Medienvermittelte transnationale Öffentlichkeiten im Zeitalter praktischer Hybridisierung (English title: Mediated transnational publics in environments of practical hybridisation)

This article is concerned with the repercussions of societal change on transnational media. It offers a new understanding of multilingual programming strategies by examining “Radio MultiKulti” (RM), a public service radio station discontinued from 1/1/2009 by Rundfunk Berlin-Brandenburg. In its fourteen years of existence, “RM” had to implement a well-intended and politically-motivated logic of ‘multiethnic, intercultural service station’. However, as we demonstrate, such a direction, despite some achievements, has resulted in the constraints to RM’s journalistic activities and language policy, drawing criticism for the station’s economic viability. This paper proposes that multilingual media services are to be framed by the concept of practical hybridity that allows a necessary responsiveness towards an ever-changing media environment, at the moment within digital culture. Our approach draws on Mikhail Bakhtin’s and Yuri Lotman’s theoretical approaches to hybridity, as well as in-depth interviews conducted with “RM” staff from 2005 onwards, further interviews with key agents outside RM and a continuous monitoring of the public debate which culminated at the end of 2008 in the controversial decision to close the radio station. Against this background, the concluding remarks are meant to contribute to the scholarly debate on hybridization as well as to inform multilingual media policy in the 21st century.

Mining patterns and factors contributing to crash severity on road curves

Road curves are an important feature of road infrastructure and many serious crashes occur on road curves. In Queensland, the number of fatalities is twice as many on curves as that on straight roads. Therefore, there is a need to reduce drivers’ exposure to crash risk on road curves. Road crashes in Australia and in the Organisation for Economic Co-operation and Development(OECD) have plateaued in the last five years (2004 to 2008) and the road safety community is desperately seeking innovative interventions to reduce the number of crashes. However, designing an innovative and effective intervention may prove to be difficult as it relies on providing theoretical foundation, coherence, understanding, and structure to both the design and validation of the efficiency of the new intervention. Researchers from multiple disciplines have developed various models to determine the contributing factors for crashes on road curves with a view towards reducing the crash rate. However, most of the existing methods are based on statistical analysis of contributing factors described in government crash reports. In order to further explore the contributing factors related to crashes on road curves, this thesis designs a novel method to analyse and validate these contributing factors. The use of crash claim reports from an insurance company is proposed for analysis using data mining techniques. To the best of our knowledge, this is the first attempt to use data mining techniques to analyse crashes on road curves. Text mining technique is employed as the reports consist of thousands of textual descriptions and hence, text mining is able to identify the contributing factors. Besides identifying the contributing factors, limited studies to date have investigated the relationships between these factors, especially for crashes on road curves. Thus, this study proposed the use of the rough set analysis technique to determine these relationships. The results from this analysis are used to assess the effect of these contributing factors on crash severity. The findings obtained through the use of data mining techniques presented in this thesis, have been found to be consistent with existing identified contributing factors. Furthermore, this thesis has identified new contributing factors towards crashes and the relationships between them. A significant pattern related with crash severity is the time of the day where severe road crashes occur more frequently in the evening or night time. Tree collision is another common pattern where crashes that occur in the morning and involves hitting a tree are likely to have a higher crash severity. Another factor that influences crash severity is the age of the driver. Most age groups face a high crash severity except for drivers between 60 and 100 years old, who have the lowest crash severity. The significant relationship identified between contributing factors consists of the time of the crash, the manufactured year of the vehicle, the age of the driver and hitting a tree. Having identified new contributing factors and relationships, a validation process is carried out using a traffic simulator in order to determine their accuracy. The validation process indicates that the results are accurate. This demonstrates that data mining techniques are a powerful tool in road safety research, and can be usefully applied within the Intelligent Transport System (ITS) domain. The research presented in this thesis provides an insight into the complexity of crashes on road curves. The findings of this research have important implications for both practitioners and academics. For road safety practitioners, the results from this research illustrate practical benefits for the design of interventions for road curves that will potentially help in decreasing related injuries and fatalities. For academics, this research opens up a new research methodology to assess crash severity, related to road crashes on curves.

Transaction mining for fraud detection in ERP Systems

Despite all attempts to prevent fraud, it continues to be a major threat to industry and government. Traditionally, organizations have focused on fraud prevention rather than detection, to combat fraud. In this paper we present a role mining inspired approach to represent user behaviour in Enterprise Resource Planning (ERP) systems, primarily aimed at detecting opportunities to commit fraud or potentially suspicious activities. We have adapted an approach which uses set theory to create transaction profiles based on analysis of user activity records. Based on these transaction profiles, we propose a set of (1) anomaly types to detect potentially suspicious user behaviour, and (2) scenarios to identify inadequate segregation of duties in an ERP environment. In addition, we present two algorithms to construct a directed acyclic graph to represent relationships between transaction profiles. Experiments were conducted using a real dataset obtained from a teaching environment and a demonstration dataset, both using SAP R/3, presently the predominant ERP system. The results of this empirical research demonstrate the effectiveness of the proposed approach.

Automation of an underground mining vehicle using reactive navigation and opportunistic localization

This paper describes the implementation of an autonomous navigation system onto a 30 tonne Load-Haul-Dump truck. The control architecture is based on a robust reactive wall-following behaviour. To make it purposeful we provide driving hints derived from an approximate nodal-map. For most of the time, the vehicle is driven with weak localization (odometry). This need only be improved at intersections where decisions must be made - a technique we refer to as opportunistic localization. The truck has achieved full-speed autonomous operation at an artificial test mine, and subsequently, at a operational underground mine.

Autonomous control of underground mining vehicles using reactive navigation

Describes how many of the navigation techniques developed by the robotics research community over the last decade may be applied to a class of underground mining vehicles (LHDs and haul trucks). We review the current state-of-the-art in this area and conclude that there are essentially two basic methods of navigation applicable. We describe an implementation of a reactive navigation system on a 30 tonne LHD which has achieved full-speed operation at a production mine.

The international regulation of transnational mergers

Transnational mergers are mergers involving firms operating in more than one jurisdiction, or which occur in one jurisdiction but have an impact on competition in another. Being of this nature, they have the potential to raise competition law concerns in more than one jurisdiction. When they do, the transaction costs of the merger to the firms involved, and the competition law authorities, are likely to increase significantly and, even where the merger is allowed to proceed, delays are likely to occur in reaping the benefits of the merger. Ultimately, these costs are borne by consumers. This thesis will identify the nature and source of regulatory costs associated with transnational merger review and identify and evaluate possible mechanisms by which these costs might be reduced. It will conclude that there is no single panacea for transnational merger regulation, but that a multi-faceted approach, including the adoption of common filing forms, agreement on filing and review deadlines and continuing efforts toward increasing international cooperation in merger enforcement, is needed to reduce regulatory costs and more successfully improve the welfare outcomes to which merger regulation is directed.

Mining robotics

Mining is the process of extracting mineral resources from the Earth for commercial value. It is an ancient human activity which can be traced back to Palaeolithic times (43 000 years ago), where for example the mineral hematite was mined to produce the red pigment ochre. The importance of many mined minerals is reflected in the names of the major milestones in human civilizations: the stone, copper, bronze, and iron ages. Much later coal provided the energy that was critical to the industrial revolution and still underpins modern society, creating 38% of world energy generation today. Ancient mines used human and later animal labor and broke rock using stone tools, heat, and water, and later iron tools. Today’s mines are heavily mechanized with large diesel and electrically powered vehicles, and rock is broken with explosives or rock cutting machines.

Reactive navigation and opportunistic localization for autonomous underground mining vehicles

This paper describes an autonomous navigation system for a large underground mining vehicle. The control architecture is based on a robust reactive wall-following behaviour. To make it purposeful we provide driving hints derived from an approximate nodal-map. For most of the time, the vehicle is driven with weak localization (odometry). This need only be improved at intersections where decisions must be made – a technique we refer to as opportunistic localization. The paper briefly reviews absolute and relative navigation strategies, and describes an implementation of a reactive navigation system on a 30 tonne Load-Haul-Dump truck. This truck has achieved full-speed autonomous operation at an artificial test mine, and subsequently, at a operational underground mine.