30,926 research outputs found

    Need to Know Review Number two: What Local Government Needs to Know about Public Health

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    This review of existing research on local government and public health focuses on the leadership role of local government in developing local public health systems that are capable of addressing the wider determinants of health

    A neural network version of the measure correlate predict algorithm for estimating wind energy yield.

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    A neural network version of the measure correlate predict algorithm for estimating wind energy yiel

    Montane lakes (lagoons) of the New England Tablelands Bioregion

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    The vegetation of montane lagoons of the New England Tablelands Bioregion, New South Wales is examined using flexible UPGMA analysis of frequency scores on all vascular plant taxa, charophytes and one liverworts. Seven communities are described: 1. Hydrocotyle tripartita – Isotoma fluviatilis – Ranunculus inundatus – Lilaeopsis polyantha herbfield; 2. Eleocharis sphacelata – Potamogeton tricarinatus sedgeland; 3. Eleocharis sphacelata – Utricularia australis – Isolepis fluitans, herbfield; 4. Utricularia australis – Nitella sonderi herbfield; 5. Eleocharis sphacelata – Utricularia australis – Ricciocarpus natans sedgeland; 6. Carex gaudichaudiana – Holcus lanatus – Stellaria angustifolia sedgeland; 7. Cyperus sphaeroides – Eleocharis gracilis – Schoenus apogon – Carex gaudichaudiana sedgeland. 58 lagoons were located and identified, only 28% of which are considered to be intact and in good condition. Two threatened species (Aldovandra vesiculosa and Arthaxon hispidus) and three RoTAP-listed taxa were encountered during the survey

    The Distribution of Mixing Times in Markov Chains

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    The distribution of the "mixing time" or the "time to stationarity" in a discrete time irreducible Markov chain, starting in state i, can be defined as the number of trials to reach a state sampled from the stationary distribution of the Markov chain. Expressions for the probability generating function, and hence the probability distribution of the mixing time starting in state i are derived and special cases explored. This extends the results of the author regarding the expected time to mixing [J.J. Hunter, Mixing times with applications to perturbed Markov chains, Linear Algebra Appl. 417 (2006) 108-123], and the variance of the times to mixing, [J.J. Hunter, Variances of first passage times in a Markov chain with applications to mixing times, Linear Algebra Appl. 429 (2008) 1135-1162]. Some new results for the distribution of recurrence and first passage times in three-state Markov chain are also presented.Comment: 24 page

    Towards Large-scale Inconsistency Measurement

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    We investigate the problem of inconsistency measurement on large knowledge bases by considering stream-based inconsistency measurement, i.e., we investigate inconsistency measures that cannot consider a knowledge base as a whole but process it within a stream. For that, we present, first, a novel inconsistency measure that is apt to be applied to the streaming case and, second, stream-based approximations for the new and some existing inconsistency measures. We conduct an extensive empirical analysis on the behavior of these inconsistency measures on large knowledge bases, in terms of runtime, accuracy, and scalability. We conclude that for two of these measures, the approximation of the new inconsistency measure and an approximation of the contension inconsistency measure, large-scale inconsistency measurement is feasible.Comment: International Workshop on Reactive Concepts in Knowledge Representation (ReactKnow 2014), co-located with the 21st European Conference on Artificial Intelligence (ECAI 2014). Proceedings of the International Workshop on Reactive Concepts in Knowledge Representation (ReactKnow 2014), pages 63-70, technical report, ISSN 1430-3701, Leipzig University, 2014. http://nbn-resolving.de/urn:nbn:de:bsz:15-qucosa-15056

    Financial signal processing: a self calibrating model

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    Previous work on multifactor term structure models has proposed that the short rate process is a function of some unobserved diffusion process. We consider a model in which the short rate process is a function of a Markov chain which represents the 'state of the world'. This enables us to obtain explicit expressions for the prices of zero-coupon bonds and other securities. Discretizing our model allows the use of signal processing techniques from Hidden Markov Models. This means we can estimate not only the unobserved Markov chain but also the parameters of the model, so the model is self-calibrating. The estimation procedure is tested on a selection of U.S. Treasury bills and bonds.Bonds

    A comparison of Olpidium isolates from a range of host plants using internal transcribed spacer sequence analysis and host range studies

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    Olpidium brassicae is a ubiquitous obligate root-infecting fungal pathogen. It is an important vector of a wide range of plant viruses. Olpidium isolates that infected brassica plants did not infect lettuce plants and vice-versa. Host range tests, PCR amplification and sequencing of the internal transcribed spacer (ITS) and 5.8S regions of 25 Olpidium isolates from brassica, carrot, cucumber and lettuce originating from four continents revealed differences between isolates. Based on their ability to infect lettuce and brassicas and the differences between their ITS1, 5.8S and ITS2 regions they could be separated into a number of distinct groups. Comparisons with other published sequences revealed two distinct genetic groups of brassica-infecting isolates, two distinct groups of lettuce-infecting isolates, one of which contained a carrot-infecting isolate and a distinct group comprising a cucumber-infecting isolate and a melon-infecting isolate. The possibility of the isolates belonging to three distinct species is discussed
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