Effect of mobile phone distraction on car-following behaviour

Multitasking, such as the concurrent use of a mobile phone and operating a motor vehicle, is a significant distraction that impairs driving performance and is becoming a leading cause of motor vehicle crashes. This study investigates the impact of mobile phone conversations on car-following behaviour. The CARRS-Q Advanced Driving Simulator was used to test a group of young Australian drivers aged 18 to 26 years on a car-following task in three randomised phone conditions: baseline (no phone conversation), hands-free and handheld. Repeated measure ANOVA was applied to examine the effect of mobile phone distraction on selected car-following variables such as driving speed, spacing, and time headway. Overall, drivers tended to select slower driving speeds, larger vehicle spacings, and longer time headways when they were engaged in either hands-free or handheld phone conversations, suggesting possible risk compensatory behaviour. In addition, phone conversations while driving influenced car-following behaviour such that variability was increased in driving speeds, vehicle spacings, and acceleration and decelerations. To further investigate car-following behaviour of distracted drivers, driver time headways were modelled using Generalized Estimation Equation (GEE). After controlling for various exogenous factors, the model predicts an increase of 0.33 seconds in time headway when a driver is engaged in hands-free phone conversation and a 0.75 seconds increase for handheld phone conversation. The findings will improve the collective understanding of distraction on driving performance, in particular car following behaviour which is most critical in the determination of rear-end crashes.

Exploring the effect of political risks in large infrastructure projects in politically unstable countries using a probabilistic modelling approach

This research aims to explore and identify political risks on a large infrastructure project in an exaggerated environment to ascertain whether sufficient objective information can be gathered by project managers to utilise risk modelling techniques. During the study, the author proposes a new definition of political risk; performs a detailed project study of the Neelum Jhelum Hydroelectric Project in Pakistan; implements a probabilistic model using the principle of decomposition and Bayes probabilistic theorem and answers the question: was it possible for project managers to obtain all the relevant objective data to implement a probabilistic model?

A recommendation system for predicting risks across multiple business process instances

This paper proposes a recommendation system that supports process participants in taking risk-informed decisions, with the goal of reducing risks that may arise during process execution. Risk reduction involves decreasing the likelihood and severity of a process fault from occurring. Given a business process exposed to risks, e.g. a financial process exposed to a risk of reputation loss, we enact this process and whenever a process participant needs to provide input to the process, e.g. by selecting the next task to execute or by filling out a form, we suggest to the participant the action to perform which minimizes the predicted process risk. Risks are predicted by traversing decision trees generated from the logs of past process executions, which consider process data, involved resources, task durations and other information elements like task frequencies. When applied in the context of multiple process instances running concurrently, a second technique is employed that uses integer linear programming to compute the optimal assignment of resources to tasks to be performed, in order to deal with the interplay between risks relative to different instances. The recommendation system has been implemented as a set of components on top of the YAWL BPM system and its effectiveness has been evaluated using a real-life scenario, in collaboration with risk analysts of a large insurance company. The results, based on a simulation of the real-life scenario and its comparison with the event data provided by the company, show that the process instances executed concurrently complete with significantly fewer faults and with lower fault severities, when the recommendations provided by our recommendation system are taken into account.

Evaluation of the performance of a dengue outbreak detection tool for China

An outbreak detection and response system, using time series moving percentile method based on historical data, in China has been used for identifying dengue fever outbreaks since 2008. For dengue fever outbreaks reported from 2009 to 2012, this system achieved a sensitivity of 100%, a specificity of 99.8% and a median time to detection of 3 days, which indicated that the system was a useful decision tool for dengue fever control and risk-management programs in China.

Can social resilience inform SA/SIA for adaptive planning for climate change in vulnerable regions?

This book represents a landmark effort to probe and analyze the theory and empirics of designing water disaster management policies. It consists of seven chapters that examine, in-depth and comprehensively, issues that are central to crafting effective policies for water disaster management. The authors use historical surveys, institutional analysis, econometric investigations, empirical case studies, and conceptual-theoretical discussions to clarify and illuminate the complex policy process. The specific topics studied in this book include a review and analysis of key policy areas and research priority areas associated with water disaster management, community participation in disaster risk reduction, the economics and politics of ‘green’ flood control, probabilistic flood forecasting for flood risk management, polycentric governance and flood risk management, drought management with the aid of dynamic inter-generational preferences, and how social resilience can inform SA/SIA for adaptive planning for climate change in vulnerable areas. A unique feature of this book is its analysis of the causes and consequences of water disasters and efforts to address them successfully through policy-rich, cross-disciplinary and transnational papers. This book is designed to help enrich the sparse discourse on water disaster management policies and galvanize water professionals to craft creative solutions to tackle water disasters efficiently, equitably, and sustainably. This book should also be of considerable use to disaster management professionals, in general, and natural resource policy analysts.

Impact of mobile phone use on car-following behaviour of young drivers

Multitasking, such as the concurrent use of a mobile phone and operating a motor vehicle, is a significant distraction that impairs driving performance and is becoming a leading cause of motor vehicle crashes. This study investigates the impact of mobile phone conversations on car-following behaviour. The CARRS-Q Advanced Driving Simulator was used to test a group of young Australian drivers aged 18–26 years on a car-following task in three randomised phone conditions: baseline (no phone conversation), hands-free and handheld. Repeated measure ANOVA was applied to examine the effect of mobile phone distraction on selected car-following variables such as driving speed, spacing, and time headway. Overall, drivers tended to select slower driving speeds, larger vehicle spacings, and longer time headways when they were engaged in either hands-free or handheld phone conversations, suggesting possible risk compensatory behaviour. In addition, phone conversations while driving influenced car-following behaviour such that variability was increased in driving speeds, vehicle spacings, and acceleration and decelerations. To further investigate car-following behaviour of distracted drivers, driver time headways were modelled using Generalized Estimation Equation (GEE). After controlling for various exogenous factors, the model predicts an increase of 0.33 s in time headway when a driver is engaged in hands-free phone conversation and a 0.75 s increase for handheld phone conversation. The findings will improve the collective understanding of distraction on driving performance, in particular car following behaviour which is most critical in the determination of rear-end crashes.

Systems-based approach to investigate unsafe pedestrian behaviour at level crossings

Crashes at level crossings are a major issue worldwide. In Australia, as well as in other countries, the number of crashes with vehicles has declined in the past years, while the number of crashes involving pedestrians seems to have remained unchanged. A systematic review of research related to pedestrian behaviour highlighted a number of important scientific gaps in current knowledge. The complexity of such intersections imposes particular constraints to the understanding of pedestrians’ crossing behaviour. A new systems-based framework, called Pedestrian Unsafe Level Crossing framework (PULC) was developed. The PULC organises contributing factors to crossing behaviour on different system levels as per the hierarchical classification of Jens Rasmussen’s Framework for Risk Management. In addition, the framework adapts James Reason’s classification to distinguish between different types of unsafe behaviour. The framework was developed as a tool for collection of generalizable data that could be used to predict current or future system failures or to identify aspects of the system that require further safety improvement. To give it an initial support, the PULC was applied to the analysis of qualitative data from focus groups discussions. A total number of 12 pedestrians who regularly crossed the same level crossing were asked about their daily experience and their observations of others’ behaviour which allowed the extraction and classification of factors associated with errors and violations. Two case studies using Rasmussen’s AcciMap technique are presented as an example of potential application of the framework. A discussion on the identified multiple risk contributing factors and their interactions is provided, in light of the benefits of applying a systems approach to the understanding of the origins of individual’s behaviour. Potential actions towards safety improvement are discussed.

Development of multi-rotor localised surveillance using multi-spectral sensors for plant biosecurity

This report describes a proof of concept for multi-rotor localised surveillance using a multi-spectral sensor for plant biosecurity applications. A literature review was conducted on previous applications using airborne multispectral imaging for plant biosecurity purposes. A ready built platform was purchased and modified in order to fit and provide suitable clearance for a Tetracam Mini-MCA multispectral camera. The appropriate risk management documents were developed allowing the platform and the multi-spectral camera to be tested extensively. However, due to technical difficulties with the platform the Mini- MCA was not mounted to the platform. Once a suitable platform is developed, future extensions can be conducted into the suitability of the Mini-MCA for airborne surveillance of Australian crops.

Process Analytical Technology Approach on Fluid Bed Granulation and Drying : Identifying Critical Relationships and Constructing the Design Space

Fluid bed granulation is a key pharmaceutical process which improves many of the powder properties for tablet compression. Dry mixing, wetting and drying phases are included in the fluid bed granulation process. Granules of high quality can be obtained by understanding and controlling the critical process parameters by timely measurements. Physical process measurements and particle size data of a fluid bed granulator that are analysed in an integrated manner are included in process analytical technologies (PAT). Recent regulatory guidelines strongly encourage the pharmaceutical industry to apply scientific and risk management approaches to the development of a product and its manufacturing process. The aim of this study was to utilise PAT tools to increase the process understanding of fluid bed granulation and drying. Inlet air humidity levels and granulation liquid feed affect powder moisture during fluid bed granulation. Moisture influences on many process, granule and tablet qualities. The approach in this thesis was to identify sources of variation that are mainly related to moisture. The aim was to determine correlations and relationships, and utilise the PAT and design space concepts for the fluid bed granulation and drying. Monitoring the material behaviour in a fluidised bed has traditionally relied on the observational ability and experience of an operator. There has been a lack of good criteria for characterising material behaviour during spraying and drying phases, even though the entire performance of a process and end product quality are dependent on it. The granules were produced in an instrumented bench-scale Glatt WSG5 fluid bed granulator. The effect of inlet air humidity and granulation liquid feed on the temperature measurements at different locations of a fluid bed granulator system were determined. This revealed dynamic changes in the measurements and enabled finding the most optimal sites for process control. The moisture originating from the granulation liquid and inlet air affected the temperature of the mass and pressure difference over granules. Moreover, the effects of inlet air humidity and granulation liquid feed rate on granule size were evaluated and compensatory techniques used to optimize particle size. Various end-point indication techniques of drying were compared. The ∆T method, which is based on thermodynamic principles, eliminated the effects of humidity variations and resulted in the most precise estimation of the drying end-point. The influence of fluidisation behaviour on drying end-point detection was determined. The feasibility of the ∆T method and thus the similarities of end-point moisture contents were found to be dependent on the variation in fluidisation between manufacturing batches. A novel parameter that describes behaviour of material in a fluid bed was developed. Flow rate of the process air and turbine fan speed were used to calculate this parameter and it was compared to the fluidisation behaviour and the particle size results. The design space process trajectories for smooth fluidisation based on the fluidisation parameters were determined. With this design space it is possible to avoid excessive fluidisation and improper fluidisation and bed collapse. Furthermore, various process phenomena and failure modes were observed with the in-line particle size analyser. Both rapid increase and a decrease in granule size could be monitored in a timely manner. The fluidisation parameter and the pressure difference over filters were also discovered to express particle size when the granules had been formed. The various physical parameters evaluated in this thesis give valuable information of fluid bed process performance and increase the process understanding.

The reliability of supply of feed grains in the northern region

Reliability of supply of feed grain has become a high priority issue for industry in the northern region. Expansion by major intensive livestock and industrial users of grain, combined with high inter-annual variability in seasonal conditions, has generated concern in the industry about reliability of supply. This paper reports on a modelling study undertaken to analyse the reliability of supply of feed grain in the northern region. Feed grain demand was calculated for major industries (cattle feedlots, pigs, poultry, dairy) based on their current size and rate of grain usage. Current demand was estimated to be 2.8Mt. With the development of new industrial users (ethanol) and by projecting the current growth rate of the various intensive livestock industries, it was estimated that demand would grow to 3.6Mt in three years time. Feed grain supply was estimated using shire scale yield prediction models for wheat and sorghum that had been calibrated against recent ABS production data. Other crops that contribute to a lesser extent to the total feed grain pool (barley, maize) were included by considering their production relative to the major winter and summer grains, with estimates based on available production records. This modelling approach allowed simulation of a 101-year time series of yield that showed the extent of the impact of inter-annual climate variability on yield levels. Production estimates were developed from this yield time series by including planted crop area. Area planted data were obtained from ABS and ABARE records. Total production amounts were adjusted to allow for any export and end uses that were not feed grain (flour, malt etc). The median feed grain supply for an average area planted was about 3.1Mt, but this varied greatly from year to year depending on seasonal conditions and area planted. These estimates indicated that supply would not meet current demand in about 30% of years if a median area crop were planted. Two thirds of the years with a supply shortfall were El Nino years. This proportion of years was halved (i.e. 15%) if the area planted increased to that associated with the best 10% of years. Should demand grow as projected in this study, there would be few years where it could be met if a median crop area was planted. With area planted similar to the best 10% of years, there would still be a shortfall in nearly 50% of all years (and 80% of El Nino years). The implications of these results on supply/demand and risk management and investment in research and development are briefly discussed.

Inferential, non-parametric statistics to assess quality of probabilistic forecast systems

Many statistical forecast systems are available to interested users. In order to be useful for decision-making, these systems must be based on evidence of underlying mechanisms. Once causal connections between the mechanism and their statistical manifestation have been firmly established, the forecasts must also provide some quantitative evidence of `quality’. However, the quality of statistical climate forecast systems (forecast quality) is an ill-defined and frequently misunderstood property. Often, providers and users of such forecast systems are unclear about what ‘quality’ entails and how to measure it, leading to confusion and misinformation. Here we present a generic framework to quantify aspects of forecast quality using an inferential approach to calculate nominal significance levels (p-values) that can be obtained either by directly applying non-parametric statistical tests such as Kruskal-Wallis (KW) or Kolmogorov-Smirnov (KS) or by using Monte-Carlo methods (in the case of forecast skill scores). Once converted to p-values, these forecast quality measures provide a means to objectively evaluate and compare temporal and spatial patterns of forecast quality across datasets and forecast systems. Our analysis demonstrates the importance of providing p-values rather than adopting some arbitrarily chosen significance levels such as p < 0.05 or p < 0.01, which is still common practice. This is illustrated by applying non-parametric tests (such as KW and KS) and skill scoring methods (LEPS and RPSS) to the 5-phase Southern Oscillation Index classification system using historical rainfall data from Australia, The Republic of South Africa and India. The selection of quality measures is solely based on their common use and does not constitute endorsement. We found that non-parametric statistical tests can be adequate proxies for skill measures such as LEPS or RPSS. The framework can be implemented anywhere, regardless of dataset, forecast system or quality measure. Eventually such inferential evidence should be complimented by descriptive statistical methods in order to fully assist in operational risk management.

Development and Accreditation of an Applied Climate Education Unit for Sustainable Land Use in Australia

In recent years, there have been significant developments in climate science relevant to agriculture and natural resource management. Assessing impacts of climate variability and use of seasonal climate forecasts have become increasingly important elements in the management "toolkit" for many Australian farmers. Consideration of climate change further increases the need for improved management strategies. While climate risk extension activities have kept pace with advances in climate science, a national review of the Vocational Education and Training system in Australia in relation to "weather and climate" showed that these topics were "poorly represented" at the management level in the Australian Qualifications Framework, and needed increased emphasis. Consequently, a new Unit of Competency concerning management of climatic risk was developed and accredited to address this deficiency. The objective of the unit was to build knowledge and skills for better management of climate variability via the elements of surveying climatic and enterprise data; analysing climatic risks and opportunities; and developing climatic risk management strategies. This paper describes establishment of a new unit for vocational education that is designed to harness recent developments in applied climate science for better management of Australia's highly variable climate. The main benefits of the new unit of competency, "Developing climatic risk management strategies,"were seen as improving decisions in climate and agriculture, and reducing climate risk exposure to enhance sustainable agriculture. The educational unit is now within the scope of agricultural colleges, universities, and registered training organisations as an accredited unit.

Deriatives disclosure in corporate annual reports: bank analysts; perceptions of usefulness

Responding to mixed evidence on the decision-usefulness of annual report disclosures for derivative financial instruments to capital market participants, and concerns identified by practice, this paper examines usefulness in a direct study of user perceptions. Interviews with analysts from Australia’s four major banks reveal essential usefulness, limited by the disclosures’ failure to reflect companies’ actual use of derivatives throughout the period, and inability of users to understand companies’ off-balance sheet risk and risk management practices from information considered generic and boilerplate. The research complements and extends existing archival and survey research and provides new evidence suggesting low-cost ways for increasing usefulness. It supports the International Accounting Standards Board’s disclosure recommendations in its recent Discussion Paper: A Review of the Conceptual Framework for Financial Reporting, but, at the same time, highlights that for these proposed measures to be successful in relation to IFRS 7, they may need to address other issues. The research increases knowledge of the informational requirements of lenders, an important class of financial information user, and supports calls from practice for companies to improve their disclosure of material economic risks.

Impact of subsoil constraints on wheat yield and gross margin on fine-textured soils of the southern Victorian Mallee

The APSIM-Wheat module was used to investigate our present capacity to simulate wheat yields in a semi-arid region of eastern Australia (the Victorian Mallee), where hostile subsoils associated with salinity, sodicity, and boron toxicity are known to limit grain yield. In this study we tested whether the effects of subsoil constraints on wheat growth and production could be modelled with APSIM-Wheat by assuming that either: (a) root exploration within a particular soil layer was reduced by the presence of toxic concentrations of salts, or (b) soil water uptake from a particular soil layer was reduced by high concentration of salts through osmotic effects. After evaluating the improved predictive capacity of the model we applied it to study the interactions between subsoil constraints and seasonal conditions, and to estimate the economic effect that subsoil constraints have on wheat farming in the Victorian Mallee under different climatic scenarios. Although the soils had high levels of salinity, sodicity, and boron, the observed variability in root abundance at different soil layers was mainly related to soil salinity. We concluded that: (i) whether the effect of subsoil limitations on growth and yield of wheat in the Victorian Mallee is driven by toxic, osmotic, or both effects acting simultaneously still requires further research, (ii) at present, the performance of APSIM-Wheat in the region can be improved either by assuming increased values of lower limit for soil water extraction, or by modifying the pattern of root exploration in the soil pro. le, both as a function of soil salinity. The effect of subsoil constraints on wheat yield and gross margin can be expected to be higher during drier than wetter seasons. In this region the interaction between climate and soil properties makes rainfall information alone, of little use for risk management and farm planning when not integrated with cropping systems models.