A coarse-grained parallel genetic algorithm employing cluster analysis for multi-modal numerical optimisation

This paper describes a technique for improving the performance of parallel genetic algorithms on multi-modal numerical optimisation problems. It employs a cluster analysis algorithm to identify regions of the search space in which more than one sub-population is sampling. Overlapping clusters are merged in one sub-population whilst a simple derating function is applied to samples in all other sub-populations to discourage them from further sampling in that region. This approach leads to a better distribution of the search effort across multiple subpopulations and helps to prevent premature convergence. On the test problems used, significant performance improvements over the traditional island model implementation are realised.

Osteo-cise : Strong bones for life': protocol for a community-based randomised controlled trial of a multi-modal exercise and osteoporosis education program for older adults at risk of falls and fractures

Background : Osteoporosis affects over 220 million people worldwide, and currently there is no 'cure' for the disease. Thus, there is a need to develop evidence-based, safe and acceptable prevention strategies at the population level that target multiple risk factors for fragility fractures to reduce the health and economic burden of the condition.

Methods : The 'Osteo-cise: Strong Bones for Life' study will investigate the effectiveness and feasibility of a multi-component targeted exercise, osteoporosis education/awareness and behavioural change program for improving bone health and muscle function, and reducing falls risk in community-dwelling older adults at an increased risk of fracture. Men and women aged 60 years or above will participate in an 18-month randomised controlled trial comprising a 12-month structured and supervised community-based program and a 6-month 'research to practise' translational phase. Participants will be randomly assigned to either the 'Osteo-cise' intervention or a self-management control group. The intervention will comprise a multi-modal exercise program incorporating high velocity progressive resistance training, moderate impact weight-bearing exercise and high challenging balance exercises performed three times weekly at local community-based fitness centres. A behavioural change program will be used to enhance exercise adoption and adherence to the program. Community-based osteoporosis education seminars will be conducted to improve participant knowledge and understanding of the risk factors and preventative measures for osteoporosis, falls and fractures. The primary outcomes measures, to be collected at baseline, 6, 12, and 18 months, will include DXA-derived hip and spine bone mineral density measurements and functional muscle power (timed stair-climb test). Secondary outcomes measures include: MRI-assessed distal femur and proximal tibia trabecular bone micro-architecture, lower limb and back maximal muscle strength, balance and function (four square step test, functional reach test, timed up-and-go test and 30-second sit-to-stand), falls incidence and health-related quality of life. Cost-effectiveness will also be assessed.

Discussion : The findings from the Osteo-cise: Strong Bones for Life study will provide new information on the efficacy of a targeted multi-modal community-based exercise program incorporating high velocity resistance training, together with an osteoporosis education and behavioural change program for improving multiple risk factors for falls and fracture in older adults at risk of fragility fracture. Trial Registration: Australian New Zealand Clinical Trials Registry reference ACTRN12609000100291

Multi-modal abnormality detection in video with unknown data segmentation

This paper examines a new problem in large scale stream data: abnormality detection which is localized to a data segmentation process. Unlike traditional abnormality detection methods which typically build one unified model across data stream, we propose that building multiple detection models focused on different coherent sections of the video stream would result in better detection performance. One key challenge is to segment the data into coherent sections as the number of segments is not known in advance and can vary greatly across cameras; and a principled way approach is required. To this end, we first employ the recently proposed infinite HMM and collapsed Gibbs inference to automatically infer data segmentation followed by constructing abnormality detection models which are localized to each segmentation. We demonstrate the superior performance of the proposed framework in a real-world surveillance camera data over 14 days.

Words, oral libraries and environmental responses : an Australian indigenous perspective to climate change adaptation

Climate change adaptation and mitigation continues to be a prevalent discourse in this country and internationally in both the sciences and the arts. While various types and degrees of change are evident, the quantification of these changes including their scope and diversity have challenged conventional sciences. This is demonstrated in their inability to succinctly answer key questions about change including the degree of change and associated patterns and consequences. Most of this discourse is nested in a temporal band comprising the last 100-200 years of data and evidence, and very much informed by Western science perspectives and protocols. Little attempt has been made to engage with Australian Indigenous communities whom possess environmental knowledge of some 10,000-100,000 years albeit embedded in their artistic and oral narrative 'histories'. This paper explores the role and values that Australian Aboriginals, the Indigenous peoples of the Australian content, can offer in shedding new light on this discourse While focusing upon a cross-peri-urban Indigenous investigation, it examines this discourse though the lens of their words, terms, sentences as a vehicle to better understand a longitudinal perspective about climate change adaptation pertinent to Australia.

In so many words: interviews with writers, scholars and intellectuals

In So Many Words features interviews with eleven of the most influential intellectuals, scholars and writers in the United States. Atherton engages with her subjects, and responds to arguments that the public intellectual is endangered, dead or in decline

Words and things: souvenirs of over-site/over-sight for place-making

This paper addresses the problem of making things in a given place (Qatar), and asks how anticipations and memories of place contribute to practice-based manoeuvres of place-making. Flying across time zones and travelling through sites suggests aspects of place-making that would draw upon both a notion of meteorites coming to earth and an awareness of the sensory consequences of global travelling. What this experience also suggests is an ‘over-sight’ (‘over-site’) in how travellers remember a place for themselves, and how they re-member it for others in the form of souvenirs. Going to a place might often default to an envisioning of pre-emptive or imaginary souvenirs in anticipation of the destination; thinking about what a place might be like is hard to separate from what we think we will eventually take away from it. Thus, the idea to be explored is how we might ‘make in to place’ as much as we ‘make something in-place,’ which perhaps results in ‘making some thing into a place’. Etymologically, souvenir already suggests this in its derivation from Old French: ‘to remember, come to mind.’ How does one ‘come to remembering’ in a place that, like all planetary places, will always be both global and local? Perhaps it depends on how one lands in a place…. Meteoroids remain in orbit around a place: nascent souvenirs always above the horizon, un-made place-makings. Meteors come closer to landing but still, by definition, burn up in the atmospheres of the new place. Meteorites, though, land: they suggest what we mean by the human element of ‘makings in-/to place.’ Travelling from somewhere, to somewhere yet to be fully determined, meteorites (people and/or words and/or senses) reflect the dispersion and compression of sensory (thing-based) and word-based experiences of place. Drawing on the work of Paul Hopper, Paul Carter, Gilles Deleuze and Félix Guattari, Michel Serres, William Desmond and Julia Kristeva, the paper concludes that words evoke a place in which the present might take place, and that the senses evoke a present in which place might take place.

Biomedical time series analysis based on bag-of-words model

This research proposes a number of new methods for biomedical time series classification and clustering based on a novel Bag-of-Words (BoW) representation. It is anticipated that the objective and automatic biomedical time series clustering and classification technologies developed in this work will potentially benefit a wide range of applications, such as biomedical data management, archiving, retrieving, and disease diagnosis and prognosis in the future.