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Nonwoven fiber materials are materials with multifunctional purposes, and are widely used to make masks for preventing the new Coronavirus Disease 2019. Because of the complexity and particularity of their structure, it becomes difficult to model the penetration and flow characteristics of liquid in nonwoven fiber materials. In this paper, a novel seepage time soft sensor model of nonwoven fabric, based on Monte Carlo (MC), integrating extreme learning machine (ELM) (MCELM) is proposed. The Monte Carlo method is used to expand data samples. Then, an ELM method is used to establish the prediction model of the dyeing time of the nonwoven fiber material overlaps with the porous medium, as well as the insertion degree and height of the different quantity of hides. Compared with the back propagation (BP) neural network and radial basis function (RBF) neural network, the results show that the prediction model based on the MCELM method has significant power in terms of accuracy and prediction speed, which is conducive to the precise and rapid manufacture of nonwoven fiber materials in practical applications between liquid seepage characteristics and structural characteristics of porous media. Furthermore, the relationship between the proposed models has certain value for predicting the behavior and use of nonwoven fiber materials with different structural characteristics and related research processes. [ABSTRACT FROM AUTHOR]

Laser time transfer is of great significance in timing and global time synchronization. However, the temperature drift may occur and affect the delay of the electronics system, optic generation and detection system. This paper proposes a post-processing method for the compensation of temperature-induced system delay, which does not require any changes to the hardware setup. The temperature drift and time stability of the whole system are compared with and without compensation. The results show that the propagation delay drift as high as 240 ps caused by temperature changes is compensated. The temperature drift coefficient was diminished down to ~0.05 ps/°C from ~20.0 ps/°C. The system precision was promoted to ~2 ps from ~11 ps over a time period of 80,000 s. This method performs significant compensation of single-photon laser time transfer system propagation drift and will help to establish an ultra-stable laser time transfer link in space applications. [ABSTRACT FROM AUTHOR]