955 resultados para Demands


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Accurate knowledge of traffic demands in a communication network enables or enhances a variety of traffic engineering and network management tasks of paramount importance for operational networks. Directly measuring a complete set of these demands is prohibitively expensive because of the huge amounts of data that must be collected and the performance impact that such measurements would impose on the regular behavior of the network. As a consequence, we must rely on statistical techniques to produce estimates of actual traffic demands from partial information. The performance of such techniques is however limited due to their reliance on limited information and the high amount of computations they incur, which limits their convergence behavior. In this paper we study strategies to improve the convergence of a powerful statistical technique based on an Expectation-Maximization iterative algorithm. First we analyze modeling approaches to generating starting points. We call these starting points informed priors since they are obtained using actual network information such as packet traces and SNMP link counts. Second we provide a very fast variant of the EM algorithm which extends its computation range, increasing its accuracy and decreasing its dependence on the quality of the starting point. Finally, we study the convergence characteristics of our EM algorithm and compare it against a recently proposed Weighted Least Squares approach.

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Accurate knowledge of traffic demands in a communication network enables or enhances a variety of traffic engineering and network management tasks of paramount importance for operational networks. Directly measuring a complete set of these demands is prohibitively expensive because of the huge amounts of data that must be collected and the performance impact that such measurements would impose on the regular behavior of the network. As a consequence, we must rely on statistical techniques to produce estimates of actual traffic demands from partial information. The performance of such techniques is however limited due to their reliance on limited information and the high amount of computations they incur, which limits their convergence behavior. In this paper we study a two-step approach for inferring network traffic demands. First we elaborate and evaluate a modeling approach for generating good starting points to be fed to iterative statistical inference techniques. We call these starting points informed priors since they are obtained using actual network information such as packet traces and SNMP link counts. Second we provide a very fast variant of the EM algorithm which extends its computation range, increasing its accuracy and decreasing its dependence on the quality of the starting point. Finally, we evaluate and compare alternative mechanisms for generating starting points and the convergence characteristics of our EM algorithm against a recently proposed Weighted Least Squares approach.

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Both stimulus and response conflict can disrupt behavior by slowing response times and decreasing accuracy. Although several neural activations have been associated with conflict processing, it is unclear how specific any of these are to the type of stimulus conflict or the amount of response conflict. Here, we recorded electrical brain activity, while manipulating the type of stimulus conflict in the task (spatial [Flanker] versus semantic [Stroop]) and the amount of response conflict (two versus four response choices). Behaviorally, responses were slower to incongruent versus congruent stimuli across all task and response types, along with overall slowing for higher response-mapping complexity. The earliest incongruency-related neural effect was a short-duration frontally-distributed negativity at ~200 ms that was only present in the Flanker spatial-conflict task. At longer latencies, the classic fronto-central incongruency-related negativity 'N(inc)' was observed for all conditions, but was larger and ~100 ms longer in duration with more response options. Further, the onset of the motor-related lateralized readiness potential (LRP) was earlier for the two vs. four response sets, indicating that smaller response sets enabled faster motor-response preparation. The late positive complex (LPC) was present in all conditions except the two-response Stroop task, suggesting this late conflict-related activity is not specifically related to task type or response-mapping complexity. Importantly, across tasks and conditions, the LRP onset at or before the conflict-related N(inc), indicating that motor preparation is a rapid, automatic process that interacts with the conflict-detection processes after it has begun. Together, these data highlight how different conflict-related processes operate in parallel and depend on both the cognitive demands of the task and the number of response options.

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This paper aims to create a picture of aspects of the working lives of some trainers of technical and further education teachers in a specialist teacher training college in Bolton, Lancashire, from the 1950s to the 1980's. There is little reference to technical teacher training in the literature on teacher training in the second half of the twentieth century. With this gap in mind, this paper sets out to record some memories and impressions of staff involved during these years. Using data from a series of semi-structured interviews, the discussion centres upon their perceptions of their work: of their students, the working environment, the curriculum and their relationships with the technical colleges for whom they were training teachers. The paper has three sections. It begins with a brief discussion of the issues arising from the choice of research methods. The second section contextualises the study and traces the history of Bolton Technical Teachers' Training College from its establishment through to its merger with the Institute of Technology in 1982. This is followed by the presentation and discussion of the interview data.

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This paper first explores the conflictual discourses employed by government agencies, citizens’ initiatives, and environmental organizations over the construction of a High Voltage Power Station (KYT) for demands of the 2004 Olympic Games, as presented in media reports and movement literature over a period of one year. Having in mind recent criticisms targeting the lack of empirical evidence in Ulrich Beck’s risk theorization, this exploration is of distinct importance. Secondly, it takes into account that both the defensive character of societal action and mistrust to expert authorities have been confirmed as prevalent characteristics of both the Greek and the general risk social context. The paper attempts to re-evaluate and/or complement existing perspectives of societal activism in general and environmental mobilizations in particular within the confines of the Greek social context. As a tentative conclusion, it is suggested that the risk perspective offers a novel prism for the examination of societal activism without confining it to the characteristics of individual national contexts.

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The present study examined whether Perceptions of organizational fairness (the procedural and interactional components) were able to diminish the negative effects of high job demands and low job control on the balance between work and family. The study participants were 713 women working in long-term care for elderly people in Finland. The results showed that high job demands, low job control, and unfair decision making were associated with high levels of time-based work interference with family (WIF). Perceptions of organizational fairness were found to partially mediate the association between Job control and WIF In addition, fair treatment and management protected against WIF when demands were low but were unable to bluffer against the negative effects of high job demands. (C) 2008 Wiley Periodicals, Inc.

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The prevailing paradigm for researching sensorimotor synchronisation in humans involves finger tapping and temporal accuracy measures. However, many successful sensorimotor synchronisation actions require not only to be 'in time', but also to be in a predefined spatial position. Reaching this spatial position in many everyday actions often exceeds the average amplitude of a finger movement. The aim of this study is to address how people coordinate their movement to be in the right place at the right time when the scale of the movement varies. Does the scale of the movement and accuracy demands of the movement change the ability to accurately synchronise? To address these questions, a sensorimotor synchronisation task with three different inter-beat intervals, two different movement amplitudes and two different target widths was used. Our experiment demonstrated that people use different timing strategies-employing either a movement strategy (varying movement time) or a waiting strategy (keeping movement time constant) for large-scale movements. Those two strategies were found to be equally successful in terms of temporal accuracy and variability (spread of errors). With longer interval durations (2.5 and 3.5 s), variability of sensorimotor synchronisation performance increased (measured as the spread of errors). Analysing the data using the Vorberg and Wing (Handbook of perception and action. Academic Press, New York, pp 181-262, 1996) model shows a need to develop further existing timing models of sensorimotor synchronisation so that they could apply to large-scale movements, where different movement strategies naturally emerge.