Journal of Cleaner Production,2012年20(1):72-81 ISSN：0959-6526
[Dong, Xiaoqing ; Li, Ji ; Li, Chaolin ; Wang, Jia ; Huang, Wantao ] Environmental Science and Engineering Research Center, Shenzhen Graduate School, Harbin Institute of Technology, Shenzhen 518055, China;[ Liao, Ruibin ] School of Medical Business, Guangdong Pharmaceutical University, Guangzhou Higher Education Mega Center, Guangzhou 510006, China
[Li, J] Harbin Inst Technol, Environm Sci & Engn Res Ctr, Shenzhen Grad Sch, Shenzhen 518055, Peoples R China.
Cleaner production - Current emissions - Electroplating industry - Heavy metal pollution - Investment decisions - Investment subsidy - Less developed countries - Optimal policies - Process modifications - Recovery technology - Surface finishing industry - System Dynamics - System dynamics approach - Tax rates - Utilization rates - Water prices
[Hao, Zhi-Feng] Guangdong Univ Technol, Fac Comp, Guangzhou 510006, Guangdong, Peoples R China.;[Chen, Zi-Jie] Guangdong Pharmaceut Univ, Sch Med Business, Guangzhou 510006, Guangdong, Peoples R China.;[Chen, Zi-Jie] South China Univ Technol, Sch Comp Sci & Engn, Guangzhou 510641, Guangdong, Peoples R China.
Multi-label Classification;Low-dimensionaI Subspace;Supervised Correlation Exploration;Latent Label Correlations;Feature Mapping;Generalized Eigen value Problems
In multi-label classification, discovering label structures or label correlations when learning can improve predictive performance and time complexity. In this paper, a unified framework is proposed to incorporate the supervised correlation exploration with the predictive model. In the framework, feature mappings to a low-dimensional subspace is obtained through a linear transformation guided by the label information. And a multi-label classifier is simultaneously built on the projected features. The framework leads to a trace optimization problem which can be solved by a generalized eigen value problem. Meanwhile, the dual form of the framework is presented to deal with different problems. Experiments on four datasets show that the proposed framework can achieve comparable performance with four other well-known methods, and achieve better performance when label correlations are important. It's also demonstrated that the framework is efficient when the dimensionality is low, and the dual form will be more efficient without extra computational tricks in the small-sample problems.
[Ruan Xianjing] Guangdong Pharmaceut Univ, Sch Med Business, Guangzhou, Guangdong, Peoples R China.
Solar thermal conversion thin film materials;New energy vehicles;TiMoAlON;Selective absorbing;Multi-layer gradient structure
The future of the world energy supply and consumption will be diversified, clean, efficient and global marketization direction. In existing thermal applications technologies, selective absorption coating technology is recognized as the more core technology, it plays a vital role in improve the conversion efficiency of solar thermal, large-scale promotion solar thermal applications. Study results suggest that: the proposed process and structural design, can be prepared in high-temperature non-vacuum environment, with a more balanced absorption performance and reliable high-temperature atmospheric environment service stability TiMoAlON selective absorption film on the new energy vehicles.
[Chen, Zi-Jie ] Medicine Business School, Guangdong Pharmaceutical University, Guangzhou 510006, China;[ Liu, Bo ] College of Computer Science and Engineering, South China University of Technology, Guangzhou 510640, China;[ He, Xu-Peng ] School of Mathematics Science, South China University of Technology, Guangzhou 510640, China
[潘琪; 罗笑南] School of Information Science and Technology (SIST), Sun Yat-Sen University, Guangzhou 510275, China;[潘琪; 罗笑南] Key Laboratory of Digital Life, Ministry of Education, Sun Yat-Sen University, Guangzhou 510275, China;[朱继武] Department of Marketing, Guangdong Pharmaceutical University, Guangzhou 510006, China