Internal representations of temporal statistics and feedback calibrate motor-sensory interval timing.

Humans have been shown to adapt to the temporal statistics of timing tasks so as to optimize the accuracy of their responses, in agreement with the predictions of Bayesian integration. This suggests that they build an internal representation of both the experimentally imposed distribution of time intervals (the prior) and of the error (the loss function). The responses of a Bayesian ideal observer depend crucially on these internal representations, which have only been previously studied for simple distributions. To study the nature of these representations we asked subjects to reproduce time intervals drawn from underlying temporal distributions of varying complexity, from uniform to highly skewed or bimodal while also varying the error mapping that determined the performance feedback. Interval reproduction times were affected by both the distribution and feedback, in good agreement with a performance-optimizing Bayesian observer and actor model. Bayesian model comparison highlighted that subjects were integrating the provided feedback and represented the experimental distribution with a smoothed approximation. A nonparametric reconstruction of the subjective priors from the data shows that they are generally in agreement with the true distributions up to third-order moments, but with systematically heavier tails. In particular, higher-order statistical features (kurtosis, multimodality) seem much harder to acquire. Our findings suggest that humans have only minor constraints on learning lower-order statistical properties of unimodal (including peaked and skewed) distributions of time intervals under the guidance of corrective feedback, and that their behavior is well explained by Bayesian decision theory.

Boundary effects on the vibration statistics of a random plate

This paper considers the estimation of statistics of displacement of a vibrating rectangular plate with random wave scatterers. The influence of uncertainty is investigated using point impedance theory. Coherent boundary effects are seen, which decrease when the number of scatterers increases. The boundary effect is investigated using images and the first side and corner reflections are found to be a minimum requirement to estimate the spatial correlation. Statistics for point driven response are investigated under the assumption that the statistics of the natural frequencies follow those of the Gaussian Orthogonal Ensemble (GOE). The estimates are compared with Monte Carlo simulation results, and they show good agreement. © 2012 Elsevier Ltd. All rights reserved.

Comparison of les to LDA and PIV measurements of a small scale high speed coflowing jet

Measurements and predictions are made of a short cowl co-flowing jet with a bypass ratio of 8:1. The Reynolds number for computations and measurements are matched at 300,000 and the Mach numbers representative of realistic jet conditions with core and co flow velocities of 240m/s and 216m/s respectively. The low Reynolds number of the measurements makes the case well suited to the assessment of large eddy resolving computational strategies. Also, the nozzle concentricity was carefully controlled to deal with the emerging metastability issues of jets with coflow. Measurements of mean quantities and turbulence statistics are made using both two dimensional coincident LDA and PIV systems. The computational simulations are completed on a modest 12×106 mesh. The simulation is now being run on a 50×106 mesh using hybrid RANSNLES (Numerical Large Eddy Simulation). Close to the nozzle wall a k-l RANS model is used. For an axisymmetric jet, comparison is made between simulations which use NLES, RANSNLES and also a simple imposed velocity profile where the nozzle is not modeled. The use of a near wall RANS model is shown to be beneficial. When compared with the measurements the NLES results are encouraging. Copyright © 2008 by the American Institute of Aeronautics and Astronautics, Inc. All rights reserved.

Review of computational aeroacoustics for application in electronics cooler noise

A review of computational aeroacoustics (CCA) was made for application in electronics cooler noise. Computational aeroacoustics encompasses all numerical methods where the purposes is to predict the noise emissions from a simulated flow. Numerical simulation of the flow inside and around heat sinks and fans can lead to a prediction of the emitted noise while they are still in the design phase. Direct CCA is theoretically the best way to predict flow-based acoustic phenomena numerically. It is typically used only for low-frequency sound prediction. The boundary element method offers low computational cost and does not use a computational grid, but instead use vortex-surface calculations to determine tonal noise. Axial fans are commonly used to increase the airflow and thus the heat transfer over the heat sinks within the computer cases. Very detailed source simulations in the fan and heat sink region coupled with the use of analogy methods could result in excellent simulation results with a reasonable computational effort.

Uncertainty increases pain: evidence for a novel mechanism of pain modulation involving the periaqueductal gray.

Predictions about sensory input exert a dominant effect on what we perceive, and this is particularly true for the experience of pain. However, it remains unclear what component of prediction, from an information-theoretic perspective, controls this effect. We used a vicarious pain observation paradigm to study how the underlying statistics of predictive information modulate experience. Subjects observed judgments that a group of people made to a painful thermal stimulus, before receiving the same stimulus themselves. We show that the mean observed rating exerted a strong assimilative effect on subjective pain. In addition, we show that observed uncertainty had a specific and potent hyperalgesic effect. Using computational functional magnetic resonance imaging, we found that this effect correlated with activity in the periaqueductal gray. Our results provide evidence for a novel form of cognitive hyperalgesia relating to perceptual uncertainty, induced here by vicarious observation, with control mediated by the brainstem pain modulatory system.

A systematic approach for improving the quality of official statistics: Case of Korean information and telecommunication industry

With the rapid growth of information and communication technology (ICT) in Korea, there was a need to improve the quality of official ICT statistics. In order to do this, various factors had to be considered, such as the quality of surveying, processing, and output as well as the reputation of the statistical agency. We used PLS estimation to determine how these factors might influence customer satisfaction. Furthermore, through a comparison of associated satisfaction indices, we provided feedback to the responsible statistics agency. It appears that our model can be used as a tool for improving the quality of official ICT statistics. © 2008 Elsevier B.V. All rights reserved.

Statistics anxiety, trait anxiety, learning behavior, and academic performance

The present study investigated the relationship between statistics anxiety, individual characteristics (e.g., trait anxiety and learning strategies), and academic performance. Students enrolled in a statistics course in psychology (N=147) filled in a questionnaire on statistics anxiety, trait anxiety, interest in statistics, mathematical selfconcept, learning strategies, and procrastination. Additionally, their performance in the examination was recorded. The structural equation model showed that statistics anxiety held a crucial role as the strongest direct predictor of performance. Students with higher statistics anxiety achieved less in the examination and showed higher procrastination scores. Statistics anxiety was related indirectly to spending less effort and time on learning. Trait anxiety was related positively to statistics anxiety and, counterintuitively, to academic performance. This result can be explained by the heterogeneity of the measure of trait anxiety. The part of trait anxiety that is unrelated to the specific part of statistics anxiety correlated positively with performance.