System enables more complete calibrations of dynamic-pressure transducers

Absolute pressure calibration system using a Michelson interferometer calibrates phase characteristics and pressure sensitivities of the transducers that monitor acoustic or aerodynamic pressure fields. The interferometer uses a helium-neon laser light source and interchangeable acoustic signal generators to produce acoustic waves

Bundles and Range Strategies: The Case of Telecom Operators

Against a background of competition and the generalisation of IP that characterises the field of electronic communications, the concept of the "bundle" has resulted in the emergence of "triple play", and even "quadruple play." This paper offers an overview of the growth of this phenomenon by introducing a distinction between the basic components of multiplay strategies and the diverse range of functions that can be linked to these strategies.Bundle; range strategy; triple play; quadruple play

Quantifying the time course of visual object processing using ERPs: it's time to up the game

Hundreds of studies have investigated the early ERPs to faces and objects using scalp and intracranial recordings. The vast majority of these studies have used uncontrolled stimuli, inappropriate designs, peak measurements, poor figures, and poor inferential and descriptive group statistics. These problems, together with a tendency to discuss any effect p < 0.05 rather than to report effect sizes, have led to a research field very much qualitative in nature, despite its quantitative inspirations, and in which predictions do not go beyond condition A > condition B. Here we describe the main limitations of face and object ERP research and suggest alternative strategies to move forward. The problems plague intracranial and surface ERP studies, but also studies using more advanced techniques – e.g., source space analyses and measurements of network dynamics, as well as many behavioral, fMRI, TMS, and LFP studies. In essence, it is time to stop amassing binary results and start using single-trial analyses to build models of visual perception

Computational linear algebra over finite fields

We present here algorithms for efficient computation of linear algebra problems over finite fields

Mobile payments: moving towards a wallet in the cloud?

This article deals with mobile payments in developed countries. Even though it only accounts for a relatively small share of the market (between 10% and 20%), mobile payment merits in-depth analysis in developed countries as there are many economic and technological issues that still need to be addressed.mobile payments, NFC

Efficient Decomposition of Dense Matrices over GF(2)

In this work we describe an efficient implementation of a hierarchy of algorithms for the decomposition of dense matrices over the field with two elements (GF(2)). Matrix decomposition is an essential building block for solving dense systems of linear and non-linear equations and thus much research has been devoted to improve the asymptotic complexity of such algorithms. In this work we discuss an implementation of both well-known and improved algorithms in the M4RI library. The focus of our discussion is on a new variant of the M4RI algorithm - denoted MMPF in this work -- which allows for considerable performance gains in practice when compared to the previously fastest implementation. We provide performance figures on x86_64 CPUs to demonstrate the viability of our approach

Symmetric indefinite triangular factorization revealing the rank profile matrix

We present a novel recursive algorithm for reducing a symmetric matrix to a triangular factorization which reveals the rank profile matrix. That is, the algorithm computes a factorization $\mathbf{P}^T\mathbf{A}\mathbf{P} = \mathbf{L}\mathbf{D}\mathbf{L}^T$ where $\mathbf{P}$ is a permutation matrix, $\mathbf{L}$ is lower triangular with a unit diagonal and $\mathbf{D}$ is symmetric block diagonal with $1{\times}1$ and $2{\times}2$ antidiagonal blocks. The novel algorithm requires $O(n^2r^{\omega-2})$ arithmetic operations. Furthermore, experimental results demonstrate that our algorithm can even be slightly more than twice as fast as the state of the art unsymmetric Gaussian elimination in most cases, that is it achieves approximately the same computational speed. By adapting the pivoting strategy developed in the unsymmetric case, we show how to recover the rank profile matrix from the permutation matrix and the support of the block-diagonal matrix. There is an obstruction in characteristic $2$ for revealing the rank profile matrix which requires to relax the shape of the block diagonal by allowing the 2-dimensional blocks to have a non-zero bottom-right coefficient. This relaxed decomposition can then be transformed into a standard $\mathbf{P}\mathbf{L}\mathbf{D}\mathbf{L}^T\mathbf{P}^T$ decomposition at a negligible cost

Computing the Kalman form

We present two algorithms for the computation of the Kalman form of a linear control system. The first one is based on the technique developed by Keller-Gehrig for the computation of the characteristic polynomial. The cost is a logarithmic number of matrix multiplications. To our knowledge, this improves the best previously known algebraic complexity by an order of magnitude. Then we also present a cubic algorithm proven to more efficient in practice.Comment: 10 page

Robust correlation analyses: false positive and power validation using a new open source Matlab toolbox

Pearson’s correlation measures the strength of the association between two variables. The technique is, however, restricted to linear associations and is overly sensitive to outliers. Indeed, a single outlier can result in a highly inaccurate summary of the data. Yet, it remains the most commonly used measure of association in psychology research. Here we describe a free Matlab(R) based toolbox (http://sourceforge.net/projects/robustcorrtool/) that computes robust measures of association between two or more random variables: the percentage-bend correlation and skipped-correlations. After illustrating how to use the toolbox, we show that robust methods, where outliers are down weighted or removed and accounted for in significance testing, provide better estimates of the true association with accurate false positive control and without loss of power. The different correlation methods were tested with normal data and normal data contaminated with marginal or bivariate outliers. We report estimates of effect size, false positive rate and power, and advise on which technique to use depending on the data at hand