the burden of computing is shifted from a centralized cloud server closer to the data source—offers the greatest promise for building a robust and scalable healthcare IoT *** this end,we explore the key enabling technologies that underpin the fog architecture,from the sensing layer all the way up to the *** is our hope that ongoing advances in sensing,communications,cryptography,storage,machine learning,and artificial intelligence will be leveraged in meaningful ways to generate unprecedented medical intelligence and thus drive improvements in the health of many people.

关键词： Internet of Things Healthcare Information Fog computing Artificial intelligence Machine learning Big data COVID-19 pandemic

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A semantic and emotion-based dual latent variable generation model for a dialogue system

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CAAI Transactions on Intelligence Technology 2023年第2期8卷 319-330页

作者： Ming Yan Xingrui Lou chien aun chan Yan Wang Wei Jiang State Key Laboratory of Media Convergence and Communication Communication University of ChinaBeijingChina School of Information and Communications Engineering Communication University of ChinaBeijingChina Key Laboratory of Acoustic Visual Technology and Intelligent Control System Communication University of ChinaBeijingChina Department of Electrical and Electronic Engineering The University of MelbourneMelbourneVictoriaAustralia School of Data Science and Intelligent Media Communication University of ChinaBeijingChina

With the development of intelligent agents pursuing humanisation,artificial intelligence must consider emotion,the most basic spiritual need in human *** emotional dialogue systems usually use an external emotional dictionary to select appropriate emotional words to add to the response or concatenate emotional tags and semantic features in the decoding step to generate appropriate ***,selecting emotional words from a fixed emotional dictionary may result in loss of the diversity and consistency of the *** propose a semantic and emotion-based dual latent variable generation model(Dual-LVG)for dialogue systems,which is able to generate appropriate emotional responses without an emotional *** from previous work,the conditional variational autoencoder(CVAE)adopts the standard transformer ***,Dual-LVG regularises the CVAE latent space by introducing a dual latent space of semantics and *** content diversity and emotional accuracy of the generated responses are improved by learning emotion and semantic features ***,the average attention mechanism is adopted to better extract semantic features at the sequence level,and the semi-supervised attention mechanism is used in the decoding step to strengthen the fusion of emotional features of the *** results show that Dual-LVG can successfully achieve the effect of generating different content by controlling emotional factors.

关键词： conditional variational autoencoder dual latent space emotional responses latent variable generation

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PECS: Towards Personalized Edge Caching for Future Service-Centric Networks

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China Communications 2019年第9期16卷 93-106页

作者： Ming Yan Wenwen Li chien aun chan Sen Bian Chih-Lin I André F. Gygax School of Information and Telecommunications Engineering Communication University of ChinaBeijing 100024China Green Communication Research Center China Mobile Research InstituteBeijing 100053China Department of Electrical and Electronic Engineering University of MelbourneVictoria 3010Australia Department of Finance Faculty of Business and EconomicsUniversity of MelbourneVictoria 3010Australia

Mobile operators face the challenge of how to best design a service-centric network that can effectively process the rapidly increasing number of bandwidth-intensive user requests while providing a higher quality of experience(QoE). Existing content distribution networks(CDN) and mobile content distribution networks(mCDN) have both latency and throughput limitations due to being multiple network hops away from end-users. Here, we first propose a new Personalized Edge Caching System(PECS) architecture that employs big data analytics and mobile edge caching to provide personalized service access at the edge of the mobile network. Based on the proposed system architecture, the edge caching strategy based on user behavior and trajectory is analyzed. Employing our proposed PECS strategies, we use data mining algorithms to analyze the personalized trajectory and service usage patterns. Our findings provide guidance on how key technologies of PECS can be employed for current and future networks. Finally, we highlight the challenges associated with realizing such a system in 5G and beyond.

关键词： big data data mining edge caching content network personalized edge caching

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移动互联网业务对基站能耗的影响

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电信科学 2015年第10期31卷 158-164页

作者：李雯雯边森 chien aun chan 邵泽才中国移动通信有限公司研究院绿色通信技术研究中心北京100053 澳大利亚墨尔本大学通信能效中

快速发展的移动互联网业务,为运营商带来了诸多挑战,业务特性与网络能耗之间的映射关系尚属空白。为了准确评估业务对网络资源的影响以及网络设备由此产生的能耗,深入物理层资源粒度,提出一种改进的"二次线性映射"模型及四步建模思路,... 详细信息

快速发展的移动互联网业务,为运营商带来了诸多挑战,业务特性与网络能耗之间的映射关系尚属空白。为了准确评估业务对网络资源的影响以及网络设备由此产生的能耗,深入物理层资源粒度,提出一种改进的"二次线性映射"模型及四步建模思路,同时选取了11种典型业务场景,定量评估数据、信令分别消耗的网络资源和能耗大小,便于业务能耗的精细化管理和运营管控,为降低端到端资源开销和业务能耗打下基础。

关键词：移动互联网业务能耗模型信令

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