the aim of this work is to use self organizing map (som) for clustering of locomotion kinetic characteristics in normal and parkinson’s disease. the classification and analysis of the kinematic characteristics of human locomotion has been greatly increased by the use of artificial neural networks in recent years. the proposed methodology aims at overcoming the constraints of traditional analysi...

With rapid advances in genomics, phylogenetics has turned to phylogenomics due to the availability of large amounts of sequence and genome data. However, incongruence between species trees and gene trees remains a challenge in molecular phylogenetics for its biological and algorithmic complexities. A state-of-the-art gene concatenation approach was proposed to resolve this problem by inferring ...

In recent years, the proliferation of multi-temporal census data products and the increased capabilities of geospatial analysis and visualization techniques have encouraged longitudinal analyses of socioeconomic census data. Traditional cartographic methods for illustrating socioeconomic change tend to rely either on comparison of multiple temporal snapshots or on explicit representation of the...

In this contribution we present two experimental scenarios in which we employed Self Organizing Maps (SOMs) to detect affective states. The first scenario is related towards designing a “Personal Stress Prevention Assistant”: we summarize our efforts to detect affective information related to stress in the posture channel. We show that a person-independent discrimination of stress from cognitiv...

This paper presents how Self-Organizing Maps and especially Kohonen maps can be applied to digital images of ancient collections in the perspective of valorization and diffusion. As an illustration, a scheme of transparency reduction of the digitized Gutenberg Bible is presented. In this two steps method, the Kohonen map is trained to generate a set of test vectors that will train in a supervis...

Manuel Rubio, Vı́ctor Giménez, Francisco Dı́az and Pedro Gómez 1 Departamento de Arquitectura y Tecnologı́a de Sistemas Informáticos 2 Departamento de Matemática Aplicada Facultad de Informática, Universidad Politécnica de Madrid Campus de Montegancedo, 28660 Boadilla del Monte, Madrid, Spain [email protected], [email protected] [email protected], [email protected]...

Current research on machine learning and related algorithms is focused mainly on numeric paradigms. It is, however, widely supposed that intelligent behavior strongly relies on ability to manipulate symbols. In this paper we present on-line versions of self-organizing maps for symbol strings. The underlying key concepts are average and similarity, applied on strings. These concepts are easily d...

Searching for relevant text documents has traditionally been based on keywords and Boolean expressions of them. Often the search results show high recall and low precision, or vice versa. Considerable eeorts have been made to develop alternative methods, but their practical applicability has been low. Powerful methods are needed for the exploration of miscellaneous document collections. The WEB...