The wedding of Prince Charles and Camilla Parker-Bowles: royal mediation and press mediatization

Bearing in mind the relationship between discourse and society at large, this article addresses the way the British monarchy represented Charles’s second marriage and the way the media constructed their accounts in the period from 10 February (announcement) until 9 April 2005 (wedding) in relation to wider issues such as power relations, newspaper economic structures and popular culture. Particular attention is paid to the multifunctional features of discourse (i.e. its ideational, interpersonal and textual functions), which requires a contextualized reading of a dual process of mediation: on the one hand, the staging of the ceremony by St. James’s Palace and its strategy for attaining monologic closure and, on the other hand, discursive representations by the British press open to a polyphony of voices and discursive frames

The daily and hourly energy consumption and load forecasting using artifitial neural network method: a case study using a set of 93 households in Portugal

It is important to understand and forecast a typical or a particularly household daily consumption in order to design and size suitable renewable energy systems and energy storage. In this research for Short Term Load Forecasting (STLF) it has been used Artificial Neural Networks (ANN) and, despite the consumption unpredictability, it has been shown the possibility to forecast the electricity consumption of a household with certainty. The ANNs are recognized to be a potential methodology for modeling hourly and daily energy consumption and load forecasting. Input variables such as apartment area, numbers of occupants, electrical appliance consumption and Boolean inputs as hourly meter system were considered. Furthermore, the investigation carried out aims to define an ANN architecture and a training algorithm in order to achieve a robust model to be used in forecasting energy consumption in a typical household. It was observed that a feed-forward ANN and the Levenberg-Marquardt algorithm provided a good performance. For this research it was used a database with consumption records, logged in 93 real households, in Lisbon, Portugal, between February 2000 and July 2001, including both weekdays and weekend. The results show that the ANN approach provides a reliable model for forecasting household electric energy consumption and load profile. © 2014 The Author.