Declining youth membership : the views of union officials

Across the industrialized west there has been a sharp decline in union membership (Frege and Kelly2003, Peetz 2002). Even more alarming are the lower unionization rates of young people and the steeper decline in these rates compared to older workers (Serrano and Waddington 2000). At the same time increasing numbers of young people still at school are participating in the labour market. There have been a number of explorations internationally of young people's union membership, but most either track membership decline over time, comparing adult and youth union density (Blanden and Machin 2003, Bryson et al. 2005, Haynes, Vowles and Boxall 2005, Canny 2002, OECD 2006), explore the general experience of young people in the labour market (for example, Lizen, Bolton and Pole 1999) or examine young people's view of unions (for example, Bulbeck 2008). This chapter however takes a different approach, exploring union officials' constructions of 'the problem' of low union density amongst youth. While the data in this study was obtained from Australia, the Australian context has strong similarities with those in other industrialized economies, not least because globalization has meant the spread of neo-liberal industrial relations (IR) policies and structures. Assuming that unions have choices open to them as to how they recruit and retain young people, it is important to analyse officials' construction of 'the problem', as this affects union strategizing and action.

Seeing the outer suburbs : addressing the urban bias in creative place thinking

Seeing the outer suburbs: addressing the urban bias in creative place thinking, Regional Studies. This paper draws upon quantitative and qualitative research into Australian cities to question the assumption that creative industries workers inherently seek to cluster in inner-urban areas. It challenges this foundational assumption by combining a critical application of the location quotient analysis of major Australian cities with qualitative research drawn from interviews with creative workers based in suburban Melbourne and Brisbane. The findings provide analyses as to why many creative industries workers prefer to locate themselves in outer suburban places. There is also discussion of the implications of these findings for future work on the cultural geography and policies of creative industries.

Evaluating automatic road detection across a large aerial imagery collection

The automated extraction of roads from aerial imagery can be of value for tasks including mapping, surveillance and change detection. Unfortunately, there are no public databases or standard evaluation protocols for evaluating these techniques. Many techniques are further hindered by a reliance on manual initialisation, making large scale application of the techniques impractical. In this paper, we present a public database and evaluation protocol for the evaluation of road extraction algorithms, and propose an improved automatic seed finding technique to initialise road extraction, based on a combination of geometric and colour features.

Towards automatic object segmentation with sequential multiple views

Object segmentation is one of the fundamental steps for a number of robotic applications such as manipulation, object detection, and obstacle avoidance. This paper proposes a visual method for incorporating colour and depth information from sequential multiview stereo images to segment objects of interest from complex and cluttered environments. Rather than segmenting objects using information from a single frame in the sequence, we incorporate information from neighbouring views to increase the reliability of the information and improve the overall segmentation result. Specifically, dense depth information of a scene is computed using multiple view stereo. Depths from neighbouring views are reprojected into the reference frame to be segmented compensating for imperfect depth computations for individual frames. The multiple depth layers are then combined with color information from the reference frame to create a Markov random field to model the segmentation problem. Finally, graphcut optimisation is employed to infer pixels belonging to the object to be segmented. The segmentation accuracy is evaluated over images from an outdoor video sequence demonstrating the viability for automatic object segmentation for mobile robots using monocular cameras as a primary sensor.

Feature-based visual odometry and featureless place recognition for SLAM in 2.5D environments

In this paper we present a novel algorithm for localization during navigation that performs matching over local image sequences. Instead of calculating the single location most likely to correspond to a current visual scene, the approach finds candidate matching locations within every section (subroute) of all learned routes. Through this approach, we reduce the demands upon the image processing front-end, requiring it to only be able to correctly pick the best matching image from within a short local image sequence, rather than globally. We applied this algorithm to a challenging downhill mountain biking visual dataset where there was significant perceptual or environment change between repeated traverses of the environment, and compared performance to applying the feature-based algorithm FAB-MAP. The results demonstrate the potential for localization using visual sequences, even when there are no visual features that can be reliably detected.

Autonomous aerial navigation and tracking of marine animals

In this paper, we describe the development of an independent and on-board visual servoing system which allows a computationally impoverished aerial vehicle to autonomously identify and track a moving surface target. Our image segmentation and target identification algorithms were developed with the specific task of monitoring whales at sea but could be adapted for other targets. Observing whales is important for many marine biology tasks and is currently performed manually from the shore or from boats. We also present hardware experiments which demonstrate the capabilities of our algorithms for object identification and tracking that enable a flying vehicle to track a moving target.

Space, place and early childhood literacy

This chapter examines the changing landscape of literacy in the early years and considers how the diverse spaces and places in which early literacy learning is promoted and takes place can be conceptualised and researched. We argue that early literacy research needs to extend beyond a language focus to become attentive to the embodied, material dimensions of learning environments. The discussion is organised in terms of three kinds of spaces within which children encounter opportunities to participate in communication and representational practices. These are domestic spaces, commercial spaces and spaces of formal education. Theories of spatiality and material semiotics provide the conceptual tools for interpreting research studies located in these spaces. Implications for educators are considered.

Making space for place-making pedagogies : stretching normative mandated literacy curriculum

In an era of normative standardised literacy curriculum continuing to make space for culturally responsive literacy pedagogy is on ongoing challenge for early childhood educators. Collaborative participatory research and ethnographic studies of teachers who accomplish innovative and inclusive early childhood education in culturally diverse high poverty communities is urgent for the profession. Such pedagogies involve complex understandings of the cultural and political histories, and the dynamic potential, of the places in which school communities are located. By incorporating the study of local histories and biographies and researching neighbourhood changes teachers adapt mandated curriculum to maintain community knowledges and allow for positive identity work at the same time as they meet the authorised systems objectives. When teachers work with children as co-researchers through the study of people's lives in particular places and times, the community and its complex histories become a rich resource for young people's literacy repertoires.

FPGA implementation of an evolutionary algorithm for autonomous unmanned aerial vehicle on-board path planning

In this paper, a hardware-based path planning architecture for unmanned aerial vehicle (UAV) adaptation is proposed. The architecture aims to provide UAVs with higher autonomy using an application specific evolutionary algorithm (EA) implemented entirely on a field programmable gate array (FPGA) chip. The physical attributes of an FPGA chip, being compact in size and low in power consumption, compliments it to be an ideal platform for UAV applications. The design, which is implemented entirely in hardware, consists of EA modules, population storage resources, and three-dimensional terrain information necessary to the path planning process, subject to constraints accounted for separately via UAV, environment and mission profiles. The architecture has been successfully synthesised for a target Xilinx Virtex-4 FPGA platform with 32% logic slices utilisation. Results obtained from case studies for a small UAV helicopter with environment derived from LIDAR (Light Detection and Ranging) data verify the effectiveness of the proposed FPGA-based path planner, and demonstrate convergence at rates above the typical 10 Hz update frequency of an autopilot system.

An integrated approach for precise road reconstruction from aerial imagery and LiDAR data

Accurate and detailed road models play an important role in a number of geospatial applications, such as infrastructure planning, traffic monitoring, and driver assistance systems. In this thesis, an integrated approach for the automatic extraction of precise road features from high resolution aerial images and LiDAR point clouds is presented. A framework of road information modeling has been proposed, for rural and urban scenarios respectively, and an integrated system has been developed to deal with road feature extraction using image and LiDAR analysis. For road extraction in rural regions, a hierarchical image analysis is first performed to maximize the exploitation of road characteristics in different resolutions. The rough locations and directions of roads are provided by the road centerlines detected in low resolution images, both of which can be further employed to facilitate the road information generation in high resolution images. The histogram thresholding method is then chosen to classify road details in high resolution images, where color space transformation is used for data preparation. After the road surface detection, anisotropic Gaussian and Gabor filters are employed to enhance road pavement markings while constraining other ground objects, such as vegetation and houses. Afterwards, pavement markings are obtained from the filtered image using the Otsu's clustering method. The final road model is generated by superimposing the lane markings on the road surfaces, where the digital terrain model (DTM) produced by LiDAR data can also be combined to obtain the 3D road model. As the extraction of roads in urban areas is greatly affected by buildings, shadows, vehicles, and parking lots, we combine high resolution aerial images and dense LiDAR data to fully exploit the precise spectral and horizontal spatial resolution of aerial images and the accurate vertical information provided by airborne LiDAR. Objectoriented image analysis methods are employed to process the feature classiffcation and road detection in aerial images. In this process, we first utilize an adaptive mean shift (MS) segmentation algorithm to segment the original images into meaningful object-oriented clusters. Then the support vector machine (SVM) algorithm is further applied on the MS segmented image to extract road objects. Road surface detected in LiDAR intensity images is taken as a mask to remove the effects of shadows and trees. In addition, normalized DSM (nDSM) obtained from LiDAR is employed to filter out other above-ground objects, such as buildings and vehicles. The proposed road extraction approaches are tested using rural and urban datasets respectively. The rural road extraction method is performed using pan-sharpened aerial images of the Bruce Highway, Gympie, Queensland. The road extraction algorithm for urban regions is tested using the datasets of Bundaberg, which combine aerial imagery and LiDAR data. Quantitative evaluation of the extracted road information for both datasets has been carried out. The experiments and the evaluation results using Gympie datasets show that more than 96% of the road surfaces and over 90% of the lane markings are accurately reconstructed, and the false alarm rates for road surfaces and lane markings are below 3% and 2% respectively. For the urban test sites of Bundaberg, more than 93% of the road surface is correctly reconstructed, and the mis-detection rate is below 10%.

Their children's first educators : parents' views about child sexual abuse prevention education

In this descriptive focus group study, we investigated parents’ views about child sexual abuse prevention education at home and in schools. Focus groups were conducted with a sample of 30 Australian adults who identified as the parent or caregiver of a child/children aged 0–5 years. The study explored (1) parents’ knowledge about child sexual abuse prevention, (2) the child sexual abuse prevention messages they provided to their children and the topics they discussed, (3) their attitudes towards child sexual abuse prevention education in schools, and (4) their preferences for content. Data analysis provided seven key themes in these four areas: knowledge (the inadequacy of their own prevention education; and how important is stranger danger now?); messages (bodies, touching, and relationships; the role of protective adults; and parent–child communication); attitudes (voice and choice); and preferences (not the nitty gritty, just the basics). The findings may be useful in assisting school authorities and providers of child sexual abuse prevention programs to better understand parents’ contributions to child sexual abuse prevention education, and their perspectives in relation to provision of school-based prevention programs.

Place and Space: Community in the Internet Economy and What This Will Mean for Property

By 2020 Australia‟s National Digital Economy Strategy aims to increase household online participation and engage 12 per cent of all employees in teleworking arrangements. Achieving these goals is generally perceived as positive due to the reduced impact on the natural environment from less use of transport. However, this also will enable greater flexibility as to where people live and thus will impact upon the maintenance and formation of communities and on property use. This paper commences by clarifying what is Australia‟s internet economy before highlighting the impact of the internet on community formation and maintenance. The paper concludes by identifying what the achievement of these goals will mean for property use in the future.

Some reflections about P2M : the place of the mirror

The purpose of this paper is to provide some insights about P2M, and more specifically, to develop some thoughts about Project Management seen as a Mirror, a place for reflection…, between the Mission of organisation and its actual creation of Values (with s: a source of value for people, organisations and society). This place is the realm of complexity, of interactions between multiple variables, each of them having a specific time horizon and occupying a specific place, playing a specific role. Before developing this paper I would like to borrow to my colleague and friend, Professor Ohara, the following, part of a paper going to be presented at IPMA World Congress, in New Delhi later this year in November 2005. “P2M is the Japanese version of project & program management, which is the first standard guide for education and certification developed in 2001. A specific finding of P2M is characterized by “mission driven management of projects” or a program which harness complexity of problem solving observed in the interface between technical system and business model.” (Ohara, 2005, IPMA Conference, New Delhi) “The term of “mission” is a key word in the field of corporate strategy, where it expresses raison d’être or “value of business”. It is more specifically used for expressing “the client needs” in terms of a strategic business unit. The concept of mission is deemed to be a useful tool to share essential content of value and needs in message for complex project.” (Ohara, 2005, IPMA Conference, New Delhi) “Mission is considered as a significant “metamodel representation” by several reasons. First, it represents multiple values for aspiration. The central objective of mission initiative is profiling of ideality in the future from reality, which all stakeholders are glad to accept and share. Second, it shall be within a stretch of efforts, and not beyond or outside of the realization. Though it looks like unique, it has to depict a solid foundation. The pragmatic sense of equilibrium between innovation and adaptation is required for the mission. Third, it shall imply a rough sketch for solution to critical issues for problems in reality.” (Ohara, 2005, IPMA Conference, New Delhi) “Project modeling” idea has been introduced in P2M program management. A package of three project models of “scheme”, “system” and “service” are given as a reference type program. (Ohara, 2005, IPMA Conference, New Delhi) If these quotes apply to P2M, they are fully congruent with the results of the research undertaken and the resulting meta-model & meta-method developed by the CIMAP, ESC Lille Research Centre in Project & Program Management, since the 80’s. The paper starts by questioning the common Project Management (PM) paradigm. Then discussing the concept of Project, it argues that an alternative epistemological position should be taken to capture Page 2 / 11 the very nature of the PM field. Based on this, a development about “the need of modelling to understand” is proposed grounded on two theoretical roots. This leads to the conclusion that, in order to enables this modelling, a standard approach is necessary, but should be understood under the perspective of the Theory of Convention in order to facilitate a situational and contextual application.

Using mobile social media and GIS in health and place research

This paper presents new research methods that combine the use of location-based, social media on mobile phones with geographic information systems (GIS) to explore connections between people, place and health. It discusses the feasibility, limitations, and benefits of using these methods, which enable real-time, location-based, quantitative data to be collected on the recreation, consumption, and physical activity patterns of urban residents in Brisbane, Queensland. The study employs mechanisms already inherent in popular mobile social media applications (Facebook, Twitter and Foursquare) to collect this data. The research methods presented in this paper are innovative and potentially applicable to an increasing number of academic research areas, as well as to a growing range of service providers that benefit from monitoring consumer behaviour, and responding to emerging changes in these patterns and trends. The ability to both collect and map objective, real-time data about the consumption, leisure, recreation, and physical activity patterns amongst urban communities has direct implications for a range of research disciplines including media studies, advertising, health promotion, social marketing, public health inequalities, and urban design.

Wind-energy based path planning for electric unmanned aerial vehicles using Markov Decision Processes

Exploiting wind-energy is one possible way to ex- tend flight duration for Unmanned Arial Vehicles. Wind-energy can also be used to minimise energy consumption for a planned path. In this paper, we consider uncertain time-varying wind fields and plan a path through them. A Gaussian distribution is used to determine uncertainty in the Time-varying wind fields. We use Markov Decision Process to plan a path based upon the uncertainty of Gaussian distribution. Simulation results that compare the direct line of flight between start and target point and our planned path for energy consumption and time of travel are presented. The result is a robust path using the most visited cell while sampling the Gaussian distribution of the wind field in each cell.