中国科学院机构知识库网格系统: 检索

浏览/检索结果: 共7条，第1-7条

帮助

条数/页：排序方式：
	Gallium Anomaly: critical view from the global picture of nu(e) and (nu)over-bar(e) disappearance 期刊论文 OAI收割 JOURNAL OF HIGH ENERGY PHYSICS, 2022, 期号: 10, 页码: 164 作者: Giunti, C; Li, YF; Ternes, CA; Tyagi, O; Xin, Z \| 收藏 \| 浏览/下载：8/0 \| 提交时间：2023/11/10 Neutrino Mixing New Light Particles Specific BSM Phenomenology
	Applying land use regression model to estimate spatial variation of PM2.5 in Beijing, China SCI/SSCI论文 OAI收割 2015 作者: Wu J. S.; Li, J. C.; Peng, J.; Li, W. F.; Xu, G. 收藏 \| 浏览/下载：56/0 \| 提交时间：2015/12/09 Land use regression Fine particulate matter PM2.5 Spatiotemporal variation Outdoor exposure Air pollution Beijing particulate air-pollution new-york-city ambient fine particulate long-term exposure source apportionment urban area matter concentrations ultrafine particles sulfur-dioxide united-states
	The new approach for infrared target tracking based on the particle filter algorithm (EI CONFERENCE) 会议论文 OAI收割 International Symposium on Photoelectronic Detection and Imaging 2011: Advances in Infrared Imaging and Applications, May 24, 2011 - May 24, 2011, Beijing, China 作者: Sun H.; Han H.-X.; Sun H. 收藏 \| 浏览/下载：59/0 \| 提交时间：2013/03/25 Target tracking on the complex background in the infrared image sequence is hot research field. It provides the important basis in some fields such as video monitoring precision and video compression human-computer interaction. As a typical algorithms in the target tracking framework based on filtering and data connection the particle filter with non-parameter estimation characteristic have ability to deal with nonlinear and non-Gaussian problems so it were widely used. There are various forms of density in the particle filter algorithm to make it valid when target occlusion occurred or recover tracking back from failure in track procedure but in order to capture the change of the state space it need a certain amount of particles to ensure samples is enough and this number will increase in accompany with dimension and increase exponentially this led to the increased amount of calculation is presented. In this paper particle filter algorithm and the Mean shift will be combined. Aiming at deficiencies of the classic mean shift Tracking algorithm easily trapped into local minima and Unable to get global optimal under the complex background. From these two perspectives that "adaptive multiple information fusion" and "with particle filter framework combining" we expand the classic Mean Shift tracking framework.Based on the previous perspective we proposed an improved Mean Shift infrared target tracking algorithm based on multiple information fusion. In the analysis of the infrared characteristics of target basis Algorithm firstly extracted target gray and edge character and Proposed to guide the above two characteristics by the moving of the target information thus we can get new sports guide grayscale characteristics and motion guide border feature. Then proposes a new adaptive fusion mechanism used these two new information adaptive to integrate into the Mean Shift tracking framework. Finally we designed a kind of automatic target model updating strategy to further improve tracking performance. Experimental results show that this algorithm can compensate shortcoming of the particle filter has too much computation and can effectively overcome the fault that mean shift is easy to fall into local extreme value instead of global maximum value.Last because of the gray and fusion target motion information this approach also inhibit interference from the background ultimately improve the stability and the real-time of the target track. 2011 Copyright Society of Photo-Optical Instrumentation Engineers (SPIE).
	Manufacture of 1.2m reaction bonded silicon carbide mirror blank CFID (EI CONFERENCE) 会议论文 OAI收割 5th International Symposium on Advanced Optical Manufacturing and Testing Technologies: Large Mirrors and Telescopes, April 26, 2010 - April 29, 2010, Dalian, China 作者: Zhang G.; Zhang G.; Zhang G. 收藏 \| 浏览/下载：29/0 \| 提交时间：2013/03/25 Silicon carbide (SiC) is a new type candidate material for large-scale lightweight space mirror. Its low thermal distortion high stiffness fine optical quality and dimensional stability make SiC an ideal material for large space born telescope. Since ten years Changchun institute optics fine mechanics and physics (CIOMP) has developed reaction bonded SiC (RB-SiC) technology for space application and can fabricate RB-SiC mirror with scale less than 1.0 meter for telescope. The green body is prepared with gel-casting method which is an attractive new ceramic forming process for making high-quality complex-shaped ceramic parts. And then unmolding drying binder burning out reacting bonded the RB-SiC can be obtained. But with the development of space-born or ground telescope the scale of primary mirror has exceeded 1.0 meter. So CIOMP has developed an assembly technique which called novel reaction-formed joint technology for larger RB-SiC mirror blank. The steps include joining of green bodies with mixture comprised of SiC particles and phenolic resin etc firing machining and sintering. Joining the 1.2 meter RB-SiC mirror blank by the novel reaction-formed joint technology. And testing the welding layer's performance the results show that the thickness of 54-77m the microstructure and thermal property can be comparable to the substrate and the mechanical property are excellent in bending strength of 307MPa. 2010 Copyright SPIE - The International Society for Optical Engineering.
	Nuclear emulsion and high-energy physics 期刊论文 OAI收割 RADIATION MEASUREMENTS, 2008, 卷号: 43, 页码: S139-S143 作者: Sun, Hancheng; Zhang, Donghai \| 收藏 \| 浏览/下载：19/0 \| 提交时间：2018/05/31 new particles new hypernuclei ultra high-energy cosmic rays
	Real time tracking by LOPF algorithm with mixture model (EI CONFERENCE) 会议论文 OAI收割 MIPPR 2007: Automatic Target Recognition and Image Analysis; and Multispectral Image Acquisition, November 15, 2007 - November 17, 2007, Wuhan, China Meng B.; Zhu M.; Han G.; Wu Z. 收藏 \| 浏览/下载：26/0 \| 提交时间：2013/03/25 A new particle filter-the Local Optimum Particle Filter (LOPF) algorithm is presented for tracking object accurately and steadily in visual sequences in real time which is a challenge task in computer vision field. In order to using the particles efficiently we first use Sobel algorithm to extract the profile of the object. Then we employ a new Local Optimum algorithm to auto-initialize some certain number of particles from these edge points as centre of the particles. The main advantage we do this in stead of selecting particles randomly in conventional particle filter is that we can pay more attentions on these more important optimum candidates and reduce the unnecessary calculation on those negligible ones in addition we can overcome the conventional degeneracy phenomenon in a way and decrease the computational costs. Otherwise the threshold is a key factor that affecting the results very much. So here we adapt an adaptive threshold choosing method to get the optimal Sobel result. The dissimilarities between the target model and the target candidates are expressed by a metric derived from the Bhattacharyya coefficient. Here we use both the counter cue to select the particles and the color cur to describe the targets as the mixture target model. The effectiveness of our scheme is demonstrated by real visual tracking experiments. Results from simulations and experiments with real video data show the improved performance of the proposed algorithm when compared with that of the standard particle filter. The superior performance is evident when the target encountering the occlusion in real video where the standard particle filter usually fails.
	Diurnal variation of number concentration and size distribution of ultrafine particles in the urban atmosphere of beijing in winter 期刊论文 iSwitch采集 Journal of environmental sciences-china, 2007, 卷号: 19, 期号: 8, 页码: 933-938 作者: Shi Zong-bo; He Ke-bin; Yu Xue-chun; Yao Zhi-liang; Yang Fu-mo 收藏 \| 浏览/下载：32/0 \| 提交时间：2019/05/10 Fine particles Nucleation mode Aitken mode New particle formation