Location and scale mixtures of Gaussians with flexible tail behaviour: Properties, inference and application to multivariate clustering

The family of location and scale mixtures of Gaussians has the ability to generate a number of flexible distributional forms. The family nests as particular cases several important asymmetric distributions like the Generalized Hyperbolic distribution. The Generalized Hyperbolic distribution in turn nests many other well known distributions such as the Normal Inverse Gaussian. In a multivariate setting, an extension of the standard location and scale mixture concept is proposed into a so called multiple scaled framework which has the advantage of allowing different tail and skewness behaviours in each dimension with arbitrary correlation between dimensions. Estimation of the parameters is provided via an EM algorithm and extended to cover the case of mixtures of such multiple scaled distributions for application to clustering. Assessments on simulated and real data confirm the gain in degrees of freedom and flexibility in modelling data of varying tail behaviour and directional shape.

Samoa’s education policy: Negotiating a hybrid space for values

This paper analyses the education policy of Samoa to examine the values that are presented within as relevant to the education system. Drawing on the theory of postcolonialism and globalization, we illustrate how the global and local interact within the education policy to create a hybrid, heterogeneous mix of values and, while the policy acknowledges the significance of Samoan values, it is principally directed towards universal values being incorporated into the education system. We undertake a critical policy analysis to illustrate how the hybrid set of values are indicative of a neo-colonial discourse and argue that universal values are required, however, these need to be equally matched with local Samoan values for the education policy to be highly relevant, authentic and applicable to the Samoan education context.

Effective earth and space science analogies

There are several good reasons why Earth and Space Science should be a part of any science curriculum. Nearly everything we do each day is connected in some way to the Earth: to its land, oceans, atmosphere, plants and animals. By 2025, eight billion people will live on Earth. If we are to continue extracting resources to maintain a high quality of life, then it is important that our children are scientifically literate in a way that allows them to exploit the Earth’s resources in a sustainable way. People who understand how earth systems work can make informed decisions and may be able to help resolve issues surrounding clean water, urban planning and development, global climate change and the use and management of natural resources.

Achieving medium-high density in low scale development: The Queensland experience in innovative ‘fine-grained’ urbanism

Worldwide population growth and economic agglomeration is driving increasing urban density within larger metropolitan conurbations. Population growth and housing diversity and affordability issues in Queensland have seen an increasing demand for more diverse and higher density development. Under Queensland’s flexible planning regulatory provisions, a level of ‘medium’ to ‘high density’ is being achieved by a focus on fine-grained urban design, low scale development, lot diversity, and delivery of single dwelling products. This for Queensland (and Australia) has been an unprecedented innovation in urban and dwelling design. Dwellings are being delivered on lots with zero regulatory minimum sizes providing for a range of new products including ‘apartments on the ground’. This paper reviews recent and nascent demonstrations of EDQ’s fine-grained urbanism principles, identifiable with historical ‘vernacular suburbanism’. The paper introduces and defines a concept of a ‘natural density’ linking human scale built form with walkability. The paper challenges the notion that (sub)urban development, outside major city centres, needs to be of a higher scale to achieve density and diversity aspirations. ‘Natural density’ provides a means of achieving the increasing demand for more diverse and higher density development.

Find my office: Navigating real space from semantic descriptions

This paper shows that by using only symbolic language phrases, a mobile robot can purposefully navigate to specified rooms in previously unexplored environments. The robot intelligently organises a symbolic language description of the unseen environment and “imagines” a representative map, called the abstract map. The abstract map is an internal representation of the topological structure and spatial layout of symbolically defined locations. To perform goal-directed exploration, the abstract map creates a high-level semantic plan to reason about spaces beyond the robot’s known world. While completing the plan, the robot uses the metric guidance provided by a spatial layout, and grounded observations of door labels, to efficiently guide its navigation. The system is shown to complete exploration in unexplored spaces by travelling only 13.3% further than the optimal path.

R1SVM: A randomised nonlinear approach to large-scale anomaly detection

The problem of unsupervised anomaly detection arises in a wide variety of practical applications. While one-class support vector machines have demonstrated their effectiveness as an anomaly detection technique, their ability to model large datasets is limited due to their memory and time complexity for training. To address this issue for supervised learning of kernel machines, there has been growing interest in random projection methods as an alternative to the computationally expensive problems of kernel matrix construction and sup-port vector optimisation. In this paper we leverage the theory of nonlinear random projections and propose the Randomised One-class SVM (R1SVM), which is an efficient and scalable anomaly detection technique that can be trained on large-scale datasets. Our empirical analysis on several real-life and synthetic datasets shows that our randomised 1SVM algorithm achieves comparable or better accuracy to deep auto encoder and traditional kernelised approaches for anomaly detection, while being approximately 100 times faster in training and testing.

Measuring the expressed emotion in Chinese family caregivers of persons with dementia: Validation of a Chinese version of the Family Attitude Scale

- Background Expressed emotion (EE) captures the affective quality of the relationship between family caregivers and their care recipients and is known to increase the risk of poor health outcomes for caregiving dyads. Little is known about expressed emotion in the context of caregiving for persons with dementia, especially in non-Western cultures. The Family Attitude Scale (FAS) is a psychometrically sound self-reporting measure for EE. Its use in the examination of caregiving for patients with dementia has not yet been explored. - Objectives This study was performed to examine the psychometric properties of the Chinese version of the FAS (FAS-C) in Chinese caregivers of relatives with dementia, and its validity in predicting severe depressive symptoms among the caregivers. - Methods The FAS was translated into Chinese using Brislin's model. Two expert panels evaluated the semantic equivalence and content validity of this Chinese version (FAS-C), respectively. A total of 123 Chinese primary caregivers of relatives with dementia were recruited from three elderly community care centers in Hong Kong. The FAS-C was administered with the Chinese versions of the 5-item Mental Health Inventory (MHI-5), the Zarit Burden Interview (ZBI) and the Revised Memory and Behavioral Problem Checklist (RMBPC). - Results The FAS-C had excellent semantic equivalence with the original version and a content validity index of 0.92. Exploratory factor analysis identified a three-factor structure for the FAS-C (hostile acts, criticism and distancing). Cronbach's alpha of the FAS-C was 0.92. Pearson's correlation indicated that there were significant associations between a higher score on the FAS-C and greater caregiver burden (r = 0.66, p < 0.001), poorer mental health of the caregivers (r = −0.65, p < 0.001) and a higher level of dementia-related symptoms (frequency of symptoms: r = 0.45, p < 0.001; symptom disturbance: r = 0.51, p < 0.001), which serves to suggest its construct validity. For detecting severe depressive symptoms of the family caregivers, the receiving operating characteristics (ROC) curve had an area under curve of 0.78 (95% confidence interval (CI) = 0.69–0.87, p < 0.0001). The optimal cut-off score was >47 with a sensitivity of 0.720 (95% CI = 0.506–0.879) and specificity of 0.742 (95% CI = 0.643–0.826). - Conclusions The FAS-C is a reliable and valid measure to assess the affective quality of the relationship between Chinese caregivers and their relatives with dementia. It also has acceptable predictability in identifying family caregivers with severe depressive symptoms.