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Detecting events on time series data generated by sensors has received a great amount of attention with increasingly deployment of variable sensors. In this paper, we propose a novel framework for classifying events upon sensors data called BEC. Given long raw time series and event labels on fuzzy time points, BEC extracts burst-based features to represent the events. There are mainly two important...
It is quite challenging to monitor an ironmaking process because of its special characteristics such as frequent fluctuations and lack of direct measurements. To tackle these issues, a two-stage PCA based monitoring method was proposed in our previous work. However, only one type of operating anomaly was considered and the historical data of one accident was utilized. To further evaluate the performance...
Water quality model is a useful tool to evaluate the future state of river water through evaluation of actual pollution loading or different management options. Based on the human brain physiology research, artificial neural network(ANN), which simulates the structure and mechanism of the human brain, is a kind of dynamic information processing system that eventually achieves certain functions of...
Infrasound is ideally suited to provide essential information of these earthquakes without any invasive measures. This necessitates automatic processing of the data as the captured phenomena need to be sortedbefore further analysis can be undertaken. Extracting the physical characters of different signals by signal processing such as Fourier Transform and Wavelets Transform are generally employed...
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