Composing with Graphics: Revealing the Compositional Process through Performance.

The research presented here is product of a practice-based process that primarily generates knowledge through collaboration and exchange in performance situations. This collaboration and exchange with various musicians over a period of five years that constitutes a body of practice that is here reflected upon. The paper focuses on non-instructional graphic scores and presents some insights based on performances of works by the author. We address how composition processes are revealed in graphic scores by looking at the conditions of decision making at the point of preparing a performance. We argue that three key elements are at play in the interpretation of these types of graphic scores: performance practice, mapping and musical form. By reflecting particularly on the work Cipher Series (Rebelo, 2010) we offer insights into the strategies for approaching the performance of graphic scores that go beyond symbolic codification.

Formação profissional em contexto empresarial

Relatório de estágio de mestrado, Ciências da Educação (Formação de Adultos), Universidade de Lisboa, Instituto de Educação, 2013

The LH5 model for data mining

In the age of E-Business many companies faced with massive data sets that must be analysed for gaining a competitive edge. these data sets are in many instances incomplete and quite often not of very high quality. Although statistical analysis can be used to pre-process these data sets, this technique has its own limitations. In this paper we are presenting a system - and its underlying model - that can be used to test the integrity of existing data and pre-process the data into clearer data sets to be mined. LH5 is a rule-based system, capable of self-learning and is illustrated using a medical data set.