Automated chemical structure analysis of organic molecules with a molecular structure generator and pattern recognition techniques

1975 ◽  
Vol 47 (11) ◽  
pp. 1829-1835 ◽  
Author(s):  
Hidetsugu. Abe ◽  
Peter C. Jurs
Keyword(s):  
Molecular Structure ◽  
Pattern Recognition ◽  
Structure Analysis ◽  
Chemical Structure ◽  
Organic Molecules ◽  
Pattern Recognition Techniques ◽  
Structure Generator

Generation of Simulated Mass Spectra of Small Organic Molecules by Computerized Pattern Recognition Techniques

1973 ◽  
Vol 27 (1) ◽  
pp. 30-40 ◽  
Author(s):  
Joseph Schechter ◽  
Peter C. Jurs
Keyword(s):  
Pattern Recognition ◽  
Mass Spectra ◽  
Organic Molecules ◽  
Molecular Descriptor ◽  
Empirical Method ◽  
Molecular Structures ◽  
Small Organic Molecules ◽  
Mass Spectral ◽  
Pattern Recognition Techniques ◽  
System A

An empirical method employing computerized pattern recognition techniques has been applied to the generation of simulated mass spectra of small organic molecules. Molecular structures are represented in computer-compatible form through the use of a fragmentation code which assigns code designations to specific groups of atoms and/or bonds within the molecules. Using such descriptions of molecules, pattern classifiers have been developed to predict the presence or absence of mass spectral peaks in each of 60 nominal m/e positions and to give a measure of the intensity of peaks in 11 of these. Information in the molecular descriptor lists which correlates with the appearance of specific peaks is shown to be present in relatively few of the descriptors developed. To test the complete system, a number of entire mass spectra were developed; in this test, 93% of the classifications were made correctly.

EEG-Based Emotion Recognition Using Different Neural Network and Pattern Recognition Techniques A Review

2019 ◽  
Vol 7 (1) ◽  
pp. 615-618
Author(s):  
Y. M. Rajput ◽  
S. Abdul Hannan ◽  
M. Eid Alzahrani ◽  
Ramesh R. Manza ◽  
Dnyaneshwari D. Patil
Keyword(s):  
Neural Network ◽  
Pattern Recognition ◽  
Emotion Recognition ◽  
Pattern Recognition Techniques

Gravity Models in International Trade: An Exploration in Econo-Physics

2021 ◽  
pp. 227797872198992
Author(s):  
Iman Pal ◽  
Saibal Kar
Keyword(s):  
Pattern Recognition ◽  
International Trade ◽  
Present Article ◽  
Gravity Models ◽  
Scientific Applications ◽  
Physical Sciences ◽  
Trade Patterns ◽  
Pattern Recognition Techniques ◽  
The Subject ◽  
Jel Classifications

Several strands of the static and dynamic theoretical constructs and the empirical applications in the subject of economics owe substantially to the well-known principles of physical sciences. The present article explores as to how the development of the popular gravity models in international trade can be traced back to Newton’s law of gravitation, and to both Ohm’s Law and Kirchhoff’s Law of current electricity, as well as to the pattern recognition techniques commonly deployed in scientific applications. In addition to surveying these theoretical analogies, the article also offers numerical applications for observed trade patterns between India and a set of countries. JEL Classifications: F41, F42, C61, F47

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