Philips

About: Philips is a company organization based out in Vantaa, Finland. It is known for research contribution in the topics: Signal & Layer (electronics). The organization has 68260 authors who have published 99663 publications receiving 1882329 citations. The organization is also known as: Koninklijke Philips Electronics N.V. & Royal Philips Electronics.

Evidence for a Soft Nuclear Equation-of-State from Kaon Production in Heavy-Ion Collisions

Abstract: The production of pions and kaons has been measured in ${}^{197}\mathrm{Au}{+}^{197}\mathrm{Au}$ collisions at beam energies from 0.6 to $1.5A\mathrm{GeV}$ with the kaon spectrometer at SIS/GSI. The ${K}^{+}$ meson multiplicity per nucleon is enhanced in $\mathrm{Au}+\mathrm{Au}$ collisions by factors up to 6 relative to $\mathrm{C}+\mathrm{C}$ reactions, whereas the corresponding pion ratio is reduced. The ratio of the ${K}^{+}$ meson excitation functions for $\mathrm{Au}+\mathrm{Au}$ and $\mathrm{C}+\mathrm{C}$ collisions increases with decreasing beam energy. This behavior is expected for a soft nuclear equation-of-state.

Ambipolar Organic Field-Effect Transistors Based on a Solution-Processed Methanofullerene

Abstract: Organic field-effect transistors (OFETs, see Figure), based on the solution-processible methanofullerene [6,6]-phenyl-C-61-butyric acid methyl ester (PCBM), have been fabricated in a bottom-contact device configuration using gold electrodes. The OFET functions either as a p- or n-channel device, depending upon the bias conditions. This is the first example of ambipolar charge transport in FETs based on pristine PCBM.

The gridding method for image reconstruction by Fourier transformation

Abstract: The authors explore a computational method for reconstructing an n-dimensional signal f from a sampled version of its Fourier transform f/spl circ/. The method involves a window function w/spl circ/ and proceeds in three steps. First, the convolution g/spl circ/=w/spl circ/*f/spl circ/ is computed numerically on a Cartesian grid, using the available samples of f/spl circ/. Then, g=wf is computed via the inverse discrete Fourier transform, and finally f is obtained as g/w. Due to the smoothing effect of the convolution, evaluating w/spl circ/*f/spl circ/ is much less error prone than merely interpolating f/spl circ/. The method was originally devised for image reconstruction in radio astronomy, but is actually applicable to a broad range of reconstructive imaging methods, including magnetic resonance imaging and computed tomography. In particular, it provides a fast and accurate alternative to the filtered backprojection. The basic method has several variants with other applications, such as the equidistant resampling of arbitrarily sampled signals or the fast computation of the Radon (Hough) transform. >

Single-accelerometer-based daily physical activity classification

Abstract: In this study, a single tri-axial accelerometer placed on the waist was used to record the acceleration data for human physical activity classification. The data collection involved 24 subjects performing daily real-life activities in a naturalistic environment without researchers’ intervention. For the purpose of assessing customers’ daily energy expenditure, walking, running, cycling, driving, and sports were chosen as target activities for classification. This study compared a Bayesian classification with that of a Decision Tree based approach. A Bayes classifier has the advantage to be more extensible, requiring little effort in classifier retraining and software update upon further expansion or modification of the target activities. Principal components analysis was applied to remove the correlation among features and to reduce the feature vector dimension. Experiments using leave-one-subject-out and 10-fold cross validation protocols revealed a classification accuracy of ~80%, which was comparable with that obtained by a Decision Tree classifier.

Quantile based noise estimation for spectral subtraction and Wiener filtering

Abstract: Elimination of additive noise from a speech signal is a fundamental problem in audio signal processing. In this paper we restrict our considerations to the case where only a single microphone recording of the noisy signal is available. The algorithms which we investigate proceed in two steps. First, the noise power spectrum is estimated. A method based on temporal quantiles in the power spectral domain is proposed and compared with pause detection and recursive averaging. The second step is to eliminate the estimated noise from the observed signal by spectral subtraction or Wiener filtering. The database used in the experiments comprises 6034 utterances of German digits and digit strings by 770 speakers in 10 different cars. Without noise reduction, we obtain an error rate of 11.7%. Quantile based noise estimation and Wiener filtering reduce the error rate to 8.6%. Similar improvements are achieved in an experiment with artificial, non-stationary noise.