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Chinese Academy of Sciences Institutional Repositories Grid
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CAS IR Grid
机构
力学研究所 [1]
长春光学精密机械与物... [1]
生态环境研究中心 [1]
软件研究所 [1]
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OAI收割 [4]
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会议论文 [2]
期刊论文 [2]
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2022 [1]
2018 [1]
2007 [1]
2006 [1]
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Insight into nitrogen removal performance of anaerobic ammonia oxidation in two reactors: Comparison based on the aspects of extracellular polymeric substances and microbial community
期刊论文
OAI收割
BIOCHEMICAL ENGINEERING JOURNAL, 2022, 卷号: 185, 期号: 0, 页码: 108526
作者:
Yang, Dongmin
;
Jiang, Cancan
;
Xu, Shengjun
;
Gu, Likun
;
Wang, Danhua
  |  
收藏
  |  
浏览/下载:28/0
  |  
提交时间:2022/11/09
WASTE-WATER TREATMENT
PROCESS START-UP
ANAMMOX GRANULES
BATCH REACTOR
PRODUCTS SMP
SLUDGE
BACTERIA
BIOFILM
EPS
RELEASE
Numerical investigation of the axial impulse load during the startup in the shock tunnel
期刊论文
OAI收割
AEROSPACE SCIENCE AND TECHNOLOGY, 2018, 卷号: 73, 页码: 332-342
作者:
Meng BQ(孟宝清)
;
Han GL(韩桂来)
;
Luo ZT(罗长童)
;
Jiang ZL(姜宗林)
  |  
收藏
  |  
浏览/下载:60/0
  |  
提交时间:2018/10/30
Hypersonic
Shock tunnel
Start-up process
Impulse force
Vibration
a multilevel reputation system for peer-to-peer networks
会议论文
OAI收割
6th International Conferernce on Grid and Cooperative Computing, Urumchi, PEOPLES R CHINA, AUG 16-18,
Xu Ziyao
;
He Yeping
;
Deng Lingli
  |  
收藏
  |  
浏览/下载:22/0
  |  
提交时间:2011/06/29
access control enforcement agent
bootstrap process
central computation and enforcement agent
cold-start problem
collusion
fair trading problem
file authenticity
incentive system
level keeping reputation computation
level up reputation computation
load bal
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.