935 resultados para On-line Prediction
Resumo:
Three experiments examine the effect of different forms of computer-generated advice on concurrent and subsequent performance of individuals controlling a simulated intensive-care task. Experiment 1 investigates the effect of optional and compulsory advice and shows that both result in an improvement in subjects' performance while receiving the advice, and also in an improvement in subsequent unaided performance. However, although the advice compliance displayed by the optional advice group shows a strong correlation with subsequent unaided performance, compulsory advice has no extra benefit over the optional use of advice. Experiment 2 examines the effect of providing users with on-line explanations of the advice, as well as providing less specific advice. The results show that both groups perform at the same level on the task as the advice groups from Experiment 1, although subjects receiving explanations scored significantly higher on a written post-task questionnaire. Experiment 3 investigates in more detail the relationship between advice compliance and performance. The results reveal a complex relationship between natural ability on the task and the following of advice, in that people who use the advice more tend to perform either better or worse than the more moderate users. The theoretical and practical implications of these experiments are discussed.
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The influence of adjunct brine cultures on the volatile compounds in Feta-type cheeses made from bovine milk was studied. Four batches of brine were produced: one with no added adjuncts, a second containing Lactobacillus paracasei subsp. paracasei, a third containing Lb. paracasei subsp. paracasei plus Debaryomyces hansenii and a fourth with Lb. paracasei subsp. paracasei plus Yarrowia lipolytica. All the cultures were isolated from commercial Feta brines. Aroma compounds were analysed by dynamic headspace analysis, on-line coupled with GC/MS. The most important volatile compounds were quantified in the experimental cheeses; it was concluded that the use of Lb. paracasei subsp. paracasei and D. hansenii as adjuncts in the manufacture of Feta-type cheeses contribute to the formation of a richer pattern of aroma compounds, namely alcohols, aldehydes and esters. The inclusion of Y. lipolytica resulted in the production of undesirable aroma compounds that are not part of the usual volatile profile of high quality Feta cheeses. (C) 2004 Elsevier Ltd. All rights reserved.
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The initial condition effect on climate prediction skill over a 2-year hindcast time-scale has been assessed from ensemble HadCM3 climate model runs using anomaly initialization over the period 1990–2001, and making comparisons with runs without initialization (equivalent to climatological conditions), and to anomaly persistence. It is shown that the assimilation improves the prediction skill in the first year globally, and in a number of limited areas out into the second year. Skill in hindcasting surface air temperature anomalies is most marked over ocean areas, and is coincident with areas of high sea surface temperature and ocean heat content skill. Skill improvement over land areas is much more limited but is still detectable in some cases. We found little difference in the skill of hindcasts using three different sets of ocean initial conditions, and we obtained the best results by combining these to form a grand ensemble hindcast set. Results are also compared with the idealized predictability studies of Collins (Clim. Dynam. 2002; 19: 671–692), which used the same model. The maximum lead time for which initialization gives enhanced skill over runs without initialization varies in different regions but is very similar to lead times found in the idealized studies, therefore strongly supporting the process representation in the model as well as its use for operational predictions. The limited 12-year period of the study, however, means that the regional details of model skill should probably be further assessed under a wider range of observational conditions.
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We propose and analyse a class of evolving network models suitable for describing a dynamic topological structure. Applications include telecommunication, on-line social behaviour and information processing in neuroscience. We model the evolving network as a discrete time Markov chain, and study a very general framework where, conditioned on the current state, edges appear or disappear independently at the next timestep. We show how to exploit symmetries in the microscopic, localized rules in order to obtain conjugate classes of random graphs that simplify analysis and calibration of a model. Further, we develop a mean field theory for describing network evolution. For a simple but realistic scenario incorporating the triadic closure effect that has been empirically observed by social scientists (friends of friends tend to become friends), the mean field theory predicts bistable dynamics, and computational results confirm this prediction. We also discuss the calibration issue for a set of real cell phone data, and find support for a stratified model, where individuals are assigned to one of two distinct groups having different within-group and across-group dynamics.
Assessing and understanding the impact of stratospheric dynamics and variability on the earth system
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Advances in weather and climate research have demonstrated the role of the stratosphere in the Earth system across a wide range of temporal and spatial scales. Stratospheric ozone loss has been identified as a key driver of Southern Hemisphere tropospheric circulation trends, affecting ocean currents and carbon uptake, sea ice, and possibly even the Antarctic ice sheets. Stratospheric variability has also been shown to affect short term and seasonal forecasts, connecting the tropics and midlatitudes and guiding storm track dynamics. The two-way interactions between the stratosphere and the Earth system have motivated the World Climate Research Programme's (WCRP) Stratospheric Processes and Their Role in Climate (SPARC) DynVar activity to investigate the impact of stratospheric dynamics and variability on climate. This assessment will be made possible by two new multi-model datasets. First, roughly 10 models with a well resolved stratosphere are participating in the Coupled Model Intercomparison Project 5 (CMIP5), providing the first multi-model ensemble of climate simulations coupled from the stratopause to the sea floor. Second, the Stratosphere Historical Forecasting Project (SHFP) of WCRP's Climate Variability and predictability (CLIVAR) program is forming a multi-model set of seasonal hindcasts with stratosphere resolving models, revealing the impact of both stratospheric initial conditions and dynamics on intraseasonal prediction. The CMIP5 and SHFP model-data sets will offer an unprecedented opportunity to understand the role of the stratosphere in the natural and forced variability of the Earth system and to determine whether incorporating knowledge of the middle atmosphere improves seasonal forecasts and climate projections. Capsule New modeling efforts will provide unprecedented opportunities to harness our knowledge of the stratosphere to improve weather and climate prediction.
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Climate change in the UK is expected to cause increases in temperatures, altered precipitation patterns and more frequent and extreme weather events. In this review we discuss climate effects on dissolved organic matter (DOM), how altered DOM and water physico-chemical properties will affect treatment processes and assess the utility of techniques used to remove DOM and monitor water quality. A critical analysis of the literature has been undertaken with a focus on catchment drivers of DOM character, removal of DOM via coagulation and the formation of disinfectant by-products (DBPs). We suggest that: (1) upland catchments recovering from acidification will continue to produce more DOM with a greater hydrophobic fraction as solubility controls decrease; (2) greater seasonality in DOM export is likely in future due to altered precipitation patterns; (3) changes in species diversity and water properties could encourage algal blooms; and (4) that land management and vegetative changes may have significant effects on DOM export and treatability but require further research. Increases in DBPs may occur where catchments have high influence from peatlands or where algal blooms become an issue. To increase resilience to variable DOM quantity and character we suggest that one or more of the following steps are undertaken at the treatment works: a) ‘enhanced coagulation’ optimised for DOM removal; b) switching from aluminium to ferric coagulants and/or incorporating coagulant aids; c) use of magnetic ion-exchange (MIEX) pre-coagulation; and d) activated carbon filtration post-coagulation. Fluorescence and UV absorbance techniques are highlighted as potential methods for low-cost, rapid on-line process optimisation to improve DOM removal and minimise DBPs.
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Public and policy discourse about the content of history curricula is frequently contested, but the voice of history teachers is often absent from such debate. Drawing on a large scale on-line survey of history teachers in England, this paper explores their responses to major curriculum reforms proposed by the Coalition government in February 2013. In particular it examines teachers' responses to government plans to prescribe a list of topics, events and individuals to be taught chronologically that all students would be expected to study. Nearly 550 teachers responded to the survey, and more than two-thirds of them provided additional written comments on the curriculum proposals. This paper examines these comments, with reference to a range of curriculum models. The study reveals a deep antagonism towards the proposals for various reasons, including concerns about the extent and nature of the substantive content proposed and the way in which it should be sequenced. Analysis of these reactions provides an illuminating insight into history teachers’ perspectives. While the rationales that underpin their thinking seem to have connections to a variety of different theoretical models, the analysis suggests that more attention could usefully be devoted to the idea of developing frameworks of reference.
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The objective of this article is to find out the influence of the parameters of the ARIMA-GARCH models in the prediction of artificial neural networks (ANN) of the feed forward type, trained with the Levenberg-Marquardt algorithm, through Monte Carlo simulations. The paper presents a study of the relationship between ANN performance and ARIMA-GARCH model parameters, i.e. the fact that depending on the stationarity and other parameters of the time series, the ANN structure should be selected differently. Neural networks have been widely used to predict time series and their capacity for dealing with non-linearities is a normally outstanding advantage. However, the values of the parameters of the models of generalized autoregressive conditional heteroscedasticity have an influence on ANN prediction performance. The combination of the values of the GARCH parameters with the ARIMA autoregressive terms also implies in ANN performance variation. Combining the parameters of the ARIMA-GARCH models and changing the ANN`s topologies, we used the Theil inequality coefficient to measure the prediction of the feed forward ANN.
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In this work Cu and Fe bioavailability in cashew nuts was evaluated using in vitro method. Extractions with simulated gastric and intestinal fluids and dialysis procedures were applied for this purpose. The proteins separation and quantification were performed by size exclusion chromatography (SEC) coupled on-line to ultra-violet (UV) and off-line to simultaneous multielement atomic absorption spectrometry (SIMAAS). The SEC-UV and SIMAAS profiles of the protein fractions obtained by alkaline extraction (NaOH) and precipitation with HCl indicated the presence of high and low molecular weight species in the range between >75 kDa and 9.3 kDa. Almost 83% of Cu and 78% of Fe were extracted during cashew nut digestion and 90% of both elements were dialyzed. With these results it is possible to assume that 75% of Cu and 70% of Fe present in cashew nut could be bioavailable. The SEC-UV and SIMAAS chromatographic profiles obtained after in vitro gastrointestinal digestion reveal that Cu and Fe not dialyzed can be associated to a compound of 9.2 kDa. (C) 2010 Elsevier B.V. All rights reserved.
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The internet has revolutionized the way we socialize, and as a consequence the way to love. The new communication technologies have facilitated intercultural relationships. Nowadays family relations are one of the major factors in immigration to European countries. Family relations means persons who arrive as family dependents and in accordance with laws regulating family reunification. This thesis aims to apply the classical assimilation theory stated by Milton Gordon (1964), which formulates a series of assimilation stages through which an individual must pass in order to be completely assimilated. In accordance with this theory, marriage is the final phase for a newcomer to fully incorporate into the host society. Thus, based on this presumption and other contemporary theories, the present study has analysed how women who get involved in intercultural marriages based on internet meeting experience these assimilation stages and evaluated the resources used by respondents to incorporate themselves into Swedish society.The main goal of the study was to determine if jumping to the last stage of assimilation does assure the incorporation in the social or/and labour spheres and the findings demonstrate that even though husbands are a valuable resource for assimilation, several cultural issues in Swedish society make it difficult to assure success for the newcomers.On the other hand, Sweden is a country with a strong national sentiment and the assimilation of immigrants still is an important issue to deal with. The Swedish Integration Board has disappeared and major projects for integration have been left in the hands of the municipalities or the Migration Board, institutions that still do not know how to deal with this dilemma.
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When an accurate hydraulic network model is available, direct modeling techniques are very straightforward and reliable for on-line leakage detection and localization applied to large class of water distribution networks. In general, this type of techniques based on analytical models can be seen as an application of the well-known fault detection and isolation theory for complex industrial systems. Nonetheless, the assumption of single leak scenarios is usually made considering a certain leak size pattern which may not hold in real applications. Upgrading a leak detection and localization method based on a direct modeling approach to handle multiple-leak scenarios can be, on one hand, quite straightforward but, on the other hand, highly computational demanding for large class of water distribution networks given the huge number of potential water loss hotspots. This paper presents a leakage detection and localization method suitable for multiple-leak scenarios and large class of water distribution networks. This method can be seen as an upgrade of the above mentioned method based on a direct modeling approach in which a global search method based on genetic algorithms has been integrated in order to estimate those network water loss hotspots and the size of the leaks. This is an inverse / direct modeling method which tries to take benefit from both approaches: on one hand, the exploration capability of genetic algorithms to estimate network water loss hotspots and the size of the leaks and on the other hand, the straightforwardness and reliability offered by the availability of an accurate hydraulic model to assess those close network areas around the estimated hotspots. The application of the resulting method in a DMA of the Barcelona water distribution network is provided and discussed. The obtained results show that leakage detection and localization under multiple-leak scenarios may be performed efficiently following an easy procedure.
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Companies have looked for many new ways to communicate with their customers. In the current scenario, Facebook has proven to be an efficient communication tool between consumers and businesses. This study aims to understand the differences in the complaint messages sent to companies, through an experiment that measured the emotional tone and the lack of formality in each message received by the website and the Facebook page of the company. As expected, people are more informal on Facebook. However, contrary to our intuition, participants tended to display more emotions on the company website. The social norms theory and the impression management contributed to explain the phenomena found.
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This exploratory research aims to find out the extent to which Corporate Social Responsibility (CSR) impacts the purchasing behavior of Peruvian consumers when it comes to convenience food products. The study includes qualitative and quantitative analysis. Qualitative analysis consists of in-depth interviews with CSR representatives from consumer product companies, CSR practitioners and some consumers from the quantitative sample. That group’s composition was selected in order to obtain a wide picture of the consumers’ perception towards CSR, including their understanding of the concept and the relevance in their decision making process when buying convenience food products. The quantitative analysis portion consists of an on-line survey focused on Peruvian consumers who live in Lima during the year 2015. Consumers included in the sample were selected by convenience. After analyzing the 134 completed surveys, the results obtained suggest that even though there is an increasing interest in CSR, including CSR as an attribute of the purchased goods, interest is not fully demonstrated by the purchasing behavior of consumers. The main breach leading to this inconsistency appears to be the lack of or failure in the companies’ CSR communication towards consumers. Consumers demand reliable information which socially responsible companies usually provide; however at this stage, the target audiences of such information are mostly corporations and communities surrounding the manufacturing plants of convenience food products.
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Lula polariza as redes sociais, de acordo com um estudo da DAPP publicado no jornal Financial Times.
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This paper presents a hybrid way mixing time and frequency domain for transmission lines modelling. The proposed methodology handles steady fundamental signal mixed with fast and slow transients, including impulsive and oscillatory behaviour. A transmission line model is developed based on lumped elements representation and state-space techniques. The proposed methodology represents an easy and practical procedure to model a three-phase transmission line directly in time domain, without the explicit use of inverse transforms. The proposed methodology takes into account the frequency-dependent parameters of the line, considering the soil and skin effects. In order to include this effect in the state matrices, a fitting method is applied. Furthermore the accuracy of proposed the developed model is verified, in frequency domain, by a simple methodology based on line distributed parameters and transfer function related to the input/output signals of the lumped parameters representation. In addition, this article proposes the use of a fast and robust analytic integration procedure to solve the state equations, enabling transient and steady-state simulations. The results are compared with those obtained by the commercial software Microtran (EMTP), taking into account a three-phase transmission line, typical in the Brazilian transmission system.