中国科学院机构知识库网格系统: 检索

Ab initio calculations of the hyperfine structure of 109Cd, 109Cd+ and reevaluation of the nuclear quadrupole moment Q(109Cd) 期刊论文 OAI收割
Journal of Physics B: Atomic, Molecular and Optical Physics, 2022, 卷号: 55, 期号: 20
作者: Lu,Benquan; Lu,Xiaotong; Wang,Tao; Chang,Hong

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收藏 | 浏览/下载：4/0 | 提交时间：2023/12/13

hyperfine structure nuclear quadrupole moment multi-configuration Dirac–Hartree–Fock theory cadmium

Attention-Based Multi-Source Domain Adaptation 期刊论文 OAI收割
IEEE TRANSACTIONS ON IMAGE PROCESSING, 2021, 卷号: 30, 页码: 3793-3803
作者: Zuo, Yukun; Yao, Hantao; Xu, Changsheng

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收藏 | 浏览/下载：38/0 | 提交时间：2021/05/06

Correlation Adaptation models Feature extraction Target recognition Data models Transfer learning Visualization Multi-source domain adaptation attention-based multi-source domain adaptation weighted moment distance

Multi-source Remote Sensing Image Registration Based on Contourlet Transform and Multiple Feature Fusion 期刊论文 OAI收割
International Journal of Automation and Computing, 2019, 卷号: 16, 期号: 5, 页码: 575-588
作者: Huan Liu; Gen-Fu Xiao; Yun-Lan Tan; Chun-Juan Ouyang

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收藏 | 浏览/下载：7/0 | 提交时间：2021/02/22

Feature fusion multi-scale circle Gaussian combined invariant moment multi-direction gray level co-occurrence matrix multi-source remote sensing image registration contourlet transform.

Calibration and decoupling of multi-axis robotic Force/Moment sensors 期刊论文 OAI收割
ROBOTICS AND COMPUTER-INTEGRATED MANUFACTURING, 2018, 卷号: 49, 期号: 无, 页码: 301-308
作者: Liang, Qiaokang; Wu, Wanneng; Coppola, Gianmarc; Zhang, Dan; Sun, Wei

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收藏 | 浏览/下载：84/0 | 提交时间：2018/08/17

Robotic Sensory System Multi-axis Force/moment Sensors Calibration And Decoupling Extreme Learning Machine

Development of a hybrid parallel MCV-based high-order global shallow-water model 期刊论文 OAI收割
The Journal of Supercomputing, 2017, 卷号: 73, 期号: 6, 页码: 2823–2842
作者: Peng Zhang; Chao Yang; Chungang Chen; Xingliang Li; Xueshun Shen

收藏 | 浏览/下载：29/0 | 提交时间：2017/07/08

Global shallow-water model Multi-moment constrained volume method Cubed-sphere Intel Xeon Phi Parallel scalability

A Slope Constrained 4th Order Multi-Moment Finite Volume Method with WENO Limiter 期刊论文 OAI收割
COMMUNICATIONS IN COMPUTATIONAL PHYSICS, 2015, 卷号: 18, 期号: 4, 页码: 901-930
作者: Sun ZY; Teng HH(滕宏辉); Xiao F

收藏 | 浏览/下载：85/0 | 提交时间：2016/01/08

Multi-moment finite volume method WENO flux reconstruction compressible flow conservative method oscillation-suppressing

A global shallow-water model on an icosahedral-hexagonal grid by amulti-moment constrained finite-volume scheme 期刊论文 OAI收割
Quarterly Journal of The Royal Meteorological Society, 2014, 卷号: 140, 期号: 679, 页码: 639-650
作者: Chen CG(陈春刚); Bin JZ(宾聚忠); Xiao F(肖锋); Li XL; Shen XS

收藏 | 浏览/下载：46/0 | 提交时间：2014/07/03

global model icosahedral-hexagonal grid multi-moment constraints high-order scheme shallow-water equations

Multi-Dimensional MEMS/Micro Sensor for Force and Moment Sensing: A Review 期刊论文 OAI收割
IEEE SENSORS JOURNAL, 2014, 卷号: 14, 期号: 8, 页码: 2643-2657
作者: Qiaokang Liang; Dan Zhang; Gianmarc Coppola; Yaonan Wang; Sun Wei

收藏 | 浏览/下载：26/0 | 提交时间：2016/03/22

Multi-dimensional Force Measurement Micro Sensor Moment Measurement

Aircraft flight simulation with landing gear based on multi-domain modeling technology (EI CONFERENCE) 会议论文 OAI收割
2012 2nd International Conference on Computer Application and System Modeling, ICCASM 2012, July 27, 2012 - July 29, 2012, Shenyang, China
作者: Li M.

收藏 | 浏览/下载：16/0 | 提交时间：2013/03/25

This paper create a full aircraft flight simulation model for accurately analyzing the performance and influence of landing gear system. The use of multi-domain modeling technology enables detailed modeling of the flight dynamic and landing gear dynamic. The simulation results show that the aircraft landing gear system mathematical model established appropriately reflects the change of force and moment in the process of taking off and landing and it is actual in the physical process. The parameter design space is easily searched by considering a number of different landing scenarios to optimize the design. the authors.

Multi-focus image fusion algorithm based on adaptive PCNN and wavelet transform (EI CONFERENCE) 会议论文 OAI收割
International Symposium on Photoelectronic Detection and Imaging 2011: Advances in Imaging Detectors and Applications, May 24, 2011 - May 26, 2011, Beijing, China
Wu Z.-G.; Wang M.-J.; Han G.-L.

收藏 | 浏览/下载：78/0 | 提交时间：2013/03/25

Being an efficient method of information fusion image fusion has been used in many fields such as machine vision medical diagnosis military applications and remote sensing.In this paper Pulse Coupled Neural Network (PCNN) is introduced in this research field for its interesting properties in image processing including segmentation target recognition et al. and a novel algorithm based on PCNN and Wavelet Transform for Multi-focus image fusion is proposed. First the two original images are decomposed by wavelet transform. Then based on the PCNN a fusion rule in the Wavelet domain is given. This algorithm uses the wavelet coefficient in each frequency domain as the linking strength so that its value can be chosen adaptively. Wavelet coefficients map to the range of image gray-scale. The output threshold function attenuates to minimum gray over time. Then all pixels of image get the ignition. So the output of PCNN in each iteration time is ignition wavelet coefficients of threshold strength in different time. At this moment the sequences of ignition of wavelet coefficients represent ignition timing of each neuron. The ignition timing of PCNN in each neuron is mapped to corresponding image gray-scale range which is a picture of ignition timing mapping. Then it can judge the targets in the neuron are obvious features or not obvious. The fusion coefficients are decided by the compare-selection operator with the firing time gradient maps and the fusion image is reconstructed by wavelet inverse transform. Furthermore by this algorithm the threshold adjusting constant is estimated by appointed iteration number. Furthermore In order to sufficient reflect order of the firing time the threshold adjusting constant is estimated by appointed iteration number. So after the iteration achieved each of the wavelet coefficient is activated. In order to verify the effectiveness of proposed rules the experiments upon Multi-focus image are done. Moreover comparative results of evaluating fusion quality are listed. The experimental results show that the method can effectively enhance the edge details and improve the spatial resolution of the image. 2011 SPIE.