Hierarchical Indexing for Out-of-Core Access to Multi-Resolution Data

2003 ◽  
pp. 225-241 ◽  
Author(s):  
Valerio Pascucci ◽  
Randall J. Frank
Keyword(s):  
Resolution Data

Energy-filtered imaging of polymer microstructure

1996 ◽  
Vol 54 ◽  
pp. 162-163
Author(s):  
K. Siangchaew ◽  
J. Bentley ◽  
M. Libera
Keyword(s):  
Energy Loss ◽  
Heavy Element ◽  
Spectroscopic Imaging ◽  
Data Set ◽  
Polymer Microstructure ◽  
Entire Energy ◽  
Staining Methods ◽  
Spectrum Imaging ◽  
Resolution Data

Energy-filtered electron-spectroscopic TEM imaging provides a new way to study the microstructure of polymers without heavy-element stains. Since spectroscopic imaging exploits the signal generated directly by the electron-specimen interaction, it can produce richer and higher resolution data than possible with most staining methods. There are basically two ways to collect filtered images (fig. 1). Spectrum imaging uses a focused probe that is digitally rastered across a specimen with an entire energy-loss spectrum collected at each x-y pixel to produce a 3-D data set. Alternatively, filtering schemes such as the Zeiss Omega filter and the Gatan Imaging Filter (GIF) acquire individual 2-D images with electrons of a defined range of energy loss (δE) that typically is 5-20 eV.

Proteins and direct methods

1991 ◽  
Vol 197 (3-4) ◽  
Author(s):  
Fan Hai-fu ◽  
Hao Quan ◽  
M. M. Woolfson
Keyword(s):  
First Principles ◽  
Figure Of Merit ◽  
Direct Methods ◽  
Large Structure ◽  
Low Resolution ◽  
Figures Of Merit ◽  
Large Structures ◽  
Resolution Data

AbstractConventional direct methods, which work so well for small structures, are less successful for macromolecules. Where it has been demonstrated that a solution might be found using direct methods it is then found that the usual figures of merit are unable to distinguish the few good sets of phases from the large number of sets generated. The reasons for the difficulties with very large structures are considered from a first-principles approach taking into account both the factors of having a large number of atoms and low resolution data. A proposal is made for trying to recognize good phase sets by taking a large structure as a sum of a number of smaller structures for each of which a conventional figure of merit can be applied.

Application of multi-resolution data fusion algorithm

2010 ◽  
Vol 30 (9) ◽  
pp. 2556-2558 ◽  
Author(s):  
Ming-bo SHI ◽  
Ji-hong CHEN ◽  
Zheng-zheng JIANG
Keyword(s):  
Data Fusion ◽  
Fusion Algorithm ◽  
Resolution Data

Using high resolution data to reveal depth-dependent mechanisms that drive land subsidence: The Venice coast, Italy

2009 ◽  
Vol 474 (1-2) ◽  
pp. 271-284 ◽  
Author(s):  
L. Tosi ◽  
P. Teatini ◽  
L. Carbognin ◽  
G. Brancolini
Keyword(s):  
High Resolution ◽  
Land Subsidence ◽  
High Resolution Data ◽  
Resolution Data

A Wavelet-Enhanced Inversion Method for Water Quality Retrieval From High Spectral Resolution Data for Complex Waters

2015 ◽  
Vol 53 (2) ◽  
pp. 869-882 ◽  
Author(s):  
Eva M. Ampe ◽  
Dries Raymaekers ◽  
Erin L. Hestir ◽  
Maarten Jansen ◽  
Els Knaeps ◽  
...  
Keyword(s):  
Water Quality ◽  
Spectral Resolution ◽  
High Spectral Resolution ◽  
Inversion Method ◽  
Resolution Data
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