The internet of things （loT） attracts great interest in many application domains concerned with monitoring and ：ontrol of physical phenomena. However, application devel- opment is still one of the main hurdles to a...
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The internet of things （loT） attracts great interest in many application domains concerned with monitoring and ：ontrol of physical phenomena. However, application devel- opment is still one of the main hurdles to a wide adoption of IoT technology. Application development is done at a low level, very close to the operating system and requires pro- grammers to focus on low-level system issues. The under- lying APIs can be very complicated and the amount of data collected can be huge. This can be very hard to deal with as a developer. In this paper, we present a runtime model based approach to IoT application development. First, the manage- ability of sensor devices is abstracted as runtime models that are automatically connected with the corresponding systems. Second, a customized model is constructed according to a personalized application scenario and the synchronization be- tween the customized model and sensor device runtime mod- els is ensured through model transformation. Thus, all the application logic can be carried out by executing programs on the customized model. An experiment on a real-world ap- plication scenario demonstrates the feasibility, effectiveness, and benefits of the new approach to IoT application develop- ment.
Based on thin-film lithium niobate platform, we experimentally demonstrate an endless automatic polarization controller which only requires a driving voltage range of 10 V, and achieves a polarization tracking speed o...
The temperature sensor network in intelligent building classified collection of big data processing has the problem of big data redundancy interference, which results in unable to determine the fixed filter thresholds...
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The maximum clique problem is to find the maximum sized clique of pairwise adjacent vertices in a given graph, which is a NP-Complete problem. In this paper, an effective parallel hybrid genetic algorithm is proposed,...
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Graph coloring problem is a well-known NP-complete problem in graph theory. Because GCP often finds its applications to various engineering fields, it is very important to find a feasible solution quickly. In this pap...
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Recently, password based authenticated key exchange (or called PAKE for short) with chaotic maps has been received much attention for researchers. In 2013, Xie et al. proposed a three party PAKE scheme (based on chaot...
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Due to the energy limitation of sensor nodes, energy efficiency is one of the main concerns in the design of wireless body area networks (WBANs). Power control plays an important role in reducing network interference ...
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ISBN:
(纸本)9781509047444
Due to the energy limitation of sensor nodes, energy efficiency is one of the main concerns in the design of wireless body area networks (WBANs). Power control plays an important role in reducing network interference and resource management in WBANs. The task of power control is to achieve a certain goal by making use of smaller and suitable power transmission, which depends on the application and network distribution, including interference reduction, throughput maximization, QoS guarantee, topology control, and so on. This paper, using stochastic geometry, develop new nearest neighbor distance power control to increase the energy efficiency of WBANs coexistence.
In this paper, a Price learning based Load Distribution Strategy (PLDS) is proposed at first. In PLDS model, Smart Power Service, Utility Company and History Load Curves are included, and by considering both the avera...
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Microblog is a social platform with huge user community and mass data. We propose a semantic recommendation mechanism based on sentiment analysis for microblog. Firstly, the keywords and sensibility words in this mech...
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Microblog is a social platform with huge user community and mass data. We propose a semantic recommendation mechanism based on sentiment analysis for microblog. Firstly, the keywords and sensibility words in this mechanism are extracted by natural language processing including segmentation, lexical analysis and strategy selection. Then, we query the background knowledge base based on linked open data （LOD） with the basic information of users. The experiment result shows that the accuracy of recommendation is within the range of 70% -89% with sentiment analysis and semantic query. Compared with traditional recommendation method, this method can satisfy users＇ requirement greatly.
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