基于密集神经网络的灰度图像着色算法

针对在灰度图像着色领域中，传统算法信息提取率不高、着色效果不理想的问题，提出了基于密集神经网络的灰度图像着色算法，以实现改善着色效果，让人眼更好地观察图片信息的目的。利用密集神经网络的信息提取高效性，构建并训练了一个端到端的深度学习模型，对图像中的各类信息及特征进行提取。训练网络时与原图像进行对比，以逐渐减小网络输出结果的信息、分类等各类型的损失。训练完成后，只需向网络输入一张灰度图片，即可生成一张颜色饱满、鲜明逼真的彩色图片。实验结果表明，引入密集网络后，可有效改善着色过程中的漏色、细节信息损失、对比度低等问题，所提算法着色效果较基于VGG网络及U-Net、双流网络结构、残差网络（ResNet）等性能优异的先进着色算法而言取得了显著的改进。     

Development of structurally modified OER catalysts with enhanced performance and longevity for PEM-based electrolytic air dehumidification

PEM-based electrolytic air dehumidification is innovative in dehumidification that requires high precision and small space due to its high efficiency, compactness, and cleanness. However, the system dehumidification performance and durability are limited by using commercial Anatase-IrO₂ catalysts. In this study, two types of structurally modified OER catalyst materials, ATO-IrO₂ and ND-MnO₂-IrO₂, are developed to improve the performance of the system. System experiments showed that, compared to the commercial catalysts, the use of ATO-IrO₂ and ND-MnO₂-IrO₂ as the anode catalyst can improve the dehumidification performance by 45% and 20%, respectively. Furthermore, in 50-h accelerated aging tests, the attenuation rates of the ATO-IrO₂ and ND-MnO₂-IrO₂ systems are 3% and 8% respectively, which are far lower than the 35% attenuation of commercial catalyst. The results indicate that, as catalysts with a classic core-shell structure, ATO-IrO₂ and ND-MnO₂-IrO₂ still have a significant impact on improving the performance of the electrolytic dehumidification systems.     

加快能源工业用钢开发支撑国家能源战略实施——武钢发展战略的思考

能源给人类带来光明,能源给社会进步提供了动力,尤其是进入21世纪以来,能源的可持续发展己成为直接影响世界经济社会可持续发展的决定性因素之一。中国政府高瞻远瞩地提出到2020年要实现国民经济翻两番和建设节约型社会的目标,描绘了支撑这一发展目标的十分宏伟的能源发展战略,使人振奋,也对我国钢铁产业的发展提出了更高的要求,作为长期以来与我国     

Fenton氧化法去除酱油生产废水中焦糖色素的研究

着重考察了Fenton试剂对水中焦糖色素降解的影响因素.从试验中得出,这些影响因素包括pH、催化剂的投加方式、催化剂与氧化剂的化学计量数以及反应时间等.Fenton反应中,pH4的条件下处理效果最好,反应进行40min时去除率达到90%.     

铁塔加工中型材零件优化下料管理系统

介绍了铁塔加工中角钢零件优化下料管理系统,阐明了系统的模块化结构及工作原理。建立的面向角钢加工工艺的优化下料管理系统可以将生产管理与下料优化两大功能整合为一体,使用极为方便。该系统在铁塔生产中,可节省大量材料,有效地提高了企业的经济效益。     

The effect of grain size, strain rate, and temperature on the mechanical behavior of commercial purity aluminum

Commercial purity aluminum AA1050 was subjected to equal channel angular extrusion (ECAE) that resulted in an ultrafine-grained (UFG) microstructure with an as-received grain size of 0.35 μm. This UFG material was then annealed to obtain microstructures with grain sizes ranging from 0.47 to 20 μm. Specimens were compressed at quasi-static, intermediate, and dynamic strain rates at temperatures of 77 and 298 K. The mechanical properties were found to vary significantly with grain size, strain rate, and temperature. Yield stress was found to increase with decreasing grain size, decreasing temperature, and increasing strain rate. The work hardening rate was seen to increase with increasing grain size, decreasing temperature, and increasing strain rate. The influence of strain rate and temperature is most significant in the smallest grain size specimens. The rate of work hardening is also influenced by strain rate, temperature, and grain size with negative rates of work hardening observed at 298 K and quasi-static strain rates in the smallest grain sizes and increasing rates of work hardening with increasing loading rate and grain size. Work hardening behavior is correlated with the substructural evolution of these specimens.