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.     

Investigation on thermal conductivity and mechanical properties of Si3N4 ceramics via one-step sintering

High thermal conductivity Si₃N₄ ceramics were fabricated using a one-step method consisting of reaction-bonded Si₃N₄ (RBSN) and post-sintering. The influence of Si content on nitridation rate, β/(α+β) phase rate, thermal conductivity and mechanical properties was investigated in this work. It is of special interest to note that the thermal conductivity showed a tendency to increase first and then decrease with increasing Si content. This experimental result shows that the optimal thermal conductivity and fracture toughness were obtained to be 66 W (m K)^-1 and 12.0 MPa m^1/2, respectively. As a comparison, the nitridation rate and β/(α+β) phase rate in a static pressure nitriding system, i.e., 97% (MS10), 97% (MS15), 97% (MS20) and 8.3% (MS10), 8.3% (MS15), 8.9% (MS20), respectively, have obvious advantages over those in a flowing nitriding system, i.e., 91% (MS10), 91% (MS15), 93% (MS20) and 3.1% (MS10), 3.3% (MS15), 3.3% (MS20), respectively. Moreover, high lattice integrity of the β-Si₃N₄ phase was observed, which can effectively confine O atoms into the β-Si₃N₄ lattice using MgO as a sintering additive. This result indicates that one-step sintering can provide a new route to prepare Si₃N₄ ceramics with a good combination of thermal conductivity and mechanical properties.     

An airlight estimation method for image dehazing based on gray projection

Multimedia Tools and Applications - As the key parameter of dehazing algorithms, airlight value directly affect the calculation accuracy of sky region, and any deviation will lead to the chromatic...     

Preparation and Characterization of Carboxymethyl Chitosan and β-Cyclodextrin Microspheres by Spray Drying

Three kinds of carboxymethyl chitosan/β-cyclodextrin microspheres loaded with theophylline were prepared by spray drying intended for pulmonary delivery. Mucociliotoxicity, permeation rate, and drug release characteristics of the product were investigated. The microspheres obtained by spray drying were found to be spherical with smooth or wrinkled surfaces. The mean particle size was between 3.39 and 6.06 µm. The microspheres demonstrated high product yield (43.7-50.2%), high drug loading (13.7-38.1%), and high encapsulation efficiency (86.9-92.8%). FT-IR indicated that there were interactions of theophylline with carboxymethyl chitosan matrix. Further studies on mucociliotoxicity and permeation confirmed that microspheres had better adaptability and high permeation rate. In vitro drug release from the microspheres was not related to the drug/polymer ratios.     

Paradigm and performance analysis of distributed frequent itemset mining algorithms based on Mapreduce

FrequentItemsetMining (FIM) is one of the most important data mining tasks and is the foundation of many data mining tasks. In Big Data era, centralized FIM algorithms cannot meet the needs of FIM for big data in terms of time and space, so Distributed Frequent Itemset Mining (DFIM) algorithms have been designed to meet the above challenges. In this paper, LocalGlobal and RedistributionMining which are two main paradigms of DFIM algorithm are discussed; Two algorithms of these paradigms on MapReduce named LG and RM are proposed while MapReduce is a popular distributed computing model, and also the related work is discussed. The experimental results show that the RM algorithm has better performance in terms of computation and scalability of sites, and can be used as the basis for designing the DFIM algorithm based on MapReduce. This paper also discusses the main ideas of improving the DFIM algorithms based on MapReduce.     

考虑电动汽车停泊概率的配电网接纳电动汽车能力评估方法

针对规模化电动汽车无序充电易导致配电网电压及潮流越限,需要定量评估配电网接纳电动汽车的能力问题,提出考虑电动汽车停泊概率的配电网接纳能力评估方法。首先在充电负荷建模环节增加考虑电动汽车停泊概率的影响,采用二阶段方法确定充电负荷所在节点;其次对基础负荷的季节特性进行建模,以研究由此导致的配电网接纳能力季节差异;建立了考虑静态安全约束的接纳能力评估模型,采用机会约束消除充电负荷预测偏差对评估准确度的影响。最后通过算例验证了所提评估方法的有效性。     

水杨醛缩-2-氨基嘧啶合Zn(Ⅱ)配合物的合成与荧光性质研究

合成了标题化合物,并用元素分析、红外光谱进行了表征。分别在固态、乙醇、丙酮、氯仿、N,N-二甲基甲酰胺及甲醇溶液中研究了配合物的荧光性质,并讨论了溶剂效应对配合物荧光强度的影响。     

注塑车间布局的设计及优化

注塑车间布局设计应以工艺流程为基础,根据生产物流的特点建立合理的车间物理布局。本文还进一步阐述了注塑车间布局优化的方法,以及节能和环境保护的措施。     

渤海莱州湾地下卤水纳滤过程的结垢趋势研究

针对莱州湾地下卤水纳滤过程中纳滤膜表面无机物结垢的问题,利用饱和度法系统研究了碳酸钙、硫酸钙在卤水体系和纳滤过程中的结垢趋势和影响因素。结果表明,在常温下原料卤水中的碳酸钙处于饱和状态,而其中的硫酸钙处于不饱和状态,因此在外部因素诱导下,碳酸钙更容易发生沉淀;降低卤水的pH可以有效抑制碳酸钙结垢;当逐步提高卤水的产水回收率时,纳滤浓水侧卤水中硫酸钙结垢的风险增大,在纳滤精制卤水过程中选择合适的产水回收率可以降低硫酸钙结垢的风险。