中国科学院机构知识库网格
Chinese Academy of Sciences Institutional Repositories Grid
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浏览/检索结果: 共9条,第1-9条 帮助

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Pt/Fe3O4 Core/Shell Triangular Nanoprisms by Heteroepitaxy: Facet Selectivity at the Pt-Fe3O4 Interface and the Fe3O4 Outer Surface 期刊论文  OAI收割
ACS NANO, 2015, 卷号: 9, 期号: 11, 页码: 10950—10960
作者:  
Jiang, MW;  Liu, W;  Yang, XL;  Jiang, Z;  Yao, T
收藏  |  浏览/下载:28/0  |  提交时间:2016/03/04
Ruthenium oxide-based nanocomposites with high specific surface area and improved capacitance as a supercapacitor 期刊论文  OAI收割
RSC ADVANCES, 2014, 卷号: 4, 期号: 81, 页码: 42839-42845
作者:  
Wang, Pengfei;  Liu, Hui;  Tan, Qiangqiang;  Yang, Jun
收藏  |  浏览/下载:19/0  |  提交时间:2015/04/01
Modelling sub-grid wetland in the ORCHIDEE global land surface model: evaluation against river discharges and remotely sensed data 期刊论文  OAI收割
GEOSCIENTIFIC MODEL DEVELOPMENT, 2012, 卷号: 5, 期号: 4, 页码: 941-962
Ringeval B (Ringeval, B.); Decharme B (Decharme, B.); Piao SL (朴世龙); Ciais P (Ciais, P.); Papa F (Papa, F.); de Noblet-Ducoudre N (de Noblet-Ducoudre, N.); Prigent C (Prigent, C.); Friedlingstein P (Friedlingstein, P.); Gouttevin I (Gouttevin, I.); Koven C (Koven, C.); Ducharne A (Ducharne, A.)
收藏  |  浏览/下载:21/0  |  提交时间:2013/05/29
An automatic pedestrian detection and tracking method: Based on mach and particle filter (EI CONFERENCE) 会议论文  OAI收割
2011 International Conference on Network Computing and Information Security, NCIS 2011, May 14, 2011 - May 15, 2011, Guilin, Guangxi, China
Han Q.; Yao Z.
收藏  |  浏览/下载:16/0  |  提交时间:2013/03/25
Plasmonic Gold-Superparamagnetic Hematite Heterostructures 期刊论文  OAI收割
Langmuir, 2011, 卷号: 27, 期号: 8, 页码: 5071-5075
Z. H. Bao; Z. H. Sun; Z. F. Li; L. W. Tian; T. Ngai; J. F. Wang
收藏  |  浏览/下载:163/0  |  提交时间:2012/04/13
Fibrous-structured magnetic and mesoporous Fe(3)O(4)/silica microspheres: synthesis and intracellular doxorubicin delivery 期刊论文  OAI收割
journal of materials chemistry, 2011, 卷号: 21, 期号: 41, 页码: 16420-16426
Gai SL; Yang PP; Ma PA; Wang D; Li CX; Li XB; Niu N; Lin J
收藏  |  浏览/下载:21/0  |  提交时间:2012/06/11
Using bidirectional binary particle swarm optimization for feature selection in feature-level fusion recognition system (EI CONFERENCE) 会议论文  OAI收割
2009 4th IEEE Conference on Industrial Electronics and Applications, ICIEA 2009, May 25, 2009 - May 27, 2009, Xi'an, China
作者:  
Wang D.;  Wang Y.;  Wang Y.;  Wang Y.;  Wang Y.
收藏  |  浏览/下载:22/0  |  提交时间:2013/03/25
In feature-level fusion recognition system  the other is optimizing system sensor design to get outstanding cost performance. So feature selection become usually necessary to reduce dimensionality of the combination of multi-sensor features and improve system performance in system design. In general  there are two main missions. One is improving the recognition correct rate as soon as possible  the optimization is usually applied to feature selection because of its computational feasibility and validity. For further improving recognition accuracy and reducing selected feature dimensions  this paper presents a more rational and accurate optimization  Bidirectional Binary Particle Swarm Optimization (BBPSO) algorithm for feature selection in feature-level fusion target recognition system. In addition  we introduce a new evaluating function as criterion function in BBPSO feature selection method. At the last  we utilized Leave-One-Out method to validate the proposed method. The experiment results show that the proposed algorithm improves classification accuracy by two percentage points  while the selected feature dimensions are less one dimension than original Particle Swarm Optimization approach with 16 original feature dimensions. 2009 IEEE.  
Scaling up ecosystem productivity from patch to landscape: a case study of Changbai Mountain Nature Reserve, China SCI/SSCI论文  OAI收割
2007
Zhang N.; Yu Z. L.; Yu G. R.; Wu J. G.
收藏  |  浏览/下载:27/0  |  提交时间:2012/06/08
Measuring the system gain of the TDI CCD remote sensing camera (EI CONFERENCE) 会议论文  OAI收割
Advanced Materials and Devices for Sensing and Imaging II, November 8, 2004 - November 10, 2004, Beijing, China
Ya-xia L.; Hai-ming B.; Jie L.; Jin R.; Zhi-hang H.
收藏  |  浏览/下载:62/0  |  提交时间:2013/03/25
The gain of a TDI CCD camera is the conversion between the number of electrons recorded by the TDI CCD and the number of digital units (counts) contained in the CCD image"[1]. TDI CCD camera has been a main technical approach for meeting the requirements of high-resolution and lightweight of remote sensing equipment. It is useful to know this conversion for evaluating the performance of the TDI CCD camera. In general  a lower gain is better. However  the resulting slope is the gain of the TDI CCD. We did the experiments using the Integration Sphere in order to get a flat field effects. We calculated the gain of the four IT-EI-2048 TDI CCD. The results and figures of the four TDI CCD are given.  this is only true as long as the total well depth (number of electrons that a pixel can hold) of the pixels can be represented. High gains result in higher digitization noise. System gains are designed to be a compromise between the extremes of high digitization noise and loss of well depth. In this paper  the mathematical theory is given behind the gain calculation on a TDI CCD camera and shows how the mathematics suggests ways to measure the gain accurately according to the Axiom Tech. The gains were computed using the mean-variance method  also known as the method of photon transfer curves. This method uses the effect of quantization on the variance in the measured counts over a uniformly illuminated patch of the detector. This derivation uses the concepts of signal and noise. A linear fit is done of variance vs. mean