906 resultados para Autoregressive-Moving Average model


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The present study contributes to theory and practice through the development of a model of shift-work tolerance with the potential to indicate interventions that reduce nurses' intention toward turnover and increase job satisfaction in hospital-based settings. Survey data from 1257 nurses were used to conduct structural equation modeling that examine the direct and indirect effects of supervisor and colleague support, team identity, team climate, and control over working environment on time-based work/life conflict, psychological well-being, physical symptoms, job satisfaction, and turnover intention. The analysis of the proposed model revealed a good fit The chi-square difference test was non-significant (χ2(26)=338.56), the fit indices were high (CFI=.923, NFI=.918, and NNFI=.868), the distribution of residuals was symmetric and approached zero, the average standardized residual was low (AASR=.04), and the standardized RMR was .072. In terms of the predictor variable, the final model explained 48% of the variance in turnover intention. The data revealed considerable evidence of both direct effects on adjustment and complex indirect links between levels of adjustment and work-related social support, team identity, team climate, and control. Nurses with high supervisor and coworker support experienced more positive team climates, identified more strongly with their team, and increased their perceptions of control over their work environment. This in turn lowered their appraisals of their time-based work/life conflict, which consequently increased their psychological well-being and job satisfaction and reduced their physical health symptoms and turnover intention. The type of shift schedule worked by the nurses influenced levels of turnover intention, control over work environment, time-based work/life conflict, and physical symptoms.

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We present AUSLEM (AUStralian Land Erodibility Model), a land erodibility modelling system that utilizes a rule-set of surficial and climatic thresholds applied through a Geographic Information System (GIs) modelling framework to predict landscape susceptibility to wind erosion. AUSLEM is distinctive in that it quantitatively assesses landscape susceptibility to wind erosion at a 5 x 5 km. spatial resolution on a monthly time-step across Australia. The system was implemented for representative wet (1984), dry (1994), and average rainfall (1997) years with corresponding low, high and moderate dust storm day frequencies. Results demonstrate that AUSLEM can identify landscape erodibility, and provide an interpretation of the physical nature and distribution of erodible landscapes in Australia. Further, results offer an assessment of the dynamic tendencies of erodibility in space and time in response to the El Nino Southern Oscillation (ENSO) and seasonal synoptic scale climate variability. A comparative analysis of AUSLEM output with independent national and international wind erosion, atmospheric aerosol and dust event records indicates a high level of model competency. (c) 2006 Elsevier B.V. All rights reserved.

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This paper presents a forecasting technique for forward electricity/gas prices, one day ahead. This technique combines a Kalman filter (KF) and a generalised autoregressive conditional heteroschedasticity (GARCH) model (often used in financial forecasting). The GARCH model is used to compute next value of a time series. The KF updates parameters of the GARCH model when the new observation is available. This technique is applied to real data from the UK energy markets to evaluate its performance. The results show that the forecasting accuracy is improved significantly by using this hybrid model. The methodology can be also applied to forecasting market clearing prices and electricity/gas loads.

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It is well known that even slight changes in nonuniform illumination lead to a large image variability and are crucial for many visual tasks. This paper presents a new ICA related probabilistic model where the number of sources exceeds the number of sensors to perform an image segmentation and illumination removal, simultaneously. We model illumination and reflectance in log space by a generalized autoregressive process and Hidden Gaussian Markov random field, respectively. The model ability to deal with segmentation of illuminated images is compared with a Canny edge detector and homomorphic filtering. We apply the model to two problems: synthetic image segmentation and sea surface pollution detection from intensity images.

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Multi-agent algorithms inspired by the division of labour in social insects are applied to a problem of distributed mail retrieval in which agents must visit mail producing cities and choose between mail types under certain constraints.The efficiency (i.e. the average amount of mail retrieved per time step), and the flexibility (i.e. the capability of the agents to react to changes in the environment) are investigated both in static and dynamic environments. New rules for mail selection and specialisation are introduced and are shown to exhibit improved efficiency and flexibility compared to existing ones. We employ a genetic algorithm which allows the various rules to evolve and compete. Apart from obtaining optimised parameters for the various rules for any environment, we also observe extinction and speciation. From a more theoretical point of view, in order to avoid finite size effects, most results are obtained for large population sizes. However, we do analyse the influence of population size on the performance. Furthermore, we critically analyse the causes of efficiency loss, derive the exact dynamics of the model in the large system limit under certain conditions, derive theoretical upper bounds for the efficiency, and compare these with the experimental results.

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This paper assesses the extent to which the equity markets of Hungary, Poland the Czech Republic and Russia have become less segmented. Using a variety of tests it is shown there has been a consistent increase in the co-movement of some Eastern European markets and developed markets. Using the variance decompositions from a vector autoregressive representation of returns it is shown that for Poland and Hungary global factors are having an increasing influence on equity returns, suggestive of increased equity market integration. In this paper we model a system of bivariate equity market correlations as a smooth transition logistic trend model in order to establish how rapidly the countries of Eastern Europe are moving away from market segmentation. We find that Hungary is the country which is becoming integrated the most quickly. © 2005 ELsevier Ltd. All rights reserved.

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This study examines the forecasting accuracy of alternative vector autoregressive models each in a seven-variable system that comprises in turn of daily, weekly and monthly foreign exchange (FX) spot rates. The vector autoregressions (VARs) are in non-stationary, stationary and error-correction forms and are estimated using OLS. The imposition of Bayesian priors in the OLS estimations also allowed us to obtain another set of results. We find that there is some tendency for the Bayesian estimation method to generate superior forecast measures relatively to the OLS method. This result holds whether or not the data sets contain outliers. Also, the best forecasts under the non-stationary specification outperformed those of the stationary and error-correction specifications, particularly at long forecast horizons, while the best forecasts under the stationary and error-correction specifications are generally similar. The findings for the OLS forecasts are consistent with recent simulation results. The predictive ability of the VARs is very weak.

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Combined bioreaction separation studies have been carried out for the first time on a moving port semi-continuous counter-current chromatographic reactor-separator (SCCR-S1) consisting of twelve 5.4cm id x 75cm long columns packed with calcium charged cross-linked polystyrene resin (KORELA V07C). The inversion of sucrose to glucose and fructose in the presence of the enzyme invertase and the biochemIcal synthesis of dextran and fructose from sucrose in the presence of the enzyme dextransucrase were investigated. A dilute stream of the appropriate enzyme in deionised water was used as the eluent stream. The effect of switch time, feed concentration, enzyme activity, eluent rate and enzyme to feed concentration ratio on the combined bioreaction-separation were investigated. For the invertase reaction, at 20.77% w/v sucrose feed concentrations complete conversions were achieved. The enzyme usage was 34% of the theoretical enzyme amount needed to convert an equivalent amount of sucrose over the same time period when using a conventional fermenter. The fructose rich (FRP) and glucose rich (GRP) product purities obtained were over 90%. By operating at 35% w/v sucrose feed concentration and employing the product splitting and recycling techniques, the total concentration and purity of the GRP increased from 32% w/v to 4.6% and from 92.3% to 95% respectively. The FRP concentration also increased from 1.82% w/v to 2.88% w/v. A mathematical model was developed for the combined reaction-separation and used to simulate the continuous inversion of sucrose and product separation using the SCCR-S1. In the biosynthesis of dextran studies, 52% conversion of a 2% w/v sucrose concentration feed was achieved. An average dextran molecular weight of 4 millIon was obtained in the dextran rich (DRP) product stream. The enzyme dextransucrase was purifed successfully using centrifugation and ultrafiltration techniques.

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Practitioners and academics are in broad agreement that, above all, organizations need to be able to learn, to innovate and to question existing ways of working. This thesis develops a model to take into account, firstly, what determines whether or not organizations endorse practices designed to facilitate learning. Secondly, the model evaluates the impact of such practices upon organizational outcomes, measured in terms of products and technological innovation. Researchers have noted that organizations that are committed to producing innovation show great resilience in dealing with adverse business conditions (e.g. Pavitt, 1991; Leonard Barton, 1998). In effect, such organizations bear many of the characteristics associated with the achievement of ‘learning organization’ status (Garvin, 1993; Pedler, Burgoyne & Boydell, 1999; Senge, 1990). Seven studies are presented to support this theoretical framework. The first empirical study explores the antecedents to effective learning. The three following studies present data to suggest that people management practices are highly significant in determining whether or not organizations are able to produce sustained innovation. The thesis goes on to explore the relationship between organizational-level job satisfaction, learning and innovation, and provides evidence to suggest that there is a strong, positive relationship between these variables. The final two chapters analyze learning and innovation within two similar manufacturing organizations. One manifests relatively low levels of innovation whilst the other is generally considered to be outstandingly innovative. I present the comparative framework for exploring the different approaches to learning manifested by the two organizations. The thesis concludes by assessing the extent to which the theoretical model presented in the second chapter is borne out by the findings of the study. Whilst this is a relatively new field of inquiry, findings reveal that organizations have a much stronger chance of producing sustained innovation where they manage people proactively where people process themselves to be satisfied at work. Few studies to date have presented empirical evidence to substantiate theoretical endorsements to engage in higher order learning, so this research makes an important contribution to existing literature in this field.

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Despite the difficulties that we have regarding the use of English in tertiary education in Turkey, we argue that it is necessary for those involved to study in the medium of English. Furthermore, significant advances have been made on this front. These efforts have been for the most part language-oriented, but also include research into needs analysis and the pedagogy of team-teaching. Considering the current situation at this level of education, however, there still seems to be more to do. And the question is, what more can we do? What further contribution can we make? Or, how can we take this process further? The purpose of the study reported here is to respond to this last question. We test the proposition that it is possible to take this process further by investigating the efficient management of transition from Turkish-medium to English-medium at the tertiary level of education in Turkey. Beyond what is achieved by only the language orientation of the EAP approach, and moving conceptually deeper than what has been achieved by the team-teaching approach, the research undertaken for the purpose of this study focuses on the idea of the discourse community that people want to belong to. It then pursues an adaptation of the essentially psycho-social approach of apprenticeship, as people become aspirants and apprentices to that discourse community. In this thesis, the researcher recognises that she cannot follow all the way through to the full implementation of her ideas in a fully-taught course. She is not in a position to change the education system. What she does here is to introduce a concept and sample its effects in terms of motivation, and thereby of integration and of success, for individuals and groups of learners. Evaluation is provided by acquiring both qualitative and quantitative data concerning mature members' perceptions of apprenticed-neophytes functioning as members in the new community, apprenticed-neophytes' perceptions of their own membership and of the preparation process undertaken, and the comparison of these neophytes' performance with that of other neophytes in the community. The data obtained provide strong evidence in support of the potential usefulness of this apprenticeship model towards the declared purpose of improving the English-medium tertiary education of Turkish students in their chosen fields of study.

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Molecular dynamics (MD) has been used to identify the relative distribution of dysprosium in the phosphate glass DyAl0.30P3.05O9.62. The MD model has been compared directly with experimental data obtained from neutron diffraction to enable a detailed comparison beyond the total structure factor level. The MD simulation gives Dy ... Dy correlations at 3.80(5) and 6.40(5) angstrom with relative coordination numbers of 0.8(1) and 7.3(5), thus providing evidence of minority rare-earth clustering within these glasses. The nearest neighbour Dy-O peak occurs at 2.30 angstrom with each Dy atom having on average 5.8 nearest neighbour oxygen atoms. The MD simulation is consistent with the phosphate network model based on interlinked PO4 tetrahedra where the addition of network modifiers Dy3+ depolymerizes the phosphate network through the breakage of P-(O)-P bonds whilst leaving the tetrahedral units intact. The role of aluminium within the network has been taken into explicit account, and A1 is found to be predominantly (78 tetrahedrally coordinated. In fact all four A1 bonds are found to be to P (via an oxygen atom) with negligible amounts of Al-O-Dy bonds present. This provides an important insight into the role of Al additives in improving the mechanical properties of these glasses.

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A nature inspired decentralised multi-agent algorithm is proposed to solve a problem of distributed task allocation in which cities produce and store batches of different mail types. Agents must collect and process the mail batches, without global knowledge of their environment or communication between agents. The problem is constrained so that agents are penalised for switching mail types. When an agent process a mail batch of different type to the previous one, it must undergo a change-over, with repeated change-overs rendering the agent inactive. The efficiency (average amount of mail retrieved), and the flexibility (ability of the agents to react to changes in the environment) are investigated both in static and dynamic environments and with respect to sudden changes. New rules for mail selection and specialisation are proposed and are shown to exhibit improved efficiency and flexibility compared to existing ones. We employ a evolutionary algorithm which allows the various rules to evolve and compete. Apart from obtaining optimised parameters for the various rules for any environment, we also observe extinction and speciation.

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IEEE 802.11 standard has achieved huge success in the past decade and is still under development to provide higher physical data rate and better quality of service (QoS). An important problem for the development and optimization of IEEE 802.11 networks is the modeling of the MAC layer channel access protocol. Although there are already many theoretic analysis for the 802.11 MAC protocol in the literature, most of the models focus on the saturated traffic and assume infinite buffer at the MAC layer. In this paper we develop a unified analytical model for IEEE 802.11 MAC protocol in ad hoc networks. The impacts of channel access parameters, traffic rate and buffer size at the MAC layer are modeled with the assistance of a generalized Markov chain and an M/G/1/K queue model. The performance of throughput, packet delivery delay and dropping probability can be achieved. Extensive simulations show the analytical model is highly accurate. From the analytical model it is shown that for practical buffer configuration (e.g. buffer size larger than one), we can maximize the total throughput and reduce the packet blocking probability (due to limited buffer size) and the average queuing delay to zero by effectively controlling the offered load. The average MAC layer service delay as well as its standard deviation, is also much lower than that in saturated conditions and has an upper bound. It is also observed that the optimal load is very close to the maximum achievable throughput regardless of the number of stations or buffer size. Moreover, the model is scalable for performance analysis of 802.11e in unsaturated conditions and 802.11 ad hoc networks with heterogenous traffic flows. © 2012 KSI.

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A nature inspired decentralised multi-agent algorithm is proposed to solve a problem of distributed task selection in which cities produce and store batches of different mail types. Agents must collect and process the mail batches, without a priori knowledge of the available mail at the cities or inter-agent communication. In order to process a different mail type than the previous one, agents must undergo a change-over during which it remains inactive. We propose a threshold based algorithm in order to maximise the overall efficiency (the average amount of mail collected). We show that memory, i.e. the possibility for agents to develop preferences for certain cities, not only leads to emergent cooperation between agents, but also to a significant increase in efficiency (above the theoretical upper limit for any memoryless algorithm), and we systematically investigate the influence of the various model parameters. Finally, we demonstrate the flexibility of the algorithm to changes in circumstances, and its excellent scalability.

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For 35 years, Arnstein's ladder of citizen participation has been a touchstone for policy makers and practitioners promoting user involvement. This article critically assesses Arnstein's writing in relation to user involvement in health drawing on evidence from the United Kingdom, the Netherlands, Finland, Sweden and Canada. Arnstein's model, however, by solely emphasizing power, limits effective responses to the challenge of involving users in services and undermines the potential of the user involvement process. Such an emphasis on power assumes that it has a common basis for users, providers and policymakers and ignores the existence of different relevant forms of knowledge and expertise. It also fails to recognise that for some users, participation itself may be a goal. We propose a new model to replace the static image of a ladder and argue that for user involvement to improve health services it must acknowledge the value of the process and the diversity of knowledge and experience of both health professionals and lay people.