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A New General Equation of Mean Particle Size for Different Atomization Processes
Liu Yunzhong,Li Yuanyuan 한국분말야금학회 2006 한국분말야금학회 학술대회논문집 Vol.2006 No.1
Based on theoretical analysis, a new general equation of mean particle size applicable to both conventional atomization methods and new atomization processes is presented. In gas atomization, it is equivalent with and can be changed into Lubanska Equation. In centrifugal atomization, it can be changed into the equations that are currently the most widely used. In water atomization, it is similar to the equation proposed by Grandzol and Tallmadge. According to the universal equation, new correlations for mean particle size in novel atomization processes such as Hybrid Atomization and Multistage Atomization were proposed and agreed with our experimental data well.
Investment and Risk Control of China's Mining Enterprises
Yunzhong Liu,Li Gao,Shuzhen Yao,Lin Yang 인하대학교 정석물류통상연구원 2009 인하대학교 정석물류통상연구원 학술대회 Vol.2009 No.10
Mining investment environment influences mining business risk factors. How enterprises face changing environment and implement successful risk management is the central task for mining enterprise management and development. This paper begins with the analysis of Chinn"s mining invesment environment, identifiesrisk factors of S Mining Limited Company, explores its risk control countermeasures, and propose resolutions of risk management for mining enterprises.
Single Low-Light Ghost-Free Image Enhancement via Deep Retinex Model
( Yan Liu ),( Bingxue Lv ),( Jingwen Wang ),( Wei Huang ),( Tiantian Qiu ),( Yunzhong Chen ) 한국인터넷정보학회 2021 KSII Transactions on Internet and Information Syst Vol.15 No.5
Low-light image enhancement is a key technique to overcome the quality degradation of photos taken under scotopic vision illumination conditions. The degradation includes low brightness, low contrast, and outstanding noise, which would seriously affect the vision of the human eye recognition ability and subsequent image processing. In this paper, we propose an approach based on deep learning and Retinex theory to enhance the low-light image, which includes image decomposition, illumination prediction, image reconstruction, and image optimization. The first three parts can reconstruct the enhanced image that suffers from low-resolution. To reduce the noise of the enhanced image and improve the image quality, a super-resolution algorithm based on the Laplacian pyramid network is introduced to optimize the image. The Laplacian pyramid network can improve the resolution of the enhanced image through multiple feature extraction and deconvolution operations. Furthermore, a combination loss function is explored in the network training stage to improve the efficiency of the algorithm. Extensive experiments and comprehensive evaluations demonstrate the strength of the proposed method, the result is closer to the real-world scene in lightness, color, and details. Besides, experiments also demonstrate that the proposed method with the single low-light image can achieve the same effect as multi-exposure image fusion algorithm and no ghost is introduced.
Pulsed Electric Current Sintering of Nano-crystalline Iron-base Powders
Li Yuanyuan,Long Yan,Li Xiaoqiang,Liu Yunzhong 한국분말야금학회 2006 한국분말야금학회 학술대회논문집 Vol.2006 No.1
A new process of pulsed electric current sintering was developed. It combines compaction with activated sintering effectively and can manufacture bulky nano-crystalline materials very quickly. A nano-structured steel is obtained with high relative density and hardness by this process. The average grain size of iron matrix is 58nm and the carbide particulate size is less than 100 nm. The densification temperature of ball-milled powders is approximately lower than that of blended powders. When the sintering temperature increases, the density of as-sintered specimen increases but the hardness of as-sintered specimen first increases and then decreases.