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	Ferritic-Martensitic Steels in Power Industry: Microstructure, Degradation Mechanism, and Strengthening Methods 期刊论文 OAI收割 STEEL RESEARCH INTERNATIONAL, 2024, 页码: 18 作者: Jiang, Hanyang; Huang, Xin; Feng, Yihui; Xiong, Wei; Jin, Zhenyu \| 收藏 \| 浏览/下载：19/0 \| 提交时间：2024/10/08 degradation mechanisms ferritic-martensitic steels microstructures strengthening methods
	Research Progress of Desertification and Its Prevention in Mongolia 期刊论文 OAI收割 SUSTAINABILITY, 2021, 卷号: 13, 期号: 12, 页码: 17 作者: Liang, Xiya; Li, Pengfei; Wang, Juanle; Chan, Faith Ka Shun; Togtokh, Chuluun \| 收藏 \| 浏览/下载：29/0 \| 提交时间：2021/08/19 land degradation spatiotemporal changes driving factors prevention research methods
	Research Progress of Desertification and Its Prevention in Mongolia 期刊论文 OAI收割 SUSTAINABILITY, 2021, 卷号: 13, 期号: 12, 页码: 17 作者: Liang, Xiya; Li, Pengfei; Wang, Juanle; Chan, Faith Ka Shun; Togtokh, Chuluun \| 收藏 \| 浏览/下载：14/0 \| 提交时间：2021/08/19 land degradation spatiotemporal changes driving factors prevention research methods
	Research Progress of Microplastics in Freshwater Sediments in China 期刊论文 OAI收割 ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH, 2020, 页码: 15 作者: Zhang, Bin; Chen, Liang; Chao, Jinyu; Yang, Xin; Wang, Qing \| 收藏 \| 浏览/下载：16/0 \| 提交时间：2021/06/21 Microplastics Freshwater sediment Separation and detection Toxicological effect Degradation methods
	Monomer composition of chitooligosaccharides obtained by different degradation methods and their effects on immunomodulatory activities 期刊论文 OAI收割 CARBOHYDRATE POLYMERS, 2017, 卷号: 157, 页码: 1288-1297 作者: Xing, Ronge; Liu, Yongliang; Li, Kecheng; Yu, Huahua; Liu, Song 收藏 \| 浏览/下载：47/0 \| 提交时间：2017/03/22 Chitooligosaccharide Degradation methods Monomer composition Immunomodulatory activities Chitosan
	Environmental Behavior and Toxicological Effects of Polycyclic Musks 期刊论文 OAI收割 PROGRESS IN CHEMISTRY, 2012, 卷号: 24, 期号: 4, 页码: 606－615 Li Zhuona; Zhou Qunfang; Liu Jiyan; Shi Yali; Cai Yaqi; Jiang Guibin 收藏 \| 浏览/下载：28/0 \| 提交时间：2014/11/04 polycyclic musks analytical methods pollution status degradation and transformation bioaccumulation toxicological effects
	Restoration of an atmospherically blurred image based on physical model fusion approach (EI CONFERENCE) 会议论文 OAI收割 2010 IEEE 10th International Conference on Signal Processing, ICSP2010, October 24, 2010 - October 28, 2010, Beijing, China 作者: Wang Y.; Li J.; Li J.; Li J. 收藏 \| 浏览/下载：26/0 \| 提交时间：2013/03/25 This paper proposes a new restoration method only using the single image information combining atmospheric physical model with fusion techniques to reduce the degradation of the image contrast in bad weather conditions caused by atmospheric aerosols such as haze and fog. The basic idea of this method is to utilize physics-based model method instead of multisensors to generate a serial of virtual images and then to fuse those virtual images into a high contrast image based on the wavelet fusion technique. In contrast to previous methods our restoration technique is not only independent on predicted structure distributions of scene reflectance or detailed knowledge about the particular weather condition but also adapt to the situation without a reference image or images with moving objects captured by a video camera. Experiments on different poorcontrast images demonstrate the availability of the proposed method in case of restoring the atmospherically blurred images. 2010 IEEE.
	Karst rocky desertification information extraction with EO-1 Hyperion data 会议论文 OAI收割 International Conference on Earth Observation Data Processing and Analysis, ICEODPA,, Wuhan, China, December 28, 2008 - December 30,2008 Yue, Yuemin; Wang, Kelin; Zhang, Bing; Jiao, Quanjun; Yu, Yizun 收藏 \| 浏览/下载：12/0 \| 提交时间：2014/12/07 Landforms Climatology Data processing Degradation Ecosystems Monte Carlo methods Observatories Remote sensing Spectrum analysis Substrates Vegetation
	Lossless wavelet compression on medical image (EI CONFERENCE) 会议论文 OAI收割 4th International Conference on Photonics and Imaging in Biology and Medicine, September 3, 2005 - September 6, 2005, Tianjin, China 作者: Liu H.; Liu H.; Liu H. 收藏 \| 浏览/下载：41/0 \| 提交时间：2013/03/25 An increasing number of medical imagery is created directly in digital form. Such as Clinical image Archiving and Communication Systems (PACS). as well as telemedicine networks require the storage and transmission of this huge amount of medical image data. Efficient compression of these data is crucial. Several lossless and lossy techniques for the compression of the data have been proposed. Lossless techniques allow exact reconstruction of the original imagery while lossy techniques aim to achieve high compression ratios by allowing some acceptable degradation in the image. Lossless compression does not degrade the image thus facilitating accurate diagnosis of course at the expense of higher bit rates i.e. lower compression ratios. Various methods both for lossy (irreversible) and lossless (reversible) image compression are proposed in the literature. The recent advances in the lossy compression techniques include different methods such as vector quantization wavelet coding neural networks and fractal coding. Although these methods can achieve high compression ratios (of the order 50:1 or even more) they do not allow reconstructing exactly the original version of the input data. Lossless compression techniques permit the perfect reconstruction of the original image but the achievable compression ratios are only of the order 2:1 up to 4:1. In our paper we use a kind of lifting scheme to generate truly loss-less non-linear integer-to-integer wavelet transforms. At the same time we exploit the coding algorithm producing an embedded code has the property that the bits in the bit stream are generated in order of importance so that all the low rate codes are included at the beginning of the bit stream. Typically the encoding process stops when the target bit rate is met. Similarly the decoder can interrupt the decoding process at any point in the bil stream and still reconstruct the image. Therefore a compression scheme generating an embedded code can start sending over the network the coarser version of the image first and continues with the progressive transmission of the refinement details. Experimental results show that our method can get a perfect performance in compression ratio and reconstructive image.