(1) Background: Irregular and non-standard work arrangements have become a serious determinant to the health and safety of workers. The aim of this study is to investigate the relationship between shift work and occupational accident absence. A representative Belgian sample considering several sociodemographic and work characteristics is used. (2) Methods: This study is based on the data of the sixth European Working Condition Survey (EWCS). The sample is restricted to 2169 respondents from Belgium. By using multivariate logistic regression modeling techniques and adjusting several confounders, the associations between shift work and occupational accident absence are studied. (3) Results: It is found that about 11.1% of the workers undergo an occupational accident absence. A multivariate regression model demonstrates an increased occupational accident absence risk for workers who have shift work (odds ratio, or OR, 1.92, 95% CI 1.06–3.46). Also, gender and biomechanical exposure were significantly associated with occupational accident absence ((OR 2.07, 95% CI 1.16–3.69) and (OR 2.03, 95% CI 1.14–3.63), respectively). No significant interaction effects are found with gender and age variables. 4) Conclusion: This study confirms that doing shift work is significantly associated with occupational accidents. In order to reduce the significance of occupational accidents, shift work should be limited through national-level policies.

Although a wide range of direction of arrival (DOA) estimation algorithms has been described for a diverse range of array configurations, no specific stochastic analysis framework has been established to assess the probability density function of the error on DOA estimates due to random errors in the array geometry. Therefore, we propose a stochastic collocation method that relies on a generalized polynomial chaos expansion to connect the statistical distribution of random position errors to the resulting distribution of the DOA estimates. We apply this technique to the conventional root-MUSIC and the Khatri–Rao-root-MUSIC methods. According to Monte-Carlo simulations, this novel approach yields a speedup by a factor of more than 100 in terms of CPU-time for a one-dimensional case and by a factor of 56 for a two-dimensional case.

This paper reports the characterization of the 2.45-GHz-ISM-band radio wave propagation channel. Specifically, measurements were performed in an underground parking garage, with the aim of optimizing breadcrumb systems for a Rapid Intervention Team application. The effects of the high penetration loss and large reflections by the concrete reinforced building structure on the path loss and the large-scale fading were studied. Based on the analysis of the wireless channel, critical points for reliable communication between members of a Rapid Intervention Team were identified. In particular, attention was paid to dealing with large, spatially confined signal losses due to shadowing, the anticipation of corner losses and the ability of the system to operate on multiple floors.

Economical, technical and strategic reasons make unreplicated experimental designs necessary and popular in industrial and management settings. This paper investigates the legitimate use of well known methods that appoint effects as significant when they are larger than a defined threshold. We found that established estimation methods, such as Lenth’s method and Dong’s method, are too tolerant and a larger threshold should be used before an effect can be determined as influencing. This comparing analysis was done by using the degree of freedom that is available when the resolution of the design is one less than the maximum value. Using the Pareto Principle we suggest a more accurate threshold estimator for significantly influencing factors and/or interactions based on analysis of variance.

Fuzziness describes event ambiguity by means of membership functions. Probability describes the uncertainty of an event’s occurrence. The primary objective of this paper is to interconnect these two disciplines by suggesting several membership function in case of the scale parameter of a Rayleigh distribution. They are based on confidence intervals and on pivotal quantities which have a normal or a χ² – distribution. We have succeeded in designing fuzzy numbers with a sharpness which is related to the underlying sample size. We found that a small sample size has an appreciable adverse impact on the likelihood of the parameter. We were able to improve the estimation by using upper record values.