How humans perform duration judgments with multisensory stimuli is an ongoing debate. Here, we investigated how sub-second duration judgments are achieved by asking participants to compare the duration of a continuous...
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How humans perform duration judgments with multisensory stimuli is an ongoing debate. Here, we investigated how sub-second duration judgments are achieved by asking participants to compare the duration of a continuous sound to the duration of an empty interval in which onset and offset were marked by signals of different modalities using all combinations of visual, auditory and tactile stimuli. The pattern of perceived durations across five stimulus durations (ranging from 100 ms to 900 ms) follows the Vierordt Law. Furthermore, intervals with a sound as onset (audio-visual, audio-tactile) are perceived longer than intervals with a sound as offset. No modality ordering effect is found for visualtactile intervals. To infer whether a single modality-independent or multiple modality-dependent time-keeping mechanisms exist we tested whether perceived duration follows a summative or a multiplicative distortion pattern by fitting a model to all modality combinations and durations. The results confirm that perceived duration depends on sensory latency (summative distortion). Instead, we did not find evidence for multiplicative distortions. The results of the model and the behavioural data support the concept of a single time-keeping mechanism that allows for judgments of durations marked by multisensory stimuli. (C) 2013 Elsevier B.V. All rights reserved.
In this paper, we introduce a generalized Liu estimator and jackknifed Liu estimator in a linear regression model with correlated or heteroscedastic errors. Therefore, we extend the Liu estimator. Under the mean squar...
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In this paper, we introduce a generalized Liu estimator and jackknifed Liu estimator in a linear regression model with correlated or heteroscedastic errors. Therefore, we extend the Liu estimator. Under the mean square error（MSE）, the jackknifed estimator is superior to the Liu estimator and the jackknifed ridge estimator. We also give a method to select the biasing parameter for d. Furthermore, a numerical example is given to illustvate these theoretical results.
Mass fraction of ash is a quality criterion for determining the botanical origin of honey At present, this parameter is generally being replaced by the measurement of electrical conductivity (K). The value K depends o...
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Mass fraction of ash is a quality criterion for determining the botanical origin of honey At present, this parameter is generally being replaced by the measurement of electrical conductivity (K). The value K depends on the ash and acid content of honey;the higher their content, the higher the resulting conductivity A linear regression model for the relationship between ash and electrical conductivity has been established for Slovenian honey by analysing 290 samples of Slovenian honey (including acacia, lime, chestnut, spruce, fir, multifloral and mixed forest honeydew honey). The obtained model differs from the one proposed by the International Honey Commission (IHC) in the slope, but not in the section part of the relation formula. Therefore, the Slovenian model is recommended when calculating the ash mass fraction from the results of electrical conductivity in samples of Slovenian honey.
This study proposes a revised Importance-Performance Analysis (IPA) approach combined with a regressionmodel due to the strong relationship between the 15 paired variables regarding seniors’ perceived importance of ...
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This study proposes a revised Importance-Performance Analysis (IPA) approach combined with a regressionmodel due to the strong relationship between the 15 paired variables regarding seniors’ perceived importance of motivations and performance experiences. Findings suggest that a combination of the traditional IPA results and predicted values (lines) from a linearregression analysis leads to a better understanding of the customers’ perceptions and behaviors in the target market, which in this study is the senior travel market. Future research should be undertaken to validate the revised IPA model suggested in this study using different constructs/variables in different markets.
One of the biggest problems that software organizations encounter is specifying the resources required and the duration of projects. Organizations that record the number of defects and the effort spent on fixing these...
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ISBN:
(纸本)9781479979196
One of the biggest problems that software organizations encounter is specifying the resources required and the duration of projects. Organizations that record the number of defects and the effort spent on fixing these defects are able to correctly predict the latent defects in the product and the effort required to remove these latent defects. The use of reliability models reported in the literature is typical to achieve this prediction, but the number of studies that report defect prediction models for iterative software development is scarce. In this article we present a case study which predicts the defectiveness of new releases in an iterative, civil project where defect arrival phase data is not recorded. We investigated linear regression model and Rayleigh model one of the statistical reliability model that contain time information, to predict the module level and project level defectiveness of the new releases of an iterative project through the iterations. The models were created by using 29 successive releases for the project level and 15 successive releases for the module level defect density data. This article explains the procedures that were applied to generate the defectiveness models and the lessons learned from the studies.
The paper intends to construct an array of advertising tools and tests the influence of the same in creating awareness, providing information, and enhancing knowledge of female consumers. The constructs focus on testi...
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In this article, we consider quasi-minimax estimation in the linear regression model where some covariates are measured with additive errors. When measurement errors are directly ignored the minimax risk of the result...
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In this article, we consider quasi-minimax estimation in the linear regression model where some covariates are measured with additive errors. When measurement errors are directly ignored the minimax risk of the resulting estimator can be large. By correcting the attenuation we propose a penalized quadratic risk function. A simulation study is conducted to illustrate the performance of the proposed estimators.
An approach is described for viewing the interrelationship between different variables and also tracing the sources of pollution of groundwater of north Chennai (India). The data set of 43 variables which include majo...
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An approach is described for viewing the interrelationship between different variables and also tracing the sources of pollution of groundwater of north Chennai (India). The data set of 43 variables which include major ions, minor ions and trace metal speciation (Cu, Pb, Cd and Zn) collected during the pre-monsoon and post-monsoon seasons of the year 2000-2001, was subjected to R-mode factor analysis to comprehend the distribution pattern of the said variables. It was found that first factor measures salinity and hardness which explained 19.12% of the total variance (comprised of variables EC, TDS, Na+, K+, Ca2+, Mg2+, total hardness, Cl- and SO42-) during pre-monsoon, while it was 25.08% during post-monsoon. The second and third factors were attributed to speciation of zinc and copper ions during both pre-monsoon and post-monsoon. Although there were two more factors, loaded with speciation parameters of lead and cadmium, the variance of them were less than 10%. From this study it is seen that sea water intrusion, municipal solid waste disposal are the identified sources of component of pollution. The importance of metal ions is taking a secondary role and the anthropogenic origin-industrial activity, is the reason in the evaluation of pollution status as they come in the second, third, fourth and fifth factors. As the trace metal speciation was grouped in separate factors, linear regression model (LRM) with correlation analysis was applied to check its validity for prediction of speciation and to apply LRM for rapid monitoring of water pollution.
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