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	Dynamic optimization of carbon capture technology deployment targeting carbon neutrality, cost efficiency and water stress: Evidence from China's electric power sector 期刊论文 OAI收割 ENERGY ECONOMICS, 2023, 卷号: 125, 页码: 18 作者: Yang, Lin; Lv, Haodong; Wei, Ning; Li, Yiming; Zhang, Xian \| 收藏 \| 浏览/下载：3/0 \| 提交时间：2025/06/27 Carbon capture utilization and storage (CCUS) Capture scale Capture cost Subsidy Water withdrawal Water consumption
	Microwave-assisted synthesis of well-shaped UiO-66-NH2 with high CO2 adsorption capacity 期刊论文 OAI收割 MATERIALS RESEARCH BULLETIN, 2018, 卷号: 98, 页码: 308-313 作者: Wan, Linlin; Huang, Aisheng; Caro, Juergen \| 收藏 \| 浏览/下载：23/0 \| 提交时间：2018/12/04 Metal-organic Frameworks Mixed-matrix Membranes Carbon-dioxide Modulated Synthesis Scale-up Capture Stability Water Mof
	Deep subwavelength electromagnetic transparence through dual metallic gratings with ultranarrow slits (EI CONFERENCE) 会议论文 OAI收割 2012 International Workshop on Metamaterials, Meta 2012, October 8, 2012 - October 10, 2012, Nanjing, China 作者: Liu Z.; Li S.; Li F. 收藏 \| 浏览/下载：32/0 \| 提交时间：2013/03/25 We study the transmission response of microwaves through two identical metallic plates perforated with periodical ultranarrow slits. The experimental and numerical transmission spectra consistently display a striking transmission peak at wavelength much larger than any characteristic length of the microstructure (e.g. about 20-fold of the lattice constant) which can not be directly interpreted by the existing mechanisms. Both the LC-circuit-based microscopic picture and the effective-medium-based macroscopic model are established to capture the essential physics behind such unexpected resonance at the deep subwavelength scale. 2012 IEEE.
	Directional multiscale edge detection using the contourlet transform (EI CONFERENCE) 会议论文 OAI收割 2010 IEEE International Conference on Advanced Computer Control, ICACC 2010, March 27, 2010 - March 29, 2010, 445 Hoes Lane - P.O.Box 1331, Piscataway, NJ 08855-1331, United States 作者: Jin L.-X.; Han S.-L.; Zhang R.-F. 收藏 \| 浏览/下载：43/0 \| 提交时间：2013/03/25 Wavelet multiresolution analysis allows us to detect edges at different scales also to obtain other important aspects of the extracted edges. However due to the usual two-dimensional tensor product wavelet transform is not optimal for representing images. The main problem in edge detection using wavelet transform is that it can only capture point-singularities and the extracted edges are not continuous. In order to solve that problem we propose a new image edge detection method based on the contourlet transform. The directional multiresolution representation Contourlet takes advantages of the intrinsic geometrical structure of images and is appropriate for the analysis of the image edges. Using the modulus maxima detection an image edge detection method based on contourlet transform is proposed. To suppress the image noise effect on edge detection the scale multiplication in contourlet domain is also proposed. Through real images experiments the proposed edge detection method's performance for the extracted edges is analyzed and compared with other two edge detection methods. The experiment result proves that the proposed edge detection method improves over wavelet-based techniques and Canny detector and also works well for noisy images. 2010 IEEE.
	Intelligent MRTD testing for thermal imaging system using ANN (EI CONFERENCE) 会议论文 OAI收割 ICO20: Remote Sensing and Infrared Devices and Systems, August 21, 2005 - August 26, 2005, Changchun, China Sun J.; Ma D. 收藏 \| 浏览/下载：31/0 \| 提交时间：2013/03/25 The Minimum Resolvable Temperature Difference (MRTD) is the most widely accepted figure for describing the performance of a thermal imaging system. Many models have been proposed to predict it. The MRTD testing is a psychophysical task for which biases are unavoidable. It requires laboratory conditions such as normal air condition and a constant temperature. It also needs expensive measuring equipments and takes a considerable period of time. Especially when measuring imagers of the same type the test is time consuming. So an automated and intelligent measurement method should be discussed. This paper adopts the concept of automated MRTD testing using boundary contour system and fuzzy ARTMAP but uses different methods. It describes an Automated MRTD Testing procedure basing on Back-Propagation Network. Firstly we use frame grabber to capture the 4-bar target image data. Then according to image gray scale we segment the image to get 4-bar place and extract feature vector representing the image characteristic and human detection ability. These feature sets along with known target visibility are used to train the ANN (Artificial Neural Networks). Actually it is a nonlinear classification (of input dimensions) of the image series using ANN. Our task is to justify if image is resolvable or uncertainty. Then the trained ANN will emulate observer performance in determining MRTD. This method can reduce the uncertainties between observers and long time dependent factors by standardization. This paper will introduce the feature extraction algorithm demonstrate the feasibility of the whole process and give the accuracy of MRTD measurement.