785 resultados para Task Clustering
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The Minister for Health and Children established the Task Force on Sudden Cardiac Death (SCD) in the Autumn of 2004, with the following terms of reference:1) Define SCD and describe its incidence and underlying causes in Ireland.2) Advise on the detection and assessment of those at high risk of SCD and their relatives.3) Advise on the systematic assessment of those engaged in sports and exercise for risk of SCD.4) Advise on maximizing access to basic life support (BLS) and automated external defibrillators (AEDs) and on:- appropriate levels of training in BLS and use of AEDs, and on the maintenance of that training- priority individuals and priority groups for such training- geographic areas and functional locations of greatest need- best practice models of first responder scheme and public access defibrillation, and- integration of such training services.5) Advise on the establishment and maintenance of surveillance systems, including a registry of SCD and information systems to monitor risk assessment, and training and equipment programmes.6) Advise and make recommendations on other priority issues relevant to SCD in Ireland.7) Outline a plan for implementation and advise on monitoring the implementation of recommendations made in the Task Force’s report. In undertaking its work the Task Force was mindful of national health policy, relevant national strategies and of the recently reformed structures for health service delivery in Ireland. Read the Report (PDF, 1.66mb)
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The study of the Schistosoma mansoni genome, one of the etiologic agents of human schistosomiasis, is essential for a better understanding of the biology and development of this parasite. In order to get an overview of all S. mansoni catalogued gene sequences, we performed a clustering analysis of the parasite mRNA sequences available in public databases. This was made using softwares PHRAP and CAP3. The consensus sequences, generated after the alignment of cluster constituent sequences, allowed the identification by database homology searches of the most expressed genes in the worm. We analyzed these genes and looked for a correlation between their high expression and parasite metabolism and biology. We observed that the majority of these genes is related to the maintenance of basic cell functions, encoding genes whose products are related to the cytoskeleton, intracellular transport and energy metabolism. Evidences are presented here that genes for aerobic energy metabolism are expressed in all the developmental stages analyzed. Some of the most expressed genes could not be identified by homology searches and may have some specific functions in the parasite.
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Report of Inter-sectoral Group on the Implementation of the Recommendations of the National Task Force on Obesity Click here to download PDF 1.25mb
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Division of labour is one of the most prominent features of social insects. The efficient allocation of individuals to different tasks requires dynamic adjustment in response to environmental perturbations. Theoretical models suggest that the colony-level flexibility in responding to external changes and internal perturbation may depend on the within-colony genetic diversity, which is affected by the number of breeding individuals. However, these models have not considered the genetic architecture underlying the propensity of workers to perform the various tasks. Here, we investigated how both within-colony genetic variability (stemming from variation in the number of matings by queens) and the number of genes influencing the stimulus (threshold) for a given task at which workers begin to perform that task jointly influence task allocation efficiency. We used a numerical agent-based model to investigate the situation where workers had to perform either a regulatory task or a foraging task. One hundred generations of artificial selection in populations consisting of 500 colonies revealed that an increased number of matings always improved colony performance, whatever the number of loci encoding the thresholds of the regulatory and foraging tasks. However, the beneficial effect of additional matings was particularly important when the genetic architecture of queens comprised one or a few genes for the foraging task's threshold. By contrast, a higher number of genes encoding the foraging task reduced colony performance with the detrimental effect being stronger when queens had mated with several males. Finally, the number of genes encoding the threshold for the regulatory task only had a minor effect on colony performance. Overall, our numerical experiments support the importance of mating frequency on efficiency of division of labour and also reveal complex interactions between the number of matings and genetic architecture.
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Distribution of socio-economic features in urban space is an important source of information for land and transportation planning. The metropolization phenomenon has changed the distribution of types of professions in space and has given birth to different spatial patterns that the urban planner must know in order to plan a sustainable city. Such distributions can be discovered by statistical and learning algorithms through different methods. In this paper, an unsupervised classification method and a cluster detection method are discussed and applied to analyze the socio-economic structure of Switzerland. The unsupervised classification method, based on Ward's classification and self-organized maps, is used to classify the municipalities of the country and allows to reduce a highly-dimensional input information to interpret the socio-economic landscape. The cluster detection method, the spatial scan statistics, is used in a more specific manner in order to detect hot spots of certain types of service activities. The method is applied to the distribution services in the agglomeration of Lausanne. Results show the emergence of new centralities and can be analyzed in both transportation and social terms.
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This handbook has been developed within the context of the institutional structures recommended under the National Drugs Strategy 2009-2016 and within the overall framework of the National Social Inclusion Plan 2007-2016. It sets out the role of the Drugs Task Forces within the national and local framework required to address the existing and emerging problems associated with drug use for individuals, families and communities in the context of the long term development of the work of the Drugs Task Forces.This resource was contributed by The National Documentation Centre on Drug Use.
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The North Dublin City and County Regional Drugs Task Force invites applications for this once-off funding which will be provided through four pillars by way of a grant up to €3,000 for innovative initiatives: • Prevention, Education & Awareness – to develop programmes and supports in the community which offer information and education in order to generate awareness. • Treatment & Rehabilitation – to develop additional short-term supports for those undertaking treatment for drug misuse or innovative rehabilitative supports. • Research – to undertake local research into drug misuse in North Dublin within the RDTF area. • Supply Reduction – to reduce access to all drugs, in particular those that cause most harm, among young people in neighbourhoods where misuse is most prevalent. Terms and conditions apply. To request an application pack or for more information contact 01 813 1786 orThis resource was contributed by The National Documentation Centre on Drug Use.
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Ireland has positioned itself to take advantage of technological change by encouraging the inward investment of high-tech industries and by providing a highly-educated workforce to sustain and enlarge them. Employment of science, engineering and technology graduates at all levels has been a hallmark of the modern Irish economy, as the educational sector responded to the mix of skills demanded by industry. An outstanding record of graduate output has contributed to the phenomenal growth in Irish-based technology. In an era of rapid technological change, the goal of "scientific literacy for all" has become a primary objective of a general education. Science is one of three literacy domains, along with reading and mathematics, that is included in measures of educational achievement by the OECD.
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In image segmentation, clustering algorithms are very popular because they are intuitive and, some of them, easy to implement. For instance, the k-means is one of the most used in the literature, and many authors successfully compare their new proposal with the results achieved by the k-means. However, it is well known that clustering image segmentation has many problems. For instance, the number of regions of the image has to be known a priori, as well as different initial seed placement (initial clusters) could produce different segmentation results. Most of these algorithms could be slightly improved by considering the coordinates of the image as features in the clustering process (to take spatial region information into account). In this paper we propose a significant improvement of clustering algorithms for image segmentation. The method is qualitatively and quantitative evaluated over a set of synthetic and real images, and compared with classical clustering approaches. Results demonstrate the validity of this new approach
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Our purpose is to provide a set-theoretical frame to clustering fuzzy relational data basically based on cardinality of the fuzzy subsets that represent objects and their complementaries, without applying any crisp property. From this perspective we define a family of fuzzy similarity indexes which includes a set of fuzzy indexes introduced by Tolias et al, and we analyze under which conditions it is defined a fuzzy proximity relation. Following an original idea due to S. Miyamoto we evaluate the similarity between objects and features by means the same mathematical procedure. Joining these concepts and methods we establish an algorithm to clustering fuzzy relational data. Finally, we present an example to make clear all the process
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Estudi, disseny i implementació de diferents tècniques d’agrupament defibres (clustering) per tal d’integrar a la plataforma DTIWeb diferentsalgorismes de clustering i tècniques de visualització de clústers de fibres de forma quefaciliti la interpretació de dades de DTI als especialistes