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Titlebook: Ubiquitous Computing and Ambient Intelligence; 11th International C Sergio F. Ochoa,Pritpal Singh,José Bravo Conference proceedings 2017 Sp

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發(fā)表于 2025-3-28 17:15:45 | 只看該作者
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發(fā)表于 2025-3-29 04:51:34 | 只看該作者
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發(fā)表于 2025-3-29 10:15:58 | 只看該作者
A Dictionary Based Protocol over LoRa (Long Range) Technology for Applications in Internet of Thingsics equipment, sharing information and enabling interaction with them from anywhere. A very important aspect in IoT applications is the communication protocols used by sensors for sending and exchange information. Traditional protocols used so far do not have the scope and ability to manage a growin
46#
發(fā)表于 2025-3-29 15:20:50 | 只看該作者
Improving Tourist Experience Through an IoT Application Based on FatBeaconson where no Internet connection is available. Rather than advertising a URL to load a web page, the FatBeacon protocol has the ability to broadcast any basic web contents actually hosted on the device. In particular, FatBeacons are here used to improve the tourist experience in places with no Intern
47#
發(fā)表于 2025-3-29 17:53:52 | 只看該作者
Protecting Industry 4.0 Systems Against the Malicious Effects of Cyber-Physical Attacks traditional definition of “cyber-attack” is not enough to represent all the situations may occur. Furthermore, traditional security policies and defense strategies are not designed to be effective in scenarios mixing cyber and physical elements. In this context, this work presents a new idea about
48#
發(fā)表于 2025-3-29 22:31:32 | 只看該作者
Fuzzy-Based Approach of Concept Alignmenttching use mapping approaches in order to achieve interoperability between heterogeneous sources. The use of multiple similarity measures that take into account lexical, structural and semantic properties of the concepts is often found in schema matching for the purpose of data integration, sharing
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發(fā)表于 2025-3-30 03:14:47 | 只看該作者
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發(fā)表于 2025-3-30 05:36:51 | 只看該作者
IOT Service Recommendation Strategy Based on Attribute Relevanced device service are computed, and the recommendation system is recommended based on the calculation results. In order to solve the cold start problem, we propose the tensor linear regression model. The experiment results show the recommendation strategy was effective.
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