Denoising stacked autoencoders-based near-infrared quality monitoring method via robust samples evaluation

This paper proposes a denoising stacked autoencoders-based near-infrared spectroscopy on-line quality monitoring model via robust sample evaluation. The previous related work tends to focus on the near infrared spectrum data from the high dimension, multicollinearity, and information redundancy, and so on, but pays less attention to its inherent nonlinearity and sensitivity caused by internal and external factors (i.e., particle size, colour, moisture, uniformity, temperature, and so on). First, this paper aims to achieve feature extraction in nonlinearity with a denoising stack autoencoder, overcoming the impact of over-sensitivity described as given distributed noise. Second, we propose a robust sample evaluation method derived from the robust statistics to tell and eliminate the individual samples contrary to the potentially statistical rules learned by the established model from the population samples and retrain the model with a more robust training set. The near-infrared spectrum data derived from the distillation process of 2, 6 xylenol are used as a case in this paper to verify the validity and accuracy of the monitoring model proposed above.     

Multi-Unit Needleless Electrospinning for One-Step Construction of 3D Waterproof MF-PVA Nanofibrous Membranes as High-Performance Air Filters

The airborne particulate matter (PM) seriously threatens people's health. Personal protective equipment with electrospun nanofibers is an effective method to make people away from air pollutants. Herein, 3D waterproof melamine-formaldehyde polyvinyl alcohol (MF-PVA) nanofibrous membranes are fabricated by a one-step method combining multi-unit needleless electrospinning and a thermal treatment device in a line. 3D nanofibrous structures can be controlled by adjusting the solution concentration of each unit. The PVA nanofibrous membranes become waterproof after cross-linking with MF resin in the following thermal treatment device. The optimized MF-PVA nanofibrous membrane shows excellent air filtration performance (97.3% for PM_0.3, 100% for PM_1.0, and 100% for PM_2.5) and low air resistance (76 Pa). These 3D waterproof MF-PVA nanofibrous membranes exhibit ultra-stable performance in various practical environments.     

Quasi-Phase Equilibrium Prediction of Multi-Element Alloys Based on Machine Learning and Deep Learning

In this study, a phase field model is established to simulate the microstructure formation during the solidification of dendrites by taking the Al-Cu-Mg ternary alloy as an example, and machine learning and deep learning methods are combined with the Kim-Kim-Suzuki (KKS) phase field model to predict the quasi-phase equilibrium. The paper first uses the least squares method to obtain the required data and then applies eight machine learning methods and five deep learning methods to train the quasi-phase equilibrium prediction models. After obtaining different models, this paper compares the reliability of the established models by using the test data and uses two evaluation criteria to analyze the performance of these models. This work find that the performance of the established deep learning models is generally better than that of the machine learning models, and the Multilayer Perceptron (MLP) based quasi-phase equilibrium prediction model achieves the best performance. Meanwhile the Convolutional Neural Network (CNN) based model also achieves competitive results. The experimental results show that the model proposed in this paper can predict the quasi-phase equilibrium of the KKS phase-field model accurately, which proves that it is feasible to combine machine learning and deep learning methods with phase-field model simulation.     

集中式MIMO雷达多模式一体化波形设计

集中式多输入多输出（multiple input multiple output, MIMO）雷达系统基于波形分集优势，可灵活改变发射方向图形状和指向方向空间合成信号的特性，从而实现多种雷达工作模式。提出了一种集中式MIMO雷达多模式一体化波形设计方法，采用方向图模板拟合、模糊函数模板拟合以及通信波形拟合的方式优化不同方向上的合成信号，使其具有不同特性，从而在单脉冲时间内实现搜索、跟踪和通信功能。采用最大块增量优化算法对构造的恒模四次多项式优化模型求解。实验结果表明，该方法可以得到具有低旁瓣模糊函数的搜索与跟踪波形，并且满足通信需求。     

磁性纳米片的制备及功能化应用研究进展

磁性纳米片因其独特的性质已在磁共振成像、微波吸收、催化剂、电池、吸附净化等领域受到了广泛关注。该文归纳了磁性纳米片的制备方法以及功能化应用方向，阐述了不同制备方法对磁性纳米片的形貌、大小以及厚度的影响。归纳了磁性纳米片的合成机理以及性能调控因素，为其规模化制备提供理论支持。此外，着重介绍了磁性纳米片在各个领域的功能化应用进展，总结出磁性纳米片基本性质及功能化改性后的作用行为对进一步应用的意义。最后，对磁性纳米片研究中亟待解决的问题以及未来的研究方向进行了展望。