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	Invariance of factor structure of the 21-item Peters et al. Delusions Inventory (PDI-21) over time and across samples 期刊论文 OAI收割 PSYCHIATRY RESEARCH, 2017, 卷号: 254, 期号: 0, 页码: 190-197 作者: Wang, Yan-Yu; Shi, Hai-Song; Liu, Wen-Hua; Yan, Chao; Wang, Yi 收藏 \| 浏览/下载：97/0 \| 提交时间：2017/08/07 The 21-item Peters et al. Delusions Inventory (PDI-21) Delusion Schizophrenia Longitudinal invariance Cross-sample invariance
	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：84/0 \| 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.
	Imaging quality analysis of KBA x-ray microscope working at grazing incidence (EI CONFERENCE) 会议论文 OAI收割 Optical Design and Testing II, November 8, 2004 - November 11, 2004, Beijing, United states 作者: Zhao L. 收藏 \| 浏览/下载：32/0 \| 提交时间：2013/03/25 In the latest 20 years x-ray imaging technology has developed fast in order to meet the need of x-ray photo-etching spatial exploration technology high-energy physics procedure diagnosis of inertial confinement fusion (ICF) et al. Since refractive index of materials in the x-ray region is lower than 1 and x-ray is strongly absorbed by materials it is very difficult to image objects in the x-ray region. Conventional imaging methods are hardly suitable to x-ray range. In general grazing reflective imaging and coding aperture imaging methods have been adopted more and more. In this paper according to user's requirement we have designed a non-coaxial grazing KBA microscope. The microscope consists of two sets of perpendicular spherical mirrors each set includes two parallel mirrors. Taking it as an example we have compiled an optical computing program for the non-coaxial grazing imaging systems so as to analyze and evaluate aberrations of KBA microscope. Thus it can help us to get an optimal comprehension of KBA x-ray imaging system. In the same time the analytical results provide reliable foundation for evaluating imaging quality of KBA microscope.