Using data mining to predict road crash count with a focus on skid resistance values

Road crashes cost world and Australian society a significant proportion of GDP, affecting productivity and causing significant suffering for communities and individuals. This paper presents a case study that generates data mining models that contribute to understanding of road crashes by allowing examination of the role of skid resistance (F60) and other road attributes in road crashes. Predictive data mining algorithms, primarily regression trees, were used to produce road segment crash count models from the road and traffic attributes of crash scenarios. The rules derived from the regression trees provide evidence of the significance of road attributes in contributing to crash, with a focus on the evaluation of skid resistance.

Corrupt police networks : uncovering hidden relationship patterns, functions and roles

This article applies social network analysis techniques to a case study of police corruption in order to produce findings which will assist in corruption prevention and investigation. Police corruption is commonly studied but rarely are sophisticated tools of analyse engaged to add rigour to the field of study. This article analyses the ‘First Joke’ a systemic and long lasting corruption network in the Queensland Police Force, a state police agency in Australia. It uses the data obtained from a commission of inquiry which exposed the network and develops hypotheses as to the nature of the networks structure based on existing literature into dark networks and criminal networks. These hypotheses are tested by entering the data into UCINET and analysing the outcomes through social network analysis measures of average path distance, centrality and density. The conclusions reached show that the network has characteristics not predicted by the literature.

Characterisation of public mobile data networks for aeronautical telemetry purposes

This paper describes the characterisation for airborne uses of the public mobile data communication systems known broadly as 3G. The motivation for this study was to explore how this mature public communication systems could be used for aviation purposes. An experimental system was fitted to a light aircraft to record communication latency, line speed, RF level, packet loss and cell tower identifier. Communications was established using internet protocols and connection was made to a local server. The aircraft was flown in both remote and populous areas at altitudes up to 8500ft in a region located in South East Queensland, Australia. Results show that the average airborne RF levels are better than those on the ground by 21% and in the order of -77 dbm. Latencies were in the order of 500 ms (1/2 the latency of Iridium), an average download speed of 0.48 Mb/s, average uplink speed of 0.85 Mb/s, a packet of information loss of 6.5%. The maximum communication range was also observed to be 70km from a single cell station. The paper also describes possible limitations and utility of using such a communications architecture for both manned and unmanned aircraft systems.

Towards a relational theory of copyright law

This research provides a systematic and theoretical analysis of the digital challenges to the established exclusive regime of the economic rights enjoyed by authors (and related rightholders) under the law of copyright. Accordingly, this research has developed a relational theory of authorship and a relational approach to copyright, contending that the regulatory emphasis of copyright law should focus on the facilitation of the dynamic relations between the culture, the creators, the future creators, the users and the public, rather than the allocation of resources in a static world. In this networked digital world, the creative works and contents have become increasingly vital for people to engage in creativity and cultural innovation, and for the evolution of the economy. Hence, it is argued that today copyright owners, as content holders, have certain obligations to make their works accessible and available to the public under fair conditions. This research sets forward a number of recommendations for the reform of the current copyright system.

Secure data aggregation in wireless sensor networks

A Wireless Sensor Network (WSN) is a set of sensors that are integrated with a physical environment. These sensors are small in size, and capable of sensing physical phenomena and processing them. They communicate in a multihop manner, due to a short radio range, to form an Ad Hoc network capable of reporting network activities to a data collection sink. Recent advances in WSNs have led to several new promising applications, including habitat monitoring, military target tracking, natural disaster relief, and health monitoring. The current version of sensor node, such as MICA2, uses a 16 bit, 8 MHz Texas Instruments MSP430 micro-controller with only 10 KB RAM, 128 KB program space, 512 KB external ash memory to store measurement data, and is powered by two AA batteries. Due to these unique specifications and a lack of tamper-resistant hardware, devising security protocols for WSNs is complex. Previous studies show that data transmission consumes much more energy than computation. Data aggregation can greatly help to reduce this consumption by eliminating redundant data. However, aggregators are under the threat of various types of attacks. Among them, node compromise is usually considered as one of the most challenging for the security of WSNs. In a node compromise attack, an adversary physically tampers with a node in order to extract the cryptographic secrets. This attack can be very harmful depending on the security architecture of the network. For example, when an aggregator node is compromised, it is easy for the adversary to change the aggregation result and inject false data into the WSN. The contributions of this thesis to the area of secure data aggregation are manifold. We firstly define the security for data aggregation in WSNs. In contrast with existing secure data aggregation definitions, the proposed definition covers the unique characteristics that WSNs have. Secondly, we analyze the relationship between security services and adversarial models considered in existing secure data aggregation in order to provide a general framework of required security services. Thirdly, we analyze existing cryptographic-based and reputationbased secure data aggregation schemes. This analysis covers security services provided by these schemes and their robustness against attacks. Fourthly, we propose a robust reputationbased secure data aggregation scheme for WSNs. This scheme minimizes the use of heavy cryptographic mechanisms. The security advantages provided by this scheme are realized by integrating aggregation functionalities with: (i) a reputation system, (ii) an estimation theory, and (iii) a change detection mechanism. We have shown that this addition helps defend against most of the security attacks discussed in this thesis, including the On-Off attack. Finally, we propose a secure key management scheme in order to distribute essential pairwise and group keys among the sensor nodes. The design idea of the proposed scheme is the combination between Lamport's reverse hash chain as well as the usual hash chain to provide both past and future key secrecy. The proposal avoids the delivery of the whole value of a new group key for group key update; instead only the half of the value is transmitted from the network manager to the sensor nodes. This way, the compromise of a pairwise key alone does not lead to the compromise of the group key. The new pairwise key in our scheme is determined by Diffie-Hellman based key agreement.

Scaling acoustic data analysis through collaboration and automation

Monitoring and assessing environmental health is becoming increasingly important as human activity and climate change place greater pressure on global biodiversity. Acoustic sensors provide the ability to collect data passively, objectively and continuously across large areas for extended periods of time. While these factors make acoustic sensors attractive as autonomous data collectors, there are significant issues associated with large-scale data manipulation and analysis. We present our current research into techniques for analysing large volumes of acoustic data effectively and efficiently. We provide an overview of a novel online acoustic environmental workbench and discuss a number of approaches to scaling analysis of acoustic data; collaboration, manual, automatic and human-in-the loop analysis.

Closing the gap between policy and 'Law' : Indigenous homelands and a working future

The Northern Territory Government's Working Future: Outstations/Homelands (2009) policy statement gives effect to the Council of Australian Government's Closing the Gap policy on Indigenous housing and remote service delivery. These policies mark a radical shift in public policy that winds back the outstations and homelands movement that began in the 1970's. This paper examines Indigenous homelands policy and considers whether these policies are consistent with the Indigenous human rights and in particular the United Nations Declaration on the Rights of Indigenous Peoples (2007), which Australia endorsed in 2009. The author argues that the current homelands policy breaches a number of Indigenous human rights and promotes assimiliation by forcing Indigenous Australians to relocate to access basic services such as health, housing and education. As a consequence these policies are counter-intuitive to the overall Closing the Gap goals of improving Indigenous health outcomes because they fail to take into account the importance of country and culture to Indigenous wellbeing. She concludes that Australian governments need to formulate a homelands policy that is consistent with Indigenous human rights and in particular the right of self determination, enjoyment of culture and protection against forced assimilation.

The Law of Real Property Mortgages

This book examines the principles and practice of real estate mortgages in an easily accessible text referenced to all the Australian States. It specifically deals with the major theoretical and practical aspects of the land mortgage including vitiating factors in formation, mortgagees powers and duties and mortgagors’ rights both statutory and other, assignment, insurance and discharge. As a successor to Mortgages Law in Australia, this book adopts an exclusive focus on real estate mortgages in Australia and provides a thorough account of the law through analysis of the plethora of court decisions and statutory provisions in this area. Duncan and Dixon analyse the substance of the mortgage transaction from creation through to rights of enforcement. This analysis includes detailed consideration of the rights and obligations of both mortgagors and mortgagees covering topics such as priorities and tacking, insurance, variation and assignment, rights of discharge, entry into possession, foreclosure and power of sale. In addition, the book contains a separate chapter on factors that may affect the validity and enforcement of a mortgage together with separate consideration of a mortgagee’s right to enforce a guarantee provided on behalf of a mortgagor and the rights and liabilities associated with a receivership regime initiated by a mortgagee. Written for the national market, the book is one of the few substantial works on this subject for practitioners throughout Australia. It is a very accessible text which enables readers to decide whether or not they have a problem and provides primary guidance to its solution. The book has been deliberately, heavily referenced to incorporate statutory references from across Australia and contains extensive case analysis in order to satisfy both these objectives.

Using reputation management in participatory sensing for data classification

Participatory sensing enables collection, processing, dissemination and analysis of environmental sensory data by ordinary citizens, through mobile devices. Researchers have recognized the potential of participatory sensing and attempted applying it to many areas. However, participants may submit low quality, misleading, inaccurate, or even malicious data. Therefore, finding a way to improve the data quality has become a significant issue. This study proposes using reputation management to classify the gathered data and provide useful information for campaign organizers and data analysts to facilitate their decisions.