8 resultados para art as knowledge
em CentAUR: Central Archive University of Reading - UK
Resumo:
A basic principle in data modelling is to incorporate available a priori information regarding the underlying data generating mechanism into the modelling process. We adopt this principle and consider grey-box radial basis function (RBF) modelling capable of incorporating prior knowledge. Specifically, we show how to explicitly incorporate the two types of prior knowledge: the underlying data generating mechanism exhibits known symmetric property and the underlying process obeys a set of given boundary value constraints. The class of orthogonal least squares regression algorithms can readily be applied to construct parsimonious grey-box RBF models with enhanced generalisation capability.
Resumo:
This major curated exhibition, publication and events builds on Rowlands’ curatorial research. Working in collaboration with co-curators Martin Clark, Artistic Director, Tate St Ives and Michael Bracewell, cultural historian, the exhibition sought to explore new narratives within British art. The innovative curatorial methodology developed from a fiction found in the infamous novel, The Dark Monarch by Sven Berlin, Gallery Press 1962. The research sought specific archival and collection work that allowed thematic strands to emerge that represented influences across generations. The exhibition features two-hundred artworks, from the Tate Collection, archives and other significant British public and private collections. It examines the development of early Modernism, in the UK, as well as the reappearance of esoteric and arcane references in a significant strand of contemporary art practice. Historical works from Samuel Palmer, Graham Sutherland, Henry Moore and Paul Nash are shown alongside contemporary artists including Derek Jarman, Cerith Wyn Evans, Eva Rothschild, Linder and John Russell. The exhibition includes a key work by Damien Hirst ¬ the first time he has been shown at Tate St Ives and a number of contemporary commissions. The Dark Monarch publication extended the discourse of the research critically examining the tension between progressive modernity and romantic knowledge, the book focuses on the way that artworks are encoded with various histories - geological, mythical and magical. Essays examine magic as a counterpoint to modernity’s transparency and rational progress, but also draw out the links modernity has with notions such as fetishism, mana, totem, and the taboo. Often viewed as counter to Modernism, this collection of essays suggest that these products of illusion and delusion in fact belong to modernity. Drawing together 15 different writers commissioned to explore magic as a counterpoint of liberal understanding of modernity, drawing out links that modernity has with notions of fetish, taboo and occult philosophy. Including essays by Marina Warner, Ilsa Colsell, Philip Hoare, Chris Stephens, Jennifer Higgie and Morrissey.
Resumo:
When two people discuss something they can see in front of them, what is the relationship between their eye movements? We recorded the gaze of pairs of subjects engaged in live, spontaneous dialogue. Cross-recurrence analysis revealed a coupling between the eye movements of the two conversants. In the first study, we found their eye movements were coupled across several seconds. In the second, we found that this coupling increased if they both heard the same background information prior to their conversation. These results provide a direct quantification of joint attention during unscripted conversation and show that it is influenced by knowledge in the common ground.
Resumo:
Earth system models are increasing in complexity and incorporating more processes than their predecessors, making them important tools for studying the global carbon cycle. However, their coupled behaviour has only recently been examined in any detail, and has yielded a very wide range of outcomes, with coupled climate-carbon cycle models that represent land-use change simulating total land carbon stores by 2100 that vary by as much as 600 Pg C given the same emissions scenario. This large uncertainty is associated with differences in how key processes are simulated in different models, and illustrates the necessity of determining which models are most realistic using rigorous model evaluation methodologies. Here we assess the state-of-the-art with respect to evaluation of Earth system models, with a particular emphasis on the simulation of the carbon cycle and associated biospheric processes. We examine some of the new advances and remaining uncertainties relating to (i) modern and palaeo data and (ii) metrics for evaluation, and discuss a range of strategies, such as the inclusion of pre-calibration, combined process- and system-level evaluation, and the use of emergent constraints, that can contribute towards the development of more robust evaluation schemes. An increasingly data-rich environment offers more opportunities for model evaluation, but it is also a challenge, as more knowledge about data uncertainties is required in order to determine robust evaluation methodologies that move the field of ESM evaluation from "beauty contest" toward the development of useful constraints on model behaviour.
Resumo:
Nature conservation may be considered a post-normal science in that the loss of biodiversity and increasing environmental degradation require urgent action but are characterised by uncertainty at every level. An ‘extended peer community’ with varying skills, perceptions and values are involved in decision-making and implementation of conservation, and the uncertainty involved limits the effectiveness of practice. In this paper we briefly review the key ecological, philosophical and methodological uncertainties associated with conservation, and then highlight the uncertainties and gaps present within the structure and interactions of the conservation community, and which exist mainly between researchers and practitioners, in the context of nature conservation in the UK. We end by concluding that an openly post-normal science framework for conservation, which acknowledges this uncertainty but strives to minimise it, would be a useful progression for nature conservation, and recommend ways in which knowledge transfer between researchers and practitioners can be improved to support robust decision making and conservation enactment.
Resumo:
Earth system models (ESMs) are increasing in complexity by incorporating more processes than their predecessors, making them potentially important tools for studying the evolution of climate and associated biogeochemical cycles. However, their coupled behaviour has only recently been examined in any detail, and has yielded a very wide range of outcomes. For example, coupled climate–carbon cycle models that represent land-use change simulate total land carbon stores at 2100 that vary by as much as 600 Pg C, given the same emissions scenario. This large uncertainty is associated with differences in how key processes are simulated in different models, and illustrates the necessity of determining which models are most realistic using rigorous methods of model evaluation. Here we assess the state-of-the-art in evaluation of ESMs, with a particular emphasis on the simulation of the carbon cycle and associated biospheric processes. We examine some of the new advances and remaining uncertainties relating to (i) modern and palaeodata and (ii) metrics for evaluation. We note that the practice of averaging results from many models is unreliable and no substitute for proper evaluation of individual models. We discuss a range of strategies, such as the inclusion of pre-calibration, combined process- and system-level evaluation, and the use of emergent constraints, that can contribute to the development of more robust evaluation schemes. An increasingly data-rich environment offers more opportunities for model evaluation, but also presents a challenge. Improved knowledge of data uncertainties is still necessary to move the field of ESM evaluation away from a "beauty contest" towards the development of useful constraints on model outcomes.
Resumo:
In this article, we review the state-of-the-art techniques in mining data streams for mobile and ubiquitous environments. We start the review with a concise background of data stream processing, presenting the building blocks for mining data streams. In a wide range of applications, data streams are required to be processed on small ubiquitous devices like smartphones and sensor devices. Mobile and ubiquitous data mining target these applications with tailored techniques and approaches addressing scarcity of resources and mobility issues. Two categories can be identified for mobile and ubiquitous mining of streaming data: single-node and distributed. This survey will cover both categories. Mining mobile and ubiquitous data require algorithms with the ability to monitor and adapt the working conditions to the available computational resources. We identify the key characteristics of these algorithms and present illustrative applications. Distributed data stream mining in the mobile environment is then discussed, presenting the Pocket Data Mining framework. Mobility of users stimulates the adoption of context-awareness in this area of research. Context-awareness and collaboration are discussed in the Collaborative Data Stream Mining, where agents share knowledge to learn adaptive accurate models.
Resumo:
This article demonstrates how early Pre-Raphaelite poetry worked according to the principle that art should be modelled on science theorised by the Pre-Raphaelites in their early essays. As the main theorists (rather than practitioners) of Pre-Raphaelite art, F. G. Stephens and William Michael Rossetti defined the Pre-Raphaelite project in terms of observation, investigation, experiment, the “adherence to fact” and the “search after truth”. In the hands of the early Pre-Raphaelite poets, and particularly Rossetti himself, poetry too becomes a mode of scientific enquiry into the natural world, the nature of observation, human psychology and medical practice.