Testing the vision: Preschool settings as places for meeting, bonding and bridging

The OECD (2006 Starting Strong II: Early Childhood Education and Care. OECD Publishing: Paris) envisions early childhood education and care settings as meeting places for diverse social groups; places that build social capital. This vision was assessed in a comparison of three preschools types: full-fee paying, subsidised-fee and publicly funded. The social composition within each was examined and the connectedness of the children (n = 472) who attended compared. Publicly funded preschools had more socially diverse populations. The quantity of social connectedness did not differ but children in publicly funded preschools described higher quality social relationships. Not all preschool settings are socially diverse but, where they are, the quality of relationships is highest.

Interaction in a Paired Speaking Test : the Rater's Perspective

Paired speaking tests are increasingly used in both low-and high-stakes second language assessment contexts. Until recently, very little was known about the way in which raters interpret and apply descriptors relating to interactional competence to a performance that is co-constructed. This book presents a study which explores the interactional features of a paired speaking test that were sailient to raters and the extent to which raters viewed the performance as separable. The study shows that raters use their own frames of reference to interpret descriptors and that they viewed certain features of the performance as mutual accomplishments. The book takes us 'beyond scores', and in doing so, contributes to the growing body of research on paired speaking tests.

Collaborative destination branding : planning for tourism development through design in the Waterfall Way, NSW, Australia

This thesis develops, applies and analyses a collaborative design methodology for branding a tourism destination. The area between the Northern Tablelands and the Mid-North Coast of New South Wales, Australia, was used as a case study for this research. The study applies theoretical concepts of systems thinking and complexity to the real world, and tests the use of design as a social tool to engage multiple stakeholders in planning. In this research I acknowledge that places (and destinations) are socially constructed through people's interactions with their physical and social environments. This study explores a methodology that is explicit about the uncertainties of the destination’s system, and that helps to elicit knowledge and system trends. The collective design process used the creation of brand concepts, elements and strategies as instruments to directly engage stakeholders in the process of reflecting about their places and the issues related to tourism activity in the region. The methods applied included individual conversations and collaborative design sessions to elicit knowledge from local stakeholders. Concept maps were used to register and interpret information released throughout the process. An important aspect of the methodology was to bring together different stakeholder groups and translate the information into a common language that was understandable by all participants. This work helped release significant information as to what kind of tourism activity local stakeholders are prepared to receive and support. It also helped the emergence of a more unified regional identity. The outcomes delivered by the project (brand, communication material and strategies) were of high quality and in line with the desires and expectation of the local hosts. The process also reinforced local sense of pride, belonging and conservation. Furthermore, interaction between participants from different parts of the region triggered some self organising activity around the brand they created together. A major contribution of the present work is the articulation of an inclusive methodology to facilitate the involvement of locals into the decision-making process related to tourism planning. Of particular significance is the focus on the social construction of meaning in and through design, showing that design exercises can have significant social impact – not only on the final product, but also on the realities of the people involved in the creative process.

Monitoring mesenchymal stem cell cultures using image processing and pattern recognition techniques

Stem cells have attracted tremendous interest in recent times due to their promise in providing innovative new treatments for a great range of currently debilitating diseases. This is due to their potential ability to regenerate and repair damaged tissue, and hence restore lost body function, in a manner beyond the body's usual healing process. Bone marrow-derived mesenchymal stem cells or bone marrow stromal cells are one type of adult stem cells that are of particular interest. Since they are derived from a living human adult donor, they do not have the ethical issues associated with the use of human embryonic stem cells. They are also able to be taken from a patient or other donors with relative ease and then grown readily in the laboratory for clinical application. Despite the attractive properties of bone marrow stromal cells, there is presently no quick and easy way to determine the quality of a sample of such cells. Presently, a sample must be grown for weeks and subject to various time-consuming assays, under the direction of an expert cell biologist, to determine whether it will be useful. Hence there is a great need for innovative new ways to assess the quality of cell cultures for research and potential clinical application. The research presented in this thesis investigates the use of computerised image processing and pattern recognition techniques to provide a quicker and simpler method for the quality assessment of bone marrow stromal cell cultures. In particular, aim of this work is to find out whether it is possible, through the use of image processing and pattern recognition techniques, to predict the growth potential of a culture of human bone marrow stromal cells at early stages, before it is readily apparent to a human observer. With the above aim in mind, a computerised system was developed to classify the quality of bone marrow stromal cell cultures based on phase contrast microscopy images. Our system was trained and tested on mixed images of both healthy and unhealthy bone marrow stromal cell samples taken from three different patients. This system, when presented with 44 previously unseen bone marrow stromal cell culture images, outperformed human experts in the ability to correctly classify healthy and unhealthy cultures. The system correctly classified the health status of an image 88% of the time compared to an average of 72% of the time for human experts. Extensive training and testing of the system on a set of 139 normal sized images and 567 smaller image tiles showed an average performance of 86% and 85% correct classifications, respectively. The contributions of this thesis include demonstrating the applicability and potential of computerised image processing and pattern recognition techniques to the task of quality assessment of bone marrow stromal cell cultures. As part of this system, an image normalisation method has been suggested and a new segmentation algorithm has been developed for locating cell regions of irregularly shaped cells in phase contrast images. Importantly, we have validated the efficacy of both the normalisation and segmentation method, by demonstrating that both methods quantitatively improve the classification performance of subsequent pattern recognition algorithms, in discriminating between cell cultures of differing health status. We have shown that the quality of a cell culture of bone marrow stromal cells may be assessed without the need to either segment individual cells or to use time-lapse imaging. Finally, we have proposed a set of features, that when extracted from the cell regions of segmented input images, can be used to train current state of the art pattern recognition systems to predict the quality of bone marrow stromal cell cultures earlier and more consistently than human experts.

Fault diagnostics and supervised testing : How fault diagnostic tools can be proactive?

The topic of fault detection and diagnostics (FDD) is studied from the perspective of proactive testing. Unlike most research focus in the diagnosis area in which system outputs are analyzed for diagnosis purposes, in this paper the focus is on the other side of the problem: manipulating system inputs for better diagnosis reasoning. In other words, the question of how diagnostic mechanisms can direct system inputs for better diagnosis analysis is addressed here. It is shown how the problem can be formulated as decision making problem coupled with a Bayesian Network based diagnostic mechanism. The developed mechanism is applied to the problem of supervised testing in HVAC systems.