193 resultados para Renewable resource


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Worldwide, science education reform is aiming to promote 'scientific literacy' among young people. Typically, this is taken to include empowering them to engage critically with science in news media. This study explored the extent and nature of secondary science teachers' use of newspapers. It found that, though a great many use the resource, the majority do so incidentally and with the intention of showing the relevance of the subject rather than developing their students' criticality.

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Paper describes an effcicient approach for provisioning of network resources based on SLAs and a range of negotiating agents. The work arose from direct collboration with Fujitsu research and invlolved a worldwide press reslease of their agent brokering system which was based on this; also, a plenary address: A.Marshall (QUB) & A.Campbell (Columbia, USA) at 4th IFIP/IEEE International conference on Management of Multimedia Networks and Services' 2001 (MMNS'01). ISSN: 0926-6801

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A key obstacle to the wide-scale development of renewable energy is that public acceptability of wind energy cannot be taken for granted when wind energy moves from abstract support to local implementation. Drawing on a case study of opposition to the siting of a proposed off-shore wind farm in Northern Ireland, we offer a rhetorical analysis of a series of representative documents drawn from government, media, pro- and anti-wind energy sources, which identifies and interprets a number of discourses of objection and support. The analysis indicates that the key issue in terms of the transition to a renewable energy economy has little to do with the technology itself. Understanding the different nuances of pro- and anti-wind energy discourses highlights the importance of thinking about new ways of looking at these conflicts. These include adopting a “conflict resolution” approach and “upstreaming” public involvement in the decision-making process and also the counter-productive strategy of assuming that objection is based on ignorance (which can be solved by information) or NIMBY thinking (which can be solved by moral arguments about overcoming “free riders”).

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Computionally efficient sequential learning algorithms are developed for direct-link resource-allocating networks (DRANs). These are achieved by decomposing existing recursive training algorithms on a layer by layer and neuron by neuron basis. This allows network weights to be updated in an efficient parallel manner and facilitates the implementation of minimal update extensions that yield a significant reduction in computation load per iteration compared to existing sequential learning methods employed in resource-allocation network (RAN) and minimal RAN (MRAN) approaches. The new algorithms, which also incorporate a pruning strategy to control network growth, are evaluated on three different system identification benchmark problems and shown to outperform existing methods both in terms of training error convergence and computational efficiency. (c) 2005 Elsevier B.V. All rights reserved.