from Webern to dance to Burton.

Commissioned by the Concorde Ensemble. Paul Roe gave the premiere performance at the RHA Gallery, Dublin, 23rd February 2014. The piece is informed by the choreography of Jiri Kylian, in particular two three minute sections of his work No More Play initially choreographed to a score by Webern (his Five Movements for String Quartet) hence the title.

NY10128

This work for chamber orchestra explores the relationship between music and architecture, specifically that of the Guggenheim Museum, NYC. It was commissioned by the Edinburgh Contemporary Music Ensemble who gave the first performance in June 2008. Subsequent performances in 2011 by the National Youth Orchestra of Scotland have been accompanied by a film I created exploring the surfaces and profiles of the Guggenheim NYC.

Miniatures for Horn Trio.

This three movement work was first performed by members of the Research Ensemble at the Peninsula Arts Contemporary Music Festival, 26 February 2010. Material from the first movement reappears in the second and third in various guises. The second movement is dedicated to the choreographer, Merce Cunningham, and the constant piano part with pedal sustained throughout is a reference to the fluidity of dance. As a contrast to this there are passages of imitation between the horn and violin, some more audible than others, which are included as an acknowledgement of the intimate relationship which exists between co-dancers on stage. The third movement is dedicated to John Cage (Cunningham's partner) and, while the piano sustains chords (reworking content from the first movement), the gestures in the other parts loosely follow the outline of sections of one of Cage's watercolours, River Rocks and Smoke no.6. Much of my music is inspired by visual art and, having admired Cage's music and writings since by student days, it seemed appropriate after dedicating the second movement to Cunningham, to turn to Cage's art work in the final part of the composition.

Poly-transformation

King, R. D. and Ouali, M. (2004) Poly-transformation. In proceedings of 5th International Conference on Intelligent Data Engineering and Automated Learning (IDEAL 2004). Springer LNCS 3177 p99-107

A experiência de vida e as expectativas futuras de famílias beneficiárias de RSI

Dissertação de Mestrado apresentada à Universidade Fernando Pessoa como parte dos requisitos para obtenção do grau de Mestre em Psicologia, especialização em Psicologia Clínica e da Saúde.

Campanhas publicitárias de prevenção rodoviária em Portugal

Dissertação de Mestrado apresentada à Universidade Fernando Pessoa como parte dos requisitos para obtenção do grau de Mestre em Ciências da Comunicação, com especialização em Marketing e Comunicação Estratégica.

Competências estratégicas de negociação em gestão comercial

Dissertação de Mestrado apresentada à Universidade Fernando Pessoa como parte dos requisitos para obtenção do grau de Mestre em Ciências Empresariais

Revoluções no fotojornalismo

Tese apresentada à Universidade Fernando Pessoa como parte dos requisitos para obtenção do grau de Doutor em Ciências da Informação, especialidade em Jornalismo

A construção ideográfica nas relações internacionais portuguesas 1945-1960

Tese apresentada à Universidade Fernando Pessoa como parte dos requisitos para obtenção do grau de Doutor em Ciências Sociais, especialidade em Relações Internacionais

Fasciathérapie et identité professionnelle

Tese apresentada à Universidade Fernando Pessoa como parte dos requisitos para obtenção do grau de Doutor em Ciências Sociais, especialidade em Psicologia

Contributo para o desenvolvimento de um Instrumento de Investigação Neuropsicológica

Tese apresentada à Universidade Fernando Pessoa como parte dos requisitos para obtenção do grau de Doutor em Ciências Sociais, especialidade em Psicologia

Dissipative Chaos in Semiconductor Superlattices

We consider the motion of ballistic electrons in a miniband of a semiconductor superlattice (SSL) under the influence of an external, time-periodic electric field. We use the semi-classical balance-equation approach which incorporates elastic and inelastic scattering (as dissipation) and the self-consistent field generated by the electron motion. The coupling of electrons in the miniband to the self-consistent field produces a cooperative nonlinear oscillatory mode which, when interacting with the oscillatory external field and the intrinsic Bloch-type oscillatory mode, can lead to complicated dynamics, including dissipative chaos. For a range of values of the dissipation parameters we determine the regions in the amplitude-frequency plane of the external field in which chaos can occur. Our results suggest that for terahertz external fields of the amplitudes achieved by present-day free electron lasers, chaos may be observable in SSLs. We clarify the nature of this novel nonlinear dynamics in the superlattice-external field system by exploring analogies to the Dicke model of an ensemble of two-level atoms coupled with a resonant cavity field and to Josephson junctions.

Smooth Multirate Multicast Congestion Control

A significant impediment to deployment of multicast services is the daunting technical complexity of developing, testing and validating congestion control protocols fit for wide-area deployment. Protocols such as pgmcc and TFMCC have recently made considerable progress on the single rate case, i.e. where one dynamic reception rate is maintained for all receivers in the session. However, these protocols have limited applicability, since scaling to session sizes beyond tens of participants necessitates the use of multiple rate protocols. Unfortunately, while existing multiple rate protocols exhibit better scalability, they are both less mature than single rate protocols and suffer from high complexity. We propose a new approach to multiple rate congestion control that leverages proven single rate congestion control methods by orchestrating an ensemble of independently controlled single rate sessions. We describe SMCC, a new multiple rate equation-based congestion control algorithm for layered multicast sessions that employs TFMCC as the primary underlying control mechanism for each layer. SMCC combines the benefits of TFMCC (smooth rate control, equation-based TCP friendliness) with the scalability and flexibility of multiple rates to provide a sound multiple rate multicast congestion control policy.

Uncertainty in wind energy forecasting

Wind energy is the energy source that contributes most to the renewable energy mix of European countries. While there are good wind resources throughout Europe, the intermittency of the wind represents a major problem for the deployment of wind energy into the electricity networks. To ensure grid security a Transmission System Operator needs today for each kilowatt of wind energy either an equal amount of spinning reserve or a forecasting system that can predict the amount of energy that will be produced from wind over a period of 1 to 48 hours. In the range from 5m/s to 15m/s a wind turbine’s production increases with a power of three. For this reason, a Transmission System Operator requires an accuracy for wind speed forecasts of 1m/s in this wind speed range. Forecasting wind energy with a numerical weather prediction model in this context builds the background of this work. The author’s goal was to present a pragmatic solution to this specific problem in the ”real world”. This work therefore has to be seen in a technical context and hence does not provide nor intends to provide a general overview of the benefits and drawbacks of wind energy as a renewable energy source. In the first part of this work the accuracy requirements of the energy sector for wind speed predictions from numerical weather prediction models are described and analysed. A unique set of numerical experiments has been carried out in collaboration with the Danish Meteorological Institute to investigate the forecast quality of an operational numerical weather prediction model for this purpose. The results of this investigation revealed that the accuracy requirements for wind speed and wind power forecasts from today’s numerical weather prediction models can only be met at certain times. This means that the uncertainty of the forecast quality becomes a parameter that is as important as the wind speed and wind power itself. To quantify the uncertainty of a forecast valid for tomorrow requires an ensemble of forecasts. In the second part of this work such an ensemble of forecasts was designed and verified for its ability to quantify the forecast error. This was accomplished by correlating the measured error and the forecasted uncertainty on area integrated wind speed and wind power in Denmark and Ireland. A correlation of 93% was achieved in these areas. This method cannot solve the accuracy requirements of the energy sector. By knowing the uncertainty of the forecasts, the focus can however be put on the accuracy requirements at times when it is possible to accurately predict the weather. Thus, this result presents a major step forward in making wind energy a compatible energy source in the future.

Current methods and advances in forecasting of wind power generation

Wind power generation differs from conventional thermal generation due to the stochastic nature of wind. Thus wind power forecasting plays a key role in dealing with the challenges of balancing supply and demand in any electricity system, given the uncertainty associated with the wind farm power output. Accurate wind power forecasting reduces the need for additional balancing energy and reserve power to integrate wind power. Wind power forecasting tools enable better dispatch, scheduling and unit commitment of thermal generators, hydro plant and energy storage plant and more competitive market trading as wind power ramps up and down on the grid. This paper presents an in-depth review of the current methods and advances in wind power forecasting and prediction. Firstly, numerical wind prediction methods from global to local scales, ensemble forecasting, upscaling and downscaling processes are discussed. Next the statistical and machine learning approach methods are detailed. Then the techniques used for benchmarking and uncertainty analysis of forecasts are overviewed, and the performance of various approaches over different forecast time horizons is examined. Finally, current research activities, challenges and potential future developments are appraised.