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.     

Polyaniline encapsulated Ti-MOF/CoS for efficient photocatalytic hydrogen evolution

We report the study of conductive polyaniline (PANI) chain embedded Ti-MOF functionalized with CoS as a cocatalyst for hydrogen evolution reaction (HER) application. The post synthetically modified hybrid photocatalyst PANI/Ti-MOF/CoS greatly influences the redox and e^? ? h⁺ separation process and exhibits an impressive rate of HER (～1322 μmol h^?1g^?1), suppressing the pristine Ti-MOF (～62 μmol h^?1g^?1) with apparent quantum yield (AQY) of ～3.2 and transient current response of ～46.4 μA cm^?2. In this system, Ti-MOF provides the circulation of Ti³⁺ and Ti⁴⁺ to the reaction of photocatalytic H₂ generation, where the additional PANI and CoS amended the performance of H₂ production through electron enrichment and thereby improving the stability and integrity of Ti-MOF. The Electrochemical studies demonstrated increased photocurrent by interweaving Ti-MOF crystal with PANI through cation-π interaction thereby enhancing interface connection and then promoting electron transfers. The charge dynamics revealed the initial charge transfer from photoexcited PANI to encapsulated MOF framework to boost the photocatalytic performance of the system. Further, the electron movement at the Ti-MOF/CoS interface is investigated through work function and electrochemical potential of electrons (Fermi level). DFT results demonstrate the importance of CoS in improving the photocatalytic performance of hybrid Ti-MOF catalyst, which leads to superior catalytic behaviour. These results establish that the encapsulation of catalytic active sites inside MOFs with desirable energy band gaps would be an ideal choice for the production of solar fuels.     

某矿快速掘进最优炮孔间距的选择

山西某矿5308底抽巷在掘进过程中速度慢、效率低，直接影响工作面的瓦斯抽采，为了改善上述情形，对炮孔间距进行研究。通过使用ANSYS软件对不同炮孔间距下快速掘进效果的模拟分析，并经现场验证，得出了适应该矿的最佳炮孔间距。结果表明：炮孔间距为500 mm时，爆破产生裂隙发育范围和岩石损伤区域都最大，快速掘进的效果最好。     

Effect of temperature on fast forging process of Mg-Ni samples for fast formation of Mg2Ni for hydrogen storage

Fast-Forging was used as a Severe Plastic Deformation technique to process Mg/Ni fine powder mixtures at a ratio corresponding to the eutectic composition. The samples were processed at different temperature, increased successively from room temperature up to above 500 °C. The one shock forging operation led to a reduction rate comprised between 80 to more than 90% depending of the applied temperature. Interestingly, a threshold temperature was pointed out for which amounts of the binary Mg₂Ni alloy were directly synthesized in increasing proportions when increasing temperature. A maximum amount of Mg₂Ni was synthesized according the nominal proportions at the highest applied temperature. Besides, numerical simulations were developed to consider and integrate to the forging process, the heat arising from the mechanical energy at deformation. Interestingly the total temperature at shock – heat applied to and heat developed in – indicates that the threshold temperature correspond well with the eutectic temperature as reported in the phase diagram. Early hydrogenation cycles suggest that both mechanical defects in brittle Mg and presence of amounts of Mg₂Ni as catalyst should be combined to optimize the hydrogenation characteristics.     

Development of a fast atom beam gun for surface-activated bonding

Surface-activated bonding (SAB), also called room-temperature bonding, is used in three-dimensional integration technology for semiconductor devices. An Ar fast atom beam (FAB) is used for SAB. However, conventional FAB guns must be replaced after hundreds of minutes of irradiation because carbon abrasion powders are generated by Ar ions sputtering in the gun. Therefore, this study develops a novel FAB gun with improved lifetime. The proposed FAB gun applies magnetic fields to guide Ar ions to reduce sputtering in the gun and improve irradiation efficiency. The proposed FAB gun indicates the possibility of improving gun lifetime.     

Techno-economic analysis for rustic electrification in Egypt using multi-source renewable energy based on PV/ wind/ FC

A technical-economic investigation based on mathematical modeling, simulation, and optimization approach is employed in this research to assemble an island combined renewable energy systems (CRES) consists of solar PV/Wind/Fuel Cell (FC) of a small-scale countryside area in Egypt. The intent of the proposed island CRES is to boost the share of renewable energy in the energy mix and to study the possibility of using fuel cells as a storage/backup system instead of using battery banks.Three combinations of CRES are presented in this research to select the most optimum one. The combinations of the hybrid systems are PV/FC, PV/WT/FC, and WT/FC. The performance and the total cost of the suggested CRES were optimized using Firefly Algorithm (FA). The results obtained from the FA are compared with those obtained from the Shuffled Frog Leaping Algorithm (SFLA) and the particle swarm optimization (PSO).The selected case study area with latitude and longitude of (29.0214 N, 30.8714 E) is identified for economic viability in this work.The simulation outcomes show that the solar PV/Wind/Fuel Cell combination incorporated with an electrolyzer for hydrogen production grants the excellent performance. The proposed system is economically viable with a levelized cost of energy of 0.47 $/kWh.     

基于改进正弦余弦算法的无线传感器节点部署优化

为了提高无线传感器网络（WSN）的性能，提出了一种基于改进正弦余弦算法（ESCA）的节点部署优化方法。首先，引入双曲正弦调节因子和动态余弦波权重系数，以平衡算法的全局探索与局部开发能力；然后，提出了一种基于拉普拉斯和高斯分布的变异策略，避免算法陷入局部最优。对于基准函数的优化实验结果表明，ESCA相比引力搜索算法、鲸鱼优化算法、基本正弦余弦算法（SCA）及其改进算法具有更高的收敛精度和收敛速度。最后，将ESCA应用于WSN节点部署优化，结果表明其优化覆盖率相比改进粒子群优化算法、外推人工蜂群算法、改进灰狼优化算法和自适应混沌量子粒子群算法分别提高了1.55个百分点、7.72个百分点、2.99个百分点和7.63个百分点，用更少节点便可达到相同目标精度。     

基于深度概率图模型的鲁棒人脸画像合成

针对基于数据驱动的人脸画像合成算法像素特征缺乏对光照变化和复杂背景的鲁棒性,常合成低质量的画像的问题,文中提出基于深度概率图模型的鲁棒人脸画像合成算法.采用预处理方法调整测试照片的光照亮度和人脸姿态,使之与训练照片一致.采用深度特征代替像素特征进行近邻匹配,采用深度概率图模型对画像重建权重和深度特征权重联合建模,得到合成画像的最佳重构表示.为了提高画像合成速度,提出快速近邻搜索方法.实验验证文中算法的鲁棒性和快速性.     

High-resolution ISAR imaging of fast rotating targets based on pattern-coupled Bayesian strategy for multiple measurement vectors

Very high resolution inverse synthetic aperture radar (ISAR) imaging of fast rotating targets is a complicated task. There may be insufficient pulses or may introduce migration through range cells (MTRC) during the coherent processing interval (CPI) when we use the conventional range Doppler (RD) ISAR technique. With compressed sensing (CS) technique, we can achieve the high-resolution ISAR imaging of a target with limited number of pulses. Sparse representation based method can achieve the super resolution ISAR imaging of a target with a short CPI, during which the target rotates only a small angle and the range migration of the scatterers is small. However, traditional CS-based ISAR imaging method generally faced with the problem of basis mismatch, which may degrade the ISAR image. To achieve the high resolution ISAR imaging of fast rotating targets, this paper proposed a pattern-coupled sparse Bayesian learning method for multiple measurement vectors, i.e. the PC-MSBL algorithm. A multi-channel pattern-coupled hierarchical Gaussian prior is proposed to model the pattern dependencies among neighboring range cells and correct the MTRC problem. The expectation-maximization (EM) algorithm is used to infer the maximum a posterior (MAP) estimate of the hyperparameters. Simulation results validate the effectiveness and superiority of the proposed algorithm.     

Ternary Blends of Renewable Fast Pyrolysis Bio-Oil,Advanced Bioethanol,and Marine Gasoil as Potential Marine Biofuel

An alternative for reducing emissions from marine fuel is to blend bio-oil from lignocellulose non-edible feedstocks to diesel fossil fuels. Phase diagrams of the ternary systems were built to represent the transition from heterogeneous regions to homogeneous regions. Four homogeneous blends of bio-oil of eucalyptus-bioethanol-marine gasoil were experimentally characterized with respect to the most important fuel parameters for marine engines: water content, flash point, low heating value, viscosity, and acidity. Blends with closer properties to marine gasoil replacement, lower costs, and environmental impacts should be tested for large engines.