Agrupamento de dados visual interactivo

Com a crescente geração, armazenamento e disseminação da informação nos últimos anos, o anterior problema de falta de informação transformou-se num problema de extracção do conhecimento útil a partir da informação disponível. As representações visuais da informação abstracta têm sido utilizadas para auxiliar a interpretação os dados e para revelar padrões de outra forma escondidos. A visualização de informação procura aumentar a cognição humana aproveitando as capacidades visuais humanas, de forma a tornar perceptível a informação abstracta, fornecendo os meios necessários para que um humano possa absorver quantidades crescentes de informação, com as suas capacidades de percepção. O objectivo das técnicas de agrupamento de dados consiste na divisão de um conjunto de dados em vários grupos, em que dados semelhantes são colocados no mesmo grupo e dados dissemelhantes em grupos diferentes. Mais especificamente, o agrupamento de dados com restrições tem o intuito de incorporar conhecimento a priori no processo de agrupamento de dados, com o objectivo de aumentar a qualidade do agrupamento de dados e, simultaneamente, encontrar soluções apropriadas a tarefas e interesses específicos. Nesta dissertação é estudado a abordagem de Agrupamento de Dados Visual Interactivo que permite ao utilizador, através da interacção com uma representação visual da informação, incorporar o seu conhecimento prévio acerca do domínio de dados, de forma a influenciar o agrupamento resultante para satisfazer os seus objectivos. Esta abordagem combina e estende técnicas de visualização interactiva de informação, desenho de grafos de forças direccionadas e agrupamento de dados com restrições. Com o propósito de avaliar o desempenho de diferentes estratégias de interacção com o utilizador, são efectuados estudos comparativos utilizando conjuntos de dados sintéticos e reais.

Conditional probability applied to the definition of limestone geochemical facies: A new Methodological Approach

A new method, based on linear correlation and phase diagrams was successfully developed for processes like the sedimentary process, where the deposition phase can have different time duration - represented by repeated values in a series - and where the erosion can play an important rule deleting values of a series. The sampling process itself can be the cause of repeated values - large strata twice sampled - or deleted values: tiny strata fitted between two consecutive samples. What we developed was a mathematical procedure which, based upon the depth chemical composition evolution, allows the establishment of frontiers as well as the periodicity of different sedimentary environments. The basic tool isn't more than a linear correlation analysis which allow us to detect the existence of eventual evolution rules, connected with cyclical phenomena within time series (considering the space assimilated to time), with the final objective of prevision. A very interesting discovery was the phenomenon of repeated sliding windows that represent quasi-cycles of a series of quasi-periods. An accurate forecast can be obtained if we are inside a quasi-cycle (it is possible to predict the other elements of the cycle with the probability related with the number of repeated and deleted points). We deal with an innovator methodology, reason why it's efficiency is being tested in some case studies, with remarkable results that shows it's efficacy. Keywords: sedimentary environments, sequence stratigraphy, data analysis, time-series, conditional probability.

An integer programming framework for sequencing cutting patterns based on interval graph completion

We derived a framework in integer programming, based on the properties of a linear ordering of the vertices in interval graphs, that acts as an edge completion model for obtaining interval graphs. This model can be applied to problems of sequencing cutting patterns, namely the minimization of open stacks problem (MOSP). By making small modifications in the objective function and using only some of the inequalities, the MOSP model is applied to another pattern sequencing problem that aims to minimize, not only the number of stacks, but also the order spread (the minimization of the stack occupation problem), and the model is tested.

An integer programming model for the minimum interval graph completion problem

The minimum interval graph completion problem consists of, given a graph G = ( V, E ), finding a supergraph H = ( V, E ∪ F ) that is an interval graph, while adding the least number of edges |F| . We present an integer programming formulation for solving the minimum interval graph completion problem recurring to a characteri- zation of interval graphs that produces a linear ordering of the maximal cliques of the solution graph.

A Multi-DAG Model for Real-Time Parallel Applications with Conditional Execution

The 30th ACM/SIGAPP Symposium On Applied Computing (SAC 2015). 13 to 17, Apr, 2015, Embedded Systems. Salamanca, Spain.

A Fractional Perspective to the Bond Graph Modelling of World Economies

Inspired in dynamic systems theory and Brewer’s contributions to apply it to economics, this paper establishes a bond graph model. Two main variables, a set of inter-connectivities based on nodes and links (bonds) and a fractional order dynamical perspective, prove to be a good macro-economic representation of countries’ potential performance in nowadays globalization. The estimations based on time series for 50 countries throughout the last 50 decades confirm the accuracy of the model and the importance of scale for economic performance.