Point-to-point speed enforcement

This report reviews the use of point-to-point speed enforcement internationally in order to provide principles for better practice for its use in Australia and New Zealand. Point-to-point enforcement is a relatively new technological approach to speed enforcement which involves measuring the average speed of vehicles passing a series of cameras, by using automatic number plate recognition (ANPR) and other technologies. The approach has been implemented or trialled in a number of countries including Australia, New Zealand, the United Kingdom, the Netherlands, Austria, Italy, Switzerland and France. The major research activities were undertaken for the preparation of this report included: (1) an extensive review of the international literature; (2) stakeholder consultation with international and domestic organisations. To date, there have been no formal evaluations of point-to- point speed enforcement in Australia or New Zealand.

Point-to-point speed enforcement : recommendations for better practice

Point-to-point speed cameras are a relatively new and innovative technological approach to speed enforcement that is increasingly been used in a number of highly motorised countries. Previous research has provided evidence of the positive impact of this approach on vehicle speeds and crash rates, as well as additional traffic related outcomes such as vehicle emissions and traffic flow. This paper reports on the conclusions and recommendations of a large-scale project involving extensive consultation with international and domestic (Australian) stakeholders to explore the technological, operational, and legislative characteristics associated with the technology. More specifically, this paper provides a number of recommendations for better practice regarding the implementation of point-to-point speed enforcement in the Australian and New Zealand context. The broader implications of the research, as well as directions for future research, are also discussed.

Rejoinder to James Hamilton

Hamilton (2001) makes a number of comments on our paper (Harding and Pagan, 2002b). The objectives of this rejoinder are, firstly, to note the areas in which we agree; secondly, to define with greater clarity the areas in which we disagree; and, thirdly, to point to other papers, including a longer version of this response, where we have dealt with some of the issues that he raises. The core of our debate with him is whether one should use an algorithm with a specified set of rules for determining the turning points in economic activity or whether one should use a parametric model that features latent states. Hamilton begins his criticism by stating that there is a philosophical distinction between the two methods for dating cycles and concludes that the method we use “leaves vague and intuitive exactly what this algorithm is intended to measure”. Nothing is further from the truth. When seeking ways to decide on whether a turning point has occurred it is always useful to ask the question, what is a recession? Common usage suggests that it is a decline in the level of economic activity that lasts for some time. For this reason it has become standard to describe a recession as a decline in GDP that lasts for more than two quarters. Finding periods in which quarterly GDP declined for two periods is exactly what our approach does. What is vague about this?

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%.

3D reconstruction of long bones utilising magnetic resonance imaging (MRI)

The design of pre-contoured fracture fixation implants (plates and nails) that correctly fit the anatomy of a patient utilises 3D models of long bones with accurate geometric representation. 3D data is usually available from computed tomography (CT) scans of human cadavers that generally represent the above 60 year old age group. Thus, despite the fact that half of the seriously injured population comes from the 30 year age group and below, virtually no data exists from these younger age groups to inform the design of implants that optimally fit patients from these groups. Hence, relevant bone data from these age groups is required. The current gold standard for acquiring such data–CT–involves ionising radiation and cannot be used to scan healthy human volunteers. Magnetic resonance imaging (MRI) has been shown to be a potential alternative in the previous studies conducted using small bones (tarsal bones) and parts of the long bones. However, in order to use MRI effectively for 3D reconstruction of human long bones, further validations using long bones and appropriate reference standards are required. Accurate reconstruction of 3D models from CT or MRI data sets requires an accurate image segmentation method. Currently available sophisticated segmentation methods involve complex programming and mathematics that researchers are not trained to perform. Therefore, an accurate but relatively simple segmentation method is required for segmentation of CT and MRI data. Furthermore, some of the limitations of 1.5T MRI such as very long scanning times and poor contrast in articular regions can potentially be reduced by using higher field 3T MRI imaging. However, a quantification of the signal to noise ratio (SNR) gain at the bone - soft tissue interface should be performed; this is not reported in the literature. As MRI scanning of long bones has very long scanning times, the acquired images are more prone to motion artefacts due to random movements of the subject‟s limbs. One of the artefacts observed is the step artefact that is believed to occur from the random movements of the volunteer during a scan. This needs to be corrected before the models can be used for implant design. As the first aim, this study investigated two segmentation methods: intensity thresholding and Canny edge detection as accurate but simple segmentation methods for segmentation of MRI and CT data. The second aim was to investigate the usability of MRI as a radiation free imaging alternative to CT for reconstruction of 3D models of long bones. The third aim was to use 3T MRI to improve the poor contrast in articular regions and long scanning times of current MRI. The fourth and final aim was to minimise the step artefact using 3D modelling techniques. The segmentation methods were investigated using CT scans of five ovine femora. The single level thresholding was performed using a visually selected threshold level to segment the complete femur. For multilevel thresholding, multiple threshold levels calculated from the threshold selection method were used for the proximal, diaphyseal and distal regions of the femur. Canny edge detection was used by delineating the outer and inner contour of 2D images and then combining them to generate the 3D model. Models generated from these methods were compared to the reference standard generated using the mechanical contact scans of the denuded bone. The second aim was achieved using CT and MRI scans of five ovine femora and segmenting them using the multilevel threshold method. A surface geometric comparison was conducted between CT based, MRI based and reference models. To quantitatively compare the 1.5T images to the 3T MRI images, the right lower limbs of five healthy volunteers were scanned using scanners from the same manufacturer. The images obtained using the identical protocols were compared by means of SNR and contrast to noise ratio (CNR) of muscle, bone marrow and bone. In order to correct the step artefact in the final 3D models, the step was simulated in five ovine femora scanned with a 3T MRI scanner. The step was corrected using the iterative closest point (ICP) algorithm based aligning method. The present study demonstrated that the multi-threshold approach in combination with the threshold selection method can generate 3D models from long bones with an average deviation of 0.18 mm. The same was 0.24 mm of the single threshold method. There was a significant statistical difference between the accuracy of models generated by the two methods. In comparison, the Canny edge detection method generated average deviation of 0.20 mm. MRI based models exhibited 0.23 mm average deviation in comparison to the 0.18 mm average deviation of CT based models. The differences were not statistically significant. 3T MRI improved the contrast in the bone–muscle interfaces of most anatomical regions of femora and tibiae, potentially improving the inaccuracies conferred by poor contrast of the articular regions. Using the robust ICP algorithm to align the 3D surfaces, the step artefact that occurred by the volunteer moving the leg was corrected, generating errors of 0.32 ± 0.02 mm when compared with the reference standard. The study concludes that magnetic resonance imaging, together with simple multilevel thresholding segmentation, is able to produce 3D models of long bones with accurate geometric representations. The method is, therefore, a potential alternative to the current gold standard CT imaging.

Labeling white matter tracts in hardi by fusing multiple tract atlases with applications to genetics

Accurate identification of white matter structures and segmentation of fibers into tracts is important in neuroimaging and has many potential applications. Even so, it is not trivial because whole brain tractography generates hundreds of thousands of streamlines that include many false positive fibers. We developed and tested an automatic tract labeling algorithm to segment anatomically meaningful tracts from diffusion weighted images. Our multi-atlas method incorporates information from multiple hand-labeled fiber tract atlases. In validations, we showed that the method outperformed the standard ROI-based labeling using a deformable, parcellated atlas. Finally, we show a high-throughput application of the method to genetic population studies. We use the sub-voxel diffusion information from fibers in the clustered tracts based on 105-gradient HARDI scans of 86 young normal twins. The whole workflow shows promise for larger population studies in the future.

My place through my eyes : a social constructionist approach to researching the relationships between socioeconomic living contexts and physical activity

There is a growing evidence-base in the epidemiological literature that demonstrates significant associations between people’s living circumstances – including their place of residence – and their health-related practices and outcomes (Leslie, 2005; Karpati, Bassett, & McCord, 2006; Monden, Van Lenthe, & Mackenbach, 2006; Parkes & Kearns, 2006; Cummins, Curtis, Diez-Roux, & Macintyre, 2007; Turrell, Kavanagh, Draper, & Subramanian, 2007). However, these findings raise questions about the ways in which living places, such as households and neighbourhoods, figure in the pathways connecting people and health (Frolich, Potvin, Chabot, & Corin, 2002; Giles-Corti, 2006; Brown et al, 2006; Diez Roux, 2007). This thesis addressed these questions via a mixed methods investigation of the patterns and processes connecting people, place, and their propensity to be physically active. Specifically, the research in this thesis examines a group of lower-socioeconomic residents who had recently relocated from poorer suburbs to a new urban village with a range of health-related resources. Importantly, the study contrasts their historical relationship with physical activity with their reactions to, and everyday practices in, a new urban setting designed to encourage pedestrian mobility and autonomy. The study applies a phenomenological approach to understanding living contexts based on Berger and Luckman’s (1966) conceptual framework in The Social Construction of Reality. This framework enables a questioning of the concept of context itself, and a treatment of it beyond environmental factors to the processes via which experiences and interactions are made meaningful. This approach makes reference to people’s histories, habituations, and dispositions in an exploration between social contexts and human behaviour. This framework for thinking about context is used to generate an empirical focus on the ways in which this residential group interacts with various living contexts over time to create a particular construction of physical activity in their lives. A methodological approach suited to this thinking was found in Charmaz’s (1996; 2001; 2006) adoption of a social constructionist approach to grounded theory. This approach enabled a focus on people’s own constructions and versions of their experiences through a rigorous inductive method, which provided a systematic strategy for identifying patterns in the data. The findings of the study point to factors such as ‘childhood abuse and neglect’, ‘early homelessness’, ‘fear and mistrust’, ‘staying indoors and keeping to yourself’, ‘conflict and violence’, and ‘feeling fat and ugly’ as contributors to an ongoing core category of ‘identity management’, which mediates the relationship between participants’ living contexts and their physical activity levels. It identifies barriers at the individual, neighbourhood, and broader ecological levels that prevent this residential group from being more physically active, and which contribute to the ways in which they think about, or conceptualise, this health-related behaviour in relationship to their identity and sense of place – both geographic and societal. The challenges of living well and staying active in poorer neighbourhoods and in places where poverty is concentrated were highlighted in detail by participants. Participants’ reactions to the new urban neighbourhood, and the depth of their engagement with the resources present, are revealed in the context of their previous life-experiences with both living places and physical activity. Moreover, an understanding of context as participants’ psychological constructions of various social and living situations based on prior experience, attitudes, and beliefs was formulated with implications for how the relationship between socioeconomic contextual effects on health are studied in the future. More detailed findings are presented in three published papers with implications for health promotion, urban design, and health inequalities research. This thesis makes a substantive, conceptual, and methodological contribution to future research efforts interested in how physical activity is conceptualised and constructed within lower socioeconomic living contexts, and why this is. The data that was collected and analysed for this PhD generates knowledge about the psychosocial processes and mechanisms behind the patterns observed in epidemiological research regarding socioeconomic health inequalities. Further, it highlights the ways in which lower socioeconomic living contexts tend to shape dispositions, attitudes, and lifestyles, ultimately resulting in worse health and life chances for those who occupy them.

“I want to see the Queen” : experiences of service use by ageing people with an intellectual disability

People with intellectual disability are a relatively new but growing minority group within Australia's ageing population. Disability policies point to the equal right of people with disabilities to a quality of life similar to that of other citizens. Disability services are increasingly required to provide individualised and responsive services, irrespective of age, for people with lifelong disabilities. The present study explored the everyday lives of older people with intellectual disability in Victoria and Queensland, examining their experiences of using disability services and the ways in which services responded to their ageing. The aim of the study was to inform practice and service development for older people with intellectual disability. The findings suggest that services facilitate important social relationships with other service users and staff. Most older people had a sense of belonging and led busy but directionless lives in two disconnected worlds. Their lives were subject to significant external present-focused control. Yet, despite this, neither services nor family members took responsibility for ensuring their sense of continuity or supporting the development of plans about their future. The experiences described suggest an urgent need for, but significant challenges in the implementation of, holistic indivdualised planning similar to the UK concept of person-centred planning.

Improved simultaneous computation of motion detection and optical flow for object tracking

Object tracking systems require accurate segmentation of the objects from the background for effective tracking. Motion segmentation or optical flow can be used to segment incoming images. Whilst optical flow allows multiple moving targets to be separated based on their individual velocities, optical flow techniques are prone to errors caused by changing lighting and occlusions, both common in a surveillance environment. Motion segmentation techniques are more robust to fluctuating lighting and occlusions, but don't provide information on the direction of the motion. In this paper we propose a combined motion segmentation/optical flow algorithm for use in object tracking. The proposed algorithm uses the motion segmentation results to inform the optical flow calculations and ensure that optical flow is only calculated in regions of motion, and improve the performance of the optical flow around the edge of moving objects. Optical flow is calculated at pixel resolution and tracking of flow vectors is employed to improve performance and detect discontinuities, which can indicate the location of overlaps between objects. The algorithm is evaluated by attempting to extract a moving target within the flow images, given expected horizontal and vertical movement (i.e. the algorithms intended use for object tracking). Results show that the proposed algorithm outperforms other widely used optical flow techniques for this surveillance application.

Accurate silhouettes for surveillance : improved motion segmentation using graph cuts

Silhouettes are common features used by many applications in computer vision. For many of these algorithms to perform optimally, accurately segmenting the objects of interest from the background to extract the silhouettes is essential. Motion segmentation is a popular technique to segment moving objects from the background, however such algorithms can be prone to poor segmentation, particularly in noisy or low contrast conditions. In this paper, the work of [3] combining motion detection with graph cuts, is extended into two novel implementations that aim to allow greater uncertainty in the output of the motion segmentation, providing a less restricted input to the graph cut algorithm. The proposed algorithms are evaluated on a portion of the ETISEO dataset using hand segmented ground truth data, and an improvement in performance over the motion segmentation alone and the baseline system of [3] is shown.

Group segmentation during object tracking using optical flow discontinuities

Within a surveillance video, occlusions are commonplace, and accurately resolving these occlusions is key when seeking to accurately track objects. The challenge of accurately segmenting objects is further complicated by the fact that within many real-world surveillance environments, the objects appear very similar. For example, footage of pedestrians in a city environment will consist of many people wearing dark suits. In this paper, we propose a novel technique to segment groups and resolve occlusions using optical flow discontinuities. We demonstrate that the ratio of continuous to discontinuous pixels within a region can be used to locate the overlapping edges, and incorporate this into an object tracking framework. Results on a portion of the ETISEO database show that the proposed algorithm results in improved tracking performance overall, and improved tracking within occlusions.

An approach to access control under uncertainty

In dynamic and uncertain environments such as healthcare, where the needs of security and information availability are difficult to balance, an access control approach based on a static policy will be suboptimal regardless of how comprehensive it is. The uncertainty stems from the unpredictability of users’ operational needs as well as their private incentives to misuse permissions. In Role Based Access Control (RBAC), a user’s legitimate access request may be denied because its need has not been anticipated by the security administrator. Alternatively, even when the policy is correctly specified an authorised user may accidentally or intentionally misuse the granted permission. This paper introduces a novel approach to access control under uncertainty and presents it in the context of RBAC. By taking insights from the field of economics, in particular the insurance literature, we propose a formal model where the value of resources are explicitly defined and an RBAC policy (entailing those predictable access needs) is only used as a reference point to determine the price each user has to pay for access, as opposed to representing hard and fast rules that are always rigidly applied.

When is a spinoff the best way to pursue a radical innovation? Insights from Shell technology ventures

The technology and innovation management literature offers somewhat conflicting evidence with regards to the formation of spinoff companies for radically new technologies. Sometimes spinoffs seem to be a very effective strategy—but not always. An obvious question emerges: under what conditions is a spinoff the best way to pursue a radical technology? This paper sheds light on this question by presenting case study evidence from spinoff firms within the Shell Technology Ventures portfolio. The data point to industry clockspeed as a potentially important variable in the decision to create a spinoff or not.

Screening to identify large truck potential blackspots : methodological issues and concerns

1. Overview of hotspot identification (HSID)methods 2. Challenges with HSID 3. Bringing crash severity into the ‘mix’ 4. Case Study: Truck Involved Crashes in Arizona 5. Conclusions • Heavy duty trucks have different performance envelopes than passenger cars and have more difficulty weaving, accelerating, and braking • Passenger vehicles have extremely limited sight distance around trucks • Lane and shoulder widths affect truck crash risk more than passenger cars • Using PDOEs to model truck crashes results in a different set of locations to examine for possible engineering and behavioral problems • PDOE models point to higher societal cost locations, whereas frequency models point to higher crash frequency locations • PDOE models are less sensitive to unreported crashes • PDOE models are a great complement to existing practice

ePortfolios and eGovernment : from technology to the entrepreneurial self

We analyse the electronic portfolio (ePortfolio) in higher education policy and practice. While evangelical accounts of the ePortfolio celebrate its power as a new eLearning technology, we argue that it allows the mutually-reinforcing couple of neoliberalism and the enterprising self to function in ways in which individual difference can be presented, cultured and grown, all the time within a standardised framework which relentlessly polices the limits of the acceptable and unacceptable. We point to the ePortfolio as a practice of (self-) government, arguing that grander policy coalesces out of a halting, experimental set of technological instruments for thinking about how life should be lived.