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A simple 1-dimensional model is presented to investigate elastic stress waves in composite laminates excited by underwater explosion shocks. The focus is on the elastic dynamic stress fields in the composite laminate immediately after the action of the shock wave. In this model, the interaction between the laminate and the water is taken into account, and the effects of the laminate-water interaction on the stress wave fields in the laminate are investigated. In the formulation of the model, wave fields in the laminate and the water are the first obtained in the frequency domain and then transferred into the time domain using the Fourier transform techniques. A quadrature technique is used to deal with the Fourier transform integrals in which the integrands have very sharp peaks on the integral axis. Numerical examples for stress waves in a steel plate and a glass reinforced plastic sandwich laminate are presented. The technique and the results presented in this article may be used in the design of ship hull structures subjected to underwater explosions.

To assess the attitudes with respect to the quality of banks’ service levels, we use survey data amongst more than 250 Chief Financial Officers (CFOs) of a range of Netherlands-based companies. These companies range from small to very large (including multinationals as Philips and Shell) companies. The survey was conducted in five subsequent years. In this paper, we explore the evaluations of the service levels of banks where, for all attributes considered, the ratings were accompanied by an importance rating. We propose a visualization method that incorporates the importance weights into correspondence analysis. The resulting maps exhibit the correlation structure of the different service items as well as the variances for each item. Moreover, the results are linked to different banks over time, thus exposing the development of the attitudes over time.

In this paper we consider the estimation of probabilistic ranking models in the context of conjoint experiments. By using approximate rather than exact ranking probabilities, we do not need to compute high-dimensional integrals. We extend the approximation technique proposed by \\citet{Henery1981} in the Thurstone-Mosteller-Daniels model for any Thurstone order statistics model and we show that our approach allows for a unified approach. Moreover, our approach also allows for the analysis of any partial ranking. Partial rankings are essential in practical conjoint analysis to collect data efficiently to relieve respondents' task burden.

Consumer preferences can be measured by rankings of alternatives. When there are too many alternatives, this consumer task becomes complex. One option is to have consumers rank only a subset of the available alternatives. This has an impact on subsequent statistical analysis, as now a large amount of ties is observed. We propose a simple methodology to perform proper statistical analysis in this case. It also allows to test whether (parts of the) rankings are random or not. An illustration shows its ease of application.

Subjective probabilities play an important role in marketing research, for example where individuals rate the likelihood that they will purchase a new to develop product. The tau-equivalent model can describe the joint behaviour of multiple test items measuring the same subjective probability. It improves the reliability of the subjective probability estimate by using a weighted sum as the outcome of the test rather than an unweighted sum. One can choose the weights to obtain maximal reliability. In this paper we stress the use of confidence intervals to assess maximal reliability, as this allows for a more critical assessment of the items as measurement instruments. Furthermore, two new confidence intervals for the maximal reliability are derived and compared to intervals derived earlier in \\citet{YuanBentler2002, RaykovPenev2006}. The comparison involves coverage curves, a methodology that is new in the field of reliability. The existing Yuan-Bentler and Raykov-Penev intervals are shown to overestimate the maximal reliability, whereas one of our proposed intervals, the stable interval, performs very well. This stable interval hardly shows any bias, and has a coverage for the true value which is approximately equal to the confidence level.