Bracketing: practical considerations in Husserlian phenomenological research

Nursing research leans heavily towards naturalism, with phenomenology commonly adopted. The three main schools of phenomenology used are Husserl's descriptive approach, Heidegger's interpretive hermeneutic approach and the Dutch Utrecht School of phenomenology which combines characteristics of both. Husserl's approach--the description of ordinary human experiences as perceived by each individual--involves four main steps: bracketing, intuiting, analysing and describing. Many phenomenological nurse researchers consciously decide to adopt a Heideggerian approach because of the perceived difficulties in achieving bracketing. This paper examines the concept of bracketing (epoché) and outlines some of the practical considerations when attempting to achieve it.

Min-BDeu and Max-BDeu Scores for Learning Bayesian Networks

This work presents two new score functions based on the Bayesian Dirichlet equivalent uniform (BDeu) score for learning Bayesian network structures. They consider the sensitivity of BDeu to varying parameters of the Dirichlet prior. The scores take on the most adversary and the most beneficial priors among those within a contamination set around the symmetric one. We build these scores in such way that they are decomposable and can be computed efficiently. Because of that, they can be integrated into any state-of-the-art structure learning method that explores the space of directed acyclic graphs and allows decomposable scores. Empirical results suggest that our scores outperform the standard BDeu score in terms of the likelihood of unseen data and in terms of edge discovery with respect to the true network, at least when the training sample size is small. We discuss the relation between these new scores and the accuracy of inferred models. Moreover, our new criteria can be used to identify the amount of data after which learning is saturated, that is, additional data are of little help to improve the resulting model.

Extended Tree Augmented Naive Classifier

This work proposes an extended version of the well-known tree-augmented naive Bayes (TAN) classifier where the structure learning step is performed without requiring features to be connected to the class. Based on a modification of Edmonds’ algorithm, our structure learning procedure explores a superset of the structures that are considered by TAN, yet achieves global optimality of the learning score function in a very efficient way (quadratic in the number of features, the same complexity as learning TANs). A range of experiments show that we obtain models with better accuracy than TAN and comparable to the accuracy of the state-of-the-art classifier averaged one-dependence estimator.

Haptic Aurality – performing in a digital world

Paper accepted at 2015 ISIS in Utrecht. This presentation will examine the performative body from the viewpoint of the listening body in digital media platforms, and thus investigates the proposed conference issues which are at the intersections of ‘play’, ‘perform’ and ‘participate’.

Moving Out of Conflict: Negotiating Social Identity in Response to Segregation in Northern Ireland

This paper examines the impact of territoriality on young people’s everyday experiences in Northern Ireland’s segregated communities. It shows how urban encounters are reproduced through negotiating differences and the ways in which living in divided communities escalates moods of social inequality and spatial imbalances. The empirical study undertaken in the city of Derry shows how individuals and community groups position and identify themselves under the impact of social segregation. Building on Gordon Allport’s (1954) theories of contact, I explain how people in Derry have established their own sense of belonging, of who they are, based on their group memberships which eventually became an important source of pride and selfesteem. They also presented their own intertextual references as a cause of routine survival and belonging, allowing them to be more constructive about their future. Under deeply rooted segregation in Northern Ireland, the young generations are sought to provide lasting change to foster peace and integration between the two communities.

Brightness perception: one simple model explaines most if not all effects

Few models can explain Mach bands (Pessoa, 1996 Vision Research 36 3205-3227) . Our own employs multiscale line and edge coding by simple and complex cells. Lines are interpreted by Gaussian functions, edges by bipolar, Gaussian-truncated errorfunctions. Widths of these functions are coupled to the scales of the underlying cells and the amplitudes are determined by their responses.