47 resultados para Context data

em CentAUR: Central Archive University of Reading - UK


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Several global quantities are computed from the ERA40 reanalysis for the period 1958-2001 and explored for trends. These are discussed in the context of changes to the global observing system. Temperature, integrated water vapor (IWV), and kinetic energy are considered. The ERA40 global mean temperature in the lower troposphere has a trend of +0.11 K per decade over the period of 1979-2001, which is slightly higher than the MSU measurements, but within the estimated error limit. For the period 1958 2001 the warming trend is 0.14 K per decade but this is likely to be an artifact of changes in the observing system. When this is corrected for, the warming trend is reduced to 0.10 K per decade. The global trend in IWV for the period 1979-2001 is +0.36 mm per decade. This is about twice as high as the trend determined from the Clausius-Clapeyron relation assuming conservation of relative humidity. It is also larger than results from free climate model integrations driven by the same observed sea surface temperature as used in ERA40. It is suggested that the large trend in IWV does not represent a genuine climate trend but an artifact caused by changes in the global observing system such as the use of SSM/I and more satellite soundings in later years. Recent results are in good agreement with GPS measurements. The IWV trend for the period 1958-2001 is still higher but reduced to +0.16 mm per decade when corrected for changes in the observing systems. Total kinetic energy shows an increasing global trend. Results from data assimilation experiments strongly suggest that this trend is also incorrect and mainly caused by the huge changes in the global observing system in 1979. When this is corrected for, no significant change in global kinetic energy from 1958 onward can be found.

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Two wavelet-based control variable transform schemes are described and are used to model some important features of forecast error statistics for use in variational data assimilation. The first is a conventional wavelet scheme and the other is an approximation of it. Their ability to capture the position and scale-dependent aspects of covariance structures is tested in a two-dimensional latitude-height context. This is done by comparing the covariance structures implied by the wavelet schemes with those found from the explicit forecast error covariance matrix, and with a non-wavelet- based covariance scheme used currently in an operational assimilation scheme. Qualitatively, the wavelet-based schemes show potential at modeling forecast error statistics well without giving preference to either position or scale-dependent aspects. The degree of spectral representation can be controlled by changing the number of spectral bands in the schemes, and the least number of bands that achieves adequate results is found for the model domain used. Evidence is found of a trade-off between the localization of features in positional and spectral spaces when the number of bands is changed. By examining implied covariance diagnostics, the wavelet-based schemes are found, on the whole, to give results that are closer to diagnostics found from the explicit matrix than from the nonwavelet scheme. Even though the nature of the covariances has the right qualities in spectral space, variances are found to be too low at some wavenumbers and vertical correlation length scales are found to be too long at most scales. The wavelet schemes are found to be good at resolving variations in position and scale-dependent horizontal length scales, although the length scales reproduced are usually too short. The second of the wavelet-based schemes is often found to be better than the first in some important respects, but, unlike the first, it has no exact inverse transform.

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Recent sedimentological and palynological research on subfossil Holocene banded sediments from the Severn Estuary Levels suggested seasonality of deposition, registered by variations in mineral grain-size and pollen assemblages between different parts of the bands. Here we provide data that strengthen this interpretation from sampling of modern sediments and pollen deposition on an active mudflat and saltmarsh on the margin of the Severn Estuary, and comparison with a vegetation survey and contemporary records of climate, river and tidal regimes. The results of grain-size analysis indicate deposition of comparatively coarse-grained silts during the relatively cool and windy conditions of winter and comparatively fine-grained sediments during relatively warm and calm summer months. Pollen analysis demonstrates the significance of long-term storage of pollen grains and fern spores in the estuarine waterbody, superimposed on which seasonal variations in pollen inputs from local and regional vegetation remain detectable. Copyright (C) 2007 John Wiley & Sons, Ltd.

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Against a background of rising adult mortality and morbidity in the context of the HIV/AIDS pandemic in sub-Saharan Africa, this paper provides both quantitative and qualitative evidence for the existence of a largely neglected group of young people with increased responsibility for caregiving. Using questionnaire surveys, focus groups, storyboards and in-depth interviews in three studies across Southern and Eastern Africa some young people in Lesotho, Tanzania and Zimbabwe are found to devote considerable time and energy to caring for sick members of their households. Examination of the tasks carried out by these youngsters finds them to be burdened beyond usual familial and societal expectations of children's 'normal' contributions to the reproduction of households via domestic chores and suchlike. It is concluded that these young people can be described as 'young carers'. The three studies are presented to illuminate different sociospatial aspects of caregiving by young people. First, using qualitative data from Lesotho the range of caring tasks young caregivers; perform for care recipients - usually a grandmother, parent, or sibling - is identified. Second, the impact caregiving responsibilities have on children's primary school attendance is examined using survey data from Tanzania. Third, the wider negative and positive impacts of caregiving including loss of friends and gaining of emotional maturity for young carers and their households is explored with in-depth individual interviews from Zimbabwe. Finally, suggestions are made for further research to deepen understanding of the geographies of caring within the context of the population geographies of the HIV/AIDS pandemic in sub-Saharan Africa and beyond. Copyright (c) 2006 John Wiley & Sons, Ltd.

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The need to map vegetation communities over large areas for nature conservation and to predict the impact of environmental change on vegetation distributions, has stimulated the development of techniques for predictive vegetation mapping. Predictive vegetation studies start with the development of a model relating vegetation units and mapped physical data, followed by the application of that model to a geographic database and over a wide range of spatial scales. This field is particularly important for identifying sites for rare and endangered species and locations of high biodiversity such as many areas of the Mediterranean Basin. The potential of the approach is illustrated with a mapping exercise in the alti-meditterranean zone of Lefka Ori in Crete. The study established the nature of the relationship between vegetation communities and physical data including altitude, slope and geomorphology. In this way the knowledge of community distribution was improved enabling a GIS-based model capable of predicting community distribution to be constructed. The paper describes the development of the spatial model and the methodological problems of predictive mapping for monitoring Mediterranean ecosystems. The paper concludes with a discussion of the role of predictive vegetation mapping and other spatial techniques, such as fuzzy mapping and geostatistics, for improving our understanding of the dynamics of Mediterranean ecosystems and for practical management in a region that is under increasing pressure from human impact.

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Facilitating the visual exploration of scientific data has received increasing attention in the past decade or so. Especially in life science related application areas the amount of available data has grown at a breath taking pace. In this paper we describe an approach that allows for visual inspection of large collections of molecular compounds. In contrast to classical visualizations of such spaces we incorporate a specific focus of analysis, for example the outcome of a biological experiment such as high throughout screening results. The presented method uses this experimental data to select molecular fragments of the underlying molecules that have interesting properties and uses the resulting space to generate a two dimensional map based on a singular value decomposition algorithm and a self organizing map. Experiments on real datasets show that the resulting visual landscape groups molecules of similar chemical properties in densely connected regions.

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The creation of OFDM based Wireless Personal Area Networks (WPANs) has allowed the development of high bit-rate wireless communication devices suitable for streaming High Definition video between consumer products, as demonstrated in Wireless-USB and Wireless-HDMI. However, these devices need high frequency clock rates, particularly for the OFDM, FFT and symbol processing sections resulting in high silicon cost and high electrical power. The high clock rates make hardware prototyping difficult and verification is therefore very important but costly. Acknowledging that electrical power in wireless consumer devices is more critical than the number of implemented logic gates, this paper presents a Double Data Rate (DDR) architecture for implementation inside a OFDM baseband codec in order to reduce the high frequency clock rates by a complete factor of 2. The presented architecture has been implemented and tested for ECMA-368 (Wireless- USB context) resulting in a maximum clock rate of 264MHz instead of the expected 528MHz clock rate existing anywhere on the baseband codec die.

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Despite the wide use of Landscape Character Assessment (LCA) as a tool for landscape planning in NW Europe, there are few examples of its application in the Mediterranean. This paper reports on the results from the development of a typology for LCA in a study area of northern Sardinia, Italy to provide a spatial framework for the analysis of current patterns of cork oak distribution and future restoration of this habitat. Landscape units were derived from a visual interpretation of map data stored within a GIS describing the physical and cultural characteristics of the study area. The units were subsequently grouped into Landscape Types according to the similarity of shared attributes using Two Way Indicator Species Analysis (TWINSPAN). The preliminary results showed that the methodology classified distinct Landscape Types but, based on field observations, there is a need for further refinement of the classification. The distribution and properties of two main cork oak habitats types was examined within the identified Landscape Types namely woodlands and wood pastures using Patch Analyst. The results show very clearly a correspondence between the distribution of cork oak pastures and cork oak woodland and landscape types. This forms the basis of the development of strategies for the maintenance, restoration and recreation of these habitat types within the study area, ultimately for the whole island of Sardinia. Future work is required to improve the landscape characterisation , particularly with respect to cultural factors, and to determine the validity of the landscape spatial framework for the analysis of cork oak distribution as part of a programme of habitat restoration and re-creation.

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The influence matrix is used in ordinary least-squares applications for monitoring statistical multiple-regression analyses. Concepts related to the influence matrix provide diagnostics on the influence of individual data on the analysis - the analysis change that would occur by leaving one observation out, and the effective information content (degrees of freedom for signal) in any sub-set of the analysed data. In this paper, the corresponding concepts have been derived in the context of linear statistical data assimilation in numerical weather prediction. An approximate method to compute the diagonal elements of the influence matrix (the self-sensitivities) has been developed for a large-dimension variational data assimilation system (the four-dimensional variational system of the European Centre for Medium-Range Weather Forecasts). Results show that, in the boreal spring 2003 operational system, 15% of the global influence is due to the assimilated observations in any one analysis, and the complementary 85% is the influence of the prior (background) information, a short-range forecast containing information from earlier assimilated observations. About 25% of the observational information is currently provided by surface-based observing systems, and 75% by satellite systems. Low-influence data points usually occur in data-rich areas, while high-influence data points are in data-sparse areas or in dynamically active regions. Background-error correlations also play an important role: high correlation diminishes the observation influence and amplifies the importance of the surrounding real and pseudo observations (prior information in observation space). Incorrect specifications of background and observation-error covariance matrices can be identified, interpreted and better understood by the use of influence-matrix diagnostics for the variety of observation types and observed variables used in the data assimilation system. Copyright © 2004 Royal Meteorological Society

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This paper presents a simple Bayesian approach to sample size determination in clinical trials. It is required that the trial should be large enough to ensure that the data collected will provide convincing evidence either that an experimental treatment is better than a control or that it fails to improve upon control by some clinically relevant difference. The method resembles standard frequentist formulations of the problem, and indeed in certain circumstances involving 'non-informative' prior information it leads to identical answers. In particular, unlike many Bayesian approaches to sample size determination, use is made of an alternative hypothesis that an experimental treatment is better than a control treatment by some specified magnitude. The approach is introduced in the context of testing whether a single stream of binary observations are consistent with a given success rate p(0). Next the case of comparing two independent streams of normally distributed responses is considered, first under the assumption that their common variance is known and then for unknown variance. Finally, the more general situation in which a large sample is to be collected and analysed according to the asymptotic properties of the score statistic is explored. Copyright (C) 2007 John Wiley & Sons, Ltd.

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Project managers in the construction industry increasingly seek to learn from other industrial sectors. Knowledge sharing between different contexts is thus viewed as an essential source of competitive advantage. It is important therefore for project managers from all sectors to address and develop appropriate methods of knowledge sharing. However, too often it is assumed that knowledge freely exists and can be captured and shared between contexts. Such assumptions belie complexities and problems awaiting the unsuspecting knowledge-sharing protagonist. Knowledge per se is a problematic esoteric concept that does not lend itself easily to codification. Specifically tacit knowledge possessed by individuals, presents particular methodological issues for those considering harnessing its utility in return for competitive advantage. The notion that knowledge is also embedded in specific social contexts compounds this complexity. It is argued that knowledge is highly individualistic and concomitant with the various surrounding contexts within which it is shaped and enacted. Indeed, these contexts are also shaped as a consequence of knowledge adding further complexity to the problem domain. Current methods of knowledge capture, transfer and, sharing fall short of addressing these problematic issues. Research is presented that addresses these problems and proposes an alternative method of knowledge sharing. Drawing on data and observations collected from its application, the findings clearly demonstrate the crucial role of re-contextualisation, social interaction and dialectic debate in understanding knowledge sharing.

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The UK Construction Industry has been criticized for being slow to change and adopt innovations. The idiosyncrasies of participants, their roles in a social system and the contextual differences between sections of the UK Construction Industry are viewed as being paramount to explaining innovation diffusion within this context. Three innovation diffusion theories from outside construction management literature are introduced, Cohesion, Structural Equivalence and Thresholds. The relevance of each theory, in relation to the UK Construction Industry, is critically reviewed using literature and empirical data. Analysis of the data results in an explanatory framework being proposed. The framework introduces a Personal Awareness Threshold concept, highlights the dominant role of Cohesion through the main stages of diffusion, together with the use of Structural Equivalence during the later stages of diffusion and the importance of Adoption Threshold levels.

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Managing a construction project supply chain effectively and efficiently is extremely difficult due to involvement of numerous sectors that are supported by ineffective communication system. An efficient construction supply chain system ensures the delivery of materials and other services to construction site while minimising costs and rewarding all sectors based on value added to the supply chain. The advancement of information, communication and wireless technologies is driving construction companies to deploy supply chain management strategies to seek better outputs. As part of the emerging wireless technologies, contextaware computing capability represents the next generation of ICT to the construction services. Conceptually, context-awareness could be integrated with Web Services in order to ensure the delivery of pertinent information to construction site and enhance construction supply chain collaboration. An initial study has indicated that this integrated system has the potential of serving and improving the construction services delivery through access to context-specific data, information and services on as-needed basis.

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The construction industry has incurred a considerable amount of waste as a result of poor logistics supply chain network management. Therefore, managing logistics in the construction industry is critical. An effective logistic system ensures delivery of the right products and services to the right players at the right time while minimising costs and rewarding all sectors based on value added to the supply chain. This paper reports on an on-going research study on the concept of context-aware services delivery in the construction project supply chain logistics. As part of the emerging wireless technologies, an Intelligent Wireless Web (IWW) using context-aware computing capability represents the next generation ICT application to construction-logistics management. This intelligent system has the potential of serving and improving the construction logistics through access to context-specific data, information and services. Existing mobile communication deployments in the construction industry rely on static modes of information delivery and do not take into account the worker’s changing context and dynamic project conditions. The major problems in these applications are lack of context-specificity in the distribution of information, services and other project resources, and lack of cohesion with the existing desktop based ICT infrastructure. The research works focus on identifying the context dimension such as user context, environmental context and project context, selection of technologies to capture context-parameters such wireless sensors and RFID, selection of supporting technologies such as wireless communication, Semantic Web, Web Services, agents, etc. The process of integration of Context-Aware Computing and Web-Services to facilitate the creation of intelligent collaboration environment for managing construction logistics will take into account all the necessary critical parameters such as storage, transportation, distribution, assembly, etc. within off and on-site project.