Un enfoque computacional para el análisis de composiciones artísticas

Los nuevos enfoques que surgen del análisis de obras de arte con herramientas computacionales tienen el potencial de ofrecer diferentes perspectivas a las obras de arte recreadas en medios digitales. Este artículo pretende revelar las relaciones implícitas entre las composiciones de Mondrian con diferentes representaciones visuales. En el ámbito del estudio, las composiciones completadas entre 1938 y 1943, que tienen una fuerte relación geometría-color, se investigaron primero a través de un enfoque basado en píxeles. En el método de fragmentación empleado a seguir, las similitudes y diferencias se expresan con datos transferidos de píxeles a matrices numéricas en dos pasos diferentes: 1) Entre los artefactos en pares, y 2) Entre un artefacto y todos los demás artefactos seleccionados. La visualización de las matrices estuvo representada por mapas de color 2D y mapas de textura 3D. Estos estilos de interpretación permiten que las composiciones se expresen de lo general a lo específico y nuevamente de lo específico a lo general, adquiriendo un nuevo significado.Novas abordagens emergem da análise de obras com ferramentas computacionais e têm potencial para oferecer diferentes perspectivas para obras recriadas em ambientes digitais. Este estudo visa revelar as relações implícitas entre as composições de Mondrian com diferentes representações visuais. No âmbito do estudo, as composições concluídas entre 1938 e 1943, que possuem uma forte relação geometria-cor, foram discutidas pela primeira vez com uma abordagem baseada em pixels. No método de fragmentação seguido, as semelhanças e diferenças são expressas com dados transferidos de pixels para matrizes numéricas em duas etapas distintas: 1. Entre os artefatos em pares, 2. Entre um artefato e todos os outros artefatos selecionados. A visualização das matrizes foi representada por mapas de cores 2D e mapas de texturas 3D. Esses estilos de interpretação permitem que as composições sejam expressas do geral para o específico e novamente do específico para o geral, ganhando um novo significado.New approaches emerging from the analysis of artworks with computational tools have the potential to offer different perspectives to artworks recreated in digital environments. This study aims to reveal the implicit relationships between Mondrian compositions with different visual representations. In the scope of the study, compositions completed between 1938 and 1943, which have a strong geometry-color relationship, were first investigated through a pixel-based approach. In the fragmentation method followed, the similarities and differences are expressed with data transferred from pixels to numerical matrices in two different steps: 1. Between the artifacts in pairs, 2. Between an artifact and all the other selected artifacts. The visualization of the matrices was represented by 2D color maps and 3D texture maps. These interpretation styles allow the compositions to be expressed from general to specific and again, from specific to general, by gaining a new meaning

Flexible Integration and Efficient Analysis of Multidimensional Datasets from the Web

If numeric data from the Web are brought together, natural scientists can compare climate measurements with estimations, financial analysts can evaluate companies based on balance sheets and daily stock market values, and citizens can explore the GDP per capita from several data sources. However, heterogeneities and size of data remain a problem. This work presents methods to query a uniform view - the Global Cube - of available datasets from the Web and builds on Linked Data query approaches

Copula mixed-membership stochastic block model

The Mixed-Membership Stochastic Blockmodels (MMSB) is a popular framework for modelling social relationships by fully exploiting each individual node's participation (or membership) in a social network. Despite its powerful representations, MMSB assumes that the membership indicators of each pair of nodes (i.e., people) are distributed independently. However, such an assumption often does not hold in real-life social networks, in which certain known groups of people may correlate with each other in terms of factors such as their membership categories. To expand MMSB's ability to model such dependent relationships, a new framework - a Copula Mixed-Membership Stochastic Blockmodel - is introduced in this paper for modeling intra-group correlations, namely an individual Copula function jointly models the membership pairs of those nodes within the group of interest. This framework enables various Copula functions to be used on demand, while maintaining the membership indicator's marginal distribution needed for modelling membership indicators with other nodes outside of the group of interest. Sampling algorithms for both the finite and infinite number of groups are also detailed. Our experimental results show its superior performance in capturing group interactions when compared with the baseline models on both synthetic and real world datasets

Deep into Pharo

International audienceThis is a book on Pharo a programming language available at http://www.pharo.or

Flexible Integration and Efficient Analysis of Multidimensional Datasets from the Web

If numeric data from the Web are brought together, natural scientists can compare climate measurements with estimations, financial analysts can evaluate companies based on balance sheets and daily stock market values, and citizens can explore the GDP per capita from several data sources. However, heterogeneities and size of data remain a problem. This work presents methods to query a uniform view - the Global Cube - of available datasets from the Web and builds on Linked Data query approaches