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.     

Model Selection for Unsupervised Learning of Visual Context

This study addresses the problem of choosing the most suitable probabilistic model selection criterion for unsupervised learning of visual context of a dynamic scene using mixture models. A rectified Bayesian Information Criterion (BICr) and a Completed Likelihood Akaike’s Information Criterion (CL-AIC) are formulated to estimate the optimal model order (complexity) for a given visual scene. Both criteria are designed to overcome poor model selection by existing popular criteria when the data sample size varies from small to large and the true mixture distribution kernel functions differ from the assumed ones. Extensive experiments on learning visual context for dynamic scene modelling are carried out to demonstrate the effectiveness of BICr and CL-AIC, compared to that of existing popular model selection criteria including BIC, AIC and Integrated Completed Likelihood (ICL). Our study suggests that for learning visual context using a mixture model, BICr is the most appropriate criterion given sparse data, while CL-AIC should be chosen given moderate or large data sample sizes.     

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     

离心泵并联运行工况点的数值求解

建立了求解多台不同型号离心泵并联运行工况点的数学模型,给出了用数值计算中的“二分法”求解该模型的方法,并附有用Exce l计算的实例。     

从频谱监测和国际协调探讨短波广播频段扩展的可行性

短波广播能够实现远距离和大范围的覆盖，至今仍是进行地区性、全国性及国际性广播覆盖的最好手段之一。ITU在2001年4月批准的1514建议书《30MHz以下广播频段的数字声音广播系统》，正式确定了DRM系统为全球统一的数字广播系统。在短波广播由模拟向数字化过渡的进程中，如何解决短波广播频谱短缺的问题，本文根据国家相关的频谱监测和国际短波频率协调的情况，对短波广播中4～10MHz频谱的扩展可行性进行初步分析。     

二极管侧面抽运薄片激光器耦合系统研究

设计了二极管侧面抽运Nd:YAG薄片激光器,耦合系统由消像差透镜组和空心光波导组成,对二极管快轴和慢轴方向的抽运光进行压缩和均匀化.采用光线追迹法,同时考虑二极管在快轴和慢轴方向的发散特性及薄片侧面的散射特性,模拟并分析了光线在耦合系统内的传输和薄片内抽运光分布的规律.模拟结果表明耦合系统具有98.1%的耦合效率,同时薄片内具有理想的抽运光分布.     

连续型衍射透镜激光直写技术研究

研究了不同于台阶形式的具有连续浮雕结构的衍射聚光透镜的激光直写工艺,简要描述了光致抗蚀剂的曝光和显影,对激光直写工艺的机理和工艺过程进行阐述.利用CLWS-300W/C极坐标激光直写设备制作出了具有良好面形微结构和较高衍射效率的连续型衍射透镜.研究表明,激光直写技术直写精度高,加工工艺灵活,利用计算机的控制,能够根据光学设计产生的浮雕分布数据制作复杂的、任意形状和外形的微型浮雕结构,非常适合于高精度微光学元件的加工制作.