The legal concept of work-related injury and disease in Australian OHS and workers' compensation systems

This paper analyses the concept of ‘work-relatedness’ in Australian workers’ compensation and occupational health and safety (OHS) systems. The concept of work-relatedness is important because it is a crucial element circumscribing the limits of the protection afforded to workers under the preventative OHS statutes, and is a threshold element which has to be satisfied before an injured or ill worker can recover statutory compensation. While the preventive and compensatory regimes do draw on some similar concepts of work-relatedness, as this paper will illustrate, there are significant differences both between, and within, these regimes.

Design, construction and evaluation of systems to predict risk in obstetrics

We present a systematic, practical approach to developing risk prediction systems, suitable for use with large databases of medical information. An important part of this approach is a novel feature selection algorithm which uses the area under the receiver operating characteristic (ROC) curve to measure the expected discriminative power of different sets of predictor variables. We describe this algorithm and use it to select variables to predict risk of a specific adverse pregnancy outcome: failure to progress in labour. Neural network, logistic regression and hierarchical Bayesian risk prediction models are constructed, all of which achieve close to the limit of performance attainable on this prediction task. We show that better prediction performance requires more discriminative clinical information rather than improved modelling techniques. It is also shown that better diagnostic criteria in clinical records would greatly assist the development of systems to predict risk in pregnancy. We present a systematic, practical approach to developing risk prediction systems, suitable for use with large databases of medical information. An important part of this approach is a novel feature selection algorithm which uses the area under the receiver operating characteristic (ROC) curve to measure the expected discriminative power of different sets of predictor variables. We describe this algorithm and use it to select variables to predict risk of a specific adverse pregnancy outcome: failure to progress in labour. Neural network, logistic regression and hierarchical Bayesian risk prediction models are constructed, all of which achieve close to the limit of performance attainable on this prediction task. We show that better prediction performance requires more discriminative clinical information rather than improved modelling techniques. It is also shown that better diagnostic criteria in clinical records would greatly assist the development of systems to predict risk in pregnancy.

On Merging Business Process Management and Geographic Information Systems : Modeling and Execution of Ecological Concerns in Processes

Business Process Management describes a holistic management approach for the systematic design, modeling, execution, validation, monitoring and improvement of organizational business processes. Traditionally, most attention within this community has been given to control-flow aspects, i.e., the ordering and sequencing of business activities, oftentimes in isolation with regards to the context in which these activities occur. In this paper, we propose an approach that allows executable process models to be integrated with Geographic Information Systems. This approach enables process models to take geospatial and other geographic aspects into account in an explicit manner both during the modeling phase and the execution phase. We contribute a structured modeling methodology, based on the well-known Business Process Model and Notation standard, which is formalized by means of a mapping to executable Colored Petri nets. We illustrate the feasibility of our approach by means of a sustainability-focused case example of a process with important ecological concerns.

3D reconfigurable autopilot flight system for both general aviation and unmanned aerial systems

This research project investigated and designed a modular architecture for a 3D Reconfigurable Autopilot Flight System that could be used to control actuators in both manned and unmanned aircraft. The system is based on a CAN Bus interface and allows seamless control of different types of actuators. During the course of the research the differences and similarities of autopilots for fixed-wing general aviation aircraft and unmanned aircraft were analysed focusing on the actuator interfaces. This project suggests that software and hardware used in commercial-of-the-shelf avionics could be used in manned and unmanned aviation.

Design of steel roof and wall cladding systems for pull-out failures

When thin steel roof and wall cladding systems are subjected to wind uplift/suction forces, local pull-through or pull-out failures occur prematurely at their screwed connections. During high wind events such as stom1s and cyclones, these localized failures then lead to severe damage to buildings and their contents. In recent times, the use of thin steel battens, purlins and girts has increased considerably, which has made the pull-out failures more critical in the design of steel cladding systems. An experimental investigation was therefore carried out to study the pull-out failure using both static and cyclic tests for a range of commonly used screw fasteners and steel battens, purlins and girts. This paper presents the details ofthis experimental investigation and its results.

Technology and the City: Systems, Applications and Implications

This book investigates and reveals the interplay between smart technologies and cities, a topic that has gained incredible currency in urban studies in recent years. Beginning with an elaboration of the historical significance of technologies in economic growth, social progress and urban development, the author then goes on to introduce the most prominent smart urban information technologies before demonstrating the use of these technologies in various smart urban systems. The book then showcases some of the most significant cases of smart city best practice from across the globe before discussing the magnitude and prospects of smart technologies and systems for our cities and societies. "The interplay between smart urban technologies and city development is a relatively uncharted territory. Technology and the City aims to fill that gap, exploring the growing importance of smart technologies and systems in contemporary cities, and providing an in-depth understanding of both theoretical and practical aspects of smart urban technology adoption, and its implications for our cities. Beginning with an elaboration of the historical significance of technologies in economic growth, social progress and urban development, Yigitcanlar introduces the most prominent smart urban information technologies. The book showcases significant smart city practices from across the globe that uses smart urban technologies and systems most effectively. It explores the role of these technologies and asks how they can be adopted into the planning, development and management processes of cities for sustainable urban futures. This pioneering volume contributes to the conceptualisation and practice of smart technology and system adoption in our cities by disseminating both conceptual and empirical research findings with real-world best practice applications. With a multidisciplinary approach to themes of technology and urban development, this book is a key reference source for scholars, practitioners, consultants, city officials, policymakers and urban technology enthusiasts."--Publisher website

Social work and complex care systems: The case of people hospitalised with a disability

Health and hospital system reforms prioritise efficiency. However, initiatives can impact on people with new or existing disabilities who require time to maximise functional independence. With greater demands for shorter hospital stays social workers face increasing pressure to facilitate discharge. This paper reports findings from research identifying factors contributing to extended stays for adults with disabilities. We sought to better understand patient characteristics and discharge planning challenges by analysing a clinical data set of 80 patients and qualitative interviews with five experienced hospital social workers. Three key factors are identified: issues around rehabilitation services; assessment and planning for community care; and availability of and access to discharge options. Strategies to reduce length of stay are reported. We argue that building collaborative partnerships and working across multiple, complex systems and disciplines are vital to ensure these patients access appropriate community-based resources within the current health reform environment.

Using Bayesian networks to model surveillance in complex plant and animal health systems

In this chapter we consider biosecurity surveillance as part of a complex system comprising many different biological, environmental and human factors and their interactions. Modelling and analysis of surveillance strategies should take into account these complexities, and also facilitate the use and integration of the many types of different information that can provide insight into the system as a whole. After a brief discussion of a range of options, we focus on Bayesian networks for representing such complex systems. We summarize the features of Bayesian networks and describe these in the context of surveillance.

Enhancing the trust of location acquisition systems for critical applications and location-based security services

This paper identifies a number of critical infrastructure applications that are reliant on location services from cooperative location technologies such as GPS and GSM. We show that these location technologies can be represented in a general location model, such that the model components can be used for vulnerability analysis. We perform a vulnerability analysis on these components of GSM and GPS location systems as well as a number of augmentations to these systems.

Early childhood education for sustainability : why it matters, what it is, and how whole centre action research and systems thinking can help

The global financial crisis, global pandemics, global warming and peak oil are indicative of a world facing major environmental, social and economic problems. At the same time, world population continues to rise and global inequalities deepen. Children are the most vulnerable to the impacts of unsustainable living with specific harms arising because of their physical and cognitive vulnerabilities. Nevertheless, children do not have to be victims in the face of these challenges. Education, including early childhood education, has an important role to in building resilience and capabilities in children that equip them as active and informed citizens now and in the future and who are capable of contributing to healthy and sustainable ways of living. Drawing on educational change literature, action research, education for sustainability, health promotion and systems theory, this paper outlines three strategies that can help reorient early childhood education towards sustainability. One strategy is the adoption of whole centre approaches to sustainability and education for sustainability. This means working across the whole of a centre’s operations – curriculum and pedagogy, physical and social environments, its partnerships and community connections. The second strategy – applied in conjunction with the first – is the use of action research to investigate the early childhood setting and to create the desired changes. The third strategy is the adoption of systems thinking as a way of leveraging support and momentum for change so that education for sustainability goes beyond the initiatives of individual teachers and centres, and becomes a systems-wide imperative.

Design Optimisation of UAVs Systems achieved on a Framework Environment via Evolution and Game Theory

Over recent years, Unmanned Air Vehicles or UAVs have become a powerful tool for reconnaissance and surveillance tasks. These vehicles are now available in a broad size and capability range and are intended to fly in regions where the presence of onboard human pilots is either too risky or unnecessary. This paper describes the formulation and application of a design framework that supports the complex task of multidisciplinary design optimisation of UAVs systems via evolutionary computation. The framework includes a Graphical User Interface (GUI), a robust Evolutionary Algorithm optimiser named HAPEA, several design modules, mesh generators and post-processing capabilities in an integrated platform. These population –based algorithms such as EAs are good for cases problems where the search space can be multi-modal, non-convex or discontinuous, with multiple local minima and with noise, and also problems where we look for multiple solutions via Game Theory, namely a Nash equilibrium point or a Pareto set of non-dominated solutions. The application of the methodology is illustrated on conceptual and detailed multi-criteria and multidisciplinary shape design problems. Results indicate the practicality and robustness of the framework to find optimal shapes and trade—offs between the disciplinary analyses and to produce a set of non dominated solutions of an optimal Pareto front to the designer.

The urban water cycle : towards integrated resource management and more sustainable water management systems

The increasing scarcity of water in the world, along with rapid population increase in urban areas, gives reason for concern and highlights the need for integrating water and wastewater management practices. The uncontrolled growth in urban areas has made planning, management and expansion of water and wastewater infrastructure systems very difficult and expensive. In order to achieve sustainable wastewater treatment and promote the conservation of water and nutrient resources, this chapter advocates the need for a closed-loop treatment system approach, and the transformation of the traditional linear treatment systems into integrated cyclical treatment systems. The recent increased understanding of integrated resource management and a shift towards sustainable management and planning of water and wastewater infrastructure are also discussed.

Optimization problems for controlled mechanical systems : bridging the gap between theory and application

Mechanical control systems have become a part of our everyday life. Systems such as automobiles, robot manipulators, mobile robots, satellites, buildings with active vibration controllers and air conditioning systems, make life easier and safer, as well as help us explore the world we live in and exploit it’s available resources. In this chapter, we examine a specific example of a mechanical control system; the Autonomous Underwater Vehicle (AUV). Our contribution to the advancement of AUV research is in the area of guidance and control. We present innovative techniques to design and implement control strategies that consider the optimization of time and/or energy consumption. Recent advances in robotics, control theory, portable energy sources and automation increase our ability to create more intelligent robots, and allows us to conduct more explorations by use of autonomous vehicles. This facilitates access to higher risk areas, longer time underwater, and more efficient exploration as compared to human occupied vehicles. The use of underwater vehicles is expanding in every area of ocean science. Such vehicles are used by oceanographers, archaeologists, geologists, ocean engineers, and many others. These vehicles are designed to be agile, versatile and robust, and thus, their usage has gone from novelty to necessity for any ocean expedition.

Local adjustment and global adaptation of control periods for QoC management of control systems

Linking real-time schedulability directly to the Quality of Control (QoC), the ultimate goal of a control system, a hierarchical feedback QoC management framework with the Fixed Priority (FP) and the Earliest-Deadline-First (EDF) policies as plug-ins is proposed in this paper for real-time control systems with multiple control tasks. It uses a task decomposition model for continuous QoC evaluation even in overload conditions, and then employs heuristic rules to adjust the period of each of the control tasks for QoC improvement. If the total requested workload exceeds the desired value, global adaptation of control periods is triggered for workload maintenance. A sufficient stability condition is derived for a class of control systems with delay and period switching of the heuristic rules. Examples are given to demonstrate the proposed approach.