911 resultados para GNSS, Ambiguity resolution, Regularization, Ill-posed problem, Success probability


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The UK population of the Spotted Flycatcher Muscicapa striata has declined markedly in the last 30 years but there have been few recent studies of the species. This study examined the relationship between nest success and the predominant habitat type around Spotted Flycatcher nests in two contrasting areas of England. A breeding population in eastern England, a region where numbers of Spotted Flycatchers are known to have decreased dramatically in recent decades, was compared with another in southwest England, where numbers have remained stable or even increased. Whilst there was no difference in breeding success between the two study areas, there were significant differences between habitats, with garden nests more successful than those in farmland or woodland, at both egg and chick stages. Estimates of productivity per nesting attempt were also lower in farmland and woodland, with nests in gardens fledging twice as many chicks as those in either woodland or farmland. The proximate cause of lower success in farmland and woodland was higher nest predation rates during both egg and chick stages. In terms of nesting success, farmland and woodland appear to be similar in quality for this species, but both appear to be suboptimal habitats when compared with gardens, providing evidence of a problem on the breeding grounds for this species, in at least these two habitats.

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The UK population of the Spotted Flycatcher Muscicapa striata has declined markedly in the last 30 years but there have been few recent studies of the species. This study examined the relationship between nest success and the predominant habitat type around Spotted Flycatcher nests in two contrasting areas of England. A breeding population in eastern England, a region where numbers of Spotted Flycatchers are known to have decreased dramatically in recent decades, was compared with another in southwest England, where numbers have remained stable or even increased. Whilst there was no difference in breeding success between the two study areas, there were significant differences between habitats, with garden nests more successful than those in farmland or woodland, at both egg and chick stages. Estimates of productivity per nesting attempt were also lower in farmland and woodland, with nests in gardens fledging twice as many chicks as those in either woodland or farmland. The proximate cause of lower success in farmland and woodland was higher nest predation rates during both egg and chick stages. In terms of nesting success, farmland and woodland appear to be similar in quality for this species, but both appear to be suboptimal habitats when compared with gardens, providing evidence of a problem on the breeding grounds for this species, in at least these two habitats.

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Williams syndrome (WS) is characterized by apparent relative strengths in language, facial processing and social cognition but by profound impairment in spatial cognition, planning and problem solving. Following recent research which suggests that individuals with WS may be less linguistically able than was once thought, in this paper we begin to investigate why and how they may give the impression of linguistic proficiency despite poor standardized test results. This case study of Brendan, a 12-year-old boy with WS, who presents with a considerable lack of linguistic ability, suggests that impressions of linguistic competence may to some extent be the result of conversational strategies which enable him to compensate for various cognitive and linguistic deficits with a considerable degree of success. These conversational strengths are not predicted by his standardized language test results, and provide compelling support for the use of approaches such as Conversation Analysis in the assessment of individuals with communication impairments.

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The well-studied link between psychotic traits and creativity is a subject of much debate. The present study investigated the extent to which schizotypic personality traits - as measured by O-LIFE (Oxford-Liverpool Inventory of Feelings and Experiences) - equip healthy individuals to engage as groups in everyday tasks. From a sample of 69 students, eight groups of four participants - comprised of high, medium, or low-schizotypy individuals - were assembled to work as a team to complete a creative problem-solving task. Predictably, high scorers on the O-LIFE formulated a greater number of strategies to solve the task, indicative of creative divergent thinking. However, for task success (as measured by time taken to complete the problem) an inverted U shaped pattern emerged, whereby high and low-schizotypy groups were consistently faster than medium schizotypy groups. Intriguing data emerged concerning leadership within the groups, and other tangential findings relating to anxiety, competition and motivation were explored. These findings challenge the traditional cliche that psychotic personality traits are linearly related to creative performance, and suggest that the nature of the problem determines which thinking styles are optimally equipped to solve it. (C) 2009 Elsevier Ltd. All rights reserved.

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By monitoring signals from the central nervous system, humans can be provided with a novel extra channel of communication that can, for example, be used for the voluntary control of peripheral devices. Meanwhile, stimulation of neural tissue can bring about sensation such as touch, can facilitate feedback from external, potentially remote devices and even opens up the possibility of new sensory input for the individual to experience. The concept of successfully harnessing and stimulating nervous system activity is though something that can only be achieved through an appropriate interface. However, interfacing the nervous system by means of implant technology carries with it many problems and dangers. Further, results achieved may not be as expected or as they at first appear. This paper describes a comparative study investigating different implant types and procedures. It is aimed at highlighting potential problem areas and is intended to provide a useful reference explaining important tolerances and limits.

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The climate belongs to the class of non-equilibrium forced and dissipative systems, for which most results of quasi-equilibrium statistical mechanics, including the fluctuation-dissipation theorem, do not apply. In this paper we show for the first time how the Ruelle linear response theory, developed for studying rigorously the impact of perturbations on general observables of non-equilibrium statistical mechanical systems, can be applied with great success to analyze the climatic response to general forcings. The crucial value of the Ruelle theory lies in the fact that it allows to compute the response of the system in terms of expectation values of explicit and computable functions of the phase space averaged over the invariant measure of the unperturbed state. We choose as test bed a classical version of the Lorenz 96 model, which, in spite of its simplicity, has a well-recognized prototypical value as it is a spatially extended one-dimensional model and presents the basic ingredients, such as dissipation, advection and the presence of an external forcing, of the actual atmosphere. We recapitulate the main aspects of the general response theory and propose some new general results. We then analyze the frequency dependence of the response of both local and global observables to perturbations having localized as well as global spatial patterns. We derive analytically several properties of the corresponding susceptibilities, such as asymptotic behavior, validity of Kramers-Kronig relations, and sum rules, whose main ingredient is the causality principle. We show that all the coefficients of the leading asymptotic expansions as well as the integral constraints can be written as linear function of parameters that describe the unperturbed properties of the system, such as its average energy. Some newly obtained empirical closure equations for such parameters allow to define such properties as an explicit function of the unperturbed forcing parameter alone for a general class of chaotic Lorenz 96 models. We then verify the theoretical predictions from the outputs of the simulations up to a high degree of precision. The theory is used to explain differences in the response of local and global observables, to define the intensive properties of the system, which do not depend on the spatial resolution of the Lorenz 96 model, and to generalize the concept of climate sensitivity to all time scales. We also show how to reconstruct the linear Green function, which maps perturbations of general time patterns into changes in the expectation value of the considered observable for finite as well as infinite time. Finally, we propose a simple yet general methodology to study general Climate Change problems on virtually any time scale by resorting to only well selected simulations, and by taking full advantage of ensemble methods. The specific case of globally averaged surface temperature response to a general pattern of change of the CO2 concentration is discussed. We believe that the proposed approach may constitute a mathematically rigorous and practically very effective way to approach the problem of climate sensitivity, climate prediction, and climate change from a radically new perspective.

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Overseas trained teachers (OTTs) have grown in numbers during the past decade, particularly in London and the South East of England. In this recruitment explosion many OTTs have experienced difficulties. In professional literature as well as press coverage OTTs often become part of a deficit discourse. A small-scale pilot investigation of OTT experience has begun to suggest why OTTs have been successful as well as the principal challenges they have faced. An important factor in their success was felt to be the quality of support in school from others on the staff. Major challenges included the complexity of the primary curriculum. The argument that globalisation leads to brain-drain may be exaggerated. Suggestions for further research are made, which might indicate the positive benefits OTTs can bring to a school.

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Numerical weather prediction (NWP) centres use numerical models of the atmospheric flow to forecast future weather states from an estimate of the current state. Variational data assimilation (VAR) is used commonly to determine an optimal state estimate that miminizes the errors between observations of the dynamical system and model predictions of the flow. The rate of convergence of the VAR scheme and the sensitivity of the solution to errors in the data are dependent on the condition number of the Hessian of the variational least-squares objective function. The traditional formulation of VAR is ill-conditioned and hence leads to slow convergence and an inaccurate solution. In practice, operational NWP centres precondition the system via a control variable transform to reduce the condition number of the Hessian. In this paper we investigate the conditioning of VAR for a single, periodic, spatially-distributed state variable. We present theoretical bounds on the condition number of the original and preconditioned Hessians and hence demonstrate the improvement produced by the preconditioning. We also investigate theoretically the effect of observation position and error variance on the preconditioned system and show that the problem becomes more ill-conditioned with increasingly dense and accurate observations. Finally, we confirm the theoretical results in an operational setting by giving experimental results from the Met Office variational system.

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The accurate prediction of the biochemical function of a protein is becoming increasingly important, given the unprecedented growth of both structural and sequence databanks. Consequently, computational methods are required to analyse such data in an automated manner to ensure genomes are annotated accurately. Protein structure prediction methods, for example, are capable of generating approximate structural models on a genome-wide scale. However, the detection of functionally important regions in such crude models, as well as structural genomics targets, remains an extremely important problem. The method described in the current study, MetSite, represents a fully automatic approach for the detection of metal-binding residue clusters applicable to protein models of moderate quality. The method involves using sequence profile information in combination with approximate structural data. Several neural network classifiers are shown to be able to distinguish metal sites from non-sites with a mean accuracy of 94.5%. The method was demonstrated to identify metal-binding sites correctly in LiveBench targets where no obvious metal-binding sequence motifs were detectable using InterPro. Accurate detection of metal sites was shown to be feasible for low-resolution predicted structures generated using mGenTHREADER where no side-chain information was available. High-scoring predictions were observed for a recently solved hypothetical protein from Haemophilus influenzae, indicating a putative metal-binding site.

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For linear multivariable time-invariant continuous or discrete-time singular systems it is customary to use a proportional feedback control in order to achieve a desired closed loop behaviour. Derivative feedback is rarely considered. This paper examines how derivative feedback in descriptor systems can be used to alter the structure of the system pencil under various controllability conditions. It is shown that derivative and proportional feedback controls can be constructed such that the closed loop system has a given form and is also regular and has index at most 1. This property ensures the solvability of the resulting system of dynamic-algebraic equations. The construction procedures used to establish the theory are based only on orthogonal matrix decompositions and can therefore be implemented in a numerically stable way. The problem of pole placement with derivative feedback alone and in combination with proportional state feedback is also investigated. A computational algorithm for improving the “conditioning” of the regularized closed loop system is derived.

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We study the regularization problem for linear, constant coefficient descriptor systems Ex' = Ax+Bu, y1 = Cx, y2 = Γx' by proportional and derivative mixed output feedback. Necessary and sufficient conditions are given, which guarantee that there exist output feedbacks such that the closed-loop system is regular, has index at most one and E+BGΓ has a desired rank, i.e., there is a desired number of differential and algebraic equations. To resolve the freedom in the choice of the feedback matrices we then discuss how to obtain the desired regularizing feedback of minimum norm and show that this approach leads to useful results in the sense of robustness only if the rank of E is decreased. Numerical procedures are derived to construct the desired feedback gains. These numerical procedures are based on orthogonal matrix transformations which can be implemented in a numerically stable way.

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The construction sector is often described as lagging behind other major industries. At first this appears fair when considering the concept of corporate social responsibility (CSR). It is argued that CSR is ill-defined, with firms struggling to make sense of and engage with it. Literature suggests that the short-termism view of construction firms renders the long-term, triple-bottom-line principle of CSR untenable. This seems to be borne out by literature indicating that construction firms typically adopt a compliance-based approach to CSR instead of discretionary CSR which is regarded as adding most value to firms and benefiting the broadest group of stakeholders. However, this research conducted in the UK using a regional construction firm offers a counter argument whereby discretionary CSR approaches are well embedded and enacted within the firms’ business operations even though they are not formally articulated as CSR strategies and thus remain 'hidden'. This raises questions in the current CSR debate. First, is ‘hidden’ CSR relevant to the long term success of construction firms? and to what extent do these firms need to reinvent themselves to formally take advantage of the CSR agenda?

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This paper examined the incidence of intrafirmcausalambiguity in the management's perception concerning the critical drivers of their firms’ performance. Building on insights from the resource-based view we developed and tested hypotheses that examine (1) linkage ambiguity as a discrepancy between perceived and measured resource–performance linkages, (2) characteristic ambiguity for resources and capabilities with a high degree of complexity and tacitness, and (3) the negative association between linkage ambiguity and performance. The observations based on the explicit perceptions of 356 surveyed managers were contrasted with the empirical findings of the resource/performance relationship derived by structural equation modelling from the same data sample. The findings validate the presence of linkage ambiguity particularly in the case of resources and capabilities with higher degree of characteristic ambiguity. The findings also provide empirical evidence in support of the advocacy for a negative relationship between intrafirmcausalambiguity and performance. The paper discusses the potential reasons for the disparities between empirical findings and management's perceptions of the key determinants of export success and makes recommendations for future research.

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Global climate and weather models tend to produce rainfall that is too light and too regular over the tropical ocean. This is likely because of convective parametrizations, but the problem is not well understood. Here, distributions of precipitation rates are analyzed for high-resolution UK Met Office Unified Model simulations of a 10 day case study over a large tropical domain (∼20°S–20°N and 42°E–180°E). Simulations with 12 km grid length and parametrized convection have too many occurrences of light rain and too few of heavier rain when interpolated onto a 1° grid and compared with Tropical Rainfall Measuring Mission (TRMM) data. In fact, this version of the model appears to have a preferred scale of rainfall around 0.4 mm h−1 (10 mm day−1), unlike observations of tropical rainfall. On the other hand, 4 km grid length simulations with explicit convection produce distributions much more similar to TRMM observations. The apparent preferred scale at lighter rain rates seems to be a feature of the convective parametrization rather than the coarse resolution, as demonstrated by results from 12 km simulations with explicit convection and 40 km simulations with parametrized convection. In fact, coarser resolution models with explicit convection tend to have even more heavy rain than observed. Implications for models using convective parametrizations, including interactions of heating and moistening profiles with larger scales, are discussed. One important implication is that the explicit convection 4 km model has temperature and moisture tendencies that favour transitions in the convective regime. Also, the 12 km parametrized convection model produces a more stable temperature profile at its extreme high-precipitation range, which may reduce the chance of very heavy rainfall. Further study is needed to determine whether unrealistic precipitation distributions are due to some fundamental limitation of convective parametrizations or whether parametrizations can be improved, in order to better simulate these distributions.

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Considerable efforts are currently invested into the setup of a Global Climate Observing System (GCOS) for monitoring climate change over the coming decades, which is of high relevance given concerns on increasing human influences. A promising potential contribution to the GCOS is a suite of spaceborne Global Navigation Satellite System (GNSS) occultation sensors for global long-term monitoring of atmospheric change in temperature and other variables with high vertical resolution and accuracy. Besides the great importance with respect to climate change, the provision of high quality data is essential for the improvement of numerical weather prediction and for reanalysis efforts. We review the significance of GNSS radio occultation sounding in the climate observations context. In order to investigate the climate change detection capability of GNSS occultation sensors, we are currently performing an end-to-end GNSS occultation observing system simulation experiment over the 25-year period 2001 to 2025. We report on this integrated analysis, which involves in a realistic manner all aspects from modeling the atmosphere via generating a significant set of stimulated measurements to an objective statistical analysis and assessment of 2001–2025 temporal trends.