A distributed architecture for the monitoring and analysis of time series data

It is estimated that the quantity of digital data being transferred, processed or stored at any one time currently stands at 4.4 zettabytes (4.4 × 2 70 bytes) and this figure is expected to have grown by a factor of 10 to 44 zettabytes by 2020. Exploiting this data is, and will remain, a significant challenge. At present there is the capacity to store 33% of digital data in existence at any one time; by 2020 this capacity is expected to fall to 15%. These statistics suggest that, in the era of Big Data, the identification of important, exploitable data will need to be done in a timely manner. Systems for the monitoring and analysis of data, e.g. stock markets, smart grids and sensor networks, can be made up of massive numbers of individual components. These components can be geographically distributed yet may interact with one another via continuous data streams, which in turn may affect the state of the sender or receiver. This introduces a dynamic causality, which further complicates the overall system by introducing a temporal constraint that is difficult to accommodate. Practical approaches to realising the system described above have led to a multiplicity of analysis techniques, each of which concentrates on specific characteristics of the system being analysed and treats these characteristics as the dominant component affecting the results being sought. The multiplicity of analysis techniques introduces another layer of heterogeneity, that is heterogeneity of approach, partitioning the field to the extent that results from one domain are difficult to exploit in another. The question is asked can a generic solution for the monitoring and analysis of data that: accommodates temporal constraints; bridges the gap between expert knowledge and raw data; and enables data to be effectively interpreted and exploited in a transparent manner, be identified? The approach proposed in this dissertation acquires, analyses and processes data in a manner that is free of the constraints of any particular analysis technique, while at the same time facilitating these techniques where appropriate. Constraints are applied by defining a workflow based on the production, interpretation and consumption of data. This supports the application of different analysis techniques on the same raw data without the danger of incorporating hidden bias that may exist. To illustrate and to realise this approach a software platform has been created that allows for the transparent analysis of data, combining analysis techniques with a maintainable record of provenance so that independent third party analysis can be applied to verify any derived conclusions. In order to demonstrate these concepts, a complex real world example involving the near real-time capturing and analysis of neurophysiological data from a neonatal intensive care unit (NICU) was chosen. A system was engineered to gather raw data, analyse that data using different analysis techniques, uncover information, incorporate that information into the system and curate the evolution of the discovered knowledge. The application domain was chosen for three reasons: firstly because it is complex and no comprehensive solution exists; secondly, it requires tight interaction with domain experts, thus requiring the handling of subjective knowledge and inference; and thirdly, given the dearth of neurophysiologists, there is a real world need to provide a solution for this domain

End-of-life care: identifying an appropriate legal framework for specialist palliative care in Ireland

This thesis argues that the legal framework in Ireland for specialist palliative care is inadequate and consequently a more appropriate legal framework must be identified. This research is guided by three central research questions. The first central research question examines the legitimacy of the distinction between specialist palliative care and euthanasia. The second central research question asks what legal framework currently exists in Ireland for specialist palliative care. The third central research question examines an alternative legal framework for specialist palliative. This thesis is composed of seven chapters. The first Chapter is an introduction to the thesis and defines the terminology and the central research questions. Chapter Two explores the development and practice of palliative care in Ireland. Chapter Three examines the distinction in criminal law between specialist palliative care practices and euthanasia. Chapter Four examines the human rights framework for specialist palliative care. Chapter Five critiques the regulatory framework in Ireland for specialist palliative care. Having gained a thorough understanding of palliative care and the related legal framework, this thesis then engages in comparative analysis of the Netherlands which is used as a source of ideas for reform in Ireland. Chapter Seven is the concluding chapter and, in it, the main findings of this thesis are summarised. The main findings being that: the distinction between specialist palliative care and euthanasia is not sufficiently supported by justifications such as a double effect or the acts and omissions distinction, there is no clear decision-making framework in Ireland for specialist palliative care, and the current legal framework lacks clarity and does not promote consistency between providers of specialist palliative care. This Chapter also proposes that detailed professional standards and guidelines are likely to be the most appropriate way to effect individual and institutional change in the provision of specialist palliative care.

Practical, appropriate, empirically-validated guidelines for designing educational games

There has recently been a great deal of interest in the potential of computer games to function as innovative educational tools. However, there is very little evidence of games fulfilling that potential. Indeed, the process of merging the disparate goals of education and games design appears problematic, and there are currently no practical guidelines for how to do so in a coherent manner. In this paper, we describe the successful, empirically validated teaching methods developed by behavioural psychologists and point out how they are uniquely suited to take advantage of the benefits that games offer to education. We conclude by proposing some practical steps for designing educational games, based on the techniques of Applied Behaviour Analysis. It is intended that this paper can both focus educational games designers on the features of games that are genuinely useful for education, and also introduce a successful form of teaching that this audience may not yet be familiar with.