899 resultados para Models performance


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In this paper two models for the simulation of glucose-insulin metabolism of children with Type 1 diabetes are presented. The models are based on the combined use of Compartmental Models (CMs) and artificial Neural Networks (NNs). Data from children with Type 1 diabetes, stored in a database, have been used as input to the models. The data are taken from four children with Type 1 diabetes and contain information about glucose levels taken from continuous glucose monitoring system, insulin intake and food intake, along with corresponding time. The influences of taken insulin on plasma insulin concentration, as well as the effect of food intake on glucose input into the blood from the gut, are estimated from the CMs. The outputs of CMs, along with previous glucose measurements, are fed to a NN, which provides short-term prediction of glucose values. For comparative reasons two different NN architectures have been tested: a Feed-Forward NN (FFNN) trained with the back-propagation algorithm with adaptive learning rate and momentum, and a Recurrent NN (RNN), trained with the Real Time Recurrent Learning (RTRL) algorithm. The results indicate that the best prediction performance can be achieved by the use of RNN.

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Peatlands are widely exploited archives of paleoenvironmental change. We developed and compared multiple transfer functions to infer peatland depth to the water table (DWT) and pH based on testate amoeba (percentages, or presence/absence), bryophyte presence/absence, and vascular plant presence/absence data from sub-alpine peatlands in the SE Swiss Alps in order to 1) compare the performance of single-proxy vs. multi-proxy models and 2) assess the performance of presence/absence models. Bootstrapping cross-validation showing the best performing single-proxy transfer functions for both DWT and pH were those based on bryophytes. The best performing transfer functions overall for DWT were those based on combined testate amoebae percentages, bryophytes and vascular plants; and, for pH, those based on testate amoebae and bryophytes. The comparison of DWT and pH inferred from testate amoeba percentages and presence/absence data showed similar general patterns but differences in the magnitude and timing of some shifts. These results show new directions for paleoenvironmental research, 1) suggesting that it is possible to build good-performing transfer functions using presence/absence data, although with some loss of accuracy, and 2) supporting the idea that multi-proxy inference models may improve paleoecological reconstruction. The performance of multi-proxy and single-proxy transfer functions should be further compared in paleoecological data.

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Researchers largely agree that there is a positive relationship between achievement motivation and athletic performance, which is why the achievement motive is viewed as a potential criterion for talent. However, the underlying mechanism behind this relationship remains unclear. In talent and performance models, main effect, mediator and moderator models have been suggested. A longitudinal study was carried out among 140 13-year-old football talents, using structural equation modelling to determine which model best explains how hope for success (HS) and fear of failure (FF), which are the aspects of the achievement motive, motor skills and abilities that affect performance. Over a period of half a year, HS can to some extent explain athletic performance, but this relationship is not mediated by the volume of training, sport-specific skills or abilities, nor is the achievement motive a moderating variable. Contrary to expectations, FF does not explain any part of performance. Aside from HS, however, motor abilities and in particular skills also predict a significant part of performance. The study confirms the widespread assumption that the development of athletic performance in football depends on multiple factors, and in particular that HS is worth watching in the medium term as a predictor of talent.

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Since 2010, the client base of online-trading service providers has grown significantly. Such companies enable small investors to access the stock market at advantageous rates. Because small investors buy and sell stocks in moderate amounts, they should consider fixed transaction costs, integral transaction units, and dividends when selecting their portfolio. In this paper, we consider the small investor’s problem of investing capital in stocks in a way that maximizes the expected portfolio return and guarantees that the portfolio risk does not exceed a prescribed risk level. Portfolio-optimization models known from the literature are in general designed for institutional investors and do not consider the specific constraints of small investors. We therefore extend four well-known portfolio-optimization models to make them applicable for small investors. We consider one nonlinear model that uses variance as a risk measure and three linear models that use the mean absolute deviation from the portfolio return, the maximum loss, and the conditional value-at-risk as risk measures. We extend all models to consider piecewise-constant transaction costs, integral transaction units, and dividends. In an out-of-sample experiment based on Swiss stock-market data and the cost structure of the online-trading service provider Swissquote, we apply both the basic models and the extended models; the former represent the perspective of an institutional investor, and the latter the perspective of a small investor. The basic models compute portfolios that yield on average a slightly higher return than the portfolios computed with the extended models. However, all generated portfolios yield on average a higher return than the Swiss performance index. There are considerable differences between the four risk measures with respect to the mean realized portfolio return and the standard deviation of the realized portfolio return.

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Regional and rural development policies in Europe increasingly emphasize entrepreneurship to mobilize the endogenous economic potential of rural territories. This study develops a concept to quantify entrepreneurship as place-dependent local potential to examine its impact on the local economic performance of rural territories in Switzerland. The short-to-medium-term impact of entrepreneurship on the economic performance of 1706 rural municipalities in Switzerland is assessed by applying three spatial random effects models. Results suggest a generally positive relationship between entrepreneurship and local development: rural municipalities with higher entrepreneurial potential generally show higher business tax revenues per capita and a lower share of social welfare cases among the population, although the impact on local employment is less clear. The explanatory power of entrepreneurship in all three models, however, was only moderate. This finding suggests that political expectations of fostering entrepreneurship to boost endogenous rural development in the short-to-medium term should be damped.

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Abstract This article disputes some basic questions concerning the coordination of seventeenth century sacred music, approaching the phenomenon through a musical species of particular interest, though largely unstudied from a performance practice point of view. Roman polychorality with its specific performing conditions offers an illuminating perspective on principles of musical direction and interaction which differ significantly from our modern access path towards these topics. The inquiry ranges from basics of performance (such as sheet music, rehearsals, direction technics, models and stylistic conditioning of the performers) over the concrete role of the maestro di cappella as well as the tactus as cornerstones of sacred music practice, up to the philosophical content the particular 'system of values', shining though this overall picture, seems to represent. On this groundwork the essay opens a discussion on conventions which have remained literally unchallenged by generations of researchers and performers.

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It is system dynamics that determines the function of cells, tissues and organisms. To develop mathematical models and estimate their parameters are an essential issue for studying dynamic behaviors of biological systems which include metabolic networks, genetic regulatory networks and signal transduction pathways, under perturbation of external stimuli. In general, biological dynamic systems are partially observed. Therefore, a natural way to model dynamic biological systems is to employ nonlinear state-space equations. Although statistical methods for parameter estimation of linear models in biological dynamic systems have been developed intensively in the recent years, the estimation of both states and parameters of nonlinear dynamic systems remains a challenging task. In this report, we apply extended Kalman Filter (EKF) to the estimation of both states and parameters of nonlinear state-space models. To evaluate the performance of the EKF for parameter estimation, we apply the EKF to a simulation dataset and two real datasets: JAK-STAT signal transduction pathway and Ras/Raf/MEK/ERK signaling transduction pathways datasets. The preliminary results show that EKF can accurately estimate the parameters and predict states in nonlinear state-space equations for modeling dynamic biochemical networks.

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This paper reports a comparison of three modeling strategies for the analysis of hospital mortality in a sample of general medicine inpatients in a Department of Veterans Affairs medical center. Logistic regression, a Markov chain model, and longitudinal logistic regression were evaluated on predictive performance as measured by the c-index and on accuracy of expected numbers of deaths compared to observed. The logistic regression used patient information collected at admission; the Markov model was comprised of two absorbing states for discharge and death and three transient states reflecting increasing severity of illness as measured by laboratory data collected during the hospital stay; longitudinal regression employed Generalized Estimating Equations (GEE) to model covariance structure for the repeated binary outcome. Results showed that the logistic regression predicted hospital mortality as well as the alternative methods but was limited in scope of application. The Markov chain provides insights into how day to day changes of illness severity lead to discharge or death. The longitudinal logistic regression showed that increasing illness trajectory is associated with hospital mortality. The conclusion is reached that for standard applications in modeling hospital mortality, logistic regression is adequate, but for new challenges facing health services research today, alternative methods are equally predictive, practical, and can provide new insights. ^

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Purpose Musicians often suffer injuries related to their music playing. Therefore, some use the Alexander Technique (AT), a psycho-physical method that helps to release unnecessary muscle tension and re-educates non-beneficial movement patterns through enhanced kinaesthetic awareness. According to a recent review AT may be effective for chronic back pain. This review aimed to evaluate the evidence for the effectiveness of AT lessons on music performance and musicians’ health and well-being. Methods The following electronic databases were searched up to July 2012 for relevant literature: PUBMED, Google Scholar, CINAHL and EMBASE. The search criteria were "Alexander technique" AND "music*" [all fields]. References were searched, and experts and societies of AT or musicians' medicine contacted for further publications. Results 100 studies were identified. 35 studies were included for further analysis, 5 of which were randomised controlled trials (RCTs), 5 controlled but not randomised, 5 not controlled, 5 qualitative case studies, 2 mixed-models (RCT and case studies), 7 surveys, 4 qualitative case reports and 2 unpublished pilot studies. 13 to 72 musicians participated per RCT. In 5 RCTs AT groups received between 12 and 20 one-to-one lessons. In 4 RCTs control groups received no interventions. Primary outcomes were performance anxiety, performance, "use" as well as respiratory function and pain. Performance anxiety decreased by AT in 3 of 4 RCTs. Music performance was improved by AT in 1 RCT, yet in 2 RCTs comparing neurofeedback (NF) to AT, only NF showed improvements. Conclusions To investigate the effectiveness of AT in musicians a variety of study designs and outcome measures have been used. Evidence from RCTs suggests that AT may improve performance anxiety in musicians. Effects on music performance, body use and respiratory function yet remain inconsistent. Future trials with well-established study designs are warranted to further and more reliably explore the potential of AT as a relatively low cost and low risk method in the interest of musicians.

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The ability of the one-dimensional lake model FLake to represent the mixolimnion temperatures for tropical conditions was tested for three locations in East Africa: Lake Kivu and Lake Tanganyika's northern and southern basins. Meteorological observations from surrounding automatic weather stations were corrected and used to drive FLake, whereas a comprehensive set of water temperature profiles served to evaluate the model at each site. Careful forcing data correction and model configuration made it possible to reproduce the observed mixed layer seasonality at Lake Kivu and Lake Tanganyika (northern and southern basins), with correct representation of both the mixed layer depth and water temperatures. At Lake Kivu, mixolimnion temperatures predicted by FLake were found to be sensitive both to minimal variations in the external parameters and to small changes in the meteorological driving data, in particular wind velocity. In each case, small modifications may lead to a regime switch, from the correctly represented seasonal mixed layer deepening to either completely mixed or permanently stratified conditions from similar to 10 m downwards. In contrast, model temperatures were found to be robust close to the surface, with acceptable predictions of near-surface water temperatures even when the seasonal mixing regime is not reproduced. FLake can thus be a suitable tool to parameterise tropical lake water surface temperatures within atmospheric prediction models. Finally, FLake was used to attribute the seasonal mixing cycle at Lake Kivu to variations in the near-surface meteorological conditions. It was found that the annual mixing down to 60m during the main dry season is primarily due to enhanced lake evaporation and secondarily to the decreased incoming long wave radiation, both causing a significant heat loss from the lake surface and associated mixolimnion cooling.

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Contemporary models of self-regulated learning emphasize the role of distal motivational factors for student's achievement, on the one side, and the proximal role of metacognitive monitoring and control for learning and test outcomes, on the other side. In the present study, two larger samples of elementary school children (9- and 11-year-olds) were included and their mastery-oriented motivation, metacognitive monitoring and control skills were integrated into structural equation models testing and comparing the relative impact of these different constituents for self-regulated learning. For one, results indicate that the factorial structure of monitoring, control and mastery motivation was invariant across the two age groups. Of specific interest was the finding that there were age-dependent structural links between monitoring, control, and test performance (closer links in the older compared to the younger children), with high confidence yielding a direct and positive effect on test performance and a direct and negative effect on adequate control behavior in the achievement test. Mastery-oriented motivation was not found to be substantially associated with monitoring (confidence), control (detection and correction of errors), or test performance underlining the importance of proximal, metacognitive factors for test performance in elementary school children.

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The present study investigated the relationship between psychometric intelligence and temporal resolution power (TRP) as simultaneously assessed by auditory and visual psychophysical timing tasks. In addition, three different theoretical models of the functional relationship between TRP and psychometric intelligence as assessed by means of the Adaptive Matrices Test (AMT) were developed. To test the validity of these models, structural equation modeling was applied. Empirical data supported a hierarchical model that assumed auditory and visual modality-specific temporal processing at a first level and amodal temporal processing at a second level. This second-order latent variable was substantially correlated with psychometric intelligence. Therefore, the relationship between psychometric intelligence and psychophysical timing performance can be explained best by a hierarchical model of temporal information processing.

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Introduction Research has shown that individuals infer their group-efficacy beliefs from the groups’ abilities to perform in specific tasks. Group abilities also seem to affect team members’ performance motivation adding a psychological advantage to teams already high on task relevant abilities. In a recent study we found the effect of group abilities on individual performance motivation to be partially mediated by the team members’ individual group-efficacy beliefs which is an example of how attributes on a group-level can be affecting individual-level parameters. Objectives The study aimed at testing the possibility to reduce the direct and mediated effects of low group abilities on performance motivation by augmenting the visibility of individual contributions to group performances via the inclusion of a separate ranking on individual performances. Method Forty-seven students (M=22.83 years, SD=2.83, 34% women) of the University of Bern participated in the study. At three collection points (t1-3) subjects were provided information about fictive team members with whom they had to imagine performing a group triathlon. Three values (low, medium, high) of the other team members’ abilities to perform in their parts of the triathlon (swimming and biking) were combined in a 3x3 full factorial design yielding nine groups with different ability profiles. At t1 subjects were asked to rate their confidence that the teams would perform well in the triathlon task, at t2 and t3 subjects were asked how motivated they were to perform at their best in the respective groups. At t3 the presence of an individual performance ranking was mentioned in the cover story. Mixed linear models (SPSS) and structural equation models for complex survey data (Mplus) were specified to estimate the effects of the individual performance rankings on the relationship between group-efficacy beliefs and performance motivation. Results A significant interaction effect for individual group-efficacy beliefs and the triathlon condition on performance motivation was found; the effect of group-efficacy beliefs on performance motivation being smaller with individual performance rankings available. The partial mediation of group attributes on performance motivation by group-efficacy beliefs disappeared with the announcement of individual performance rankings. Conclusion In teams low in task relevant abilities the disadvantageous effect of group-efficacy beliefs on performance motivation might be reduced by providing means of evaluating individual performances apart from a group’s overall performance. While it is believed that a common group goal is a core criterion for a well performing sport group future studies should also aim at the possible benefit of individualized goal setting in groups.

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Since 2010, the client base of online-trading service providers has grown significantly. Such companies enable small investors to access the stock market at advantageous rates. Because small investors buy and sell stocks in moderate amounts, they should consider fixed transaction costs, integral transaction units, and dividends when selecting their portfolio. In this paper, we consider the small investor’s problem of investing capital in stocks in a way that maximizes the expected portfolio return and guarantees that the portfolio risk does not exceed a prescribed risk level. Portfolio-optimization models known from the literature are in general designed for institutional investors and do not consider the specific constraints of small investors. We therefore extend four well-known portfolio-optimization models to make them applicable for small investors. We consider one nonlinear model that uses variance as a risk measure and three linear models that use the mean absolute deviation from the portfolio return, the maximum loss, and the conditional value-at-risk as risk measures. We extend all models to consider piecewise-constant transaction costs, integral transaction units, and dividends. In an out-of-sample experiment based on Swiss stock-market data and the cost structure of the online-trading service provider Swissquote, we apply both the basic models and the extended models; the former represent the perspective of an institutional investor, and the latter the perspective of a small investor. The basic models compute portfolios that yield on average a slightly higher return than the portfolios computed with the extended models. However, all generated portfolios yield on average a higher return than the Swiss performance index. There are considerable differences between the four risk measures with respect to the mean realized portfolio return and the standard deviation of the realized portfolio return.

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Introduction Research has shown that individuals infer their group-efficacy beliefs from the groups’ abilities to perform in specific tasks. Group abilities also seem to affect team members’ performance motivation adding a psychological advantage to teams already high on task relevant abilities. In a recent study we found the effect of group abilities on individual performance motivation to be partially mediated by the team members’ individual group-efficacy beliefs which is an example of how attributes on a group-level can be affecting individual-level parameters. Objectives The study aimed at testing the possibility to reduce the direct and mediated effects of low group abilities on performance motivation by augmenting the visibility of individual contributions to group performances via the inclusion of a separate ranking on individual performances. Method Forty-seven students (M=22.83 years, SD=2.83, 34% women) of the University of Bern participated in the study. At three collection points (t1-3) subjects were provided information about fictive team members with whom they had to imagine performing a group triathlon. Three values (low, medium, high) of the other team members’ abilities to perform in their parts of the triathlon (swimming and biking) were combined in a 3x3 full factorial design yielding nine groups with different ability profiles. At t1 subjects were asked to rate their confidence that the teams would perform well in the triathlon task, at t2 and t3 subjects were asked how motivated they were to perform at their best in the respective groups. At t3 the presence of an individual performance ranking was mentioned in the cover story. Mixed linear models (SPSS) and structural equation models for complex survey data (Mplus) were specified to estimate the effects of the individual performance rankings on the relationship between group-efficacy beliefs and performance motivation. Results A significant interaction effect for individual group-efficacy beliefs and the triathlon condition on performance motivation was found; the effect of group-efficacy beliefs on performance motivation being smaller with individual performance rankings available. The partial mediation of group attributes on performance motivation by group-efficacy beliefs disappeared with the announcement of individual performance rankings. Conclusion In teams low in task relevant abilities the disadvantageous effect of group-efficacy beliefs on performance motivation might be reduced by providing means of evaluating individual performances apart from a group’s overall performance. While it is believed that a common group goal is a core criterion for a well performing sport group future studies should also aim at the possible benefit of individualized goal setting in groups.