All you have do is shut up and enjoy the hospitality.'' Terry
Harold Pinter''s Party Time (1991) is an extraordinary distillation of the playwright''s key concerns. Pulsing with political anger, it marks a stepping stone on Pinter''s path from iconic dramatist of existential unease to Nobel Prize-winning poet of human rights.
G. D. White situates this underrated play within a recognisably ''Pinteresque'' landscape of ambiguous, brittle social drama while also recognising its particularity: Party Time is haunted by Augusto Pinochet''s right-wing coup against Salvador Allende''s democratically elected government in Chile. This book considers the play and its confederate works in the dual context of Pinter''s literary career and burgeoning international concern with human rights and freedom of expression.
White contrasts Pinter''s uneasy relationship with the UK''s powerful elite with the worldwide acclaim garnered by his dramatic eviscerations of power.
Accurate predictions of storm surge are of importance in many coastal areas in the world to avoid and mitigate its destructive impacts. For this purpose the physically-based (process) numerical models are typically utilized. However, in data-rich cases, one may use data-driven methods aiming at reconstructing the internal patterns of the modelled processes and relationships between the observed descriptive variables. This book focuses on data-driven modelling using methods of nonlinear dynamics and chaos theory. First, some fundamentals of physical oceanography, nonlinear dynamics and chaos, computational intelligence and European operational storm surge models are covered. After that a number of improvements in building chaotic models are presented: nonlinear time series analysis, multi-step prediction, phase space dimensionality reduction, techniques dealing with incomplete time series, phase error correction, finding true neighbours, optimization of chaotic model, data assimilation and multi-model ensemble prediction. The major case study is surge prediction in the North Sea, with some tests on a Caribbean Sea case. The modelling results showed that the enhanced predictive chaotic models can serve as an efficient tool for accurate and reliable short and mid-term predictions of storm surges in order to support decision-makers for flood prediction and ship navigation.
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