984 resultados para Service Interruption Modelling


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We present the first mathematical model on the transmission dynamics of Schistosoma japonicum. The work extends Barbour's classic model of schistosome transmission. It allows for the mammalian host heterogeneity characteristic of the S. japonicum life cycle, and solves the problem of under-specification of Barbour's model by the use of Chinese data we are collecting on human-bovine transmission in the Poyang Lake area of Jiangxi Province in China. The model predicts that in the lake/marshland areas of the Yangtze River basin: (1) once-early mass chemotherapy of humans is little better than twice-yearly mass chemotherapy in reducing human prevalence. Depending on the heterogeneity of prevalence within the population, targeted treatment of high prevalence groups, with lower overall coverage, can be more effective than mass treatment with higher overall coverage. Treatment confers a short term benefit only, with prevalence rising to endemic levels once chemotherapy programs are stopped (2) depending on the relative contributions of bovines and humans, bovine treatment can benefit humans almost as much as human treatment. Like human treatment, bovine treatment confers a short-term benefit. A combination of human and bovine treatment will dramatically reduce human prevalence and maintains the reduction for a longer period of time than treatment of a single host, although human prevalence rises once treatment ceases; (3) assuming 75% coverage of bovines, a bovine vaccine which acts on worm fecundity must have about 75% efficacy to reduce the reproduction rate below one and ensure mid-term reduction and long-term elimination of the parasite. Such a vaccination program should be accompanied by an initial period of human treatment to instigate a short-term reduction in prevalence, following which the reduction is enhanced by vaccine effects; (4) if the bovine vaccine is only 45% efficacious (the level of current prototype vaccines) it will lower the endemic prevalence, but will not result in elimination. If it is accompanied by an initial period of human treatment and by a 45% improvement in human sanitation or a 30% reduction in contaminated water contact by humans, elimination is then possible. (C) 2002 Elsevier Science B.V. All rights reserved.

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Activated sludge flocculation was modelled using population balances. The model followed the dynamics of activated sludge flocculation providing a good approximation of the change in mean floe size with time. Increasing the average velocity gradient decreased the final floe size. The breakage rate coefficient and collision efficiency also varied with the average velocity gradient. A power law relationship was found for the increase in breakage rate coefficient with increasing average velocity gradient. Further investigation will be conducted to determine the relationship between the collision efficiency and particle size to provide a better approximation of dynamic changes in the floe size distribution during flocculation. (C) 2002 Published by Elsevier Science B.V.

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A technique based on laser light diffraction is shown to be successful in collecting on-line experimental data. Time series of floc size distributions (FSD) under different shear rates (G) and calcium additions were collected. The steady state mass mean diameter decreased with increasing shear rate G and increased when calcium additions exceeded 8 mg/l. A so-called population balance model (PBM) was used to describe the experimental data, This kind of model describes both aggregation and breakage through birth and death terms. A discretised PBM was used since analytical solutions of the integro-partial differential equations are non-existing. Despite the complexity of the model, only 2 parameters need to be estimated: the aggregation rate and the breakage rate. The model seems, however, to lack flexibility. Also, the description of the floc size distribution (FSD) in time is not accurate.

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This study details the novel application of predacious copepods, genus Mesocyclops, for control of Ochlerotatus tremulus (Theobald) group and Aedes aegypti (L.) mosquito larvae in subterranean habitats in north Queensland, Australia. During June 1997, 50 Mesocyclops sp. I were inoculated into one service manhole in South Townsville. Wet season rainfall and flooding in both 1998 and 2000 was responsible for the dispersal of copepods via the underground pipe system to 29 of 35 manholes over an area of 1.33 km(2). Significant reductions in Aedes and Ochlerotatus larvae ensued. In these habitats, Mesocyclops and Metacyclops were able to survive dry periods, when substrate moisture content ranged from 13.8 to 79.9%. At the semiarid inland towns of Hughenden and Richmond, cracking clay soil prevents drainage of water from shallow service pits where Oc. tremulus immatures numbered from 292-18,460 per pit. Introduction of Mesocyclops copepods into these sites during May 1999 resulted in 100% control of Oc. tremulus for 18 mo. One uninoculated pit subsequently became positive for Mesocyclops with resultant control of mosquito larvae.

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We focus on mixtures of factor analyzers from the perspective of a method for model-based density estimation from high-dimensional data, and hence for the clustering of such data. This approach enables a normal mixture model to be fitted to a sample of n data points of dimension p, where p is large relative to n. The number of free parameters is controlled through the dimension of the latent factor space. By working in this reduced space, it allows a model for each component-covariance matrix with complexity lying between that of the isotropic and full covariance structure models. We shall illustrate the use of mixtures of factor analyzers in a practical example that considers the clustering of cell lines on the basis of gene expressions from microarray experiments. (C) 2002 Elsevier Science B.V. All rights reserved.

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We compare Bayesian methodology utilizing free-ware BUGS (Bayesian Inference Using Gibbs Sampling) with the traditional structural equation modelling approach based on another free-ware package, Mx. Dichotomous and ordinal (three category) twin data were simulated according to different additive genetic and common environment models for phenotypic variation. Practical issues are discussed in using Gibbs sampling as implemented by BUGS to fit subject-specific Bayesian generalized linear models, where the components of variation may be estimated directly. The simulation study (based on 2000 twin pairs) indicated that there is a consistent advantage in using the Bayesian method to detect a correct model under certain specifications of additive genetics and common environmental effects. For binary data, both methods had difficulty in detecting the correct model when the additive genetic effect was low (between 10 and 20%) or of moderate range (between 20 and 40%). Furthermore, neither method could adequately detect a correct model that included a modest common environmental effect (20%) even when the additive genetic effect was large (50%). Power was significantly improved with ordinal data for most scenarios, except for the case of low heritability under a true ACE model. We illustrate and compare both methods using data from 1239 twin pairs over the age of 50 years, who were registered with the Australian National Health and Medical Research Council Twin Registry (ATR) and presented symptoms associated with osteoarthritis occurring in joints of the hand.

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Conceptual modelling is an activity undertaken during information systems development work to build a representation of selected semantics about some real-world domain. Ontological theories have been developed to account for the structure and behavior of the real world in general. In this paper, I discuss why ontological theories can be used to inform conceptual modelling research, practice, and pedagogy. I provide examples from my research to illustrate how a particular ontological theory has enabled me to improve my understanding of certain conceptual modelling practices and grammars. I describe, also, how some colleagues and I have used this theory to generate several counter-intuitive, sometimes surprising predictions about widely advocated conceptual modelling practices - predictions that subsequently were supported in empirical research we undertook. Finally, I discuss several possibilities and pitfalls I perceived to be associated with our using ontological theories to underpin research on conceptual modelling.

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Free independent travelers require flexible, reactive service delivery due to their regularly changing location and activities and the lack of a wired Internet connection. A ubiquitous travel service delivery system that is able to dynamically deliver services in response to relevant events, such as changing location, availability of new last-minute specials, work opportunities, and safety issues can provide added value while retaining the flexibility that is so important to independent travelers. This article describes such a system. An engineering design research approach has been adopted to design the system. Issues addressed include traveler and service states and events, contexts, situations, and situation-action rules. An architecture is proposed that is based on distributed, cooperating software agents and mobile data technologies. The role of these agents is to continuously monitor situations that are occurring in the physical and virtual service spaces and to take the required action for any situations that are relevant to the traveler.

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This article presents a fairness theory-based conceptual framework for studying and managing consumers’ emotions during service recovery attempts. The conceptual framework highlights the central role played by counterfactual thinking and accountability. Findings from five focus groups are also presented to lend further support to the conceptual framework. Essentially, the article argues that a service failure event triggers an emotional response in the consumer, and from here the consumer commences an assessment of the situation, considering procedural justice, interactional justice, and distributive justice elements, while engaging in counterfactual thinking and apportioning accountability. More specifically, the customer assesses whether the service provider could and should have done something more to remedy the problem and how the customer would have felt had these actions been taken. The authors argue that during this process situational effort is taken into account when assessing accountability. When service providers do not appear to exhibit an appropriate level of effort, consumers attribute this to the service provider not caring. This in turn leads to the customer feeling more negative emotions, such as anger and frustration. Managerial implications of the study are discussed.

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Male and female consumers place different emphasis on elements of the service recovery process. Perceptions were influenced by gender of the service provider and by a match of customer and service provider gender. The study, an experimental design with 712 respondents, found that when service providers, irrespective of gender, display concern and give customers voice and a sizable compensation, both men and women reported more positive attitudes compared with when this was not so. Combinations of high voice with high outcome and high voice with high concern were especially important in positively influencing perceptions of effort, regardless of gender. However, the authors also found that there were significant differences between male and female respondents regarding their perceptions of how service recovery should be handled. Women want their views heard during service recovery attempts and to be allowed to provide input. Men, in contrast, do not view voice as important.

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This paper proposes a template for modelling complex datasets that integrates traditional statistical modelling approaches with more recent advances in statistics and modelling through an exploratory framework. Our approach builds on the well-known and long standing traditional idea of 'good practice in statistics' by establishing a comprehensive framework for modelling that focuses on exploration, prediction, interpretation and reliability assessment, a relatively new idea that allows individual assessment of predictions. The integrated framework we present comprises two stages. The first involves the use of exploratory methods to help visually understand the data and identify a parsimonious set of explanatory variables. The second encompasses a two step modelling process, where the use of non-parametric methods such as decision trees and generalized additive models are promoted to identify important variables and their modelling relationship with the response before a final predictive model is considered. We focus on fitting the predictive model using parametric, non-parametric and Bayesian approaches. This paper is motivated by a medical problem where interest focuses on developing a risk stratification system for morbidity of 1,710 cardiac patients given a suite of demographic, clinical and preoperative variables. Although the methods we use are applied specifically to this case study, these methods can be applied across any field, irrespective of the type of response.

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Colour pattern variation is a striking and widespread phenomenon. Differential predation risk between individuals is often invoked to explain colour variation, but empirical support for this hypothesis is equivocal. We investigated differential conspicuousness and predation risk in two species of Australian rock dragons, Ctenophorus decresii and C. vadnappa. To humans, the coloration of males of these species varies between 'bright' and 'dull'. Visual modelling based on objective colour measurements and the spectral sensitivities of avian visual pigments showed that dragon colour variants are differentially conspicuous to the visual system of avian predators when viewed against the natural background. We conducted field experiments to test for differential predation risk, using plaster models of 'bright' and 'dull' males. 'Bright' models were attacked significantly more often than 'dull' models suggesting that differential conspicuousness translates to differential predation risk in the wild. We also examined the influence of natural geographical range on predation risk. Results from 22 localities suggest that predation rates vary according to whether predators are familiar with the prey species. This study is among the first to demonstrate both differential conspicuousness and differential predation risk in the wild using an experimental protocol. (C) 2003 Published by Elsevier Ltd on behalf of The Association for the Study of Animal Behaviour.