Visual-Empirical Region-of-Influence Pattern Recognition Applied to Chemical Microsensor Array Selection and Chemical Analysis

1998 ◽  
Vol 31 (5) ◽  
pp. 297-305 ◽  
Author(s):  
G. C. Osbourn ◽  
J. W. Bartholomew ◽  
A. J. Ricco ◽  
G. C. Frye
Keyword(s):  
Pattern Recognition ◽  
Chemical Analysis

CHEMICAL ANALYSIS METHODS FOR CRUDE OIL

1995 ◽  
Vol 1995 (1) ◽  
pp. 1004-1006
Author(s):  
Zhendi Wang ◽  
Mervin F. Fingas
Keyword(s):  
Pattern Recognition ◽  
Chemical Analysis ◽  
Crude Oil ◽  
Analysis Method ◽  
Weathered Oil ◽  
Specific Individual ◽  
Using Data ◽  
Oil Exposure ◽  
Spilled Oil ◽  
Weathering Process

ABSTRACT Using an oil chemical analysis method developed in our laboratory, more than 280 compounds in the Alberta Sweet Mixed Blend (ASMB) oil have been positively identified. The distribution of selected target compounds offers unique and sensitive fingerprints for matching the source of spilled oil and tracing the weathering process of oil in the environment. The pattern recognition plots involving more than 100 oil-specific individual components and component groupings permit deduction of a best set of values for oil exposure to weathering. Using data from different samples including crude oil, weathered oil, and 22-year-old spilled oil as examples, the distinct advantages of the described method over the current methods are examined.

Classification of weathered crude oils using multimethod chemical analysis, statistical methods and SIMCA pattern recognition

1986 ◽  
Vol 17 (8) ◽  
pp. 366-373 ◽  
Author(s):  
K Urdal ◽  
N.B Vogt ◽  
S.P Sporstøl ◽  
R.G Lichtenthaler ◽  
H Mostad ◽  
...  
Keyword(s):  
Pattern Recognition ◽  
Chemical Analysis ◽  
Statistical Methods ◽  
Crude Oils

Aspects of microanalysis in a transmission electron microscope

1978 ◽  
Vol 36 (1) ◽  
pp. 510-511
Author(s):  
R. Sinclair ◽  
B.E. Jacobson
Keyword(s):  
Grain Size ◽  
Electron Beam ◽  
Electron Microscope ◽  
Chemical Analysis ◽  
Transmission Electron Microscope ◽  
Vapor Deposition ◽  
Critical Currents ◽  
X Ray ◽  
Fine Grain ◽  
Transmission Electron

INTRODUCTIONThe prospect of performing chemical analysis of thin specimens at any desired level of resolution is particularly appealing to the materials scientist. Commercial TEM-based systems are now available which virtually provide this capability. The purpose of this contribution is to illustrate its application to problems which would have been intractable until recently, pointing out some current limitations.X-RAY ANALYSISIn an attempt to fabricate superconducting materials with high critical currents and temperature, thin Nb3Sn films have been prepared by electron beam vapor deposition [1]. Fine-grain size material is desirable which may be achieved by codeposition with small amounts of Al2O3 . Figure 1 shows the STEM microstructure, with large (∽ 200 Å dia) voids present at the grain boundaries. Higher quality TEM micrographs (e.g. fig. 2) reveal the presence of small voids within the grains which are absent in pure Nb3Sn prepared under identical conditions. The X-ray spectrum from large (∽ lμ dia) or small (∽100 Ǻ dia) areas within the grains indicates only small amounts of A1 (fig.3).

Software pattern recognition applied to nanodiffraction patterns from a STEM instrument

1986 ◽  
Vol 44 ◽  
pp. 694-695
Author(s):  
G.Y. Fan ◽  
J.M. Cowley
Keyword(s):  
Image Processing ◽  
Pattern Recognition ◽  
Computer Software ◽  
Processing System ◽  
Light Level ◽  
Host Computer ◽  
Low Light ◽  
Image Processing System ◽  
Recent Developments ◽  
On Line

In recent developments, the ASU HB5 has been modified so that the timing, positioning, and scanning of the finely focused electron probe can be entirely controlled by a host computer. This made the asynchronized handshake possible between the HB5 STEM and the image processing system which consists of host computer (PDP 11/34), DeAnza image processor (IP 5000) which is interfaced with a low-light level TV camera, array processor (AP 400) and various peripheral devices. This greatly facilitates the pattern recognition technique initiated by Monosmith and Cowley. Software called NANHB5 is under development which, instead of employing a set of photo-diodes to detect strong spots on a TV screen, uses various software techniques including on-line fast Fourier transform (FFT) to recognize patterns of greater complexity, taking advantage of the sophistication of our image processing system and the flexibility of computer software.

Integrated morphometrical and electron energy loss image analysis in cytochemistry

1989 ◽  
Vol 47 ◽  
pp. 402-403
Author(s):  
W.C. de Bruijn ◽  
A.A.W. de Jong ◽  
C.W.J. Sorber
Keyword(s):  
Image Analysis ◽  
Acid Phosphatase ◽  
Chemical Analysis ◽  
Active Form ◽  
List Type ◽  
Type Number ◽  
Enzyme Cytochemistry ◽  
Related Data ◽  
Endogenous Peroxidase ◽  
Electron Energy Loss

One aspect of enzyme cytochemistry is, whether all macrophage lysosomal hydrolytical enzymes are present in an active form, or are activated upon stimulation. Integrated morphometrical and chemical analysis has been chosen as a tool to illucidate that cytochemical problem. Mouse peritoneal resident macrophages have been used as a model for this complicated integration of morphometrical and element-related data. Only aldehyde-fixed cells were treated with three cytochemical reactions to detect different enzyme activities within one cell (for details see [1,2]). The enzyme-related precipitates anticipated to be differentiated, were:(1).lysosomal barium and sulphur from aryl sulphatase activity,(2).lysosomal cerium and phosphate from acid phosphatase activity and(3).platinum/di-amino-benzidine( D A B) complex from endogenous peroxidase activity.

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