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Nowadays, the message diffusion links among users or Web sites drive the development of countless innovative applications. However, in reality, it is easier for us to observe the time stamps when different nodes in the network react on a message, while the connections empowering the diffusion of the message remain hidden. This motivates recent extensive studies on the network inference problem: unveiling the edges from the records of messages disseminated through them. Existing solutions are computationally expensive, which motivates us to develop an efficient two-step general framework, Clustering Embedded Network Inference(CENI). CENI integrates clustering strategies to improve the efficiency of network inference. By clustering nodes directly on the time lines of messages, we propose two naive implementations of CENI: Infection-centric CENIand Cascade-centric CENI. Additionally, we point out the critical dimensionproblem of CENI: Instead of one-dimensional time lines, we need to first project the nodes to an Euclidean space of certain dimension before clustering. A CENI adopting clustering method on the projected space can better preserve the structure hidden in the cascades and generate more accurately inferred links. By addressing the critical dimension problem, we propose the third implementation of the CENI framework: Projection-based CENI. Through extensive experiments on two real datasets, we show that the three CENI models only need around 20–50 % of the running time of state-of-the-art methods. Moreover, the inferred edges of Projection-based CENI preserve or even outperform the effectiveness of state-of-the-art methods.

In the boiler combustion of power plants, the smoke loss is the main combustion heat loss of the boiler. Reducing the exhaust gas temperature is one of the main means to reduce the heat loss of the exhaust gas, and it is also the main measure for improving the thermal efficiency of the boiler in each power plant. This paper summarizes and discusses the application and economics of installing composite phase change heat exchangers for coal-fired boilers.