Modeling Risk‐Related Knowledge in Tunneling Projects

Knowledge on failure events and their associated factors, gained from past construction projects, is regarded as potentially extremely useful in risk management. However, a number of circumstances are constraining its wider use. Such knowledge is usually scarce, seldom documented, and even unavailable when it is required. Further, there exists a lack of proven methods to integrate and analyze it in a cost‐effective way. This article addresses possible options to overcome these difficulties. Focusing on limited but critical potential failure events, the article demonstrates how knowledge on a number of important potential failure events in tunnel works can be integrated. The problem of unavailable or incomplete information was addressed by gathering judgments from a group of experts. The elicited expert knowledge consisted of failure scenarios and associated probabilistic information. This information was integrated using Bayesian belief‐networks‐based models that were first customized in order to deal with the expected divergence in judgments caused by epistemic uncertainty of risks. The work described in the article shows that the developed models that integrate risk‐related knowledge provide guidance as to the use of specific remedial measures.     

Re-distributed manufacturing and the food-water-energy nexus: opportunities and challenges

Abstract

Addressing the intersection of two important emerging research areas, re-distributed manufacturing (RDM) and the food-energy-water (FEW) nexus, this work combines insights from engineering, business and policy perspectives and explores opportunities and challenges towards a more localized and sustainable food system. Analysis centred on two specific food products, namely bread and tomato paste reveals that the feasibility and potential of RDM vary with the type of food product and the supply chain (SC) components. Physically, energy efficiency, water consumption and reduction of waste and carbon footprint may be affected by scale and location of production activities and potentials of industrial symbiosis. From the business perspective, novel products, new markets and new business models are expected in order for food RDM to penetrate within the established food industry. Studies on policies, through the lens of public procurement, call for solid evidence of envisioned environmental, social and economic benefits of a more localized food system. An initial integrated framework is proposed for understanding and assessing food RDM and the FEW nexus.     

The effect of ergonomic intervention on neck/shoulder and low back pain

The aim of this study was to examine the effect of two types of ergonomic intervention on pain and pain-related disability in the neck/shoulder and low back regions. A cohort of 492 subjects of various occupations with non-specific neck/shoulder or low back pain was followed over a five to six year period. The study subjects were classified into four intervention groups: no ergonomic intervention, educational worksite intervention, workplace intervention, and combined workplace and educational worksite intervention. The group with no ergonomic intervention was used as the reference group. The changes in pain intensity and pain-related disability from baseline to follow-up in each of the three groups with intervention were compared to the changes in the reference group. During the follow-up, 39% of the subjects had received ergonomic intervention. The average change in pain intensity and pain-related disability was smaller in the educational worksite intervention group than in the reference group. The average reduction of pain intensity and pain-related disability did not differ between the two other intervention groups and the reference group. Thus, for subjects still at work, ergonomic intervention seemed to be ineffective for reducing neck/shoulder and low back pain and pain-related disability.     

A recursive approach to parameter estimation in regression and time series models

In this paper we discuss the recursive (or on line) estimation in (i) regression and (ii) autoregressive integrated moving average (ARIMA) time series models. The adopted approach uses Kalman filtering techniques to calculate estimates recursively. This approach is used for the estimation of constant as well as time varying parameters. In the first section of the paper we consider the linear regression model. We discuss recursive estimation both for constant and time varying parameters. For constant parameters, Kalman filtering specializes to recursive least squares. In general, we allow the parameters to vary according to an autoregressive integrated moving average process and update the parameter estimates recursively. Since the stochastic model for the parameter changes will "be rarely known, simplifying assumptions have to be made. In particular we assume a random walk model for the time varying parameters and show how to determine whether the parameters are changing over time. This is illustrated with an example.     

The use of a reference variety for comparisons in incomplete series of crop variety trials

In a series of crop variety trials, ‘test varieties’ are compared with one another and with a ‘reference’ variety that is included in all trials. The series is typically analyzed with a linear mixed model and the method of generalized least squares. Usually, the estimates of the expected differences between the test varieties and the reference variety are presented. When the series is incomplete, i.e. when all test varieties were not included in all trials, the method of generalized least squares may give estimates of expected differences to the reference variety that do not appear to accord with observed differences. The present paper draws attention to this phenomenon and explores the recurrent idea of comparing test varieties indirectly through the use of the reference. A new ‘reference treatment method’ was specified and compared with the method of generalized least squares when applied to a five-year series of 85 spring wheat trials. The reference treatment method provided estimates of differences to the reference variety that agreed with observed differences, but was considerably less efficient than the method of generalized least squares.     

A Bernstein inequality for exponentially growing graphs

In this article, we present a Bernstein inequality for sums of random variables which are defined on a graphical network whose nodes grow at an exponential rate. The inequality can be used to derive concentration inequalities in highly connected networks. It can be useful to obtain consistency properties for non parametric estimators of conditional expectation functions which are derived from such networks.     

Job stressors and coping characteristics in work-related disease: Issues of validity

There is now broad evidence that stressful work conditions and critical person characteristics contribute to the development of coronary dysfunction and disease via sustained autonomic nervous system activation. To improve the prediction of coronary risk and disease we combined information on psychosocial work stressors and work-related coping characteristics ('need for control') in several studies. The theoretical model termed 'effort-reward imbalance' assumes that high extrinsic (e.g. work pressure, cumulative workload) and intrinsic (e.g. 'need for control') effort spent at work in combination with low reward obtained (e.g. status control, esteem, monetary gratification) trigger sustained neuro-hormonal activation. In this paper the results of a 6 year prospective study conducted in 416 male blue-collar workers underline the validity of this model. The main findings indicate that components of effort-reward imbalance are strongly related to new coronary events and to elevated levels of established coronary risk factors (e.g. hypertension, atherogenic lipids) as well as to reduced cardiovascular responsiveness. It is concluded that the results clearly demonstrate the validity of effort-reward imbalance as an important predictor of coronary risk and disease, and indicate the need for structural and behavioural intervention in the workplace to prevent coronary heart dseases.     

Anisotropy analysis of pressed point processes

This paper introduces methods for the detection of anisotropies which are caused by compression of regular 3D point patterns. Isotropy tests based on directional summary statistics and estimators for the compression factor are developed. Using simulated data, the dependence of the power of these methods on the intensity, the degree of regularity, and the compression strength is studied. Finally, our methods are applied to the point patterns of centers of air pores extracted from tomographic images of ice cores. This way the presence of anisotropies in the ice caused by the compression of the ice sheet and an increase of their strength with increasing depth are shown.