Xi'an Jiaotong University

About: Xi'an Jiaotong University is a education organization based out in Xi'an, China. It is known for research contribution in the topics: Heat transfer & Dielectric. The organization has 85440 authors who have published 99682 publications receiving 1579683 citations. The organization is also known as: '''Xi'an Jiaotong University''' & Xi'an Jiao Tong University.

A Deep Learning Scheme for Motor Imagery Classification based on Restricted Boltzmann Machines

Abstract: Motor imagery classification is an important topic in brain–computer interface (BCI) research that enables the recognition of a subject’s intension to, e.g., implement prosthesis control. The brain dynamics of motor imagery are usually measured by electroencephalography (EEG) as nonstationary time series of low signal-to-noise ratio. Although a variety of methods have been previously developed to learn EEG signal features, the deep learning idea has rarely been explored to generate new representation of EEG features and achieve further performance improvement for motor imagery classification. In this study, a novel deep learning scheme based on restricted Boltzmann machine (RBM) is proposed. Specifically, frequency domain representations of EEG signals obtained via fast Fourier transform (FFT) and wavelet package decomposition (WPD) are obtained to train three RBMs. These RBMs are then stacked up with an extra output layer to form a four-layer neural network, which is named the frequential deep belief network (FDBN). The output layer employs the softmax regression to accomplish the classification task. Also, the conjugate gradient method and backpropagation are used to fine tune the FDBN. Extensive and systematic experiments have been performed on public benchmark datasets, and the results show that the performance improvement of FDBN over other selected state-of-the-art methods is statistically significant. Also, several findings that may be of significant interest to the BCI community are presented in this article.

Convolutional Sparse Coding for Image Super-Resolution

Abstract: Most of the previous sparse coding (SC) based super resolution (SR) methods partition the image into overlapped patches, and process each patch separately. These methods, however, ignore the consistency of pixels in overlapped patches, which is a strong constraint for image reconstruction. In this paper, we propose a convolutional sparse coding (CSC) based SR (CSC-SR) method to address the consistency issue. Our CSC-SR involves three groups of parameters to be learned: (i) a set of filters to decompose the low resolution (LR) image into LR sparse feature maps, (ii) a mapping function to predict the high resolution (HR) feature maps from the LR ones, and (iii) a set of filters to reconstruct the HR images from the predicted HR feature maps via simple convolution operations. By working directly on the whole image, the proposed CSC-SR algorithm does not need to divide the image into overlapped patches, and can exploit the image global correlation to produce more robust reconstruction of image local structures. Experimental results clearly validate the advantages of CSC over patch based SC in SR application. Compared with state-of-the-art SR methods, the proposed CSC-SR method achieves highly competitive PSNR results, while demonstrating better edge and texture preservation performance.

High-entropy ceramics: Present status, challenges, and a look forward

Abstract: High-entropy ceramics (HECs) are solid solutions of inorganic compounds with one or more Wyckoff sites shared by equal or near-equal atomic ratios of multi-principal elements. Although in the infant stage, the emerging of this new family of materials has brought new opportunities for material design and property tailoring. Distinct from metals, the diversity in crystal structure and electronic structure of ceramics provides huge space for properties tuning through band structure engineering and phonon engineering. Aside from strengthening, hardening, and low thermal conductivity that have already been found in high-entropy alloys, new properties like colossal dielectric constant, super ionic conductivity, severe anisotropic thermal expansion coefficient, strong electromagnetic wave absorption, etc., have been discovered in HECs. As a response to the rapid development in this nascent field, this article gives a comprehensive review on the structure features, theoretical methods for stability and property prediction, processing routes, novel properties, and prospective applications of HECs. The challenges on processing, characterization, and property predictions are also emphasized. Finally, future directions for new material exploration, novel processing, fundamental understanding, in-depth characterization, and database assessments are given.

Ultrahigh energy storage density lead-free multilayers by controlled electrical homogeneity

Abstract: Ultrahigh discharge energy density (Wdis = 10.5 J cm−3) and efficiency (η = 87%) have been obtained in doped BiFeO3–BaTiO3 ceramic multilayers by achieving an electrically rather than chemically homogeneous microstructure. Back scattered scanning and transmission electron microscopy combined with energy dispersive X-ray spectroscopy mapping of (0.7 − x)BiFeO3–0.3BaTiO3–xNd(Zn0.5Zr0.5)O3 (0.05 ≤ x ≤ 0.10) ceramics revealed a core–shell grain structure which switched from a bright to dark contrast as x increased. Compositions with x = 0.08 were at the point of cross over between these two manifestations of core–shell contrast. Dielectric measurements together with the absence of macrodomains in diffraction contrast TEM images suggested that compositions with x = 0.08 exhibited relaxor behaviour within both the core and shell regions. Impedance spectroscopy demonstrated that, despite being chemical dissimilar, the grains were electrically homogeneous and insulating with little evidence of conductive cores. Multilayers of x = 0.08 had enhanced breakdown strength, EBDS > 700 kV cm−1 and a slim hysteresis loop which resulted in large Wdis and high η which were temperature stable to <15% from 25 to 150 °C.