66 resultados para k-out-of-n system


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This article explores the impact of wider social contact on the experience of Chinese postgraduate students of adaptation to life in the UK. Focus group and individual interviews were conducted with a group of 11 Chinese students on an MA programme at a university in southern England and individual interviews with three representatives of a local volunteer group (LVG) offering support to the Chinese students. Although it was perceived that the students’ support needs were not adequately met by the University, the additional support offered outside the University was unanimously valued and considered as enriching their cultural and linguistic experiences and meeting their expectations. However, frequent social contact with the LVG, whose members were mostly Christians, also had an impact on their values, religious beliefs and identities. In a discussion framed within the sociological perspective of proselytization or religious conversion and the broad framework of international education and globalization, the different responses to this contact are described in terms of believers, doubters, empathisers and commentators. Implications are considered for universities, people involved in providing social support for international students, and sponsors of international students.

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In this paper a new system identification algorithm is introduced for Hammerstein systems based on observational input/output data. The nonlinear static function in the Hammerstein system is modelled using a non-uniform rational B-spline (NURB) neural network. The proposed system identification algorithm for this NURB network based Hammerstein system consists of two successive stages. First the shaping parameters in NURB network are estimated using a particle swarm optimization (PSO) procedure. Then the remaining parameters are estimated by the method of the singular value decomposition (SVD). Numerical examples including a model based controller are utilized to demonstrate the efficacy of the proposed approach. The controller consists of computing the inverse of the nonlinear static function approximated by NURB network, followed by a linear pole assignment controller.

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This paper examines the growing dysfunction between the apparently increasing significance of diverse leisure practices in the countryside and the largely unchanging official response towards them. Although there is recognition in the recent rural White Paper (DOE and MAFF, 1995) that access is essential to enjoying the countryside, the construction of this term is dubious, since paid access agreements, based on producer requirements, are favoured over any form of demand-driven freedom to roam. Using the Countryside Stewardship Scheme (CSS) as an example of the incentive structure developed to promote this policy, the paper applies Plato's simulacrum as a reading of how this process is being utilised to underpin the dominant rights associated with rural property interests. In particular, the paper makes the point that rather than representing the corollary of a market situation, as its supporters claim, the CSS involves government grant for the eclectic provision of short term licences over ground which remains unmapped as anything other than its continued agricultural use. In concluding, the paper asserts that rather than representing an increase in the availability of leisure sites in the countryside, the CSS and other schemes represent a diversion from the wider and deeper socio-cultural process of continued wealth and power redistribution.

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When performing data fusion, one often measures where targets were and then wishes to deduce where targets currently are. There has been recent research on the processing of such out-of-sequence data. This research has culminated in the development of a number of algorithms for solving the associated tracking problem. This paper reviews these different approaches in a common Bayesian framework and proposes an architecture that orthogonalises the data association and out-of-sequence problems such that any combination of solutions to these two problems can be used together. The emphasis is not on advocating one approach over another on the basis of computational expense, but rather on understanding the relationships among the algorithms so that any approximations made are explicit. Results for a multi-sensor scenario involving out-of-sequence data association are used to illustrate the utility of this approach in a specific context.

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In data fusion systems, one often encounters measurements of past target locations and then wishes to deduce where the targets are currently located. Recent research on the processing of such out-of-sequence data has culminated in the development of a number of algorithms for solving the associated tracking problem. This paper reviews these different approaches in a common Bayesian framework and proposes an architecture that orthogonalises the data association and out-of-sequence problems such that any combination of solutions to these two problems can be used together. The emphasis is not on advocating one approach over another on the basis of computational expense, but rather on understanding the relationships between the algorithms so that any approximations made are explicit.

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Data assimilation refers to the problem of finding trajectories of a prescribed dynamical model in such a way that the output of the model (usually some function of the model states) follows a given time series of observations. Typically though, these two requirements cannot both be met at the same time–tracking the observations is not possible without the trajectory deviating from the proposed model equations, while adherence to the model requires deviations from the observations. Thus, data assimilation faces a trade-off. In this contribution, the sensitivity of the data assimilation with respect to perturbations in the observations is identified as the parameter which controls the trade-off. A relation between the sensitivity and the out-of-sample error is established, which allows the latter to be calculated under operational conditions. A minimum out-of-sample error is proposed as a criterion to set an appropriate sensitivity and to settle the discussed trade-off. Two approaches to data assimilation are considered, namely variational data assimilation and Newtonian nudging, also known as synchronization. Numerical examples demonstrate the feasibility of the approach.

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Limnologists had an early preoccupation with lake classification. It gave a necessary structure to the many chemical and biological observations that were beginning to form the basis of one of the earliest truly environmental sciences. August Thienemann was the doyen of such classifiers and his concept with Einar Naumann of oligotrophic and eutrophic lakes remains central to the world-view that limnologists still have. Classification fell into disrepute, however, as it became clear that there would always be lakes that deviated from the prescriptions that the classifiers made for them. Continua became the de rigeur concept and lakes were seen as varying along many chemical, biological and geographic axes. Modern limnologists are comfortable with this concept. That all lakes are different guarantees an indefinite future for limnological research. For those who manage lakes and the landscapes in which they are set, however, it is not very useful. There may be as many as 300000 standing water bodies in England and Wales alone and maybe as many again in Scotland. More than 80 000 are sizable (> 1 ha). Some classification scheme to cope with these numbers is needed and, as human impacts on them increase, a system of assessing and monitoring change must be built into such a scheme. Although ways of classifying and monitoring running waters are well developed in the UK, the same is not true of standing waters. Sufficient understanding of what determines the nature and functioning of lakes exists to create a system which has intellectual credibility as well as practical usefulness. This paper outlines the thinking behind a system which will be workable on a north European basis and presents some early results.

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The article discusses various reports published within the issue, including one by Carmine Bianchi on understanding public sector from different levels and perspectives, one by Mauro Lo Tennero on the aspiration and structure of Sicily to enforce public policy, and one by Nuno Videira and colleagues on the use of group model building in the public sector to concur sustainable policies.

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This study puts forward a method to model and simulate the complex system of hospital on the basis of multi-agent technology. The formation of the agents of hospitals with intelligent and coordinative characteristics was designed, the message object was defined, and the model operating mechanism of autonomous activities and coordination mechanism was also designed. In addition, the Ontology library and Norm library etc. were introduced using semiotic method and theory, to enlarge the method of system modelling. Swarm was used to develop the multi-agent based simulation system, which is favorable for making guidelines for hospital's improving it's organization and management, optimizing the working procedure, improving the quality of medical care as well as reducing medical charge costs.

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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.

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Since the Dearing Report .1 there has been an increased emphasis on the development of employability and transferable (‘soft’) skills in undergraduate programmes. Within STEM subject areas, recent reports concluded that universities should offer ‘greater and more sustainable variety in modes of study to meet the changing demands of industry and students’.2 At the same time, higher education (HE) institutions are increasingly conscious of the sensitivity of league table positions on employment statistics and graduate destinations. Modules that are either credit or non-credit bearing are finding their way into the core curriculum at HE. While the UK government and other educational bodies argue the way forward over A-level reform, universities must also meet the needs of their first year cohorts in terms of the secondary to tertiary transition and developing independence in learning.

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Purpose – The purpose of this study is to address a recent call for additional research on electronic word-of-mouth (eWOM). In response to this call, this study draws on the social network paradigm and the uses and gratification theory (UGT) to propose and empirically test a conceptual framework of key drivers of two types of eWOM, namely in-group and out-of-group. Design/methodology/approach – The proposed model, which examines the impact of usage motivations on eWOM in-group and eWOM out-of-group, is tested in a sample of 302 internet users in Portugal. Findings – Results from the survey show that the different drivers (i.e. mood-enhancement, escapism, experiential learning and social interaction) vary in terms of their impact on the two different types of eWOM. Surprisingly, while results show a positive relationship between experiential learning and eWOM out-of-group, no relationship is found between experiential learning and eWOM in-group. Research limitations/implications – This is the first study investigating the drivers of both eWOM in-group and eWOM out-of-group. Additional research in this area will contribute to the development of a general theory of eWOM. Practical implications – By understanding the drivers of different eWOM types, this study provides guidance to marketing managers on how to allocate resources more efficiently in order to achieve the company's strategic objectives. Originality/value – No published study has investigated the determinants of these two types of eWOM. This is the first study offering empirical considerations of how the various drivers differentially impact eWOM in-group and eWOM out-of-group.

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Purpose– The purpose of this study is to address a recent call for additional research on electronic word‐of‐mouth (eWOM). In response to this call, this study draws on the social network paradigm and the uses and gratification theory (UGT) to propose and empirically test a conceptual framework of key drivers of two types of eWOM, namely in‐group and out‐of‐group. Design/methodology/approach– The proposed model, which examines the impact of usage motivations on eWOM in‐group and eWOM out‐of‐group, is tested in a sample of 302 internet users in Portugal. Findings– Results from the survey show that the different drivers (i.e. mood‐enhancement, escapism, experiential learning and social interaction) vary in terms of their impact on the two different types of eWOM. Surprisingly, while results show a positive relationship between experiential learning and eWOM out‐of‐group, no relationship is found between experiential learning and eWOM in‐group. Research limitations/implications– This is the first study investigating the drivers of both eWOM in‐group and eWOM out‐of‐group. Additional research in this area will contribute to the development of a general theory of eWOM. Practical implications– By understanding the drivers of different eWOM types, this study provides guidance to marketing managers on how to allocate resources more efficiently in order to achieve the company's strategic objectives. Originality/value– No published study has investigated the determinants of these two types of eWOM. This is the first study offering empirical considerations of how the various drivers differentially impact eWOM in‐group and eWOM out‐of‐group.