Deep fusion of multi-channel neurophysiological signal for emotion recognition and monitoring

How to fuse multi-channel neurophysiological signals for emotion recognition is emerging as a hot research topic in community of Computational Psychophysiology. Nevertheless, prior feature engineering based approaches require extracting various domain knowledge related features at a high time cost. Moreover, traditional fusion method cannot fully utilise correlation information between different channels and frequency components. In this paper, we design a hybrid deep learning model, in which the 'Convolutional Neural Network (CNN)' is utilised for extracting task-related features, as well as mining inter-channel and inter-frequency correlation, besides, the 'Recurrent Neural Network (RNN)' is concatenated for integrating contextual information from the frame cube sequence. Experiments are carried out in a trial-level emotion recognition task, on the DEAP benchmarking dataset. Experimental results demonstrate that the proposed framework outperforms the classical methods, with regard to both of the emotional dimensions of Valence and Arousal

Changes of pore structure and chloride content in cement pastes after pore solution expression

Pore solution expression is a widely accepted approach to extract pore solution of cement-based materials by appllying high pressure. In this study, the variations of pore solution distribution and chloride content in cement pastes before and after pore solution expression were examined. The results showed that the value of chloride concentration index N-c were mostly higher than 1.0 for cement pastes immersed in NaCl solution, and decreased with the chloride concentration of soaking solution and water-to-binder (w/b) ratio. During the pore solution expression, the pores larger than 40 nm were totally removed and the porosity of smaller pore was decreased. Based on a proposed physical model on structure of cement paste, the value of N-c was calculated according to the variations of pore structure and chloride content during pore solution expression. The calculated results showed similar trend as the experimental results obtained by pore solution expression method