Improving a leaves automatic recognition process using PCA

In this work we present a simulation of a recognition process with perimeter characterization of a simple plant leaves as a unique discriminating parameter. Data coding allowing for independence of leaves size and orientation may penalize performance recognition for some varieties. Border description sequences are then used, and Principal Component Analysis (PCA) is applied in order to study which is the best number of components for the classification task, implemented by means of a Support Vector Machine (SVM) System. Obtained results are satisfactory, and compared with [4] our system improves the recognition success, diminishing the variance at the same time.

Automatic Recognition of Leaves by Shape Detection Pre-Processing with Ica

In this work we present a simulation of a recognition process with perimeter characterization of a simple plant leaves as a unique discriminating parameter. Data coding allowing for independence of leaves size and orientation may penalize performance recognition for some varieties. Border description sequences are then used to characterize the leaves. Independent Component Analysis (ICA) is then applied in order to study which is the best number of components to be considered for the classification task, implemented by means of an Artificial Neural Network (ANN). Obtained results with ICA as a pre-processing tool are satisfactory, and compared with some references our system improves the recognition success up to 80.8% depending on the number of considered independent components.

Metabolic origin of δ15N values in nitrogenous compounds from Brassica napus L. leaves

Nitrogen isotope composition (δ15N) in plant organic matter is currently used as a natural tracer of nitrogen acquisition efficiency. However, the δ15N value of whole leaf material does not properly reflect the way in which N is assimilated because isotope fractionations along metabolic reactions may cause substantial differences among leaf compounds. In other words, any change in metabolic composition or allocation pattern may cause undesirable variability in leaf δ15N. Here, we investigated the δ15N in different leaf fractions and individual metabolites from rapeseed (Brassica napus) leaves. We show that there were substantial differences in δ15N between nitrogenous compounds (up to 30 ) and the content in (15N enriched) nitrate had a clear influence on leaf δ15N. Using a simple steady-state model of day metabolism, we suggest that the δ15N value in major amino acids was mostly explained by isotope fractionation associated with isotope effects on enzyme-catalysed reactions in primary nitrogen metabolism. δ15N values were further influenced by light versus dark conditions and the probable occurrence of alternative biosynthetic pathways. We conclude that both biochemical pathways (that fractionate between isotopes) and nitrogen sources (used for amino acid production) should be considered when interpreting the δ15N value of leaf nitrogenous compounds

Voting by committees with exit

We study the problem of a society choosing a subset of new members from a finite set of candidates (as in Barberà, Sonnenschein, and Zhou, 1991). However, we explicitly consider the possibility that initial members of the society (founders) may want to leave it if they do not like the resulting new society. We show that, if founders have separable (or additive) preferences, the unique strategy-proof and stable social choice function satisfying voters' sovereignty (on the set of candidates) is the one where candidates are chosen unanimously and no founder leaves the society.

Note on homology of expanding foliations

This note contains some remarks about the homologies that can be associated to a foliation which is invariant and uniformly expanded by a diffeomorphism. We construct a family of 'dynamical' closed currents supported on the foliation which help us relate the geometric volume growth of the leaves under the diffeomorphism with the map induced on homology in the case when these currents have nonzero homology.