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Characterizing and understanding the structure and the evolution of networks is an important problem for many different fields. While in the real-world networks, especially the spatial networks, the influence from one node to another tends to vary over both space and time due to the different space distances and propagation speeds between nodes. Thus the time lag plays an essential role in interpreting...
Nonparametric regression is a classic method for short-term traffic flow forecasting in Intelligent Transportation Systems (ITS). Feature space construction and distance metric selection are two important parts in nonparametric regression. Few of previous works have taken both these two aspects into account together. In addition, how to use information of related stations in network scale is a key...
Learning temporal causal structures between time series is one of key tools for analyzing time series data. Most previous works focuse on learning with static temporal causal relationships. However, in many real world applications, such as climate environment and transportation system, the causal structures vary dramatically over time. In this paper, we propose a probabilistic dynamic causal (PDC)...
ZigBee technology is an emerging wireless network technology with merits such as short-range, low-power and low-cost, which is mainly used for short-range wireless communications. To meet the current need in the fields of archaeology and guardianship of the nursing home, an intelligent alarm and positioning system based on ZigBee wireless network is developed. The alarm circuit whose main part is...
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