Values, wellness and the social sciences curriculum

Recent initiatives in values education in Australia emphasise the importance of the process of valuing and general methodologies that foster this in the classroom. Although a range of strategies are available, this chapter argues that inquiry-based approaches in the Social Sciences play a significant role in linking valuing processes with decision making skills. Collectively, these approaches prompt the development of reasoning and self awareness which also impact on student wellness. This chapter proposes some curriculum approaches to foreground values education in the Australian Social Sciences classroom. It argues that valuing is an important life skill that can be cultivated in the classroom through specific valuing strategies. It contends that the development of the capacity to make informed value choices is a critical factor in promoting wellness and resilience in students and in preparing them for the decision making skills required for effective participation in society.

Consumers’ concepts of materials

User needs and wants dictate the way in which products are designed, produced, used and disposed of. Western society in particular has become very consumer driven and the waste resulting from such activity has the potential to be disastrous. The creation of emotional attachment with possessions is one way of approaching sustainable consumer-product relationships. The aim of this research was to gain a deeper understanding of the interaction and emotional attachment that consumers have and develop with their products. It outlines literature relating to consumer emotion and experience in relation to products, and how pleasurable product user relationships can be prolonged. It is evident from the literature that the roles of materials in the emotional attachment consumers have with products needed to be further explored. A study was conducted to determine consumers. concepts of six materials currently used in product design. This involved participants being given a Concept Prompt Probe with textual prompts to assist in discussion about the materials in question. The discussions between the 15 participant groups of two people, one male and one female, were then transcribed and coded ready for analysis. The study findings demonstrate consumers. concepts of the six materials. The findings show both physical and emotional consumer concepts of the materials. It is, however, the interaction of these concepts that is the most significant finding of this research. Each material concept is not only judged emotionally by consumers in its own right but in relation to other concepts as well. The interaction of the consumers. concepts of materials can considerably effect the emotional judgement made about the material and the appropriateness of its application. This research makes a significant contribution to knowledge regarding the effect materials have on the consumers by identifying how materials can prompt emotional judgements and thereby alter the product user experience.

Decentralised Data Fusion with Parzen Density Estimates

Decentralised sensor networks typically consist of multiple processing nodes supporting one or more sensors. These nodes are interconnected via wireless communication. Practical applications of Decentralised Data Fusion have generally been restricted to using Gaussian based approaches such as the Kalman or Information Filter This paper proposes the use of Parzen window estimates as an alternate representation to perform Decentralised Data Fusion. It is required that the common information between two nodes be removed from any received estimates before local data fusion may occur Otherwise, estimates may become overconfident due to data incest. A closed form approximation to the division of two estimates is described to enable conservative assimilation of incoming information to a node in a decentralised data fusion network. A simple example of tracking a moving particle with Parzen density estimates is shown to demonstrate how this algorithm allows conservative assimilation of network information.

Similarity metrics within a point of view

In vector space based approaches to natural language processing, similarity is commonly measured by taking the angle between two vectors representing words or documents in a semantic space. This is natural from a mathematical point of view, as the angle between unit vectors is, up to constant scaling, the only unitarily invariant metric on the unit sphere. However, similarity judgement tasks reveal that human subjects fail to produce data which satisfies the symmetry and triangle inequality requirements for a metric space. A possible conclusion, reached in particular by Tversky et al., is that some of the most basic assumptions of geometric models are unwarranted in the case of psychological similarity, a result which would impose strong limits on the validity and applicability vector space based (and hence also quantum inspired) approaches to the modelling of cognitive processes. This paper proposes a resolution to this fundamental criticism of of the applicability of vector space models of cognition. We argue that pairs of words imply a context which in turn induces a point of view, allowing a subject to estimate semantic similarity. Context is here introduced as a point of view vector (POVV) and the expected similarity is derived as a measure over the POVV's. Different pairs of words will invoke different contexts and different POVV's. Hence the triangle inequality ceases to be a valid constraint on the angles. We test the proposal on a few triples of words and outline further research.

Remixing social media for location sharing on public urban screens

This paper introduces Sapporo World Window (hereafter SWW), an interactive social media mash-up deployed in a newly built urban public underground space utilising ten public displays and urban dwellers’ mobile phones. SWW enables users to share their favourite locations with fellow citizens and visitors through integrating various social media contents to a coherent whole. The system aims to engage citizens in socio-cultural and technological interactions, turning the underground space into a creative and lively social space. We present first insight from an initial user study in a real world setting.

Effective pattern discovery for text mining

Many data mining techniques have been proposed for mining useful patterns in text documents. However, how to effectively use and update discovered patterns is still an open research issue, especially in the domain of text mining. Since most existing text mining methods adopted term-based approaches, they all suffer from the problems of polysemy and synonymy. Over the years, people have often held the hypothesis that pattern (or phrase) based approaches should perform better than the term-based ones, but many experiments did not support this hypothesis. This paper presents an innovative technique, effective pattern discovery which includes the processes of pattern deploying and pattern evolving, to improve the effectiveness of using and updating discovered patterns for finding relevant and interesting information. Substantial experiments on RCV1 data collection and TREC topics demonstrate that the proposed solution achieves encouraging performance.

Response : letter to the editor by Al-Azri and Al-Maniri

Firstly, the authors would like to thank the editor for the opportunity to respond to Dr Al-Azri’s and Dr Al-Maniri’s letter. Secondly, while the current authors also accept that deterrence-based approaches should act as only one corner-stone of a suite of interventions and public policy initiatives designed to improve road safety, deterrence-based approaches have nonetheless consistently proven to be a valuable resource to improve road safety. Dr Al-Azri and Dr Al-Maniri reinforce their assertion about the limited utility of deterrence by citing drink driving research, and the issue of drink driving is particularly relevant within the current context given that the problem of driving after drinking has historically been addressed through deterrence-based approaches. While the effectiveness of deterrence-based approaches to reduce drink driving will always be dependent upon a range of situational and contextual factors (including police enforcement practices, cultural norms, etc), the utilisation of this approach has proven particularly effective within Queensland, Australia. For example, a relatively recent comprehensive review of Random Breath Testing in Queensland demonstrated that this initiative not only had a deterrent impact upon self-reported intentions to drink and drive, but was also found to have significantly reduced alcohol-related fatalities in the state. However, the authors agree that deterrence-based approaches can be particularly transient and thus require constant “topping up” not least through sustained public reinforcement, which was clearly articulated in the seminal work by Homel.

Information extraction from web services : a comparison of Tokenisation algorithms

Most web service discovery systems use keyword-based search algorithms and, although partially successful, sometimes fail to satisfy some users information needs. This has given rise to several semantics-based approaches that look to go beyond simple attribute matching and try to capture the semantics of services. However, the results reported in the literature vary and in many cases are worse than the results obtained by keyword-based systems. We believe the accuracy of the mechanisms used to extract tokens from the non-natural language sections of WSDL files directly affects the performance of these techniques, because some of them can be more sensitive to noise. In this paper three existing tokenization algorithms are evaluated and a new algorithm that outperforms all the algorithms found in the literature is introduced.

Infinite-horizon policy-gradient estimation

Gradient-based approaches to direct policy search in reinforcement learning have received much recent attention as a means to solve problems of partial observability and to avoid some of the problems associated with policy degradation in value-function methods. In this paper we introduce GPOMDP, a simulation-based algorithm for generating a biased estimate of the gradient of the average reward in Partially Observable Markov Decision Processes (POMDPs) controlled by parameterized stochastic policies. A similar algorithm was proposed by Kimura, Yamamura, and Kobayashi (1995). The algorithm's chief advantages are that it requires storage of only twice the number of policy parameters, uses one free parameter β ∈ [0,1) (which has a natural interpretation in terms of bias-variance trade-off), and requires no knowledge of the underlying state. We prove convergence of GPOMDP, and show how the correct choice of the parameter β is related to the mixing time of the controlled POMDP. We briefly describe extensions of GPOMDP to controlled Markov chains, continuous state, observation and control spaces, multiple-agents, higher-order derivatives, and a version for training stochastic policies with internal states. In a companion paper (Baxter, Bartlett, & Weaver, 2001) we show how the gradient estimates generated by GPOMDP can be used in both a traditional stochastic gradient algorithm and a conjugate-gradient procedure to find local optima of the average reward. ©2001 AI Access Foundation and Morgan Kaufmann Publishers. All rights reserved.

Spatially stratified sampling using auxiliary information for geostatistical mapping

This paper presents a method of spatial sampling based on stratification by Local Moran’s I i calculated using auxiliary information. The sampling technique is compared to other design-based approaches including simple random sampling, systematic sampling on a regular grid, conditional Latin Hypercube sampling and stratified sampling based on auxiliary information, and is illustrated using two different spatial data sets. Each of the samples for the two data sets is interpolated using regression kriging to form a geostatistical map for their respective areas. The proposed technique is shown to be competitive in reproducing specific areas of interest with high accuracy.

Having a yarn about smoking : using action research to develop a 'no smoking' policy within an Aboriginal health organisation

Objectives: This article reports on a culturally appropriate process of development of a smoke-free workplace policy within the peak Aboriginal Controlled Community Health Organisation in Victoria, Australia. Smoking is acknowledged as being responsible for at least 20% of all deaths in Aboriginal communities in Australia, and many Aboriginal health workers smoke. Methods: The smoke-free workplace policy was developed using the iterative, discursive and experience-based methodology of Participatory Action Research, combined with the culturally embedded concept of ‘having a yarn’. Results: Staff members initially identified smoking as a topic to be avoided within workplace discussions. This was due, in part, to grief (everyone had suffered a smoking related bereavement). Further, there was anxiety that discussing smoking would result in culturally difficult conflict. The use of yarning opened up a safe space for discussion and debate,enabling development of a policy that was accepted across the organisation. Conclusions: Within Aboriginal organisations, it is not sufficient to focus on the outcomes of policy development. Rather, due attention must be paid to the process employed in development of policy, particularly when that policy is directly related to an emotionally and communally weighted topic such as smoking.

Application of Mesenchymal Stem Cells for repair and regeneration of cartilage and bone

Australian efforts to provide orthopaedic surgeons with living, load-bearing scaffolds suitable for current joint (knee and hip) replacement surgery, non-union fracture repair, and miniscal and growth plate cartilage regeneration are being lead by teams at the Institute for Medical and Veterinary Science and Women's and Children's Hospital in Adelaide; the Peter MacCallum and St Vincent's Medical Research Institutes in Melbourne; and the Mater Medical Research Institute and new Institute for Health and Biomedical Innovation at QUT, Brisbane. In each case multidisciplinary teams are attempting to develop autologous living tissue constructs, utilising mesenchymal stem cells (MSC), with the intention of effecting seamless repair and regeneration of skeletal trauma and defects. In this article we will briefly review current knowledge of the phenotypic properties of MSC and discuss the potential therapeutic applications of these cells as exemplified by their use in cartilage repair and tissue engineering based approaches to the treatment of skeletal defects.

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.

3D ellipsoid fitting for multi-view gait recognition

Gait recognition approaches continue to struggle with challenges including view-invariance, low-resolution data, robustness to unconstrained environments, and fluctuating gait patterns due to subjects carrying goods or wearing different clothes. Although computationally expensive, model based techniques offer promise over appearance based techniques for these challenges as they gather gait features and interpret gait dynamics in skeleton form. In this paper, we propose a fast 3D ellipsoidal-based gait recognition algorithm using a 3D voxel model derived from multi-view silhouette images. This approach directly solves the limitations of view dependency and self-occlusion in existing ellipse fitting model-based approaches. Voxel models are segmented into four components (left and right legs, above and below the knee), and ellipsoids are fitted to each region using eigenvalue decomposition. Features derived from the ellipsoid parameters are modeled using a Fourier representation to retain the temporal dynamic pattern for classification. We demonstrate the proposed approach using the CMU MoBo database and show that an improvement of 15-20% can be achieved over a 2D ellipse fitting baseline.

Gait energy volumes and frontal gait recognition using depth images

Gait energy images (GEIs) and its variants form the basis of many recent appearance-based gait recognition systems. The GEI combines good recognition performance with a simple implementation, though it suffers problems inherent to appearance-based approaches, such as being highly view dependent. In this paper, we extend the concept of the GEI to 3D, to create what we call the gait energy volume, or GEV. A basic GEV implementation is tested on the CMU MoBo database, showing improvements over both the GEI baseline and a fused multi-view GEI approach. We also demonstrate the efficacy of this approach on partial volume reconstructions created from frontal depth images, which can be more practically acquired, for example, in biometric portals implemented with stereo cameras, or other depth acquisition systems. Experiments on frontal depth images are evaluated on an in-house developed database captured using the Microsoft Kinect, and demonstrate the validity of the proposed approach.