3 resultados para Expectation maximization

em CORA - Cork Open Research Archive - University College Cork - Ireland


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For two multinormal populations with equal covariance matrices the likelihood ratio discriminant function, an alternative allocation rule to the sample linear discriminant function when n1 ≠ n2 ,is studied analytically. With the assumption of a known covariance matrix its distribution is derived and the expectation of its actual and apparent error rates evaluated and compared with those of the sample linear discriminant function. This comparison indicates that the likelihood ratio allocation rule is robust to unequal sample sizes. The quadratic discriminant function is studied, its distribution reviewed and evaluation of its probabilities of misclassification discussed. For known covariance matrices the distribution of the sample quadratic discriminant function is derived. When the known covariance matrices are proportional exact expressions for the expectation of its actual and apparent error rates are obtained and evaluated. The effectiveness of the sample linear discriminant function for this case is also considered. Estimation of true log-odds for two multinormal populations with equal or unequal covariance matrices is studied. The estimative, Bayesian predictive and a kernel method are compared by evaluating their biases and mean square errors. Some algebraic expressions for these quantities are derived. With equal covariance matrices the predictive method is preferable. Where it derives this superiority is investigated by considering its performance for various levels of fixed true log-odds. It is also shown that the predictive method is sensitive to n1 ≠ n2. For unequal but proportional covariance matrices the unbiased estimative method is preferred. Product Normal kernel density estimates are used to give a kernel estimator of true log-odds. The effect of correlation in the variables with product kernels is considered. With equal covariance matrices the kernel and parametric estimators are compared by simulation. For moderately correlated variables and large dimension sizes the product kernel method is a good estimator of true log-odds.

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The healthcare industry is beginning to appreciate the benefits which can be obtained from using Mobile Health Systems (MHS) at the point-of-care. As a result, healthcare organisations are investing heavily in mobile health initiatives with the expectation that users will employ the system to enhance performance. Despite widespread endorsement and support for the implementation of MHS, empirical evidence surrounding the benefits of MHS remains to be fully established. For MHS to be truly valuable, it is argued that the technological tool be infused within healthcare practitioners work practices and used to its full potential in post-adoptive scenarios. Yet, there is a paucity of research focusing on the infusion of MHS by healthcare practitioners. In order to address this gap in the literature, the objective of this study is to explore the determinants and outcomes of MHS infusion by healthcare practitioners. This research study adopts a post-positivist theory building approach to MHS infusion. Existing literature is utilised to develop a conceptual model by which the research objective is explored. Employing a mixed-method approach, this conceptual model is first advanced through a case study in the UK whereby propositions established from the literature are refined into testable hypotheses. The final phase of this research study involves the collection of empirical data from a Canadian hospital which supports the refined model and its associated hypotheses. The results from both phases of data collection are employed to develop a model of MHS infusion. The study contributes to IS theory and practice by: (1) developing a model with six determinants (Availability, MHS Self-Efficacy, Time-Criticality, Habit, Technology Trust, and Task Behaviour) and individual performance-related outcomes of MHS infusion (Effectiveness, Efficiency, and Learning), (2) examining undocumented determinants and relationships, (3) identifying prerequisite conditions that both healthcare practitioners and organisations can employ to assist with MHS infusion, (4) developing a taxonomy that provides conceptual refinement of IT infusion, and (5) informing healthcare organisations and vendors as to the performance of MHS in post-adoptive scenarios.

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In an attempt to provide an analytical entry point into my compositional practice, I have identified eight themes which are significantly recurrent: reduction – the selection of a small number of elements; imperfection – a damaged or warped characteristic of sound; hierarchy – a concern with the roles of instruments with regard to their relative prominence; motion – apparently static sound masses consist of fine internal movement; listener perception – expectations for change influence the experience of affect; translation – the transitioning of electronic sounds to the acoustic realm, and vice versa; immersion – the creation of an accommodating soundscape; blurring – smearing and overlapping sounds or genres. Each of these eight factors is associated with relevant precedents in the history and theory of music that have been influential on my work. These include the minimalist compositions of Steve Reich and Arvo Pärt; the lo-fi aesthetic of Boards of Canada and My Bloody Valentine; concerns with political hierarchy in the work of Louis Andriessen; the variations of dynamics and microtonal shifts of Giacinto Scelsi; Leonard B. Meyer's account of expectation in music; cross-fertilisation of the acoustic and electronic in pieces by Gérard Grisey and Gyorgy Ligeti; the immersive technique of Brian Eno's ambient music; and the overlapping sounds of Aphex Twin. These eight factors are variously applicable to the eleven submitted pieces, which are individually analysed with reference to the most significant of the categories. Together they form a musical language that sustains the interaction of a variety of techniques, concepts and genres.