Important omitted spatial variables in safety models: Understanding contributing crash causes at intersections

Advances in safety research—trying to improve the collective understanding of motor vehicle crash causation—rests upon the pursuit of numerous lines of inquiry. The research community has focused on analytical methods development (negative binomial specifications, simultaneous equations, etc.), on better experimental designs (before-after studies, comparison sites, etc.), on improving exposure measures, and on model specification improvements (additive terms, non-linear relations, etc.). One might think of different lines of inquiry in terms of ‘low lying fruit’—areas of inquiry that might provide significant improvements in understanding crash causation. It is the contention of this research that omitted variable bias caused by the exclusion of important variables is an important line of inquiry in safety research. In particular, spatially related variables are often difficult to collect and omitted from crash models—but offer significant ability to better understand contributing factors to crashes. This study—believed to represent a unique contribution to the safety literature—develops and examines the role of a sizeable set of spatial variables in intersection crash occurrence. In addition to commonly considered traffic and geometric variables, examined spatial factors include local influences of weather, sun glare, proximity to drinking establishments, and proximity to schools. The results indicate that inclusion of these factors results in significant improvement in model explanatory power, and the results also generally agree with expectation. The research illuminates the importance of spatial variables in safety research and also the negative consequences of their omissions.

A 'conceptual models' approach to organisational resilience

Gibson and Tarrant discuss the range of inter-dependant factors needed to manage organisational resilience. Over the last few years there has been considerable interest in the idea of resilience across all areas of society. Like any new area or field this has produced a vast array of definitions, processes, management systems and measurement tools which together have clouded the concept of resilience. Many of us have forgotten that ultimately resilience is not just about ‘bouncing back from adversity’ but is more broadly concerned with adaptive capacity and how we better understand and address uncertainty in our internal and external environments. The basis of organisational resilience is a fundamental understanding and treatment of risk, particularly non-routine or disruption related risk. This paper presents a number of conceptual models of organisational resilience that we have developed to demonstrate the range of inter-dependant factors that need to be considered in the management of such risk. These conceptual models illustrate that effective resilience is built upon a range of different strategies that enhance both ‘hard’ and ‘soft’ organisational capabilities . They emphasise the concept that there is no quick fix, no single process, management system or software application that will create resilience.

Advanced mathematical modelling and experimental investigation of new torque arms for shaft-mounted drives

Shaft-mounted gearboxes are widely used in industry. The torque arm that holds the reactive torque on the housing of the gearbox, if properly positioned creates the reactive force that lifts the gearbox and unloads the bearings of the output shaft. The shortcoming of these torque arms is that if the gearbox is reversed the direction of the reactive force on the torque arm changes to opposite and added to the weight of the gearbox overloads the bearings shortening their operating life. In this paper, a new patented design of torque arms that develop a controlled lifting force and counteract the weight of the gearbox regardless of the direction of the output shaft rotation is described. Several mathematical models of the conventional and new torque arms were developed and verified experimentally on a specially built test rig that enables modelling of the radial compliance of the gearbox bearings and elastic elements of the torque arms. Comparison showed a good agreement between theoretical and experimental results.

Mathematical modelling of chronic wound healing

Chronicwounds fail to proceed through an orderly process to produce anatomic and functional integrity and are a significant socioeconomic problem. There is much debate about the best way to treat these wounds. In this thesis we review earlier mathematical models of angiogenesis and wound healing. Many of these models assume a chemotactic response of endothelial cells, the primary cell type involved in angiogenesis. Modelling this chemotactic response leads to a system of advection-dominated partial differential equations and we review numerical methods to solve these equations and argue that the finite volume method with flux limiting is best-suited to these problems. One treatment of chronic wounds that is shrouded with controversy is hyperbaric oxygen therapy (HBOT). There is currently no conclusive data showing that HBOT can assist chronic wound healing, but there has been some clinical success. In this thesis we use several mathematical models of wound healing to investigate the use of hyperbaric oxygen therapy to assist the healing process - a novel threespecies model and a more complex six-species model. The second model accounts formore of the biological phenomena but does not lend itself tomathematical analysis. Bothmodels are then used tomake predictions about the efficacy of hyperbaric oxygen therapy and the optimal treatment protocol. Based on our modelling, we are able to make several predictions including that intermittent HBOT will assist chronic wound healing while normobaric oxygen is ineffective in treating such wounds, treatment should continue until healing is complete and finding the right protocol for an individual patient is crucial if HBOT is to be effective. Analysis of the models allows us to derive constraints for the range of HBOT protocols that will stimulate healing, which enables us to predict which patients are more likely to have a positive response to HBOT and thus has the potential to assist in improving both the success rate and thus the cost-effectiveness of this therapy.

Cytochrome p450 isozyme protein verified in the skin of southern hemisphere humpback whales (megaptera novaeangliae) : implications for biochemical biomarker assessment

Large mysticete whales represent a unique challenge for chemical risk assessment. Few epidemiological investigations are possible due to the low incidence of adult stranding events. Similarly their often extreme life-history adaptations of prolonged migration and fasting challenge exposure assumptions. Molecular biomarkers offer the potential to complement information yielded through tissue chemical analysis, as well as providing evidence of a molecular response to chemical exposure. In this study we confirm the presence of cytochrome P450 reductase (CPR) and cytochrome P450 isoenzyme 1A1 (CYP1A1) in epidermal tissue of southern hemisphere humpback whales (Megaptera novaeangliae). The detection of CYP1A1 in the integument of the humpback whale affords the opportunity for further quantitative non-destructive investigations of enzyme activity as a function of chemical stress.

Improving accuracy and intelligibility of decisions

Intelligible and accurate risk-based decision-making requires a complex balance of information from different sources, appropriate statistical analysis of this information and consequent intelligent inference and decisions made on the basis of these analyses. Importantly, this requires an explicit acknowledgement of uncertainty in the inputs and outputs of the statistical model. The aim of this paper is to progress a discussion of these issues in the context of several motivating problems related to the wider scope of agricultural production. These problems include biosecurity surveillance design, pest incursion, environmental monitoring and import risk assessment. The information to be integrated includes observational and experimental data, remotely sensed data and expert information. We describe our efforts in addressing these problems using Bayesian models and Bayesian networks. These approaches provide a coherent and transparent framework for modelling complex systems, combining the different information sources, and allowing for uncertainty in inputs and outputs. While the theory underlying Bayesian modelling has a long and well established history, its application is only now becoming more possible for complex problems, due to increased availability of methodological and computational tools. Of course, there are still hurdles and constraints, which we also address through sharing our endeavours and experiences.

Comparison of scoring systems for invasive pests using ROC analysis and Monte Carlo simulation

Different international plant protection organisations advocate different schemes for conducting pest risk assessments. Most of these schemes use structured questionnaire in which experts are asked to score several items using an ordinal scale. The scores are then combined using a range of procedures, such as simple arithmetic mean, weighted averages, multiplication of scores, and cumulative sums. The most useful schemes will correctly identify harmful pests and identify ones that are not. As the quality of a pest risk assessment can depend on the characteristics of the scoring system used by the risk assessors (i.e., on the number of points of the scale and on the method used for combining the component scores), it is important to assess and compare the performance of different scoring systems. In this article, we proposed a new method for assessing scoring systems. Its principle is to simulate virtual data using a stochastic model and, then, to estimate sensitivity and specificity values from these data for different scoring systems. The interest of our approach was illustrated in a case study where several scoring systems were compared. Data for this analysis were generated using a probabilistic model describing the pest introduction process. The generated data were then used to simulate the outcome of scoring systems and to assess the accuracy of the decisions about positive and negative introduction. The results showed that ordinal scales with at most 5 or 6 points were sufficient and that the multiplication-based scoring systems performed better than their sum-based counterparts. The proposed method could be used in the future to assess a great diversity of scoring systems.

A framework for integrating disadvantaged analysis into transportation planning models

This research paper aims to develop a method to explore the travel behaviour differences between disadvantaged and non-disadvantaged populations. It also aims to develop a modelling approach or a framework to integrate disadvantage analysis into transportation planning models (TPMs). The methodology employed identifies significantly disadvantaged groups through a cluster analysis and the paper presents a disadvantage-integrated TPM. This model could be useful in determining areas with concentrated disadvantaged population and also developing and formulating relevant disadvantage sensitive policies. (a) For the covering entry of this conference, please see ITRD abstract no. E214666.

Model selection and error estimation

We study model selection strategies based on penalized empirical loss minimization. We point out a tight relationship between error estimation and data-based complexity penalization: any good error estimate may be converted into a data-based penalty function and the performance of the estimate is governed by the quality of the error estimate. We consider several penalty functions, involving error estimates on independent test data, empirical VC dimension, empirical VC entropy, and margin-based quantities. We also consider the maximal difference between the error on the first half of the training data and the second half, and the expected maximal discrepancy, a closely related capacity estimate that can be calculated by Monte Carlo integration. Maximal discrepancy penalty functions are appealing for pattern classification problems, since their computation is equivalent to empirical risk minimization over the training data with some labels flipped.

The power of historical causal components involved in engaging at risk youth at three alternative schools

This article addresses the causal powers associated with the social phenomena of alternative schooling for youth at risk. It stems from a doctoral thesis, Alternative Schooling Programs for At Risk Youth – Three Case Studies which addresses wider issues integral to alternative schooling: youth at risk, alternative schooling models, and literacy. This article explores one aspect of alternative schooling: the historical causal factors involved in the establishment and continuance of three alternative case study models in Queensland, Australia. By adhering to Bhaskar’s transformational model of social activity (TMSA) , social structures and individuals will be analytically distinguished to uncover their separate causal powers and how these have effected the establishment and continuance of three alternative schools.

Modeling perceived collision risk in port water navigation

An increase in the likelihood of navigational collisions in port waters has put focus on the collision avoidance process in port traffic safety. The most widely used on-board collision avoidance system is the automatic radar plotting aid which is a passive warning system that triggers an alert based on the pilot’s pre-defined indicators of distance and time proximities at the closest point of approaches in encounters with nearby vessels. To better help pilot in decision making in close quarter situations, collision risk should be considered as a continuous monotonic function of the proximities and risk perception should be considered probabilistically. This paper derives an ordered probit regression model to study perceived collision risks. To illustrate the procedure, the risks perceived by Singapore port pilots were obtained to calibrate the regression model. The results demonstrate that a framework based on the probabilistic risk assessment model can be used to give a better understanding of collision risk and to define a more appropriate level of evasive actions.

Measuring the effect of motorcycle rider training on psychosocial influences for risk taking

Aim: Whilst motorcycle rider training is commonly incorporated into licensing programs in many developed nations, little empirical support has been found in previous research to prescribe it as an effective road safety countermeasure. It has been posited that the lack of effect of motorcycle rider training on crash reduction may, in part, be due to the predominant focus on skills-based training with little attention devoted to addressing attitudes and motives that influence subsequent risky riding. However, little past research has actually endeavoured to measure attitudinal and motivational factors as a function of rider training. Accordingly, this study was undertaken to assess the effect of a commercial motorcycle rider training program on psychosocial factors that have been shown to influence risk taking by motorcyclists. Method: Four hundred and thirty-eight motorcycle riders attending a competency-based licence training course in Brisbane, Australia, voluntarily participated in the study. A self-report questionnaire adapted from the Rider Risk Assessment Measure (RRAM) was administered to participants at the commencement of training, then again at the conclusion of training. Participants were informed of the independent nature of the research and that their responses would in no way effect their chance of obtaining a licence. To minimise potential demand characteristics, participants were instructed to seal completed questionnaires in envelopes and place them in a sealed box accessible only by the research team (i.e. not able to be viewed by instructors). Results: Significant reductions in the propensity for thrill seeking and intentions to engage in risky riding in the next 12 months were found at the end of training. In addition, a significant increase in attitudes to safety was found. Conclusions: These findings indicate that rider training may have a positive short-term influence on riders’ propensity for risk taking. However, such findings must be interpreted with caution in regard to the subsequent safety of riders as these factors may be subject to further influence once riders are licensed and actively engage with peers during on-road riding. This highlights a challenge for road safety education / training programs in regard to the adoption of safety practices and the need for behavioural follow-up over time to ascertain long-term effects. This study was the initial phase of an ongoing program of research into rider training and risk taking framed around Theory of Planned Behaviour concepts. A subsequent 12 month follow-up of the study participants has been undertaken with data analysis pending.

Navigational safety in port waters: Techniques for modeling collision risk

Navigational collisions are one of the major safety concerns for many seaports. Continuing growth of shipping traffic in number and sizes is likely to result in increased number of traffic movements, which consequently could result higher risk of collisions in these restricted waters. This continually increasing safety concern warrants a comprehensive technique for modeling collision risk in port waters, particularly for modeling the probability of collision events and the associated consequences (i.e., injuries and fatalities). A number of techniques have been utilized for modeling the risk qualitatively, semi-quantitatively and quantitatively. These traditional techniques mostly rely on historical collision data, often in conjunction with expert judgments. However, these techniques are hampered by several shortcomings, such as randomness and rarity of collision occurrence leading to obtaining insufficient number of collision counts for a sound statistical analysis, insufficiency in explaining collision causation, and reactive approach to safety. A promising alternative approach that overcomes these shortcomings is the navigational traffic conflict technique (NTCT), which uses traffic conflicts as an alternative to the collisions for modeling the probability of collision events quantitatively. This article explores the existing techniques for modeling collision risk in port waters. In particular, it identifies the advantages and limitations of the traditional techniques and highlights the potentials of the NTCT in overcoming the limitations. In view of the principles of the NTCT, a structured method for managing collision risk is proposed. This risk management method allows safety analysts to diagnose safety deficiencies in a proactive manner, which consequently has great potential for managing collision risk in a fast, reliable and efficient manner.

Numerical simulation of a fractional mathematical model for epidermal wound healing

A number of mathematical models investigating certain aspects of the complicated process of wound healing are reported in the literature in recent years. However, effective numerical methods and supporting error analysis for the fractional equations which describe the process of wound healing are still limited. In this paper, we consider numerical simulation of fractional model based on the coupled advection-diffusion equations for cell and chemical concentration in a polar coordinate system. The space fractional derivatives are defined in the Left and Right Riemann-Liouville sense. Fractional orders in advection and diffusion terms belong to the intervals (0; 1) or (1; 2], respectively. Some numerical techniques will be used. Firstly, the coupled advection-diffusion equations are decoupled to a single space fractional advection-diffusion equation in a polar coordinate system. Secondly, we propose a new implicit difference method for simulating this equation by using the equivalent of the Riemann-Liouville and Gr¨unwald-Letnikov fractional derivative definitions. Thirdly, its stability and convergence are discussed, respectively. Finally, some numerical results are given to demonstrate the theoretical analysis.

Risk-based approach to the management of on-site wastewater treatment facilities

Background On-site wastewater treatment system (OWTS) siting, design and management has traditionally been based on site specific conditions with little regard to the surrounding environment or the cumulative effect of other systems in the environment. The general approach has been to apply the same framework of standards and regulations to all sites equally, regardless of the sensitivity, or lack thereof, to the receiving environment. Consequently, this has led to the continuing poor performance and failure of on-site systems, resulting in environmental and public health consequences. As a result, there is increasing realisation that more scientifically robust evaluations in regard to site assessment and the underlying ground conditions are needed. Risk-based approaches to on-site system siting, design and management are considered the most appropriate means of improvement to the current standards and codes for on-site wastewater treatment systems. The Project Research in relation to this project was undertaken within the Gold Coast City Council region, the major focus being the semi-urban, rural residential and hinterland areas of the city that are not serviced by centralised treatment systems. The Gold Coast has over 15,000 on-site systems in use, with approximately 66% being common septic tank-subsurface dispersal systems. A recent study evaluating the performance of these systems within the Gold Coast area showed approximately 90% were not meeting the specified guidelines for effluent treatment and dispersal. The main focus of this research was to incorporate strong scientific knowledge into an integrated risk assessment process to allow suitable management practices to be set in place to mitigate the inherent risks. To achieve this, research was undertaken focusing on three main aspects involved with the performance and management of OWTS. Firstly, an investigation into the suitability of soil for providing appropriate effluent renovation was conducted. This involved detailed soil investigations, laboratory analysis and the use of multivariate statistical methods for analysing soil information. The outcomes of these investigations were developed into a framework for assessing soil suitability for effluent renovation. This formed the basis for the assessment of OWTS siting and design risks employed in the developed risk framework. Secondly, an assessment of the environmental and public health risks was performed specifically related the release of contaminants from OWTS. This involved detailed groundwater and surface water sampling and analysis to assess the current and potential risks of contamination throughout the Gold Coast region. Additionally, the assessment of public health risk incorporated the use of bacterial source tracking methods to identify the different sources of fecal contamination within monitored regions. Antibiotic resistance pattern analysis was utilised to determine the extent of human faecal contamination, with the outcomes utilised for providing a more indicative public health assessment. Finally, the outcomes of both the soil suitability assessment and ground and surface water monitoring was utilised for the development of the integrated risk framework. The research outcomes achieved through this project enabled the primary research aims and objects to be accomplished. This in turn would enable Gold Coast City Council to provide more appropriate assessment and management guidelines based on robust scientific knowledge which will ultimately ensure that the potential environmental and public health impacts resulting from on-site wastewater treatment is minimised. As part of the implementation of suitable management strategies, a critical point monitoring program (CPM) was formulated. This entailed the identification of the key critical parameters that contribute to the characterised risks at monitored locations within the study area. The CPM will allow more direct procedures to be implemented, targeting the specific hazards at sensitive areas throughout Gold Coast region.