Cooperation across multiple healthcare clinics on the cloud

Many healthcare units are creating cloud strategies and mi- gration plans in order to exploit the benefits of cloud based computing. This generally involves collaboration between healthcare specialists and data management researchers to create a new wave of healthcare tech- nology and services. However, in many cases the technology pioneers are ahead of government policies as cloud based storage of healthcare data is not yet permissible in many jurisdictions. One approach is to store anonymised data on the cloud and maintain all identifying data locally. At login time, a simple protocol can be developed to allow clinicians to combine both sets of data for selected patients for the current session. However, the management of o↵-cloud identifying data requires a frame- work to ensure sharing and availability of data within clinics and the ability to share data between users in remote clinics. In this paper, we introduce the PACE healthcare architecture which uses a combination of Cloud and Peer-to-Peer technologies to model healthcare units or clin- ics where o↵-cloud data is accessible to all, and where exchange of data between remote healthcare units is also facilitated

FibLSS: A scalable label storage scheme for dynamic XML updates

Dynamic labeling schemes for XML updates have been the focus of significant research activity in recent years. However the label storage schemes underpinning the dynamic labeling schemes have not received as much attention. Label storage schemes specify how labels are physically encoded and stored on disk. The size of the labels and their logical representation directly influence the computational costs of processing the labels and can limit the functionality provided by the dynamic labeling scheme to an XML update service. This has significant practical implications when merging XML repositories such as clinical studies. In this paper, we provide an overview of the existing label storage schemes. We present a novel label storage scheme based on the Fibonacci sequence that can completely avoid relabeling existing nodes under dynamic insertions. Theoretical analysis and experimental results confirm the scalability and performance of the Fibonacci label storage scheme in comparison to existing approaches

A framework for selecting deep learning hyper-parameters

Recent research has found that deep learning architectures show significant improvements over traditional shallow algorithms when mining high dimensional datasets. When the choice of algorithm employed, hyper-parameter setting, number of hidden layers and nodes within a layer are combined, the identification of an optimal configuration can be a lengthy process. Our work provides a framework for building deep learning architectures via a stepwise approach, together with an evaluation methodology to quickly identify poorly performing architectural configurations. Using a dataset with high dimensionality, we illustrate how different architectures perform and how one algorithm configuration can provide input for fine-tuning more complex models

Distribution, population structure, growth and reproduction of the razor clam Ensis arcuatus (Jeffreys) (Solenaceae) in coastal waters of western Ireland

Samples of razor clams, Ensis arcuatus, the species which makes up the majority of landings from the west coast of Ireland, were collected by commercial fishery methods, in association with the dredge fishery and by scuba diving, from three locations off the coast of Co Galway. E. arcuatus occupies coarse sand (of maerl and shell fragments) and rarely co-exists with the other common species of the region, E. siliqua. E. arcuatus were aged, an age-length-key devised for them, and growth parameters (Linf, k and t0) were calculated. Their maturation state was established by histological examination. Evidence suggests that Ensis arcuatus is mainly a spring spawner, although some spawning appears to take place in most months, with a spatfall in June/July. Maturation commences in its third year. Asymptotic length is achieved at 10 years, approximately, and there was little variability in growth among the three sampling areas or between the sexes. In a small bed of razor clams in Cill Chiarain Bay, Co Galway, there would appear to have been a spatfall in most, if not all, of the past 15 years. The quantitative distribution of E. arcuatus in a single bay within the boundaries of Comharchuman Sliogeisc Chonamara Teo, Co Galway, was estimated by divers salting quadrats of 0.33 m2. The razor clam community is divided into a generally distributed fraction occurring at low density (described as the non-bed) and at a relatively higher density (described as the clam bed). The bed was situated in the lee of reefs, which is usually the case for this species along the Atlantic seaboard. More than 90% of the biomass was above the E.U. minimum size limit.Funder: Marine Institut

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architecture for interoperability among healthcare systems D. Landers, M. Buckley an