833 resultados para membership


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The South Eastern Museums Service is one of ten Area Museums Councils in Great Britain. They are partnerships; membership organizations to which the 2 000 + museums belong. They provide advice, support, technical services, information and training for their members. They are the principal channel of government grant-in-aid to local government, university and independent museums. This funding comes from the Department of National Heritage via the Museums & Galleries Commission. At the South Eastern Museums Service I am responsible for the development and delivery of training for 600 museums in our region and the provision of information about museums and of interest to museums. This paper explains how we approach in-service training and the value of the definition of national standards for our work. It will pose some questions: What is training? What is a training need? and describe a new initiative, the development of training materials and their delivery.

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Este estudo caracteriza os processos de exploração vocacional e de ajustamento académico, e os traços de personalidade de estudantes universitários a frequentar o ISLA Leiria. A amostra inclui 115 estudantes, de ambos os sexos (62,6%) mulheres e (37,4%) homens, com idades compreendidas entre os 18 e 61 anos, a frequentar o 1º Ciclo do Ensino Superior, no ano letivo de 2010/2011. As medidas aplicadas foram o Career Exploration Survey (CES, Stumpf et al., 1983, versão adaptada por Taveira, 1997), o Academic Adjustment Questionnaire (AAQ; Lent et al., 2005; versão adaptada por Lent & Taveira, 2004) e o Inventário de Personalidade Neo - Revisto (NEOPI-R; Costa & Crae, 1992; versão adaptada por Lima, 1997). Os resultados indicam que a exploração vocacional dos alunos está ativada, ao nível das suas crenças, comportamentos, e reações à exploração, e que estes se encontram envolvidos em objetivos de trabalho. Verificou-se que não existem diferenças estatisticamente significativas nos processos de exploração vocacional em função do sexo dos participantes e em função dos anos que frequentam. Em termos de personalidade os resultados apresentam um nível de Neuroticismo moderado, assim como uma Abertura à Experiencia moderada também. A Conscienciosidade, a Extroversão e a Amabilidade revelam níveis mais positivos. Não são verificados níveis significantes de diferença em função do sexo de pertença ou do anos que frequentam. Relativamente ao Ajustamento Académico o dado mais relevante é a fraca autoeficácia para ultrapassar obstáculos. Aqui também não são registadas alterações em função do sexo de pertença ou do ano que frequentam.

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Without corrective measures, Greek public debt will exceed 190 percent of GDP, instead of peaking at the anyway too-high target ratio of 167 percent of GDP of the March 2012 financial assistance programme. The rise is largely due to a negative feedback loop between high public debt and the collapse in GDP, and endangers Greek membership of the euro area. But a Greek exit would have devastating impacts both inside and outside Greece. A small reduction in the interest rate on bilateral loans, the exchange of European Central Bank holdings, buy-back of privately-held debt, and frontloading of some privatisation receipts are unlikely to be sufficient. A credible resolution should involve the reduction of the official lending rate to zero until 2020, an extension of the maturity of all official lending, and indexing the notional amount of all official loans to Greek GDP. Thereby, the debt ratio would fall below 100 percent of GDP by 2020, and if the economy deteriorates further, there will not be a need for new arrangements. But if growth is better than expected, official creditors will also benefit. In exchange for such help, the fiscal sovereignty of Greece should be curtailed further. An extended privatisation plan and future budget surpluses may be used to pay back the debt relief. The Greek fiscal tragedy highlights the need for a formal debt restructuring mechanism

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In 2005 the EU and Turkey officially started accession negotiations that were intended to lead to Turkey’s full membership of the EU. Yet today, the Turkish accession process has virtually ground to a halt and lost all credibility. Talk of alternatives to full membership can be heard from various sides; we highlight four instances of what we call ‘parallelism’, namely the elusive concept of a ‘privileged partnership’, the EU-Turkey customs union, the recently launched ‘Positive Agenda’ and Turkish participation in the Energy Community Treaty. While a privileged partnership represents a more comprehensive but still remote framework for EU-Turkish relations, the latter three are merely an escape route from preaccession. We conclude our analysis with a discussion on Turkey’s possible membership of the European Economic Area, which in effect would serve none of the parties involved. We conclude that both partners, the EU and Turkey, would be well advised to remember their pre-accession commitments of 13 years ago – for their mutual benefit.

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Despite the success of studies attempting to integrate remotely sensed data and flood modelling and the need to provide near-real time data routinely on a global scale as well as setting up online data archives, there is to date a lack of spatially and temporally distributed hydraulic parameters to support ongoing efforts in modelling. Therefore, the objective of this project is to provide a global evaluation and benchmark data set of floodplain water stages with uncertainties and assimilation in a large scale flood model using space-borne radar imagery. An algorithm is developed for automated retrieval of water stages with uncertainties from a sequence of radar imagery and data are assimilated in a flood model using the Tewkesbury 2007 flood event as a feasibility study. The retrieval method that we employ is based on possibility theory which is an extension of fuzzy sets and that encompasses probability theory. In our case we first attempt to identify main sources of uncertainty in the retrieval of water stages from radar imagery for which we define physically meaningful ranges of parameter values. Possibilities of values are then computed for each parameter using a triangular ‘membership’ function. This procedure allows the computation of possible values of water stages at maximum flood extents along a river at many different locations. At a later stage in the project these data are then used in assimilation, calibration or validation of a flood model. The application is subsequently extended to a global scale using wide swath radar imagery and a simple global flood forecasting model thereby providing improved river discharge estimates to update the latter.

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Studies of construction labour productivity have revealed that limited predictability and multi-agent social complexity make long-range planning of construction projects extremely inaccurate. Fire-fighting, a cultural feature of construction project management, social and structural diversity of involved permanent organizations, and structural temporality all contribute towards relational failures and frequent changes. The main purpose of this paper is therefore to demonstrate that appropriate construction planning may have a profound synergistic effect on structural integration of a project organization. Using the general systems theory perspective it is further a specific objective to investigate and evaluate organizational effects of changes in planning and potentials for achieving continuous project-organizational synergy. The newly developed methodology recognises that planning should also represent a continuous, improvement-leading driving force throughout a project. The synergistic effect of the process planning membership duality fostered project-wide integration, eliminated internal boundaries, and created a pool of constantly upgrading knowledge. It maintained a creative environment that resulted in a number of process-related improvements from all parts of the organization. As a result labour productivity has seen increases of more than 30%, profits have risen from an average of 12% to more than 18%, and project durations have been reduced by several days.

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The paper explores the low uptake of livestock vaccination among poor farming communities in Bolivia utilising core elements of the original innovation diffusion theory. Contrary to the recent literature, we found that vaccination behaviour was strongly Linked to social and cultural, rather than economic, drivers. While membership in a group increased uptake, the 'hot' and 'cold' distinctions which dictate health versus illness within Andean cosmology also played a role, with vaccination viewed as a means of addressing underlying imbalances. We concluded that uptake of livestock vaccination was unlikely to improve without knowledge transfer that acknowledges local. epistemologies for Livestock disease. (C) 2008 Elsevier Ltd. All rights reserved.

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A questionnaire survey of 408 households explored the role of socio-economic and cultural factors in rice (Oryza sativa L.) varietal diversity management on-farm in two contrasting eco-sites in Nepal. Multiple regression outputs suggest that number of parcels of land, livestock number, number of rice ecosystems, agro-ecology (altitude), and use of chemical fertilizer have a significant positive influence on landrace diversity on-farm, while membership in farmers' groups linked to extension services has significant but negative influence on landrace diversity. Factors with significant positive influence on diversity of modern varieties on-farm were number of parcels of land and of rice ecosystems, access to irrigation, membership in farmers' groups, and use of insecticide. Within communities, resource-endowed households maintain significantly higher varietal diversity on-farm than resource-poor households and play a significant role in conserving landraces that are vulnerable to genetic erosion and those with socio-cultural and market-preferred traits. Resource-poor households also contribute to local diversity conservation but at lower richness and area coverage levels than resource-endowed households. Households where a female had assumed the role of head of household due to death or migrant work of her husband had less diversity due to lower labor availability. Landraces with socio-cultural and market-preferred traits are few in number but have potential to be conserved on-farm.

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Background Recent research provides evidence for specific disturbance in feeding and growth in children of mothers with eating disorders. Aim To investigate the impact of maternal eating disorders during the post-natal year on the internal world of children, as expressed in children's representations of self and their mother in pretend mealtime play at 5 years of age. Methods Children of mothers with eating disorders (n = 33) and a comparison group (n = 24) were videotaped enacting a family mealtime in pretend play. Specific classes of children's play representations were coded blind to group membership. Univariate analyses compared the groups on representations of mother and self. Logistic regression explored factors predicting pretend play representations. Results Positive representations of the mother expressed as feeding, eating or body shape themes were more frequent in the index group. There were no other significant group differences in representations. In a logistic regression analysis, current maternal eating psychopathology was the principal predictor of these positive maternal representations. Marital criticism was associated with negative representations of the mother. Conclusions These findings suggest that maternal eating disorders may influence the development of a child's internal world, such that they are more preoccupied with maternal eating concerns. However, more extensive research on larger samples is required to replicate these preliminary findings.

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This paper introduces a new neurofuzzy model construction and parameter estimation algorithm from observed finite data sets, based on a Takagi and Sugeno (T-S) inference mechanism and a new extended Gram-Schmidt orthogonal decomposition algorithm, for the modeling of a priori unknown dynamical systems in the form of a set of fuzzy rules. The first contribution of the paper is the introduction of a one to one mapping between a fuzzy rule-base and a model matrix feature subspace using the T-S inference mechanism. This link enables the numerical properties associated with a rule-based matrix subspace, the relationships amongst these matrix subspaces, and the correlation between the output vector and a rule-base matrix subspace, to be investigated and extracted as rule-based knowledge to enhance model transparency. The matrix subspace spanned by a fuzzy rule is initially derived as the input regression matrix multiplied by a weighting matrix that consists of the corresponding fuzzy membership functions over the training data set. Model transparency is explored by the derivation of an equivalence between an A-optimality experimental design criterion of the weighting matrix and the average model output sensitivity to the fuzzy rule, so that rule-bases can be effectively measured by their identifiability via the A-optimality experimental design criterion. The A-optimality experimental design criterion of the weighting matrices of fuzzy rules is used to construct an initial model rule-base. An extended Gram-Schmidt algorithm is then developed to estimate the parameter vector for each rule. This new algorithm decomposes the model rule-bases via an orthogonal subspace decomposition approach, so as to enhance model transparency with the capability of interpreting the derived rule-base energy level. This new approach is computationally simpler than the conventional Gram-Schmidt algorithm for resolving high dimensional regression problems, whereby it is computationally desirable to decompose complex models into a few submodels rather than a single model with large number of input variables and the associated curse of dimensionality problem. Numerical examples are included to demonstrate the effectiveness of the proposed new algorithm.

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Group biases based on broad category membership appear early in human development. However, like many other primates humans inhabit social worlds also characterised by small groups of social coalitions which are not demarcated by visible signs or social markers. A critical cognitive challenge for a young child is thus how to extract information concerning coalition structure when coalitions are dynamic and may lack stable and outwardly visible cues to membership. Therefore, the ability to decode behavioural cues of affiliations present in everyday social interactions between individuals would have conferred powerful selective advantages during our evolution. This would suggest that such an ability may emerge early in life, however, little research has investigated the developmental origins of such processing. The present paper will review recent empirical research which indicates that in the first 2 years of life infants achieve a host of social-cognitive abilities that make them well adapted to processing coalition-affiliations of others. We suggest that such an approach can be applied to better understand the origins of intergroup attitudes and biases. Copyright © 2010 John Wiley & Sons, Ltd.

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Neurofuzzy modelling systems combine fuzzy logic with quantitative artificial neural networks via a concept of fuzzification by using a fuzzy membership function usually based on B-splines and algebraic operators for inference, etc. The paper introduces a neurofuzzy model construction algorithm using Bezier-Bernstein polynomial functions as basis functions. The new network maintains most of the properties of the B-spline expansion based neurofuzzy system, such as the non-negativity of the basis functions, and unity of support but with the additional advantages of structural parsimony and Delaunay input space partitioning, avoiding the inherent computational problems of lattice networks. This new modelling network is based on the idea that an input vector can be mapped into barycentric co-ordinates with respect to a set of predetermined knots as vertices of a polygon (a set of tiled Delaunay triangles) over the input space. The network is expressed as the Bezier-Bernstein polynomial function of barycentric co-ordinates of the input vector. An inverse de Casteljau procedure using backpropagation is developed to obtain the input vector's barycentric co-ordinates that form the basis functions. Extension of the Bezier-Bernstein neurofuzzy algorithm to n-dimensional inputs is discussed followed by numerical examples to demonstrate the effectiveness of this new data based modelling approach.

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This paper introduces a new neurofuzzy model construction algorithm for nonlinear dynamic systems based upon basis functions that are Bezier-Bernstein polynomial functions. This paper is generalized in that it copes with n-dimensional inputs by utilising an additive decomposition construction to overcome the curse of dimensionality associated with high n. This new construction algorithm also introduces univariate Bezier-Bernstein polynomial functions for the completeness of the generalized procedure. Like the B-spline expansion based neurofuzzy systems, Bezier-Bernstein polynomial function based neurofuzzy networks hold desirable properties such as nonnegativity of the basis functions, unity of support, and interpretability of basis function as fuzzy membership functions, moreover with the additional advantages of structural parsimony and Delaunay input space partition, essentially overcoming the curse of dimensionality associated with conventional fuzzy and RBF networks. This new modeling network is based on additive decomposition approach together with two separate basis function formation approaches for both univariate and bivariate Bezier-Bernstein polynomial functions used in model construction. The overall network weights are then learnt using conventional least squares methods. Numerical examples are included to demonstrate the effectiveness of this new data based modeling approach.

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A key reason for pessimism with respect to greenhouse gas emissions reduction relates to the ‘motivation problem’, whereby those who could make the biggest difference prima facie have the least incentive to act because they are most able to adapt: how can we motivate such people (and thereby everyone else) to accept, indeed to initiate, the changes to their lifestyles that are required for effective emissions reductions? This paper offers an account inspired by Rawls of the good of membership of ‘intergenerational cooperative union’ to achieve justice that provides a solution to the motivation problem.