Experimental demonstration of phase determination in neutron reflectometry by variation of the surrounding media

2000 ◽  
Vol 283 (1-3) ◽  
pp. 248-252 ◽  
Author(s):  
C.F. Majkrzak ◽  
N.F. Berk ◽  
V. Silin ◽  
C.W. Meuse
1998 ◽  
Vol 248 (1-4) ◽  
pp. 338-342 ◽  
Author(s):  
C.F. Majkrzak ◽  
N.F. Berk ◽  
J.A. Dura ◽  
S.K. Satija ◽  
A. Karim ◽  
...  

2019 ◽  
Vol 1389 ◽  
pp. 012153 ◽  
Author(s):  
E S Nikova ◽  
Yu A Salamatov ◽  
E A Kravtsov ◽  
V V Ustinov

Author(s):  
Douglas L. Dorset

The quantitative use of electron diffraction intensity data for the determination of crystal structures represents the pioneering achievement in the electron crystallography of organic molecules, an effort largely begun by B. K. Vainshtein and his co-workers. However, despite numerous representative structure analyses yielding results consistent with X-ray determination, this entire effort was viewed with considerable mistrust by many crystallographers. This was no doubt due to the rather high crystallographic R-factors reported for some structures and, more importantly, the failure to convince many skeptics that the measured intensity data were adequate for ab initio structure determinations.We have recently demonstrated the utility of these data sets for structure analyses by direct phase determination based on the probabilistic estimate of three- and four-phase structure invariant sums. Examples include the structure of diketopiperazine using Vainshtein's 3D data, a similar 3D analysis of the room temperature structure of thiourea, and a zonal determination of the urea structure, the latter also based on data collected by the Moscow group.


2008 ◽  
Vol 128 (4) ◽  
pp. 677-682 ◽  
Author(s):  
Taku Takaku ◽  
Noriyuki Iwamuro ◽  
Yoshiyuki Uchida ◽  
Ryuichi Shimada

Author(s):  
Suresha .M ◽  
. Sandeep

Local features are of great importance in computer vision. It performs feature detection and feature matching are two important tasks. In this paper concentrates on the problem of recognition of birds using local features. Investigation summarizes the local features SURF, FAST and HARRIS against blurred and illumination images. FAST and Harris corner algorithm have given less accuracy for blurred images. The SURF algorithm gives best result for blurred image because its identify strongest local features and time complexity is less and experimental demonstration shows that SURF algorithm is robust for blurred images and the FAST algorithms is suitable for images with illumination.


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