An Enhancement of the Usage of the Poincare Index for the Detection and Classification of Characteristic Points in Dactylograms

2011 ◽  
pp. 117-124
Author(s):  
Angélica González ◽  
Marco A. Ameller F.
Keyword(s):  
Poincaré Index ◽  
Characteristic Points ◽  
Poincare Index

scholarly journals Poincaré index and the volume functional of unit vector fields on punctured spheres

2019 ◽  
Vol 161 (3-4) ◽  
pp. 487-499
Author(s):  
Fabiano G. B. Brito ◽  
André O. Gomes ◽  
Icaro Gonçalves
Keyword(s):  
Vector Fields ◽  
Unit Vector ◽  
Volume Functional ◽  
Poincaré Index ◽  
Unit Vector Fields ◽  
Poincare Index

scholarly journals Poincaré index of plane polynomial fields of third and fourth degree

2019 ◽  
Vol 55 (1) ◽  
pp. 22-31
Author(s):  
P. P. Zabreiko ◽  
A. V. Krivko-Krasko
Keyword(s):  
Singular Point ◽  
Greatest Common Divisor ◽  
Fourth Degree ◽  
Real Zeros ◽  
Poincaré Index ◽  
Poincare Index

The conditions of isolation of a zero singular point of plane polynomial fields of third and fourth degree are considered in terms of the coefficients of the components of these fields. The isolation conditions depend on the greatest common divisor of the components of polynomial fields: in some cases only on its degree, and in some cases, additionally, on the presence of nonzero real zeros. The reasoning, which allows one to write out the isolation conditions, is based on the concept of the resultant and subresultants of components of plane polynomial fields. If the zero singular point is isolated, its index is calculated through the values of subresultants and coefficients of components.

scholarly journals Development of a method of exposed characteristic points in activity pattern for rat behaviour classification

2012 ◽  
Vol 18 (1) ◽  
pp. 23-28
Author(s):  
Kamil Stefko ◽  
Tomasz Bukowski ◽  
Michał Urbański
Keyword(s):  
Locomotor Activity ◽  
Activity Pattern ◽  
Fast Method ◽  
Activity Data ◽  
Activity Diagram ◽  
Laboratory Rats ◽  
Characteristic Points ◽  
Classic Form ◽  
Build System

A fast method for visual inspection and classification of massive locomotor activity data registered from laboratory rats is presented. Positions in the home cage of one hundred rats have been constantly recorded during 90 day period using photodiodes and beam crossing method with use of custom build system. Direct inspection and comparison of classic form of actograms did not bring information for fast and easy recognition of anomalies in daily behavioural cycle. A method of obtaining fast and easy to compare locomotor activity pattern is presented. The key point of proposed method is exposition of characteristic points in the activity diagram. About 9000 actograms were inspected and classified for investigation with use of ANOVA.

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