Using image quality metrics to detect smoke-affected laser data

Field robots often rely on laser range finders (LRFs) to detect obstacles and navigate autonomously. Despite recent progress in sensing technology and perception algorithms, adverse environmental conditions, such as the presence of smoke, remain a challenging issue for these robots. In this paper, we investigate the possibility to improve laser-based perception applications by anticipating situations when laser data are affected by smoke, using supervised learning and state-of-the-art visual image quality analysis. We propose to train a k-nearest-neighbour (kNN) classifier to recognise situations where a laser scan is likely to be affected by smoke, based on visual data quality features. This method is evaluated experimentally using a mobile robot equipped with LRFs and a visual camera. The strengths and limitations of the technique are identified and discussed, and we show that the method is beneficial if conservative decisions are the most appropriate.

Corporate reputation and financial performance : underlying dimensions of corporate reputation and their relation to sustained financial performance

This thesis examined the relationship between firms' corporate reputation and their future financial performance. Corporate reputation was represented by measuring the level of senior executives' attention to a number of intangible firm' resources (e.g. financial reputation, service culture) within firms' annual reports over a 17 year period. Initial findings suggested there was only a small relationship between reputation and future performance which lead to a reformulation of the problem. Reputation was posited to be a source of corporate resilience that helped firms with stronger reputations to sustain superior financial performance in times of difficulty, as well as allowing them to rebound more quickly from performance decline. Results suggest this interpretation of corporate reputation as well as indicating that industry sectors operate in different reputational 'domains' in which the relative importance of financial versus stakeholder aspects of corporate reputation varies.

Constructing a clinical decision-making framework for image-guided radiotherapy using a Bayesian Network

A decision-making framework for image-guided radiotherapy (IGRT) is being developed using a Bayesian Network (BN) to graphically describe, and probabilistically quantify, the many interacting factors that are involved in this complex clinical process. Outputs of the BN will provide decision-support for radiation therapists to assist them to make correct inferences relating to the likelihood of treatment delivery accuracy for a given image-guided set-up correction. The framework is being developed as a dynamic object-oriented BN, allowing for complex modelling with specific sub-regions, as well as representation of the sequential decision-making and belief updating associated with IGRT. A prototype graphic structure for the BN was developed by analysing IGRT practices at a local radiotherapy department and incorporating results obtained from a literature review. Clinical stakeholders reviewed the BN to validate its structure. The BN consists of a sub-network for evaluating the accuracy of IGRT practices and technology. The directed acyclic graph (DAG) contains nodes and directional arcs representing the causal relationship between the many interacting factors such as tumour site and its associated critical organs, technology and technique, and inter-user variability. The BN was extended to support on-line and off-line decision-making with respect to treatment plan compliance. Following conceptualisation of the framework, the BN will be quantified. It is anticipated that the finalised decision-making framework will provide a foundation to develop better decision-support strategies and automated correction algorithms for IGRT.

‘Our’ community : corporate social responsibility, neoliberalisation, and mining industry community engagement in rural Australia

This paper addresses contemporary neoliberal mobilisations of community undertaken by private corporations. It does so by examining the ways in which the mining industry, empowered through the legitimising framework of corporate social responsibility, is increasingly and profoundly involved in shaping the meaning, practice, and experience of ‘local community’. We draw on a substantial Australian case study, consisting of interviews and document analysis, as a means to examine ‘community-engagement’ practices undertaken by BHP Billiton’s Ravensthorpe Nickel Operation in the Shire of Ravensthorpe in rural Australia. This engagement, we argue, as a process of deepening neoliberalisation simultaneously defines and transforms local community according to the logic of global capital. As such, this study has implications for critical understandings of the intersections among corporate social responsibility, neoliberalisation, community, and capital.

Four Aces : Bringing Communication Perspectives to Corporate Social Responsibility

The purpose of this chapter is to address the question of how communication studies can prove its value in relation to corporate social responsibility (CSR). As many disciplines seek to understand CSR, the role of communication has been relatively underexplored despite its prevalence in demonstrating and shaping social responsibility positions and practice. Literature review. The literature review points to what we consider as four aces. Communication studies alert us to (1) how meaning is constructed through communication, something that has implications for the management of organizations as publics hold different views of CSR and expect different things from them; (2) how a dialogue between an organization and its publics should unfold; (3) how practices of transparency can assist organizations to come across as trustworthy actors; and, importantly, (4) how a complexity view is fruitful to grasp the CSR communication process. These four key themes could be instructive for practitioners who want to argue for and demonstrate the usefulness of strategic communication for the management of CSR and bridge meso and macro levels of analysis.

Towards training-free appearance-based localization : probabilistic models for whole-image descriptors

Whole image descriptors have recently been shown to be remarkably robust to perceptual change especially compared to local features. However, whole-image-based localization systems typically rely on heuristic methods for determining appropriate matching thresholds in a particular environment. These environment-specific tuning requirements and the lack of a meaningful interpretation of these arbitrary thresholds limits the general applicability of these systems. In this paper we present a Bayesian model of probability for whole-image descriptors that can be seamlessly integrated into localization systems designed for probabilistic visual input. We demonstrate this method using CAT-Graph, an appearance-based visual localization system originally designed for a FAB-MAP-style probabilistic input. We show that using whole-image descriptors as visual input extends CAT-Graph’s functionality to environments that experience a greater amount of perceptual change. We also present a method of estimating whole-image probability models in an online manner, removing the need for a prior training phase. We show that this online, automated training method can perform comparably to pre-trained, manually tuned local descriptor methods.

Evaluation of MegaVoltage Cone Beam CT image quality with an unmodified Elekta Precise Linac and EPID : a feasibility study

In order to increase the accuracy of patient positioning for complex radiotherapy treatments various 3D imaging techniques have been developed. MegaVoltage Cone Beam CT (MVCBCT) can utilise existing hardware to implement a 3D imaging modality to aid patient positioning. MVCBCT has been investigated using an unmodified Elekta Precise linac and 15 iView amorphous silicon electronic portal imaging device (EPID). Two methods of delivery and acquisition have been investigated for imaging an anthropomorphic head phantom and quality assurance phantom. Phantom projections were successfully acquired and CT datasets reconstructed using both acquisition methods. Bone, tissue and air were 20 clearly resolvable in both phantoms even with low dose (22 MU) scans. The feasibility of MegaVoltage Cone beam CT was investigated using a standard linac, amorphous silicon EPID and a combination of a free open source reconstruction toolkit as well as custom in-house software written in Matlab. The resultant image quality has 25 been assessed and presented. Although bone, tissue and air were resolvable 2 in all scans, artifacts are present and scan doses are increased when compared with standard portal imaging. The feasibility of MVCBCT with unmodified Elekta Precise linac and EPID has been considered as well as the identification of possible areas for future development in artifact correction techniques to 30 further improve image quality.

Supermarkets’ governance of the agri-food supply chain : is the ‘corporate-environmental’ food regime evident in Australia?

This article investigates the extent to which the purported greening of food retailing and consumption in Australia is consistent with the development of a corporate-environmental food regime. Recent developments in food regime theory, particularly the concept of an emerging third food regime (the so-called ‘corporate-environmental food regime’), provide a useful organizing framework for understanding recent agri-restructuring trends. We find that, while a globally based, third food regime is becoming more apparent, the attributes that relate to corporate retail-driven greening of the supply chain are less evident within Australia’s domestic market than in its EU counterparts. However, there is some evidence that Australia’s export market is subject to some degree of ‘greening at a distance’ due to private regulations imposed by supermarkets overseas. We argue that while broader agri-restructuring trends may be evident at an international level, elements of greening specific to national contexts are important for determining the trajectory of any third food regime.

Continuous disclosure compliance: Does corporate governance matter?

Our study investigates the quality of firms’ continuous disclosure compliance during mandatory continuous disclosure reform, and whether the compliance quality is impacted by corporate governance, using the New Zealand market as the setting. We use a novel coding of different categories of disclosures (nonroutine, non-procedural and internal), which represents the extent of proprietary insider information inherent in disclosures, to evaluate firms’compliance quality. Our findings provide evidence that firms’ compliance quality improved after the reform, and this improvement is inconsistently impacted by corporate gvernance. Our findings provide important implications for regulators in their quest for a superior disclosure regime

Moulding them in the industry's image : journalism education's impact on students' professional views

Long-running debates over the value of university-based journalism education have suffered from a lack of empirical foundation, leading to a wide range of assertions both from those who see journalism education playing a crucial role in moulding future journalists and those who do not. Based on a survey of 320 Australian journalism students from six universities across the country, this study provides an account of the professional views these future journalists hold. Findings show that students hold broadly similar priorities in their role perceptions, albeit to different intensities from working journalists. The results point to a relationship between journalism education and the way in which students' views of journalism's watchdog role and its market orientation change over the course of their degree – to the extent that, once they are near completion of their degree, students have been moulded in the image of industry professionals.

Cell image classification using histograms, higher order statistics and adaboost

A cell classification algorithm that uses first, second and third order statistics of pixel intensity distributions over pre-defined regions is implemented and evaluated. A cell image is segmented into 6 regions extending from a boundary layer to an inner circle. First, second and third order statistical features are extracted from histograms of pixel intensities in these regions. Third order statistical features used are one-dimensional bispectral invariants. 108 features were considered as candidates for Adaboost based fusion. The best 10 stage fused classifier was selected for each class and a decision tree constructed for the 6-class problem. The classifier is robust, accurate and fast by design.

Real-time image classification for adaptive mission planning using an Autonomous Underwater Vehicle

Real-time image analysis and classification onboard robotic marine vehicles, such as AUVs, is a key step in the realisation of adaptive mission planning for large-scale habitat mapping in previously unexplored environments. This paper describes a novel technique to train, process, and classify images collected onboard an AUV used in relatively shallow waters with poor visibility and non-uniform lighting. The approach utilises Förstner feature detectors and Laws texture energy masks for image characterisation, and a bag of words approach for feature recognition. To improve classification performance we propose a usefulness gain to learn the importance of each histogram component for each class. Experimental results illustrate the performance of the system in characterisation of a variety of marine habitats and its ability to operate onboard an AUV's main processor suitable for real-time mission planning.

Effects of corporate support of a charity on public perceptions of the charity

A quasi-experimental design (N=517) was used to investigate the effect on audience response to a supported charity if corporate support is featured in an advertisement. The results indicate that corporate support of a charity appears not to influence audience attitudes and donation intentions for the charity. A small portion of the audience may be motivated to donate when learning of a large corporate donation to the charity. The level of individual's favourability for the charity was the strongest predictor of their attitudes and intentions. Gender was also a predictor of more positive charity attitudes, with females reporting more positive attitudes than males for three of four charities. Managerial implications and areas for future research are discussed.

Digital image databases support GIS operations

Evaluates trends in the imagery built into GIS applications to supplement existing vector data of streets, boundaries, infrastructure and utilities. These include large area digital orthophotos, Landsat and SPOT data. Future developments include 3 to 5 metre pixel resolutions from satellites, 1 to 2 metres from aircraft. GPS and improved image analysis techniques will also assist in improving resolution and accuracy.

The impact of corporate governance on private placements in Australia

In private placement transactions, issuing firms sell a block of securities to just a small group of investors at a discounted price. Non-participating shareholders suffer from ownership dilution and lose the opportunity to receive the discount. This thesis provides the first evidence on whether and how corporate governance can protect non-participating shareholders' interests. Results from an examination of 329 private placements issued by the top 250 Australian firms between 2002 and 2009 demonstrate that firms with higher governance quality are more likely to issue a share purchase plan (SPP) along with the private placement, thus providing greater protection to non-participating shareholders' interests.