A quasi-current representation for information needs inspired by Two-State Vector Formalism

Recently, a number of quantum theory (QT)-based information retrieval (IR) models have been proposed for modeling session search task that users issue queries continuously in order to describe their evolving information needs (IN). However, the standard formalism of QT cannot provide a complete description for users’ current IN in a sense that it does not take the ‘future’ information into consideration. Therefore, to seek a more proper and complete representation for users’ IN, we construct a representation of quasi-current IN inspired by an emerging Two-State Vector Formalism (TSVF). With the enlightenment of the completeness of TSVF, a “two-state vector” derived from the ‘future’ (the current query) and the ‘history’ (the previous query) is employed to describe users’ quasi-current IN in a more complete way. Extensive experiments are conducted on the session tracks of TREC 2013 & 2014, and show that our model outperforms a series of compared IR models

Piezoelectric/Triboelectric Nanogenerators for Biomedical Applications

Bodily movements can be used to harvest electrical energy via nanogenerators and thereby enable self-powered healthcare devices. In this chapter, first we summarize the requirements of nanogenerators for the applications in biomedical fields. Then, the current applications of nanogenerators in the biomedical field are introduced, including self-powered sensors for monitoring body activities; pacemakers; cochlear implants; stimulators for cells, tissues, and the brain; and degradable electronics. Remaining challenges to be solved in this field and future development directions are then discussed, such as increasing output performance, further miniaturization, encapsulation, and improving stability. Finally, future outlooks for nanogenerators in healthcare electronics are reviewed

Hermite Positive Definite Solution of a Class of Matrix Equation

AbstractIn this paper, the Hermite positive definite solutions of the nonlinear matrix equation XS+A*X−tA=Q are discussed. A sufficient condition and two necessary and sufficient conditions for the existence of Hermite positive definite solutions for this equation are derived. The existence of minimal Hermite positive definite solution is also studied here, and an iterative method for obtaining the minimal Hermite positive definite solution is given

Multi-hierarchical Convolutional Network for Efficient Remote Photoplethysmograph Signal and Heart Rate Estimation from Face Video Clips

Heart beat rhythm and heart rate (HR) are important physiological parameters of the human body. This study presents an efficient multi-hierarchical spatio-temporal convolutional network that can quickly estimate remote physiological (rPPG) signal and HR from face video clips. First, the facial color distribution characteristics are extracted using a low-level face feature Generation (LFFG) module. Then, the three-dimensional (3D) spatio-temporal stack convolution module (STSC) and multi-hierarchical feature fusion module (MHFF) are used to strengthen the spatio-temporal correlation of multi-channel features. In the MHFF, sparse optical flow is used to capture the tiny motion information of faces between frames and generate a self-adaptive region of interest (ROI) skin mask. Finally, the signal prediction module (SP) is used to extract the estimated rPPG signal. The experimental results on the three datasets show that the proposed network outperforms the state-of-the-art methods.Comment: 33 pages,9 figure