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	Development of a two-domain-approach-based multi-scale model for the two-phase flows in space accumulators in microgravity 期刊论文 OAI收割 INTERNATIONAL JOURNAL OF HEAT AND MASS TRANSFER, 2026, 卷号: 254, 页码: 14 作者: Wang, Qing; Wang, Qinggong; Gu, Junping; Cheverda, Vyacheslav Vladimirovich; Zhu ZQ(朱志强) \| 收藏 \| 浏览/下载：13/0 \| 提交时间：2025/09/29 Two-domain approach Multi-scale structure Space accumulator Fluid management Microgravity
	Fluid distribution in a two-phase space accumulator predicted by a coupled multi-scale model based on single-domain approach 期刊论文 OAI收割 INTERNATIONAL COMMUNICATIONS IN HEAT AND MASS TRANSFER, 2025, 卷号: 162, 页码: 16 作者: Wang, Qing; Yu, Qiang; Du WF(杜王芳); Fang, Zenong; Li K(李凯) \| 收藏 \| 浏览/下载：65/0 \| 提交时间：2025/02/24 Two-phase space accumulator Microgravity Dynamic fluid distribution Multi-scale model Single-domain approach
	An information theoretic approach to model reduction based on frequency-domain Cross-Gramian information (EI CONFERENCE) 会议论文 OAI收割 2010 8th World Congress on Intelligent Control and Automation, WCICA 2010, July 7, 2010 - July 9, 2010, Jinan, China 作者: Zhou J. 收藏 \| 浏览/下载：47/0 \| 提交时间：2013/03/25 We focused our attention on model reduction for linear time invariant (LTI) continuous time systems with single input and single output (SISO). We analyzed the strongpoint and shortcoming of an information theoretic approach called minimum information loss method for model reduction. We explained relationships between the steady-state information entropy and controllability information for the Gaussian systems. The controllability observability and Cross-Gramian information were analyzed in the time-domain. The frequency-domain Cross-Gramian information (FCGI) was defined based on Cross-Gramian matrix containing information associated with both controllability and observability. Furthermore a valuable application of the frequency-domain Cross-Gramian information to model reduction (FCGMIL) was developed by using the concept and properties of frequency-domain Cross-Gramian information. The performance index of FCGMIL is to minimize the frequency-domain Cross-Gramian information loss caused by eliminating the state variables with weak contributions to Cross-Gramian information over some frequency band. Two numerical examples are illustrated to verify the efficiency of FCGMIL. 2010 IEEE.
	A new approach for the removal of mixed noise based on wavelet transform (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 作者: Li Y.; Li Y.; Li Y.; Li Y. 收藏 \| 浏览/下载：60/0 \| 提交时间：2013/03/25 This paper proposed a new approach for the removal of mixed noise. There are many different ways in image denoising. Donoho et al have proposed a method for image de-noising by thresholding ambiguity is often resulted in determining the correspondence of a modulus maximum to a singularity. In the light and indeed we combine the merits of the two techniques to form a new approach for the removal of mixed noise. At first the application of their method to image denoising has been extremely successful. But the method of Donoho is based on the assumption that the type of noise is only additive Gaussian noise we used wavelet singularity detection (WSD) technique to analyze singularities of signal and noise. According to the characteristic that wavelet transform modulus maxima of impulse noise rapidly decreases as the scale increases in wavelet domain which is not successful for impulse noise. Mallat has also presented a method for signal denoising by discriminating the noise and the signal singularities through an analysis of their wavelet transform modulus maxima (WTMM). Nevertheless it can be accurately located with multiscale space by going through dyadic orthogonal wavelet transform and removed. Furthermore the Gaussian noise is also removed through a level-dependent thresholding algorithm the tracing of WTMM is not just tedious procedure computationally algorithm. The experimental results demonstrate that the proposed method can effectively detect impulse noise and remove almost all of the noise while preserve image details very well.