Threshold behaviour of L x-ray excitation in Xe - Ag collisions

In the collision system Xe - Ag, the thresholds for excitation of quasimolecular L radiation and characteristic Ag L radiation have been found to lie at about 5 MeV and 1 MeV, respectively. These results are discussed on the basis of ab initio calculations of the screened interaction potential and the electron-correlation diagram.

Approximate solutions and error estimates for a Stokes boundary value problem

The aim of this paper is the numerical treatment of a boundary value problem for the system of Stokes' equations. For this we extend the method of approximate approximations to boundary value problems. This method was introduced by V. Maz'ya in 1991 and has been used until now for the approximation of smooth functions defined on the whole space and for the approximation of volume potentials. In the present paper we develop an approximation procedure for the solution of the interior Dirichlet problem for the system of Stokes' equations in two dimensions. The procedure is based on potential theoretical considerations in connection with a boundary integral equations method and consists of three approximation steps as follows. In a first step the unknown source density in the potential representation of the solution is replaced by approximate approximations. In a second step the decay behavior of the generating functions is used to gain a suitable approximation for the potential kernel, and in a third step Nyström's method leads to a linear algebraic system for the approximate source density. For every step a convergence analysis is established and corresponding error estimates are given.

An Analysis of the Effect of Gaussian Error in Object Recognition

Object recognition is complicated by clutter, occlusion, and sensor error. Since pose hypotheses are based on image feature locations, these effects can lead to false negatives and positives. In a typical recognition algorithm, pose hypotheses are tested against the image, and a score is assigned to each hypothesis. We use a statistical model to determine the score distribution associated with correct and incorrect pose hypotheses, and use binary hypothesis testing techniques to distinguish between them. Using this approach we can compare algorithms and noise models, and automatically choose values for internal system thresholds to minimize the probability of making a mistake.

Comparing Support Vector Machines with Gaussian Kernels to Radial Basis Function Classifiers

The Support Vector (SV) machine is a novel type of learning machine, based on statistical learning theory, which contains polynomial classifiers, neural networks, and radial basis function (RBF) networks as special cases. In the RBF case, the SV algorithm automatically determines centers, weights and threshold such as to minimize an upper bound on the expected test error. The present study is devoted to an experimental comparison of these machines with a classical approach, where the centers are determined by $k$--means clustering and the weights are found using error backpropagation. We consider three machines, namely a classical RBF machine, an SV machine with Gaussian kernel, and a hybrid system with the centers determined by the SV method and the weights trained by error backpropagation. Our results show that on the US postal service database of handwritten digits, the SV machine achieves the highest test accuracy, followed by the hybrid approach. The SV approach is thus not only theoretically well--founded, but also superior in a practical application.

Moderating effects of management control systems and innovation on performance. Simple methods for correcting the effects of measurement error for interaction effects in small samples

In the accounting literature, interaction or moderating effects are usually assessed by means of OLS regression and summated rating scales are constructed to reduce measurement error bias. Structural equation models and two-stage least squares regression could be used to completely eliminate this bias, but large samples are needed. Partial Least Squares are appropriate for small samples but do not correct measurement error bias. In this article, disattenuated regression is discussed as a small sample alternative and is illustrated on data of Bisbe and Otley (in press) that examine the interaction effect of innovation and style of use of budgets on performance. Sizeable differences emerge between OLS and disattenuated regression

Correcting Measurement Error Bias in Interaction Models with Small Samples

Several methods have been suggested to estimate non-linear models with interaction terms in the presence of measurement error. Structural equation models eliminate measurement error bias, but require large samples. Ordinary least squares regression on summated scales, regression on factor scores and partial least squares are appropriate for small samples but do not correct measurement error bias. Two stage least squares regression does correct measurement error bias but the results strongly depend on the instrumental variable choice. This article discusses the old disattenuated regression method as an alternative for correcting measurement error in small samples. The method is extended to the case of interaction terms and is illustrated on a model that examines the interaction effect of innovation and style of use of budgets on business performance. Alternative reliability estimates that can be used to disattenuate the estimates are discussed. A comparison is made with the alternative methods. Methods that do not correct for measurement error bias perform very similarly and considerably worse than disattenuated regression

Bondad de ajuste en ??tems polit??micos : tasas de error tipo I y potencia de tres ??ndices de ajuste

Resumen tomado de la publicaci??n

A vueltas con el error de Otelo : aplicación del modelo de control de fuentes a la credibilidad del testimonio y su afectación por la carga emocional.

Resumen tomado de la publicación

PILT Threshold 1

Files used for and during the Threshold 1 workshop

PILT Threshold 2

Files used for and during the Threshold 2 workshop

El currículum integrat : una errada de les autoritats educatives. 'El currículum integrado : un error de las autoridades educativas'.

Resumen tomado de la revista

El error del asegurador en el contrato de seguro

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El error en el derecho penal

Se pretende realizar un estudio suficiente del tema del error, sus diferentes modalidades y repercusiones. Y de manera muy especial, lo que se refiere al error como causal excluyente de responsabilidad, así como de aquellos eventos en los que se convierte en fuente de una menor punibilidad.

La responsabilidad del estado por error judicial frente a la acción de tutela como mecanismo para denunciarlo

La carta política de 1991 consagró una cláusula general de responsabilidad institucional del Estado según la cual éste responderá patrimonialmente por los daños antijurídicos que le sean imputables, causados por la acción o la omisión

Parametric pension reform and the intensive margin of labor supply, evidence from Colombia

We analyze the effect of a parametric reform of the fully-funded pension regime in Colombia on the intensive margin of the labor supply. We take advantage of a threshold defined by law in order to identify the causal effect using a regression discontinuity design. We find that a pension system that increases retirement age and the minimum weeks during which workers must contribute to claim pension benefits causes an increase of around 2 hours on the number of weekly worked hours; this corresponds to 4% of the average number of weekly worked hours or around 14% of a standard deviation of weekly worked hours. The effect is robust to different specifications, polynomial orders and sample sizes.