“You could scream the place down”: Five poems on the experience of aged care

This article presents five poems constructed from interviews with older people adjusting to living in residential aged care. They are part of the “Inside Aged Care” project, on-going longitudinal phenomenological research tracking the lived experience of aged care from the perspective of residents, family members and service providers. Poetry, through the process of poetic transcription, provided an engaging, evocative and almost visceral way to help us appreciate what it might be like to be ageing in aged care. To date, despite a growing body of work documenting the importance and impact of research in the form of poetry, applying a literary lens is rare in gerontological research. At a very practical level, therefore, we hope these poems help older people, their families, students and those working in aged care better understand the unique world and perspective of new aged care residents.

Building energy simulation and parallel computing : opportunities and challenges

Increased focus on energy cost savings and carbon footprint reduction efforts improved the visibility of building energy simulation, which became a mandatory requirement of several building rating systems. Despite developments in building energy simulation algorithms and user interfaces, there are some major challenges associated with building energy simulation; an important one is the computational demands and processing time. In this paper, we analyze the opportunities and challenges associated with this topic while executing a set of 275 parametric energy models simultaneously in EnergyPlus using a High Performance Computing (HPC) cluster. Successful parallel computing implementation of building energy simulations will not only improve the time necessary to get the results and enable scenario development for different design considerations, but also might enable Dynamic-Building Information Modeling (BIM) integration and near real-time decision-making. This paper concludes with the discussions on future directions and opportunities associated with building energy modeling simulations.

Learning analytics beyond the LMS : the Connected Learning Analytics toolkit

We present a Connected Learning Analytics (CLA) toolkit, which enables data to be extracted from social media and imported into a Learning Record Store (LRS), as defined by the new xAPI standard. Core to the toolkit is the notion of learner access to their own data. A number of implementational issues are discussed, and an ontology of xAPI verb/object/activity statements as they might be unified across 7 different social media and online environments is introduced. After considering some of the analytics that learners might be interested in discovering about their own processes (the delivery of which is prioritised for the toolkit) we propose a set of learning activities that could be easily implemented, and their data tracked by anyone using the toolkit and a LRS.

In search of Nirvana : why Nirvana : the True Story could never be "true"

In my book Nirvana: The True Story (2006), I undertake an autoethnographical approach to biography, attempting to impart an understanding of my chosen subject - the rock band Nirvana - via discussion of my own experiences. On numerous occasions, I veer off into tangential asides, frequently using extensive footnotes to explain obscure musical references. Personal anecdotes are juxtaposed with "insider" information; at crucial points in the story (notable concerts, the first meeting of singer Kurt Cobain with his future wife Courtney Love, the news of Cobain's suicide), the linear thread of the narrative spills over into a multi-faceted approach, with several different (and sometimes opposing) voices given equal prominence. Despite my firsthand experience of the band, however, Nirvana: The True Story is not considered authoritative, even within its own field. This article considers the reasons why this may be the case.In my book Nirvana: The True Story (2006), I undertake an autoethnographical approach to biography, attempting to impart an understanding of my chosen subject - the rock band Nirvana - via discussion of my own experiences. On numerous occasions, I veer off into tangential asides, frequently using extensive footnotes to explain obscure musical references. Personal anecdotes are juxtaposed with "insider" information; at crucial points in the story (notable concerts, the first meeting of singer Kurt Cobain with his future wife Courtney Love, the news of Cobain's suicide), the linear thread of the narrative spills over into a multi-faceted approach, with several different (and sometimes opposing) voices given equal prominence. Despite my firsthand experience of the band, however, Nirvana: The True Story is not considered authoritative, even within its own field. This article considers the reasons why this may be the case.

In silico biology : making the most of parallel computing

Biological systems are typically complex and adaptive, involving large numbers of entities, or organisms, and many-layered interactions between these. System behaviour evolves over time, and typically benefits from previous experience by retaining memory of previous events. Given the dynamic nature of these phenomena, it is non-trivial to provide a comprehensive description of complex adaptive systems and, in particular, to define the importance and contribution of low-level unsupervised interactions to the overall evolution process. In this chapter, the authors focus on the application of the agent-based paradigm in the context of the immune response to HIV. Explicit implementation of lymph nodes and the associated lymph network, including lymphatic chain structure, is a key objective, and requires parallelisation of the model. Steps taken towards an optimal communication strategy are detailed.

Model refinement through high-performance computing: an agent-based HIV example

Background Recent advances in Immunology highlighted the importance of local properties on the overall progression of HIV infection. In particular, the gastrointestinal tract is seen as a key area during early infection, and the massive cell depletion associated with it may influence subsequent disease progression. This motivated the development of a large-scale agent-based model. Results Lymph nodes are explicitly implemented, and considerations on parallel computing permit large simulations and the inclusion of local features. The results obtained show that GI tract inclusion in the model leads to an accelerated disease progression, during both the early stages and the long-term evolution, compared to a theoretical, uniform model. Conclusions These results confirm the potential of treatment policies currently under investigation, which focus on this region. They also highlight the potential of this modelling framework, incorporating both agent-based and network-based components, in the context of complex systems where scaling-up alone does not result in models providing additional insights.

Complexity and high-end computing in biology and medicine

Biomedical systems involve a large number of entities and intricate interactions between these. Their direct analysis is, therefore, difficult, and it is often necessary to rely on computational models. These models require significant resources and parallel computing solutions. These approaches are particularly suited, given parallel aspects in the nature of biomedical systems. Model hybridisation also permits the integration and simultaneous study of multiple aspects and scales of these systems, thus providing an efficient platform for multidisciplinary research.

From bio-inspired computing to e-Biology

Several algorithms and techniques widely used in Computer Science have been adapted from, or inspired by, known biological phenomena. This is a consequence of the multidisciplinary background of most early computer scientists. The field has now matured, and permits development of tools and collaborative frameworks which play a vital role in advancing current biomedical research. In this paper, we briefly present examples of the former, and elaborate upon two of the latter, applied to immunological modelling and as a new paradigm in gene expression.

High-performance computing for data analytics

One of the main challenges in data analytics is that discovering structures and patterns in complex datasets is a computer-intensive task. Recent advances in high-performance computing provide part of the solution. Multicore systems are now more affordable and more accessible. In this paper, we investigate how this can be used to develop more advanced methods for data analytics. We focus on two specific areas: model-driven analysis and data mining using optimisation techniques.

Performance evaluation of cloud-based parallel computing

As computational models in fields such as medicine and engineering get more refined, resource requirements are increased. In a first instance, these needs have been satisfied using parallel computing and HPC clusters. However, such systems are often costly and lack flexibility. HPC users are therefore tempted to move to elastic HPC using cloud services. One difficulty in making this transition is that HPC and cloud systems are different, and performance may vary. The purpose of this study is to evaluate cloud services as a means to minimise both cost and computation time for large-scale simulations, and to identify which system properties have the most significant impact on performance. Our simulation results show that, while the performance of Virtual CPU (VCPU) is satisfactory, network throughput may lead to difficulties.

Transdisciplinary approaches to urban computing

The research field of urban computing – defined as “the integration of computing, sensing, and actuation technologies into everyday urban settings and lifestyles” – considers the design and use of ubiquitous computing technology in public and shared urban environments. Its impact on cities, buildings, and spaces evokes innumerable kinds of change. Embedded into our everyday lived environments, urban computing technologies have the potential to alter the meaning of physical space, and affect the activities performed in those spaces. This paper starts a multi-themed discussion of various aspects that make up the, at times, messy and certainly transdisciplinary field of urban computing and urban informatics.

Growing food in the city : Design ideations for urban residential gardeners

Urban agriculture refers to the production of food in urban and peri-urban spaces. It can contribute positively to health and food security of a city, while also reducing ‘food miles.’ It takes on many forms, from the large and organised community garden, to the small and discrete backyard or balcony. This study focuses on small-scale food production in the form of residential gardening for home or personal use. We explore opportunities to support people’s engagement in urban agriculture via human-computer interaction design. This research presents the findings and HCI design insights from our study of residential gardeners in Brisbane, Australia. By exploring their understanding of gardening practice with a human-centred design approach, we present six key themes, highlighting opportunities and challenges relating to available time and space; the process of learning and experimentation; and the role of existing online platforms to support gardening practice. Finally we discuss the overarching theme of shared knowledge, and how HCI could improve community engagement and gardening practice.

GPU accelerated algorithms for computing matrix function vector products with applications to exponential integrators and fractional diffusion

The efficient computation of matrix function vector products has become an important area of research in recent times, driven in particular by two important applications: the numerical solution of fractional partial differential equations and the integration of large systems of ordinary differential equations. In this work we consider a problem that combines these two applications, in the form of a numerical solution algorithm for fractional reaction diffusion equations that after spatial discretisation, is advanced in time using the exponential Euler method. We focus on the efficient implementation of the algorithm on Graphics Processing Units (GPU), as we wish to make use of the increased computational power available with this hardware. We compute the matrix function vector products using the contour integration method in [N. Hale, N. Higham, and L. Trefethen. Computing Aα, log(A), and related matrix functions by contour integrals. SIAM J. Numer. Anal., 46(5):2505–2523, 2008]. Multiple levels of preconditioning are applied to reduce the GPU memory footprint and to further accelerate convergence. We also derive an error bound for the convergence of the contour integral method that allows us to pre-determine the appropriate number of quadrature points. Results are presented that demonstrate the effectiveness of the method for large two-dimensional problems, showing a speedup of more than an order of magnitude compared to a CPU-only implementation.