Academic strategy planning for a university research centre

The Signal Processing Research Centre (SPRC) at QUT recently formulated an academic strategy plan. This paper describes the various factors that must be considered in undertaking such a planning process. It also illustrates the need for a university research centre to plan for its teaching activities as well as its research activities. Complementary teaching and research are essential to the achievement of the strategic objectives of a university centre.

Spaces of possibility in pre-service teacher education

Pre-service teacher education is a spatialized enterprise. It operates across a number of spaces that may or may not be linked ideologically and/or physically. These spaces can include daily practices, locations, infrastructure, relationships and representations of power and ideology. The interrelationships between and within these (sometimes competing) spaces for pre-service teachers will influence their identities as teachers and learners across time and space. Pre-service teachers are expected to make the connections between these often-contradictory spaces with little or no guidance on how to negotiate such complex relationships. These are difficult spaces, yet the slippages and gaps between these spaces offer generative possibilities. This paper explores these spaces of possibility for pre-service teacher education, and uses the spatial theories of Lefebvre (1991) and Foucault (1977, 1980) to argue that critical reflective practice can be used to create a ‘thirdspace’ (Soja, 1996) for reconstructing future practice.

A genome-based strategy uncovers frequent BRAF mutations in melanoma

Using a genome-scanning approach to search for oncogenes, a recent report identifies somatic mutations in the signaling gene BRAF that are particularly prevalent in melanoma.

Stochastic regularization method for backward Cauchy problem in Banach spaces

We consider a stochastic regularization method for solving the backward Cauchy problem in Banach spaces. An order of convergence is obtained on sourcewise representative elements.

Redesigning school spaces : creating possibilities for learning

This chapter reports on a project in which university researchers’ expertise in architecture, literacy and communications enabled two teachers in one school to expand the forms of literacy that primary school children engaged in. Starting from the school community’s concerns about an urban renewal project in their neighbourhood, participants collaborated to develop a curriculum of spatial literacies with real-world goals and outcomes. We describe how the creative re-design of curriculum and pedagogy by classroom teachers, in collaboration with university academics and students, allowed students aged 8 to 12 years to appropriate semiotic resources from their local neighbourhood, home communities, and popular culture to make a difference to their material surrounds. We argue that there are productive possibilities for educators who integrate critical and place-based approaches to the design and teaching of the literacy curriculum with work in other learning areas such as society and environment, technology and design and the arts. The student production of expansive and socially significant texts enabled by such approaches may be especially necessary in contemporary neoconservative policy contexts that tend to limit and constrain what is possible in schools.

Activity modelling in crowded environments : a soft decision approach

Probabilistic topic models have recently been used for activity analysis in video processing, due to their strong capacity to model both local activities and interactions in crowded scenes. In those applications, a video sequence is divided into a collection of uniform non-overlaping video clips, and the high dimensional continuous inputs are quantized into a bag of discrete visual words. The hard division of video clips, and hard assignment of visual words leads to problems when an activity is split over multiple clips, or the most appropriate visual word for quantization is unclear. In this paper, we propose a novel algorithm, which makes use of a soft histogram technique to compensate for the loss of information in the quantization process; and a soft cut technique in the temporal domain to overcome problems caused by separating an activity into two video clips. In the detection process, we also apply a soft decision strategy to detect unusual events.We show that the proposed soft decision approach outperforms its hard decision counterpart in both local and global activity modelling.

Analysis of rural activity spaces and transport disadvantage using a multi-method approach

Current knowledge about the relationship between transport disadvantage and activity space size is limited to urban areas, and as a result, very little is known about this link in a rural context. In addition, although research has identified transport disadvantaged groups based on their size of activity space, these studies have, however, not empirically explained such differences and the result is often a poor identification of the problems facing disadvantaged groups. Research has shown that transport disadvantage varies over time. The static nature of analysis using the activity space concept in previous research studies has lacked the ability to identify transport disadvantage in time. Activity space is a dynamic concept; and therefore possesses a great potential in capturing temporal variations in behaviour and access opportunities. This research derives measures of the size and fullness of activity spaces for 157 individuals for weekdays, weekends, and for a week using weekly activity-travel diary data from three case study areas located in rural Northern Ireland. Four focus groups were also conducted in order to triangulate quantitative findings and to explain the differences between different socio-spatial groups. The findings of this research show that despite having a smaller sized activity space, individuals were not disadvantaged because they were able to access their required activities locally. Car-ownership was found to be an important life line in rural areas. Temporal disaggregation of the data reveals that this is true only on weekends due to a lack of public transport services. In addition, despite activity spaces being at a similar size, the fullness of activity spaces of low-income individuals was found to be significantly lower compared to their high-income counterparts. Focus group data shows that financial constraint, poor connections both between public transport services and between transport routes and opportunities forced individuals to participate in activities located along the main transport corridors.

Pattern recognition using invariants defined from higher order spectra - one-dimensional inputs

A new approach to pattern recognition using invariant parameters based on higher order spectra is presented. In particular, invariant parameters derived from the bispectrum are used to classify one-dimensional shapes. The bispectrum, which is translation invariant, is integrated along straight lines passing through the origin in bifrequency space. The phase of the integrated bispectrum is shown to be scale and amplification invariant, as well. A minimal set of these invariants is selected as the feature vector for pattern classification, and a minimum distance classifier using a statistical distance measure is used to classify test patterns. The classification technique is shown to distinguish two similar, but different bolts given their one-dimensional profiles. Pattern recognition using higher order spectral invariants is fast, suited for parallel implementation, and has high immunity to additive Gaussian noise. Simulation results show very high classification accuracy, even for low signal-to-noise ratios.