52 resultados para Modelo conceptual


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Improvement in the quality of end-of-life (EOL) care is a priority health care issue since serious deficiencies in quality of care have been reported across care settings. Increasing pressure is now focused on Canadian health care organizations to be accountable for the quality of palliative and EOL care delivered. Numerous domains of quality EOL care upon which to create accountability frameworks are now published, with some derived from the patient/family perspective. There is a need to reach common ground on the domains of quality EOL care valued by patients and families in order to develop consistent performance measures and set priorities for health care improvement. This paper describes a meta-synthesis study to develop a common conceptual framework of quality EOL care integrating attributes of quality valued by patients and their families. © 2005 Centre for Bioethics, IRCM.

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According to the World Health Organization, the patient and family should be viewed as the "unit of care" when palliative care is required. Therefore family caregivers should receive optimal supportive care from health professionals. However, the impact of supporting a dying relative is frequently described as having negative physical and psychosocial sequalae. Furthermore, family caregivers consistently report unmet needs and there has been a dearth of rigorous supportive interventions published. In addition, comprehensive conceptual frameworks to navigate the family caregiver experience and guide intervention development are lacking. This article draws on Lazarus and Folkman's seminal work on the transactional stress and coping framework to present a conceptual model specific to family caregivers of patients receiving palliative care. A comprehensive account of key variables to aid understanding of the family caregiver experience and intervention design is provided.

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Prior research has argued that use of optional properties in conceptual models results in loss of information about the semantics of the domains represented by the models. Empirical research undertaken to date supports this argument. Nevertheless, no systematic analysis has been done of whether use of optional properties is always problematic. Furthermore, prior empirical research might have deliberately or unwittingly employed models where use of optionality always causes problems. Accordingly, we examine analytically whether use of optional properties is always problematic. We employ our analytical results to inform the design of an experiment where we systematically examined the impact of optionality on users’ ability to understand domains represented by different types of conceptual models. We found evidence that use of optionality undermines users’ ability to understand the domain represented by a model but that this effect weakens when use of mandatory properties to replace optional properties leads to more-complex models.

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Bayesian probabilistic analysis offers a new approach to characterize semantic representations by inferring the most likely feature structure directly from the patterns of brain activity. In this study, infinite latent feature models [1] are used to recover the semantic features that give rise to the brain activation vectors when people think about properties associated with 60 concrete concepts. The semantic features recovered by ILFM are consistent with the human ratings of the shelter, manipulation, and eating factors that were recovered by a previous factor analysis. Furthermore, different areas of the brain encode different perceptual and conceptual features. This neurally-inspired semantic representation is consistent with some existing conjectures regarding the role of different brain areas in processing different semantic and perceptual properties. © 2012 Springer-Verlag.

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A core activity in information systems development involves understanding the
conceptual model of the domain that the information system supports. Any conceptual model is ultimately created using a conceptual-modeling (CM) grammar. Accordingly, just as high quality conceptual models facilitate high quality systems development, high quality CM grammars facilitate high quality conceptual modeling. This paper seeks to provide a new perspective on improving the quality of CM grammar semantics. For the past twenty years, the leading approach to this topic has drawn on ontological theory. However, the ontological approach captures just half of the story. It needs to be coupled with a logical approach. We show how ontological quality and logical quality interrelate and we outline three contributions of a logical approach: the ability to see familiar conceptualmodeling problems in simpler ways, the illumination of new problems, and the ability to prove the benefit of modifying CM grammars.

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This article provides the genealogy of bricolage and underscores the modifications it has undergone within the sociologies of culture and religion. It draws on the study of three new religious movements that teach unconventional versions of Hinduism and kabbalah, to show that the current understanding of bricolage in the studies of popular culture and religion overestimates its eclectic and personal nature and neglects its sociocultural logics. It tends to take for granted the availability of cultural resources used in bricolage, and finally it fails to understand the social significance of individualism, overlooking the ways in which norms and power could be expressed through culture in the contemporary world. This article suggests that it would be best reclaiming bricolage’s original meaning, prompting questions about the contexts that make certain elements available, social patterns that may organise bricolage, who ‘bricole’, what for, who is empowered, from what and by using whose tradition.

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Although only addressed by EU law from 2000, age discrimination has been the theme of quite a few cases before the Court of Justice, with a high proportion decided by the Grand Chamber recently. This is due to the conceptual and theoretical challenges that a prohibition to use age as differentiating factor poses. After all, age has been an important stratifier used to synchronize life courses through welfare State regimes in Europe. Partly due to these traditions, there are stereotypes associated with old age, and young age, that in turn lead to disadvantage in employment. For the same reason, age discrimination frequently intersects with discrimination on other grounds, such as sex, race or disability. EU legislation on age discrimination has sought to accommodate the traditional role of age in employment policy by allowing wider justifications than for other forms of discrimination. This leads to contradictions within the larger field of discrimination law, which may even threaten to dilute its efficiency. This article analyses how recent case law of the Court of Justice, and in particular its Grand Chamber, deals with the theoretical challenges posed by these conflicting demands on age discrimination and on discrimination law at large.

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Multivariate classification techniques have proven to be powerful tools for distinguishing experimental conditions in single sessions of functional magnetic resonance imaging (fMRI) data. But they are vulnerable to a considerable penalty in classification accuracy when applied across sessions or participants, calling into question the degree to which fine-grained encodings are shared across subjects. Here, we introduce joint learning techniques, where feature selection is carried out using a held-out subset of a target dataset, before training a linear classifier on a source dataset. Single trials of functional MRI data from a covert property generation task are classified with regularized regression techniques to predict the semantic class of stimuli. With our selection techniques (joint ranking feature selection (JRFS) and disjoint feature selection (DJFS)), classification performance during cross-session prediction improved greatly, relative to feature selection on the source session data only. Compared with JRFS, DJFS showed significant improvements for cross-participant classification. And when using a groupwise training, DJFS approached the accuracies seen for prediction across different sessions from the same participant. Comparing several feature selection strategies, we found that a simple univariate ANOVA selection technique or a minimal searchlight (one voxel in size) is appropriate, compared with larger searchlights.

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Inspired by the commercial application of the Exechon machine, this paper proposed a novel parallel kinematic machine (PKM) named Exe-Variant. By exchanging the sequence of kinematic pairs in each limb of the Exechon machine, the Exe-Variant PKM claims an arrangement of 2UPR/1SPR topology and consists of two identical UPR limbs and one SPR limb. The inverse kinematics of the 2UPR/1SPR parallel mechanism was firstly analyzed based on which a conceptual design of the Exe-Variant was carried out. Then an algorithm of reachable workspace searching for the Exe-Variant and the Exchon was proposed. Finally, the workspaces of two example systems of the Exechon and the Exe-Variant with approximate dimensions were numerically simulated and compared. The comparison shows that the Exe-Variant possesses a competitive workspace with the Exechon machine, indicating it can be used as a promising reconfigurable module in a hybrid 5-DOF machine tool system.