Abstract
Label Ranking (LR) problems, such as predicting rankings of financial analysts, are becoming increasingly important in data mining. While there has been a significant amount of work on the development of learning algorithms for LR in recent years, pre-processing methods for LR are still very scarce. However, some methods, like Naive Bayes for LR and APRIORI-LR, cannot deal with real-valued data directly. As a make-shift solution, one could consider conventional discretization methods used in classification, by simply treating each unique ranking as a separate class. In this paper, we show that such an approach has several disadvantages. As an alternative, we propose an adaptation of an existing method, MDLP, specifically for LR problems. We illustrate the advantages of the new method using synthetic data. Additionally, we present results obtained on several benchmark datasets. The results clearly indicate that the discretization is performing as expected and in some cases improves the results of the learning algorithms.

Abstract

Abstract
Este artigo descreve a avaliação de um ambiente ubíquo utilizando a APEX, uma plataforma de prototipagem rápida de ambientes ubíquos que permite que os utilizadores naveguem num mundo virtual, podendo experimentar muitas das funcionalidades da solução e do design proposto.

Abstract

Abstract
Large scale integration of micro-generation, together with active loads and energy storage devices, under micro-grid and multi micro-grid concepts, requires the adoption of advanced control strategies at different distribution network levels. This paper presents advanced control functionality to be housed at high voltage (HV)/medium voltage (MV) substations and to be used to manage micro-generation, active loads and energy storage, subject to different constraints. Some of these constraints involve inter-temporal relations, such as the ones related with energy storage levels in consecutive time moments. This functionality is specially oriented to deal with stressed MV network operation involving overload and excessive voltage drops situations.

Abstract
An analytical model based on geometrical optics and multilayer transfer matrix method is applied to the surface plasmonic resonance supported by fibre taper structures in the context of optical sensing applications. Phase interrogation is considered in particular as a methodology to attain enhanced sensitivities, and the performance of the sensing heads as function of the metal clad and taper parameters is analyzed. General topics concerning the actual relevance of plasmonics are also presented, first in a global perspective and then when applied to sensing.