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.     

基于推理注意力机制的二阶段网络图像修复

现有的图像修复方法在处理大面积缺失或高度纹理化的图像时，通常会产生扭曲的结构或与周围区域不一致的模糊纹理，无法重建合理的图像结构。为此，提出了一种基于推理注意力机制的二阶段网络图像修复方法。首先通过边缘生成网络生成合理的幻觉边缘信息，然后在图像补全网络完成图像的重建工作。为了进一步生成视觉效果更逼真的图像，提高图像修复的精确度，在图像补全网络采用推理注意力机制，有效控制了生成特征的不一致性，从而生成更有效的信息。所提方法在多个数据集上进行了实验验证，结果表明该图像修复方法的结构相似性指数达到了88.9%，峰值信噪比达到了25.56 dB，与现有的图像修复方法相比，该方法具有更高的图像修复精确度，生成的图像更逼真。     

Fabrication of reduced Graphene Oxide supported Gd3+ doped V2O5 nanorod arrays for superior photocatalytic and antibacterial activities

In the current report, pure V₂O₅, a series of Gd doped V₂O₅ (1 wt%, 3 wt%, 5 wt% and 10 wt%) and graphene integrated Gd–V₂O₅ photocatalysts have been prepared using a facile wet chemical approach. The effect of Gd⁺³ ions substitution and RGO support on V₂O₅ was studied by the different analytical techniques. X-ray diffraction (XRD) results showed the orthorhombic crystal structure of synthesized samples with crystallize size in range of 22–35 nm. Morphological analysis showed nanorods and nanorod arrays like appearance of V₂O₅, Gd–V₂O₅ and GdV-₂O₅/RGO, respectively. Gd–V₂O₅ and Gd–V₂O₅/RGO exhibited enhanced optical response in the visible region along with decrease in the band gap values for Gd doped V₂O₅ samples. BET surface area of Gd–V₂O₅ and Gd- V₂O₅/RGO was calculated as 12.39 g/m² and 15.35 g/m² that was found to be higher than pristine V₂O₅. To study the photocatalytic activity of synthesized photocatalysts, methylene blue (MB) was chosen as model pollutant. Among the Gd doped V₂O₅ samples, highest photocatalytic activity (45.62%) was achieved by optimal concentration of 5 wt% Gd–V₂O₅ that is accredited to effective separation of electron-hole pairs. While Gd–V₂O₅/RGO showed 2.1 times higher dye removal (97.12%) than unsupported Gd–V₂O₅, under the visible light irradiation. The significantly high photocatalytic activity of Gd–V₂O₅/RGO is due to the synergistic effect aroused by combined action of Gd⁺³ ions doping and advantageous properties of highly conductive and large surfaced graphene. Recycling experiments for V₂O₅ derivatives showed good stability and recyclability of photocatalysts. Additionally, Gd–V₂O₅/RGO was found to be more potential anti-bacterial agent than V₂O₅ and Gd–V₂O₅.     

On the design of secure primitives for real world applications

This editorial paper provides an overview of new advances on hardware security challenges and promising solutions for real world applications. It first presents the increasing hardware vulnerabilities with the emergence of diverse computing platforms. Then, it details the technical challenges, research opportunities, and potential solutions to cyber-attacks on -physical- devices.     

Approximation Optimal Vibration Control with Applications to Jacket Offshore Platforms with Nonlinear Dynamic Characteristics

International Journal of Control, Automation and Systems - The vibration control problem of offshore jacket platforms is studied. The model of offshore platforms with nonlinear interactions of the...     

Multiple clusterings of heterogeneous information networks

Machine Learning - Traditional clustering algorithms focus on a single clustering result; as such, they cannot explore potential diverse patterns of complex real world data. To deal with this...