Task analysis for error identification: Theory, method and validation

This paper presents the underlying theory of Task Analysis for Error Identification. The aim is to illustrate the development of a method that has been proposed for the evaluation of prototypical designs from the perspective of predicting human error. The paper presents the method applied to representative examples. The methodology is considered in terms of the various validation studies that have been conducted, and is discussed in the light of a specific case study

Sediment-accumulatie in transportleidingen af waterproductiebedrijven

In drinkwatertransportleidingen hoopt zich sediment op, ondanks het feit dat de maximale stroomsnelheid hoger is dan de snelheid die voor distributieleidingen zelfreinigend is. Opwervelend sediment zorgt voor klachten over de kwaliteit van het drinkwater. Het sediment accumuleert vooral dicht bij het pompstation. De hoeveelheid wordt vooral bepaald door de troebelheid van het water af waterproductiebedrijf

Improved Kaiser-Bessel Window Parameter Selection for Gridding

Introduction The gridding algorithm is frequently used to reconstruct an image from a non-uniformly sampled k-space. An important part of the algorithm is a convolution with a window. Usually, the Kaiser-Bessel window is used [1], which has a width L and a parameter B. A criterion for selecting an optimal value for B is the relative amount of aliased energy (including roll-off correction) of the window as used by Jackson [2]. In this abstract we show that the values for B found in [2] are not always optimal and introduce a method to find improved values for B given the sampling distribution. Method Resampling the convolved samples to a Cartesian grid in k- space causes aliasing. We write the aliased energy as: Z jxj?FOV fi fi fi fi c(x) \Delt

Increasing the semantic transparency of the KAOS goal model concrete syntax

FCT-MCTES SFRH/BD/108492/2015Stakeholders without formal training in requirements modelling languages, such as KAOS, struggle to understand requirements specifications. The lack of semantic transparency of the KAOS goal model concrete syntax is perceived as a communication barrier between stakeholders and requirements engineers. We report on a series of related empirical experiments that include the proposal of alternative concrete syntaxes for KAOS by leveraging design contributions from novices and their evaluation with respect to semantic transparency, in contrast with the standard KAOS goal model concrete syntax. We propose an alternative concrete syntax for KAOS that increases its semantic transparency (mean difference of.23, in [−1.00.1.00]) leading to a significantly higher correct symbol identification (mean difference of 19%) by novices. These results may be a stepping stone for reducing the communication gap between stakeholders and requirements engineers.preprintpublishe