555 resultados para Mixed Models
Resumo:
Aims – To develop local contemporary coefficients for the Trauma Injury Severity Score in New Zealand, TRISS(NZ), and to evaluate their performance at predicting survival against the original TRISS coefficients. Methods – Retrospective cohort study of adults who sustained a serious traumatic injury, and who survived until presentation at Auckland City, Middlemore, Waikato, or North Shore Hospitals between 2002 and 2006. Coefficients were estimated using ordinary and multilevel mixed-effects logistic regression models. Results – 1735 eligible patients were identified, 1672 (96%) injured from a blunt mechanism and 63 (4%) from a penetrating mechanism. For blunt mechanism trauma, 1250 (75%) were male and average age was 38 years (range: 15-94 years). TRISS information was available for 1565 patients of whom 204 (13%) died. Area under the Receiver Operating Characteristic (ROC) curves was 0.901 (95%CI: 0.879-0.923) for the TRISS(NZ) model and 0.890 (95% CI: 0.866-0.913) for TRISS (P<0.001). Insufficient data were available to determine coefficients for penetrating mechanism TRISS(NZ) models. Conclusions – Both TRISS models accurately predicted survival for blunt mechanism trauma. However, TRISS(NZ) coefficients were statistically superior to TRISS coefficients. A strong case exists for replacing TRISS coefficients in the New Zealand benchmarking software with these updated TRISS(NZ) estimates.
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Advertising research has generally not gone beyond offering support for a positive effect where ethnic models in advertising are viewed by consumers of the same ethnicity. This study offers an explanation behind this phenomenon that can be useful to marketers using self-reference theory. Our experiment reveals a strong self-referencing effect for ethnic minority individuals. Specifically, Asian subjects (the ethnic minority group) self-referenced ads with Asian models more than white subjects (the ethnic majority group). However, this result was not evident for white subjects. Implications for academics and advertisers are discussed.
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Objectives: To report on the design, significance and potential impacts of the first documented human clinical trial assessing the anxiolytic and thymoleptic efficacy of an aqueous monoextract of Piper methysticum (kava). The significance of the qualitative element of our clinical trial is also explored. The Kava Anxiety Depression Spectrum Study (KADSS) is a 3-week placebocontrolled, double-blind, cross-over trial involving 60 adult participants (18—65) with elevated stable anxiety and varying levels of depressive symptoms. Aims: The aims of KADSS are: (1) to determine whether an aqueous standardised extract of kava is effective for the treatment of anxiety; (2) to assess the effects of kava on differing levels of depression; and (3) to explore participants’ experience of taking kava via qualitative research. The study also provides preliminary assessment of the safety of an aqueous extract of kava in humans. Conclusion: If results reveal that the aqueous kava preparation exerts significant anxiolytic effects and appears safe, potentially beneficial impacts may occur. Data supporting a safe and effective kava extract may encourage a re-introduction of kava to Europe, UK and Canada. This may provide a major socioeconomic benefit to Pacific Island nations, and to sufferers of anxiety disorders.
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The mixed anion mineral parnauite Cu9[(OH)10|SO4|(AsO4)2].7H2O has been studied by Raman spectroscopy. Characteristic bands associated with arsenate, sulphate, hydroxyl units are identified. Broad bands are observed and are resolved into component bands. Two intense bands at 859 and 830 cm-1 are assigned to the 1 (AsO4)3- symmetric stretching and 3 (AsO4)3- antisymmetric stretching modes. The comparatively sharp band at 976 cm-1 is assigned to the ν1 (SO4)2- symmetric stretching mode and a broad spectral profile centered upon 1097 cm-1 is attributed to the ν3 (SO4)2- antisymmetric stretching mode. A comparison of the Raman spectra is made with other arsenate bearing minerals such as carminite, clinotyrolite, kankite, tilasite and pharmacosiderite.
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Australia needs highly skilled workers to sustain a healthy economy. Current employment-based training models have limitations in meeting the demands for highly skilled labour supply. The research explored current and emerging models of employment-based training to propose more effective models at higher VET qualifications that can maintain a balance between institution and work-based learning.
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Cognitive modelling of phenomena in clinical practice allows the operationalisation of otherwise diffuse descriptive terms such as craving or flashbacks. This supports the empirical investigation of the clinical phenomena and the development of targeted treatment interventions. This paper focuses on the cognitive processes underpinning craving, which is recognised as a motivating experience in substance dependence. We use a high-level cognitive architecture, Interacting Cognitive Subsystems (ICS), to compare two theories of craving: Tiffany's theory, centred on the control of automated action schemata, and our own Elaborated Intrusion theory of craving. Data from a questionnaire study of the subjective aspects of everyday desires experienced by a large non-clinical population are presented. Both the data and the high-level modelling support the central claim of the Elaborated Intrusion theory that imagery is a key element of craving, providing the subjective experience and mediating much of the associated disruption of concurrent cognition.
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Rural land has not always been considered as a major long-term investment with both institutional investors and absentee owners in countries such as U.K. and Australia. Although rural land is included in both single asset and mixed asset portfolios in the U.S, it is not at the same levels as either commercial or industrial property. Rural land occupies over 50% of the total area of Australia, and comprises over 115,000 economic farm properties (excludes rural residential, hobby farms and rural lifestyle blocks. However, less than 1.6% of the total economic farm numbers are actually owned by corporate or institutional investors. This low level of corporate involvement in the Australian rural property market has limited both the investment performance research and inclusion of this rural land type in both property and mixed asset investment portfolios. In the U.S. rural land is also the most extensive real estate type based on total area occupied. The United States Department of Agriculture statistics (1998) show that in 1997 there were 2.06 million farms in the U.S., covering 968 million acres, with a total value of $912 billion and generating an annual income of $202 billion. The level of corporate ownership of farms in the U.S. is also higher than the level of corporate farm ownership in Australia. This high level of institutional ownership in rural land in U.S has provided the opportunity for the rural property asset class to be analysed in relation to it’s investment performance and possible role in a mixed asset or mixed property investment portfolio.
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This paper addresses the following problem: given two or more business process models, create a process model that is the union of the process models given as input. In other words, the behavior of the produced process model should encompass that of the input models. The paper describes an algorithm that produces a single configurable process model from an arbitrary collection of process models. The algorithm works by extracting the common parts of the input process models, creating a single copy of them, and appending the differences as branches of configurable connectors. This way, the merged process model is kept as small as possible, while still capturing all the behavior of the input models. Moreover, analysts are able to trace back from which original model(s) does a given element in the merged model come from. The algorithm has been prototyped and tested against process models taken from several application domains.
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Childcare workers play a significant role in the learning and development of children in their care. This has major implications for the training of workers. Under new reforms of the childcare industry the Australian government now requires all workers to obtain qualifications from a vocational education and training provider (eg. Technical and Further Education) or university. Effective models of employment-based training are critical to provide training to highly competent workers. This paper presents findings from a study that examined current and emerging models of employment-based training in the childcare sector, particularly at the Diploma level. Semi-structured interviews were conducted with a sample of 16 participants who represented childcare directors, employers, and workers located in childcare services in urban, regional and remote locations in the State of Queensland. The study proposes a ‘best-fit’ employment-based training approach that is characterised by a compendium of five models instead of a ‘one size fits all’. Issues with successful implementation of the EBT models are also discussed
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We developed orthogonal least-squares techniques for fitting crystalline lens shapes, and used the bootstrap method to determine uncertainties associated with the estimated vertex radii of curvature and asphericities of five different models. Three existing models were investigated including one that uses two separate conics for the anterior and posterior surfaces, and two whole lens models based on a modulated hyperbolic cosine function and on a generalized conic function. Two new models were proposed including one that uses two interdependent conics and a polynomial based whole lens model. The models were used to describe the in vitro shape for a data set of twenty human lenses with ages 7–82 years. The two-conic-surface model (7 mm zone diameter) and the interdependent surfaces model had significantly lower merit functions than the other three models for the data set, indicating that most likely they can describe human lens shape over a wide age range better than the other models (although with the two-conic-surfaces model being unable to describe the lens equatorial region). Considerable differences were found between some models regarding estimates of radii of curvature and surface asphericities. The hyperbolic cosine model and the new polynomial based whole lens model had the best precision in determining the radii of curvature and surface asphericities across the five considered models. Most models found significant increase in anterior, but not posterior, radius of curvature with age. Most models found a wide scatter of asphericities, but with the asphericities usually being positive and not significantly related to age. As the interdependent surfaces model had lower merit function than three whole lens models, there is further scope to develop an accurate model of the complete shape of human lenses of all ages. The results highlight the continued difficulty in selecting an appropriate model for the crystalline lens shape.
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This chapter will address psychodynamic, cognitive-behavioural, and developmental models in supervision by initially considering the historical underpinnings of each and then examining in turn some of the key processes that are evident in the supervisory relationships. Case studies are included where appropriate to highlight the application of theory to practice and several processes are fully elaborated over all models to enable a contemporary view of style and substance in the supervision context.
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Intuitively, any `bag of words' approach in IR should benefit from taking term dependencies into account. Unfortunately, for years the results of exploiting such dependencies have been mixed or inconclusive. To improve the situation, this paper shows how the natural language properties of the target documents can be used to transform and enrich the term dependencies to more useful statistics. This is done in three steps. The term co-occurrence statistics of queries and documents are each represented by a Markov chain. The paper proves that such a chain is ergodic, and therefore its asymptotic behavior is unique, stationary, and independent of the initial state. Next, the stationary distribution is taken to model queries and documents, rather than their initial distri- butions. Finally, ranking is achieved following the customary language modeling paradigm. The main contribution of this paper is to argue why the asymptotic behavior of the document model is a better representation then just the document's initial distribution. A secondary contribution is to investigate the practical application of this representation in case the queries become increasingly verbose. In the experiments (based on Lemur's search engine substrate) the default query model was replaced by the stable distribution of the query. Just modeling the query this way already resulted in significant improvements over a standard language model baseline. The results were on a par or better than more sophisticated algorithms that use fine-tuned parameters or extensive training. Moreover, the more verbose the query, the more effective the approach seems to become.
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Spoken term detection (STD) popularly involves performing word or sub-word level speech recognition and indexing the result. This work challenges the assumption that improved speech recognition accuracy implies better indexing for STD. Using an index derived from phone lattices, this paper examines the effect of language model selection on the relationship between phone recognition accuracy and STD accuracy. Results suggest that language models usually improve phone recognition accuracy but their inclusion does not always translate to improved STD accuracy. The findings suggest that using phone recognition accuracy to measure the quality of an STD index can be problematic, and highlight the need for an alternative that is more closely aligned with the goals of the specific detection task.
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Information System (IS) success may be the most arguable and important dependent variable in the IS field. The purpose of the present study is to address IS success by empirically assess and compare DeLone and McLean’s (1992) and Gable’s et al. (2008) models of IS success in Australian Universities context. The two models have some commonalities and several important distinctions. Both models integrate and interrelate multiple dimensions of IS success. Hence, it would be useful to compare the models to see which is superior; as it is not clear how IS researchers should respond to this controversy.
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One of the classic forms of intermediate representation used for communication between compiler front-ends and back-ends are those based on abstract stack machines. It is possible to compile the stack machine instructions into machine code by means of an interpretive code generator, or to simulate the stack machine at runtime using an interpreter. This paper describes an approach intermediate between these two extremes. The front-end for a commercial Modula 2 compiler was ported to the "industry standard PC", and a partially compiling back-end written. The object code runs with the assistance of an interpreter, but may be linked with libraries which are fully compiled. The intent was to provide a programming environment on the PC which is identical to that of the same compilers on 32-bit UNIX machines. This objective has been met, and the compiler is available to educational institutions as free-ware. The design basis of the new compiler is described, and the performance critically evaluated.