Impact forces at dipped rail joints

Impact forces develop at the wheel/rail interface due to the presence of defects in the running surface of the wheel and/ or the railhead. This paper reports on wheel impacts, caused by permanently dipped rail joints, that are characterised by high-frequency impact forces generated by high amplifications of the static load that occur for a very short duration (P1 forces), followed by relatively low frequency, lower amplitude forces (P2 forces) that occur for a longer duration. These impact forces are affected by the design of components adjacent to the wheel and rail, namely the bogie’s primary suspension and rail seat pads; the influences of stiffness and damping characteristics of these components are investigated. A modified three-dimensional simulation model of the dynamics of the wagon/track system that includes defects in the track is created and is used to obtain the time series of the impact force. This is converted into impact force factors that are compared with a set of field-measured data reported in the literature. A simplified equation for the determination of impact force factors due to dipped rail joints is also proposed and validated.

Integrating the impact of climate into event based failure models for water pipes

This paper presents an event-based failure model to predict the number of failures that occur in water distribution assets. Often, such models have been based on analysis of historical failure data combined with pipe characteristics and environmental conditions. In this paper weather data have been added to the model to take into account the commonly observed seasonal variation of the failure rate. The theoretical basis of existing logistic regression models is briefly described in this paper, along with the refinements made to the model for inclusion of seasonal variation of weather. The performance of these refinements is tested using data from two Australian water authorities.

Impact of child labor on academic performance : evidence from the program "Edúcame Primero Colombia"

In this study, the effects of different variables of child labor on academic performance are investigated. To this end, 3302 children participating in the child labor eradication program “Edúcame Primero Colombia” were interviewed. The interview format used for the children's enrollment into the program was a template from which socioeconomic conditions, academic performance, and child labor variables were evaluated. The academic performance factor was determined using the Analytic Hierarchy Process (AHP). The data were analyzed through a logistic regression model that took into account children who engaged in a type of labor (n = 921). The results showed that labor conditions, the number of weekly hours dedicated to work, and the presence of work scheduled in the morning negatively affected the academic performance of child laborers. These results show that the relationship between child labor and academic performance is based on the conflict between these two activities. These results do not indicate a linear and simple relationship associated with the recognition of the presence or absence of child labor. This study has implications for the formulation of policies, programs, and interventions for preventing, eradicating, and attenuating the negative effects of child labor on the social and educational development of children.

An investigation of the impact of various geographical scales for the specification of spatial dependence

Ecological studies are based on characteristics of groups of individuals, which are common in various disciplines including epidemiology. It is of great interest for epidemiologists to study the geographical variation of a disease by accounting for the positive spatial dependence between neighbouring areas. However, the choice of scale of the spatial correlation requires much attention. In view of a lack of studies in this area, this study aims to investigate the impact of differing definitions of geographical scales using a multilevel model. We propose a new approach -- the grid-based partitions and compare it with the popular census region approach. Unexplained geographical variation is accounted for via area-specific unstructured random effects and spatially structured random effects specified as an intrinsic conditional autoregressive process. Using grid-based modelling of random effects in contrast to the census region approach, we illustrate conditions where improvements are observed in the estimation of the linear predictor, random effects, parameters, and the identification of the distribution of residual risk and the aggregate risk in a study region. The study has found that grid-based modelling is a valuable approach for spatially sparse data while the SLA-based and grid-based approaches perform equally well for spatially dense data.

The impact of mobile phone distraction on the braking behaviour of young drivers : a hazard-based duration model

Braking is a crucial driving task with a direct relationship with crash risk, as both excess and inadequate braking can lead to collisions. The objective of this study was to compare the braking profile of young drivers distracted by mobile phone conversations to non-distracted braking. In particular, the braking behaviour of drivers in response to a pedestrian entering a zebra crossing was examined using the CARRS-Q Advanced Driving Simulator. Thirty-two licensed drivers drove the simulator in three phone conditions: baseline (no phone conversation), hands-free, and handheld. In addition to driving the simulator, each participant completed questionnaires related to driver demographics, driving history, usage of mobile phones while driving, and general mobile phone usage history. The drivers were 18–26 years old and split evenly by gender. A linear mixed model analysis of braking profiles along the roadway before the pedestrian crossing revealed comparatively increased decelerations among distracted drivers, particularly during the initial 20 kph of deceleration. Drivers’ initial 20 kph deceleration time was modelled using a parametric accelerated failure time (AFT) hazard-based duration model with a Weibull distribution with clustered heterogeneity to account for the repeated measures experiment design. Factors found to significantly influence the braking task included vehicle dynamics variables like initial speed and maximum deceleration, phone condition, and driver-specific variables such as licence type, crash involvement history, and self-reported experience of using a mobile phone whilst driving. Distracted drivers on average appear to reduce the speed of their vehicle faster and more abruptly than non-distracted drivers, exhibiting excess braking comparatively and revealing perhaps risk compensation. The braking appears to be more aggressive for distracted drivers with provisional licenses compared to drivers with open licenses. Abrupt or excessive braking by distracted drivers might pose significant safety concerns to following vehicles in a traffic stream.

Rescaling clustering trees using impact ratios for robust hierarchical speaker clustering

We present a novel method for improving hierarchical speaker clustering in the tasks of speaker diarization and speaker linking. In hierarchical clustering, a tree can be formed that demonstrates various levels of clustering. We propose a ratio that expresses the impact of each cluster on the formation of this tree and use this to rescale cluster scores. This provides score normalisation based on the impact of each cluster. We use a state-of-the-art speaker diarization and linking system across the SAIVT-BNEWS corpus to show that our proposed impact ratio can provide a relative improvement of 16% in diarization error rate (DER).