Machine learning algorithm selection for windage alteration fault diagnosis of mine ventilation system

Machine learning algorithms have been widely used in mine fault diagnosis. The correct selection of the suitable algorithms is the key factor that affects the fault diagnosis. However, the impact of machine learning algorithms on the prediction performance of mine fault diagnosis models has not been fully evaluated. In this study, the windage alteration faults (WAFs) diagnosis models, which are based on K-nearest neighbor algorithm (KNN), multi-layer perceptron (MLP), support vector machine (SVM), and decision tree (DT), are constructed. Furthermore, the applicability of these four algorithms in the WAFs diagnosis is explored by a T-type ventilation network simulation experiment and the field empirical application research of Jinchuan No. 2 mine. The accuracy of the fault location diagnosis for the four models in both networks was 100%. In the simulation experiment, the mean absolute percentage error (MAPE) between the predicted values and the real values of the fault volume of the four models was 0.59%, 97.26%, 123.61%, and 8.78%, respectively. The MAPE for the field empirical application was 3.94%, 52.40%, 25.25%, and 7.15%, respectively. The results of the comprehensive evaluation of the fault location and fault volume diagnosis tests showed that the KNN model is the most suitable algorithm for the WAFs diagnosis, whereas the prediction performance of the DT model was the second-best. This study realizes the intelligent diagnosis of WAFs, and provides technical support for the realization of intelligent ventilation.     

Sealing behaviour of glass-based composites for oxygen transport membranes

In this study, seven different filler materials in different proportions were added to a Ba-Ca-Si glass matrix “H” to investigate new sealant with higher thermal expansion coefficient (CTE) value and good sealing performance for application in oxygen transport membrane (OTM). SrTi_0.75Fe_0.25O_3-δ (STF25) was used as an OTM, and the sealing partners were ferritic steel Aluchrom and pre-oxidized Aluchrom. Compatibility tests were carried out to investigate the feasibility of the composites. Higher CTE values were found in dilatometer tests on composite samples by adding 40 wt% Ag (HAg40) and 30 wt% Ni-Cr (HNC30). Gas-tightness measurements of sandwiched samples produced appropriate helium leakage rates in the range of 10^?6 mbar·l·s^?1. Sealing behaviour of sealants HAg40 and HNC30 were investigated by joining STF25 and as-delivered/pre-oxidized Aluchrom together. Scanning electron microscopy (SEM) on cross-sections of the joints revealed a homogeneous microstructure and good adherence of the glass sealants to support metals and STF25.     

Micro-structural study of Yaozhou celadons (Tang to Yuan Dynasty): probing crystalline and glassy phases

The Yaozhou kiln complex is a representative production center of ancient northern China, famous for the celadon production. In this work, bubbles, glassy matrix and residual crystals of celadon glazes produced from the Tang to Yuan Dynasty were analyzed by using optical microscopy, Raman spectroscopy and scanning electron microscopy-energy dispersive X-ray spectroscopy (SEM-EDS). The results revealed that the Song, Jin and Yuan productions present bigger bubble and higher area ratios of the Si-O bending over stretching modes than the Tang and Wudai productions. This is consistent with firings at higher temperatures during Song, Jin and Yuan Dynasties. It is also in agreement with the historical studies, which revealed the change from wood-firing to coal-firing during Song Dynasty. The observation of calcium phosphate in Yaozhou productions indicated that the glaze ash had been used. No iron-based particle was identified by Raman spectroscopy in the glazes of all periods. The green color is certainly due to iron ion dispersed in the glassy matrix. Our study also confirmed no significant change in glaze raw materials used for Yaozhou productions from Tang to Yuan Dynasty.     

Design and Fabrication of Concentration‐Gradient Generators with Two and Three Inlets in Microfluidic Chips

A simple and low‐cost method for designing and fabricating concentration‐gradient generators with two and three inlets is proposed which can generate different concentration gradients at varying flow velocities. The microchannel structure was designed in S‐shape and left‐right symmetry. The concentration‐gradient generator was simulated based on the finite element method. The microchannels were processed on a computer numerical control (CNC) engraving and milling machine on poly(methylmethacrylate) substrate, and then two concentration‐gradient generators were fabricated by hot bonding technology. The results of experiment and simulation were compared to prove the feasibility of the method. Flow velocity was an important factor for generating different concentration gradients. The concentration‐gradient profiles of the generators with two and three inlets present approximately linear and quadratic curves.     

Image and Feature Space Based Domain Adaptation for Vehicle Detection

The application of deep learning in the field of object detection has experienced much progress. However, due to the domain shift problem, applying an off-the-shelf detector to another domain leads to a significant performance drop. A large number of ground truth labels are required when using another domain to train models, demanding a large amount of human and financial resources. In order to avoid excessive resource requirements and performance drop caused by domain shift, this paper proposes a new domain adaptive approach to cross-domain vehicle detection. Our approach improves the cross-domain vehicle detection model from image space and feature space. We employ objectives of the generative adversarial network and cycle consistency loss for image style transfer in image space. For feature space, we align feature distributions between the source domain and the target domain to improve the detection accuracy. Experiments are carried out using the method with two different datasets, proving that this technique effectively improves the accuracy of vehicle detection in the target domain.     

Formation of γ-LiAlO2 nano-network in an Al-based metal matrix composite

We report the synthesis of a nanostructured γ-LiAlO₂ network in an Al-based metal matrix composite (MMC) by arc-melting a powder compact of Al–15 wt.%Li₂O. During synthesis, chemical reactions between Al and Li₂O occurred, and a two-phase Al-γ-LiAlO₂ MMC was produced. The γ-LiAlO₂ was in the form of nano-network extended evenly in the Al matrix. The apparent density and Vickers' hardness number of the MMC were determined to be 2.31 gcm^− 3 and 143, respectively, and having a relative density of 0.87. The MMC was made nano-porous by etching away Al with a 2 M NaOH solution. The sizes of pores were about 150 nm and the width of the branches in the γ-LiAlO₂ network was about 90 nm. Atomic force microscopy revealed that the branches were composed of fine grains of 50 nm in diameter. Microstructure of the network was not altered even after prolonged etching, and this suggested that γ-LiAlO₂ was chemically inert to NaOH corrosion. Specific surface area of the γ-LiAlO₂ nano-network was measured to be 79 m²/g, and its porosity was determined to be 43.7%.     

An improved global-best harmony search algorithm for faster optimization

In this paper, an improved global-best harmony search algorithm, named IGHS, is proposed. In the IGHS algorithm, initialization based on opposition-based learning for improving the solution quality of the initial harmony memory, a new improvisation scheme based on differential evolution for enhancing the local search ability, a modified random consideration based on artificial bee colony algorithm for reducing randomness of the global-best harmony search (GHS) algorithm, as well as two perturbation schemes for avoiding premature convergence, are integrated. In addition, two parameters of IGHS, harmony memory consideration rate and pitch adjusting rate, are dynamically updated based on a composite function composed of a linear time-varying function, a periodic function and a sign function in view of approximate periodicity of evolution in nature. Experimental results tested on twenty-eight benchmark functions indicate that IGHS is far better than basic harmony search (HS) algorithm and GHS. In further study, IGHS has also been compared with other eight well known metaheuristics. The results show that IGHS is better than or at least similar to those approaches on most of test functions.     

面向钢轨监测的无线传感器网络网关设计与性能测试

针对我国铁路钢轨实时广域监测的重大需求,通过研究异构无线传感器网络（WSNs）通信技术,设计并实现了一种基于Zig Bee-3G通信的无线传感器网络网关.进行了通信电路设计和电磁兼容设计,并在WinCE操作系统平台上实现了Zig Bee网络与3G网络之间的互联,开发了网关远程维护管理模块.对网关设备分别进行了网络传输性能测试和电磁兼容测试,测试结果表明：此网关传输效率高、抗电磁干扰能力强,能够满足铁路轨道监测现场的应用要求.     

1D helical ZnII metal–organic polymers: Syntheses,structures and fluorescent properties

Hydrothermal reactions of 1,1′-(1,5-pentanediyl)bis-1H-benzimidazole (pbbm) with ZnCl₂ afford two 1D helical metal–organic polymers {[ZnCl₂(pbbm)] · (H₂O)_1/8}_n (1) and {[Zn(pbbm)₂] · Cl₂ · (H₂O)_1/2}_n (2). Polymer 1 features a 1D single helical architecture, whereas 2 possesses a 1D cationic double helical chain framework. Photoluminescence investigations reveal that both of them display strong emissions in the solid state at room temperature, which could originate from a ligand-to-ligand charge-transfer (LLCT) transition, as confirmed by the molecular orbital (MO) calculations.